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Understanding the role of transport and photochemistry is essential to mitigate tropospheric ozone (O3) pollution within a region. In previous studies, the O3 concentration budget has been widely used to determine the contributions of two processes to the variations of O3 concentrations. These studies often conclude that local photochemistry is the main cause of regional O3 pollution; however, they fail to explain why O3 in a targeted region is often primarily derived from O3 and/or its precursors transported from the outside regions, as reported by many studies of O3 source apportionment. Here, we present a method to calculate the hourly contributions of O3-related processes to the variations of not only the mean O3 concentration but also the total O3 mass (the corresponding budgets are noted as the O3 concentration and mass budget, respectively) within the atmospheric boundary layer (ABL) of the concerned region. Based on the modelling results of WRF-CMAQ (Weather Research and Forecasting and Community Multiscale Air Quality), the two O3 budgets were applied to comprehensively understand the effects of transport and photochemistry on the O3 pollution over the Pearl River Delta (PRD) region in China. Quantified results demonstrate the different role of transport and photochemistry when comparing the two O3 budgets: photochemistry drives the rapid increase of O3 concentrations during the day, whereas transport, especially vertical exchange through the ABL top, controls both rapid O3 mass increase in the morning and decrease in the afternoon. The diurnal changes of the transport contributions in the two O3 budgets highlight the influences of the ABL diurnal cycle and regional wind fields on regional O3 pollution. Through high contributions to the O3 mass increase in the morning, transport determines that most O3 in the PRD originates from the global background and emissions outside the region. However, due to the simultaneous rapid increase of ABL volumes, this process only has a relatively limited effect on O3 concentration increase compared to photochemistry, and transport effect on the regional sources of O3 cannot be illustrated by the O3 concentration budget. For future studies targeting O3 and other secondary pollutants with moderately long atmospheric lifetimes (e.g. fine particulate matter and some of its components), insights from both concentration and mass budgets are required to fully understand the role of transport, chemistry and other related processes.

Unmanned aerial vehicles (UAVs) provide a cost-effective way to fill in gaps between surface in situ observations and remotely sensed data from space. In this study, a novel portable CO2 measuring system suitable for operations on board small-sized UAVs has been developed and validated. It is based on a low-cost commercial nondispersive near-infrared (NDIR) CO2 sensor (Senseair AB, Sweden), with a total weight of 1058 g, including batteries. The system performs in situ measurements autonomously, allowing for its integration into various platforms. Accuracy and linearity tests in the lab showed that the precision remains within ± 1 ppm (1σ) at 1 Hz. Corrections due to temperature and pressure changes were applied following environmental chamber experiments. The accuracy of the system in the field was validated against a reference instrument (Picarro, USA) on board a piloted aircraft and it was found to be ± 2 ppm (1σ) at 1 Hz and ± 1 ppm (1σ) at 1 min. Due to its fast response, the system has the capacity to measure CO2 mole fraction changes at 1 Hz, thus allowing the monitoring of CO2 emission plumes and of the characteristics of their spatial and temporal distribution. Details of the measurement system and field implementations are described to support future UAV platform applications for atmospheric trace gas measurements.

The geographical origin and source apportionment of submicron carbonaceous aerosols (organic aerosols, OAs, and black carbon, BC) have been investigated here for the first time, deploying high time-resolution measurements at an urban background site of Nicosia, the capital city of Cyprus, in the eastern Mediterranean. This study covers a half-year period, encompassing both the cold and warm periods with continuous observations of the physical and chemical properties of PM1 performed with an Aerosol Chemical Speciation Monitor (ACSM), an aethalometer, accompanied by a suite of various ancillary offline and online measurements. Carbonaceous aerosols were dominant during both seasons (cold and warm periods), with a contribution of 57 % and 48 % to PM1, respectively, and exhibited recurrent intense nighttime peaks (> 20–30 µg m−3) during the cold period, associated with local domestic heating. The findings of this study show that high concentrations of sulfate (close to 3 µg m−3) were continuously recorded, standing among the highest ever reported for Europe and originating from the Middle East region. Source apportionment of the OA and BC fractions was performed using the positive matrix factorization (PMF) approach and the combination of two models (aethalometer model and multilinear regression), respectively. Our study revealed elevated hydrocarbon-like organic aerosol (HOA) concentrations in Nicosia (among the highest reported for a European urban background site), originating from a mixture of local and regional fossil fuel combustion sources. Although air masses from the Middle East had a low occurrence and were observed mostly during the cold period, they were shown to strongly affect the mean concentrations levels of BC and OA in Nicosia during both seasons. Overall, the present study brings to our attention the need to further characterize primary and secondary carbonaceous aerosols in the Middle East, an undersampled region characterized by continuously increasing fossil fuel (oil and gas) emissions and extreme environmental conditions, which can contribute to photochemical ageing.

In order to face the challenges of climate change, coordinated actions and efforts are required on global, regional and local scales. To succeed, they must be conveyed to informed, conscious and active citizens who understand the challenges and are ready to alter their way of living and thinking toward protecting our planet. Therefore, educating young people is one of the most effective tools for combating climate change. However, the increasing interest in climate change education by stakeholders, policymakers and the research community is not yet broadly incorporated into science education activities. Atmospheric research stations provide valuable information about evolving climate change. Long-term observations of atmospheric parameters provide scientific evidence for the connections between the anthropogenic effect on atmospheric composition and the resulting changes in the planet’s climate. Here we present educational activities at well-established atmospheric observatories part of international observational networks like ACTRIS, LTER, GAW and ICOS. The stations in those networks provide the necessary data and the links between atmospheric composition changes and climate perturbations. At the same time, these stations host at their premises local hubs where teachers and students have the chance to receive hands-on training on using environmental data in education and, ultimately, in school classrooms. The atmospheric research stations support networking, training and community building by stimulating personal engagement and out-of-school education of trainees.

The implementation of the Air Pollution Prevention and Action Plan (2013–2017) in China has led to a significant decrease in anthropogenic emissions. However, at the same time, ozone (O­3), a secondary pollutant formed from nitrogen oxides (NOx) and volatile organic compounds (VOCs) in the presence of sunlight, has increased in the large urban agglomerations of China. To better understand the reasons behind this increase, high-quality anthropogenic emission inventories are needed. In this study, we compared ozone precursor emissions in China from various anthropogenic emission inventories (EIs), including the national EI, Multi-resolution Emission Inventory for China (MEIC), and three global EIs from the Copernicus Atmosphere Monitoring Service (CAMs), Community Emission Data System (CEDS), and Hemispheric Transport of Air Pollution project (HTAP). Differences in emission magnitudes, trends, and spatial distributions were investigated. Global-scale and regional EIs were homogenized by sector and specie to obtain ‘harmonized’ EIs. These harmonized inventories were then used to drive WRF-Chem simulations for the winter and summer of 2017, and the results for each EI were evaluated against observations from the air quality monitoring network developed by the Ministry of Environmental Protection of China. The outcome of this study denotes that using harmonized regional and global EIs can significantly improve the performance of the numerical models when simulating the atmospheric composition of large agglomerations in China.

