GI1.3 | Monitoring networks

GI1.3

Ground-based networks for monitoring of atmospheric chemical composition and meteorology improve our understanding of local, regional, and continental scale atmospheric events and long-term trends, and inform decisions critical to air quality, climate change, weather forecasting, and human health. Monitoring networks serve an important role within the research community, providing a backbone of data to support modeling, satellite data product validation, and short-term measurement campaigns. Ongoing collaboration, communication, and promotion of monitoring network developments and data products is necessary in order to fully leverage the bene t from such networks. This session explores how ground-based atmospheric monitoring networks can be utilized to:
- promote cross-network and -discipline engagement
- develop and test new technologies and sensors
- expand quality assurance methods and techniques
- support modelling and satellite data products

Co-organized by AS5/CL5/ESSI4
Convener: Jeffery Riggs | Co-conveners: Misha KrassovskiECSECS, Andrea BaroneECSECS, Raffaele Castaldo
Orals
| Fri, 28 Apr, 10:45–12:30 (CEST)
 
Room -2.91
Posters on site
| Attendance Fri, 28 Apr, 14:00–15:45 (CEST)
 
Hall X4
Posters virtual
| Attendance Fri, 28 Apr, 14:00–15:45 (CEST)
 
vHall ESSI/GI/NP
Orals |
Fri, 10:45
Fri, 14:00
Fri, 14:00

Orals: Fri, 28 Apr | Room -2.91

Chairpersons: Jeffery Riggs, Andrea Barone, Raffaele Castaldo
10:45–10:50
10:50–11:00
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EGU23-7839
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GI1.3
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ECS
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On-site presentation
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Kristen Okorn, Laura Iraci, and Michael Hannigan

Even in the presence of more reliable air quality tools, low-cost sensors have the benefit of recording data on highly localized spatial and temporal scales, allowing for multiple measurements within a single satellite pixel and on pixel boundaries. However, they are less accurate than their regulatory-grade counterparts, requiring regular co-locations with accepted instruments to ensure their validity. Thus, the addition of low-cost sensors to a field campaign – where reference-grade air quality instruments are abundant – not only provides ample opportunities for low-cost sensor co-location and calibration, but also allows the low-cost instruments to be used for sub-pixel validation, covering more surface area than the regulatory instruments alone with a network of sensors. During the summer of 2014, our low-cost sensor network was deployed during the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ) campaign conducted to sample the composition of air at and above ground level in northeastern Colorado, USA. The low-cost sensor platform included a suite of gas-phase sensors, notably NO2 and two generalized volatile organic compound (VOC) sensors, which were leveraged together to quantify speciated hydrocarbons such as formaldehyde. These key pollutants were chosen for their impacts on human health and climate change, as well as their inclusion on the TEMPO satellite launching this year. Airborne campaign measurements included slant column optical observations of formaldehyde (HCHO), nitrogen dioxide (NO2), and ozone (O3). Myriad additional in-situ instruments described chemical composition up to approximately 5 km above surface level. Ground-based instrumentation included both stationary and mobile regulatory-grade instruments, which were used for sensor calibration. Machine learning techniques such as artificial neural networks (ANNs) were used to match the low-cost signals to that of the reference-grade instruments. Here, we compare calibrated low-cost sensor data collected at ground level in a variety of locations along Colorado’s Front Range to various data sources from the FRAPPÉ campaign to better understand how well airborne and regulatory ground-based measurements can be extrapolated to other locations. Further, as the slant column measurements act as satellite simulators, we explore how low-cost instruments can be used for satellite validation purposes. Comparisons among these different data types also have important implications in data fusion.

How to cite: Okorn, K., Iraci, L., and Hannigan, M.: Comparing Low-Cost Sensors with Ground-Based and Airborne In-Situ and Column Observations of NO2 and HCHO during the FRAPPE Field Campaign in Colorado, USA, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7839, https://doi.org/10.5194/egusphere-egu23-7839, 2023.

11:00–11:10
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EGU23-14459
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GI1.3
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ECS
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On-site presentation
Francesco Barbano, Erika Brattich, Carlo Cintolesi, Juri Iurato, Vincenzo Mazzarella, Massimo Milelli, Abdul Ghafoor Nizamani, Maryam Sarfraz, Antonio Parodi, and Silvana Di Sabatino

With the increasing attempt to empower citizens and civil society in promoting virtuous behaviours and relevant climate actions, novel user-friendly and low-cost tools and sensors are nowadays being developed and distributed on the market. Most of these sensors are typically easy to install with a ready-to-use system, while measured data are automatically uploaded on a mobile application or a web dashboard which also guarantees secure and open access to measurements gathered by other users. However, the quality of the datum and the calibration of these sensors are often ensured against research-grade instrumentations only in the laboratory and rarely in real-world measurement. The discrepancies arising between these low-cost sensors and research-grade instrumentations are such that the first might be impossible to use if a validation (and re-calibration if needed) under environmental conditions is not performed. Here we propose a validation procedure applied to the MeteoTracker, a recently developed portable sensor to monitor atmospheric quantities on the move. The ultimate scope is to develop and implement a general procedure to test and validate the quality of the MeteoTracker data to compile user guidelines tailored for on-the-move sensors. The result will evaluate the feasibility of MeteoTracker (and potentially other on-the-move sensors) to integrate the existing monitoring networks on the territory, improve the atmospheric data local coverage and support the informed decision by the authorities. The procedure will include multi-sensor testing of all the sensor functionalities, validation of all data simultaneously acquired by several sensors under similar conditions, methods and applications of comparisons with research-grade instruments. The first usage of the MeteoTracker will be also presented for different geographical contexts where the sensors will be used for citizen science activities and develop a monitoring network of selected Essential Variables within the HORIZON-EU project I-CHANGE (Individual Change of HAbits Needed for Green European transition).

