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Surface ozone (O3) pollution has adverse impacts on the yield of winter wheat. The North China Plain (NCP), one of the globally significant primary regions for winter wheat production, has been frequently plagued by severe O3 pollution in recent years. In this study, the effects of O3 pollution on winter wheat yield and economic impact were evaluated in the NCP during the 2015–2018 seasons using the regional atmospheric chemical transport model (WRF-Chem), O3 metrics including the phytotoxic surface O3 dose above 12 nmol m−2 s−1 (POD12), and the accumulated daytime O3 above 40 ppb (AOT40). Results showed that the modeled O3, exposure-based AOT40, and flux-based POD12 increased during the winter wheat growing season from 2015 to 2018. The annual average daytime O3, exposure-based AOT40, and flux-based POD12 were 44 ppb, 5.32 ppm h, and 1.78 mmol m−2, respectively. During 2015–2018, winter wheat relative production loss averaged 10.9% with AOT40 and 14.6% with POD12. This resulted in an average annual production loss of 12.4 million metric tons, valued at approximately USD 4.5 billion. This study enhances our understanding of the spatial sensitivity of winter wheat to O3 impacts, and suggests that controlling O3 pollution during the key growth stages of winter wheat or improving its O3 tolerance will enhance food security. [ABSTRACT FROM AUTHOR]

In this study, high‐resolution CO2 concentration data were generated for East Asia to analyse long‐term changes in atmospheric CO2 concentrations, as East Asia is an important region for understanding the global carbon cycle. Using the Weather Research and Forecasting model coupled with Chemistry (WRF‐Chem), atmospheric CO2 concentrations were simulated in East Asia at a resolution of 9 km for a period of 10 years (2009–2018). The generated CO2 concentration data include CO2 concentrations, biogenic CO2 concentrations, anthropogenic CO2 concentrations, oceanic CO2 concentrations, biospheric CO2 uptake, biospheric CO2 release and meteorological variables at 3‐h intervals. The simulated high‐resolution CO2 concentrations, biogenic CO2 concentrations and anthropogenic CO2 concentrations are stored in NetCDF‐4 (Network Common Data Form, version 4) format and are available for download at https://doi.org/10.7910/DVN/PJTBF3. The simulated annual mean surface CO2 concentrations in East Asia were 391.027 ppm in 2009 and 412.949 ppm in 2018, indicating an increase of 21.922 ppm over the 10‐year period with appropriate seasonal variabilities. The monthly mean CO2 concentrations in East Asia were verified using surface CO2 observations and satellite column‐averaged CO2 mole fraction (XCO2) from Orbiting Carbon Observatory 2 (OCO‐2). Based on surface CO2 observations and OCO‐2 XCO2 concentrations, the average root‐mean‐square error (RMSE) of the simulated CO2 concentrations in WRF‐Chem was 2.474 and 0.374 ppm, respectively, which is smaller than the average RMSE of the low‐resolution CarbonTracker 2019B (CT2019B) simulation. Therefore, the simulated high‐resolution atmospheric CO2 concentrations in East Asia in WRF‐Chem over 10 years are reliable data that resemble the observed values and could be highly valuable in understanding the carbon cycle in East Asia. [ABSTRACT FROM AUTHOR]

Air pollution from fine particulate matter (PM2.5) has been associated with various health implications that can lead to increased morbidity and excess mortality. Epidemiological and toxicological studies have shown that carbonaceous particles (black carbon and organic aerosols) may be more hazardous to human health than inorganic ones. Health impact studies and emission reduction policies are based on total PM2.5 concentration without differentiating the more harmful components. In such assessments, PM2.5 and their sub-component concentrations are usually modeled with air quality models. Organic aerosols have been shown to be consistently underestimated, which may affect excess mortality estimates. Here, we use the WRF-Chem model to simulate PM2.5 (including carbonaceous particles) over the wider European domain and assess some of the main factors that contribute to uncertainty. In particular, we explore the impact of anthropogenic emissions and meteorological modeling on carbonaceous aerosol concentrations. We further assess their effects on excess mortality estimates by using the Global Exposure Mortality Model (GEMM). We find that meteorological grid nudging is essential for accurately representing both PM2.5 and carbonaceous aerosols and that, for this application, results improve more significantly compared to spectral nudging. Our results indicate that the explicit account of organic precursors (semi-volatile and intermediate-volatile organic carbons—SVOCs/IVOCs) in emission inventories would improve the accuracy of organic aerosols modeling. We conclude that uncertainties related to PM2.5 modeling in Europe lead to a ∼15% deviation in excess mortality, which is comparable to the risk model uncertainty. This estimate is relevant when all PM2.5 sub-components are assumed to be equally toxic but can be higher by considering their specific toxicity. [ABSTRACT FROM AUTHOR]

On July 21, 2012, a catastrophic precipitation event occurred in Beijing, highlighting the serious threat of extreme precipitation on socio-economic development and human health under climate change. Nevertheless, whether, how and to what extent aerosols and urbanization, as the two main influencing factors of urban extreme precipitation, have affected this highly damaging extreme event remains largely unexplored. Here, we employed the weather research and forecasting model coupled with chemistry (WRF-Chem) and a single-layer urban canopy model to investigate the influences of urbanization, aerosols and their interactions on this extreme precipitation event. We found that the joint intensification effects of urbanization and aerosols on extreme precipitation events greatly enhance its negative influence on megacities. The results indicate that aerosols are enhanced by increasing cloud droplet numbers, thereby intensifying the feedback between precipitation and latent heating. Consequently, the total precipitation increased by 22.6%, raising the precipitation in the Beijing area increase by at least 50 mm. By stimulating atmospheric instability and strengthening vertical air motion (over 0.25 m s−1), the urban heat island effect considerably influences the temporal and spatial distributions of extreme precipitation events, resulting in an increase in warm cloud precipitation (80%) and a decrease (30%) in frontal precipitation. Consequently, joint intensification effects resulted in more concentrated precipitation in the southwest of Beijing, leading to a substantial increase (more than 40%, ∼80 mm). This condition may be an important reason for the most severe disasters in the southwest of Beijing.

Abstract In this study, high‐resolution CO2 concentration data were generated for East Asia to analyse long‐term changes in atmospheric CO2 concentrations, as East Asia is an important region for understanding the global carbon cycle. Using the Weather Research and Forecasting model coupled with Chemistry (WRF‐Chem), atmospheric CO2 concentrations were simulated in East Asia at a resolution of 9 km for a period of 10 years (2009–2018). The generated CO2 concentration data include CO2 concentrations, biogenic CO2 concentrations, anthropogenic CO2 concentrations, oceanic CO2 concentrations, biospheric CO2 uptake, biospheric CO2 release and meteorological variables at 3‐h intervals. The simulated high‐resolution CO2 concentrations, biogenic CO2 concentrations and anthropogenic CO2 concentrations are stored in NetCDF‐4 (Network Common Data Form, version 4) format and are available for download at https://doi.org/10.7910/DVN/PJTBF3. The simulated annual mean surface CO2 concentrations in East Asia were 391.027 ppm in 2009 and 412.949 ppm in 2018, indicating an increase of 21.922 ppm over the 10‐year period with appropriate seasonal variabilities. The monthly mean CO2 concentrations in East Asia were verified using surface CO2 observations and satellite column‐averaged CO2 mole fraction (XCO2) from Orbiting Carbon Observatory 2 (OCO‐2). Based on surface CO2 observations and OCO‐2 XCO2 concentrations, the average root‐mean‐square error (RMSE) of the simulated CO2 concentrations in WRF‐Chem was 2.474 and 0.374 ppm, respectively, which is smaller than the average RMSE of the low‐resolution CarbonTracker 2019B (CT2019B) simulation. Therefore, the simulated high‐resolution atmospheric CO2 concentrations in East Asia in WRF‐Chem over 10 years are reliable data that resemble the observed values and could be highly valuable in understanding the carbon cycle in East Asia.

