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This paper presents a three-dimensional variational (3DVAR) data assimilation (DA) system for aerosol optical properties, including aerosol optical thickness (AOT) retrievals and lidar-based aerosol profiles, developed for the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) within the Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model. For computational efficiency, 32 model variables in the MOSAIC_4bin scheme are lumped into 20 aerosol state variables that are representative of mass concentrations in the DA system. To directly assimilate aerosol optical properties, an observation operator based on the Mie scattering theory was employed, which was obtained by simplifying the optical module in WRF-Chem. The tangent linear (TL) and adjoint (AD) operators were then established and passed the TL/AD sensitivity test. The Himawari-8 derived AOT data were assimilated to validate the system and investigate the effects of assimilation on both AOT and PM 2.5 simulations. Two comparative experiments were performed with a cycle of 24 h from 23 to 29 November 2018, during which a heavy air pollution event occurred in northern China. The DA performances of the model simulation were evaluated against independent aerosol observations, including the Aerosol Robotic Network (AERONET) AOT and surface PM 2.5 measurements. The results show that Himawari-8 AOT assimilation can significantly improve model AOT analyses and forecasts. Generally, the control experiments without assimilation seriously underestimated AOTs compared with observed values and were therefore unable to describe real aerosol pollution. The analysis fields closer to observations improved AOT simulations, indicating that the system successfully assimilated AOT observations into the model. In terms of statistical metrics, assimilating Himawari-8 AOTs only limitedly improved PM 2.5 analyses in the inner simulation domain (D02); however, the positive effect can last for over 24 h. Assimilation effectively enlarged the underestimated PM 2.5 concentrations to be closer to the real distribution in northern China, which is of great value for studying heavy air pollution events. [ABSTRACT FROM AUTHOR]

In this paper, complex network theory has been applied to reveal the transport patterns and cooperative regions of fine particulate matter (PM 2.5) over China from 2015 to 2019. The results show that the degrees, weighted degrees, and edge lengths of PM 2.5 cities follow power law distributions. We find that the cities in the Beijing–Tianjin–Hebei–Henan–Shandong (BTHHS) region have a strong ability to export PM 2.5 pollution to other cities. By analyzing the transport routes, we show that a mass of links extends southward from the BTHHS to the Yangtze River Delta (YRD) regions with 1 or 2 d time lags. Hence, we conclude that earlier emission reduction in the BTHHS region and early warning measures in the YRD region will provide better air pollution mitigation in both regions. Moreover, significant links are concentrated in wintertime, suggesting the impact of the winter monsoon. In addition, all cities have been divided into nine clusters according to their spatial correlations. We suggest that the cities in the same clusters should be regarded as a whole to control the level of air pollution. This approach is able to characterize the transport and cluster for other air pollutants, such as ozone and NOx. [ABSTRACT FROM AUTHOR]

This paper presents the first development and evaluation of a reduced-complexity air quality model for China. In this study, the reduced-complexity Intervention Model for Air Pollution over China (InMAP-China) is developed by linking a regional air quality model, a reduced-complexity air quality model, an emission inventory database for China, and a health impact assessment model to rapidly estimate the air quality and health impacts of emission sources in China. The modeling system is applied over mainland China for 2017 under various emission scenarios. A comprehensive model evaluation is conducted by comparison against conventional Community Multiscale Air Quality (CMAQ) modeling system simulations and ground-based observations. We found that InMAP-China satisfactorily predicted total PM 2.5 concentrations in terms of statistical performance. Compared with the observed PM 2.5 concentrations, the mean bias (MB), normalized mean bias (NMB) and correlations of the total PM 2.5 concentrations are - 8.1 µ g m -3 , - 18 % and 0.6, respectively. The statistical performance is considered to be satisfactory for a reduced-complexity air quality model and remains consistent with that evaluated in the USA. The underestimation of total PM 2.5 concentrations was mainly caused by its composition, primary PM 2.5. In terms of the ability to quantify source contributions of PM 2.5 concentrations, InMAP-China presents similar results to those based on the CMAQ model, with variation mainly caused by the different treatment of secondary inorganic aerosols in the two models. Focusing on the health impacts, the annual PM 2.5 -related premature mortality estimated using InMAP-China in 2017 was 1.92 million, which was 250 000 deaths lower than estimated based on CMAQ simulations as a result of the underestimation of PM 2.5 concentrations. This work presents a version of the reduced-complexity air quality model over China that provides a powerful tool to rapidly assess the air quality and health impacts associated with control policy and to quantify the source contribution attributable to many emission sources. [ABSTRACT FROM AUTHOR]

