AS3.15 | Urban Air Quality and Greenhouse Gases
Urban Air Quality and Greenhouse Gases
Convener: Juliane Fry | Co-conveners: Ulrike Dusek, Sander Houweling, Dominik Brunner
Orals
| Fri, 28 Apr, 08:30–12:30 (CEST), 14:00–15:45 (CEST), 16:15–18:00 (CEST)
 
Room M2
Posters on site
| Attendance Thu, 27 Apr, 16:15–18:00 (CEST)
 
Hall X5
Posters virtual
| Attendance Thu, 27 Apr, 16:15–18:00 (CEST)
 
vHall AS
Orals |
Fri, 08:30
Thu, 16:15
Thu, 16:15
Cities are hotspots for the emissions of air pollutants and greenhouse gases from traffic, industry, household heating and energy production. Air pollution impacts are episodic and often exacerbated during heat waves, and greenhouse gases are often co-emitted with air pollutants. These relationships make cities both a major driver of climate change, and the locus of many harmful climate impacts. Urban air quality and the effect of policy measures are a challenge to monitor with traditional fixed stations or with models, because of the extreme variability in the cities’ geometry and emission patterns.

This session intends to bring together researchers of urban air quality and greenhouse gases. We invite submissions on topics related to urban air quality, heat stress, urban carbon budgets, and air pollution impacts including health. Topics may include sensor networks, personal monitoring, airborne observations, high spatial and temporal resolution model approaches, downscaling, source apportionment, isotopic source attribution methods, atmospheric processes, mechanisms for air quality deterioration, biogenic and anthropogenic precursors, allergens, community and personal exposure quantification, and air pollution effects.

Orals: Fri, 28 Apr | Room M2

Chairpersons: Dominik Brunner, Sander Houweling
08:30–08:35
08:35–08:55
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EGU23-17536
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AS3.15
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solicited
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Highlight
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On-site presentation
Jia Chen, Adrian Wenzel, Andreas Luther, Andreas Forstmaier, Patrick Aigner, Vigneshkumar Balamurugan, Florian Dietrich, Daniel Kühbacher, Moritz Makowski, Haoyue Tang, Xinxu Zhao, Friedrich Klappenbach, Hossein Maazallahi, Thomas Roeckmann, Hugo Denier van der Gon, Taylor Jones, and Bradley Matthews

As more than 70% of fossil fuel-based carbon dioxide (CO2) is emitted in urban areas, urban greenhouse gas (GHG) monitoring plays a crucial role in achieving emission reduction goals. Nowadays, most cities rely on downscaled national data to calculate their total emissions, or on bottom-up methods, where emission factors are multiplied with activity data, such as energy consumption, economic activity, and traffic density. However, at the scale of individual cities, errors of 50-100% in fossil fuel CO2 emission estimates have been reported. Furthermore, in terms of methane (CH4), urban emissions are suspected to be substantially underestimated by inventory methods.

Measurements of atmospheric GHG concentrations offer opportunities to identify unknown emission sources and to address biases in urban emission inventories. Urban areas however pose significant challenges to measurement-based emissions quantification, due to the heterogeneous geometry of the cities and the complex atmospheric circulation in this environment. Therefore, representative measurements combined with sophisticated atmospheric models are vital to arrive at robust estimates of urban GHG emissions.

In Munich, Germany, we created an integrated measurement and modeling framework to better understand urban GHG emissions. MUCCnet (Munich Urban Carbon Column network) is a permanent urban GHG sensor network, consisting of five automated ground-based remote sensing systems. It is based on the differential column method (DCM), which features high precision and is relatively insensitive to vertical redistribution of tracer mass and surface fluxes upwind of the city, thus providing favorable input for urban flux inversions. MUCCnet serves to validate satellite measurements, to independently monitor local GHG emissions over the long term, and to detect unknown emission sources.

Using the Munich Oktoberfest as an example, large festivals have been identified as a potentially significant source of fossil fuel CH4, despite likely being poorly represented in CH4 emission inventories. In a recent measurement campaign in Hamburg, where DCM was deployed, we have found several significant anthropogenic sources, such as refineries and a farm as well as large area sources such as the River Elbe, whose CH4 emissions are not yet included in the standard inventories or are highly underestimated.

To assess emissions from the measured concentrations, inverse modeling is an essential tool. We developed a novel Bayesian inversion framework to inversely model emissions using column measurements. We further use mobile in-situ measurements, isotopic measurements, and eddy covariance measurements to enhance the prior knowledge of the emission map.

Within the ICOS Cities project (PAUL), we have been improving the GHG emission assessments in Munich by refining the prior emission localization and timing and by adding additional monitoring capacities, including 100 street-level low-cost CO2 sensors as well as 20 roof-level mid-cost CO2 sensors based on the NDIR measurement principle. In addition, we are establishing an autonomous NOx, PM, CO and O3 network in Munich with 50 stand-alone sensor nodes. This network is used to study the spatial distribution of urban air pollutants and to assess co-emitted species of CO2 emitters.

How to cite: Chen, J., Wenzel, A., Luther, A., Forstmaier, A., Aigner, P., Balamurugan, V., Dietrich, F., Kühbacher, D., Makowski, M., Tang, H., Zhao, X., Klappenbach, F., Maazallahi, H., Roeckmann, T., Denier van der Gon, H., Jones, T., and Matthews, B.: Novel Sensor Networks and Methods for Urban Greenhouse Gas Monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17536, https://doi.org/10.5194/egusphere-egu23-17536, 2023.

08:55–09:05
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EGU23-7172
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AS3.15
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ECS
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On-site presentation
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Stuart Grange, Pascal Rubli, Christoph Hueglin, Andrea Fischer, Simone Baffelli, Dominik Brunner, and Lukas Emmenegger

Since July 2022, a high-density CO2 monitoring network has been operating in and around Zürich City, Switzerland as part of the ICOS Cities project. The network is formed of 80 sites that have been equipped with CO2 monitors with varying performance and cost points. Three high-precision CO2 gas analysers, 20 mid-cost sensors (installed with reference gas cylinders), and 114 low-cost sensors are in use with some sites having multiple sensors installed. Combined with several modelling approaches, the observations from the sensor network will allow for the characterisation of the city's emissions and to validate the city's CO2 emission inventory. The different types of CO2 monitors are combined with different data processing strategies to ensure their observations are adjusted for sensor drift and changes in responses so they can be used for robust analysis in near-real time. Between July 2022 and early January 2023, the CO2 network's mean concentration was 446 ppm and the difference between the network's background and urban-traffic sites was 31 ppm suggesting a significant urban enhancement during this period. Distinct daily and seasonal patterns were observed for different types of sensor locations, reflecting diverse emission regimes across the urban area. Despite careful efforts during the site selection process, local contamination has been observed for many rooftop sensors due to their proximity to heating stacks. However, the installation of wind sensors allows for the observations to be flagged for such situations, which will be important for downstream data users. Details on the sensor adjustment strategies, the technologies in use for the data processing pipeline, the results from several months of CO2 monitoring, and future plans with the other two ICOS Cities sensor network collaborators (Munich and Paris) will be discussed. 

How to cite: Grange, S., Rubli, P., Hueglin, C., Fischer, A., Baffelli, S., Brunner, D., and Emmenegger, L.: Design, deployment, and exploitation of a high-density CO2 sensor network in Zürich City, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7172, https://doi.org/10.5194/egusphere-egu23-7172, 2023.

09:05–09:15
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EGU23-7712
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AS3.15
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On-site presentation
Hugo Denier van der Gon, Rianne Dröge, Ingrid Super, Arjan Droste, Dominik Brunner, Ivo Suter, Lionel Constantin, Olivier Perrussel, Olivier Sanchez, Jia Chen, Patrick Aigner, and Daniel Kühbacher

The ICOS-cities PAUL project aims to support the European Green Deal by solving specific scientific and technological problems related to the observation and verification of greenhouse gas (GHG) emissions from densely populated urban landscapes. To this end, comprehensive city observatories, applying various in situ and ground-based remote sensing GHG measurement technologies, will be developed and evaluated in a relatively large (Paris), medium (Munich) and small (Zürich) city. A critical input for the optimal design of such observatories are complete, spatially explicit, state-of-the-art city emission inventories for greenhouse gases and co-emitted species. Currently the emission data available for European cities vary considerably in source sector completeness, spatial resolution, base year and temporal disaggregation. Our target resolution in the ICOS-cities PAUL project is 100 x 100 meter, hourly resolution for a recent year like 2018 or 2019 to avoid impact of the Covid-19 pandemic. Such data would allow evaluation of the city budget and more detailed district level budgets, which can support tailored climate action plans. For Paris (3 x 3 km) and Zurich (100 x 100 m), emission inventories are developed by respectively, AIRPARIF and EMPA in collaboration with the municipality of Zurich. The emission inventory for Munich is based on the downscaling of the 1 x 1 km TNO-GHGco inventory where key source sectors are stepwise replaced by bottom-up estimates by TUM and TNO. Here we harmonize source sectors and evaluate and intercompare the emission inventories of the three cities. We identify dominant source sectors and potentially missing sources, and determine ratios between GHG and co-emitted species necessary for source sector attribution. Furthermore, we compare the results against downscaled national reported emission data in line with the official reporting to UNFCCC, and draw conclusions on consistency between national scale and city scale inventories. Lessons learned will lead to the development of a more general methodology to provide city emission data to other European cities and, as part of the overall ICOS-cities objective, robust observation-based methods for quantifying city GHG emissions and sinks to assess the impact of city climate actions.

How to cite: Denier van der Gon, H., Dröge, R., Super, I., Droste, A., Brunner, D., Suter, I., Constantin, L., Perrussel, O., Sanchez, O., Chen, J., Aigner, P., and Kühbacher, D.: Development, intercomparison and analysis of city emission inventories in support of independent verification of city greenhouse gas budgets, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7712, https://doi.org/10.5194/egusphere-egu23-7712, 2023.

09:15–09:25
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EGU23-7542
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AS3.15
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ECS
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On-site presentation
Nikolai Ponomarev, Michael Steiner, Erik Koene, Lionel Constantin, Pascal Rubli, Lukas Emmenegger, and Dominik Brunner

Switzerland like many other countries has set ambitious goals to reach net zero CO2 emissions by 2050. The city of Zurich has committed to an even more ambitious goal of becoming climate neutral by 2040. Recent developments in atmospheric observations and inverse modelling, including the results of the European infrastructure project ICOS, have already laid down the foundations for estimating emissions on national and continental scales. At urban scales, however, only few emission estimation studies have been conducted so far, and it is still an open question, which observational and modeling approaches are best suited and to what level of accuracy they are able to quantify the emissions of a city. The project ICOS-Cities/PAUL aims to answer these questions by evaluating different monitoring approaches in three European pilot cities. One of these cities is Zurich, where a street-level network of about 93 low-cost sensors at 60 locations is combined with a network of 21 mid-cost sensors, located mainly on roof-tops, and high-precision instruments at 3 background sites.

Our goal is to estimate the CO2 emissions of Zurich by combining the observations from the mid-cost and high-precision instruments with the state-of-the-art atmospheric transport model ICON-ART. To this end, numerical experiments were conducted for two offline-nested domains, a European domain at ~6.6 km resolution and a second domain centered over the city of Zurich with a much higher resolution of ~0.6 km to represent the main topographic features of the urban area. Anthropogenic emission inputs were produced by merging three different inventories: the TNOGHGco inventory for areas outside Switzerland, a Swiss national inventory at 100 m resolution, and a detailed inventory of point, line and area sources produced by the city of Zurich. The biogenic fluxes of CO2 were computed online using the Vegetation Photosynthesis and Respiration Model (VPRM) integrated into ICON-ART.

Here we present a first analysis of comparisons between model simulations and CO2 observations inside and surrounding the city. This allows us to better understand the capabilities and weaknesses of the model at urban scales as well as to design optimal strategies for setting up an inversion framework.  A particular focus is placed on biospheric CO2 and on how much it contributes to variability within the city in comparison with anthropogenic CO2. The next steps will include the use of the CTDAS (The CarbonTracker Data Assimilation Shell) assimilation system in order to obtain information on CO2 fluxes in the urban and suburban areas of Zurich and to apply the model system also to the city of Paris. During this work, we strive to develop approaches which can then be shared and applied by researchers to other cities around the world.

How to cite: Ponomarev, N., Steiner, M., Koene, E., Constantin, L., Rubli, P., Emmenegger, L., and Brunner, D.: Application of the ICON-ART model for CO2 fluxes estimation in the city of Zurich, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7542, https://doi.org/10.5194/egusphere-egu23-7542, 2023.

09:25–09:35
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EGU23-7768
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AS3.15
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On-site presentation
Alina Jasek-Kaminska, Miroslaw Zimnoch, Lukasz Chmura, and Jakub Bartyzel

Urban areas, with dynamically changing, varied sources and sinks in highly heterogeneous terrain, are one of the most complicated ecosystems to explore. Being also a significant CO2 net source, they contribute largely to uncertainty in local and global carbon balance calculations. Experimental data are required to verify existing CO2 emission inventories and to become a reliable input to climate models.

Since 2021 an eddy covariance site has operated in Krakow, southern Poland. Site neighborhood includes various anthropogenic sources and sinks such as traffic, household heating, mainly with natural gas, and people themselves. On the other hand, a significant part of the source area is covered in green, with a municipal park and a number of home gardens.

We are presenting a data record from the beginning of the measurements in February 2021 up to the present. As expected, the area is a net CO2 source, emitting on average around 7 kg of CO2 per square meter yearly. Clear diurnal and seasonal patterns of CO2 net flux were observed: morning and evening traffic peaks and negative values during the day due to active photosynthesis; also higher diurnal amplitude during the warm season but on average higher net CO2 emission in winter. Directional flux analysis reveals that 1) the highest emissions come from the area where individual households as well as busy traffic lanes are located; and 2) urban green areas have a potential to become a net CO2 sink during the day in all seasons except winter, however, mean diurnal emission on average remains positive.

This project has been partially supported by the European Union’s Horizon 2020 research and innovation program CoCO2 under grant agreement No. 958927, "Excellence Initiative - Research University" program at AGH University of Science and Technology, and the subsidy of the Ministry of Education and Science.

How to cite: Jasek-Kaminska, A., Zimnoch, M., Chmura, L., and Bartyzel, J.: CO2 net ecosystem flux in Krakow, Poland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7768, https://doi.org/10.5194/egusphere-egu23-7768, 2023.

09:35–09:45
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EGU23-2434
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AS3.15
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ECS
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On-site presentation
Robert Maiwald and Sanam Noreen Vardag

Urban areas and cities play a crucial role in mitigating climate change. First, a large share of greenhouse gases (about 60%) is emitted in urban areas. Second, city networks have formed to implement climate change mitigation measures at the local level. Therefore, cities have great potential to significantly reduce greenhouse gas emissions.

Realizing this potential requires solid knowledge of local greenhouse gas sources, which can be obtained through robust measurements of greenhouse gases in an urban network. These measurements can then serve as a starting point for quantifying and thus verifying local emissions. In order to optimize the investment in a measurement network and maximize the knowledge gained from these measurements, several parameters need to be considered, such as the number and location of nodes, the uncertainty of the measurements, and the co-measured species.

These parameters can be evaluated and optimized in an Observing System Simulation Experiment (OSSE). In our study we perform a high-resolution OSSE using the atmospheric transport model GRAMM/GRAL. We first feed a high-resolution anthropogenic emission inventory into the model and simulate CO2 concentration in the urban atmosphere on 10 m resolution in a 12 km x 12 km domain. Next, we approximate CO2 fluxes on neighborhood scale using an inverse framework. We test different configurations of possible measurement networks to assess under which circumstances and how well we can estimate CO2 fluxes. We find that the accuracy of the estimated fluxes increases with node number and precision, reaching a mean error reduction of about 50 % for 16 nodes and a precision of 1.0 ppm in the best configurations. Sources emitted on ground level can be successfully estimated on hourly resolution, but the measurement stations are not sensitive enough to detect sources emitted from tall emission stacks in the vicinity of the measurement nodes. We further discuss the advantages of using CO as an additional tracer in the inversion with respect to measurement precision and sectoral source disaggregation. The framework developed allows for the planning of an optimal measurement network and can thereafter be used to derive fluxes and associated uncertainties in urban areas. This allows for verification of emissions and targeted monitoring of mitigation measures at the local scale.

How to cite: Maiwald, R. and Vardag, S. N.: Observing System Simulation Experiment for designing a monitoring network in urban areas using the GRAMM/GRAL model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2434, https://doi.org/10.5194/egusphere-egu23-2434, 2023.

09:45–09:55
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EGU23-15178
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AS3.15
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ECS
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On-site presentation
Katharina Heimerl, Sander Houweling, Frank Hase, Mahesh Kumar Sha, Filip Desmet, Nicolas Kumps, Bavo Langerock, Thorsten Warneke, Nils Hase, Jonas Hachmeister, and Andre Butz

Urban areas are home to many people on the globe, and centres of industry. Emissions from cities contribute to atmospheric concentrations of greenhouse gases like CO2 and CH4, which influence the Earth’s energy budget. The Ruisdael Observatory is a Dutch research infrastructure to investigate the atmosphere over the Netherlands by bringing together measurements and high resolution modelling. One part of it is a semi-mobile trailer to be flexibly deployed as measurement station for targeted field measurements. Mounted on the roof of this trailer are a Bruker EM27/SUN (EM27) for columnar trace gas measurements and a Cimel for columnar aerosol measurements. A targeted field campaign was conducted in August and September 2022 to study Rotterdam, one of the biggest city in the Netherlands and the biggest harbour in Europe. Three EM27s were set up around Rotterdam in an upwind-downwind configuration. To ensure the comparability of the data, the instruments measured in parallel for three days before and after the measurement period, which showed good agreement between the instruments. Four different configurations of instrument locations were used during the three week campaign to account for changes in wind direction and investigate specific targets as well as separate between the influence of the harbour area and the city itself. Enhancements in the CO2 column were around 1-3 ppm across the harbour and about 1 ppm across the city. CH4 columnar concentrations were not significantly enhanced across the city, but increased by several ppb across the harbour area. The CO columnar concentrations increased across the harbour by up to 10 ppb and 5 ppb across the city area.

