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.

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.

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.

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.

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.

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.

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.

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 CO₂ (δ¹³C) 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.

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.

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.

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.

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 NO_x-saturated to NO_x-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 NO_x (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.

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 (NO_x, 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 NO_x 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 NO_x 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 NO_x 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.

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.

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.

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 PM_2.5. 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 PM_2.5.

Both locations experience seasonally elevated levels of PM_2.5 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 PM_2.5 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 PM_2.5 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 PM_2.5 variations between sensor locations in each network were found. The results showed that a small town in Ireland can experience PM_2.5 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.

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.

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.

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 (AAE_ff; fossil) and 2 (AAE_wb; 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 AAE_ff and AAE_wb 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 AAE_ff and AAE_wb 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 AAE_ff and AAE_wb. 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.

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 (NO_X) 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 NO_X data was recorded by a nCLD-AL² NO_X 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 (BC^FF) concentration was assumed as the tracer of traffic emission, while biomass burning-related BC (BC^BB) 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 (BC^FF or BC^BB). 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 NO_X 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 NO_X 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.

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.

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 PM_2.5, 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 PM_2.5 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 PM_2.5 respectively. From the model’s explained variability, the most significant predictor for both pollutants was on-road NO₂ and PM_2.5 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 PM_2.5, 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 PM_2.5 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 PM_2.5.

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.

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.

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.

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.

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 (NO_x = 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 NO_x 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 (ΔNO_x/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.

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.

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.

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.

Ammonia (NH₃) emission control has been advocated for its potential to mitigate PM_2.5 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 PM_2.5 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 PM_2.5 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.

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 NO_x 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 NO_x emissions, high NO_x/CO and high NO_x/NO₂ ratios are consistent with known industrial areas; relatively lower NO_x emissions, high NO_x/CO and low NO_x/NO₂ ratio are consistent with known urban aeras. While the time series of both NO_x 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 PM_2.5, 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 NO_x 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 NO_x 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 NO_x and CO integrated with detailed PM_2.5 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.

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, PM_2.5 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.

Transition metal components in PM_2.5 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 PM_2.5 total mass, Fe, Cu, Zn and aerosol acidity in Japan over 2050 was evaluated using a regional meteorology-chemistry model. The primary emissions of PM_2.5, 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 PM_2.5 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 PM_2.5 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 SO_x and NO_x emissions from thermal power plants and decreased aerosol acidity near power plants (approximately pH +0.2), while the passenger car electrification reduced NO_x 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.

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 (PM_2.5) 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 PM_2.5 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.