AS3.20

Black carbon (BC) aerosol emission is an important contributor to particulate matter (PM) pollution in China, leading to adverse health effects and premature deaths. BC aerosols can also affect boundary layer meteorology by heating the atmosphere, due to the unique property of BC to absorb solar radiation. In contrast, sulphate aerosols reflect solar radiation and thus cool the surface. How individual aerosol pollutants influence boundary layer meteorology on a multi-year timescale is not well known. A particularly important aspect of this influence is a potential feedback process, where changed boundary layer conditions may influence present aerosol concentrations, potentially exacerbating near-surface pollution levels. In this work, we use the Weather Research and Forecasting model with Chemistry (WRF-Chem) at 45 km horizontal resolution covering East and South Asia, and at 15 km resolution covering East China. Simulations are driven by the ECMWF Reanalysis v5 (ERA5), and anthropogenic emissions are from the latest version of the Community Emissions Data System (CEDS). Multi-year simulations are evaluated against observations of meteorological parameters and air quality data for China. Preliminary results show that aerosol-radiation interactions due to BC lead to higher annual near-surface PM concentrations, underscoring the importance of mitigating black carbon aerosol emissions. The elevated PM concentrations can be explained by a shallower boundary layer and reduced turbulent mixing near the surface associated with BC. Possible effects of aerosol-radiation interactions on extreme pollution events, including not only extreme PM events but also extreme ozone (O3) events, will be examined.

How to cite: Hodnebrog, Ø., Stjern, C. W., Marelle, L., Myhre, G., Pisso, I., and Wang, S.: Influence of aerosol-radiation interactions on air pollution in East Asia, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5828, https://doi.org/10.5194/egusphere-egu22-5828, 2022.

Tropospheric ozone (O₃) exerts strong adverse impacts on human health, climate, vegetation, biodiversity, agricultural crop yields and thus food security. O₃ is formed in the atmosphere through non-linear photochemical reactions between volatile organic compounds (VOCs) and nitrogen oxides (NOx) precursors. Currently, there are no observational methods that differentiate the origin of O₃. Despite their inherent uncertainties, chemical transport models (CTMs) allow for the apportionment of the contribution of any source to O₃ concentrations. The mass-transfer source apportionment method is an optimal approach to study the contribution of different sources to ozone levels.

In this study, we provide a quantitative estimation of the foreign and domestic contributions to ozone among European countries relative to the contribution of hemispheric imported ozone. We use CMAQ-ISAM within the CALIOPE air quality modelling system to simulate the O₃ dynamics over Europe at a 18 x 18 km² horizontal resolution and quantify national contributions for the ozone season from May to October during the years 2015, 2016 and 2017. We tag both O₃ and its precursors, NOx and VOCs, from the different European countries, all the way through their lifetime, from emission to deposition. We discuss the results for 35 European countries, including their ozone contribution to other countries, the role of hemispheric background ozone concentrations in each country, and the changes from one year to another.

How to cite: Garatachea, R., Achebak, H., Jorba, O., Ballester, J., Pay, M. T., and García-Pando, C. P.: Foreign and domestic contributions to surface ozone among European countries, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7252, https://doi.org/10.5194/egusphere-egu22-7252, 2022.