How to cite: Heimerl, K., Houweling, S., Hase, F., Sha, M. K., Desmet, F., Kumps, N., Langerock, B., Warneke, T., Hase, N., Hachmeister, J., and Butz, A.: Remote sensing of columnar trace gases during the Ruisdael Rotterdam campaign in 2022, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15178, https://doi.org/10.5194/egusphere-egu23-15178, 2023.

09:55–10:05
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EGU23-1234
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AS3.15
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ECS
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On-site presentation
Lena Feld, Pablo Schmid, Frank Hase, Roland Ruhnke, Marios Mermigkas, Dimitrios Balis, and Peter Braesicke

The reduction of carbon emissions is required to limit global warming. Thus, measurement-based methods to monitor the progress in reducing emissions are essential. A significant part of the global emissions is produced in urban areas where also industry is located. Here, we investigate the urban area of Thessaloniki to better understand the distribution of local greenhouse gas sources during October 2021 and the summer of 2022.

We present results of a measurement campaign using a pair of Fourier-Transform Infrared (FTIR) Spectrometers of the type EM27/SUN developed by Bruker and KIT.
The measurement campaign took part in the framework of the Collaborative Carbon Column Observing Network (COCCON). During the campaign the spectrometers were used in an up- downwind setup. One spectrometer was located in a central position of the city while the second instrument was transported to various locations at the boundaries of the city, selected according to the prevailing wind direction. Additionally, measurements to characterize the advected background variability were performed. Here, the spectrometers were arranged orthogonal to the prevailing wind direction to estimate the variability of the background concentrations of carbon dioxide and methane.
In total, 30 days of measurements were collected, giving a comprehensive dataset to study the emissions of the city area. The measurements are interpreted using a box model to estimate the averaged emission area fluxes. We present results for both, carbon dioxide and methane, and discuss the temporal and spatial variability we encountered.

In a next step, we aim to confront these measurements with simulation results with idealized tracer emission patterns using the ICON-ART modeling framework, a numerical weather forecast model developed and used operationally by the German Weather Service (DWD). The results from the box model introduced above will be used as a starting point to combine measurements and simulations. First simulations produced for this purpose will be shown.

How to cite: Feld, L., Schmid, P., Hase, F., Ruhnke, R., Mermigkas, M., Balis, D., and Braesicke, P.: A Measurement Campaign in Thessaloniki, Greece, to Detect and Estimate Local Greenhouse Gas Emissions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1234, https://doi.org/10.5194/egusphere-egu23-1234, 2023.

10:05–10:15
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EGU23-13255
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AS3.15
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ECS
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On-site presentation
Kathiravan Meeran, Bradley Matthews, Simon Leitner, Hans Sanden, Jia Chen, and Andrea Watzinger

Cities contribute significantly to global carbon dioxide (CO2) emissions, and it is important to understand and accurately measure these emissions in order to effectively mitigate climate change. Current methods for estimating emissions, such as emission inventories, can be very uncertain at the scale of individual cities. Measurement methods that involve analyzing local atmospheric CO2 levels and the respective stable carbon isotopic composition of CO2 can provide additional, independent information on local emissions, particularly in terms of source contributions from combustion of different fossil fuels and natural respiration. As part of the Vienna Urban Carbon Laboratory (VUCL), a cavity-ring-down laser isotope spectrometer (G2201-i, Picarro Inc., USA) has been operating on a radio tower in Vienna’s city centre since May 2022 to measure atmospheric mixing ratios of CO2 and stable carbon isotopic composition of CO213C) 144 m above the surface.

The overall objective here is to establish an analysis framework to best utilize these measurements in combination with tall-tower eddy covariance measurements for the identification and quantification of local CO2 emission emitters in Vienna. Initial analysis of the half-hourly CO2 concentrations and fluxes between May and Dec 2022 show that a night-time increase of measured CO2 concentrations are followed by an early morning peak, due to a nocturnal build-up of surface-level CO2 that is followed by an upward flush of CO2 in the morning. The δ13C of CO2 (based on keeling plot analysis) suggests that fluxes from natural respiration are dominant over the night. In the afternoon, the δ13C of CO2 sources decreases, which may be due to an increased contribution from sources with isotopically depleted CO2, such as traffic emissions and small-scale stationary methane combustion. We also observed higher concentrations CO2 that are isotopically depleted, during the summer when winds came from the area southeast of the tower, which has more industrial and refinery activity. In addition to these initial results from keeling plot analysis, our presentation will also include results from the ongoing winter measurements, where we expect to see indications of enhanced methane combustion for space heating. Furthermore, results from ongoing tests of other analysis methods for identifying emitting sources (e.g., application of the miller trans model method, analysis of the data at higher temporal resolutions) will be presented.

How to cite: Meeran, K., Matthews, B., Leitner, S., Sanden, H., Chen, J., and Watzinger, A.: Tall tower measurements with laser isotope spectrometry to investigate urban CO2 emissions in Vienna, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13255, https://doi.org/10.5194/egusphere-egu23-13255, 2023.

Coffee break
Chairpersons: Sander Houweling, Juliane Fry
10:45–10:50
10:50–11:00
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EGU23-13203
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AS3.15
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ECS
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On-site presentation
Benedikt Hemmer, Vincent Enders, Frank Hase, Ralph Kleinschek, Julian Kostinek, Thomas Pongetti, Stanley Sander, Zhao-Cheng Zeng, and André Butz

Precise knowledge of sources and sinks in the carbon cycle is desired to understand its sensitivity to climate change and to account and verify man-made emissions. In this context, extended sources like urban areas play an important role. While in-situ measurements of carbon dioxide (CO2) and methane (CH4) are highly accurate but localized, satellites measure column-integrated concentrations over an extended footprint. The CLARS-FTS [1, 2] stationed at the Mt. Wilson observatory looking downward into the Los Angeles basin has pioneered an innovative measurement technique that fills the sensitivity gap between in-situ and satellite measurements. The technique enables mapping the urban greenhouse gas concentration fields by collecting spectra of ground scattered sunlight and scanning through the region.

We develop a similar but portable instrument using a CLARS-FTS-like measurement geometry. It is based on the EM27/SUN FTS with a modified pointing system, increased throughput and a more sensitive detector than the standard type. The compact setup enables campaign-based observations in various source regions of interest, utilizing the increased sensitivity to boundary layer concentration by the horizontal light path component.

Here, we present the portable instrument setup and its performance. Throughout April 2022, we observed the Los Angeles basin with both the portable setup and the CLARS-FTS simultaneously. The retrieval algorithm is based on the RemoTeC software, previously employed for solar backscatter satellite measurements. From this, we evaluate the XCO2 and XCH4 precision of our setup under field conditions, and compare our instrument to the concurrent CLARS-FTS measurements.

 

References:
[1] Fu, D. et al., 2014: Near-infrared remote sensing of Los Angeles trace gas distributions from a mountaintop site, Atmos. Meas. Tech., 7, 713–729, https://doi.org/10.5194/amt-7-713-2014
[2] Wong, K. W. et al., 2015: Mapping CH4 : CO2 ratios in Los Angeles with CLARS-FTS from Mount Wilson, California, Atmos. Chem. Phys., 15, 241–252, https://doi.org/10.5194/acp-15-241-2015

How to cite: Hemmer, B., Enders, V., Hase, F., Kleinschek, R., Kostinek, J., Pongetti, T., Sander, S., Zeng, Z.-C., and Butz, A.: A portable, ground-based FTS for reflected sunlight: Performance evaluation for mapping CO2 and CH4 above Los Angeles, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13203, https://doi.org/10.5194/egusphere-egu23-13203, 2023.

11:00–11:10
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EGU23-4938
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AS3.15
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ECS
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On-site presentation
JeongEun Kim, Jinho Ahn, and Sambit Ghosh

Fossil fuel combustion is one of the largest contributors to anthropogenic greenhouse gas (GHG) emissions, especially in megacities around the world. To characterize the vehicle emissions in Seoul, the megacity of South Korea, we collected air samples from the entry and exit points of three tunnels (Sang-Do, Bong-Cheon, and Gwan-Ak Tunnel) and Seoul National University Campus and measured dry molar mixing ratios of major greenhouse gases spices (CO2, CH4, and N2O). The N2O:CO2 emission molar ratio from vehicles is 4.3 ± 0.3 × 10-5, within a range of 1.8 – 18.7 × 10-5 previously reported in Germany, Switzerland, Sweden, and the USA. The CH4:CO2 emission molar ratio from the Sang-Do tunnel is 50.6 ± 18.0 × 10-5, which is significantly greater than those observed in Switzerland, the USA, and China (3.5 - 15 ± 4 ×10–5). In the Bong-Cheon and Gwan-Ak tunnels, however, there was little difference in entry and exit, or rather, the exit was smaller, and it might be related to the ventilation system and vehicle types. We also compared our estimation of the GHG emissions from vehicles with the National Greenhouse Gas Inventory Report of Korea (GIR, 2021) which is based on a bottom-up emission calculation method. With the CO2 emissions (8108.33 Gg CO2eq) from the GIR, the N2O and CH4 emissions in Seoul are estimated to be (108.08±24.60) Gg CO2eq and (62.75±18.92) Gg CO2 eq, respectively. The differences between our observations and inventory imply that the estimation of the non-CO2 gas (CH4, N2O) emission factors should be improved. To characterize the N2O from vehicles, we analyzed N2O stable isotopic compositions by an IRMS method. The δ15N and δ18O values of N2O emitted from the vehicles are estimated as -7.1 ± 1.5 ‰ and 41.2 ± 0.2 ‰, respectively. The δ15N values support the idea that the N2O is produced through catalytic convertors in vehicles which are attached to reduce the NOx emission at the tailpipe. The newly measured data from Seoul may help us better understand greenhouse gas emissions from vehicles in megacities.

How to cite: Kim, J., Ahn, J., and Ghosh, S.: Greenhouse gas emission from vehicles in Seoul megacity, South Korea: Molar ratios (N2O:CO2, CH4:CO2) and stable isotopic compositions of N2O (d15N, d18O), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4938, https://doi.org/10.5194/egusphere-egu23-4938, 2023.

11:10–11:20
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EGU23-14015
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AS3.15
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Highlight
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On-site presentation
Marco Brunner, Morten Hundt, and Oleg Aseev

Urban air pollution and greenhouse gas emissions are two closely linked problems. They can be attributed to a variety of sources, such as transportation and buildings, waste management and agricultural production, natural events such as forest fires and many others. Monitoring air pollutants and GHG simultaneously with high selectivity and sensitivity enables to detect and evaluate their sources and sinks and to discover the links between them. Precise measurements at various spatial and temporal scales are required for modelling and validation of emission inventories or satellite observations. 

Solutions to monitor air pollutants or GHG with high precision and temporal resolution were commonly offered as “one-species-one-instrument”, leading to large, immobile measurement setups with high energy consumption. We provide a new compact laser absorption spectrometer that combines several mid-IR lasers. Our solution allows simultaneous high-precision measurements of the greenhouse gases CO2, N2O, H2O and CH4, and the pollutants CO, NO, NO2, O3, SO2 and NH3 within a single instrument and is therefore well suited to detect the relations of the co-emitted pollutants and GHGs.

In our contribution, we will demonstrate examples of our instruments’ applications for mobile monitoring of 10 GHGs and air pollutants in urban areas and airborne measurements with airships. Furthermore, we will present the results of parallel monitoring with our instrument and standard conventional gas analysers used for GHG and air pollutant measurements. It demonstrates the ability of our instrument to serve as an all-in-one solution and to replace up to 7 standard gas analysers opening a wide range of new mobile multi-compound gas monitoring applications, for example, in (small) airplanes or cars.

How to cite: Brunner, M., Hundt, M., and Aseev, O.: A single instrument for simultaneous monitoring of greenhouse gases and air pollutants, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14015, https://doi.org/10.5194/egusphere-egu23-14015, 2023.

11:20–11:30
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EGU23-6009
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AS3.15
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ECS
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On-site presentation
Eleanor Gershenson-Smith, Robert G. Ryan, Eloise A. Marais, Robbie Ramsay, Jan-Peter Muller, Jan-Lukas Tirpitz, and Udo Friess

In the UK, the public health threat of heatwaves is exacerbated by the co-occurrence of ozone pollution episodes. Here we present retrieved vertical profiles of nitrogen dioxide (NO2) and formaldehyde (HCHO) over Central London from a newly installed long-term Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument on a 60-m altitude rooftop site during two of three heatwaves in the hottest summer on record. We evaluate routine space-based sensor observations of air pollutant precursors over London and enhance the permanent air quality monitor network. Daily mean tropospheric column densities of NO2 and HCHO from the TROPOspheric Monitoring Instrument (TROPOMI) are consistent with those from the MAX-DOAS (both R = 0.71) after accounting for different vertical sensitivities. As expected, TROPOMI NO2 is 27-31% less than MAX-DOAS NO2, due to horizontal dilution of local sources of road-traffic NO2. TROPOMI HCHO is 20% more than MAX-DOAS HCHO; a larger difference than in past validation studies, but within the range of systematic retrieval errors. MAX-DOAS lowest layer (0-110 m) retrievals have analogous day-to-day variability to surface site NO2 (R ≥ 0.7). Surface site measurements of isoprene, which rapidly oxidises to HCHO with a high yield, also have similar diurnal variations to MAX-DOAS HCHO (R > 0.6). Generally, daytime ozone production, which is diagnosed with MAX-DOAS HCHO:NO2 tropospheric column ratios, is limited by the availability of volatile organic compounds. During heatwaves, ozone production shifts from NOx-saturated to NOx-limited as biogenic emissions of isoprene increase exponentially with temperature, leading to non-compliance with ozone regulatory standards. In ongoing work, we are assessing the ability to retrieve the NOx (NO + NO2) reservoir compound nitrous acid (HONO) to address uncertainties in HONO chemistry. This will aid understanding of the oxidation capacity of the atmosphere and ozone budget in centres of megacities such as London.

How to cite: Gershenson-Smith, E., Ryan, R. G., Marais, E. A., Ramsay, R., Muller, J.-P., Tirpitz, J.-L., and Friess, U.: MAX-DOAS measurements characterise severe ozone pollution in Central London during summer 2022 heatwaves, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6009, https://doi.org/10.5194/egusphere-egu23-6009, 2023.

11:30–11:40
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EGU23-10906
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AS3.15
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ECS
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On-site presentation
Xinwei Li and shuncheng Lee

Air pollution is recognized as the biggest environmental health risk in urban cities, as air pollution is pervasive and hard to escape. As one of the notorious atmospheric pollutants, nitrogen oxides (NOx, NO + NO2) not only promotes the formation of ozone and secondary aerosols but also have direct adverse health effects on human beings. As a typical densely populated modern metropolis, Hong Kong can serve as a reference for world cities in terms of air pollution control. Even though air quality in Hong Kong Environment Protection Department (HKEPD) has improved over recent decades, the roadside NO2 level in Hong Kong still exceeds the Hong Kong Air Quality Objectives (HKAQO), European Union Air Quality Directives (EUEQD) and the most stringent World Health Organization Air Quality Guidelines (WHOAQG). Nanomaterial-based photocatalysis that only relies upon solar energy excitation provides a sustainable solution for air pollution redemption. Generally, photocatalysts developed in the laboratory are in powder form which is not appropriate for real-world applications. However, these limitations can be overcome by coating photocatalysts on the surfaces of various substrates to immobilize those powders as films. More importantly, photocatalytic coatings are available to be supported on different substrates without changing or affecting existing settings. In this study, enhancement of NOx photocatalytic degradation ability and solar light utilization were implemented in a reformative Titanium Dioxide (TiO2) film. Hydrogen peroxide solution was utilized to peptize the crystallized nanoparticles around 5-6 nm at room temperature instead of the traditional calcination process at high temperatures, which limited the commercialization due to the expensiveness of heating. Moreover, the nanosized TiO2 film was expected to provide more active sites for reactions, which contributes to a promising photocatalytic degradation ability. Based on ISO 22197-1 evaluation standards, the as-developed photocatalytic coating possesses a NOx degradation rate of 4.402 mg*m-2h-1 when applied on the concrete surface, which was higher than Degussa (Evonik) P25 and other commercial coating products at the same conditions. An artificial weather resistance test investigation implies the photocatalytic coating will provide a strong bonding interaction with substrate materials which is beneficial to the lifetime of the coating. Further investigating from a 180-day field trial in a roadside environment in Hong Kong, the as-developed coating concrete specimen presented about 5% of attenuation in the first 30 days and sustained 13.9%-18.5% photocatalytic activity after the entire 180-day outdoor exposure. The application of photocatalytic coatings is supposed to convert the roadside NOx compounds to NO2- and NO3- which are harmless in small quantities and would be washed away by water droplets. In response to practical demands, functional nanomaterials-based photocatalytic technology has been gradually promoted as a green strategy for improvements in the air quality of megacities all over the world.

How to cite: Li, X. and Lee, S.: Development and Application of Nanomaterials-based Photocatalytic Technology for Improvement of Urban Air Quality, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10906, https://doi.org/10.5194/egusphere-egu23-10906, 2023.

11:40–11:50
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EGU23-15106
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AS3.15
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ECS
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Highlight
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On-site presentation
Stuart E Lacy, Sebastian Diez, Thomas J Bannan, Michael Flynn, Nathan Watson, Nicholas Marsden, Max Priestman, and Pete M Edwards

Low-cost air pollution sensors (LCS) have a potentially vital role to play in tackling air pollution. Their affordability facilitates the creation of dense networks, which coupled with their intrinsic high time resolution offers a vast spatio-temporal coverage unlike that possible with conventional instrumentation, offering a paradigm shift in the way we measure key pollutants, evaluate health impacts of air pollution exposure and assess clean air policies. However, despite the availability of numerous commercial LCS products, there is limited current understanding as to their suitability for these tasks.