Ocean biogeochemical (BGC) models are, in addition to measurements, the primary tools for investigating ocean biogeochemistry, marine ecosystem functioning, and the global carbon cycle. These models contain a large number of not precisely known parameters and are highly uncertain regarding those parametrizations. The values of these parameters depend on the physical and biogeochemical context, but in practice values derived from limited field measurements or laboratory experiments are used in the model keeping them constant in space and time. This study aims to estimate spatially and temporally varying parameters in a global ocean BGC model and to assess the effect of those estimated parameters on model fields and dynamics. Utilizing the BGC model Regulated Ecosystem Model 2 (REcoM2), we estimate ten selected BGC parameters with heterogeneity in parameter values both across space and over time using an ensemble data assimilation technique. We assimilate satellite ocean color and BGC-ARGO data using an ensemble Kalman filter provided by the Parallel Data Assimilation Framework (PDAF) to simultaneously estimate the BGC model states and parameters. We assess the improvement in the model predictions with space and time-dependent parameters in reference to the simulation with globally constant parameters against both assimilative and independent data. We quantify the spatiotemporal uncertainties regarding the parameter estimation and the prediction uncertainties induced by those parameters. We study the effect of estimated parameters on the biogeochemical fields and dynamics to get deeper insights into modeling processes and discuss insights from spatially and temporally varying parameters beyond parameter values.

With the drastic actions initiated by the Chinese authorities to improve air quality, the level of several secondary pollutants including near-surface ozone still has been increasing significantly between years 2013 and 2020, most notably in the Northern China Plain. Alleviating ozone pollution requires a quantitative understanding of the different processes that contribute to the photochemical formation and destruction of secondary species. It also requires that the budget of fast-reacting radicals that are directly involved in photochemical oxidation processes be investigated in detail. Here, we used a modified regional chemical transport model (the WRF-Chem) to analyze the influence of different photochemical processes on the entire geographical area covered by China. This analysis provides a quantitative estimate of the different factors that affect the oxidation capacity of the atmosphere in different regions of the country. Besides that, our model simulations will assess the relative importance of different photochemical processes that contribute to the budget of near-surface ozone in different chemical environments and provide some theoretical considerations on which our analysis is based. This study should support to reduction of ozone and other secondary pollutants in China.

The emission of mono- and sesquiterpenes from terrestrial vegetation plays a significant role in ecological interactions and atmospheric chemistry. Previous research has suggested that global emissions of these hydrocarbons are largely driven by responses to abiotic stress and can be simulated using a fixed exponential relationship (β coefficient) between different forest ecosystems and environmental conditions. However, our meta-analysis of published emission data (89 studies/835 β coefficients) reveals that the relationship between mono- and sesquiterpene emissions and temperature is more complex than previously thought. We have found that co-occurring environmental stresses can amplify the temperature sensitivity of monoterpene emissions, which is primarily related to the specific plant functional type (PFT). In contrast, the temperature sensitivity of sesquiterpene emissions decreases over the years. On average, warmer ecosystems appear more sensitive, indicating that plants adjust their emission rates in response to thermal stress. When a PFT-dependent β coefficient for monoterpenes was implemented in a biogenic emission model and coupled with a chemistry-climate model, it was found that atmospheric processes are highly sensitive to this coefficient and subject to amplified variations under rising temperatures.

The atmospheric oxidation capacity (AOC) characterizes the ability of the atmosphere to scavenge air pollutants. However, it is not well understood in China, where anthropogenic emissions have changed dramatically in the past decade. A detailed analysis of different parameters that determine the AOC in China is presented on the basis of numerical simulations performed with the regional chemical-meteorological model WRF-Chem. The model results, with the aerosol effects of extinction and heterogeneous processes taken into account, show that the presence of aerosols leads to a decrease in surface ozone of approximately 8–10 ppbv in NOx-limited rural areas and an increase of 5–10 ppbv in VOC-limited urban areas. The ozone reduction in NOx-sensitive regions is due to the combined effect of nitrogen dioxide and peroxy radical uptake on particles and of the light extinction by aerosols, which affects the photodissociation rates. The ozone increase in VOC-sensitive areas is attributed to the uptake of NO2 by aerosols, which is offset by the reduced ozone formation associated with HO2 uptake and with the aerosol extinction. Our study concludes that more than 90 % of the daytime AOC is due to the reaction of the hydroxyl radical with VOCs and carbon monoxide. In urban areas, during summertime, the main contributions to daytime AOC are the reactions of OH with alkene (30–50 %), oxidized volatile organic compounds (OVOCs) (33–45 %), and carbon monoxide (20–45 %). In rural areas, the largest contribution results from the reaction of OH with alkenes (60 %). Nocturnal AOC is dominantly attributed to the nitrate radical (50–70 %). Our results shed light on the contribution of aerosol-related NOx loss and the high reactivity of alkenes for photochemical pollution. With the reduction of aerosols and anthropogenic ozone precursors, the chemistry of nitrogen and temperature-sensitive VOCs will become increasingly important. More attention needs to be paid to the role of photodegradable OVOCs and nocturnal oxidants in the formation of secondary pollutants.

The Thermal And Near infrared Sensor for carbon Observation – Fourier Transform Spectrometer (TANSO-FTS) on the Japanese Greenhouse gases Observing SATellite (GOSAT) has been returning data since April 2009. The version 9 (v9) Atmospheric Carbon Observations from Space (ACOS) Level 2 Full Physics (L2FP) retrieval algorithm (Kiel et al., 2019) was used to derive estimates of carbon dioxide (CO2) dry air mole fraction (XCO2) from the TANSO-FTS measurements collected over its first 11 years of operation. The bias correction and quality filtering of the L2FP XCO2 product were evaluated using estimates derived from the Total Carbon Column Observing Network (TCCON) as well as values simulated from a suite of global atmospheric inversion systems (models) which do not assimilate satellite-derived CO2. In addition, the v9 ACOS GOSAT XCO2 results were compared with collocated XCO2 estimates derived from NASA's Orbiting Carbon Observatory-2 (OCO-2), using the version 10 (v10) ACOS L2FP algorithm. These tests indicate that the v9 ACOS GOSAT XCO2 product has improved throughput, scatter, and bias, when compared to the earlier v7.3 ACOS GOSAT product, which extended through mid 2016. Of the 37 million soundings collected by GOSAT through June 2020, approximately 20 % were selected for processing by the v9 L2FP algorithm after screening for clouds and other artifacts. After post-processing, 5.4 % of the soundings (2×106 out of 37×106) were assigned a “good” XCO2 quality flag, as compared to 3.9 % in v7.3 (