In the heavy industrial city of Northeast China, there has been a significant decrease in particulate matter pollution while experiencing a sharp increase in ozone (O3) pollution. However, the main influencing factors and source contributions to O3 remain unclear. Taking the case of Siping as an example, this study analyzed the spatiotemporal characteristics, assessed local source contributions to O3, and revealed regional transmission effects using numeric simulation and statistical methods. Temporally, higher O3 concentrations were observed in summer and the afternoon, with hourly peaks up to 254 µg/m3. Spatially, O3 pollution was mainly contributed by background concentrations (34.52%), external transport (34.50%), and local emissions (30.98%) during the case study period (June 11–18, 2021). Among the local emission sources, biological emissions, the industrial sector, and the traffic sector accounted for 35.30%, 32.09%, and 23.58% of the O3 concentration, respectively. For regional atmospheric transmission, high O3 pollution was accompanied by wind from the southwest directions, and the trajectory of air mass transport suggests that eastern Mongolia, the Korean Peninsula, and its neighboring regions contribute to O3 pollution. Furthermore, sensitivity analysis showed that O3 pollution in Siping is a co-controlled region by anthropogenic volatile organic compounds (AVOCs) and NOX, which implies control in an optimal ratio of VOCs and NOX emissions. Thus, our results highlight the importance of joint prevention and control of O3 pollution in the region, optimization of biogenic landscape ecology, and control of VOCs and NOx in both the industrial and transport sectors. [ABSTRACT FROM AUTHOR]

This study investigates the impact of dust on radiation over the Arabian Peninsula (AP) during the reported high, low, and normal dust seasons (March–August) of 2012, 2014, and 2015, respectively. Simulations were performed using the Weather Research and Forecasting model coupled to a Chemistry module (WRF‐Chem). The simulated seasonal horizontal and vertical dust concentrations, and their interannual distinctions, match well with those from two ground‐based AERONET observations, and measurements from MODIS and CALIOP satellites. The maximum dust concentrations over the dust‐source regions in the southern AP reach vertically upto 700 hPa during the high dust season, but only upto 900–950 hPa during the low/normal dust seasons. Stronger incoming low‐level winds along the southern Red Sea and those from Iraq bring in higher‐than‐normal dust during the high dust summers. We conducted a sensitivity experiment by switching‐off the dust module to assess the radiative perturbations due to dust. The results suggest that active dust‐module improved the fidelity of simulated radiation fluxes distributions at the surface and top of the atmosphere vis‐à‐vis Clouds and the Earth's Radiant Energy System (CERES) measurements. Dust results in a 26 Wm−2 short‐wave (SW) radiative forcing in the tropospheric‐column over the AP. The SW radiative forcing increases by another 6–8 Wm−2 during the high dust season due to the increased number of extreme dust days, which also amplifies atmospheric heating. During extreme dust days, the heating rate exhibits a dipolar structure, with cooling over the Iraq region and warming of 40%–60% over the southern‐AP. Plain Language Summary: Dust is the dominant tropospheric aerosol in the Arabian Peninsula (AP). High dust loading and prolonged episodes are crucial in dust‐radiation feedback mechanisms. WRF‐Chem successfully simulated the spatial distribution of dust aerosols and their underlying dust‐transport mechanisms over the study region. Model results reveal that dust aerosols influence surface and atmospheric radiation, resulting in cooling at the surface and warming in the overlying atmosphere. Extreme dust days exhibit significant heating in the south and cooling in the north. This study enhances our understanding of dust‐aerosol interactions with regional meteorology, aiding in better weather and climate prediction in dust‐laden regions like the AP. Key Points: This study explores the influence of dust aerosols on radiative fluxes over the Arabian Peninsula (AP)WRF‐Chem model effectively captures the physical mechanisms of dust transportExtreme dustiness significantly modulates the radiative fluxes, thereby exerting a notable influence on the atmospheric heating rates [ABSTRACT FROM AUTHOR]

Dust transported from rangelands of the Southwestern United States (US) to mountain snowpack in the Upper Colorado River Basin during spring (March‐May) forces earlier and faster snowmelt, which creates problems for water resources and agriculture. To better understand the drivers of dust events, we investigated large‐scale meteorology responsible for organizing two Southwest US dust events from two different dominant geographic locations: (a) the Colorado Plateau and (b) the northern Chihuahuan Desert. High‐resolution Weather Research and Forecasting coupled with Chemistry model (WRF‐Chem) simulations with the Air Force Weather Agency dust emission scheme incorporating a MODIS albedo‐based drag‐partition was used to explore land surface‐atmosphere interactions driving two dust events. We identified commonalities in their meteorological setups. The meteorological analyses revealed that Polar and Sub‐tropical jet stream interaction was a common upper‐level meteorological feature before each of the two dust events. When the two jet streams merged, a strong northeast‐directed pressure gradient upstream and over the source areas resulted in strong near‐surface winds, which lifted available dust into the atmosphere. Concurrently, a strong mid‐tropospheric flow developed over the dust source areas, which transported dust to the San Juan Mountains and southern Colorado snowpack. The WRF‐Chem simulations reproduced both dust events, indicating that the simulations represented the dust sources that contributed to dust‐on‐snow events reasonably well. The representativeness of the simulated dust emission and transport in different geographic and meteorological conditions with our use of albedo‐based drag partition provides a basis for additional dust‐on‐snow simulations to assess the hydrologic impact in the Southwest US. Plain Language Summary: Dust transported from rangelands of the Southwestern United States (US) to the mountain snowpack in the Upper Colorado River Basin during spring (March–May) is a growing problem for water resources and agriculture. Understanding the drivers of dust events is essential to better forecast the possible impact of dust on water resources. We investigated the weather conditions that led to two dust events originating from the Colorado Plateau and northern Chihuahuan Desert. We also performed computer simulations with an improved dust emission model to explore the influence of vegetation on the susceptibility of landscapes to wind erosion during dust events. Our meteorological analysis revealed commonalities in the upper‐level meteorology before dust event formation and provided valuable insights into where and when high‐impact dust events may occur. However, further investigation is needed to generalize the impact of jet stream interaction on dust events' intensity. Our simulations represented the dust sources reasonably well by using an improved dust emission model. The improved dust emission and transport simulation under different meteorological and geographical conditions provided a basis for future dust‐on‐snow simulations to assess the hydrological impact in the Southwestern US. Key Points: Large‐scale meteorological analysis and dust emission and transport simulation of Southwest US dust‐on‐snow eventsPolar and Sub‐tropical jet stream interaction was a common upper‐level meteorological feature to Southwest US dust eventsSimulated dust source areas on the Colorado Plateau and Chihuahuan Desert reflect observed dust emission hot spots [ABSTRACT FROM AUTHOR]

Understanding the mechanisms behind tropospheric ozone pollution formation is crucial for developing precise pollution prevention and control policies. However, the contribution of different sectors to ozone generation has not been thoroughly elucidated. Utilizing the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), this study simulated the spatiotemporal variations of ozone concentrations in Henan Province of China under different sectoral emission reduction scenarios. We also quantified the contribution of different sectors to ozone concentrations. Significant spatiotemporal disparities were observed in annual ozone concentrations across different scenarios. Higher ozone concentrations in scenarios where emissions were zeroed out from the industrial, power, and residential sectors were concentrated in the southwestern region of Henan province, while lower ozone concentrations were concentrated in the northeastern region. Conversely, higher ozone concentrations in the transportation sector zero-out scenario were concentrated in the northwestern region. Overall, ozone concentrations peaked at 50 ppb in summer, followed by spring (20 ppb) and autumn (21 ppb), with the lowest concentrations of 11 ppb observed in winter. The power sector was found to contribute the most to yearly ozone concentrations was about −12 to 9 ppb, followed by the residential sector, while the transportation and industrial sectors made the least contributions. Seasonal contributions to ozone concentrations from the industrial, power, and residential sectors were primarily observed in spring, followed by summer, whereas the transportation sector’s contribution was mainly concentrated in summer.