How to cite: Barbano, F., Brattich, E., Cintolesi, C., Iurato, J., Mazzarella, V., Milelli, M., Nizamani, A. G., Sarfraz, M., Parodi, A., and Di Sabatino, S.: Developing and testing a validation procedure to successfully use on-the-move sensors in urban environments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14459, https://doi.org/10.5194/egusphere-egu23-14459, 2023.

11:10–11:20
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EGU23-8960
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GI1.3
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ECS
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Highlight
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On-site presentation
The unequal global distribution of weather forecast accuracy and the value of ground-based observations
(withdrawn)
Manuel Linsenmeier and Jeffrey G. Shrader
11:20–11:30
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EGU23-16779
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GI1.3
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Highlight
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On-site presentation
Alexander Haefele, Maxime Hervo, Philipp Bättig, Daniel Leuenberger, Claire Merker, Daniel Regenass, Pirmin Kaufmann, and Marco Arpagaus

EMER-Met is the new meteorological forecasting system for the protection of the population in Switzerland. It provides the meteorological basis for coping with all types of emergencies, especially in case of nuclear and chemical accidents. EMER-Met consists of a dedicated upper air measurement network and a high-resolution numerical weather prediction model. The measurement network is composed of state-of-the-art remote sensing instruments to measure accurate wind and temperature profiles in the boundary layer. At three sites, a radar wind profiler PCL1300, a Doppler lidar Windcube-200s and a microwave radiometer Hatpro-G5 are installed. The data from the measurement network are assimilated into the operational 1-km ensemble numerical weather prediction (NWP) system. In the case of the microwave radiometers, we assimilate the brightness temperatures using an adapted version of the RTTOV observation operator. To ensure best impact on the NWP results, the data quality of the measurements is of high importance and is monitored closely on a daily and monthly basis against radiosondes and the NWP model itself. EMER-Met is operational since 2022 and to our best knowledge, it is the first time that the brightness temperatures measured by surface-based microwave radiometers are assimilated operationally. This presentation will focus on the upper air network performance and its impact on NWP. 

How to cite: Haefele, A., Hervo, M., Bättig, P., Leuenberger, D., Merker, C., Regenass, D., Kaufmann, P., and Arpagaus, M.: An integrated meteorological forecasting system for emergency response, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16779, https://doi.org/10.5194/egusphere-egu23-16779, 2023.

11:30–11:40
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EGU23-11385
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GI1.3
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ECS
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On-site presentation
Rebecca Biagi, Martina Ferrari, Franco Tassi, and Stefania Venturi

Monitoring networks, able to effectively provide high-frequency geochemical data for characterizing the geochemical behavior of the main greenhouse gases (i.e., CO2 and CH4) and pollutants (e.g., heavy metals) are crucial tools for the assessment of air quality and its role in climate changes. However, the provision of measurement stations dedicated to monitor gas species and particulate in polluted areas is complicated by the high cost of their set-up and maintenance. In the last decade, traditional instruments have tentatively been coupled with low-cost sensors for improving spatial coverage and temporal resolution of air quality surveys. The main concerns of this new approach regard the in-field accuracy of the low-cost sensors, being significantly dependent on: (i) cross-sensitivities to other atmospheric pollutants, (ii) environmental parameters (e.g., relative humidity and temperature), and (iii) detector signal degradation over time.

This study presents the results of a geochemical survey carried out in the Greve River Basin (Chianti territory, Central Italy) from May to September 2022 by adopting two measuring strategies: (i) deployment of a mobile station, along predefined transepts within the Greve valley, equipped with a Picarro G2201-i analyzer to measure CO2 and CH4 concentrations and δ13C-CO2 and δ13C-CH4 values (‰ vs. V-PDB) by Wavelength-Scanned Cavity Ring-Down Spectroscopy (WS-CRDS); (ii) continuous monitoring, at five fixed sites positioned at different altitudes, of CO2 and CH4 concentrations through prototyped low-cost stations, coupled with atmospheric deposition and rain samplers to collect particulate samples for chemical lab analysis. The low-cost monitoring stations housed (i) a non-dispersive infrared (NDIR) sensor for CO2 concentrations, (ii) a solid-state metal oxide sensor (MOS) for CH4 concentrations, (iii) a laser light scattering sensor (LSPs) for PM2.5 and PM10 concentrations, and (iv) a sensor for temperature and relative humidity in the air. The CO2 and CH4 sensors have been calibrated in-field based on parallel measurements with the Picarro G2201-i and elaborating the calibration data with the Random Forest machine learning-based algorithm.

The measurements carried out along the transepts showed that the downstream areas next to the metropolitan city of Florence were affected by the highest concentrations of CO2 and CH4, marked by isotopic signatures revealing a clear anthropogenic origin, mainly ascribed to vehicular traffic. The distribution of these carbon species reflected the evolution of the atmospheric boundary layer, displaying higher concentrations during the early morning, when gas accumulation occurred due to stable atmospheric conditions, and lower concentrations during daytime when the heating of the surface favored the dilution of air pollutants due to the establishment of convective turbulence. These observations were confirmed by the network of low-cost stations, which allowed to simultaneously monitor the distribution of the atmospheric pollutants at different altitudes in the valley. The distribution of particulate was consistent with that of the gaseous species, and the main sources were clearly distinguished based on the chemical composition of the atmospheric deposition in the collection sites. The promising results from the present study could result in an affordable approach to effectively improve air quality monitoring strategies and support data-driven policy actions to reduce carbon emissions.