Worldwide the number of large urban agglomerations is steadily increasing. At a local scale, their emissions lead to air pollution, directly affecting people’s health. On a global scale, their emissions lead to an increase of greenhouse gases, affecting climate. In this context, in 2017 and 2018, the airborne campaigns EMeRGe (Effect of Megacities on the transport and transformation of pollutants on the Regional to Global scales) investigated emissions of European and Asian major population centres (MPCs) to improve the understanding and predictability of pollution outflows. Here, we present two methods to identify and characterise emission outflows probed during EMeRGe. First, we use a set of volatile organic compounds (VOCs) as chemical tracers to characterise air-masses by specific source signals, i.e. benzene from anthropogenic emissions of targeted regions, acetonitrile from biomass burning (BB, primarily during EMeRGe-Asia) and isoprene from fresh biogenic signals (primarily during EMeRGe-Europe). Second, we attribute probed air-masses to source regions and estimate their individual contribution by constructing and applying a simple emission uptake scheme for the boundary layer which combines FLEXTRA back-trajectories and EDGAR carbon monoxide (CO) emission rates (acronyms are provided in Appendix A). During EMeRGe-Europe, we identified anthropogenic emission outflows from Northern Italy, Southern Great Britain, the Belgium-Netherlands-Ruhr area and the Iberian Peninsula. Additionally, our uptake scheme indicates significant long-range transport of emissions from the USA and Canada. During EMeRGe-Asia, the emission outflow is dominated by sources in China and Taiwan, with further emissions (mostly from BB) originating from Southeast Asia and India. Emissions of pre-selected MPC targets are identified in less than 20 % of the sampling time, due to restrictions in flight planning and constraints of the measurement platform itself. Still, EMeRGe combines in a unique way near- and far-field measurements, which show signatures of local and distant sources, transport and conversion fingerprints and complex emission mixtures. Our approach already provides a valuable classification and characterisation of the EMeRGe dataset, e.g. for BB and anthropogenic influence of potential source regions, and paves the way for a more comprehensive analysis and various model studies.

Ice-nucleating particles (INPs) enable ice formation, profoundly affecting the microphysical and radiative properties, lifetimes, and precipitation rates of clouds. Mineral dust emitted from arid regions, particularly potassium-containing feldspar (K-feldspar), has been shown to be a very effective INP through immersion freezing in mixed-phase clouds. However, despite the fact that quartz has a significantly lower ice nucleation activity, it is more abundant than K-feldspar in atmospheric desert dust and therefore may be a significant source of INPs. In this contribution, we test this hypothesis by investigating the global and regional importance of quartz as a contributor to INPs in the atmosphere relative to K-feldspar. We have extended a global 3-D chemistry transport model (TM4-ECPL) to predict INP concentrations from both K-feldspar and quartz mineral dust particles with state-of-the-art parameterizations using the ice-active surface-site approach for immersion freezing. Our results show that, although K-feldspar remains the most important contributor to INP concentrations globally, affecting mid-level mixed-phase clouds, the contribution of quartz can also be significant. Quartz dominates the lowest and the highest altitudes of dust-derived INPs, affecting mainly low-level and high-level mixed-phase clouds. The consideration of quartz INPs also improves the comparison between simulations and observations at low temperatures. Our simulated INP concentrations predict ~¿51¿% of the observations gathered from different campaigns within 1 order of magnitude and ~¿69¿% within 1.5 orders of magnitude, despite the omission of other potentially important INP aerosol precursors like marine bioaerosols. Our findings support the inclusion of quartz in addition to K-feldspar as an INP in climate models and highlight the need for further constraining their abundance in arid soil surfaces along with their abundance, size distribution, and mixing state in the emitted dust atmospheric particles. This work has been supported by the project “PANhellenic infrastructure for Atmospheric Composition and climatE change” (PANACEA; MIS 5021516), which is implemented under the Action “Reinforcement of the Research and Innovation Infrastructure”, funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund). Nikos Daskalakis, Maria Kanakidou, Mihalis Vrekousis acknowledge support from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy (University Allowance, EXC 2077, University of Bremen). Maria Kanakidou, Marios Chatziparaschos, Athanasios Nenes, Montserrat CostaSurós, María Gonçalves Ageitos, and Carlos Pérez García-Pando acknowledge support by the European Union Horizon 2020 project FORCeS under grant agreement no. 821205. Carlos Pérez GarcíaPando, Montserrat Costa-Surós, and María Gonçalves Ageitos acknowledge support from the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant no. 773051; FRAGMENT) and from the AXA Research Fund. Montserrat Costa-Surós has received funding from the European Union’s Horizon 2020 research and innovation programme, under the Marie Skłodowska-Curie grant agreements, grant no. 754433, from the call H2020-MSCA-COFUND-2016. We thank Joseph M. Prospero for PM10 measurements in Banizoumbou (Niger), Cinzana (Mali), M’Bour (Senegal), which were performed in the framework of the French National Observatory Service INDAAF (International Network to study Deposition and Atmospheric composition in Africa; https://indaaf.obs-mip.fr/, last access: 27 January 2021), piloted by the LISA and LAERO and supported by the INSU/CNRS, the IRD, and the Observatoire MidiPyrénées and the Observatoire des Sciences de l’Univers EFLUVE and Michael Pikridas from the Climate and Atmosphere Research Center of The Cyprus Institute. This research has been supported by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014-2020) and co-financed by Greece and the European Regional Development Fund (grant no. MIS 5021516) and EU-Horizon 2020 project FORCeS (grant no. 821205). Peer Reviewed Objectius de Desenvolupament Sostenible::13 - Acció per al Clima

Terrestrial vegetation emits vast amounts of monoterpenes into the atmosphere, influencing ecological interactions and atmospheric chemistry. Global emissions, mostly driven by responses to abiotic stress, are simulated as a function of temperature with a fixed exponential relationship (β coefficient) across forest ecosystems and environmental conditions. We applied meta-analysis algorithms on all published monoterpene emission data and show that this relationship is more intricate and sensitive than previously thought. We find that co-occurring environmental stresses amplify the temperature sensitivity of the emissions that is primarily related to the specific plant functional type (PFT). On average, warmer ecosystems appear more sensitive, indicating the adjustment of plants in response to thermal stress. Implementing a PFT-dependent β in a biogenic emission model, coupled with a chemistry – climate model, demonstrated that atmospheric processes are exceptionally dependent on monoterpene emissions which are subject to amplified variations under rising temperatures.