Stratosphere-to-troposphere transport results in the stratospheric intrusion (SI) of O 3 into the free troposphere through the folding of the tropopause. However, the mechanism of SI that influences the atmospheric environment through the cross-layer transport of O 3 from the stratosphere and free troposphere to the atmospheric boundary layer has not been elucidated thoroughly. In this study, an SI event over the North China Plain (NCP; 33–40° N, 114–121° E) during 19–20 May 2019 was chosen to investigate the mechanism of the cross-layer transport of stratospheric O 3 and its impact on the near-surface O 3 based on multi-source reanalysis, observation data, and air quality modeling. The results revealed a mechanism of stratospheric O 3 intrusion into the atmospheric environment induced by an extratropical cyclone system. The SI with downward transport of stratospheric O 3 to the near-surface layer was driven by the extratropical cyclone system, with vertical coupling of the upper westerly trough, the middle of the northeast cold vortex (NECV), and the lower extratropical cyclone, in the troposphere. The deep trough in the westerly jet aroused the tropopause folding, and the lower-stratospheric O 3 penetrated the folded tropopause into the upper and middle troposphere; the westerly trough was cut off to form a typical cold vortex in the upper and middle troposphere. The compensating downdrafts of the NECV further pushed the downward transport of stratospheric O 3 in the free troposphere; the NECV activated an extratropical cyclone in the lower troposphere; and the vertical cyclonic circulation governed the stratospheric O 3 from the free troposphere across the boundary layer top, invading the near-surface atmosphere. In this SI event, the average contribution of stratospheric O 3 to near-surface O 3 was accounted for at 26.77 %. The proposed meteorological mechanism of the vertical transport of stratospheric O 3 into the near-surface atmosphere, driven by an extratropical cyclone system, could improve the understanding of the influence of stratospheric O 3 on the atmospheric environment, with implications for the coordinated control of atmospheric pollution. [ABSTRACT FROM AUTHOR]

Since China's clean air action, PM 2.5 (particulate matter with an aerodynamic equivalent diameter of 2.5 µm or less) air quality has improved, while ozone (O 3) pollution has become more severe. Here we apply a coupled meteorology–chemistry model (WRF-Chem: Weather Research and Forecasting model coupled to Chemistry v3.7.1) to quantify the responses of aerosol–radiation interaction (ARI) to anthropogenic emission reductions from 2013 to 2017, including aerosol–photolysis interaction (API) related to photolysis rate change and aerosol–radiation feedback (ARF) related to meteorological field change and their contributions to O 3 increases over eastern China in summer and winter. Sensitivity experiments show that the decreased anthropogenic emissions play a more prominent role in the increased daily maximum 8 h average (MDA8) O 3 in both summer (+ 1.96 ppb vs. + 0.07 ppb) and winter (+ 3.56 ppb vs. - 1.08 ppb) than the impacts of changed meteorological conditions in urban areas. The decreased PM 2.5 caused by emission reductions can result in a weaker impact of ARI on O 3 concentrations, which superimposes its effect on the worsened O 3 air quality. The weakened ARI due to decreased anthropogenic emissions aggravates the summer (winter) O 3 pollution by + 0.81 ppb (+ 0.63 ppb), averaged over eastern China, with weakened API contributing 55.6 % (61.9 %) and ARF contributing 44.4 % (38.1 %), respectively. This superimposed effect is more significant for urban areas during summer (+ 1.77 ppb). Process analysis indicates that the enhanced chemical production is the dominant process for the increased O 3 concentrations caused by weakened ARI in both summer and winter. This study innovatively reveals the adverse effect of weakened aerosol–radiation interaction due to decreased anthropogenic emissions on O 3 air quality, indicating that more stringent coordinated air pollution control strategies should be implemented for significant improvements in future air quality. [ABSTRACT FROM AUTHOR]