 

The QUANT project aims to address this deficit in order to enable the use of LCS to support UK clean air ambitions. Over a period of three years, 52 commercial LCS instruments from 14 companies have been measuring real world air quality data in a range of UK urban environments, collocated with reference grade instruments. With the data collection period having ended in November 2022, there now exists a comprehensive dataset of measurements from multiple pollutants across a variety of LCS systems, differing in both the underlying sensor technology as well as the software layer that converts the noisy raw signals into meaningful concentrations. 

 

This talk summarises the initial conclusions emerging from this study, highlighting the various factors that should be taken into account when considering LCS for a specific task, for example: the robustness of the calibration algorithm, variability between devices from the same company, how well the measurements transfer between sites, and differing response to meteorological conditions. To help make this knowledge accessible to a wider audience, a web-app is presented that can allow researchers and decision makers to interactively explore the dataset to assess the applicability of devices to their particular requirements.

How to cite: Lacy, S. E., Diez, S., Bannan, T. J., Flynn, M., Watson, N., Marsden, N., Priestman, M., and Edwards, P. M.: Low-cost air quality sensors: The good, the bad, and the ugly. Preliminary findings from the QUANT study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15106, https://doi.org/10.5194/egusphere-egu23-15106, 2023.

11:50–12:00
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EGU23-9195
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AS3.15
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On-site presentation
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Jun Zhang, Ruben Goudriaan, Janot Tokaya, Arjan Hensen, Daniëlle van Dinther, Sjaak Kaandorp, Marcus Blom, and Arjan Plomp

Air pollution may threaten both human health and ecosystem vitality in Eindhoven city, the Netherlands. Although air quality changes are monitored hourly with high-end equipment at multiple national stations, it remains difficult for individual cities or citizens to trace local air quality based on national-scale information. A monitoring network of 44 low-cost airbox sensors was established around Eindhoven city to measure atmospheric concentrations of particulate matter (PM10, PM2.5, PM1) and nitrogen dioxide (NO2) at 10-min intervals from January 2021 onwards, with ultra-fine particle (UFP) sensors added at 3 dedicated sites around the airport. To address local government and citizen’s health concerns, the monitoring network was spread among three major areas: urban area (23), Eindhoven airport (3), and rural area outside of the city (18). The urban area was further divided into clean-background area, downtown, industrial zone, traffic intensified ring-roads and highways. Based on a one-year seasonal and diurnal analysis, we concluded that at least 70% of the average PM concentration was determined by the regional background contribution whilst 60% - 72% of total PM10 was contributed by fine particles with a diameter below 2.5 µm. On average, the PM values of the urban background area were still 10 - 15% higher than those for the rural area despite the assistance of city-greening facilities (such as tree-lined streets and parks). However, higher PM10 values were also frequently observed downwind of the livestock farms within the rural area across seasons. On the other hand, NO2 concentrations were mainly driven by local sources’ behavior, notably traffic emissions during morning and evening rush-hours. The three UFP sensors located around the airport showed more frequent peaks and higher values related to flight activities and airport traffic, also outside the airport terrain. The combined results underline the importance of taking spatial variability of urban air pollution sources into explicit account. Moreover, a good-quality airbox real-time monitoring network will allow local policy-makers to take proper actions to mitigate air pollution, inform local citizens and reduce health impacts at the appropriate scale.

How to cite: Zhang, J., Goudriaan, R., Tokaya, J., Hensen, A., van Dinther, D., Kaandorp, S., Blom, M., and Plomp, A.: A low-cost airbox network to assist air quality policy-making and citizen involvement: Eindhoven city, Southeast Brabant, the Netherlands, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9195, https://doi.org/10.5194/egusphere-egu23-9195, 2023.

12:00–12:10
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EGU23-11085
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AS3.15
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ECS
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Highlight
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On-site presentation
Sheng Ye, Melanie Ziemann, and Mark Wenig

Air quality have become a global issue with increasing attention. There is a growing concern in the public about both in- and outdoor air quality. In order to monitor individual air pollutants exposure in real-time, we developed several wearable air quality monitoring devices to study personal exposure to different pollutants in different environments. The devices are equipped with different type of sensors to measure NO2, aerosols, CO2, etc, in addition to environmental parameters sensor to measure temperature, relative humidity and pressure. In order to optimize the accuracy, we compared different retrieval approaches such as multiple linear regression, generalized linear model, neural network, etc. This allows us to perform the personal exposure study with a high temporal resolution in the order of seconds. We classified daily activities into different categories: different ways of commuting such as bus, tram, subway, bicycle, on foot; indoor activities like cooking, lighting candles, etc.; outdoor exercises next to busy street, in a park, etc. In this presentation, we will present our first result of this personal exposure study.

How to cite: Ye, S., Ziemann, M., and Wenig, M.: Personal air pollution exposure assessment using wearable sensors, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11085, https://doi.org/10.5194/egusphere-egu23-11085, 2023.

12:10–12:20
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EGU23-11110
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AS3.15
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ECS
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On-site presentation
Rósín Byrne, John C Wenger, and Stig Hellebust

High density air quality sensor (AQS) networks offer a unique opportunity to better understand the local variations and temporal patterns of air pollutant levels in a city. With the coordination of reference instrumentation and meteorological data, they are even more useful. This work compares two sensor networks that are the first or their kind in Ireland. The first is in Cork City (population ~ 220,000) in the south of Ireland, which currently has five regulatory monitoring stations, three of which monitor PM2.5. The second location is Edenderry which is a rural town (population ~ 8,000) in the Irish midlands served by one regulatory monitoring site. The Cork City AQS network is comprised solely of PurpleAir devices, while the Edenderry network combines both PurpleAir and Clarity Movement Co. devices. The networks provide increased spatial and temporal data in relation to PM2.5.

Both locations experience seasonally elevated levels of PM2.5 due to higher instances of domestic solid fuel burning during the winter months. However, Edenderry generally experiences significantly higher levels, despite its much smaller size. During the winter heating period of 2020-2021 (01/10/20 - 31/0321), there were 23 instances where the PM2.5 24-hour mean at a regulatory monitoring site in Cork exceeded the WHO Global Air Quality Guidelines of 15 µg m-3, while there were 83 instances in Edenderry over the same period.

A correction model was applied to the AQS data collected in both networks to align the values with respective local reference data. Multiple linear regression (MLR) models were used to calibrate the networks using data from periods of colocation of the reference instrument with air quality sensors. By combining these robustly calibrated and co-ordinated networks with local meteorological information, the data was used to investigate the local spatial and temporal variations in PM2.5 for the period 01/02/2022 to 29/07/2022. The typical daily cycle of PM pollution in Ireland was observed in both locations, with a dominant afternoon/evening peak during the colder months due to solid fuel burning for home heating. Significant PM2.5 variations between sensor locations in each network were found. The results showed that a small town in Ireland can experience PM2.5 pollution levels that are as substantially higher than more populated urban areas.

This work was supported by the EU LIFE Programme through the project LIFE Emerald - LIFE19 GIE/IE/001101 and the Cork City AQS network is supported by Cork City Council.

How to cite: Byrne, R., Wenger, J. C., and Hellebust, S.: Using air quality sensor networks to compare variations of PM2.5 in a small town and a city in Ireland., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11110, https://doi.org/10.5194/egusphere-egu23-11110, 2023.

12:20–12:30
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EGU23-8403
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AS3.15
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ECS
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On-site presentation
Tommaso Giordano, Lorenzo Brilli, Federico Carotenuto, Alice Cavaliere, Giovanni Gualtieri, Beniamino Gioli, Carolina Vagnoli, and Alessandro Zaldei

The current socio-economic and political scenario is posing serious challenges to energy usage, mobility, residential and industrial activities, which may impact local emission patterns, fossil fuel vs alternative fuels usage and air quality in unknown ways. On top of this, winter 2022-23 is being exceptionally warm across the European continent.

The investigation of the interactions between air quality, meteorological factors and emissions sources at high spatio-temporal resolution plays a crucial role to detect areas and periods characterized by critical conditions, especially in complex urban environments. Data at such fine resolution can today be obtained through dense low-cost sensor networks integrating sparse official air quality stations. This research aims to assess meteorological forcing, emission proxies (i.e., population density, CO2 local enhancement, land-use) and particulate matter concentrations (PMs) for the last three winter seasons (2020-2023) characterized by contrasting conditions. The study was focused on the Lucca plain (central Italy), an area characterized by heterogeneous emission sources and classified among the most polluted in the region. Sixteen low-cost stations (“AirQino”), equipped with high-frequency sensors to detect PM10, PM2.5, air-temperature, relative humidity (RH), and CO2 concentration were installed on an area spanning approximately 10 x 20 km. Local land use surrounding the measurement stations was obtained from the Corine Land Cover. Mixing Layer Height (Hmix) and wind data were obtained from a WRF-CALMET coupled model. Population density was computed with demographic data from the Global Human Settlement database. For CO2 data, the nocturnal enhancement normalized by wind speed with respect the minimum midday values was used as an emission proxy (ΔCO2). Population density and land use including fractions of residential, industrial, and agricultural areas were computed in a 1-km radius surrounding each station.

Preliminary comparisons between winter 2021/2022 and 2022/23 were performed to assess the effects of energy crisis and climatic conditions on air-quality. Different multivariate regression models were developed to investigate the inference between Hmix, air-temperature, RH, ΔCO2, population density, land use and PMs concentrations.

Most recent analysis shows a consistent and robust positive air temperature anomaly in November-December 2022 vs 2021 (+ 1.25 °C). CO2 enhancements were on average 20% lower (-19.0 to +3.7 ppm in 2022 vs 2021 respectively) suggesting a relevant emission reduction occurring at the landscape scale. However, these reductions did not always translate into PM10 and PM2.5 reductions and air quality improvements. Among the 16 stations, 11 exhibited a decrease in PM2.5 concentration (-21.60 % on average) and only 9 in PM10 (-21.55 % on average). The locations where air quality did not improve or was even worse this year are characterized by the lowest population density and lowest presence of residential neighborhoods, being mostly in rural or rural/industrial contexts. This suggests that alternative fuels such as wood biomass are likely replacing natural gas in peri-urban areas for domestic heating, generating a negative impact on air quality that could be much worst when usual lower temperature conditions will be met. A complete multivariate analysis to confirm these patterns will be presented.

How to cite: Giordano, T., Brilli, L., Carotenuto, F., Cavaliere, A., Gualtieri, G., Gioli, B., Vagnoli, C., and Zaldei, A.: Winter 2022 thermal anomaly and energy crisis impact on air quality in urban and rural areas assessed with dense sensor networks, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8403, https://doi.org/10.5194/egusphere-egu23-8403, 2023.

Lunch break
Chairpersons: Juliane Fry, Ulrike Dusek
14:00–14:05
14:05–14:25
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EGU23-17285
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AS3.15
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solicited
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Highlight
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On-site presentation
Linda George, Andrew Rogers, Kirsten Sarle, and Lyndsey DeMarco

Diesel emissions are ubiquitous around the world and adversely impacts human and environmental health. One of the primary pollutants of concern from diesel combustion are the solid particles formed as a byproduct of the combustion diesel fuel, known as diesel particulate matter. In regions where there is significant transport of goods, such as port cities, emissions from trucks, ships and trains can raise ambient levels of diesel particulate matter above health standards. We studied diesel emissions in Portland, Oregon USA, a mid-sized port city through a combination of source testing/evaluation, ambient monitoring and modeling (CALPUF) to produce a validated model of ambient diesel particulate matter. Similar work is starting in Rotterdam, Netherlands. Through our model we were able to identify policies that can be used to reduce emissions and ambient concentrations of diesel particulate matter. We collaborated with a state regulators and community groups identify mitigation strategies to model. For example, we modeled the potential effect of electrification of trucks and the use of cleaner diesel construction equipment. In addition, we were able, through modelling, to explore the impact of shipping distribution centers, an emerging and growing source of diesel emissions within cities in an era of on-line shopping. Validated modeling can improve understanding of the drivers of elevated levels of diesel particulate level as well as identify potential mitigation strategies.

Keywords: Air pollution, diesel emissions, diesel particulate matter, air pollution monitoring, air pollution modeling

How to cite: George, L., Rogers, A., Sarle, K., and DeMarco, L.: Identifying strategies to reduce diesel particulate matter levels in cities, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17285, https://doi.org/10.5194/egusphere-egu23-17285, 2023.

14:25–14:35
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EGU23-7014
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AS3.15
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ECS
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On-site presentation
Marjan Savadkoohi, Marco Pandolfi, Andrés Alastuey, Xavier Querol, and Olivier Favez

Among the aerosol particles optical properties, the Absorption Angstrom Exponent (AAE) is a crucial parameter describing the spectral dependence of light absorption by aerosols. It is intensively employed for black carbon (BC) source apportionment and aerosol characterization (e.g., BC, Brown Carbon “BrC,” and dust). AAE has been widely investigated using data from filter-based absorption photometers such as the AE33 that measure light absorption at seven wavelengths (370-950 nm). BC source contribution is commonly obtained by applying the most frequent source apportionment method, the Aethalometer model. This model requires a-priori knowledge of the AAE of the fossil and non-fossil (e.g. biomass burning) BC sources and values of around 1 (AAEff; fossil) and 2 (AAEwb; non-fossil) are commonly used. In this work, in order to improve the results of the aethalometer model for BC source apportionment, we investigate the model performances resulting from using site-dependent AAEff and AAEwb determined from the experimental data. These latter were obtained by studying the frequency distributions of experimental AAE calculated from AE33 data collected at urban sites in the frame of the RI-URBANS project. However, AAE can also vary with time depending on changing burning fuels and burning conditions, and single constant AAEff and AAEwb values cannot be representative of the whole measurement period considered. For this reason, we also evaluated the use in the Aethalometer model of experimental time-dependent rolling AAEff and AAEwb. This improved AAE-frequency-distribution-based Aethalometer model could be applied in near-real time to obtain the BC source apportionment. Thus, it could help to improve our understanding of AAE values considering uncertainties to provide a better and more accurate quantity to differentiate between BC sources.

How to cite: Savadkoohi, M., Pandolfi, M., Alastuey, A., Querol, X., and Favez, O.: Black Carbon source apportionment using time-dependent Absorption Angstrom Exponent (AAE), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7014, https://doi.org/10.5194/egusphere-egu23-7014, 2023.

14:35–14:45
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EGU23-6314
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AS3.15
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On-site presentation
Balint Alfoldy, Asta Gregorič, Matič Ivančič, Irena Ježek-Brecelj, and Martin Rigler

Urban air quality deterioration has different reasons in warm and cold seasons. During summer, the photochemical production of secondary air pollution causes problems (ozone, secondary particles), while domestic heating significantly increases the primary emission during winter. In addition, the elevated emission is concentrated in a shallow mixing layer that leads to high air pollution levels. The source profile of domestic heating depends on the heating method. In European cities gas heating and wood combustion are the most common heating methods. Although distant heating is also commonly used, its emissions appear at the industrial source and are negligible for local air quality (similarly for less spread electric heating). In this work, we determined the emission ratios (ER) and emission factors (EF) of black carbon (BC), organic carbon (OC), and nitrogen oxide (NOX) in an urban environment, during the heating season. BC and OC concentrations were measured by the Carbonaceous Aerosol Specification System (CASS, Aerosol d.o.o, Slovenia), while NOX data was recorded by a nCLD-AL2 NOX analyzer (Eco Physics AG., Switzerland). The monitoring system was complemented by a Carbocap GMP-343 CO2 sensor (Vaisala, Finland) in order to measure the CO2 concentration for the EF calculation. The measurement took place in the atmospheric monitoring station of the Aerosol d.o.o in Ljubljana, Slovenia, which can be characterized as an urban background location. The source apportionment was implemented by using the Aethalometer model – multilinear regression combination (AM-MLR) assuming two major sources of urban air pollution: traffic and domestic heating. Fossil fuel-derived BC (BCFF) concentration was assumed as the tracer of traffic emission, while biomass burning-related BC (BCBB) was considered as the tracer of domestic heating. The Aethalometer model provides the source-specific (FF- or BB-derived) BC component. During the AM-MLR method, we supposed that the source-specific pollution component is correlated with the corresponding BC component (BCFF or BCBB). The slope of the regression line provides the ER, while the ratio of CO2 to the other pollutants can be converted to EF (g(kg fuel)-1) using the carbon balance approach. We applied the AM-MLR method to the dataset for the winter of 2021-2022 and determined the ER and EF values. The obtained EFs for traffic-related BC, OC, and NOX are 0.39, 0.33, and 0.03 g(kg fuel)-1 respectively, while the heating-related EFs are 0.13, 0.48, and0.01 g(kg fuel)-1 respectively. This work provided real-world emission factor data of a city that can help to estimate the total BC, OC, and NOX emissions in a city based on the sold fuel or consumed wood and gas.

How to cite: Alfoldy, B., Gregorič, A., Ivančič, M., Ježek-Brecelj, I., and Rigler, M.: Black carbon, organic carbon, and nitrogen oxide emission factors for traffic and domestic heating in an urban environment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6314, https://doi.org/10.5194/egusphere-egu23-6314, 2023.

14:45–14:55
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EGU23-15411
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AS3.15
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On-site presentation
Joanna Struzewska, Marcin Kawka, Anahita Sattari, Aleksandra Starzomska, Aleksander Norowski, Grzegorz Jeleniewicz, Lech Gawuć, and Karol Szymankiewicz

Urban air quality is one of the challenges due to high exposure resulting from high population density and high pollutant concentrations. Developing effective strategies to improve air quality requires determining the contribution of different emission sources within the city compared to the influence of the inflow from surrounding areas.