Accurate accounting of emissions and removals of CO2 is critical for the planning and verification of emission reduction targets in support of the Paris Agreement. Here, we present a pilot dataset of country-specific net carbon exchange (NCE; fossil plus terrestrial ecosystem fluxes) and terrestrial carbon stock changes aimed at informing countries' carbon budgets. These estimates are based on “top-down” NCE outputs from the v10 Orbiting Carbon Observatory (OCO-2) modeling intercomparison project (MIP), wherein an ensemble of inverse modeling groups conducted standardized experiments assimilating OCO-2 column-averaged dry-air mole fraction (XCO2) retrievals (ACOS v10), in situ CO2 measurements or combinations of these data. The v10 OCO-2 MIP NCE estimates are combined with “bottom-up” estimates of fossil fuel emissions and lateral carbon fluxes to estimate changes in terrestrial carbon stocks, which are impacted by anthropogenic and natural drivers. These flux and stock change estimates are reported annually (2015–2020) as both a global 1∘ × 1∘ gridded dataset and a country-level dataset and are available for download from the Committee on Earth Observation Satellites' (CEOS) website: https://doi.org/10.48588/npf6-sw92 (Byrne et al., 2022). Across the v10 OCO-2 MIP experiments, we obtain increases in the ensemble median terrestrial carbon stocks of 3.29–4.58 Pg CO2 yr−1 (0.90–1.25 Pg C yr−1). This is a result of broad increases in terrestrial carbon stocks across the northern extratropics, while the tropics generally have stock losses but with considerable regional variability and differences between v10 OCO-2 MIP experiments. We discuss the state of the science for tracking emissions and removals using top-down methods, including current limitations and future developments towards top-down monitoring and verification systems.

Megacities and other major population centres (MPCs) worldwide are major sources of air pollution, both locally as well as downwind. The overall assessment and prediction of the impact of MPC pollution on tropospheric chemistry are challenging. The present work provides an overview of the highlights of a major new contribution to the understanding of this issue based on the data and analysis of the EMeRGe (Effect of Megacities on the transport and transformation of pollutants on the Regional to Global scales) international project. EMeRGe focuses on atmospheric chemistry, dynamics, and transport of local and regional pollution originating in MPCs. Airborne measurements, taking advantage of the long range capabilities of the High Altitude and LOng Range Research Aircraft (HALO, https://www.halo-spp.de, last access: 22 March 2022), are a central part of the project. The synergistic use and consistent interpretation of observational data sets of different spatial and temporal resolution (e.g. from ground-based networks, airborne campaigns, and satellite measurements) supported by modelling within EMeRGe provide unique insight to test the current understanding of MPC pollution outflows. In order to obtain an adequate set of measurements at different spatial scales, two field experiments were positioned in time and space to contrast situations when the photochemical transformation of plumes emerging from MPCs is large. These experiments were conducted in summer 2017 over Europe and in the inter-monsoon period over Asia in spring 2018. The intensive observational periods (IOPs) involved HALO airborne measurements of ozone and its precursors, volatile organic compounds, aerosol particles, and related species as well as coordinated ground-based ancillary observations at different sites. Perfluorocarbon (PFC) tracer releases and model forecasts supported the flight planning, the identification of pollution plumes, and the analysis of chemical transformations during transport. This paper describes the experimental deployment and scientific questions of the IOP in Europe. The MPC targets - London (United Kingdom; UK), the Benelux/Ruhr area (Belgium, the Netherlands, Luxembourg and Germany), Paris (France), Rome and the Po Valley (Italy), and Madrid and Barcelona (Spain) - were investigated during seven HALO research flights with an aircraft base in Germany for a total of 53 flight hours. An in-flight comparison of HALO with the collaborating UK-airborne platform Facility for Airborne Atmospheric Measurements (FAAM) took place to assure accuracy and comparability of the instrumentation on board. Overall, EMeRGe unites measurements of near- and far-field emissions and hence deals with complex air masses of local and distant sources. Regional transport of several European MPC outflows was successfully identified and measured. Chemical processing of the MPC emissions was inferred from airborne observations of primary and secondary pollutants and the ratios between species having different chemical lifetimes. Photochemical processing of aerosol and secondary formation or organic acids was evident during the transport of MPC plumes. Urban plumes mix efficiently with natural sources as mineral dust and with biomass burning emissions from vegetation and forest fires. This confirms the importance of wildland fire emissions in Europe and indicates an important but discontinuous contribution to the European emission budget that might be of relevance in the design of efficient mitigation strategies. The present work provides an overview of the most salient results in the European context, with these being addressed in more detail within additional dedicated EMeRGe studies. The deployment and results obtained in Asia will be the subject of separate publications., The HALO deployment during EMeRGe was funded by a consortium comprising the German Research Foundation (DFG) Priority Program HALO-SPP 1294, the Institute of Atmospheric Physics of DLR, the Max Planck Society (MPG), and the Helmholtz Association. Flora Kluge, Benjamin Schreiner, and Klaus Pfeilsticker acknowledge the support given by the DFG through the project nos. PF 384-16, PF 384-17, and PG 385-19. Ralf Koppmann and Marc Krebsbach acknowledge DFG funding through project no. KR3861_1-1. Katja Bigge acknowledges additional funding from the Heidelberg Graduate School for Physics. Johannes Schneider, Katharina Kaiser, and Stephan Borrmann acknowledge funding through the DFG (project no. 316589531). Lisa Eirenschmalz and Hans Schlager acknowledge support by DFG through project MEPOLL (SCHL1857/4-1). Anna B. Kalisz Hedegaard would like to thank DAAD and DLR for a Research Fellowship. Hans Schlager acknowledge financial support by the DLR TraK (Transport and Climate) project. Michael Sicard acknowledges support from the EU (GA nos. 654109, 778349, 871115, and 101008004) and the Spanish Government (ref. nos. CGL2017-90884-REDT, PID2019-103886RB-I00, RTI2018-096548-B-I00, and MDM-2016-0600). Midhun George, Yangzhuoran Liu, M. Dolores Andrés Hernández, and John Phillip Burrows acknowledge financial support from the University of Bremen. FLEXPART simulations were performed on the HPC cluster Aether at the University of Bremen, financed by DFG within the scope of the Excellence Initiative. Anne-Marlene Blechschmidt was partly funded through the CAMS-84 project. Jennifer Wolf acknowledges support from the German Federal Ministry for Economic Affairs and Energy – BMWi (project Digitally optimized Engineering for Services – DoEfS; contract no. 20X1701B). Theresa Harlass thanks DLR VO-R for funding the young investigator research group “Greenhouse Gases”. Mariano Mertens, Patrick Jöckel, and Markus Kilian acknowledge resources of the Deutsches Klimarechenzentrum (DKRZ) granted by the WLA project ID bd0617 for the MECO(n) simulations and the financial support from the DLR projects TraK (Transport und Klima) and the Initiative and Networking Fund of the Helmholtz Association through the project “Advanced Earth System Modelling Capacity” (ESM). Bruna A. Holanda acknowledges the funding from Brazilian CNPq (process 200723/2015-4). The article processing charges for this open-access publication were covered by the University of Bremen.

Unmanned Aerial Vehicles (UAVs) provide a cost-effective way to fill in gaps between surface in-situ observations and remote-sensed data from space. In this study, a novel portable CO2 measuring system suitable for operations on-board small-sized UAVs has been developed and validated. It is based on a low-cost commercial nondispersive near-infrared (NDIR) CO2 sensor (Senseair AB, Sweden), with a total weight of 1058 g, including batteries. The system performs in situ measurements autonomously, allowing for its integration into various platforms. Accuracy and linearity tests in the lab showed that the precision remains within ±1 ppm (1σ) at 1 Hz. Corrections due to temperature and pressure changes were applied following environmental chamber experiments. The accuracy of the system in the field was validated against a reference instrument (Picarro, USA) onboard a piloted aircraft and it was found to be ±2 ppm (1σ) at 1 Hz and ±1 ppm (1σ) at 1 min. Due to its fast response, the system has the capacity to measure CO2 mole fraction changes at 1 Hz, thus allowing the monitoring of CO2 emission plumes and the characteristic of their spatial and temporal distribution. Details of the measurement system and field implementations are described to support future UAV platform applications for atmospheric trace gas measurements.