Two-way coupled meteorology and air quality models, which account for aerosol–radiation–cloud interactions, have been employed to simulate meteorology and air quality more realistically. Although numerous related studies have been conducted, none have compared the performances of multiple two-way coupled models in simulating meteorology and air quality over eastern China. Thus, we systematically evaluated annual and seasonal meteorological and air quality variables simulated by three open-source, widely utilized two-way coupled models (Weather Research and Forecasting (WRF)–Community Multiscale Air Quality (WRF–CMAQ), WRF coupled with chemistry (WRF–Chem), and WRF coupled with a regional chemistry-transport model named CHIMERE (WRF–CHIMERE)) by validating their results with surface and satellite observations for eastern China in 2017. Although we have made every effort to evaluate these three coupled models by using configurations that are as consistent as possible, there are still unavoidable differences between them in their treatments of physical and chemical processes. Our thorough evaluations revealed that all three two-way coupled models captured the annual and seasonal spatiotemporal characteristics of meteorology and air quality reasonably well. Notably, the role of the aerosol–cloud interaction (ACI) in improving the models' performances was limited compared to that of the aerosol–radiation interaction (ARI). The sources of uncertainties and bias in the different ACI schemes in the two-way coupled models were identified. With sufficient computational resources, these models can provide more accurate air quality forecasting to support atmospheric environment management and deliver timely warnings of heavy air pollution events. Finally, we propose potential improvements to two-way coupled models for future research. [ABSTRACT FROM AUTHOR]

PM 2.5 pollution is a major air quality issue that deteriorates human health, and numerous studies have focused on PM 2.5 pollution in major regions such as the North China Plain (NCP) and Yangtze River Delta (YRD). However, the characteristics of PM 2.5 concentrations and the associated formation mechanism in the transport corridor (referred to as SWLY) between the NCP and YRD are largely ignored. Based on observational data, we find that the number of PM 2.5 pollution events in SWLY is comparable to that in the NCP, far exceeding that in the YRD, which is indicative of the severity of air pollution in this area. Utilizing a regional climate and air quality model, we isolate the effect of seesaw transport events, e.g., transport between the NCP and YRD, and atmospheric stagnation on the accumulation of PM 2.5 over SWLY. Specifically, seesaw events and stagnation, comparable to each other, collectively account for an average of 67 % of pollution days, with PM 2.5 exceeding 75 µgm-3 , and this fraction (85 %) is even larger for severe haze events, with PM 2.5 exceeding 150 µgm-3. Furthermore, the connection between seesaw transport and large-scale circulation is examined. The transregional transport of pollutants from the NCP to the YRD (YRD to NCP) is likely stimulated by positive (negative) to negative (positive) geopotential height anomalies at 500 hPa located in northern China. The health effect due to short-term PM 2.5 exposure induced by the transregional transport and stagnation is investigated, yielding a total of 8634 (95 % CI: 6023–11 223) and 9496 (95 % CI: 6552–12 413) premature deaths, respectively, in SWLY during winter 2014–2019, which is as high as 9 % of the total premature deaths in China, even though SWLY takes up less than 1 % of China's area. While atmospheric stagnation is in general projected to occur more frequently under a warming climate, this study indicates the importance of regional emission control to alleviate PM 2.5 pollution from seesaw transport and stagnation. [ABSTRACT FROM AUTHOR]