In Polish cities, the residential sector is a dominant source of particulate matter. However, transportation is also a significant source of pollution, especially concerning NO2.

The main goal of the project was to assess the impact of the transportation sector on air quality in Warsaw. We have applied a muti-tool approach. The analysis of a 5-year series of air quality observations at urban background stations and the traffic station let to identify systemic differences attributed to road transport. Based on the GEM-AQ model results, the contribution of the transport setor in selected districts was assessed. The SHERPA bottom-up tool for Poland was applied to estimate the impact of line sources on PM10, PM2.5 and NO2 concentrations in Warsaw metropolitan area. Also, two local models were used – the IEP-NRI gaussian model combined with the machine learning techniques, and the ATMOSYS model developed by VITO. The intercomparison brought a valuable outcomes on the completeness and accuracy of the emission data applied.

We will present and discuss the percentage contribution of road transport-related pollutant concentrations in Warsaw based on the different model results.

How to cite: Struzewska, J., Kawka, M., Sattari, A., Starzomska, A., Norowski, A., Jeleniewicz, G., Gawuć, L., and Szymankiewicz, K.: Impact of transport sector on air quality in Warsaw – a multi-tool study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15411, https://doi.org/10.5194/egusphere-egu23-15411, 2023.

14:55–15:05
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EGU23-9755
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AS3.15
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ECS
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Highlight
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On-site presentation
Vasileios Matthaios, Roy Harrison, Petros Koutrakis, and William Bloss

In many developed cities, commuters spend more than 1.5-h inside vehicles daily, which may result in elevated exposures to traffic-related NO2 and PM2.5, which are known to have harmful health effects. In addition, time spend inside vehicles is likely to be greater for professional drivers, whereas the impacts of these exposures may be greater for vulnerable groups such as the elderly or obese. Therefore, reducing in-vehicle exposure and the associated risk for adverse health effects is very important.

This study measured in-vehicle NO2 and PM2.5 during repeated transects of the same route on city streets for 10 vehicles under real-world conditions, and as a function of ventilation settings and cabin filters. The results were used to assess personal exposure for driver/passengers, and to develop stepwise general additive models in order to identify important controllable factors that can reduce in-vehicle exposure.

The overall variability of in-vehicle exposure explained by these models was R2 = 0.58 and 0.52, for NO2 and PM2.5 respectively. From the model’s explained variability, the most significant predictor for both pollutants was on-road NO2 and PM2.5 levels accounting for 25.4 and 35.6% respectively. Vehicle-based predictors included car type, odometer, use of activated carbon filter, air exchange rate and use of air conditioning/air recirculation ventilation settings that, in combination, explained 48.9% and 61.1%, of NO2 and PM2.5, variability, respectively. Driving-based predictors included road traffic conditions, presence of traffic lights roundabouts and high emitters, explained 25.7% and 3.3% of NO2 and PM2.5 in-vehicle concentration variability, respectively. By carefully regulating vehicle-based factors under driver or passenger control, such as ventilation and filtration options, vehicle occupants can significantly reduce their exposure to NO2 and PM2.5.

How to cite: Matthaios, V., Harrison, R., Koutrakis, P., and Bloss, W.: In-vehicle exposure to NO2 and PM2.5: influences of environmental, vehicle and driving factors, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9755, https://doi.org/10.5194/egusphere-egu23-9755, 2023.

15:05–15:15
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EGU23-11781
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AS3.15
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On-site presentation
Daniëlle van Dinther, Andreas Weigelt, Jörg Beecken, Johan Mellqvist, Vladimir Conde Jacobo, Marcus Blom, and Jan Duyzer

Air quality in urban cities with ports can significantly be impacted by shipping. For example Visschedijk and Denier van der Gon (2022) showed that, within Rotterdam area (the Netherlands), sea shipping is the main source of ultra-fine particles (UFP) with a contribution of 56% to total UFP emissions. Within EU-project SCIPPER (Shipping Contributions to Inland Pollution Push for the Enforcement of Regulations) a measurement campaign of six weeks was undertaken at the river Elbe near Hamburg (Germany). Sea going vessels pass by on the way to or from the port of Hamburg, which is located about 10 km upstream of the measurement site. Three different groups measured side-by side different gaseous compounds and aerosols on-shore. The aerosol measurements consisted of different equipment measuring different sizes ranging from 6 to 10 000 nm, also black carbon was measured by two groups. The emission factors (EF) of the different ships were calculated in #/kg fuel as well as mg/kg fuel from these measurements. This provides a unique dataset to better understand the emission characteristics of different ships as well as the comparability of different devices. This comparability is important if in the future legislation to decrease aerosol emissions of shipping is applied and needs to be verified. Results showed the relatively large contribution of mainly ultrafine particles, with 90% of the total amount of particles being smaller 80 nm and 75% of the total particle mass comes from particles smaller 200 nm. The comparison showed very promising results when the same equipment was tested side-by-side (R2 above 0.85 for all size ranges). The comparability of EFs of same sources that were measured by different devices was somewhat lower, but especially for smaller size ranges still promising (R2 of 0.69 for particle number ranging from 90 to 300 nm). For black carbon the experimental set-up proved to be too different (drying vs non-drying and different inlet cut-offs) to give comparable emission factors. Concluding the data showed promising results to be able to use on-shore monitoring in the future to monitor aerosol ship emissions, also when using different equipment.

References:

Visschedijk, A., Denier van der Gon, H. (2022). UFP emissie in de Rijnmond regio in 2019 (in Dutch). Utrecht: TNO-report R10616.

How to cite: van Dinther, D., Weigelt, A., Beecken, J., Mellqvist, J., Conde Jacobo, V., Blom, M., and Duyzer, J.: Comparison of emission factors of particles from shipping using different equipment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11781, https://doi.org/10.5194/egusphere-egu23-11781, 2023.

15:15–15:25
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EGU23-2239
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AS3.15
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On-site presentation
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Matthias Karl, Martin O. P. Ramacher, Sonia Oppo, Ludovic Lanzi, Elisa Majamäki, Jukka-Pekka Jalkanen, Grazia Maria Lanzafame, Brice Temime-Roussel, and Barbara D'Anna

Ship emissions of air pollutants in and around ports adversely affect local air quality and human health, especially in harbour cities. In coastal Mediterranean cities, shipping activities are an important contributor to emissions of fine particulate matter (PM2.5) within the urban area. In addition to primary particles emitted in ship exhaust, secondary organic aerosols (SOA) may form in ship plumes through chemical oxidation of volatile organic compounds (VOC) and through condensation of intermediate volatile or semi-volatile organic gases. Shipping also emerges as a major source of ultrafine particles below 100 nm diameter in coastal cities. Ultrafine particles have been estimated to significantly affect human mortality in coastal areas. While a large number of studies investigated the effect of ship-related PM2.5 in coastal areas, currently only few studies deal with the effect of ship emissions on SOA concentrations and number concentrations of ultrafine particles in harbour cities.

In this study, we investigate the effect of ship emissions on SOA concentrations and number concentrations of UFP in the harbour city Marseille in southern France, which is an important hub of ferry and cruise ship traffic in the Mediterranean Sea. For city-scale simulations of Marseille, the urban chemistry transport model EPISODE-CityChem (https://doi.org/10.5281/zenodo.1116173) was applied in a coupled setup with the regional-scale Community Multiscale Air Quality Modelling System (CMAQ). EPISODE-CityChem combines a 3-D Eulerian grid model with sub-grid Gaussian plume models and solves the photochemistry of multiple reactive pollutants, including the chemistry of 12 different VOC. New developments in EPISODE-CityChem include the P8P+2 scheme for calculating particle number (PN) concentration and particle number size distribution (PNSD) and the SOA module of the aerosol model MAFOR v2.0 (https://github.com/mafor2/mafor). The STEAM-3 emission inventory for the local shipping in and around the port of Marseille consists of hourly emissions of major pollutants, VOC and particle numbers from ships on 250 m grid resolution. Hourly model output of EPISODE-CityChem for July 2020 was compared to measurements at monitoring stations in Marseille operated by AtmoSud and campaign data recorded at La Major, a site in proximity of the port.

Our results show that the potential impact from local shipping to the monthly mean concentration in the urban area of Marseille is only up to 3% for PM2.5, whereas it is up to 42% for total PN. The abundance of ship-related semi-volatile organic vapours is high in the areas of SOA formation, which indicates that volatile organics are mainly in the gas phase because available pre-existing particle surfaces and high ambient temperatures limit their condensation. Ship plumes at La Major were detected based on the difference of total PN concentration between the reference run and a model run excluding ship emissions. The maximum of the modelled and the observed PNSD notably corresponded to the typical size distribution maximum of ship exhaust particles. Total PN should be considered as a more suitable metric for monitoring ship emission impact than PM2.5 because it allows for a better discrimination of ship plumes from the background pollution.

How to cite: Karl, M., Ramacher, M. O. P., Oppo, S., Lanzi, L., Majamäki, E., Jalkanen, J.-P., Lanzafame, G. M., Temime-Roussel, B., and D'Anna, B.: Ship-related ultrafine particles and SOA formation in a Mediterranean port city, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2239, https://doi.org/10.5194/egusphere-egu23-2239, 2023.

15:25–15:35
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EGU23-7484
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AS3.15
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On-site presentation
Sabine Fritz, Sebastian Aust, and Tobias Sauter

Airports contribute significantly to the concentration of ultrafine particles (UFP) at the local level. UFP from combustion processes are produced when aircraft take off and land, during aircraft movements on the tarmac, when turbines are started, but also by vehicles transporting goods and people on the airfield. UFP are considered particularly harmful to human health due to their large surface area. They can also penetrate far into the human body due to their small size.

This study examines the extent to which particle number concentration (PNC) responds to the cessation of air traffic due to the relocation of an airport. PNC and wind data were measured at one station on the airfield downwind of the runways for the prevailing wind direction for about three weeks each before and after the closure of the airport.

We observed a 30 - 40 % drop in PNC after the closure of the airport regardless of the wind direction. 70 % higher PNC on average, 2.5 times higher maximum values as well as a three times higher dispersion of PNC occured with wind from the direction of the airport before the closure of the airport than afterwards. These differences are only evident during the day when air traffic is active and not during the nighttime flight restrictions. More frequent and higher concentration peaks occur in conjunction with wind from the airport before flight operations ceased.

The special circumstances resulting from the relocation of the airport allow clear conclusions to be drawn about the importance of airport operations for PNC in the area of the airfield. As the study took place under Covid-19 pandemic conditions, it shows the impact of aircraft movements on PNC, but does not allow conclusions about air pollution during normal air traffic. Further studies or modelling on the spatial dispersion of airport-related air pollutants and thus on the exposure of the population living and working nearby can close the gap on health effects of air traffic.

The study has been published as Fritz S., Aust S. and Sauter T. (2022): Impact of the closure of Berlin-Tegel Airport on ultrafine particle number concentrations on the airfield. Front. Environ. Sci. 10:1061584, doi: 10.3389/fenvs.2022.1061584. The study was supported by the German Federal Ministry of Education and Research (BMBF) under grant FKZ 01LP 1912B (Urban Climate under Change, Phase II, Module 3DO + M).

How to cite: Fritz, S., Aust, S., and Sauter, T.: Effects of the closure of Berlin-Tegel Airport on ultrafine particle concentration on the airport site, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7484, https://doi.org/10.5194/egusphere-egu23-7484, 2023.

15:35–15:45
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EGU23-13016
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AS3.15
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On-site presentation
Fabio Monforti-Ferrario, Luana Valentini, Enrico Pisoni, and Marta Giulia Baldi

Tackling Climate Change is a priority for the European Union, who has set targets for reducing greenhouse gas emissions progressively up to 2050. In 2008, acknowledging the role of local authorities, the European Commission (EC) launched the Covenant of Mayors (CoM) initiative to endorse their efforts in the implementation of sustainable energy and climate policies. The JRC plays a central role in the CoM ecosystem, providing the methodological guidelines that enable cities to process their own GHG emission data. Furthermore, the JRC provides scientific supervision and makes comprehensive GHG datasets available to the whole CoM community (Baldi et al., 2022).

Since 2018, in the frame of its support to the EU Covenant of Mayor (CoM) initiative, the JRC is bringing to the attention of the city administrators the importance of tuning climate change mitigation and air quality. For this goal, in cooperation with the CoM stakeholders we have developed a specific tool aimed at allowing the CoM signatories to evaluate the consequences of their mitigation policies on the air pollutants emissions taking place in their territory.

 

The tool was developed in two steps: (1) in the first part of the research project, a pilot version of the tool has been developed based on the methodology reported in two previous studies, Monforti-Ferrario et al. (2018) and Peduzzi et al. (2020); (2) after setting up the tool, the pilot tool has been made available to a group of of CoM signatories. Their comments and feedbacks  have been through a questionnaire and showed how the tool i especially useful for small and middle-sized signatories.

As reported in Peduzzi et al. (2020) the tool is based on the comparison between the Baseline Emission Inventory (BEI) and the successive Monitoring Emission Inventories (MEI) the signatories need to submit to comply with CoM requirements.The changes in energy consumption (by sector and carrier) between BEI and MEI were translated into the corresponding changes in air pollutant emissions by means of estimated emission factors.

 

Updated data on the actual use of the tool and feedback from users and practitioners will be provided and discussed. We will complete the presentation with reflections and suggestions for local authorities to practically improve the co-designing of climate and air pollution policies based on the experience collected throughout the CoM initiative.

 

 

References

Baldi et al., (2022): GCoM - MyCovenant, 2021, Second release. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/9cefa6ca-1391-4bcb-a9c8-46e029cf99bb

Monforti-Ferrario et al, 2018, The impact on air quality of energy saving measures in the major cities signatories of the Covenant of Mayors initiative. Environmental International, 118, 222-234

Peduzzi  et al, 2020, Impacts of a climate change initiative on air pollutant emissions: Insights from the Covenant of Mayors, Environment International, Volume 145,  106029

How to cite: Monforti-Ferrario, F., Valentini, L., Pisoni, E., and Baldi, M. G.: Evaluating climate mitigation and air quality synergies and trade-offs throughout the Covenant of Mayors initiative, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13016, https://doi.org/10.5194/egusphere-egu23-13016, 2023.

Coffee break
Chairpersons: Ulrike Dusek, Dominik Brunner
16:15–16:20
16:20–16:30
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EGU23-13131
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AS3.15
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On-site presentation
Shona Wilde, Naomi Farren, Rebecca Wagner, James Lee, Samuel Wilson, Lauren Padilla, Greg Slater, Daniel Peters, Ramon Alvarez, and David Carslaw

Tailpipe emissions from road transport have fallen dramatically over the last 30 years due to the combined
effect of increasingly stringent regulations and technological improvements. However, the air pollution
burden due to road vehicle emissions remains the dominant source of many air pollutants in urban
areas. Policies such as Low Emission Zones (LEZs) have become increasingly popular as a method of reducing
on-road emissions by restricting access to the oldest and most polluting vehicles. Most modern vehicles
are fitted with sophisticated exhaust aftertreatment systems, which should lead to significantly reduced
emissions of pollutants such as nitrogen oxides (NOx = NO + NO2). However, the performance of such
systems is non-uniform across all driving conditions. Urban driving conditions are among the most challenging,
where vehicle speeds are often low and congestion results in a considerable amount of stop-start
driving with repeated accelerations and decelerations. Under such conditions some aftertreatment systems
cannot reach the high temperatures required to operate efficiently, which may limit the effectiveness of
policies that target vehicle type alone. Therefore, to develop effective air quality management strategies it
is necessary to understand the relative importance of factors that influence vehicle emissions, such as fleet
composition, traffic state, driver behaviour and ambient temperature.
In this work we present results from a mobile monitoring campaign in London, UK. Measurements were
made in two unique locations (central and outer London) in order to provide a quantitative understanding
of the main drivers for concentrations in terms of traffic conditions. We show that there is a significant low
speed penalty for NOx concentrations in central London, where there is a high proportion of diesel vehicles,
which are predominately taxis and buses. This effect arises due to the near constant congestion and
slow average moving speed of only 12 km h-1, resulting in the non-optimal performance of aftertreatment
technologies fitted to diesel vehicles. Moreover, despite the heavy restrictions imposed by the Ultra Low
Emissions Zone, which requires all diesel vehicles in the zone to be Euro 6/VI (light/heavy vehicles) compliant,
we find that the mean emissions intensity (ΔNOx/ΔCO2) in central London was 0.0039 ppb ppb-1, a
factor of 2 higher than outer London (0.0021 ppb ppb-1). For context we compared the measured emissions
intensity to an “urban average" value (0.0018 ppb ppb-1) derived from 135,000 remote sensing measurements
made directly at the tailpipe. Whilst good agreement was found for outer London, central London
was twice as high, suggesting there is a highly unfavourable mix of technology and conditions, which may
hinder the improvements due to current policies. This work aims to quantify the unique effect of congestion
on different vehicle types and to provide policy makers with the information needed to better understand
the benefits of congestion control, given that restrictions on technology alone may not always be enough to
reduce emissions.

How to cite: Wilde, S., Farren, N., Wagner, R., Lee, J., Wilson, S., Padilla, L., Slater, G., Peters, D., Alvarez, R., and Carslaw, D.: Using Mobile Monitoring to Understand Vehicle Emissions in Urban Areas, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13131, https://doi.org/10.5194/egusphere-egu23-13131, 2023.