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97∘ N, 4.93∘ E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

Recently, the Fast atmOspheric traCe gAs retrievaL (FOCAL) algorithm has been applied to measurements of the Greenhouse gases Observing SATellite (GOSAT) and its successor GOSAT-2. FOCAL has been originally developed for Orbiting Carbon Observatory-2 (OCO-2) retrievals with the focus on the derivation of carbon dioxide (XCO2). However, depending on the available spectral windows, FOCAL also successfully retrieves total column amounts for other atmospheric species. Here, we show new results from updated GOSAT and GOSAT-2 FOCAL retrievals. The main focus is placed on methane (XCH4; full physics and proxy product), water vapour (XH2O) and the relative ratio of semi-heavy water (HDO) to water vapour (δD). Due to the extended spectral range of GOSAT-2 it is also possible to derive information on carbon monoxide (XCO) and nitrous oxide (XN2O) for which we also show first results. We also present an update on XCO2 from both instruments. Compared to the previous product version (v1), the number of valid XCO2 data could be significantly increased in the updated version (v3.0) by 50 % for GOSAT and about a factor of two for GOSAT-2. All FOCAL data products show reasonable spatial distribution and temporal variations. Comparisons with TCCON (Total Carbon Column Observing Network) result in station-to-station biases which are generally in line with the reported TCCON uncertainties. With this updated version of the GOSAT-2 FOCAL data, we provide a first total column average XN2O product. Global XN2O maps show a gradient from the tropics to higher latitudes in the order of 15 ppb, which can be explained by variations in tropopause height. The new GOSAT-2 XN2O product compares well with TCCON. Its station-to-station variability is lower than 2 ppb, which is about the magnitude of the typical N2O variations close to the surface. However, both GOSAT-2 and TCCON measurements show that the seasonal variations in the total column average XN2O are in the order of 8 ppb peak-to-peak, which can be easily resolved by the GOSAT-2 FOCAL data.

The ozone mixing ratio spatiotemporal variability in the pristine South Pacific Ocean is studied, for the first time, using 21-year-long ozone (O3) records from the entire southern tropical and subtropical Pacific between 1994 and 2014. The analysis considered regional O3 vertical observations from ozonesondes, surface carbon monoxide (CO) observations from flasks, and three-dimensional chemistry-transport model simulations of the global troposphere. Two 21-year-long numerical simulations, with and without biomass burning emissions, were performed to disentangle the importance of biomass burning relative to stratospheric intrusions for ambient ozone levels in the region. Tagged tracers of O3 from the stratosphere and CO from various biomass burning regions have been used to track the impact of these different regions on the southern tropical Pacific O3 and CO levels. Patterns have been analyzed based on atmospheric dynamics variability. Considering the interannual variability in the observations, the model can capture the observed ozone gradients in the troposphere with a positive bias of 7.5 % in the upper troposphere/lower stratosphere (UTLS) as well as near the surface. Remarkably, even the most pristine region of the global ocean is affected by distant biomass burning emissions by convective outflow through the mid and high troposphere and subsequent subsidence over the pristine oceanic region. Therefore, the biomass burning contribution to tropospheric CO levels maximizes in the UTLS. The Southeast Asian open fires have been identified as the major contributing source to CO from biomass burning in the tropical South Pacific, contributing on average for the study period about 8.5 and 13 ppbv of CO at Rapa Nui and Samoa, respectively, at an altitude of around 12 km during the burning season in the spring of the Southern Hemisphere. South America is the second-most important biomass burning source region that influences the study area. Its impact maximizes in the lower troposphere (6.5 ppbv for Rapa Nui and 3.8 ppbv for Samoa). All biomass burning sources contribute about 15–23 ppbv of CO at Rapa Nui and Samoa and account for about 25 % of the total CO in the entire troposphere of the tropical and subtropical South Pacific. This impact is also seen on tropospheric O3, to which biomass burning O3 precursor emissions contribute only a few ppbv during the burning period, while the stratosphere–troposphere exchange is the most important source of O3 for the mid troposphere of the South Pacific Ocean, contributing about 15–20 ppbv in the subtropics.

The Thermal And Near infrared Sensor for carbon Observation – Fourier Transform Spectrometer (TANSO-FTS) on the Japanese Greenhouse gases Observing SATellite (GOSAT) has been returning data since April 2009. The version 9 (v9) Atmospheric Carbon Observations from Space (ACOS) Level 2 Full Physics (L2FP) retrieval algorithm (Kiel et al., 2019) was used to derive estimates of carbon dioxide (CO2) dry air mole fraction (XCO2) from the TANSO-FTS measurements collected over it's first eleven years of operation. The bias correction and quality filtering of the L2FP XCO2 product were evaluated using estimates derived from the Total Carbon Column Observing Network (TCCON) as well as values simulated from a suite of global atmospheric inverse modeling systems (models). In addition, the v9 ACOS GOSAT XCO2 results were compared with collocated XCO2 estimates derived from NASA's Orbiting Carbon Observatory-2 (OCO-2), using the version 10 (v10) ACOS L2FP algorithm. These tests indicate that the v9 ACOS GOSAT XCO2 product has improved throughput, scatter and bias, when compared to the earlier v7.3 ACOS GOSAT product, which extended through mid 2016. Of the 37 million (M) soundings collected by GOSAT through June 2020, approximately 20 % were selected for processing by the v9 L2FP algorithm after screening for clouds and other artifacts. After post-processing, 5.4 % of the soundings (2M out of 37M) were assigned a “good” XCO2 quality flag, as compared to 3.9 % in v7.3 (