This paper presents a three- dimensional variational (3DVAR) data assimilation (DA) system for aerosol optical properties, including aerosol optical depth (AOD) retrievals and lidar- based aerosol profiles, which was developed for the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) within the Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model. For computational efficiency, 32 model variables in the MOSAIC_4bin scheme are lumped into 20 aerosol state variables that are representative of mass concentrations in the DA system. To directly assimilate aerosol optical properties, an observation operator based on the Mie scattering theory was employed, which was obtained by simplifying the optical module in WRF-Chem. The tangent linear (TL) and adjoint (AD) operators were then established and passed the TL/AD sensitivity test. The Himawari-8 derived aerosol optical thickness (AOT) data were assimilated to validate the system and investigate the effects of assimilation on both AOT and PM2.5 simulations. Two comparative experiments were performed with a cycle of 24 h from November 23 to 29, 2018, during which a heavy air pollution event occurred in North China. The DA performances of the model simulation were evaluated against independent aerosol observations, including the Aerosol Robotic Network (AERONET) AOT and surface PM2.5 measurements. The results show that Himawari-8 AOT assimilation can significantly improve model AOT analyses and forecasts. Generally, the control experiments without assimilation seriously underestimated AOTs compared with observed values and were therefore unable to describe real aerosol pollution. The analysis fields closer to observations improved AOT simulations, indicating that the system successfully assimilated AOT observations into the model. In terms of statistical metrics, assimilating Himawari-8 AOTs only limitedly improved PM2.5 analyses in the inner simulation domain (D02); however, the positive effect can last for over 24 h. Assimilation effectively enlarged the underestimated PM2.5 concentrations to be closer to the real distribution in North China, which is of great value for studying heavy air pollution events [ABSTRACT FROM AUTHOR]

Over the past decades, northern China has been suffering from persistent air pollution caused by both fine and coarse atmospheric particles. Although there are plenty of theoretical and observational studies on aerosols in northern China, most of them only consider total aerosol concentrations and focus on heavy pollution episodes; the long-term vertical distributions of dust (coarse) and anthropogenic aerosols (fine) and their relationships with the mixing layer height (MLH) have not been revealed. In this study, the dust and anthropogenic aerosols' mass concentration and the MLH were retrieved by polarization Raman lidar over Beijing from May 2019 to February 2022. We found that large amounts of anthropogenic aerosols accumulate at the top of the mixing layer, which is most noticeable in summer, with monthly mean mass concentration up to 57 µ g m -3. It is mainly influenced by the southward transport in the upper air, where the atmosphere is relatively stable and moist, favoring hygroscopic growth of particles. Dust mass concentration is discontinuous in the vertical direction, not only on the ground but also in lofted layers that reach up to several kilometers. The heights of these lofted dust layers exhibited apparent seasonal dependence, with the height of the main dust layer gradually ascending from 1.1 km to about 2.5 km from April to June and below 3 km from October to December. In addition, there is a significant negative correlation between bottom anthropogenic aerosols' mass concentration and the MLH, and an inverse function fit is more suitable to characterize this relationship, while the relationship between bottom dust mass concentration and the MLH is insignificant. These results will enhance our understanding of the sophisticated interactions between dust and anthropogenic aerosols, the MLH, and regional transport in northern China. It will also help to refine atmospheric chemistry models and improve surface prediction capabilities. [ABSTRACT FROM AUTHOR]

Studies assessing the achievability of future air quality goals in China have focused on the role of reducing China's domestic emissions, yet the influence of transboundary pollution of foreign origins has been largely underappreciated. Here, we assess the extent to which future changes in foreign transboundary pollution would affect the achievability of air quality goals in 2030 and 2060 for China. We find that in 2030, under the current-policy scenario in China, transboundary contributions to population-weighted PM 2.5 in China would be reduced by 29 % (1.2 µ g m -3) as foreign countries transition from the fossil-fuel-intensive to the low-carbon pathway. By 2060, the difference would be increased to 45 % (1.8 µ g m -3). Adopting the low-carbon instead of the fossil-fuel-intensive pathway in foreign countries would prevent 10 million Chinese people from being exposed to PM 2.5 concentrations above China's ambient air quality standard (35 µ g m -3) in 2030 and 5 million Chinese people from being exposed to PM 2.5 concentrations above the World Health Organization air quality guideline (5 µ g m -3) in 2060. Meanwhile, China adopting the carbon-neutral pathway rather than its current pathway would also be helpful to reduce transboundary PM 2.5 produced from the chemical interactions between foreign-transported and locally emitted pollutants. In 2060, adopting a low-carbon pathway in China and foreign countries coincidentally would prevent 63 % of transboundary pollution and 386 000 associated premature deaths in China, relative to adopting a fossil-fuel-intensive pathway in both regions. Thus, the influence of transboundary pollution should be carefully considered when making future air quality expectations and pollution mitigation strategies. [ABSTRACT FROM AUTHOR]