16:30–16:40
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EGU23-14901
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AS3.15
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ECS
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Highlight
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On-site presentation
Leyla Sungur, Wolfgang Babel, Sophie Arzberger, Sophia Ramer, Johann Schneider, Frederik R. Bachmann, Ines Bamberger, Anke Nölscher, and Christoph Thomas

Urban air quality directly determines urban quality of life. To improve it, we need to know about local emissions, chemical transformations, and transport processes of the energy-containing vortices in the air. The combination of high-resolution ultrasonic anemometers and state-of-the-art vortex-resolving Large Eddy Simulation (LES) technique is a powerful key tool enabling this understanding. Here, we investigated the dynamics and transport of air with particular focus on nitrogen dioxide (NO2) in a highest-traffic street canyon with eight driving lanes in the urban setting of the city of Munich, Germany. Using spatially distributed observations and results from flow-resolving simulations, temporally and spatially resolved patterns and trends of airflow and pollutant concentrations are presented. The airflow conditions in the wide (approx. 80m) urban street canyon are largely decoupled from the synoptic flow over the city. The street is mostly characterized by a channeled, northerly current and weak wind speeds and turbulence kinetic energy (TKE) during the day, independent of prevailing synoptic forcing conditions. At night, the channeled current shifts to southern flow and reverses back to northerly winds in the early morning transition. One exception to this rule are infrequent synoptic easterly flows perpendicular to the street canyon orientation, which lead to a deflection of the flow by the building fronts and a flow reversal to westerly flows at the street level. In this case, TKE is strongly enhanced, and pollutant concentrations are low due to enhanced mixing and inflow of less polluted above-city air. Emission coefficients from the Handbook for Emission Factors for Road Transport (HBEFA) have been used in combination with traffic demand data from loop detectors to compute the respective NO2 emissions. These emissions show daily peaks in the morning and afternoon hours, and a significant differentiation between weekday, Saturday, and Sundays with less traffic. The individual lanes also differentiate in amount of emission. Linking the results from the point turbulence and NO2 measurements with the LES approach helps to understand the turbulent air transport and NO2 in parts of the street canyon where no observations exist. The first results from an LES run in a twofold nested domain with a spatial resolution of Δx,y,z = 1m for the street canyon and buildings show promising similarities in airflow patterns and dynamics compared to the observations and are currently undergoing further validation. This study is financed by the Bavarian Ministry of the Environment and Consumer Protection.

How to cite: Sungur, L., Babel, W., Arzberger, S., Ramer, S., Schneider, J., Bachmann, F. R., Bamberger, I., Nölscher, A., and Thomas, C.: Transport and emissions of gaseous air pollutants in a high-traffic urban street canyon, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14901, https://doi.org/10.5194/egusphere-egu23-14901, 2023.

16:40–16:50
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EGU23-13640
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AS3.15
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On-site presentation
An analysis of city-wide changes of NO2 distribution in Munich, Germany
(withdrawn)
Mark Wenig, Sheng Ye, Hanlin Zhang, and Zeqing Chen
16:50–17:00
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EGU23-12661
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AS3.15
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ECS
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On-site presentation
David Jean du Preez, Christoph Knote, and Maximilian May

Populations in urban areas have continued increasing in developing and developed countries worldwide. The ability to accurately simulate the dynamical and chemical atmospheric conditions in urban areas is essential when investigating the health impacts related to environmental conditions in urban areas. To simulate atmospheric conditions in urban areas one must consider how the airflow is affected by urban structures, vegetation, and mesoscale meteorology as well as local emitters and non-linear chemical reactions. 

There are a variety of different models available to simulate atmospheric conditions in urban areas. These models differ in many ways such as numerical methods, spatial and temporal resolution, and initial and lateral boundary conditions. Here we compare an Eulerian (PALM) and a Lagrangian (GRAL) model to determine which model can best simulate atmospheric conditions in an urban environment. These numerical differences affect the computational resources required and therefore influence how each model can be used to study the urban environment. The initial and lateral boundary conditions used in the simulations are derived from the Weather Research and Forecasting (WRF) model coupled with Chemistry (WRF-Chem) and a library of horizontal wind fields for PALM and GRAL, respectively. The results from both models will be compared for a domain over Heidelberg, Germany over a two-week period against hourly surface observations of wind and air quality parameters. 

How to cite: du Preez, D. J., Knote, C., and May, M.: Comparison between Eulerian and Lagrangian models for simulating atmospheric conditions in urban environments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12661, https://doi.org/10.5194/egusphere-egu23-12661, 2023.

17:00–17:10
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EGU23-1535
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AS3.15
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ECS
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Highlight
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On-site presentation
Michelle Wan and Alexander Archibald

After the Great Smog of London in 1952, the health impacts of air pollution exposure were launched into local public awareness. Today, these impacts have been established by epidemiological studies across the world. 

Machine learning (ML) techniques applied to this field of study in recent years have demonstrated potential advantages over traditional statistical approaches. These techniques are well-suited to large sets of input features, which can describe more holistically the numerous factors affecting human health. Additionally, the data-driven nature of these techniques eliminates the requirement for prior definition of the mathematical relationships between driving factors, confounders, and health outcomes. Previous examples of ML applications have included the identification of exposure profiles, and prediction of disease rates.

In this work, a simplified feature set was used to develop predictive ML models of daily mortality in Greater London, UK. The input features to the predictive models were: outdoor nitrogen dioxide concentrations recorded by the London Air Quality Network, outdoor temperature measurements recorded by the UK Met Office, and gross disposable household income per capita, as published by the UK Office for National Statistics. Preliminary work explored the trends and correlations observed in the dataset, which spanned the years 1997–2018. Predictive model performance was then compared between linear and neural network regressor models. Each of the three input features were also excluded in turn, to test the roles they played as predictors of mortality rates in London. 

Results found that, while both types of regressor architectures learnt to predict seasonal cycles in mortality rates, the neural network made test set predictions with a 73% reduction in mean squared error compared to the equivalent linear model. This illustrates the improved modelling power conferred by the nonlinear nature of neural networks, despite the network here being shallow in depth. 

Additionally, the ablation studies demonstrated that both types of models were dependent on the income input feature in order to accurately predict general trends in mortality rates over the two decades. Only this input feature provided information about changing trends through time, and its inclusion in this modelling approach was intended to represent the gradual improvement of societal and individual health factors.

In ongoing work, the exploration of factors affecting mortality is extended using long short-term memory neural network architectures. This type of neural network is additionally able to consider the temporal dimension by handling sequences of time series datapoints. Information is incorporated from the sequence of previous time steps into a memory vector, which then forms part of the input to the subsequent time step. Sequence length thus corresponds to the length of time-lagged associations learnt by the network. By varying sequence length, it is then possible to examine the significance of time-lag windows of different day lengths.

How to cite: Wan, M. and Archibald, A.: Neural network studies of air quality and socioeconomic predictors of mortality, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1535, https://doi.org/10.5194/egusphere-egu23-1535, 2023.

17:10–17:20
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EGU23-1379
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AS3.15
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ECS
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On-site presentation
Jiayu Xu, Lin Zhang, Mengran Lu, Yixin Guo, Youfan Chen, Zehui Liu, Mi Zhou, Weili Lin, Weiwei Pu, Zhiqiang Ma, Yu Song, Yuepeng Pan, Lei Liu, and Dongsheng Ji

Ammonia (NH3) emission control has been advocated for its potential to mitigate PM2.5 air pollution, yet emission quantifications at city levels are limited. Here we develop high-resolution (3 km) bottom-up emission inventories of agricultural NH3 in the Beijing-Tianjin-Hebei (BTH) region and traffic NH3 in Beijing for the year 2016. The resulting WRF-Chem simulated NH3 and PM2.5 are compared against ground-based and satellite observations. Our estimated annual BTH agricultural NH3 emissions (625 Gg) and Beijing’s traffic emissions (7.8 Gg) are within the ranges of published inventories. However, simulated NH3 concentrations are significantly lower than observations during August in urban Beijing, while wintertime underestimations are much more moderate. Further evaluation and sensitivity experiments show that such discrepancies cannot be attributed to biases in meteorology or regional transport. Using measurements as constraints, our inversed NH3 inventory indicates both agricultural and non-agricultural NH3 emissions in Beijing during August should increase by ~5 times to match NH3 and PM2.5 observations. Current underestimations may result from the missing power sector, urban green space emissions, the lack of representation of industrial hotspots, and uncertainties in traffic emissions. Our study highlights that denser and more frequent urban NH3 observations are urgently needed to constrain and validate bottom-up inventories.

How to cite: Xu, J., Zhang, L., Lu, M., Guo, Y., Chen, Y., Liu, Z., Zhou, M., Lin, W., Pu, W., Ma, Z., Song, Y., Pan, Y., Liu, L., and Ji, D.: Summertime urban ammonia emissions may be substantially underestimated in Beijing, China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1379, https://doi.org/10.5194/egusphere-egu23-1379, 2023.

17:20–17:30
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EGU23-12644
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AS3.15
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ECS
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On-site presentation
Xiaolu Li, Jason Blake Cohen, Kai Qin, and Hong Geng

This work used a Mass-Conserving inversion estimate framework based on daily TROPOMI NO2 and CO columns and observed stack fluxes of large industrial and commercial combustion sources from the continuous emissions monitoring systems (CEMS) to quantify three years of daily-scale, grid-by-grid emissions of NOx and CO at 0.05°×0.05° over Shanxi Province. This region was selected due to its complex topography, rapid development, and the fact that it currently contributes to more than 25% of China’s total coal production and consumption. For these reasons, the region is also highly representative in terms of rapid changes in the spatial-temporal distribution of emissions found in many different regions of the Global South. The calculated emissions, their ratio, and the day-to-day emissions variability are calculated and explained over four different land-use types: rural, natural, urban, and industrial. It is observed that relatively high NOx emissions, high NOx/CO and high NOx/NO2 ratios are consistent with known industrial areas; relatively lower NOx emissions, high NOx/CO and low NOx/NO2 ratio are consistent with known urban aeras. While the time series of both NOx and CO emissions are found to decrease from 2019-2021 overall, there are some complicated inter- and intra-year variations in the emissions, and such trends are not statistically significant over specific sub-regions. The observed variations include both known and unknown special events, as results of intentional policy changes, properties of the climate, and long-range transport atmospheric events. Combined with the Empirical Orthogonal Functions Principal Components Analysis (EOF), the joint composition of PM2.5, NO2, and CO emission in the largest city in Shanxi show further insights. Special festivals and economic events including Chinese New Year are clearly observed. There is also a significant decrease in the NOx to CO emissions ratio observed in urban and rural areas during the COVID-19 induced lockdowns in 2020, but an obvious increase after first-order lockdown. Specifically, it is observed that while there was a drop from 2019 to 2020 due to the COVID lockdowns, that the lowest emissions levels observed actually were found in 2021. On top of this, there was an observed see-saw effect with further reduction of pollution from large enterprises and poorer control of small sources and residential combustion sources. Finally, a switch in the NOx to CO emissions ratio is observed to rapidly change for strict control measures were introduced during the 2022 Winter Olympics. Diagnosis of pollution events using emissions of NOx and CO integrated with detailed PM2.5 chemical components is successfully attempted for the first time.

How to cite: Li, X., Cohen, J. B., Qin, K., and Geng, H.: Diagnosis of pollution events by NOx and CO Emissions calculated by Mass-Conserving Inversion method and composition of PM2.5 in Big City of Energy Rich Northern China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12644, https://doi.org/10.5194/egusphere-egu23-12644, 2023.

17:30–17:40
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EGU23-11503
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AS3.15
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ECS
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On-site presentation
Shuwen Han, Yan Tan, and Shun-cheng Lee

Air pollution is a serious environmental issue and has attracted much attention owing to the rapid urbanization and industrialization worldwide. Hong Kong, one of the well-developed cities located in the southeast of the Pearl River Delta (PRD) region, struggling with frequent air pollution episodes because of the intensive land use, dense daily anthropogenic activities, and enormous vehicle emissions. Therefore, a 10-year evaluation of air pollutants across roadside, urban and background sites was conducted to analyze the variations of air quality and contamination in Hong Kong. The continuous decrease of annual averaged concentrations of traffic-related NO2, SO2, CO, PM2.5 and PM10 and numbers of days with severe pollution conditions validated the efficiency of the series of air pollution control schemes implemented by the Hong Kong government. However, the concentration of O3 at roadside and urban stations increased by 135% ± 25% and 37% ± 18% from 2011 to 2020, respectively, meanwhile the highest 8-hour averaged O3 concentration was observed as 294 μg/m3 at background station in 2020, which pointed out the worsening ozone pollution in Hong Kong. To further investigate typical precursors of ozone and secondary organic aerosols, the intensive measurements of VOCs and OVOCs were conducted at both urban roadside station with heavy traffic and coastal station in suburban area to study the chemical compositions and emission patterns of ambient VOCs and OVOCs thoroughly. Results from those two campaigns showed significant differences across Hong Kong. Acetone, formaldehyde, and acetaldehyde were the most abundant species at roadside environment, while formaldehyde, methanol and acetone were the major species in suburban atmosphere. The major contributors to ozone formation were formaldehyde (89.64 μg/m3) at roadside and isoprene (13.46 μg/m3) at suburban among the measured VOCs in Hong Kong. In addition, the source apportionment results from positive matrix factorization (PMF) analysis showed that the sampling site at the southeastern tip of Hong Kong was strongly influenced by urban plumes from the PRD region and by oceanic emissions as well.

How to cite: Han, S., Tan, Y., and Lee, S.: Characterization and Evaluation of Long-term Air Quality Across Urban Hong Kong, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11503, https://doi.org/10.5194/egusphere-egu23-11503, 2023.

17:40–17:50
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EGU23-4749
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AS3.15
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ECS
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On-site presentation
Satoko Kayaba and Mizuo Kajino

Transition metal components in PM2.5 induce inflammation of the respiratory system. The increase in aerosol acidity due to gaseous pollutants promotes metal dissolution and contributes to redox activation. In this study, the impact of renewable energy shifting, passenger car electrification and light-weighting on atmospheric concentration of PM2.5 total mass, Fe, Cu, Zn and aerosol acidity in Japan over 2050 was evaluated using a regional meteorology-chemistry model. The primary emissions of PM2.5, Fe, Cu, and Zn were reduced by 9%, 19%, 18% and 10%, and their surface wide-area concentrations decreased 6 – 8%, 10 – 12%, 16 – 18% and 2 – 4%, respectively. On a PM2.5 mass basis, battery electric vehicles (BEVs) have been considered to have no advantage in non-exhaust PM emissions because the increased tire and road wear and resuspension due to their heavy weight offset the benefit of brake wear reduction by regenerative brake. Indeed, passenger car electrification without light-weighting also did not significantly reduce total primary PM2.5 emissions in Japan in this study (-1.4%), but was highly effective in reducing metals, especially Fe and Cu (-6.7% and -11.4%, respectively). Furthermore, this study estimated that even tire and road wear and resuspension could be reduced if the drive battery and body frame were light-weighted, and the benefit would be larger. Therefore, vehicle electrification (mainly BEVs) and light-weighting could be one of the effective means of reducing the risks of respiratory inflammation. The renewable energy shifting reduced SOx and NOx emissions from thermal power plants and decreased aerosol acidity near power plants (approximately pH +0.2), while the passenger car electrification reduced NOx and NH3 emissions and slightly increased aerosol acidity in urban, as a result of acid-base balance (in July, approximately pH -0.1 – -0.2). However, anyway, the sensitivity of water-soluble metal concentrations was mostly dependent on changes in primary metal emissions and little affected by changes in aerosol acidity (0 – +2% for Fe, 0 – +0.5% for Cu and Zn). Therefore, it was suggested that primary emission control of metals is more important than gaseous pollutants in reducing water-soluble metal concentrations.

How to cite: Kayaba, S. and Kajino, M.: Impact of energy and vehicle transformation through 2050 on atmospheric PM2.5-metals concentration and aerosol acidity that induce respiratory inflammation in Japan;  focus on the changes in exhaust/non-exhaust and upstream emissions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4749, https://doi.org/10.5194/egusphere-egu23-4749, 2023.

17:50–18:00
|
EGU23-5216
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AS3.15
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Highlight
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On-site presentation
Haofan Zhang, Dianyu Zhu, Pan He, Miaomiao Liu, and Jun Bi

Understanding the health impact of air pollution is critical for understanding the benefit of environmental regulations, especially under the synergies of carbon neutrality and air pollution control. We examine the effect of fine particulate matter (PM2.5) on individual healthcare expenditures in China from 2017 to 2019 using daily transaction data from 320 cities and evaluate the health co-benefits of carbon neutrality. Results show that each 10 μg/m3 increase in daily PM2.5 exposure is associated with a 0.31 percent increase in three-day healthcare consumption and a 0.53 percent increase in three-day individual healthcare expenses. Achieving carbon neutrality goals with the national air quality daily standard of 35 μg/m3 can save 1.5 billion yuan annually. Ambitious goals with World Health Organization Air Quality Guidelines of 15 μg/m3 can nearly double the saving. This study not only provides insight into the potential health benefits of carbon neutrality in China but also suggests that extensive benefits may result from more ambitious targets.

How to cite: Zhang, H., Zhu, D., He, P., Liu, M., and Bi, J.: The Short-Term Impact of Air Pollution on Healthcare Expenditures, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5216, https://doi.org/10.5194/egusphere-egu23-5216, 2023.

Posters on site: Thu, 27 Apr, 16:15–18:00 | Hall X5

Chairpersons: Juliane Fry, Dominik Brunner
X5.96
|
EGU23-7589
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AS3.15
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ECS
|
Zixuan Cheng, James Allan, Dawei Hu, Eiko Nemitz, Ben Langford, Carole Helfter, Will Drysdale, James Lee, James Cash, Sam Cliff, Dantong Liu, and Joshi Rutambhara

Black carbon (BC) is a significant environmental health and climate forcing concern. Direct measurement of black carbon fluxes using eddy covariance can quantify emissions and identify sources. Previous studies have quantified urban black carbon emissions in highly polluted countries such as China and India, but to date no research has been done in the UK and Europe. This study uses an eddy covariance system using a Single Particle Soot Photometer (SP2) deployed on the BT Tower in London to directly measure BC fluxes in central London. This is as part of the UK Integrated Research Observation System for Clean Air (OSCA). We have produced some primary results including time series of black carbon concentrations and fluxes in central London in winter and summer and diurnal profiles. Comparisons with NOx and organic matter fluxes are also underway to identify the main sources of black carbon in central London and suggest that due to recent emissions controls, cooking may now be the most significant local source rather than transport or space heating.