Since May 2017 and August 2018, two ground-based MAX-DOAS (multi-axis differential optical absorption spectroscopy) instruments have been continuously recording daytime spectral UV–visible measurements in the northwest (University of Natural Resources and Life Sciences (BOKU) site) and south (Arsenal site), respectively, of the Vienna city center (Austria). In this study, vertical aerosol extinction (AE) profiles, aerosol optical depth (AOD), and near-surface AE are retrieved from MAX-DOAS measurements recorded on cloud-free days applying the Bremen Optimal estimation REtrieval for Aerosols and trace gaseS (BOREAS) algorithm. Measurements of atmospheric profiles of pressure and temperature obtained from routinely performed sonde ascents are used to calculate box-air-mass factors and weighting functions for different seasons. The performance of BOREAS was evaluated against co-located ceilometer, sun photometer, and in situ instrument observations covering all four seasons. The results show that the vertical AE profiles retrieved from the BOKU UV–visible MAX-DOAS observations are in very good agreement with data from the co-located ceilometer, reaching correlation coefficients (R) of 0.936–0.996 (UV) and 0.918–0.999 (visible) during the fall, winter, and spring seasons. Moreover, AE extracted using the lowest part of MAX-DOAS vertical profiles (up to 100 m above ground) is highly consistent with near-surface ceilometer AE (R>0.865 and linear regression slopes of 0.815–1.21) during the fall, winter, and spring seasons. A strong correlation is also found for the BOREAS-based AODs when compared to the AERONET ones. Notably, the highest correlation coefficients (R=0.953 and R=0.939 for UV and visible, respectively) were identified for the fall season. While high correlation coefficients are generally found for the fall, winter, and spring seasons, the results are less reliable for measurements taken during summer. For the first time, the spatial variability of AOD and near-surface AE over the urban environment of Vienna is assessed by analyzing the retrieved and evaluated BOREAS aerosol profiling products in terms of different azimuth angles of the two MAX-DOAS instruments and for different seasons. We found that the relative differences of averaged AOD between different azimuth angles are 7–13 %, depending on the season. Larger relative differences of up to 32 % are found for near-surface AE in the different azimuthal directions. This study revealed the strong capability of BOREAS to retrieve AE profiles, AOD, and near-surface AE over urban environments and demonstrated its use for identifying the spatial variability of aerosols in addition to the temporal variation.

The Sentinel-5 Precursor (S5P) mission with the TROPOspheric Monitoring Instrument (TROPOMI) onboard has been measuring solar radiation backscattered by the Earth's atmosphere and its surface since its launch on 13 October 2017. Methane (CH4) and carbon monoxide (CO) data with a spatial resolution (initially 7 x 7 km2, upgraded to 5.5 x 7 km2 on 6th of August 2019) have been retrieved from shortwave infrared (SWIR) and near-infrared (NIR) measurements since the end of November 2017 and made available to the experts for early validation and quality checks before the official product release. In this paper, we present for the first time the S5P CH4 and CO validation results (covering a period from November 2017 to September 2020) using global Total Carbon Column Observing Network (TCCON) and Infrared Working Group of the Network for the Detection of Atmospheric Composition Change (NDACC-IRWG) network data, accounting for a priori alignment and smoothing uncertainties in the validation, and testing the sensitivity of validation results towards the application of advanced co-location criteria.We found that the required bias (systematic error) of 1.5 % and random error of 1 % for the S5P standard and bias-corrected methane data are met for measurements over land surfaces with pixels having quality assurance (QA) value > 0.5. The systematic difference between the S5P standard XCH4 and TCCON data is on average −0.69 ± 0.73 %. The systematic difference changes to a value of −0.25 ± 0.57 % for the S5P bias-corrected XCH4 data. We found a correlation of above 0.6 for most stations, which is mostly dominated by the seasonal cycle. The contributions of smoothing uncertainty at the individual stations are estimated and found to be dependent on the location. The highest contribution of the smoothing uncertainty is observed for mid-latitude TCCON stations and high latitude stations for NDACC. A seasonal dependency of the relative bias is seen. We observe a high bias during the springtime measurements at high SZA and a decreasing bias with increasing SZA for the rest of the year.We found that the required bias (systematic error) of 15 % and random error of < 10 % for the S5P carbon monoxide data are met in general for measurements over all surfaces with pixels having quality assurance value of > 0.5. There are a few stations where this is not the case, mostly due to co-location mismatches and the limited availability of co-located data. We compared the S5P XCO data with respect to standard TCCON XCO and unscaled TCCON XCO (without application of the empirical scaling factor) data sets. The systematic difference between the S5P XCO and the TCCON data is on average 9.14 ± 3.33 % (standard TCCON XCO data) and 2.36 ± 3.22 % (unscaled TCCON XCO data). We found that the systematic difference between the S5P CO column and NDACC CO column data (excluding two stations that were obvious outliers) is on average 6.44 ± 3.79 %. We found a correlation of above 0.9 for most TCCON and NDACC stations indicating that the temporal variations in CO column captured by the ground-based instruments are reproduced very similarly by the S5P CO column. The contribution of smoothing uncertainty at the individual stations is estimated and found to be significant. They are found to be dependent on the location with large changes seen for stations located in the Southern Hemisphere as compared to the Northern Hemisphere and at highly polluted stations. A cone co-location criterion, which gives a better match between the ground-based instrument's line-of-sight and satellite pixels, seems to give better results for high latitude stations and stations located close to emission sources. The validation results for the clear-sky and cloud cases of S5P pixels are comparable to the validation results including all pixels with quality assurance value of > 0.5. We observe that the relative bias increases with increasing SZA. We estimated this increase is about 10 % over the complete range of measurement SZAs.The study shows the high quality of S5P CH4 and CO data by validating the products against reference global TCCON and NDACC stations covering a wide range of latitudinal bands, atmospheric conditions, and surface conditions.

In this study, we report on the retrieval of aerosol extinction profiles from ground-based scattered sunlight multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, carried out at Athens, Greece. It is the first time that aerosol profiles are retrieved from MAX-DOAS measurements in Athens. The reported aerosol vertical distributions at 477 nm are derived from the oxygen dimer (O4) differential slant column density observations at different elevation angles by applying the BOREAS retrieval algorithm. Four case studies have been selected for validation purposes; the retrieved aerosol profiles and the corresponding aerosol optical depths (AODs) from the MAX-DOAS are compared with lidar extinction profiles and with sun photometric measurements (AERONET observations), respectively. Despite the different approach of each method regarding the retrieval of the aerosol information, the comparison with the lidar measurements at 532 nm reveals a very good agreement in terms of vertical distribution, with r > 0.85 in all cases. The AODs from the MAX-DOAS and the sun-photometer (the latter at 500 nm) show a satisfactory correlation (with r ≈ 0.6 in three out of the four cases). The comparison indicates that the MAX-DOAS systematically underestimates the AOD in the cases of large particles (small Ångström exponent) and for measurements at small relative azimuthal angles between the viewing direction and the Sun. Better agreement is achieved in the morning, at large relative azimuthal angles. Overall, the aerosol profiles retrieved from MAX-DOAS measurements are of good quality; thus, new perspectives are opened up for assessing urban aerosol pollution on a long term-basis in Athens from continuous and uninterrupted MAX-DOAS measurements.