Despite continuous improvement during recent decades, state of the art global chemistry-climate models (CCMs) are still showing biases compared to observational data, illustrating remaining difficulties and challenges in the simulation of atmospheric processes. Therefore, CCM output is frequently bias-corrected in studies seeking to explore changing air quality burdens e.g., in form of the number of exceedances of threshold values for the protection of human health [e.g. Rieder et al., 2018].This study focuses on assessing strengths and limitations of different bias correction methods for global CCM simulations with focus on maximum daily 8-hour average surface ozone data. Ozone is chosen as it is known as regional pollutant and thus shows smaller spatial heterogeneity in its burden than e.g. particulate matter. Within the comparison a set of different innovative, as well as, common bias correction techniques are applied to output of several global coupled CCMs contributing hindcast simulations to the Coupled Model Intercomparison Project Phase 6 (CMIP6). For bias correction and evaluation, data from ground-based observations pooled by the European Environment Agency is used. To this end, the station data is spatially averaged by adopting an inverse distance weighting method proposed by Schnell et al. [2014] to match the individual model grid cells. For the actual bias correction four different methods are used and compared. These include quantile mapping, delta-function, relative and mean bias correction approaches. As surface ozone pollution is commonly associated with a strong seasonal cycle, the adjustment techniques are applied to model data on both seasonal and annual basis, and skill scores for individual bias correction techniques are compared across CMIP6 models.

References:

Rieder, H.E., Fiore A.M., Clifton, O.E., Correa, G., Horowitz, L.W., Naik, V.: Combining model projections with site-level observations to estimate changes in distributions and seasonality of ozone in surface air over the U.S.A., Atmos. Env., 193, 302-315, https://doi.org/10.1016/j.atmosenv.2018.07.042, 2018.

Schnell, J. L., Holmes, C. D., Jangam, A., and Prather, M. J.: Skill in forecasting extreme ozone pollution episodes with a global atmospheric chemistry model, Atmos. Chem. Phys., 14, 7721–7739, https://doi.org/10.5194/acp-14-7721-2014, 2014.

How to cite: Stähle, C., Mayer, M., Checa-Garcia, R., and Rieder, H.: An evaluation of global chemistry-climate model output bias correction techniques for surface ozone burdens, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10045, https://doi.org/10.5194/egusphere-egu22-10045, 2022.

In the last two decades reanalyses have become a powerful tool for modern geosciences as they combine both model- and observation-based (mostly from remote-sensing sources) information to provide physically-consistent data of land, ocean and atmospheric fields with continuous spatial and temporal coverage. In the frame of the ERC project EARLY-ADAPT (https://early-adapt.eu/), a pioneer health dataset is currently being collected over Europe to investigate the time-varying health effects of climate and air pollution, which will shed light into the early adaptation response to climate change in the area of human health. This impact will be quantified by fitting epidemiological models on historical local health, climate and air pollution data, which thus requires a long-term air quality database at daily-scale over all of Europe. In this context, atmospheric composition reanalyses provide highly valuable information, but remain subject to biases and errors both in terms of spatiotemporal variability and long-term trends. It is therefore key to determine whether these reanalyses correctly capture the values, trends and cyclic processes of the different aforementioned fields.

Our work aims to evaluate how the Copernicus Atmosphere Monitoring Service global reanalysis (CAMSRA), developed by the ECMWF, and the Modern-Era Retrospective Analysis for Research and Applications v2 (MERRA-2), produced by NASA, perform against independent ground-level in-situ observations over Europe for a period of 18 years (2003 – 2020). We analyse these reanalyses products considering the most harmful pollutants for human health, namely O₃, NO₂, SO₂, CO, PM_2.5 and PM₁₀. A careful quality-assurance filtering of the surface observations is performed using GHOST, which stands for Globally Harmonised Observational Surface Treatment, a BSC in-house project dedicated to the harmonisation of global air pollution surface observations and its metadata, with the purpose of facilitating a greater quality of observational/model comparison in the atmospheric chemistry community. This study considers a domain extending from 25°W to 45°E in longitude, and from 27°N to 72°N in latitude, thus covering all continental Europe as well as the Canary Islands, Iceland, Western/European Russia, North Africa and the westernmost regions of the Middle East and the Caucasus.