How to cite: Cheng, Z., Allan, J., Hu, D., Nemitz, E., Langford, B., Helfter, C., Drysdale, W., Lee, J., Cash, J., Cliff, S., Liu, D., and Rutambhara, J.: Eddy covariance measurements of black carbon emissions in central London, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7589, https://doi.org/10.5194/egusphere-egu23-7589, 2023.

X5.97
|
EGU23-179
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AS3.15
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ECS
Horia Camarasan, Andrei Radovici, Horatiu Stefanie, Alexandru Mereuta, Nicolae Ajtai, and Camelia Botezan

Apart from affecting citizens health and wellbeing across urban and rural areas, air pollution has significant economic implications which inhibit progress, especially for developing countries. The role of air quality monitoring to ensure population wellness is a key topic in the current pursuit for the sustainable development goals, promoting active response from decision-makers to address acute socio-environmental challenges and to promote a resilient and sustainable future. In this study, an integrated air quality monitoring system was proposed within the municipality of Cluj-Napoca, by adopting a novel methodology for sensor-placement throughout the city, composing an efficient network of stations with high spatial and temporal resolution. The purpose of this network is to assist the population and local authorities by providing a platform that offers real-time mapped data related to local air quality and potential health threats. This approach was based upon a thorough geospatial data analysis of land-use in the area, where possible correlations between air quality and anthropic activities that generate emissions were studied. Using these factors, an analysis of possible placement locations was carried out, in order to determine the most representative network shape that would reflect the air quality variations throughout different locations of the study area and will prove to be cost-efficient by using a limited number of sensors. A series of maps with various networks morphologies, were generated and compared. An innovative method of using a “natural pattern”-based approach for the network morphology, proved to be the most efficient in fulfilling all the proposed requirements of the network.

How to cite: Camarasan, H., Radovici, A., Stefanie, H., Mereuta, A., Ajtai, N., and Botezan, C.: Air Quality Monitoring for Sustainable Development in Cluj-Napoca, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-179, https://doi.org/10.5194/egusphere-egu23-179, 2023.

X5.98
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EGU23-397
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AS3.15
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ECS
Liliana Gina Lazurca (Andrei), Dumitru Mihăilă, Petruț Ionel Bistricean, and Vasilică Dănuț Horodnic

According to the Air Quality Framework Directive, air pollutant concentration levels have to be assessed and reported annually by each European Union member state, taking into consideration European air quality standards. Plans and programmes should be implemented in zones and agglomerations where pollutant concentrations exceed the limit and target values. The main purpose of this research study is to analyse the concentrations of pollutants in the atmosphere, their spatial and temporal trends and to draw an overall picture of air quality in Suceava County. The study uses an hourly database for SO2, NO2, CO, PM10 and O3 pollutants, from 2009-2020, from 4 air quality monitoring stations in Suceava County. Pollutant levels were statistically and graphically / cartographically modeled for the entire 2009-2020 interval on the distributive-spatial and regime, temporal component. Inter-station differences and similarities were analyzed causally. The results showed that PM10 air pollution is the biggest challenge for the Suceava city, the highest multi-year average of 31.86 µg/m3 is recorded at the SV2 station in the Burdujeni district although it does not exceed the limit value for the protection of human health (40 µg/m3). Average daily PM10 levels place Suceava County in quality class III (good). SO2 pollution in Suceava County is limited, with average hourly concentrations well below the hourly limit for the protection of human health throughout the period analysed. Based on diurnal average levels, statistical calculations for SO2 and NO2 show that at all four stations in the county, air quality was excellent. The ozone is measured only at three stations: EM3, SV1, SV2. In Suceava county, the multi-year average ozone concentration was 49.61 μg/m3. According to the daily average level of O3, the study area falls into quality class II, very good.  The average CO levels indicate an excelent air quality.

How to cite: Lazurca (Andrei), L. G., Mihăilă, D., Bistricean, P. I., and Horodnic, V. D.: Air quality assement for Suceava County, Romania, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-397, https://doi.org/10.5194/egusphere-egu23-397, 2023.

X5.99
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EGU23-4794
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AS3.15
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ECS
|
Chaerin Park and Sujong Jeong

As it is predicted that the amount of urban on-road CO2 emissions will continue to increase, it is essential to manage urban on-road CO2 concentration for effective urban CO2 mitigation. However, limited observation of on-road CO2 concentration prevents the full understanding of the variation of urban on-road CO2 concentration. Therefore, in this study, a machine learning based model that predicts on-road CO2 concentration (CO2traffic) was developed for Seoul, South Korea. This model predicts hourly CO2traffic with high precision (R2 = 0.8 and RMSE = 22.9 ppm) by utilizing CO2 observation, traffic volume, traffic speed, and wind speed data as main factors. Analyzing the CO2traffic data predicted by the model, the high spatiotemporal inhomogeneity of CO2traffic over Seoul with 14.3 ppm by time and 345.1 ppm by road was found. The large spatiotemporal variability of CO2traffic is related to different road types (major arterial road, minor arterial road, and urban highway) and land-use types (residential, commercial, bare ground, and urban vegetation) where the road belongs. The cause of the increase in CO2traffic was different by its road type, and the diurnal variation of CO2traffic was different by its land-use type. Our results demonstrate that high spatiotemporal on-road CO2 monitoring is needed to manage the urban on-road CO2 concentration showing high inhomogeneity. In addition, it suggests that a model using machine learning techniques can be an alternative for monitoring CO2 concentrations on all roads without conducting the observation.

This work was supported by Korea Environment Industry &Technology Institute(KEITI) through "Climate Change R&D Project for New ClimateRegime.", funded by Korea Ministry of Environment(MOE) (2022003560006).

How to cite: Park, C. and Jeong, S.: Machine learning based estimation of urban on-road CO2 concentration in Seoul, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4794, https://doi.org/10.5194/egusphere-egu23-4794, 2023.

X5.100
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EGU23-1779
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AS3.15
Woosuk Choi

Since the Seoul Metropolitan Area, Republic of Korea, is highly populated, a large number of people are frequently exposed to high concentrations of particulate matter (PM) with mean aerodynamic diameters of <= 10 mm (PM10) in cold season. The concentration of PM10 in Seoul Metropolitan Area increases by transboundary transport, local direct emissions, and chemical reactions of aerosol precursors in the atmosphere. Here, the Seoul Metropolitan Area (Seoul, Gyeonggi-do, and Incheon) and surrounding region (Chungcheongnam-do, Daejeon, and Sejong) are regionally classified by clustering analysis based on the variability of PM10 concentrations. According to the inertia score by the number of clusters, the optimum cluster number of regional variability of PM10 is four. The region of cluster 1 is divided into southern Gyeonggi-do and eastern Chungcheongnam-do, the cluster 2 is mainly classified Incheon, western Gyeonggi-do, and Seoul. The cluster 3 region is western Chungcheongnam-do adjacent to Yellow Sea, and the cluster 4 is classified into eastern Gyeonggi-do. The variability of PM10 in each region is distinguished by the local chemical pollutants emission and weather conditions such as wind speed and direction in each region. This regional classification of PM10 variability is different from administrative districts. Considering most of policies for responding to high concentrations of PM10 are being prepared by administrative districts, this study suggests that a response on the basis of these regional PM10 distribution would be more effective way to improve air quality in the Seoul Metropolitan and Chungcheong Area.

How to cite: Choi, W.: Regional classification according to PM10 concentrations in the Seoul Metropolitan and Chungcheong Area, Republic of Korea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1779, https://doi.org/10.5194/egusphere-egu23-1779, 2023.

X5.101
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EGU23-4163
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AS3.15
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ECS
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Shubham Dhaka and Amit Sharma

Western India is a region which is exposed to pollution contributed by both natural and anthropogenic sources that may be local, regional or remote sources as reported in limited observational studies that have been conducted in the region. In the present study, temporal variation of surface ozone is studied at two urban centres (Jodhpur and Ajmer) in western India during a winter season (December 2018 – February 2019) by using ground based observation data from Central Pollution Control Board (CPCB). Jodhpur is found to have the higher seasonal average ozone (~48 µg/m3) with the daily mean values reaching to as high as 87.5 µg/m3. Ajmer closely followed with seasonal average ozone as ~44 µg/m3 and the daily mean values reaching upto 80 µg/m3. Diurnal trend (seasonally averaged) for ozone at Ajmer reveals comparatively higher afternoon values (even exceeding 100 µg/m3) but lower night time levels (close to 20 µg/m3) thus suggesting a stronger ozone production rate (~9.2 µg/m3/hr) at Ajmer during daytime (0600 – 1500 hrs local time). The ozone production rate at Jodhpur is lower (5.4 µg/m3/hr) during the same time due to lower afternoon values (~80 µg/m3) and higher nighttime levels (> 30 µg/m3). Subsequently, a detailed analysis is performed for the monthly peak ozone days in each winter month for both urban centres using ground based observation data, a back trajectory model  and a widely used reanalysis dataset. The analysis reveals contribution of both regional as well as long range transport from different directions in different months to higher levels of surface ozone, in addition to enhanced photochemistry and/or weak ozone titration on some days.  The ozone levels even breached the Indian National Ambient Air Quality Standards (NAAQS) limit of 100 µg/m3 set by CPCB for daily maximum 8 hour ozone concentration on some of the monthly peak ozone days at both urban centres. The study highlights the importance of transported ozone in enhancing ozone levels over the western India region during winter which may have severe impacts on vegetation, human health and climate change.

How to cite: Dhaka, S. and Sharma, A.: Analysis of wintertime ozone at two urban centres in western India., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4163, https://doi.org/10.5194/egusphere-egu23-4163, 2023.

X5.102
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EGU23-8003
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AS3.15
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ECS
Mali Chariot, Olivier Laurent, Damien Delanoe, Guillaume Nief, Hervé Utard, and Luc Lienhardt

As part of the European research project ICOS-Cities, the Laboratoire des Sciences du Climat et de l'Environnement (LSCE) and Origins.earth are seeking to extend the Greenhouse Gases (GHG) measurement network in Paris and its immediate suburbs by installing new sensors on the roofs of tall buildings. Each sensor will measure CO2 concentration in real time, which will then be used in an inversion model to determine CO2 emissions at the scale of a district. Several sensors will be upgraded in a second phase with the addition of an Air Quality (AQ) measurement cell.

We present a new stand-alone sensor box design (called AtmoBox) that allows to connect GHG and AQ sensors in a single box, as well as the implementation of these Atmoboxes in a ground-based atmospheric monitoring network. In addition to 9 long-term stations equipped with high precision CRDS spectrometers, about 30 Mid Cost instruments are deployed within Paris and its near suburb, measuring CO2 through NDIR sensors. We will detail the steps from the search for suitable sites for the urban measurements, the characterisation of the sensors in relation to the environmental parameters in the laboratory, the related calibration and quality control strategy to meet the performance objective and the performance assessment of the sensors.

How to cite: Chariot, M., Laurent, O., Delanoe, D., Nief, G., Utard, H., and Lienhardt, L.: Development and deployment of a “Mid Cost” sensor network for urban Greenhouse Gases and Air Quality monitoring with a focus on CO2., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8003, https://doi.org/10.5194/egusphere-egu23-8003, 2023.

X5.103
|
EGU23-11897
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AS3.15
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ECS
Alicja Skiba, Mirosław Zimnoch, Zbigniew Gorczyca, Mikita Maslouski, and Michał Marzec

Regular, monthly based, diurnal measurements of atmospheric carbon dioxide concentration and its carbon isotope composition (13C/12C and 14C/12C ratios) were performed between 9 February 2021 and 1st February 2022 in Krakow, the second biggest city of Poland, populated by around 780,000 inhabitants. Spot air samples were collected in 3 l glass flasks every 4 hours from the roof of the building (50°04’ N 19°55’ E 220 AMSL, ∼ 20 m above the surface) during each measurement campaign. A total of 72 air samples were collected during 12 measurement campaigns. The samples were analyzed with Picarro G2101i (Picarro Inc., Santa Clara, California, USA) to determine the carbon dioxide. After that, the samples were analyzed with Isotope-Ratio Mass Spectrometry (IRMS) and Accelerator Mass Spectrometry (AMS) in order to determine δ13C and Δ14C composition. The carbon dioxide concentration during the campaign ranged from 404 ppm (7 September 2021) to 617 ppm (1 February 2022) with the one-year average of 463 ppm. δ13C ranged from -14.79 ‰ (1st February 2022) to -8.5 ‰ (7th September 2021). The one-year average results of Δ14C were -35 ‰.

Furthermore, measurement of gas concentration and its isotopic composition, along with the use of the isotope-mass balance, allowed determination of fossil fuel-related and biogenic contributions to the total measured CO2 load during campaign days, allowing to characterise the diurnal and seasonal variability of those components in the urban environment. Based on the obtained results, a dataset dedicated for the validation of WRF-CHEM high-resolution simulations of the city atmosphere has been prepared.

 

ACKNOWLEDGEMENTS

The presented work was funded by the CoC02 project, which has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 958927 and the "Excellence Initiative - Research University" program at AGH University of Science and Technology.

How to cite: Skiba, A., Zimnoch, M., Gorczyca, Z., Maslouski, M., and Marzec, M.: Atmospheric concentrations of carbon dioxide and its isotopic composition in Krakow (Southern Poland) based on one-year CoCO2 measurement campaign, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11897, https://doi.org/10.5194/egusphere-egu23-11897, 2023.

X5.104
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EGU23-12300
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AS3.15
Sarath Guttikunda, Puja Jawahar, and Sai Krishna Dammalapati

Representative emissions and pollution data is a critical requirement for supporting clean air action plans for cities. The data can be used for both long-term policy assessments and short-term pollution alert systems via modeling at various scales. In a data sparse environment, several assumptions are made, and several data resources are accessed to construct a reliable emissions and pollution modeling framework to support public and policy dialogue. These assumptions include interpolation of observations from one zone to another, extrapolation of operational conditions from one country to another, and utilization all available source and emissions data, complemented with open satellite retrievals and global databases with information on population, topography, land use, urbanization level, road network, locations of commercial and other points of interest, to compile a city’s spatially and temporally representative dynamic emissions map. The urban airshed inventory is maintained at a spatial resolution of 0.01 degrees (~1km) and with monthly and hourly temporal modulation suitable for chemical transport modeling. Here, we will present examples from the Air Pollution knowledge Assessments (APnA) program implemented for 60 Indian cities and expansion of the program to Balkan, Central Asian, and African cities, while addressing data gaps using emerging technology and big data feeds, combined with traditional meteorological and chemical transport modeling (WRF-CAMx) systems. Where available validation of the model results against available monitoring data from reference-grade and sensor networks is also included in the study. All the methodologies and data resources are accessible @ https://www.urbanemissions.info

How to cite: Guttikunda, S., Jawahar, P., and Dammalapati, S. K.: Air Pollution knowledge Assessments (APnA) City Program in Asia and Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12300, https://doi.org/10.5194/egusphere-egu23-12300, 2023.

X5.105
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EGU23-7665
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AS3.15
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ECS
Xiaojuan Lin, Ronald van der A, Jos de Laat, Henk Eskes, and Zhu Liu

CO2 emissions of power plants are often self-reported and calculated based on fuel consumption. The authenticity of CO2 emission data from power plants are preferable to be verified by independent measurements. Satellite observations can provide these CO2 emission observations from isolated power plants. However, there are two difficulties in the current top-down anthropogenic CO2 emission inversions, that is, (1) the anthropogenic CO2 emission signal is difficult to distinguish from the background of other emitted CO2, and (2) the temporal and spatial resolution of CO2 satellite observation data are currently limited. In this study, we focus on how to improve the accuracy of CO2 emissions using different methods and wind data estimates. We assess these emission estimates by comparison with USA EPA emission data, and identify and explore suitable cases elsewhere in the world. We have selected only isolated power plants for this study, to avoid complications because of multiple sources in close proximity. We first compare the Gaussian plume model and cross-sectional flux methods for estimating CO2 emissions of power plants. Then we examine the sensitivity of the emission estimates to possible choices for the wind field. For verification we have used power plant emissions that are reported on an hourly basis by the Environmental Protection Agency (EPA) in the United States. By using the OCO-2 and OCO-3 observations over the past four years we identified emission signals of isolated power plants and arrived at a total of 50 collocated cases involving 22 power plants. We found the wind field halfway the height of planetary boundary layer (PBL) yielded the best results. We found that the instantaneous satellite estimated emissions of these 50 cases and reported emissions display a weak correlation (R2=0.12). The correlation improves with averaging over multiple observations of the 22 power plants (R2=0.40). The method was subsequently applied to 106 power plants cases worldwide. We demonstrate that accurate estimation of power plant emissions can be achieved by monitoring from future satellite missions with more frequent observations.

How to cite: Lin, X., van der A, R., de Laat, J., Eskes, H., and Liu, Z.: Monitoring and quantifying CO2 emissions of isolated power plants from space, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7665, https://doi.org/10.5194/egusphere-egu23-7665, 2023.