Unmanned Aerial Vehicles (UAVs) have the potential to fill in gaps in greenhouse gases (GHG) observations by providing high-resolution vertical profiling, horizontal mapping of fluxes and 3D measurements close to the ground. UAVs can ultimately allow better characterizing the spatial distribution of various GHG sources and sinks. To achieve these goals, important efforts are currently put towards the development of compact, lightweight, low powered and highly accurate GHG sensors on UAVs.This study aims to develop and validate a UAV-CO2 sensor system to map specific source emissions close to the ground. The CO2 sensor used here is the High-Performance Platform (HPP 3.2, SenseAir AB) of a total weight 1058g including battery. Prior to its integration in the UAV, the CO2 sensor accuracy and linearity tests were performed in the laboratory. Allan Deviation showed the sensor precision to be within ±1ppm at 1 Hz. Corrections due to temperature and pressure changes were performed using specific formulas obtained from chamber experiments. Field (manned aircraft) tests were performed, where the P/T correction equations were evaluated for two CO2 sensors which were compared against an airborne reference instrument (Picarro G2401-m). After laboratory tests and field deployment, the HPP CO2 sensor was integrated into a small fixed-wing UAV with a wingspan of 1.83m and customized avionics and payload developed by the Unmanned Systems Research Laboratory of the Cyprus Institute performed successful atmospheric profiling below/above the boundary layer, at an agricultural site in Cyprus. This HPP CO2 sensor is also to be integrated in a quad-copter for vertical take-off ＆ landing (VTOL) in urban environments to execute intensive (every 20-min) atmospheric profiling (0-1km altitude) over the city of Nicosia (Cyprus). These flights provide us with useful insights into the CO2 vertical distribution within the planetary boundary layer (and above) for different (remote/urban) regions in Cyprus.

Within the project VINDOBONA (VIenna horizontal aNd vertical Distribution OBservations Of Nitrogen dioxide and Aerosols), a method was developed to retrieve the spatial distribution of trace gases using data from three ground based MAX-DOAS instruments and was applied on the example of NO2. At three different locations in Vienna (Austria) MAX-DOAS instruments were installed performing measurements in the visible and UV spectral range. Currently, each instrument is set up to determine the column densities in different azimuthal directions and low elevation angles within approximately a horizontal plane. The different lines of sight of the three instruments intersect horizontally and can be used to estimate the horizontal spatial distribution of trace gases. With the knowledge of vertical profiles, even the vertical distribution can be estimated using this method. The intersections of the different lines of sight define segments along the slant columns for which the mass concentrations can be estimated. Knowledge about the vertical profiles for a chosen trace gas can be used to correct the retrieved trace gas concentration to specific altitudes above ground. Such corrections are also required since the three instruments were set up at different heights above ground, at different altitudes relative to sea level and with different elevation angles of the lowest viewing direction. One open issue for the retrieval process is the terrain in Vienna in combination with the prevailing wind condition that impacts the horizontal and vertical trace gas distribution and make the retrieval challenging.

EMeRGe (Effect of Megacities on the Transport and Transformation of Pollutants on the Regional to Global Scales) aims to investigate the impact of MPC emissions on air pollution and chemical processing at local, regional and hemispheric scales by making dedicated airborne measurements using the German research aircraft HALO. Transects and vertical profiling for diverse MPCs (e.g. Rome, London, Taipei, Manila) were performed to determine the composition and transformation of various pollution plumes in Europe and Asia.To characterize air masses we evaluate different volatile organic compounds (VOCs), measured by a Proton-Transfer-Reaction Mass Spectrometer (PTR-MS), with different or similar sources and different lifetimes. We use the specific tracer acetonitrile to identify air masses influenced by biomass burning (BB), the aromatic compound benzene to tag anthropogenic pollution plumes (e.g. from traffic or industry) and short-lived isoprene as indicator for fresh biogenic influences. Back trajectories based on FLEXTRA (FLEXible TRAjectory model) are used to determine potential source regions of BB affected air and anthropogenic pollution plumes.Results show that in Europe only minor BB influenced air masses were sampled. However, in Southern France fresh BB close to the source was detected. In contrast to Europe, numerous plumes affected by BB were identified in Asia originating mostly from Southeast Asia.Air masses with enhanced concentrations in benzene and low concentrations in acetonitrile, indicating anthropogenic pollution, were sampled in Europe over the Po-Valley, Rome, Barcelona and the English Channel. In Asia, plumes were identified along the west coast of Taiwan, the East China Sea and Manila originating from local sources as well as transported from Mainland China.Significant fresh biogenic influence was found in Europe, as the measurements were performed mostly in summer over land in contrast to Asia were just a minor influence was detected.

Carbon Monoxide (CO) is an important atmospheric trace gas, and among the key O3 precursors in the troposphere, alongside NOx and VOCs. It is among the most important sinks of OH radical in the atmosphere, which controls lifetime of CH4 — a major greenhouse gas. Biomass burning sources contribute about 25% to the global emissions of CO, with the remaining CO being either emitted from anthropogenic sources, or being chemically formed in the atmosphere. Because of CO tropospheric lifetime is about two months; it can be transported in the atmosphere thus its sources have a hemispheric impact on atmospheric composition.The extent of the impact of biomass burning to remote areas of the world through long range transport is here investigated using the global 3-dimensional chemistry transport model TM4-ECPL. For this, tagged biomass burning CO tracers from the 13 different HTAP (land) source regions are used in the model in order to evaluate the contribution of each source region to the CO concentrations in the 170 HTAP receptor regions that originate from biomass burning. The global simulations cover the period 1994—2015 in order to derive climatological transport patterns for CO and assess the contribution of each of the source regions to each of the receptor regions in the global troposphere. The CO simulations are evaluated by comparison with satellite observations from MOPITT and ground based observations from WDCGG. We show the significant impact of biomass burning emissions to the most remote regions of the world.

Particulate matter is of special interest in atmospheric studies because it has important effects on both the Earth's climate and on human health. Currently, aerosols contribute largest to the overall uncertainty of the net radiative effects in studies of climate change. At the same time, aerosols are responsible for a large fraction of the overall impact of air quality on human health. Mineral dust is an important aerosol constituent and makes up a significant part of the total aerosol load. After its emission, mineral dust can be transported over very large distances in the atmosphere, and in extreme cases influence air quality far away from its source region.The project Effect of Megacities on the Transport and Transformation of Pollutants on the Regional to Global Scales (EMeRGe) consisted of two measurement campaigns with the research aircraft HALO. HALO operated for two four-week periods in Europe (based close to Munich) and East Asia (based in Taiwan) in July 2017 and March 2018, respectively. The aircraft was fully equipped with extensive measurement instrumentation to sample atmospheric composition with a focus on the air pollution outflow from major population centers.Here, we present simulations of coarse-mode aerosol transport to the East China Sea, where EMeRGe-Asia flight E_AS_F#11 was flying from Taiwan to Japan and back on 30 Mar 2018. During the flight, enhanced concentrations of aerosol in the 0.5-3µm diameter range were measured using an optical particle counter (OPC) in several different locations. We used version 10.4 of the FLEXPART Lagrangian dispersion model to simulate sensitivity fields to emissions of dust, sea-sealt, and biomass burning aerosol. Combined with emission data for the three aerosol species, we can estimate the contribution of the different species and source regions to the measured aerosol enhancements.Among others, our simulations show that mineral dust from as far as the Sahara desert in North Africa can contribute significantly to the total aerosol concentration over the East China Sea.