CAMSRA and MERRA-2 reproduce the observational values, trends and seasonal cycles with a varying degree of accuracy, depending on the pollutant considered, though significant and persistent biases are found in almost all cases. As the computed statistics present strong spatiotemporal dependencies, given the long-term scope of the evaluation, a regional and country-level analysis has been performed in order to provide a more exhaustive and complete evaluation. An intercomparison between CAMSRA and MERRA-2 has also been conducted for the pollutants available in both reanalyses. The obtained results highlight the necessity of applying bias correction schemes when working with air pollution reanalysis data, and open the door for improved continental-wide, regional-scale, environmental epidemiological analyses of the health impacts of air pollutants.

How to cite: Lacima, A., Petetin, H., Soret, A., Bowdalo, D., Chen, Z., Méndez, R., Achebak, H., Ballester, J., and Pérez García-Pando, C.: Long-term evaluation of surface air pollution in CAMSRA and MERRA-2 global reanalyses over Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11704, https://doi.org/10.5194/egusphere-egu22-11704, 2022.

Summary

This study aims to quantify the combined effect of changing emissions and population activity in the estimation of urban population during the first COVID19-lockdown measures in the beginning of the year 2020. While most studies focus on the impact of changing emissions in concentration reductions due to lockdown measures, we identified the additional change in population exposure for three different cities in Europe, when taking into account the change in population activity in a dynamic urban population exposure model. The results show that population exposure is underestimated by up to 8% for NO₂ and by up to 29% for PM_2.5 exposure, when neglecting the change in population activity.

Introduction

The lockdown response to the coronavirus disease 2019 (COVID-19) has caused an exceptional reduction in global economic and transport activity. Many recent measurement and modelling studies tested the hypothesis that this has reduced ground-level air pollution concentrations as well as the associated population exposure and health effects, especially in urban areas. Although Google and Apple mobility data is utilized in such air quality modelling studies to derive changes in emissions, the mobility data is not used to reflect changes in population activity patterns. Nevertheless, neglecting the mobility of populations in exposure estimates is known to introduce substantial BIAS; especially on urban-scales. Therefore, we identified the additional change in population exposure for three different cities in Europe (Hamburg - DE, Liège - BE, Marseille - FR), when taking into account the change in population activity in a dynamic urban population exposure model.

Methods

To model the impact of (1) changing emissions and (2) the change in population activity patterns in our multi-city exposure study, we applied mobility data as derived from different sources (Google, Eurostat, Automatic Identification System, etc.). The aim is to quantify the BIAS in air pollution (PM_2.5, NO₂) exposure estimates that arises from neglecting population activity under COVID-19 lockdown conditions. We applied the urban-scale chemistry transport model EPISODE-CityChem (Karl et. al 2019) and the urban dynamic exposure model UNDYNE (Ramacher et al. 2020) in the European cities Marseille (FR), Liège (BE) and Hamburg (DE) in the first six months of 2020. Based on flexible microenvironment definitions for different surroundings (based on the Copernicus UrbanAtlas) and modes of transport (based on OpenStreetMap), the UNDYNE model allows for a flexible application of population activity in European urban areas. This feature was used to evaluate and compare a set of emission and activity scenarios.

Results

Compared to non-lockdown conditions, the derived lockdown activity profiles showed substantial additional changes in the total exposure of the urban population in all cities with up to 8% for NO₂ and by up to 29% for PM_2.5. The analysis of estimated exposure in the different microenvironments home, work and transport reflects the changes in population activity with increasing exposure in the home environment and decreasing exposure in the work and transport environments. Due to the general high reduction of population exposure in transport activities, a significant change of exposure for different modes of transport was not observed.

How to cite: Ramacher, M. O. P., Badeke, R., Quante, M., Feldner, J., Fink, L., Arndt, J., Petrik, R., and Matthias, V.: The underestimation of Cov19 lockdown effects in modeling urban population exposure to air pollution, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1121, https://doi.org/10.5194/egusphere-egu22-1121, 2022.

How to cite: du Preez, D. J. and Knote, C.: Investigating the influence of mesoscale dynamics and chemistry on urban air pollution, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7168, https://doi.org/10.5194/egusphere-egu22-7168, 2022.