X5.106
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EGU23-8718
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AS3.15
Lucyna Samek, Anna Ryś, Zdzisław Stęgowski, and Katarzyna Styszko

Samples of PM10 were collected at the traffic station in Krakow, Poland during two periods: 2nd February- 30th May 2018 and 2nd February 17th June 2020. PM10 concentrations were determined gravimetrically. PM10 concentrations dropped by 50% from 74±29 µg/m3 to 37±13 µg/m3 in 2018 and 2020, respectively. Elemental concentrations were determined by energy dispersive X-ray fluorescence method (EDXRF) and ion concentrations by ion chromatography (IC). 18 elements and 8 ions were measured. Ratios of concentrations in 2018 to 2020 were above 1.7 for the following elements: S, Cl, K, Zn, Br and ions SO42-, Na+, NH4+. The above-mentioned ratio was equal to 1.4 for Cu, Fe and Co. Similar concentrations in 2018 and 2020 were observed for the following chemical species: Ca, Ti, Mn, Ni, Rb, Sr, K+, Mg2+, Ca2+, PO43-. Cr concentration was higher in 2020 compared to 2018. Four factors were obtained from PMF (Positive Matrix Factorization) modelling. The following sources were attributed: solid fuel combustion, secondary inorganic aerosols, traffic/industry/construction work and soil. The contribution of traffic/industry/construction work to PM10 mass was the highest. It was equal to 24.6 µg/m3 and 23.4 µg/m3 in 2018 and 2020, respectively. The contribution of solid fuel combustion and secondary inorganic aerosols was five times lower in 2020 than in 2018. Contribution of solid fuel combustion was 14.5 µg/m3 and 2.6 µg/m3 in 2018 compared to 2020. SIA was lowering from 15.7 µg/m3 in 2018 to 2.5 µg/m3 in 2020. Traffic/industry/construction work and soil contribution was on the similar level in both years. Two factors affected characteristic of PM10: one was a ban of using coal and wood for heating purpose introduced in Krakow in September 2019 and second one was pandemic of COVID-19 started in March 2020. Our study will be helpful for the local authority in preparing future plans for reducing air pollution within the city.

Acknowledgments: This research project was supported/partly supported by the program “Excellence initiative—research university” for the University of Science and Technology. The bilateral cooperation  project nr BPN/BPT/2021/1/00001 between Poland and Republic of Portugal partially financed this work together with the subsidy of the Ministry of Science and Higher Education, grant number 16.16.220.842.

How to cite: Samek, L., Ryś, A., Stęgowski, Z., and Styszko, K.: Characterization of PM10 fraction before pandemic and during pandemic COVID-19 at the traffic station in Krakow, Poland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8718, https://doi.org/10.5194/egusphere-egu23-8718, 2023.

X5.107
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EGU23-11161
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AS3.15
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ECS
Hyemin Hwang, Jong Sung Park, Joon Young Ahn, Kwang Yul Lee, Jong Bum Kim, and Jae Young Lee

Since smaller particles can get through deeper into the human body, a model that predicts PM1.0 concentration temporally and spatially is important. Despite their importance, there are significantly fewer PM1.0 measurement stations than PM2.5 and PM10 in South Korea. Therefore, in this study, PM1.0 prediction models were constructed using a machine learning algorithm to predict the spatiotemporal concentration of PM1.0 in a place where the PM1.0 measurement was not available.

From January to December 2021, hourly data for the concentration of particulate matters(PM10 and PM2.5), the composition of PM2.5, the concentration of gaseous pollutants(SO2, O3, CO, NO, NOy, NH3), and weather conditions(wind direction, wind speed, temperature, relative humidity, press, precipitation, cloud) measured at three different Air Quality Measurement Systems were collected. PM1.0 concentrations were collected at two of these sites which are Seoul and Ansan(Gyeonggi-do), and no PM1.0 concentration was measured at the other site which is Seosan(Chungcheongnam-do). Since the three measurement stations were located close to each other and had similar sources and characteristics, the concentration of PM1.0 in Seosan was predicted by using a model trained based on Seoul and Ansan data.

Based on collected data, the importance of variables in the model was identified and variables that are important in predicting PM1.0 concentration were selected. Ensemble models (Random Forest, gradient boosting) and sequence models (RNN, LSTM, GRU) were compared to find a better model. Each model was evaluated by calculating the coefficient of determination and the proportion of impossible concentrations. Finally, based on the model with the best prediction result, the PM1.0 concentration was predicted at the target location (Ansan) where the PM1.0 concentration was unknown.

Our results showed that PM1.0 concentration can be predicted with high accuracy considering both the spatial distribution and temporal variability of the concentration. The results of this study can be used as data for selecting models in air quality prediction studies using machine learning. In addition, economical and efficient choices can be made in the construction of new monitoring stations in the future.

 

Acknowledgments

This study was supported by the National Research Foundation of Korea (grant number NRF-2021R1C1C1013350) and by a grant from the National Institute of Environmental Research (NIER), funded by the Ministry of Environment (ME) of the Republic of Korea (NIER-2022-04-02-087).

How to cite: Hwang, H., Park, J. S., Ahn, J. Y., Lee, K. Y., Kim, J. B., and Lee, J. Y.: Spatio-Temporal Prediction of PM1.0 Concentration in South Korea Using a Machine Learning Algorithm, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11161, https://doi.org/10.5194/egusphere-egu23-11161, 2023.

X5.108
|
EGU23-11286
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AS3.15
Jin-Ho Yoon, Dasom Lee, Hyun Cheol Kim, Jee-Hoon Jeong, Baek-Min Kim, and Shih-Yu (Simon) Wang

East Asia, including South Korea, has become a regional hot spot for the deteriorating air quality in recent years. During winter and spring, Particulate Matter (PM) is a dominant air pollutant. On the other hand, ozone becomes a major issue during summer season. In this talk, we’d like to show how synoptic scale weather pattern affects both PM and ozone in South Korea. Particularly, spatial synoptic classification (SSC) data are used to analyze characteristics of PM and ozone concentration according to synoptic weather patterns. During winter, dry moderate (DM) types occur frequently alongside high PM cases. The composite weather map showed a weak northwesterly wind field as a potential cause. On the contrary, it is interesting to note that dry polar (DP) types can be associated with low PM cases as well as high PM depending on near-surface wind speed. On the other hand, we found that DM, DT, and MT are commonly associated with high ozone; dry tropical (DT) produces ozone with the greatest efficiency, especially high levels of concentration. This finding implies a strong connection between surface ozone and climate change, because the occurrence of DT weather has increased by more three times over the past fifty years in South Korea.

How to cite: Yoon, J.-H., Lee, D., Kim, H. C., Jeong, J.-H., Kim, B.-M., and Wang, S.-Y. (.: Relationship between air pollution and synoptic scale weather in South Korea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11286, https://doi.org/10.5194/egusphere-egu23-11286, 2023.

X5.109
|
EGU23-13290
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AS3.15
Juliane Fry, Pascale Ooms, Roel Vermeulen, and Jules Kerckhoffs

The Ruisdael Rotterdam campaign in August - September, 2021 featured a comprehensive suite of air pollutant, greenhouse gas, and meteorological data collection across the city and port of Rotterdam, Netherlands. We will present data from the Utrecht University Air Quality car mobile platform, which was deployed for >80 hours of sampling across the region, measuring particulate matter (PM1, PM2.5 and PM10), ultrafine particulate matter count (UFP), black carbon (BC), carbon dioxide (CO2), and nitrogen dioxide (NO2). We analyze this data with particular focus on the relative contribution of urban and port emissions to air pollution levels across the city, and on the role of neighborhood design in determining street-level concentrations of pollutants.

How to cite: Fry, J., Ooms, P., Vermeulen, R., and Kerckhoffs, J.: Air pollution in Rotterdam: urban vs. port contributions and the role of neighborhood design, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13290, https://doi.org/10.5194/egusphere-egu23-13290, 2023.

X5.110
|
EGU23-14039
|
AS3.15
Miroslaw Zimnoch, Michał Gałkowski, Piotr Sekula, and Lukasz Chmura

Effective mitigation efforts in the face of observed climate change require independent tools based on atmospheric observations to estimate greenhouse gas emissions at different spatial and temporal scales. Atmospheric transport models constitute a key element of anthropogenic emissions monitoring and verification systems. It represents atmospheric transport in such systems, which allows the use of inverse methodology to estimate emissions from observed concentrations. Reliable numerical simulations of atmospheric transport over complex urban areas require model configurations that provide adequate resolution reflecting the complex topography and land cover, as well as parameterization of physical processes optimised for the specifics of urban areas. This study presents an attempt to apply the WRF-CHEM model for the simulation of CO2 transport in the urban area of Krakow, the second largest city located in the southern part of Poland. The simulation has been performed for a 3 day period in October 2021 and was validated by a CO2 molar fraction vertical measurements performed on board of a tethered balloon operating as a commercial touristic attraction in the city centre. The modelling results have been compared with the observations to determine model performance in terms of: (i) capture the temporal dynamics of the nocturnal boundary layer formation and (ii) identifying detected CO2 plume originating from a point source to confirm the expected source position and estimate the CO2 emission from that source.

The presented work was funded by the CoCO2 project, which has received funding from the European Union's Horizon 2020 research and innovation program under Grant Agreement No. 958927 and the "Excellence Initiative - Research University" program at AGH University of Science and Technology.

How to cite: Zimnoch, M., Gałkowski, M., Sekula, P., and Chmura, L.: High-resolution simulation of CO2 dispersion in urban atmosphere of Krakow, Southern Poland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14039, https://doi.org/10.5194/egusphere-egu23-14039, 2023.

X5.111
|
EGU23-14432
|
AS3.15
|
ECS
Darijo Brzoja, Velimir Milić, Vesna Gugec, Valentina Jagić, and Stipica Šarčević

This study aims to improve the knowledge of air quality in Zagreb, the capital of Croatia. It gives insight into the spatial distribution of concentrations of the main city pollutants (fraction of particulate matter < 10 µm and nitrogen dioxide) within the process of developing an air quality modeling system in high resolution. The work is a part of an ongoing AIRQ project (AIRQ - Expansion and Modernisation of the National Network for Continuous Air Quality Monitoring) funded by the European Regional Development Fund and Environmental Protection and Energy Efficiency Fund (FZOEU).

Air pollution is perceived as the second biggest environmental concern for Europeans, next to climate change, as quoted by European Commission in 2017., and it is the most important environmental risk to human health. Over the last three decades, policies to reduce air pollution have led to improved air quality, nevertheless, in some European cities, air pollution still poses risks to health. Zagreb is, unfortunately, one of them. Based on the levels of fine particulate matter measured in the air in 2019. and 2020., among 323 European cities, Zagreb is ranked 256th, and air quality in the city is categorized as „poor“ (EEA, 2022.).

In cities, pollutant concentrations have strong gradients, in particular those related to traffic. Since continuous air quality measurements are usually representative of several square kilometers for urban background locations or representative of a specific street, authorities are encouraged to use dispersion models to complement the observations for a city.

In this study, the ADMS-Urban model was set up for the Zagreb agglomeration. Within the model, measurement data from the Desinic site were used as background data representing the contribution of long-range transport to the city. Gridded emissions (500 m by 500 m resolution) were obtained from the Croatian National Emission Inventory (source: Ministry of Economy and Sustainable Development). Since emission sectors with low emission heights, such as traffic and household emissions, generally make larger contributions to surface concentrations and health impacts in urban areas than emissions from high stacks, special attention was given to road emissions, their spatial distribution, and time profiles taking into consideration the limitation of available data.  Thus, road emissions and two large point sources were modeled explicitly. The meteorology data used within the model were from the Maksimir measurement site and are representative of the whole modeling domain.

                The focus of the analysis was the main pollutants usually found to exceed EU limit values within the city and the surrounding area PM10 and NO2. The model's performance is assessed against measurements from 14 urban, urban-background, and near-traffic sites using a range of metrics concerning annual averages, high hourly average concentrations, and diurnal cycles. The model shows good performance compared to measurements for PM10, although it underestimates concentration values during high-pollution winter episodes. First NO2 results show characteristic high concentrations at the traffic hot spots and next to the main roads.

How to cite: Brzoja, D., Milić, V., Gugec, V., Jagić, V., and Šarčević, S.: Air quality simulations of PM10 and NO2 for Zagreb using ADMS-Urban dispersion modeling system, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14432, https://doi.org/10.5194/egusphere-egu23-14432, 2023.

X5.112
|
EGU23-17283
|
AS3.15
Manolis N. Romanias, Jerome Lasne, Anais Lostier, Sabine Vassaux, Didier Lesueur, Vincent Gaudion, Marina Jamar, Richard Derwent, Sebastian Dusanter, and Therese Salameh

Outdoor air pollution is the fourth cause of death worldwide, linked to around 4.2 million deaths per year. Air pollution is more severe in urban environments of cities/megacities, due to the high population density and intense anthropogenic activities. More than 50% of global population lives currently in urban areas,1 and a projected 70% is anticipated by 2050,2 even reaching 84% of the population in the EU.3

Around 40% of urban areas are covered by asphalt pavements, a fraction that keeps increasing with urbanization.4,5 Asphalt is a petroleum byproduct composed of a large number of organic species 6-8 capable of emitting a wide variety of organic compounds. Although emission of pollutants by asphalt mixtures have been investigated at deposition temperatures (120-160°C), data at service temperatures (i.e., atmospheric relevant conditions) are lacking.

Among atmospheric pollutants, Volatile Organic Compounds (VOCs) play a key role in urban atmospheres, as efficient ozone (O3) and Secondary Organic Aerosol (SOA) precursors. In the present work, we characterize and quantify VOC emissions by fresh and aged asphalt surfaces as a function of temperature. Experiments were performed inside a Teflon atmospheric simulation chamber coupled with PTR-ToF-MS, and GC-MS/FID for VOC speciation and quantification. We observe that at atmospheric relevant temperatures, asphalt surfaces significantly contribute to urban pollution, and therefore urgently need to be included in emission inventories, and in air quality models. Emissions are shown to be key in terms of ozone and SOA formation potential in urban areas to account for observations of urban air pollution.

 

References

(1)          Ritchie, H.; Roser, M. Urbanization. Our World in Data 2018.

(2)          United Nations “World Urbanization Prospects: The 2018 revision ”, 2018.

(3)          EuropeanCommission; Eurostat. Urban Europe : statistics on cities, towns and suburbs : 2016 edition; Publications Office, 2016.

(4)          Akbari, H.; Shea Rose, L.; Taha, H. Analyzing the land cover of an urban environment using high-resolution orthophotos. Landsc. Urban Plan. 2003, 63 (1), 1.

(5)          Pacheco-Torgal, F.; Labrincha, J.; Cabeza, L. Eco-efficient Materials for Mitigating Building Cooling Needs; 1st Edition ed., 2015.

(6)          Lesueur, D. The colloidal structure of bitumen: Consequences on the rheology and on the mechanisms of bitumen modification. Advances in Colloid and Interface Science 2009, 145 (1), 42.

(7)          Hung, A. M.; Goodwin, A.; Fini, E. H. Effects of water exposure on bitumen surface microstructure. Construction and Building Materials 2017, 135, 682.

(8)          Mirwald, J.; Nura, D.; Eberhardsteiner, L.; Hofko, B. Impact of UV–Vis light on the oxidation of bitumen in correlation to solar spectral irradiance data. Construction and Building Materials 2022, 316, 125816.

How to cite: Romanias, M. N., Lasne, J., Lostier, A., Vassaux, S., Lesueur, D., Gaudion, V., Jamar, M., Derwent, R., Dusanter, S., and Salameh, T.: How VOC Emissions by Asphalt Pavements under Service Conditions Impact Air Quality in Cities?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17283, https://doi.org/10.5194/egusphere-egu23-17283, 2023.

X5.113
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EGU23-15484
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AS3.15
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Highlight
Matthias Zeeman, Kit Benjamins, Ferdinand Briegel, Marc-Antoine Drouin, Gregor Feigel, Daniel Fenner, Simone Kotthaus, Rainer Hilland, Fred Meier, William Morrison, Marvin Plein, Swen Metzger, Karthik Reddy, Nektarios Chrysoulakis, Sue Grimmond, and Andreas Christen

Field observation networks are becoming denser, more diverse, and more mobile, while being required to provide real-time results. The ERC urbisphere program is coordinating multiple field campaigns simultaneously to collect datasets on urban atmospheric and environmental conditions and processes in cities of different sizes. The datasets are used for improving climate and weather models and services, including assessing the impact of cities on the atmosphere (e.g. aerosols, greenhouse gases) as well as the exposure of urban populations in the context of atmospheric extreme events (heat waves, heavy precipitation, air pollution). For model development and evaluation, we are using meshed networks of in-situ observations with ground-based and airborne (remote-)sensing platforms. This contribution describes the urbisphere data management infrastructure and processes required to handle a variety of data streams from primarily novel modular observation systems deployed in complex urban environments.

The modular observation systems consist of short-term deployed instrumentation and are separated into three thematic modules. Module A aims at characterizing urban form and function affecting urban climates. Module B quantifies the impact of urban emissions (heat, pollutants, greenhouse gases, etc.) on the urban boundary layer over and downwind of cities. Module C provides data on human exposure at street and indoor-level. The three modules are served with consistent data management, documentation and calibration. Systems deployed in Modules A, B and C include customized automatic weather stations, (Doppler) lidars and ceilometers, scintillometers, balloon radio sounding and spectral camera imaging. Systems are street-light-mounted, located on building roof-tops or indoors as well as on mobile platforms (vehicles, drones). Data ingestion processes are automated, delivering moderate data volumes in real-time to central data infrastructure through mobile phone and IOT connectivity. A meta data system helps keep track of the location and configuration of all deployed components and forms the backbone for conversion of instrument records into location-aware, conventions-aligned and quality-assured F.A.I.R. data products. Furthermore, the data management infrastructure provides services (APIs, Apps, IDEs, etc.) for data inspection and computations by scientists and students involved in the campaigns. Select datasets are integrated in near real-time into other global or local data systems such as, e.g., AERONET, the Phenocam Network, ICOS, or PANAME, for multiple uses.

Besides technical aspects and design considerations, we discuss how cooperation and attribution are safeguarded when data are being accessed for immediate academic and citizen data science.

 

How to cite: Zeeman, M., Benjamins, K., Briegel, F., Drouin, M.-A., Feigel, G., Fenner, D., Kotthaus, S., Hilland, R., Meier, F., Morrison, W., Plein, M., Metzger, S., Reddy, K., Chrysoulakis, N., Grimmond, S., and Christen, A.: A modular data management approach for environmental observation campaigns in multiple cities, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15484, https://doi.org/10.5194/egusphere-egu23-15484, 2023.