How to cite: Biagi, R., Ferrari, M., Tassi, F., and Venturi, S.: Multi-instrumental approach for air quality monitoring: characterization and distribution of greenhouse gases and atmospheric metal deposition in the Greve River Basin (Chianti territory, Central Italy)., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11385, https://doi.org/10.5194/egusphere-egu23-11385, 2023.

11:40–11:50
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EGU23-7462
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GI1.3
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ECS
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On-site presentation
Daniel Bertocci, Burcu Celikkol, Shaojie Zhuang, and Jasper Fabius

Emissions of nitrogen compounds, including nitrogen dioxide (NO2) and ammonia (NH3), have significant impacts on air quality and the environment. To effectively monitor the spatial and temporal variability of these emissions and the efficacy of emission mitigation measures, OnePlanet Research Center is developing a low-cost sensor system to monitor outdoor NO2 and NH3concentrations. This sensor system is designed to be deployable in fine-grained networks to accurately capture the dispersion from an emitting source. The deployment of multitudes of such sensor systems will result in large volumes of data. For this purpose, we developed a data infrastructure using the OGC SensorThings API and TimescaleDB, a time-series database extending PostgreSQL. This infrastructure allows for the efficient storage, management, and analysis of large volumes of spatiotemporal data from various sources, such as air quality monitoring networks, meteorological data, and agricultural practices. We demonstrate the potential of this infrastructure by using it in citizen science project COMPAIR, combining data from various sensors to gain insights on the air quality impact of urban circulation policies. The resulting data platform will facilitate the development of decision support tools and the implementation of targeted emission reduction strategies.

How to cite: Bertocci, D., Celikkol, B., Zhuang, S., and Fabius, J.: Data infrastructure for nitrogen compound emissions monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7462, https://doi.org/10.5194/egusphere-egu23-7462, 2023.

11:50–12:00
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EGU23-17535
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GI1.3
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ECS
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On-site presentation
Therese Salameh, Emmanuel Tison, Evdokia Stratigou, Sébastien Dusanter, Vincent Gaudion, Marina Jamar, Ralf Tillmann, Franz Rohrer, Benjamin Winter, Teresa Verea, Amalia Muñoz, Fanny Bachelier, Véronique Daele, and Audrey Grandjean

Formaldehyde is an important hazardous air pollutant, classified as carcinogenic to humans by the International Agency for Research on Cancer (IARC). It is emitted directly by many anthropogenic and natural sources, and formed as a secondary product from volatile organic compounds (VOCs) photo-oxidation. Formaldehyde is, as well, a significant source of radicals in the atmosphere resulting in ozone and secondary organic aerosols formation. Routine measurements of formaldehyde in regulatory networks within Europe (EMEP) and USA (EPA Compendium Method TO 11A) rely on sampling with DNPH (2,4-Dinitrophenylhydrazine)- impregnated silica cartridges, followed by analysis with HPLC (High-performance liquid chromatography).

In the framework of the EURAMET-EMPIR project « MetClimVOC » (Metrology for climate relevant volatile organic compounds: http://www.metclimvoc.eu/), the European ACTRIS (Aerosol, Cloud and Trace Gases Research InfraStructure: https://www.actris.eu/) Topical Centre for Reactive Trace Gases in-situ Measurements (CiGas), IMT Nord Europe unit – France, organized a side-by-side intercomparison campaign in Douai-France, dedicated to formaldehyde measurement in a low amount fraction range of 2 - 20 nmol/mol, from 30 May to 8 June 2022. The objectives of the intercomparison are to evaluate the instruments metrological performance under the same challenging conditions, and to build best practices and instrumental knowledge.

Here, we present the results from the intercomparison, where ten instruments belonging to seven different techniques were challenged with the same formaldehyde gas mixture generated either from a cylinder or from a permeation system, in different conditions (amount fractions, relative humidity, interference, blanks, etc.), flowing through a high-flow (up to 50 L/min) Silcosteel-coated manifold. The advantages/drawbacks of the techniques will be discussed.

How to cite: Salameh, T., Tison, E., Stratigou, E., Dusanter, S., Gaudion, V., Jamar, M., Tillmann, R., Rohrer, F., Winter, B., Verea, T., Muñoz, A., Bachelier, F., Daele, V., and Grandjean, A.: ACTRIS - CiGas side-by-side interlaboratory comparison of new and classical techniques for formaldehyde measurement in the nmol/mol range, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17535, https://doi.org/10.5194/egusphere-egu23-17535, 2023.

12:00–12:10
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EGU23-8841
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GI1.3
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On-site presentation
Colin Lee, Paul Makar, and Joana Soares

Air quality monitoring networks provide invaluable data for studying human health, environmental impacts, and the effects of policy changes,  but obtaining high quality data can be costly, with each site in a monitoring network requiring instrumentation and skilled operator time. It is therefore important to ensure that each monitor in the network is providing unique data to maximize the value of the entire network.  Differences in measurement approaches for the same chemical between monitoring stations may also result in discontinuities in the network data.  Both of these factors suggest the need for objective, machine-learning methodologies for monitoring network data analysis.   

Air quality models are another valuable tool to augment monitoring networks.  The models simulate air quality over a large region where monitoring may be sparse. The gridded output from air-quality models thus contain inherent information on the similarity of sources, chemical oxidation pathways and removal processes for chemicals of interest, provided appropriate tools are available to identify these similarities on a gridded basis.  The output from these models can be immense, again requiring the use of special, highly optimized tools for post-processing analysis.