The US National Ambient Air Quality Standard (NAAQS) dictates the limits on atmospheric pollutants, including the tropospheric ozone (O₃). Its exceedance of the limit typically happens in the summer because of changes in meteorology, chemistry, and emissions. Since O₃ affects pulmonary function and has been linked to higher risks of depression and anxiety diagnoses, it is essential to understand O₃ and its precursor nitrogen dioxide (NO₂) variations. In July 2021, the Finite Volume Cube-Sphere Dynamic Core in Global Forecasting System (FV3-based GFS) became the new meteorological driver coupled with the Environmental Protection Agency’s Community Multiscale Air Quality System (CMAQ). Together they make up the National Air Quality Forecasting Capability (NAQFC), which provides hourly forecasts of a variety of atmospheric species and meteorological fields. Therefore, it is necessary to evaluate the model’s output relevant to O₃ production in an urban environment and investigate potential biases.

This study uses integrated remote sensing from a ceilometer, a wind LIDAR, the PANDORA spectrometer, and satellite Sentinel-5, and surface observations to investigate the spatial and temporal variability of NO₂, O₃, and planetary-boundary-layer height (PBLH) in August 2020 and 2021.

At first, surface-level and column NO₂ was observed from the co-located in-situ samplers and the PANDORA spectrometers at City College of New York (CCNY) and Queens College (QC) sites in New York City area. Then, the NO₂ and O₃ temporal variations at the two sites were compared and indicated a strong correlation for O₃ and a moderate correlation for NO₂. Meanwhile, the TROPOMI observations show spatial variation of tropospheric column NO₂.

The performance of the model’s product was evaluated using integrated observations and showed to be in good agreement with observations for the surface O₃ at the two sites for the month of August 2020. For the surface NO₂, the model forecast product generally showed similar diurnal variation but over-predicted the peak values likely related to complex urban emission sources and NO₂ vertical mixing in the PBL. The correlation analysis of the model and observation data over weekdays and weekends were conducted that demonstrated the increased emission effects from the vehicular traffic during weekdays. The O₃-NO₂ titration from the model showed good consistency with the observations. Additionally, O₃-NO₂ variations from the month of August 2021 were evaluated and compared against the levels in 2020.

How to cite: Kulko, M., Liang, M., McQueen, J., Huang, H.-C., Strobach, E., Wu, Y., and Moshary, F.: Analysis of NO2 and O3 variation in 2020 and 2021 and application to evaluate the GFS-CMAQ model forecast in New York city, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10840, https://doi.org/10.5194/egusphere-egu22-10840, 2022.

Large amounts of energy consumption in recent years have not only increased air pollution and greenhouse gas emissions, but have also released more anthropogenic heat into the atmosphere. However, the latter was overlooked in previous air quality and pollution-related health impacts studies. Here we use the atmospheric chemistry model coupled the exposure mortality model to investigate the effects of increased anthropogenic heat flux on PM_2.5 pollution and related health burden in China. We find the ignoring anthropogenic heat leads nighttime PM_2.5 concentrations to be overestimated, especially in metropolitan areas. The rising anthropogenic heat flux between 2000-2016 decreases surface PM_2.5 by 4 ug·m^-3 in Chinese urban region through altering microphysical processes and enhancing vertical mixing. Furthermore, the anthropogenic heat changes could avoid additional 15% (47 thousand) premature deaths, compare to anthropogenic emission reductions. Our findings indicate that anthropogenic heat should be included in air quality modeling and reveal the health benefit of energy use from a microphysical standpoint.

How to cite: Liu, Z. and Zhang, L.: Anthropogenic heat helps reduce PM2.5 pollution and related health burden in China, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11077, https://doi.org/10.5194/egusphere-egu22-11077, 2022.

Predicting air quality in megacities is challenging due to the diversity and variability of emission sources, as well as the specific meteorology and photochemistry occurring in the urban boundary layer.