The Fenwei Plain, home to 50 million people in central China, is one of the most polluted regions in China. In 2018, the Fenwei Plain was designated as one of the three key regions for the "Blue Sky Protection Campaign", along with the Beijing–Tianjin–Hebei (BTH) and Yangtze River Delta (YRD) regions. However, compared to BTH and YRD, our understanding of the current status of air pollution in the Fenwei Plain is limited partly due to a lack of detailed analysis of the transformation from precursor gases to secondary products including secondary organic aerosol (SOA) and ozone. Through the analysis of 7 years (2015–2021) of surface monitoring of the air pollutants in Xi'an, the largest city in the Fenwei Plain, we show that roughly two-thirds of the days exceeded either the PM 2.5 or the O 3 level-1 air quality standard, highlighting the severity of air pollution. Moreover, an increase in O 3 pollution in the winter haze was also revealed, due to the constantly elevated reactive oxygenated volatile organic compounds (OVOCs), in particular formaldehyde, with an ozone formation potential of over 50 µ g m -3 , in combination with the reduced NO 2. The abrupt decrease of NO 2 , as observed during the lockdown in 2020, provided real-world evidence of the control measures, targeting only NO x (70 % decrease on average), and were insufficient to reduce ozone pollution because reactive OVOCs remained constantly high in a volatile organic compound (VOC)-limited regime. Model simulation results showed that with NO 2 reduction from 20 %–70 %, the self-reaction rate between peroxy radicals, a pathway for SOA formation, was intensified by up to 75 %, while the self-reaction rate was only reduced with a further reduction of VOCs of > 50 %. Therefore, a synergic reduction in PM 2.5 and O 3 pollution can only be achieved through a more aggressive reduction of their precursor gases. This study elucidates the status of ozone and PM 2.5 pollution in one of the most polluted regions in China, revealing a general trend of increasing secondary pollution, i.e., ozone and SOA in winter haze. Controlling precursor gas emissions is anticipated to curb both ozone and SOA formation, which will benefit not just the Fenwei Plain but also other regions in China. [ABSTRACT FROM AUTHOR]

Vehicle emissions are regarded as a primary contributor to air pollution and related adverse health impacts. Heavy traffic congestion increases traffic flow and thus produces more O3 precursor emissions, leading to more adverse air quality issues. Although the development of a vehicle emission inventory has received great concern and continuous efforts, limitations still exist. For example, real-time diurnal variations and increases in emission rates due to traffic congestion are not well understood. In this study, we developed a new temporal allocation approach in transportation emissions to investigate the impact on air quality and health burden due to traffic congestion in China in 2020. Both real-time congestion-level data and emission correction factors were considered in the approach. Results show that traffic congestion aggravates air pollution and health burden across China, especially in the urban clusters such as the North China Plain and Sichuan Basin. In these regions, the average annual increases in fine particulate matter (PM2.5) and ozone (O3) could be up to 3.5 µgm-3 and 1.1 ppb , respectively. The excess PM2.5 and O3 attributed to the traffic congestion also induce an additional 20 000 and 5000 premature deaths in China, respectively. In major cities, the increased rate of premature mortality caused by traffic congestion may reach 17.5 %. Therefore, more effective and comprehensive vehicle emission control policies or better planning of the road network should be established to reduce traffic congestion and improve air quality in China. [ABSTRACT FROM AUTHOR]

We use the United Kingdom Earth System Model, UKESM1, to investigate the influence of the winter large-scale circulation on daily concentrations of PM 2.5 (particulate matter with an aerodynamic diameter of 2.5 µ m or less) and their sensitivity to emissions over major populated regions of China over the period 1999–2019. We focus on the Yangtze River delta (YRD), where weak flow of cold, dry air from the north and weak inflow of maritime air are particularly conducive to air pollution. These provide favourable conditions for the accumulation of local pollution but limit the transport of air pollutants into the region from the north. Based on the dominant large-scale circulation, we construct a new index using the north–south pressure gradient and apply it to characterise PM 2.5 concentrations over the region. We show that this index can effectively distinguish different levels of pollution over YRD and explain changes in PM 2.5 sensitivity to emissions from local and surrounding regions. We then project future changes in PM 2.5 concentrations using this index and find an increase in PM 2.5 concentrations over the region due to climate change that is likely to partially offset the effect of emission control measures in the near-term future. To benefit from future emission reductions, more stringent emission controls are required to offset the effects of climate change. [ABSTRACT FROM AUTHOR]