Abstract With its high energy consumption and pollutant emissions, the iron and steel industry is a significant source of air pollution and carbon emissions in the Beijing–Tianjin–Hebei (BTH) region. To improve air quality and reduce greenhouse gas emissions, a series of policies involving ultra-low emission, synergistic reduction of pollution, and carbon application have been implemented in the region. This study has assessed air pollutant and CO2 emission patterns in the iron and steel industry of the region by employing co-control effects coordinate system, marginal abatement cost curve, and numerical modeling, along with the synergistic benefits of typical technologies. The results have demonstrated that: (1) the intensive production activities pertinent to iron and steel enterprises has contributed greatly to the emission in Tangshan and Handan, where the sintering process is the main source of SO2, NOx, PM2.5, and CO, accounting for 64.86%, 55.15%, 29.98%, and 46.43% of the total emissions, respectively. (2) Among the typical pollution control and reduction measures, industrial restructuring and adjustment of the energy-resource structure have led to the greatest effects on emission reduction. Technologies exhibiting great potential in emission reduction and high-cost efficiency such as Blast Furnace Top Gas Recovery Turbine Unit (TRT) need to be promoted. (3) In Tangshan city with the highest level of steel production, the iron and steel production activities contributed to the concentration of 30.51% of PM2.5, 50.67% of SO2, and 42.54% of NO2 during the non-heating period. During the heating period, pollutants pertinent to the combustion of fossil energy for heating have increased, while iron and steel induced emissions have decreased to 23.7%, 34.32%, and 29.13%, respectively. By 2030, it is speculated that the contribution of the iron and steel industry to air quality will be significantly decreased as result of successful implementation of ultra-low emission policies and typical synergistic reduction technologies.

With its high energy consumption and pollutant emissions, the iron and steel industry is a significant source of air pollution and carbon emissions in the Beijing–Tianjin–Hebei (BTH) region. To improve air quality and reduce greenhouse gas emissions, a series of policies involving ultra-low emission, synergistic reduction of pollution, and carbon application have been implemented in the region. This study has assessed air pollutant and CO2 emission patterns in the iron and steel industry of the region by employing co-control effects coordinate system, marginal abatement cost curve, and numerical modeling, along with the synergistic benefits of typical technologies. The results have demonstrated that: (1) the intensive production activities pertinent to iron and steel enterprises has contributed greatly to the emission in Tangshan and Handan, where the sintering process is the main source of SO2, NOx, PM2.5, and CO, accounting for 64.86%, 55.15%, 29.98%, and 46.43% of the total emissions, respectively. (2) Among the typical pollution control and reduction measures, industrial restructuring and adjustment of the energy-resource structure have led to the greatest effects on emission reduction. Technologies exhibiting great potential in emission reduction and high-cost efficiency such as Blast Furnace Top Gas Recovery Turbine Unit (TRT) need to be promoted. (3) In Tangshan city with the highest level of steel production, the iron and steel production activities contributed to the concentration of 30.51% of PM2.5, 50.67% of SO2, and 42.54% of NO2 during the non-heating period. During the heating period, pollutants pertinent to the combustion of fossil energy for heating have increased, while iron and steel induced emissions have decreased to 23.7%, 34.32%, and 29.13%, respectively. By 2030, it is speculated that the contribution of the iron and steel industry to air quality will be significantly decreased as result of successful implementation of ultra-low emission policies and typical synergistic reduction technologies. [ABSTRACT FROM AUTHOR]

Land cover is a key factor affecting dust emissions. Substantial changes in land cover have occurred due to human activities and climate change in northern China. However, the extent to which these changes influence dust emissions is still controversial. Here, we explored the specific impact of land use type transformation on dust emissions between 2000 and 2020 by using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) from the perspective of land cover changes. Two scenarios were set up and compared to quantify this impact. One scenario was using the land cover data in 2000, and the other scenario was to use the land cover data in 2020. Both scenarios were driven by the initial meteorological conditions in 2020. Results indicated that the land cover changes between 2000 and 2020 reduced dust emissions in northern China, but the weakened intensity showed obvious spatial differences. Different land use conversion types had significant differences in their impact on dust emissions. Transforming bare areas to water bodies can reduce dust emissions by up to -3.62 g m-2 year-1. This is followed by the change from bare areas to sparse vegetation areas, which can decrease dust emissions by -2.9 g m-2 year-1, and then by the conversion from bare areas to cropland, with a reduction of -2.57 g m-2 year-1. These findings can offer methodologies and data support for the quantitative evaluation of the effects of land cover changes on dust emissions. They can also serve as a reference for environmental management when formulating land use policies. [ABSTRACT FROM AUTHOR]

Assessing long-term air quality trends helps evaluate the effectiveness of adopted air pollution control policies. A decade of SAFAR observations revealed that the trend of particulate matter (PM2.5 and PM10) in Delhi shows a reduction of 2.98 ± 0.53 µg/m³/y (4.91 ± 1.01 µg/m³/y) or overall 29% (23.7%) reduction between 2011 and 2021 while vehicles almost doubled but with the implementation of cleaner technologies and stricter industrial regulation. Seasonal negative trends of pre-monsoon (March-April-May; -3.43 ± 1.02 µg/m³/y) and postmonsoon (October-November; -4.51 ± 1.59 µg/m³/y) are relatively higher. The role of trends in dust storms, fire counts and annual rainy days are also discussed. The contribution of meteorology to the trend is estimated using WRF-Chem simulation of PM2.5 for October when maximum stubble burning occurs and gets transported to Delhi. The model is run with the meteorological initial conditions of 2018, 2015, and 2011 while keeping the emissions of 2018 with identical model configuration and found that meteorology contributed 9.8% in October, while the observed decline in PM2.5 is 35% (best fit) and 25% (value). The study identifies the governmental control measures at various levels and green initiatives as the significant contributors to air quality improvement during 2011-2021. [ABSTRACT FROM AUTHOR]

This study addresses the pressing issue of urban air pollution impact, emphasizing the need for emissions control to ensure environmental equity. Focused on the Toluca Valley Metropolitan Area (TVMA), this research employs air quality modeling to examine ozone, sulfur dioxide, nitrogen dioxide, and carbon monoxide concentrations during three different periods in 2019. It quantitatively assesses the performance of a state-of-the-art air quality model while evaluating the efficacy of a No-Driving day mitigation measure program, similar to the one which is currently implemented in Mexico City. Using an updated national emissions inventory for 2016, this study highlights the model capability of representing ozone formation and shows that reducing mobile emissions of key pollutants contributes to lowering downwind surface ozone levels, albeit with a minimal local impact. The insights and tools from this work hold potential value for decision-making in the broader Megalopolis context, aligning with global efforts to comprehend and mitigate urban air pollution impacts. [ABSTRACT FROM AUTHOR]

The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), a type of online coupled chemistry-meteorology model (CCMM), considers the interaction between air quality and meteorology to improve air quality forecasting. Meteorological data assimilation (DA) can be used to reduce uncertainty in meteorological field, which is one factor causing prediction uncertainty in the CCMM. In this study, WRF-Chem and three-dimensional variational DA were used to examine the impact of meteorological DA on air quality and meteorological forecasts over the Korean Peninsula. The nesting model domains were configured over East Asia (outer domain) and the Korean Peninsula (inner domain). Three experiments were conducted by using different DA domains to determine the optimal model domain for the meteorological DA. When the meteorological DA was performed in the outer domain or both the outer and inner domains, the root-mean-square error (RMSE), bias of the predicted particulate matter (PM) concentrations, and the RMSE of predicted meteorological variables against the observations were smaller than those in the experiment where the meteorological DA was performed only in the inner domain. This indicates that the improvement of the synoptic meteorological fields by DA in the outer domain enhanced the meteorological initial and boundary conditions for the inner domain, subsequently improving air quality and meteorological predictions. Compared to the experiment without meteorological DA, the RMSE and bias of the meteorological and PM variables were smaller in the experiments with DA. The effect of meteorological DA on the improvement of PM predictions lasted for approximately 58–66 h, depending on the case. Therefore, the uncertainty reduction in the meteorological initial condition by the meteorological DA contributed to a reduction of the forecast errors of both meteorology and air quality. [ABSTRACT FROM AUTHOR]

Surface ozone (O3) pollution has adverse impacts on the yield of winter wheat. The North China Plain (NCP), one of the globally significant primary regions for winter wheat production, has been frequently plagued by severe O3 pollution in recent years. In this study, the effects of O3 pollution on winter wheat yield and economic impact were evaluated in the NCP during the 2015–2018 seasons using the regional atmospheric chemical transport model (WRF-Chem), O3 metrics including the phytotoxic surface O3 dose above 12 nmol m−2 s−1 (POD12), and the accumulated daytime O3 above 40 ppb (AOT40). Results showed that the modeled O3, exposure-based AOT40, and flux-based POD12 increased during the winter wheat growing season from 2015 to 2018. The annual average daytime O3, exposure-based AOT40, and flux-based POD12 were 44 ppb, 5.32 ppm h, and 1.78 mmol m−2, respectively. During 2015–2018, winter wheat relative production loss averaged 10.9% with AOT40 and 14.6% with POD12. This resulted in an average annual production loss of 12.4 million metric tons, valued at approximately USD 4.5 billion. This study enhances our understanding of the spatial sensitivity of winter wheat to O3 impacts, and suggests that controlling O3 pollution during the key growth stages of winter wheat or improving its O3 tolerance will enhance food security.