São Paulo is by far the largest city in South America, one of the biggest megacities of the world, located near the coast and on a plateau at about 800 m above sea level, in a tropical climate. A megacity such as São Paulo is therefore a challenge for regional air quality models, which must be used at a resolution high enough to sufficiently accurately represent the processes leading to the high concentrations and high diurnal variability of the main pollutants. On the other hand, the measurement network is composed of 26 stations within the metropolitan area and another 63 within the state of São Paulo mostly in or near other cities, which constitutes an excellent support for evaluating the model outputs.

In this study, we assess the strengths and weaknesses of modeled concentrations of regulated pollutants (CO, O3, NO2, PM2.5, PM10), over three contrasting time periods in 2019. Four Chemistry-Transport models are involved in this intercomparison of high-resolution modeling results, less than 5 km. We study primary pollutants, meteorology, photochemistry as well as the performance of ozone and PM2.5 alerts when WHO air quality standards are not met. The results show that all models have good performance depending on the period and pollutants, and the performance of multi-model median is the best, as has already been shown for other regions.

In the framework of the KLIMAPOLIS project, the perspective of our study is to build an operational air quality forecasting system for the São Paulo region based on ensemble forecasts.

How to cite: Deroubaix, A., Hoelzemann, J., Duarte, E., Franke, P., Elbern, H., de Fatima Andrade, M., Lange, A.-C., Martins, L., Pedruzzi, R., Toledo, T., Von-Marttens, L., Ynoue, R. Y., and Brasseur, G.: Intercomparison of air quality models in São Paulo, towards an operational ensemble forecasts system, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11591, https://doi.org/10.5194/egusphere-egu22-11591, 2022.

In the past decade, the introduction of intensive clean air policies across China has led to a decline in particulate matter and NO_x concentrations, responsible for poor air quality detrimental to human health¹. Recent studies suggest that Beijing’s anthropogenic emissions of NO_x­ and PM_2.5 have reduced by 83.6% and 54.7% respectively, as a result of the Clean Air Action Plan, implemented in 2013.² However, despite much progress, concentrations of surface leave O₃, another harmful pollutant, have increased. In Beijing, O₃ increased at a rate of approximately 5% per year between 2013 and 2017_, with a mean increase of 19.32% per year observed at one monitoring site in the city.³ Due to the complex chemical processing leading to O₃ production, reductions in NO_x and PM may have inadvertently led to the increased secondary formation of O₃. To fully understand the chemical processes leading to surface-level O₃ production, a detailed analysis of its photochemical precursor species, volatile organic compounds (VOCs) and NO_x, and the role of aerosol-radical interactions, is required. This study utilises a detailed chemical box model to examine the propensity of observed VOCs at a site in Beijing to undergo oxidation, forming radical species, leading to in situ ozone production. The impact of the heterogenous uptake of the hydroxyl radical onto aerosol surfaces is also assessed.

During May/June 2017, concentrations of a large range of VOCs, NO_x, CO and O₃ were continuously measured at the Institute of Atmospheric Physics (IAP), an urban site in central Beijing. Measurements were taken as part of the Air Pollution and Human Health-Beijing (APHH) project. During the observation period, O₃ concentrations regularly breached recommended WHO 8-hour exposure limits of 50 ppb, with maximum concentrations exceeding 150 ppb. The sensitivity of in situ ozone production to changes in the observed reactive VOCs, NO_x, and aerosol surface area, are explored in detail using a chemical box model incorporating the Master Chemical Mechanism. The model is used to investigate the chemical regime of the measurement site in Beijing, and the key reactive species leading to in situ ozone production in the city are identified. This study aims to highlight the key species that could be targeted in future pollution reduction policies, to alleviate the continued increase in O₃ production rates in the city of Beijing.

1. Zhang, Q. et al.: Drivers of improved PM₅ air quality in China from 2013 to 2017, P. Natl. Acad. Sci. USA, 116, 24463–24469, 2019.