X5.114
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EGU23-6240
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AS3.15
Christoph Beck, Verena Fricke, Andreas Philipp, Carlos Pusch, Florian Reich, and Jonathan Simon

A network of low-cost air quality sensors for monitoring NO2- and O3-concentrations has been installed at an urban high traffic site in the city of Munich (Bavaria, South Germany). NO2-measurements conducted over a period of several seasons are used to analyse the effectiveness of novel air filtering systems that have been installed alongside the street section.

Estimates of hourly mean NO2-concentrations at the network sites are determined by applying several calibration methods (linear and non-linear models) that were fitted, validated and compared based on data gathered during two periods where all sensors were co-located at an on site official reference station.

Resulting NO2-estimates at the low-cost network sites are further analysed with respect to spatiotemporal variations in NO2-concentrations. Thereby the effects of local scale variations in the urban environment, varying traffic loads, changing synoptic weather types and different operating conditions of the air filtering systems are considered.

The contribution presents and discusses different approaches for the calibration of the low-cost NO2 measurements and shows preliminary results of the analyses of spatiotemporal NO2 variations in a high traffic urban environment under special consideration of the effectiveness of novel air filtering systems.

How to cite: Beck, C., Fricke, V., Philipp, A., Pusch, C., Reich, F., and Simon, J.: Low-cost NO2 measurements at an urban high traffic site, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6240, https://doi.org/10.5194/egusphere-egu23-6240, 2023.

X5.115
|
EGU23-12404
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AS3.15
|
ECS
Shruti Tripathi, Abhishek Chakraborty, and Debayan Mandal

Particulate matter (PM) is collected in the urban coastal city of Mumbai. The PM2.5 concentrations averaged from 200 μg m−3 to 90 μg m−3 throughout the year during sampling. These values were substantially higher than national ambient air quality standards (60 μg m−3). The Organic carbon (OC) concentration in PM ranged from 6 μg m−3 to 17 μg m−3 from summer to winter, whereas elemental carbon (EC) has varied from 1.2 μg m−3 to 4.8 μg m−3. The OC/EC ratio was lower in winter than summer because of high EC emissions during winter and low photochemical activities. The summer samples have a high percentage of low volatile OC fraction (53%) than the winter samples. The calculated secondary organic carbon (SOC) also varies seasonally. The fraction of SOC in overall OC was highest in summer (65.7%), whereas the concentration of SOC was higher in winter, i.e., 9 μg m−3. High temperatures and strong solar radiation favor SOC formation during the summer, resulting in a high percentage of low volatile OC in total OC. The overall chemical composition of PM2.5 reveals that almost 68% of the total mass was elemental composition (SO42−, NO3, NH4+, Na+, Ca2+and K+) in winter and 16% in summer. Seasalt contribution to PM2.5 was 32% and 5% in winter and summer, respectively. Chlorine to sodium molar ratios was below the seawater ratio line in both seasons (0.69 winters and 0.30 summers), but the drop in the summer season might indicate more loss of chlorine. In summer, aerosols are slightly less acidic than in winter and pH value ranged from 3.2 to 7.1. Therefore, we can say that Mumbai suffers from air pollution problems during the winter, despite being a coastal city. These high concentrations of PM have an adverse effect on the health of the urban population.

How to cite: Tripathi, S., Chakraborty, A., and Mandal, D.: Variations in particulate matter chemical composition in the urban coastal city of India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12404, https://doi.org/10.5194/egusphere-egu23-12404, 2023.

X5.116
|
EGU23-10675
|
AS3.15
Violeta Mugica, Jesús Figueroa, Brenda Valle, Tamara Alvarez, Mirella Gutiérrez, and Miguel Torres

Carbonaceous species such as nitro-polycyclic aromatic hydrocarbons (NPAHs) are toxic ubiquitous pollutants contained in the organic fraction of airborne particles, since several of them have mutagenic and carcinogenic properties. Black carbon has been recognized as a short live climatic pollutant which must be controlled in order to mitigate climatic change. Morelos is a little state of Mexico located at the South of the Metropolitan Area of Mexico City which has grown in the last years, but only few studies related with atmospheric pollution have been performed, then, with the aim to have better information related with carbonaceous compounds contained in the PM2.5 of the two main cities of Morelos, a monitoring campaign was carried out in Cuernavaca City, from 2016 to 2018, whereas in the Cuautla city the campaign was performed from 2017 to 2018. PM2.5 were collected with HighVol Tish equipment every six days. Elemental and organic carbon were analyzed with a Sunset Lab and toxic NPAHs were extracted with dichloromethane and sonication and further analyzed by gas chromatography–mass spectrometry (GC-MS). Median annual PM2.5 concentrations were 22.5 ± 7.2 mg m-3 and 19.6 ± 6.1 mg m-3, for Cuautla and Cuernavaca, respectively. Black carbon concentrations were higher in Cuautla than in Cuernavaca with 1.9 ± 0.5 mg m-3, and 1.3 ± 0.4 mg m-3 respectively, since Cuautla is a rural zone with frequent biomass burning The highest NHAPs concentrations were found in Cuautla with medians of 280.74 pg m-3, 90.67 pg/m-3 and 156.61 pg m-3, for the warm dry season (March-June), the rainy season (July-October) and the cold dry season (November-February) respectively. In Cuernavaca, the NHAPs presented lower concentrations in the three seasons with 116.41 pg m-3, 63.82 pg/m-3 and 128.99 pg m-3, respectively. 1-nitronaphtalene, 2-nitrophenentrene and 2-nitroanthracene were the most abundant compounds in both sites. Although PM2.5 Mexican Standard was not exceeded, the high concentrations of black carbon and NPAHs are of concern since black carbon is a climatic pollutant and some of the NHAPs compounds are carcinogenic.

How to cite: Mugica, V., Figueroa, J., Valle, B., Alvarez, T., Gutiérrez, M., and Torres, M.: Temporal variations of black carbon and nitro polycyclic aromatic hydrocarbons in Morelos, México, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10675, https://doi.org/10.5194/egusphere-egu23-10675, 2023.

X5.117
|
EGU23-11991
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AS3.15
|
ECS
|
Highlight
|
|
Miriam Chacón-Mateos, Ulrich Vogt, Bernd Laquai, Héctor García-Salamero, Christian Witt, Uta Liebers, and Frank Heimann

The increase in evidence on the adverse health effects of air pollution has been possible thanks to the advances in technology for air pollution monitoring and personal exposure. In this context, air quality sensors present a huge potential for enhancing long-term personal exposure prediction. In order to prove the potential of air sensors for health research, a pilot study with patients suffering from chronic obstructive pulmonary diseases or Asthma was carried out in Stuttgart (Germany) in cooperation with the University Hospital Charité in Berlin, and an outpatient pulmonary practice in Stuttgart.

Prior to the pilot study, we first tested several sensor models for PM and NO2 in the laboratory as well as in the field. The sensors with the best performance were selected to build two different sensor boxes for indoor and outdoor measurements. Temperature and relative humidity sensors were also included in the boxes. To avoid the overestimation of the PM readings due to hygroscopic growth, a low-cost dryer was designed and evaluated for the PM sensor of the outdoor boxes (Chacón-Mateos et al. 2022).

The measurements inside and outside the houses were carried out over 30 days. Passive sampling of NO2 was done additionally for quality assurance of the NO2 measurements. Participants completed spirometry, a questionnaire assessing respiratory symptoms, and a protocol of activities on a daily basis. The calibration and validation of the sensors were conducted two weeks before the start of the measurements. To perform the quality assurance, the sensor boxes for indoors were collocated in the laboratory, and the sensor boxes for outdoors in the field, together with reference-grade instruments. The PM2.5 concentrations were corrected using univariate linear regression whereas multilinear regression and machine learning algorithms were tested and applied to correct the raw data of the NO2 sensors.

The sensor validations have shown that measuring low concentrations of PM2.5 and NO2 has higher expanded uncertainty, but high concentrations can be measured with expanded uncertainties that fulfill the Data Quality Objectives (DQO) set by the Air Quality Directives for indicative measurements. However, we also found a high unit-to-unit variability which means that model coefficients cannot be transferred from one sensor to another. We also recommend collocating NO2 passive samples close to the sensor boxes to determine whether or not the sensor is measuring within the expected range as the signal of some NO2 sensors drifted unexpectedly during the measurements in the houses of the patients.

In conclusion, air sensors are not yet to be recommended to quantify the effects of low-level air pollution but they are a promising tool to increase the ubiquity of epidemiological studies for low- and middle-income countries where high air pollution is expected. Moreover, it is important to consider that in order to get actionable data with air sensors, a significant amount of time in sensor calibration should be invested.

References:

Chacón-Mateos, M., Laquai, B., Vogt, U., and Stubenrauch, C.: Evaluation of a low-cost dryer for a low-cost optical particle counter, Atmos. Meas. Tech., 15, 7395–7410, https://doi.org/10.5194/amt-15-7395-2022, 2022

How to cite: Chacón-Mateos, M., Vogt, U., Laquai, B., García-Salamero, H., Witt, C., Liebers, U., and Heimann, F.: Evaluation of air quality sensors for environmental epidemiology, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11991, https://doi.org/10.5194/egusphere-egu23-11991, 2023.

Posters virtual: Thu, 27 Apr, 16:15–18:00 | vHall AS

Chairpersons: Ulrike Dusek, Sander Houweling
vAS.7
|
EGU23-372
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AS3.15
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ECS
|
Manuj Sharma and Suresh Jain

Particulate bound Polycyclic Aromatic Hydrocarbons (PAHs) are ubiquitous in the urban atmosphere, posing carcinogenic and mutagenic risk to urban population. The present study analysed the seasonal variation, identification of air pollution sources, and evaluation of carcinogenic risk for different geographical locations in the urban region structure. PM10 and PM2.5 concentrations were monitored at five different locations; Traffic, Commercial, Industrial, Residential, and Background during winter (January 2021) and summer season (April 2021) in the Vijayawada city, Andhra Pradesh, India. The average concentration of PM10 and PM2.5 at traffic (122±29 µg/m3, 70±14 µg/m3), commercial (106±20 µg/m3, 57±10 µg/m3), industrial (154±42 µg/m3, 82±21 µg/m3), residential (92±13 µg/m3, 54±12 µg/m3), and background (98±16 µg/m3, 61±10 µg/m3) during winter season respectively. All monitoring locations exceeds the National Ambient Air Quality Standards (NAAQS) (PM10~100 µg/m3, PM2.5~60 µg/m3). Similarly, in summer, the average concentration of PM10 and PM2.5 was evaluated at traffic (76±21 µg/m3, 38±09 µg/m3), commercial (59±17 µg/m3, 36±08 µg/m3), industrial (86±24 µg/m3, 52±15 µg/m3), residential (50±16 µg/m3, 26±05 µg/m3), and background (56±14 µg/m3, 26±05 µg/m3) respectively. The spatiotemporal variation illustrates the highest average ∑16PAHs concentration was at the industrial region (64.5-24.3 ng/m3), followed by commercial (47.9-15.5 ng/m3), traffic (44.1-33.2 ng/m3), background (43.4-19.6 ng/m3), and residential (35.5-17.0 ng/m3). High concentration in background region compared to residential is attributed with the local activities (coal and wood burning for cooking and heating purposes in slums), national highway, and international airport near the monitoring location. Winter to summer (W/S) ratio of average ∑16PAHs in PM10 ranges from 3.09 to 0.96 depicting high PAHs concentration even in summer especially at the traffic location where uniform vehicular emission can be observed. However, ∑16PAHs W/S ratio in PM2.5 ranges from 2.13 to 1.17.  Coefficient of Divergence (COD) revealed the similarity in PAHs sources in most of the cases for both size fractions. Source apportionment techniques like MDR and PCA-MLR indicated that the contribution from vehicular emission (i.e., gasoline and diesel combustion) was the highest in PAHs concentration, whereas stationary sources (coal combustion and biomass burning) also contributed to significant PAHs emissions in both sizes fractions. The results can be attributed to the heavy usage of coal, wood, briquettes, and other biomass products as fuel requirements in various industries operating inside the city boundaries. Total Benzo(A)Pyrene equivalent (BaPeq.) concentration for PM10 and PM2.5 ranges from (204.8-34.2 ng/m3) and (190.8-46.9 ng/m3) respectively. The Lifetime Lung Cancer Risk (3.01×10-3-1.01×10-4) and (1.39×10-3-1.40×10-4) in winter and summer, respectively, exceeds the acceptable limits i.e., (10-6) stated by the USEPA. High carcinogenic risk required the attention to reduce the toxic pollutants emissions from the vehicular emissions and biomass burning.

Keywords: PM10 and PM2.5, PAHs, Source Apportionment, Urban Air Quality, Lifetime Lung Cancer Risk

 

 

 

How to cite: Sharma, M. and Jain, S.: Atmospheric Particulate Bound Polycyclic Aromatic Hydrocarbons in Urban Region Structure: Spatiotemporal Variation, Source Apportionment, And Human Health Risk Analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-372, https://doi.org/10.5194/egusphere-egu23-372, 2023.

vAS.8
|
EGU23-3614
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AS3.15
Jun Zheng, Shengnan Zhu, Dongsen Yang, and Yan Ma

Atmospheric alkaline gases, including NH3 and amines, have been demonstrated to play crucial roles in atmospheric chemical processes, from enhancing atmospheric nucleation to promoting secondary particulate matter formation. It has been suggested that new particle formation can contribute significantly to haze formation in Beijing and other megacities in China. Although NH3 and amines have been ubiquitously detected in the atmosphere, little is known about the specific source profiles and the corresponding source contributions. It is well accepted that agriculture-related emissions dominate the global NH3 budget in the atmosphere. However, several recent field studies demonstrated that non-agricultural emissions are the primary NH3 sources in many urban areas in China. Therefore, atmospheric models based on emission inventories concentrated on agricultural emissions may not realistically simulate the atmospheric environment, particularly in the populated megacities of China. Recently, NH3, amines, amides, and imines emission characteristics of motor vehicles have been determined explicitly through in situ roadside measurements. However, the emission features from many other anthropogenic activities are still unknown. In this study, based on constrained SoFi-PMF analysis, we have investigated the specific impacts of motor vehicle emissions on NH3 and other alkaline gases in urban Beijing. It was found that motor vehicles can contribute a predominant portion of amines in the urban environment, particularly during daytime. Hence, reducing on-road vehicular emissions can decrease primary emissions of criteria air pollutants (such as NOx, SO2, and PM2.5) and suppress secondary aerosol formation. Although the PMF-based source apportionment analysis may be subjective to individual bias, it provides a valuable opportunity to explore other non-vehicular sources. The septic system in the urban area is recognized as a significant contributor to background NH3 and amines in urban Beijing. Motor vehicle emissions usually show less seasonal variability. Intense demands for central heating, power generation, and biofuel usage in suburban areas may play a significant role in wintertime haze formation. These emission activities, however, may highly depend on environmental conditions, such as temperature and humidity. Further investigations of the underlying releasing mechanisms and emission intensities are critically needed.

How to cite: Zheng, J., Zhu, S., Yang, D., and Ma, Y.: Observation and source apportionment of atmospheric alkaline gases in urban Beijing, China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3614, https://doi.org/10.5194/egusphere-egu23-3614, 2023.

vAS.9
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EGU23-12910
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AS3.15
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ECS
|
Janani Venkatraman Jagatha, Tobias Sauter, and Christoph Schneider

Urban climate research is primarily based on point or location-based measurements of climate and air quality data. Advances in microsensor technologies and low cost due to production facilities, sensors for measuring air quality have spread to a large scale in the last decade. In contrast to reference devices, sensors are simple in design, lightweight, and easier to deploy in larger scales.

United Nations environment programme regards Air pollution to be a major global health concern that causes one in nine deaths worldwide. Although a number of sources and factors have been identified as a cause of air pollution it is difficult to pinpoint a particular source and manage it due to the variability of the pollutants in space, time, and the socio-economic factors involved.

This study aims to answer two questions: the possibility to use mobile measurement systems to identify the major sources that contribute to higher aerosol concentration in time and space and if low-cost particulate matter sensors are suitable for land-use-based modeling using conventional regression analysis and machine learning methods such as random forest and neural networks.

The data used was collected using the OPC-N2 sensor from Alphasense Ltd., as a part of the measurement campaign of the project Urban Climate under Change, Phase 1 and 2 [2016-2023].

How to cite: Venkatraman Jagatha, J., Sauter, T., and Schneider, C.: Suitability of Particulate matter low-cost sensor data for land-use-based modeling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12910, https://doi.org/10.5194/egusphere-egu23-12910, 2023.

vAS.10
|
EGU23-10970
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AS3.15
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ECS
Soroosh Roozitalab, Khosro Ashrafi, and Kiana Yahyazadeh Shourabi

Tehran, the capital and most populous city of Iran, is always listed as one of the most air-polluted cities in the world. Nevertheless, it has not received much attention until recent years. Tehran’s PM2.5 (i.e., particulate matters with diameter smaller than 2.5 µm) annual mean concentration in 2022 was 40 µg/m3 and it experienced less than 10 days with clean air. While high emissions are the main reason of air pollution in Tehran, some studies have suggested that meteorology is also another major driver of its air pollution. Here, we investigate the correlation between PM2.5 and different meteorological parameters such as temperature, wind speed, visibility, relative, humidity, and dew point temperature. In particular, we use Multiple Linear Regression and CCM (Convergent Cross Mapping) statistical methods to analyze the ground measurements data for one year. Our primary results show that, several meteorological parameters have a significant impact on PM2.5 concentrations. The findings of this study helps characterizing the source of air pollution in Tehran.

How to cite: Roozitalab, S., Ashrafi, K., and Yahyazadeh Shourabi, K.: The effect of meteorological parameters on PM2.5 pollutant by CCM method in Tehran megacity, Iran, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10970, https://doi.org/10.5194/egusphere-egu23-10970, 2023.