Spatiotemporal clustering is a family of techniques that have seen widespread use in air quality, whereby time-series taken at different locations are grouped based on the level of similarity between time-series data within the dataset.   Hierarchical clustering is one such algorithm, which has the advantage of not requiring an a priori assumption about how many clusters there might be (unlike K-means).  However, traditional approaches for hierarchical clustering become computationally expensive as the number of time-series increases in size, resulting in prohibitive computational costs  when the total number of time-series to be compared rises above 30,000, even on a supercomputer.  Similarly, the comparison and clustering of large numbers of discrete data (such as multiple mass spectrometer data sampled at high time resolution from a moving laboratory platform) becomes computationally prohibitive using conventional methods. 

In this study we present a high-performance hierarchical clustering algorithm which is able to run in parallel over many nodes on massively parallel computer systems, thus allowing for efficient clustering for very large monitoring network and model output datasets.   The new high-performance program is able to cluster 290,000 annual time series (from either monitoring network data or gridded model output) in 13 hours on 800 nodes. We present here some example results showing how the algorithm can be used to analyse very large datasets, providing new insights into “airsheds” depicting regions of similar chemical origin and history, different spatial regimes for nitrogen, sulphur, and base cation deposition, .  These analyses show how different processes control each species at different potential monitoring site locations, via cluster-generated airshed maps for each species. The efficiency and flexibility of the algorithm allows for extremely large datasets to be analysed in hours of wall-clock time instead of weeks or months. The new algorithm is being used as the numerical engine for a new tool for the analysis of EU monitoring network data. 

How to cite: Lee, C., Makar, P., and Soares, J.: Spatio-temporal clustering on a high-performance computing platform for high-resolution monitoring network analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8841, https://doi.org/10.5194/egusphere-egu23-8841, 2023.

12:10–12:20
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EGU23-9356
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GI1.3
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On-site presentation
Roland Schrödner, Honey Alas, and Jens Voigtländer

22 cost-efficient (aka ‘low-cost’) commercially available particulate matter (PM) measurement devices were installed in a diverse urban area in Leipzig, Germany. The instruments measure mostly PM2.5, some additionally PM10, and are equipped with methods for quality assurance such as conditioning to a defined temperature and regular internal calibration. In order to investigate the spread between the instruments and to enable a pre-campaign calibration, all instruments were setup in the laboratory and the outside air and compared against the same reference measurements.

Since July 2022, the measurement network was installed. It covers roughly 2x2 km2 and holds different urban features like residential and commercial buildings, important main roads, city parks, and small open building gaps. Within the network there is an official air quality monitoring station located directly at a main road. In addition, at two further official monitoring stations as well as at observation stations of the Leibniz Institute for Tropospheric Research instruments were installed to study the long-term performance, dependence on meteorological conditions and comparison to reference measurements. The measurements will take place until end of 2023.

The cost-efficient instruments perform generally quite well after the calibration. In particularly for higher PM loads > 10 µg m-3 the agreement against references is mostly satisfying. However, under very high relative humidity and cold temperatures, some instruments lacked to condition the air sufficiently. Despite these difficulties, the chosen instruments have the potential for application in monitoring of air quality limit values, i.e. the answer the question how often are certain limits exceeded.

Furthermore, differences between different local features in the observation area could be observed in e.g., the diurnal cycle but also peak and mean concentrations.

This work is co-financed with tax funds on the basis of the budget passed by the Saxon State Parliament (funding number 100582357).

How to cite: Schrödner, R., Alas, H., and Voigtländer, J.: Application of cost-efficient particulate matter measurement devices in an urban network and comparison to state-of-the-art air quality monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9356, https://doi.org/10.5194/egusphere-egu23-9356, 2023.

12:20–12:30
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EGU23-14442
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GI1.3
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Highlight
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On-site presentation
Sergi Moreno

The Global Atmosphere Watch (GAW) Programme was established in 1989 in recognition of the need for improved scientific understanding of the increasing influence of human activities on atmospheric composition and subsequent societal impacts. It is implemented as an activity of the World Meteorological Organization, a specialized agency of the United Nations system, and is funded by the organization member countries.

As an international programme, GAW supports a broad spectrum of applications from atmospheric composition-related services to contribution to environmental policy. The examples of the later include provision of a comprehensive set of high quality and long-term globally harmonized observations and analysis of atmospheric composition for the United Nations Framework Convention on Climate Change (UNFCCC), the Montreal Protocol on Substances that Deplete the Ozone Layer and follow-up amendments, and the Convention on Long-Range Transboundary Air Pollution (CLRTAP).

The programme includes six focal areas: Greenhouse Gases, Ozone, Aerosols, Reactive Gases, Total Atmospheric Deposition and SolarUltraviolet Radiation.

The surface-based observational network of the programme includes Global (31 stations) and Regional (about 400 stations) stations where observations of various GAW parameters occur. These stations are complemented by regular ship cruises and various contributing networks. All observations are linked to common reference standards and the observational data are made available at seven designated World Data Centres (WDC).

Surface-based observations are complemented by airborne and space-based observations that help to characterize the upper troposphere and lower stratosphere, with regards to ozone, solar radiation, aerosols, and certain trace gases.

Requirements to become a GAW station are detailed in the GAW Implementation Plan 2016-2023 (WMO, 2017). A new IP is in preparation, the four strategic objectives will be presented.

  • The GAW Quality Management comprises: Data Quality Objectives, Measurement Guidelines, Standard Operating Procedures and Data Quality Indicators. Throughout the programme the common quality assurance principles apply, that include requirements for the long-term sustainability of the observations, use of one network standard for each variable and implementation of the measurement practices that satisfy the set data quality objectives. GAW implements open data policy and requires observational data be made available in the dedicated data centers operated by WMO Member countries.