Lightning‐generated nitrogen oxides (LNOx) have an impact on the concentration of ground‐level ozone which acts as a toxic air pollutant, thereby negatively influencing human health and the environment. To understand the impact of LNOx on ground‐level ozone, we simulated four thunderstorm events in Tehran using the WRF‐Chem model. As observations of LNOx are not available, we evaluated the temporal distribution of the simulated ground‐level ozone concentration against an air quality monitoring station. We also compared the simulation results against the spatial distribution of the total column ozone from the Ozone Monitoring Instrument. WRF‐Chem performs well in the simulation of ground‐level ozone concentration, with the best performance for an event with the highest lightning activity (correlation coefficient of 0.91). The analysis of the spatial distribution of the observed and simulated total column ozone also indicates the good performance of WRF‐Chem. Hourly variation in the simulated LNOx during lightning activity is compared against both hourly variation in the observed ground‐level ozone and the number of lightning for four thunderstorm events. There is an agreement between the simulated LNOx and the observed ground‐level ozone during lightning for two events, with correlation coefficients of 0.55 and 0.57. LNOx emissions enhance ozone production in the middle to upper troposphere, which can subsequently contribute to an increase in ground‐level ozone by transport, vertical mixing, and chemistry. In addition, the initiation of chemical processes in response to cloud‐to‐ground lightning strikes may contribute to an increase in both LNOx and the concentration of ground‐level ozone. Plain Language Summary: Lightning‐generated nitrogen oxides (LNOx) contribute to higher ground‐level ozone, which acts as a harmful air pollutant for humans and the environment. We applied the WRF‐Chem model to simulate four thunderstorm events in Tehran, aiming to understand the impact of LNOx on ground‐level ozone concentration. Overall, WRF‐Chem performs well in the simulation of ground‐level ozone, particularly for an event with the highest lightning activity. The comparison of the spatial distribution of the observed and simulated total column ozone also indicates the good performance of WRF‐Chem. By comparing the simulated LNOx against the observed ground‐level ozone, we found that WRF‐Chem performs well for two thunderstorm events. The produced ozone in the middle to upper troposphere due to LNOx emissions can be transported downward and increase ground‐level ozone. Cloud‐to‐ground lightning strikes also contribute to an increase in both LNOx and ground‐level ozone pollution, which can negatively influence human health and the environment. Key Points: The simulated ground‐level ozone concentration is consistent with the observationThe initiation of chemical processes in response to cloud‐to‐ground lightning contributes to an increase in both LNOx and surface ozoneLNOx influence tropospheric ozone production, which can contribute to an increase in ground‐level ozone [ABSTRACT FROM AUTHOR]

Sulfate aerosol greatly contributes to wintertime haze pollution in emission‐intensive regions like the North China Plain (NCP) in China. Fast sulfate increase and accumulation are usually recorded during winter haze; however, the multiphase oxidation of sulfur dioxide (SO2) and the physical processes affecting near‐surface sulfate are not fully understood. By combining in situ observations and numerical simulations, we found that high sulfur oxidation ratios (>0.6) under heavily polluted conditions are associated with low clouds and fog over NCP, induced by the moist southerly airflow. Thick low clouds and high SO2 levels in NCP provide a reaction environment for sulfate production. The sulfate production rate in cloud water can reach 0.5–1.3 μg m−3 h−1. The results demonstrate that the vertical mixing of sulfate generated within the cloud water to the surface plays a significant role in rapid sulfate production, highlighting the importance of understanding cloud‐water processes in haze pollution. Plain Language Summary: Sulfate has been recognized as an important chemical component of atmospheric aerosols, especially during winter haze events. Rapid increases in sulfate concentrations are frequently observed during heavy pollution in the North China Plain (NCP) of China. However, the processes involved in the multiphase oxidation of sulfur dioxide (SO2) and the physical processes influencing sulfate variations near the surface remain unclear. In particular, the contribution of traditional in‐cloud sulfate production to the surface sulfate has been considered to be negligible in the NCP. Here, we revisited the role of in‐cloud sulfate production in the NCP by using ground‐based observations, radiosonde measurements, and model simulation. Our results indicate that the rapid conversion of SO2 to sulfates during heavy pollution is associated with the presence of low clouds and fog. We find that high sulfate production rates in cloud water lead to the rapid accumulation of sulfate, which is vertically mixed to the surface, resulting in a rapid increase in surface sulfate concentrations. This work sheds a new perspective on understanding the role of sulfate production in cloud water and its impact on air pollution. Key Points: High sulfur oxidation ratios under heavy pollution conditions in the North China Plain are associated with low clouds and fog formationSulfate production rates within cloud water can reach 0.5–1.3 μg m−3 h−1, with NO2 and O3 oxidation pathways dominatingVertical mixing of sulfate produced in cloud water to the surface causes a rapid increase in near‐surface sulfate concentration [ABSTRACT FROM AUTHOR]

The region surrounding the Tibetan Plateau (TP) is widely considered a primary global dust source, with mineral dust comprising a significant proportion of aerosols over the TP. Current research on TP dust has mainly focused on transport from the surrounding deserts, with little focus on dust emissions from the TP's interior. The erodibility factor used by the WRF‐Chem (ERODDEF) is 0 for the TP, so the model cannot simulate the dust emissions inside the plateau. Thus, we constructed a high‐resolution erodibility data set (ERODSDS) based on a reliable dust source distribution and intensity map. Based on the modified EROD map, the WRF‐Chem model was used to simulate dust emissions and direct radiative forcing on the TP in 2018. With the modified EROD map, WRF‐Chem can well simulate the temporal variation and spatial pattern of mineral dust on the plateau, which greatly improves the model's dust emissions simulation accuracy on the TP. Plain Language Summary: Due to certain limitations of the ERODDEF, the previous WRF‐Chem model was unable to accurately simulate dust emissions from the TP's interior. Thus, we constructed a more realistic ERODSDS and improved simulations of dust emissions and dust direct radiative forcing within the plateau. The west‐central part of the plateau is also an important source of dust emissions, and the amount of dust emitted within the plateau should not be neglected. Key Points: The WRF‐Chem model seriously underestimates local dust emissions on the Tibetan PlateauHigh‐precision erodibility data on the Tibetan Plateau is constructed to accurately describe the surface dust emission potentialThe temporal and spatial distribution of the local dust emission on the Tibetan Plateau was estimated [ABSTRACT FROM AUTHOR]

We analyzed a widespread dust event that influenced the Urmia Basin in northwestern Iran from 28 to 31 October 2017. To this end, we applied the Global Forecast System (GFS) data to investigate the origin and the mechanism of the formation of dust storms in this period, and the transport pathways of dust particles toward the Urmia Basin. We also used the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and compared the spatial distribution of the simulated dust against the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) and the Moderate Resolution Imaging Spectroradiometer (MODIS) visible image. A mid-tropospheric trough associated with positive relative vorticity contributed to the development of a surface low pressure and strong winds at lower levels in western Iraq, which caused the emission of dust from multiple sources. The analysis of the simulation results, satellite images, and MERRA-2 indicates that dust storms in western Iraq were mainly responsible for the occurrence of dust events in the Urmia Basin in late October 2017. Dust particles were lifted up to 450 hPa, which made it possible to pass high mountains in western Iran and reach the Urmia Basin. Dust concentration was higher in the eastern compared to the western and southern parts of Lake Urmia. Considering the dominance of westerlies in this region, this suggests that the dried parts of Lake Urmia act as a local source of dust. Our results have important implications for the understanding of the emergence of new sources of dust in the Urmia Basin and the potential impact of dust particles from these sources on climate and environment through a wide range of mechanisms. [ABSTRACT FROM AUTHOR]