With the explosive growth of atmospheric data, machine learning models have achieved great success in air pollution forecasting because of their higher computational efficiency than the traditional chemical transport models. However, in previous studies, new prediction algorithms have only been tested at stations or in a small region; a large-scale air quality forecasting model remains lacking to date. Huge dimensionality also means that redundant input data may lead to increased complexity and therefore the over-fitting of machine learning models. Feature selection is a key topic in machine learning development, but it has not yet been explored in atmosphere-related applications. In this work, a regional feature selection-based machine learning (RFSML) system was developed, which is capable of predicting air quality in the short term with high accuracy at the national scale. Ensemble-Shapley additive global importance analysis is combined with the RFSML system to extract significant regional features and eliminate redundant variables at an affordable computational expense. The significance of the regional features is also explained physically. Compared with a standard machine learning system fed with relative features, the RFSML system driven by the selected key features results in superior interpretability, less training time, and more accurate predictions. This study also provides insights into the difference in interpretability among machine learning models (i.e., random forest, gradient boosting, and multi-layer perceptron models). [ABSTRACT FROM AUTHOR]

The cold air outbreak (CAO) is the most important way to reduce air pollution during the winter over northern and eastern China. However, a rapid reappearance of air pollution is usually observed during its decay phase. Is there any relationship between the reappearance of air pollution and the properties of CAO? To address this issue, we investigated the possible connection between air pollution reappearance and CAO by quantifying the properties of the residual cold air mass after CAO. Based on the analyses of recent winters (2014–2022), we found that the rapid reappearance of air pollution in the CAO decay phase has an occurrence frequency of 63 %, and the air quality in more than 50 % of CAOs worsens compared to that before CAO. The reappearance of air pollution tends to occur in the residual cold air mass with a weak horizontal flux during the first 2 d after CAO. By categorizing the CAOs into groups of rapid and slow air pollution reappearance, we found that the residual cold air mass with a moderate depth of 150–180 hPa, a large negative heat content, and small slopes of isentropes is favorable for the rapid reappearance of air pollution. Among these factors, the cold air mass depth is highly consistent with the mixing layer height, below which most air pollutants are found; the negative heat content and slope of isentropes in the cold air mass jointly determine the intensity of low-level vertical stability. The rapid reappearance of air pollution is also attributed to the maintenance of the residual cold air mass and the above conditions, which are mainly regulated by the dynamic transport process rather than diabatic cooling or heating. Furthermore, analysis of the large-scale circulation of CAOs in their initial stage shows that the anticyclonic (cyclonic) pattern in northern Siberia (northeastern Asia) can be recognized as a precursor for the rapid (slow) reappearance of air pollution after the CAO. [ABSTRACT FROM AUTHOR]

High spatial resolution PM 2.5 data covering a long time period are urgently needed to support population exposure assessment and refined air quality management. In this study, we provided complete-coverage PM 2.5 predictions with a 1 km spatial resolution from 2000 to the present under the Tracking Air Pollution in China (TAP, http://tapdata.org.cn/ , last access: 3 October 2022) framework. To support high spatial resolution modeling, we collected PM 2.5 measurements from both national and local monitoring stations. To correctly reflect the temporal variations in land cover characteristics that affected the local variations in PM 2.5 , we constructed continuous annual geoinformation datasets, including the road maps and ensemble gridded population maps, in China from 2000 to 2021. We also examined various model structures and predictor combinations to balance the computational cost and model performance. The final model fused 10 km TAP PM 2.5 predictions from our previous work, 1 km satellite aerosol optical depth retrievals, and land use parameters with a random forest model. Our annual model had an out-of-bag R2 ranging between 0.80 and 0.84, and our hindcast model had a by-year cross-validation R2 of 0.76. This open-access, 1 km resolution PM 2.5 data product, with complete coverage, successfully revealed the local-scale spatial variations in PM 2.5 and could benefit environmental studies and policymaking. [ABSTRACT FROM AUTHOR]