The programme relies on different types of central facilities: Central Calibration Laboratories, Quality Assurance/Science Activity Centres, World and Regional Calibration Centres, which are also directly supported and implemented by the individual Member countries for the global services.

Majority of the recommendations regarding measurement and quality assurance procedures are developed by the expert and advisory groups within the programme, often those rely on the expertise withing the contributing networks and collaborating organizations, like the Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS) or the Integrated Carbon Observation System (ICOS).

One of the GAW priorities is to expand and strengthen partnerships with contributing networks, through development of statements and strategies to articulate the mutual benefits for the collaborations and stream-line processes of data reporting and exchange of QA standards and metadata. This involves collaboration with national and regional environmental protection agencies and the development of harmonized metadata and data exchange and quality information.

How to cite: Moreno, S.: The WMO Global Atmosphere Watch Programme new implementation plan and strategic objectives, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14442, https://doi.org/10.5194/egusphere-egu23-14442, 2023.

Posters on site: Fri, 28 Apr, 14:00–15:45 | Hall X4

Chairpersons: Misha Krassovski, Andrea Barone, Raffaele Castaldo
X4.166
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EGU23-15609
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GI1.3
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ECS
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Gregor Feigel, Marvin Plein, Matthias Zeeman, Ferdinand Briegel, and Andreas Christen

Climate adaptation and emergency management are major challenges in cities, that benefit from the incorporation of real-time weather, air quality, differential exposure and vulnerability data. We therefore need systems that allow us to map, for example, localised thermal heat stress, heavy precipitation events or air quality spatially resolved across cities at high temporal resolution. Key to the assessment of average conditions and weather extremes in cities are systems that are capable of resolving intra-urban variabilities and microclimates at the level of people, hence in the urban canopy layer at street-level. Placing sensors at street-level, however, is challenging: Sensors need to be small, rugged, safe, and they must measure a number of quantities within limited space. Such systems may ideally require little or no external power, provide remote accessibility, sensor interoperability and real-time data transfer and must be cost-effective for mass deployment. However, these characteristics as well as a wide spectrum of observed variables are not available in current commercial sensor network solutions, hence we designed and implemented a custom partly in-house developed two-tiered sensor system for mounting and installation at 3 m height on city-owned street lights in Freiburg, Germany.

Our partly in-house developed two-tiered sensor network, consisting of fifteen fully self-developed, cost-effective “Tier-I stations” and 35 commercial “Tier-II stations” (LoRAIN, Pessl Instruments GmbH), aims to fill these gaps and to provide a modular, user-friendly WSN with a high spatial density and temporal resolution for research, practical applications and the general public. The Tier-I stations were designed and optimised from the ground up, including the printed circuit board (PCB), for temporally high-resolution WSNs that support wide ranges of sensors and that is expandable. The core of the system is a low-power embedded computer (Raspberry Pi Zero) running a custom multithreaded generic logging and remote control software that locally stores the data and transmits it to a custom vapor-based TCP server via GSM. The software also features system monitoring and error detection functions, as well as remote logging. The setup can easily be expanded on the fly by adding predefined sensors to a configuration file. For better modularity, each station registers itself on the server and will be automatically integrated in all further processes and vice versa. Custom frontends as well as bidirectional communication and task distribution protocols enable remote access and across node interaction, resulting in a more easy-to-maintain system. 

In addition to air temperature, humidity and precipitation measured by the Tier II stations, the Tier-I station feature a ClimaVUE 50 all-in-one weather sensor and a BlackGlobe (Campbell Scientific, Inc.) that provides data on wind, radiation, pressure, lightning, solar radiation and black globe temperatures. That allows for calculation of thermal comfort indices in real-time. A webpage and the self-developed “uniWeather” (iOS-App, API) offers near-realtime data access and data interpretation for stakeholders and public outreach.

How to cite: Feigel, G., Plein, M., Zeeman, M., Briegel, F., and Christen, A.: A compact and customisable street-level sensor system for real-time weather monitoring and outreach in Freiburg, Germany, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15609, https://doi.org/10.5194/egusphere-egu23-15609, 2023.

X4.167
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EGU23-345
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GI1.3
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ECS
sunaina sunaina

The deposition of heavy metals on water bodies and soil has adverse consequences on
human health. The elevated Coal-based energy production and increased industrial emissions
have also prompted us to study about heavy metals reactive nitrogen species in the
atmosphere. In the present work, the samples of rain water were collected from a residential
site in south-west Delhi. The samples were analyzed for selected heavy metals by using ICP-
OES. The heavy metals analysis involved voltammetry method using 797 VA Computrace
(Metrohm, Switzerland) instrument. The analysis of Total Nitrogen (TN) and dissolved
organic carbon (DOC) was carried out by using chemiluminescence based TN/TOC analyzer
(Shimadzu model TOC-LCPH E200 ROHS). The mean values of Cu, Mn, Zn, Al, As and Hg
were calculated as 34.5 mg/l, 19.5 mg/l, 52.7 mg/l, 392.3 mg/l, 9.8 mg/l and 1.6 mg/l
respectively. The mean values for TN and DOC were 12.7mg/l and 2.8 mg/l respectively. The
detailed results will be discussed in the EGU General Assembly Meeting.

Keywords: Total Nitrogen, wet deposition, ICP-OES, voltammetry, agricultural area.

How to cite: sunaina, S.: Wet deposition of heavy metals, reactive nitrogen species and dissolved organic carbonat a residential site in Delhi region, India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-345, https://doi.org/10.5194/egusphere-egu23-345, 2023.