Lightning‐induced nitrogen oxides (LNOx) can affect ozone (O3) through photochemical processes. However, the impact of LNOx on the Tibetan Plateau (TP) O3 valley, an area with a lower O3 column compared to surrounding areas, remains controversial. Prior to this study, the impact of monsoonal transport on LNOx and related effects on the TP O3 valley has been overlooked. The objectives of this study are to differentiate between locally generated LNOx and monsoon‐transported LNOx over the TP and to evaluate their impacts on tropospheric NOx vertical column density, tropospheric column O3, and O3 at different altitudes. The Weather Research and Forecasting model coupled with Chemistry model was used to replicate LNOx, NOx, and O3 over the TP during July 2010, for which nesting techniques and sensitivity experiments were implemented. The findings emphasize the importance of LNOx as a source of NOx in this region, with nonlocal lightning activity being the primary source. Conversely, the influence of locally generated LNOx on NOx levels over the TP is comparatively minor. Overall, LNOx contributes to an increase in O3 over the TP, but one order lower than the O3 depletion. The impact of LNOx on O3 varies across different altitude ranges; it is broadly "C" shaped, reflecting increase in O3 at near‐surface and in upper troposphere–lower stratosphere (UTLS) regions and decrease in the middle troposphere. The increase in surface‐level O3 over the TP is mainly caused by monsoon‐transported LNOx, while locally generated LNOx also plays a crucial role in O3 formation in the UTLS region. Plain Language Summary: Lightning‐induced nitrogen oxides (LNOx) play an important role in ozone (O3) production. However, the impact of LNOx on the Tibetan Plateau (TP) O3 valley, an area with a lower O3 column compared to surrounding areas, remains controversial. Prior to this study, the impact of monsoonal transport on LNOx and related effects on the TP O3 valley has been overlooked. In this research, we distinguish between locally generated LNOx over the TP and LNOx transported by the monsoon from surrounding areas, and we discuss their individual effects on NOx and O3 over the TP. We found that NOx over the TP is mainly composed of LNOx, with a higher proportion of monsoon‐transported LNOx than locally generated LNOx. Generally, LNOx increases O3 over the TP but the effect is small. The impact of LNOx on O3 varies across different altitude ranges; it is broadly "C" shaped, reflecting increase in O3 at near‐surface and in upper troposphere–lower stratosphere (UTLS) regions and decrease in the middle troposphere. The increase in surface‐level O3 over the TP is mainly caused by monsoon‐transported LNOx, while locally generated LNOx also plays a crucial role in O3 formation in the UTLS region. Key Points: Lightning‐induced nitrogen oxides and ozone over the Tibetan Plateau were simulated by Weather Research and Forecasting model coupled with Chemistry for 1 monthMonsoon‐transported lightning‐induced nitrogen oxides significantly contribute to Tibetan Plateau nitrogen oxidesLightning‐induced nitrogen oxides increase Tibetan Plateau ozone and the increment exhibits a C‐shaped curve in the vertical axis [ABSTRACT FROM AUTHOR]

In recent years, the issue of air pollution has garnered significant public attention globally, with a particular emphasis on the challenge of atmospheric fine particulate matter (PM2.5) pollution. The efficient and precise simulation of changes in pollutant concentrations, as well as their spatial and temporal distribution, is essential for effectively addressing the air pollution issue. In this paper, the WRF-Chem model is used to simulate the meteorological elements including temperature (T), relative humidity (RH), wind speed (WS), and pressure (P), and the concentrations of PM2.5 and PM10 atmospheric pollutants in December 2020 in Xuzhou City. Simultaneously, the ADMS-Urban model was employed to conduct a higher spatial resolution study of PM2.5 concentrations during the heavy pollution days of 11–12 December 2020 in Xuzhou City. The study shows that the WRF-Chem model can simulate the meteorological conditions of the study time period better, and the correlation coefficients (R) of pressure, temperature, wind speed, and relative humidity are 0.99, 0.87, 0.75, and 0.70, respectively. The WRF-Chem model can accurately simulate the PM2.5 concentration on clean days (R of 0.66), but the simulation of polluted days is not satisfactory. Therefore, the ADMS-Urban model was chosen to simulate the PM2.5 concentration on polluted days in the center of Xuzhou City. The ADMS-Urban model can simulate the distribution characteristics and concentration changes of PM2.5 around roads and buildings in the center of Xuzhou City. Comparing the simulation results of the two models, it was found that the two models have their own advantages in PM2.5 concentration simulation, and how to better couple the two models is the next research direction. [ABSTRACT FROM AUTHOR]

Elevated concentrations of particulate matter (PM) significantly deteriorate the air quality; however, the contributions from regional versus remote anthropogenic sources have remained uncertain over the western Indian region. In this regard, we have performed high-resolution regional modeling (WRF-Chem v3.9.1) to quantify the contribution of regional versus trans-regional anthropogenic sources to PM2.5 (fine PM) and PM2.5-10 (coarse PM) concentrations in contrasting seasons. Seasonal variability in spatial mean Aerosol Optical Depth (AOD) derived from the WRF-Chem model (0.21–0.42) agreed reasonably with MERRA-2 reanalysis (0.29–0.54) and MODIS satellite (0.23–0.51) over western India. Variability in surface PM2.5 and PM10 concentrations were also reproduced as per the benchmarks (|Fractional Bias| ≤ 60% and |Fractional Error| ≤ 75%) at most of the stations in this region. Results from sensitivity simulations reveal the dominant contribution of both regional and trans-regional anthropogenic sources to PM2.5 concentrations over western India in winter and post-monsoon, when PM2.5 concentrations are generally high. On the other hand, contribution from background levels (due to domain-wide natural emissions, fire emissions and pollutant transport from beyond domain boundaries) is highest during pre-monsoon and monsoon with a significant contribution of mineral dust especially to PM2.5-10 (coarse PM). Analysis of PM spatial distribution at ∼900hpa pressure level reveals greater relative contributions of trans-regional emissions and background levels compared to that near the surface. Our study highlights key roles of trans-regional anthropogenic emissions and mineral dust, besides the local and regional emissions, in air pollution over western India. The quantitative analyses presented here would be useful for designing measures to minimize health and environmental impacts in line with the objectives of the National Clean Air Programme (NCAP) in India.

This study investigates the impact of black carbon (BC) emissions on monsoon rainfall patterns across the Indian subcontinent. The results show that BC exerts localized warming effects, providing valuable insights into the mechanisms influencing the rainfall distribution across the Indian landmass. The study analyzes the vertical profile of mean tropospheric temperature differences between two sets of simulations: (i) with default BC emissions (WBC) and (ii) with BC emissions reduced by 99% (WoBC), conducted for JJAS, 2017, focusing on the region along the eastern coast. The analysis of the tropospheric temperature variations over the eastern coast reveals significant rainfall differences, primarily attributed to the intensification of convective rainfall. The results indicate that WoBC simulation leads to abnormal cooling in the lower troposphere and warming in the mid-upper troposphere, plausibly linked to the release of latent heat from the enhanced convective activity observed over the region. These alterations in the tropospheric temperature profile correspond remarkably well with the changes in the spatial distribution of rainfall over this area, providing valuable insights into the intricate dynamics of the climate system over this region.

In the present research, a statistical analysis of all pollution incidents occurring from 2015 to 2019 in the cities of the urban agglomeration centered on Shenyang was performed. The results indicated that heavy pollution mainly occurred during the heating season, and the main pollutants were (particulate matter) PM2.5 and PM10. It was also determined that the heavy pollution that occurred during the heating season in Shenyang was of the soot type. The weather research forecast-chemistry (WRF-Chem) was used to simulate the meteorological elements and particle concentration during the two heavy pollution periods in 2019 and compared the simulation data with the monitoring data to verify the simulation performance of the model. Results demonstrated that the model had a better simulation effect on temperature and pressure than on wind speed and wind direction. By comparing the hourly particle concentration data, it was found that the simulation results for pollutants obtained with the WRF-Chem model were lower than the measured values. The simulation effect on PM2.5 was better than that on PM10, and the simulation results were basically consistent in the high- and low-value areas, and the time of peak and valley was basically synchronous. It was proven that the selected parameterization scheme properly simulated the weather situation and changes in pollutants during heavy pollution events in the Shenyang area. These results verified the application value of the WRF-Chem model during the investigation of heavy pollution events.