A knowledge gap exists concerning how chemical composition and sources respond to implemented policy control measures for aerosols, particularly in a semi-arid region. To address this, a single year's offline measurement was conducted in Hohhot, a semi-arid city in northern China, to reveal the driving factors of severe air pollution in a semi-arid region and assess the impact of the COVID-19 lockdown measures on chemical characteristics and sources of PM 2.5. Organic matter, mineral dust, sulfate and nitrate accounted for 31.5 %, 14.2 %, 13.4 % and 12.3 % of the total PM 2.5 mass, respectively. Coal combustion, vehicular emission, crustal source and secondary inorganic aerosols were the main sources of PM 2.5 in Hohhot, at 38.3 %, 35.0 %, 13.5 %, and 11.4 %, respectively. Due to the coupling effect of emission reduction and improved atmospheric conditions, the concentration of secondary inorganic components, organic matter and elemental carbon declined substantially from the pre-lockdown (pre-LD) period to the lockdown (LD) and post-lockdown (post-LD) periods. The source contribution of secondary inorganic aerosols increased (from 21.1 % to 37.8 %), whereas the contribution of vehicular emission reduced (from 35.5 % to 4.4 %) due to lockdown measures. The rapid generation of secondary inorganic components caused by unfavorable meteorological conditions during lockdown led to serious pollution. This study elucidates the complex relationship between air quality and environmental policy. [ABSTRACT FROM AUTHOR]

Using a new high-resolution air quality reanalysis dataset for China for five winters from December 2013 to February 2018, we examine the influence of large-scale circulation on daily PM 2.5 variability through its direct effect on key regional meteorological variables over three major populated regions of China: Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD) and the Pearl River Delta (PRD). In BTH, a shallow East Asian trough curbs northerly cold and dry air from the Siberian High, enhancing PM 2.5 pollution levels. Weak southerly winds in eastern and southern China, associated with a weakened Siberian High, suppress horizontal dispersion, contributing to air pollution accumulation over YRD. In PRD, weak southerly winds and precipitation deficits over southern China are conducive to high PM 2.5 pollution levels. To account for these dominant large-scale circulation–PM 2.5 relationships, we propose three new circulation-based indices for predicting different levels of air pollution based on regional PM 2.5 concentrations in each region: a 500 hPa geopotential height-based index for BTH, a sea level pressure-based index for YRD and an 850 hPa meridional wind-based index for PRD. These three indices can effectively distinguish clean days from heavily polluted days in these regions, assuming variation is solely due to meteorology. We also find that including the most important regional meteorological variable in each region improves the performance of the circulation-based indices in predicting daily PM 2.5 concentrations on the regional scale. These results are beneficial to understanding and forecasting the occurrence of heavily polluted PM 2.5 days in BTH, YRD and PRD from a large-scale perspective. [ABSTRACT FROM AUTHOR]