2. Cheng, J. et al.: Dominant role of emission reduction in PM_2.5 air quality improvement in Beijing during 2013–2017: a model-based decomposition analysis. Atmos. Chem. Phys., 19(9), 6125–6146, 2019.

3. Squires, F. A: Gas Phase Air Pollution in Remote and Urban Atmospheres: From then Azores to Beijing, PhD thesis, 2020.

How to cite: Nelson, B., Lee, J., Hopkins, J., and Rickard, A.: Examining the sensitivity of in situ ozone production to its precursor chemical species in Beijing, China, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4282, https://doi.org/10.5194/egusphere-egu22-4282, 2022.

Human-made halocarbons contribute about 11 % of the anthropogenically caused radiative forcing by long-lived greenhouse gases. Moreover, chlorinated or brominated halocarbons cause stratospheric ozone depletion. Synthetic halocarbons are emitted to the atmosphere by a wide range of production or consumption-related activities, being used as foam blowing, cooling, or fire extinguishing agents for example. To derive observation-based estimates of halocarbon emissions so-called "top-down" inverse modeling methods have been developed. These methods rely on global atmospheric observations from long-term halocarbon measurement networks such as the Advanced Global Atmospheric Gases Experiment (AGAGE) and the National Oceanic and Atmospheric Administration (NOAA). However, to assess halocarbon emissions on a country to regional level and to complement national emission inventories by top-down methods, measurements are required, which capture regional pollution events.

We present 18 months of continuous, high-frequency, high-precision halocarbon measurements from the Beromünster and Sottens tall towers (Swiss Plateau). Together, the two sites are sensitive to the most densely populated and industrialized region of Switzerland and parts of southeastern France. For analysis, hourly two-liter air samples were pre-concentrated at low temperatures (down to -165 ^oC), before the analytes were separated by gas chromatography and detected by quadrupole mass spectrometry (GC-MS).

Based on the measured concentration records, we assessed Swiss emissions and source regions of 28 halocarbons, covering the halocarbons of the Montreal and Kyoto Protocols. This includes the banned chlorofluorocarbons (CFCs) and halons, the regulated hydrochlorofluorocarbons (HCFCs), hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs), as well as the recently introduced unregulated hydrofluoroolefins (HFOs). The emissions were quantified using two independent top-down methods: a tracer ratio method and a Bayesian inversion based on regional atmospheric transport modeling.

We found good agreement between our top-down results and the emissions reported in the Swiss national greenhouse gas inventory for the major HFCs, HFC-125 and HFC-32, for which we calculated emissions of 100 Mg yr^-1 and 45 Mg yr^-1, respectively. For HFC-134a, our calculated emissions of 280 Mg yr^-1 hint at an overestimation of the Swiss national inventory. For the CFCs and HCFCs, we observed moderately elevated atmospheric concentrations with the corresponding emissions likely being related to the ongoing outgassing from existing banks. For the recently phased-in HFOs HFO-1234yf, HFO-1234ze(E), and HCFO-1233zd(E), we report the first national emission numbers, totaling to 56 Mg yr^-1. In addition, we present the first quantitative atmospheric measurements of the newly marketed HFO-1336mzz(Z), belonging to the group of emerging unsaturated halocarbons, of which the future environmental impacts are yet unclear.

To continue resolving the picture for Europe, another 6 months (December 2021 to May 2022) measurement campaign is currently being conducted in the Netherlands. The aim is to investigate local halocarbon emissions and locate regional emission sources with the above-described methods.

How to cite: Rust, D., Katharopoulos, I., Vollmer, M. K., Henne, S., Emmenegger, L., Zenobi, R., and Reimann, S.: Assessing Halogenated Greenhouse Gas Emissions from Regional Atmospheric Measurements, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6867, https://doi.org/10.5194/egusphere-egu22-6867, 2022.