Abstract Lightning‐generated nitrogen oxides (LNOx) have an impact on the concentration of ground‐level ozone which acts as a toxic air pollutant, thereby negatively influencing human health and the environment. To understand the impact of LNOx on ground‐level ozone, we simulated four thunderstorm events in Tehran using the WRF‐Chem model. As observations of LNOx are not available, we evaluated the temporal distribution of the simulated ground‐level ozone concentration against an air quality monitoring station. We also compared the simulation results against the spatial distribution of the total column ozone from the Ozone Monitoring Instrument. WRF‐Chem performs well in the simulation of ground‐level ozone concentration, with the best performance for an event with the highest lightning activity (correlation coefficient of 0.91). The analysis of the spatial distribution of the observed and simulated total column ozone also indicates the good performance of WRF‐Chem. Hourly variation in the simulated LNOx during lightning activity is compared against both hourly variation in the observed ground‐level ozone and the number of lightning for four thunderstorm events. There is an agreement between the simulated LNOx and the observed ground‐level ozone during lightning for two events, with correlation coefficients of 0.55 and 0.57. LNOx emissions enhance ozone production in the middle to upper troposphere, which can subsequently contribute to an increase in ground‐level ozone by transport, vertical mixing, and chemistry. In addition, the initiation of chemical processes in response to cloud‐to‐ground lightning strikes may contribute to an increase in both LNOx and the concentration of ground‐level ozone.

Abstract Sulfate aerosol greatly contributes to wintertime haze pollution in emission‐intensive regions like the North China Plain (NCP) in China. Fast sulfate increase and accumulation are usually recorded during winter haze; however, the multiphase oxidation of sulfur dioxide (SO2) and the physical processes affecting near‐surface sulfate are not fully understood. By combining in situ observations and numerical simulations, we found that high sulfur oxidation ratios (>0.6) under heavily polluted conditions are associated with low clouds and fog over NCP, induced by the moist southerly airflow. Thick low clouds and high SO2 levels in NCP provide a reaction environment for sulfate production. The sulfate production rate in cloud water can reach 0.5–1.3 μg m−3 h−1. The results demonstrate that the vertical mixing of sulfate generated within the cloud water to the surface plays a significant role in rapid sulfate production, highlighting the importance of understanding cloud‐water processes in haze pollution.

Abstract The region surrounding the Tibetan Plateau (TP) is widely considered a primary global dust source, with mineral dust comprising a significant proportion of aerosols over the TP. Current research on TP dust has mainly focused on transport from the surrounding deserts, with little focus on dust emissions from the TP's interior. The erodibility factor used by the WRF‐Chem (ERODDEF) is 0 for the TP, so the model cannot simulate the dust emissions inside the plateau. Thus, we constructed a high‐resolution erodibility data set (ERODSDS) based on a reliable dust source distribution and intensity map. Based on the modified EROD map, the WRF‐Chem model was used to simulate dust emissions and direct radiative forcing on the TP in 2018. With the modified EROD map, WRF‐Chem can well simulate the temporal variation and spatial pattern of mineral dust on the plateau, which greatly improves the model's dust emissions simulation accuracy on the TP.

The increase of the CO2 content in the atmosphere caused by anthropogenic emissions from the territories of large cities (~70%) is the critical factor in determining the accuracy of emission estimations. Advanced experiment-based methods of anthropogenic CO2 emission estimation are based on the solution of an inverse problem, using accurate measurements of CO2 content and numerical models of atmospheric transport and chemistry. The accuracy of such models decreases the errors of the emission estimations. The aim of the current study is to adapt numerical weather prediction and atmospheric chemistry model WRF-Chem and validate its capability to simulate atmospheric CO2 for the territories of the two large coastal cities of the Gulf of Finland—St. Petersburg (Russia) and Helsinki (Finland). The research has demonstrated that the WRF-Chem model is able to simulate annual variation, as well as the mean seasonal and diurnal variations of the near-surface CO2 mixing ratio, in Helsinki, at a high spatial resolution (2 km). Correlation between the modelled and measured CO2 mixing ratio is relatively high, at ~0.73, with a mean difference and its standard deviation of 0.15 ± 0.04 and 1.7%, respectively. The differences between the WRF-Chem data and the measurements might be caused by errors in the modelling of atmospheric transport and in a priori CO2 emissions and biogenic fluxes. The WRF-Chem model simulates well the column-averaged CO2 mixing ratio (XCO2) in St. Petersburg (January 2019–March 2020), with a correlation of ~0.95 relative to ground-based spectroscopic measurements by the IR–Fourier spectrometer Bruker EM27/SUN. The error of the XCO2 modelling constitutes ~0.3%, and most likely is related to inaccuracies in chemical boundary conditions and a priori anthropogenic CO2 emissions. The XCO2 time series in St. Petersburg by the WRF-Chem model fits well with global CAMS reanalysis and CarbonTracker-modelled data (the differences are less than ~1%). However, due to much higher spatial resolution (2 vs. over 100 km), the WRF-Chem data are in the best agreement with the ground-based remote measurements of XCO2. According to the study, the modelling errors of XCO2 in St. Petersburg during the whole simulated period are sufficiently minimal to fit the requirement of "Error ≤ 0.2%" in 60% of cases. This requirement should be satisfied to evaluate properly the anthropogenic CO2 emissions of St. Petersburg on a city-scale. [ABSTRACT FROM AUTHOR]

Atmospheric pollutant gases emitted from straw burning and forest fires can lead to air quality and human health problems. This work explored the evolutionary trends of atmospheric CO 2 and other pollutant gases in five countries of Peninsular Southeast Asia (PSEA) over a long time series using various satellite remote sensing data. The research results indicate that a considerable number of fires occur in the region every spring, which negatively affects air quality. The concentration of CO 2 increased every year, indicating a correlation coefficient of 0.57 with the number of fire points. The concentration of CO and NO 2 , respectively, showed a correlation coefficient of 0.87 and 0.95 with the number of fire points as well. Additionally, the AOD reflects the relationship between fire points and air quality. The study also used the meteorological and air quality Weather Research and Forecasting with Chemistry (WRF-Chem) to simulate the fire season in March 2016. In this sensitivity study, we examined the impact of air pollutant gases on air quality in PSEA under a hypothetical scenario with and without fire emissions. The simulation results were also compared with satellite observations, which showed that the WRF-Chem model and the FINN (Fire INventory from NCAR) inventory could effectively simulate the spatial distribution and spatial–temporal variability characteristics of CO concentration in the fire, but the simulation result of NO 2 was not satisfactory. This study suggests that spring wildfires affect not only air quality, but also short-term weather in the region. [ABSTRACT FROM AUTHOR]

In desert regions like the Middle East, dust has a profound impact on the environment, climate, air quality, and solar devices. The size of dust particles determines the extent of these effects. Dust deposition (DD) measurements show that coarse dust particles with geometric radius r > 10 μm comprise most of the deposited mass. Still, these particles are not represented in the current models that are tuned to fit the observed aerosol optical depth (AOD). As a result, the existing models and reanalysis products underestimate DD and dust emission (DE) almost 3 times. This is the first study to constrain the dust simulations by both AOD and DD measurements to quantify the effect of coarse and fine dust using the WRF‐Chem model. We found that, on average, coarse dust contributes less than 10% to dust shortwave radiative forcing (RF) at the surface but comprises more than 70% of DE. Annual mean net RF over the Arabian Peninsula and regional seas locally reaches −25 W m−2. Airborne fine dust particles with radii r < 3 μm are mainly responsible for the significant dimming (5%–10%) of solar radiation, cooling the surface, and hampering solar energy production. However, dust mass deposition is primarily linked to coarse particles, decreasing the efficiency of photovoltaic panels by 2%–5% per day. Therefore, incorporating coarse dust in model simulations and data assimilation would improve the overall description of the dust mass balance and its impact on environmental systems and solar devices. Plain Language Summary: Most dust emission schemes used in aerosol chemical transport models are constrained primarily by observed aerosol optical depth (AOD) and do not generate enough coarse dust particles. This study represents the first attempt to constrain the dust emission scheme using AOD and dust deposition (DD) measurements conducted at King Abdullah University of Science and Technology (KAUST). By incorporating both AOD and DD observations, we aimed to enhance the accuracy of the dust emission scheme and provide a more comprehensive understanding of dust mass balance and dynamics in the region. We found that accounting for generating coarse and giant dust particles led to a tripling of dust emissions compared with the previous estimates. We assessed the size distribution of dust particles and their impact on shortwave and longwave radiation. We quantified how particles of different sizes contributed to the regional radiative forcing and examined the implications of DD on the performance and efficiency of solar panels for optimizing solar energy systems in dust‐prone regions. Key Points: Models and reanalysis products underestimate coarse dust emission and dust deposition by 2–3 timesFine dust affects radiation, but coarse dust dominates mass deposition ratesAtmospheric dust dims solar radiation, and coarse dust causes the soiling of solar panels [ABSTRACT FROM AUTHOR]