Within the scope of the VINDOBONA (VIenna horizontal aNd vertical Distribution OBservations Of Nitrogen dioxide and Aerosols) project, spectral UV/vis measurements at selected viewing directions are performed with three MAX-DOAS (Multi AXis Differential Optical Absorption Spectroscopy) instruments, which are located in the northeast, northwest, and south of the city center of Vienna, Austria. The selection of viewing directions of the three instruments was chosen in a way to provide data for the retrieval of horizontal and vertical trace gas and aerosol distributions, in particular over the urban core.In the present work, the profile retrieval algorithm BOREAS (Bremen Optimal estimation REtrieval for Aerosols and trace gaseS) is used to retrieve aerosol and NO2 vertical profiles as well as accompanying parameters aerosol optical depth, tropospheric NO2 vertical columns (TVC NO2), and near-surface NO2 on days with cloudless conditions. The retrieval results are compared with co-located ceilometer, sun photometer, surface air quality, and TVC NO2 measurements, with the latter being obtained by applying the geometrical approximation and converting zenith-sky NO2 measurements.

A clear understanding of carbon monoxide (CO) emissions is important at various scales. On the local scale CO is toxic to living organisms, and on the global scale CO plays in role in the budget of the hydroxyl radical (OH). OH, in turn, is important for the oxidizing capacity of the atmosphere. Additionally, CO is a precursor of the greenhouse gases ozone and carbon dioxide, hence CO influences also climate on a global scale.Approximately one quarter of the global atmospheric CO load emanates from wildfires. However, these emissions are sometimes underrepresented in the emission datasets. Among the reasons for this discrepancy are clouds and smoke plumes hampering observations of land cover and active fires and uncertainties in emission factors. These issues are less relevant for top-down approaches like inverse modeling, which allow tracing back an atmospheric signal to its source even if it is only observed days after emission.In this study, we attempt to improve the emission estimates of an existing inventory by applying an inverse modeling approach to the CO emissions of the California wildfires in 2018, that devastated more than 7500 square kilometers of forested and residential area. More specifically, we used the Fire Emission Inventory from NCAR (FINN) together with the CO observations from the TROPOMI instrument onboard the Sentinel 5 Precursor (S5P) satellite and the TM5-4dvar inverse model. The high resolution of the TROPOMI observations enables better spatial constraints compared to previous instruments. Preliminary results suggest significant positive emission increments compared to FINN.

Oxygenated volatile organic compounds (OVOCs) are released to the atmosphere from biogenic, anthropogenic, and pyrogenic sources. The role and importance of OVOCs in ambient atmospheric composition and their role in climate change was established many years ago. Another topical issue is the formation of secondary organic aerosols (SOA), which potentially are relevant for cloud formation, heterogeneous chemistry, and can also contribute to the long-term transport of volatile organic compounds. OVOCs can be detected from space-borne observations using the Differential Optical Absorption Spectroscopy (DOAS) method. Here, measurements from the TROPOMI instrument, which was launched on the Sentinel-5 Precursor (S5P) platform in October 2017, are used. During the year 2019, large wildfires occurred in North America, Amazonia, Siberia, and Australia. These fires created elevated amounts of many different gases, e.g. CO, NOx, OVOC, O3, SO2, CO, HONO, CH3CO.O2.NO2 (PAN) and other toxic species as well as aerosols affecting air quality. During the transport of plumes from fires, photochemical transformation of emitted species occurs. Overall, polluted air is transported to regions where the plumes are dispersed. For many of the fires, unexpectedly high amounts of OVOCs are detected in plumes as consequence of continued emission and conversion of some OVOCs. The amounts of OVOCs emitted were found to depended on the type of biomass burned and the location of the fires. Here, a characterization of OVOC emissions from fires is performed by using OVOC S5P observations, in combination with forward trajectories simulated with the FLEXPART model and proxies of vegetation types, leading to new insights in the emissions of OVOCs from fires.

At the industrial revolution (1750-1800), the population of the earth was around 1 Billion and less than 5% of population lived in urban areas. In 1950, when the population reached about 2.9 billion, there were two megacities New York/Newark and Tokyo. In 2020, the earth’s population is around 7.8 Billion, more than 50% live in urban areas and there are now approximately 38 around the world. Since 2007, more than 50% of the population live in urban areas and the earth’s population has now reached 7.8 Billion. Anthropogenic activity to sustain and feed MPC is now one of the most important sources of pollution, modifying atmospheric chemistry, air quality and climate. To assess the impact of MPC emissions locally and regionally requires knowledge of the transport and transformation of the MPC plumes. The EMeRGe project was proposed to address this need and investigate the transport and transformation of the chemical composition of MPC plumes. Secondary objectives include the improvement of our understanding of the impact of biomass burning, which mixes with the plumes from MPC. EMeRGe selected European and Asian MPC as targets, where the regulations on emissions are significantly different.EMeRGe assumes that the nature of the local emissions, the meteorology and photochemistry/chemistry determines the transport and transformation of the plumes from MPCs. To test this hypothesis, the following scientific questions are addressed: a) which transport and dispersion processes dominate the MPC outflows in Europe and Asia during the selected measurement periods;b) which oxidation or other processes determine the chemical transformation of MPC emissions;c) what are the regional impacts of the emission by the selected European and Asian MPCs;d) what is the relevance of emission from European and Asian MPCs for radiative forcing and climate change;e) do our chemical models adequately simulate of transport and transformation processes of European and Asian MPC outflows.An integrating focus of EMeRGe were the measurement campaigns exploiting the capabilities of the German HALO research were undertaken during EMeRGe, which investigated the outflow from: i) European MPCs in July 2017; ii) MPCs in East and South East Asia during March and April 2018. In addition to the HALO aircraft measurements, the EMeRGe International scientists contributed studies of the measurement from instrumentation from ground based, airborne and satellite platforms. For example in EMeRGe in Europe the UK NERC FAAM (https://nerc.ukri.org/research/sites/facilities/aircraft/) "ERA - CNR - ISAFOM" (https://www.eufar.net/aircrafts/44) were deployed to make measurements around London and Rome respectively. In EMeRGe in Asia, measurement were made ground based and Lidar measurements were made by EMeRGe partners from Taiwan, Japan, the Philippines, Thailand and China. EMeRGe benefited from the support by iCACGP (international Commission on Atmospheric Chemistry and Global Pollution). This presentation will provide an overview of the objectives, the planning, the measurements and some highlights from the EMeRGe HALO campaigns.

Long-term particulate matter (PM) mass concentration measurements have been performed in Cyprus at three major cities, one industrial area and two remote stations covering the entire southern part of the island in an effort to assess; i) the spatial and temporal variability of sub-10 μm (PM10), fine (PM2.5) and submicron (PM1) particulate matter in the eastern Mediterranean, ii) the main source areas contributing to their levels and iii) the relative contribution of regional and local anthropogenic and natural sources to PM levels. It was found that dust is responsible for the 33.6 ± 5.2% or about 10 μg m−3 of the annual PM10 levels reported in background stations; the latter underlines the significant contribution of natural sources on the ambient PM10 amounts in the eastern Mediterranean region. A significant (p