X4.168
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EGU23-1075
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GI1.3
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ECS
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Nicole Cowell, Clarissa Baldo, William Bloss, and Lee Chapman

Birmingham is a city within the West Midlands region of the United Kingdom. In June 2021, coinciding with the introduction of the Clean Air Zone by Birmingham City Council (BCC), multiple low-cost IoT sensor networks for air pollution were deployed across the city by both the University of Birmingham and BCC. Low-cost sensor networks are growing in popularity due to their lower costs compared to regulatory instruments (£10’s-£1000’s per unit compared to £10,000+ per unit) and the reduced need for specialised staff allow for deployments at greater spatial scales (1-3).  Although such low-cost sensing is often associated with uncertainty, the measurement of PM2.5 optical particle counters have been generally shown to perform well, giving indicative insight into concentrations following calibrations and corrections for external influence such as humidity (4-7). 

One common problem with sensor networks is they tend to be isolated and unopen deployments, deployed and maintained by an interested party with the focus of their own monitoring goal. To tackle this, Birmingham Urban Observatory was an online platform created and used by researchers at the University of Birmingham to host and share open access meteorological and air pollution data from low-cost sensor deployments. Whilst hosting and displaying data from two of their own deployments of air quality sensors (Zephyrs by Earthsense and AltasensePM: an in-house designed PM sensor), the platform also pulled data from the DEFRA AURN sites and collaborated with local government to pull data from their own low-cost sensor network. The result was a real-time view of environmental data produced from a series of nested arrays of sensors.

This poster presents findings from this combined low-cost network, considering the successes and pitfalls of the low-cost monitoring network alongside insight into regional and local PM2.5 concentrations. Colocations against reference instruments within the network demonstrate good performance of the low-cost sensors after calibration and data validation but the project experienced challenges in deploying the network and sensor reliability. Low-cost sensor data generally gives novel insight into spatial analysis of PM2.5 across the city and this is presented alongside other experiences of deploying and using sensor networks for air quality.

1 Lewis et al., (2016) https://doi.org/10.1039/C5FD00201J

2 Chong and Kumar. (2003) doi: 10.1109/JPROC.2003.814918

3 Snyder et al., (2013) https://doi.org/10.1021/es4022602

4 Magi et al., (2020) https://doi.org/10.1080/02786826.2019.1619915

5 Crilley et al., (2018) https://doi.org/10.5194/amt-11-709-2018

6 Cowell et al., (2022) https://doi.org/10.3389/fenvs.2021.798485

7 Cowell et al., (2022) https://doi.org/10.1039/D2EA00124A

How to cite: Cowell, N., Baldo, C., Bloss, W., and Chapman, L.: What can we learn from nested IoT low-cost sensor networks for air quality?  A case study of PM2.5 in Birmingham UK., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1075, https://doi.org/10.5194/egusphere-egu23-1075, 2023.

X4.169
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EGU23-8631
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GI1.3
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Highlight
Wolfgang Kausch, Stefan Kimeswenger, Stefan Noll, and Roland Holzlöhner

The Atacama Desert in the Chilean Andes region is one of the dryest areas in the world. Due to its unique location with stable subtropical meteorological conditions and high mountains, it is an ideal site for the astronomical telescope facilities of the European Southern Observatory (ESO). The special meteorological conditions are continuously monitored at Cerro Paranal (the location of the Very Large Telescope) by measuring various parameters like temperature, pressure, humidity, precipitable water vapour (PWV), wind speed and direction, and sky radiance and bolometric sky temperature, respectively, the latter being crucial for astronomical observations in the thermal infrared regime. ESO operates several site monitoring systems for that purpose, e.g. the ESO MeteoMonitor, the Differential Image Motion Monitor (DIMM) and a Low Humidity And Temperature PROfiler (L-HATPRO) microwave radiometer providing detailed water vapour and temperate profiles up to a height of 12km in various directions. 


We have assembled all available data for a period of 4.5 years (2015-07-01 through 2019-12-31) and created a unique data set from it. This period also covers the strong El Niño event at the end of 2015. In this poster we present statistical results on the overall conditions and trends, and compare our measurements of the nocturnal sky brightness with an empirical model as function of the ambient temperature, PWV and zenith distance.

How to cite: Kausch, W., Kimeswenger, S., Noll, S., and Holzlöhner, R.: Ambient conditions and infrared sky brightness in the Chilean Atacama Desert, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8631, https://doi.org/10.5194/egusphere-egu23-8631, 2023.

X4.170
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EGU23-9537
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GI1.3
Daniel Klingenberg, D. Michelle Bailey, David Lang, and Mark Shimamoto

The Global Environmental Measurement and Monitoring (GEMM) Initiative is an international project of Optica and the American Geophysical Union seeking to provide precise and usable environmental data for local impact. The Initiative brings together science, technology, and policy stakeholders to address critical environmental challenges and provide solutions to inform policy decisions on greenhouse gases (GHGs) and air and water quality. GEMM Centers are currently established in Scotland, Canada, New Zealand, and the United States. These Centers represent partnerships with leading institutions that are actively working toward developing or deploying new measurement technology and improved climate models. Additional Centers are under development in India and Australia with plans to expand to Asia and Africa.

In addition to establishing monitoring centers worldwide, GEMM actively engages with other sectors (including industry, standards organizations, and regional or national governments) to support the incorporation or adoption of these evidence-based approaches into decision making processes. For example, Glasgow, Scotland is piloting the GEMM Urban Air Project, deploying a low-cost, real-time, ground-based network of devices that continuously monitors GHGs and air pollutants at a neighborhood scale. The sensor network in Glasgow is increasing the precision of local models that can provide the city with information to assess current policies and support future action. Here we will share the progress and outputs of the GEMM Initiative to date and highlight paths forward to grow the network.