Prevailing dry conditions and rainfall deficit during the spring season in North India led to heat wave conditions which resulted in widespread and intense forest fire events in the Himalayan state of Uttarakhand during April 16–30, 2022. A total of 7589 active fires were detected by VIIRS during the second half of April 2022 compared to 1558 during the first half. The TROPOMI observed total column values of CO and NO2 increased by 4.4% and 11.7%, respectively during April 16–30, 2022 with respect to April 1–15, 2022. A noticeable increase in surface level concentration of trace gases was also observed at Dehradun. In situ measurements of CO, NOx, and O3 during April 16–30, 2022 show an increase of 133, 35, and 6% compared to previous year observations during the same period. Weather Research and Forecasting model with chemistry (WRF-Chem) is utilized to quantitatively estimate the contribution of this event on the distribution of air pollutants over this state. The model results were evaluated against ERA5 reanalysis, upper air soundings, and TROPOMI-retrieved total column density (TCD) of CO, NO2, and O3. Two simulations with (Fire) and without (NoFire) biomass burning emissions input were performed to quantify the contribution of forest fires to the concentration of trace gases and particulates. The CO, NO2, and O3 emitted/produced from forest fire over Uttarakhand during April 2022 contributed approximately 39.95, 35.73, and 9.97% to the surface concentration of respective gas. In the case of aerosols, it was around 71.20, 71.44, and 33.62% for PM2.5, PM10, and BC respectively. The vertical profile analysis of pollutants revealed that extreme forest fire events can perturb the distribution of air pollutants from the surface up to 450 hPa. [ABSTRACT FROM AUTHOR]

The Northeast Plain in China ranks among the top five regions that have been significantly impacted by haze pollution. To effectively control pollution, it is crucial to accurately assess the effects of emission reduction measures. In this study, we analyzed surveillance data and found substantial decreases (ranging from 19.0% to 50.1%) in average annual mass concentrations of key pollutants (such as CO, SO 2 , NO 2 , and PM 2.5) in the Northeast Plain from 2016 to 2020. To precisely determine the contributions of meteorological conditions and emission reductions to the improvement of air quality in the Northeast Plain, we conducted three scenario simulations. By comparing source emissions in December 2016 and 2020 using the WRF-Chem model (except for SO 2), we observed significant reductions of 21.3%, 8.8%, and 9.8% in mass concentrations of PM 2.5 , NO 2 , and CO, respectively, from 2016 to 2020. This highlights the essential role that meteorological conditions play in determining air quality in the Northeast Plain. Moreover, further reducing source emissions by 30% in December 2016 resulted in subsequent reductions of 25.3%, 29.0%, 4.5%, and 30.3% in mass concentrations of PM 2.5 , SO 2 , NO 2 , and CO, respectively, under the same meteorological conditions. Notably, source emission reduction was effective for PM 2.5 , SO 2 , and CO, but not for NO 2. The improvement in air quality in the Northeast Plain from 2016 to 2020 can be attributed to the combined effects of improved meteorological conditions and reduced pollution sources. [ABSTRACT FROM AUTHOR]

Dust storms are one of the most frequent meteorological disasters in China, endangering agricultural production, transportation, air quality, and the safety of people's lives and property. Against the backdrop of climate change, Mongolia's contribution to China's dust cannot be ignored in recent years. In this study, we used the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), along with dynamic dust sources and the HYSPLIT model, to analyze the contributions of different dust sources to dust concentrations in northern China in March and April 2023. The results show that the frequency of dust storms in 2023 was the highest observed in the past decade. Mongolia and the Taklimakan Desert were identified as two main dust sources contributing to northern China. Specifically, Mongolia contributed more than 42% of dust, while the Taklimakan Desert accounted for 26%. A cold high-pressure center, a cold front, and a Mongolian cyclone resulted in the transport of dust aerosols from Mongolia and the Taklimakan Desert to northern China, where they affected most parts of the region. Moreover, two machine learning methods [the XGBoost algorithm and the Synthetic Minority Oversampling Technique (SMOTE)] were used to forecast the dust storms in March 2023, based on ground observations and WRF-Chem simulations over East Asia. XGBoost-SMOTE performed well in predicting hourly PM10 concentrations in China in March 2023, with a mean absolute error of 33.8 µg m−3 and RMSE of 54.2 µg m−3. [ABSTRACT FROM AUTHOR]

The present work focuses on the long-range transport of dust particles emanated after a severe dust storm hit the Middle East during 18–22 March 2012. The effect of dust-induced aerosol particles on short- and long-wave radiation over the region and positive feedback on oceanic primary productivity have been investigated. For this purpose, we have carried out simulations of dust storm using WRF-Chem and evaluated the results with respect to the in situ and remotely sensed observations using descriptive statistical analysis. It is noted that the dust transport pathway has been nicely captured by the WRF-Chem model. Model simulated higher aerosol optical depth (AOD) values (> 2.0) are found over a large part of North and North-western India on 20 March 2012. A considerable drop of 50 W m−2 in short-wave radiation was noticed over the Northern India region due to the considerably high dust loading in the atmosphere. Model simulated AOD revealed significant correlation (at 99% confidence interval) with the AERONET observations (r = 0.92 for Meziara, r = 0.85 for KAUST campus and r = 0.62 for Jaipur stations) along the dust transport path. Substantial decrease in sea surface temperature from 20 to 7 °C is noted over the Arabian Sea during dusty days. A significant increase in the chlorophyll-a concentration from 4 to 14 mg/m3 is also observed with a time lag of 4 days subsequent to the increase in AOD over the central Arabian Sea. Results obtained here indicate a positive feedback mechanism of dust deposition on enhanced primary productivity. [ABSTRACT FROM AUTHOR]

In this study, we utilized a 20-bin WRF-Chem (Weather Research and Forecast coupled with Chemistry regional model) to investigate the contributions of chemical drivers to the growth of newly formed particles, as well as to simulate the three-dimensional dynamics of new particle formation (NPF) events over the North China Plain during a summer campaign in 2019, which was reported in the accompanying paper. The model demonstrated good performance in replicating the occurrence of NPF, the growth pattern of newly formed particles, and the number concentration of particles in the size range of 10–40 nm in five events between June 29 and July 6. This period was characterized by a high frequency of NPF occurrence (>60 %). During this time, the model was also able to accurately reproduce the levels of organics in PM1.0 relative to observations, and to reasonably replicate the levels of SO4 2- and NH4 + in PM1.0, as well as PM2.5 mass concentrations. Therefore, we further analyzed three NPF events with distinct particle growth characteristics: Case 1, featuring observable growth of newly formed particles to cloud condensation nuclei (CCN) size on July 1–2; Case 2, characterized by continuous growth of new particles for several hours without any net contribution to CCN on July 3; and Case 3, where no detectable continuous growth of newly formed particles was observed on July 6. In these instances, the model tended to overpredict the condensation of H2SO4 vapor during daytime and the formation of NH4NO3 during nighttime, resulting in an overestimation of the hygroscopicity parameter of nanometer particles. Nevertheless, the model was able to reasonably reproduce the CCN (cloud condensation nuclei) at a super saturation (SS) of 0.4 % on days with NPF, compared to the observations. This was because the overestimation effect caused by inorganics was offset by the model's underestimation of CCN originating from submicron-sized particles. Additionally, three-dimensional simulations of NPF events have demonstrated some key findings. Firstly, NPF consistently initiates at the upper fraction of the planetary boundary layer (PBL) before expanding. Secondly, during daytime growth of newly formed particles in the PBL, organics play a dominant role, whereas the primary chemical drivers shift to inorganic species in the free troposphere. However, to confirm these findings, vertical observations are required. [ABSTRACT FROM AUTHOR]