How to cite: Klingenberg, D., Bailey, D. M., Lang, D., and Shimamoto, M.: The Global Environmental Measurement and Monitoring Initiative – An International Network for Local Impact, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9537, https://doi.org/10.5194/egusphere-egu23-9537, 2023.

X4.171
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EGU23-11033
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GI1.3
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ECS
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Irene Pardo Cantos and Emmanuel Mahieu

Since the discovery of the chlorofluorocarbons (CFCs) implication in stratospheric ozone destruction, the Montreal Protocol (1987) has aimed at controlling the production of CFCs and other ozone depleting substances (ODS) in order to protect and then recover the ozone layer. Consequently, temporary substitutes for CFCs have been developed and produced by the industry. First substitute molecules were hydrochlorofluorocarbons (HCFCs), which have smaller ozone depletion potentials (ODP) than CFCs since their atmospheric lifetimes are shorter. Nevertheless, HCFCs still contain chlorine atoms and hence, also deplete the stratospheric ozone, requiring them to be banned in turn. Thus, chlorine-free molecules, i.e. hydrofluorocarbons (HFCs) such as CH2FCF3 (HFC-134a) were introduced to replace both CFCs and HCFCs. Even if HFCs do not contribute to ozone depletion, they are very powerful greenhouse gases since they have great global warming potentials (GWPs). Consequently, the Kigali amendment (2016) to the Montreal Protocol aimed for their phase-out.

The atmospheric concentrations of CFCs have decreased in response to the phase-out and ban of their production by the Montreal Protocol and its subsequent amendments, while the HCFCs burden is now leveling off. In contrast, the atmospheric concentrations of HFCs have increased notably in the last two decades.

We present the first retrievals of HFC-134a from Fourier Transform Infra-Red (FTIR) solar spectra obtained from a remote site of the Network for the Detection of Atmospheric Composition Change (NDACC.org): the Jungfraujoch station (Swiss Alps). We discuss of the applicability of our retrieval strategy to other NDACC sites, for future quasi global monitoring from ground-based observations. We further perform first comparisons with other datasets as ACE-FTS satellite observations.

 

How to cite: Pardo Cantos, I. and Mahieu, E.: First HFC-134a retrievals and analysis of long-term trends from FTIR solar spectra above NDACC network stations: the Jungfraujoch case, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11033, https://doi.org/10.5194/egusphere-egu23-11033, 2023.

X4.172
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EGU23-13997
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GI1.3
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ECS
Dina Rapp, Bo Møllesøe Vinther, Jacob L. Høyer, and Eigil Kaas

As climate change is amplified in the Arctic, it is crucial to have temperature records of high temporal resolution and quality in this area. This will help improve understanding of the involved physical mechanisms, assessment of the past changes and improve predictions for the future temperature development in the Arctic. In this study temperature measurements from the DMI Greenland station network spanning 1784-present day are corrected, gap-filled and homogenized on a daily level. Currently homogenized data is only available on a monthly level, and the more recent data has not been homogenized. The data is currently used for purposes like assessment and predictions of the surface mass balance of the Greenland Ice Sheet, temperature/climate reanalyses, validation of proxy data, etc.  

This study presents a method for improving the calculation of daily average temperatures, from the current practice of averaging the available measurements without considering what time of day they are from and how the measurements are distributed. The method is based on a moving average taking into consideration time of day, time of year and latitude/longitude of the station in question. An estimate of the related uncertainty is also calculated. Following the generation of daily average temperatures, different gap filling methods are tested. The different algorithms tested and compared are: simple gap filling by linear interpolation with other stations, single station temporal linear interpolation and MEM (Maximum Entropy Method). Finally, homogenization on daily level is performed. These steps will in turn also improve the monthly and annual average temperatures for the DMI Greenland station network. 

How to cite: Rapp, D., Møllesøe Vinther, B., L. Høyer, J., and Kaas, E.: Correction, gap filling and homogenization on daily level of the historical DMI station network temperature data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13997, https://doi.org/10.5194/egusphere-egu23-13997, 2023.

X4.173
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EGU23-2847
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GI1.3
Aude Bourin, Pablo Espina-Martin, Anna Font, Sabine Crunaire, and Stéphane Sauvage

Ammonia (NH3) is the major alkaline gas in the atmosphere and the third most abundant N-containing species, after N2 and N2O. It plays an important role in N deposition processes, responsible of several damages on ecosystems, and it is also a precursor of fine particulate matter, known to cause numerous impacts on human health. Despite this, not many countries have implemented long-term monitoring of NH3 in their air quality programs due to the lack of consensus on limit values for ambient levels and a reference method of measuring this gas. In the climate change context, governments and health organizations are increasingly concerned about NH3 and its effects. As a proof, the revision of the EU air quality directives proposes the inclusion of NH3 as a mandatory pollutant for several urban and rural supersites for all member states.

Currently, there are only 12 long term programs worldwide dedicated specifically to measure NH3 or including gas-phase measurements of NH3. The longest NH3 time series come from UK and Africa, where measurements start in mid-1990. The rest of locations have started after 2000 and they have lower temporal coverage, between 5 and 22 years. The objectives pursued by these networks are to follow long term spatio-temporal trends, assess the N deposition on sensitive ecosystems, validate emission and/or chemistry transport models and help to understand the effectiveness of air pollution control and mitigation policies. Most of these networks operate using a combination of low-cost samplers with a high spatial density with few collocated sites with high time resolution instrumentation to help calibrate passive samplers and to better monitor the fine temporal variability of NH3. This combined approach has proven to be successful for most of the proposed objectives.

However, there are several differences that may difficult harmonizing the information at both the technical and scientific level. At the technical level these include type and number of passive samplers per site, calibration protocol, data control and quality analysis, exposure duration and type of high time resolution sampling method. On the scientific level, increased difficulty understanding the operative parameters and scientific results may come from language barriers (non-English reports), availability of the data (whether it is public or not), and gaps on the knowledge of NH3 levels on a spatial scale due to differences in the implementation of monitoring strategies within the same country.

This work aims to review synthetically the world current long-term NH3 networks and provide some insight and recommendations for other countries and supranational programs aiming to establish long term monitoring networks of NH3, based on cost-effective, technical, and operational criteria.

How to cite: Bourin, A., Espina-Martin, P., Font, A., Crunaire, S., and Sauvage, S.: Atmospheric ammonia in-situ long-term monitoring: review worldwide strategies and recommendations for implementation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2847, https://doi.org/10.5194/egusphere-egu23-2847, 2023.

X4.174
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EGU23-15087
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GI1.3
Joana Soares, Christoffer Stoll, Islen Vallejo, Colin Lee, Paul Makar, and Leonor Tarrasón

Air quality monitoring networks provide invaluable data for studying human health, environmental impacts, and the effects of policy changes. In a European legislative context, the data collected constitutes the basis for reporting air quality status and exceedances under the Ambient Air Quality Directives (AAQD) following specific requirements. Consequently, the network's representativity and ability to accurately assess the air pollution situation in European countries become a key issue. The combined use of models and measurements is currently understood as the most robust way to map the status of air pollution in an area, allowing it to quantify both the spatial and temporal distribution of pollution. This spatial-temporal information can be used to evaluate the representativeness of the monitoring network and support air quality monitoring design using hierarchical clustering techniques.

The hierarchical clustering methodology applied in this context can be used as a screening tool to analyse the level of similarity or dissimilarity of the air concentration data (time-series) within a monitoring network. Hierarchical clustering assumes that the data contains a level of (dis)similarity and groups the station records based on the characteristics of the actual data. The advantage of this type of clustering is that it does not require an a priori assumption about how many clusters there might be, but it can become computationally expensive as the number of time-series increases in size. Three dissimilarity metrics are used to establish the level of similarity (or dissimilarity) of the different air quality measurements across the monitoring network: (1) 1-R, where R is the Pearson linear correlation coefficient, (2) the Euclidean distance (EuD), and (3) multiplication of metric (1) and (2). The metric based on correlation assesses dissimilarities associated with the changes in the temporal variations in concentration. The metric based on the EuD assesses dissimilarities based on the magnitude of the concentration over the period analysed. The multiplication of these two metrics (1-R) x EuD assesses time variation and pollution levels correlations, and it has been demonstrated to be the most useful metric for monitoring network optimization.

This study presents the MoNET webtool developed based on the hierarchical clustering methodology. This webtool aims to provide an easy solution for member states to quality control the data reported as a tier-2 level check and evaluate the representativeness of the air quality network reporting under the AAQD. Some examples from the ongoing evaluation of the monitoring site classification carried out as a joint exercise under the Forum for Air Quality Modeling (FAIRMODE) and the National Air Quality Reference Laboratories Network (AQUILA) are available to show the usability of the tool. MoNet should be able to identify outliers, i.e., issues with the data or data series with very specific temporal-magnitude profiles, and to distinguish, e.g., pollution regimes within a country and if it resembles the air quality zones required by the AAQD and set by the member states; stations monitoring high-emitting sources; background regimes vs. a local source driving pollution regime in cities.

How to cite: Soares, J., Stoll, C., Vallejo, I., Lee, C., Makar, P., and Tarrasón, L.: Applications of an advanced clustering tool for EU AQ monitoring network data analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15087, https://doi.org/10.5194/egusphere-egu23-15087, 2023.

Posters virtual: Fri, 28 Apr, 14:00–15:45 | vHall ESSI/GI/NP

Chairpersons: Misha Krassovski, Jeffery Riggs, Andrea Barone
vEGN.6
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EGU23-2984
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GI1.3
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ECS
Matthias Max Frey, Isamu Morino, Hirofumi Ohyama, Akihiro Hori, Darko Dubravica, and Frank Hase

Greenhouse gases (GHGs) play a crucial role regarding global warming. Therefore, precise and accurate observations of anthropogenic GHGs, especially carbon dioxide and methane, are of utmost importance for the estimation of their emission strengths, flux changes and long-term monitoring. Satellite observations are well suited for this task as they provide global coverage. However, like all measurements these need to be validated.

The COllaborative Carbon Column Observing Network (COCCON) performs ground-based observations to retrieve column-averaged dry air mole fractions of GHGs (XGAS) with reference precision. The instrument used by the network is the EM27/SUN, a solar-viewing Fourier Transform infrared (FTIR) spectrometer. COCCON data are of high accuracy as COCCON uses species dependent airmass-independent and airmass-dependent adjustments for tying the XGAS products to TCCCON (Total Carbon Column Observing Network) and thereby to the World Meteorological Organization (WMO) reference scale. Moreover, instrument specific characteristics are measured for each COCCON spectrometer, and taken into account in the data analysis.

Here we first introduce the COCCON network in general and summarize its capabilities for various challenges including satellite and model validation, long-term observation of GHGs, and local and regional GHG source emission strength estimations. By example of the COCCON Tsukuba station we highlight in detail its usefulness for the above-mentioned applications.

How to cite: Frey, M. M., Morino, I., Ohyama, H., Hori, A., Dubravica, D., and Hase, F.: The COllaborative Carbon Column Observing Network COCCON: Showcasing GHG observations at the COCCON Tsukuba site, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2984, https://doi.org/10.5194/egusphere-egu23-2984, 2023.