The influence of urbanization on the frequent winter aerosol pollution events in Northeast China is not fully understood. The Weather Research and Forecasting Model with Chemistry (WRF–Chem) coupled with urban canopy (UC) models was used to simulate the impact of urbanization on an aerosol pollution process in the Central Liaoning city cluster (CLCC), China. To investigate the main mechanisms of urban expansion and UC on the winter atmospheric environment and the atmospheric diffusion capacity (ADC) in the CLCC, three simulation cases were designed using land-use datasets from different periods and different UC schemes. A comparative analysis of the simulation results showed that the land-use change (LU) and both LU and UC (LUUC) effects lead to higher surface temperature and lower relative humidity and wind speed in the CLCC by decreasing surface albedo, increasing sensible heat flux, and increasing surface roughness, with a spatial distribution similar to the distribution of LU. The thermal effect leads to an increase in atmospheric instability, an increase in boundary layer height and diffusion coefficient, and an increase in the ADC. The LU and LUUC effects lead to a significant decrease in near-surface PM2.5 concentrations in the CLCC due to changes in meteorological conditions and ADC within the boundary layer. The reduction in surface PM2.5 concentrations due to the LU effect is stronger at night than during daytime, while the LUUC effect leads to a greater reduction in surface PM2.5 concentrations during the day, mainly due to stronger diffusion and dilution caused by the effect of urban turbulence within different levels caused by the more complex UC scheme. In this study, the LU and LUUC effects result in greater thermal than dynamic effects, and both have a negative impact on surface PM2.5 concentrations, but redistribute pollutants from the lower urban troposphere to higher altitudes. [ABSTRACT FROM AUTHOR]

Dust storms are a common phenomenon in arid and semi-arid regions of the world. The erosion in the desert, agricultural, urban, and rural areas contributes to atmospheric mineral dust. Low vegetation cover drives intense dust storms in arid regions like northern Mexico and the southwestern USA. The seasonality associated with winter cold fronts from October to June regulates dust storms. The impact of dust storms is considerable, from massive soil deterioration to health problems caused by policies of changing land use from grasslands and forests to rainfed agriculture. This process has increased notably in recent decades. To identify potential dust storm events, we applied the criterion of a threshold wind speed of 9 m/s in all meteorological stations and data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. The analysis of wind data allowed identifying 245 cases of potential dust storms occurring between 2006 and 2018, but only 15 were chosen to be analyzed by numerical modeling. The WRF-Chem model version 3.6 was applied. Numerical experiments allowed calculating the fraction of PM10 emitted during each simulated event, where the concentration varied from 34 to 350 μg/m3. From the CALIPSO profiles, the atmospheric dust from the outputs of the numerical simulations was verified. Extensive distribution of dust revealed high contributions of PM10 that affect the air quality. The analysis of 13 years of wind data yielded 9 extreme wind events each year exceeding the speed threshold for dust removal. [ABSTRACT FROM AUTHOR]

We present simulations of a series of dust‐and‐rain events in July/August 2020 that caused significant loss of life and property over northeast Africa and the Red Sea coast using convection‐permitting Weather Research and Forecasting‐Chem simulations at 1.5 km horizontal grid spacing coupled with prognostic dust and aerosol scheme together with a double‐moment cloud microphysical scheme. The model generally captures the optical properties and vertical profiles of dust but has difficulty reproducing the seasonal dust plumes that originate over northeast Africa and reach the western Arabian Peninsula through the Tokar gap. Overlapping of synoptic events with local, diurnal‐scale, convective features caused continuous rainfall over the study domain in July/August 2020. The model well simulates the synoptically‐driven clouds over the ocean (∼4–8 km) and daytime deep convective clouds over the land but cannot reproduce cumulus clouds over the ocean advected from land, which leads to some biases in simulating peak rainfall rates. Although our simulations do not explicitly consider aerosol particles as ice nuclei, the model reproduces the cirrus clouds found at ∼10–15 km height during the study period. Simulations with a planetary boundary layer (PBL) scheme better represented the diurnal profile of surface temperature and winds, as well as the rainfall distribution, than without using a PBL scheme. Dust generally enhanced rainfall during the synoptic rain event through indirect effects but suppressed rainfall during sea‐breeze‐induced convective events through dust direct effects by weakening the sea‐breeze circulation. Plain Language Summary: Although extreme rainfall events have been studied extensively over the Middle East and North Africa (MENA), the underlying physical mechanisms are not well known, particularly in relation to dust, the reason why most models do not consider the effect of dust on rainfall or consider limited treatment of dust‐cloud‐rainfall interactions. Consequently, there exists high uncertainty in simulating rainfall over the region. Here, we assess the performance of Weather Research and Forecasting (WRF)‐Chem in simulating dust and rainfall dynamics and calculate the direct and indirect effect of dust on rainfall over the Red Sea coast. WRF‐Chem generally reproduces the optical properties and vertical profiles of dust but has difficulty reproducing the seasonal dust plumes. The model well simulates the synoptically‐driven clouds over the ocean (∼4–8 km) and daytime convective clouds over the land but cannot reproduce cumulus clouds over the ocean advected from land, which leads to some biases in peak rainfall rates. Dust enhanced rainfall during the synoptic rain event through indirect effects but suppressed rainfall during convective events through dust direct effects by weakening the sea‐breeze circulation. Our results can help improve regional climate model simulations in dusty regions and better inform regional water resource planning, which requires accurate rainfall predictions. Key Points: Weather Research and Forecasting‐Chem captures the aerosol optical properties during dust events but has difficulty reproducing seasonal dust plumes over the Red SeaSynoptic systems produced long‐lasting rainfall whereas deep convective clouds caused diurnal‐scale rainfall over the Red SeaThe direct effect of dust dominates the indirect effects during large dust events but both effects are comparable during small dust events [ABSTRACT FROM AUTHOR]

The uncharacteristically extreme outbreak of particulate matter took place over the Balkan region from 27 to 30 March 2020. Observations at air quality stations in Croatia recorded hourly PM10 concentrations up to 412 μgm−3. The meteorological analysis shows that the increase in PM10 concentrations was primarily due to the advection of dust from the deserts east of the Caspian Sea. The anticyclone north of Croatia and the cyclone over Anatolia formed a strong pressure gradient driving transport from the east. Both back trajectories and satellite products pointed to the dry Aral Sea as the main source of dust. A dust plume influenced the PM10 increase observed in Croatia, starting at the easternmost air quality stations. The modeling study shows that the vertical extent of the dust plume was up to ∼2 km. However, the chemical and morphological (scanning electron microscope analysis) composition of PM10 at the sites in the northeastern Adriatic Sea showed mainly the presence of Saharan dust. Prior to the advection of the Asian dust, the transport of Saharan dust, driven by Sharav cyclone, was observed in the PM10 values at several stations in the Adriatic Sea and on the Croatian mainland on 26 March 2020. Modeling results showed that the Saharan dust transport occurred at altitudes below ∼8 km. The mixing of the Asian and Saharan dust plumes over the Balkans was favored by the subsidence due to anticyclonic high‐pressure conditions and is the most likely explanation for the observed PM chemical and morphological results. Plain Language Summary: The event of extreme air pollution in Croatia occurred at the end of March 2020. Exceptionally high aerosol concentrations were observed at several air quality stations. The outbreak was studied using a numerical chemical transport model. Chemical analysis was also performed for the aerosol sample and the sample was viewed with an electronic microscope. The analysis revealed that the composition of the aerosol was due to desert dust transported by air masses from the deserts east of the Caspian Sea and the Sahara Desert. Key Points: The extraordinary dust episode over the Balkan region was simulated with the WRF‐Chem modelThe dried Aral Sea was identified as the main source, but the dust plume from the Sahara was also presentChemical and morphological analysis of the PM10 sample shows that the dust originated from the Sahara Desert [ABSTRACT FROM AUTHOR]