We examined the impacts of aerosol–radiation interactions, including the effects of aerosol–photolysis interaction (API) and aerosol–radiation feedback (ARF), on surface-layer ozone (O3) concentrations during four multi-pollutant air pollution episodes characterized by high O3 and PM2.5 levels during 28 July to 3 August 2014 (Episode1), 8–13 July 2015 (Episode2), 5–11 June 2016 (Episode3), and 28 June to 3 July 2017 (Episode4) in North China, by using the Weather Research and Forecasting with Chemistry (WRF-Chem) model embedded with an integrated process analysis scheme. Our results show that API and ARF reduced the daytime shortwave radiative fluxes at the surface by 92.4–102.9 Wm-2 and increased daytime shortwave radiative fluxes in the atmosphere by 72.8–85.2 Wm-2 , as the values were averaged over the complex air pollution areas (CAPAs) in each of the four episodes. As a result, the stabilized atmosphere decreased the daytime planetary boundary layer height and 10 m wind speed by 129.0–249.0 m and 0.05–0.15 ms-1 , respectively, in CAPAs in the four episodes. Aerosols were simulated to reduce the daytime near-surface photolysis rates of J[NO2] and J[O1D] by 1.8 × 10 -3 –2.0 × 10 -3 and 5.7 × 10 -6 –6.4 × 10 -6 s-1 , respectively, in CAPAs in the four episodes. All of the four episodes show the same conclusion, which is that the reduction in O3 by API is larger than that by ARF. API (ARF) was simulated to change daytime surface-layer O3 concentrations by - 8.5 ppb (parts per billion; - 2.9 ppb), - 10.3 ppb (- 1.0 ppb), - 9.1 ppb (- 0.9 ppb), and - 11.4 ppb (+ 0.7 ppb) in CAPAs of the four episodes, respectively. Process analysis indicated that the weakened O3 chemical production made the greatest contribution to API effect, while the reduced vertical mixing was the key process for ARF effect. Our conclusions suggest that future PM2.5 reductions may lead to O3 increases due to the weakened aerosol–radiation interactions, which should be considered in air quality planning. [ABSTRACT FROM AUTHOR]

The heterogeneous reaction of N2O5 on Cl-containing aerosols (heterogeneous N2O5 + Cl chemistry) plays a key role in chlorine activation, NOx recycling, and consequently O3 and PM2.5 formation. In this study, we use the GEOS-Chem model with additional anthropogenic and biomass burning chlorine emissions combined with updated parameterizations for the heterogeneous N2O5 + Cl chemistry (i.e., the uptake coefficient of N2O5 (γN2O5) and the ClNO2 yield (φClNO2)) to investigate the impacts of chlorine chemistry on air quality in China, the role of the heterogeneous N2O5 + Cl chemistry, and the sensitivity of air pollution formation to chlorine emissions and parameterizations for γN2O5 and φClNO2. The model simulations are evaluated against multiple observational datasets across China and show significant improvement in reproducing observations of particulate chloride, N2O5 , and ClNO2 when including anthropogenic chlorine emissions and updates to the parameterization of the heterogeneous N2O5 + Cl chemistry relative to the default model. The simulations show that total tropospheric chlorine chemistry could increase annual mean maximum daily 8 h average (MDA8) O3 by up to 4.5 ppbv but decrease PM2.5 by up to 7.9 µgm-3 in China, 83 % and 90 % of which could be attributed to the effect of the heterogeneous N2O5 + Cl chemistry. The heterogeneous uptake of N2O5 on chloride-containing aerosol surfaces is an important loss pathway of N2O5 as well as an important source of O3 and hence is particularly useful in elucidating the commonly seen ozone underestimations relative to observations. The importance of chlorine chemistry largely depends on both chlorine emissions and the parameterizations for the heterogeneous N2O5 + Cl chemistry. With the additional chlorine emissions, the simulations show that annual MDA8 O3 in China could be increased by up to 3.5 ppbv. The corresponding effect on PM2.5 concentrations varies largely with regions, with an increase of up to 4.5 µgm-3 in the North China Plain but a decrease of up to 3.7 µgm-3 in the Sichuan Basin. On the other hand, even with the same chlorine emissions, the effects on MDA8 O3 and PM2.5 in China could differ by 48 % and 27 %, respectively, between different parameterizations. [ABSTRACT FROM AUTHOR]

As an important issue in atmospheric environment, the contributions of anthropogenic emissions and meteorological conditions to air pollution have been little assessed over receptor regions in regional transport of air pollutants. In the present study of 5-year observations and modeling, we targeted the Twain-Hu Basin (THB), a large region of heavy PM2.5 pollution in central China, to assess the effects of meteorology on PM2.5 change over a receptor region in the regional transport of air pollutants. Based on observations of environment and meteorology over 2015–2019, the Kolmogorov–Zurbenko (KZ) filter was performed to decompose the PM2.5 variations into multiple timescale components over the THB, where the short-term, seasonal and long-term components accounted for, respectively, 47.5 %, 41.4 % and 3.7 % of daily PM2.5 changes. The short-term and seasonal components dominated the day-to-day PM2.5 variations with long-term component determining the change trend of PM2.5 concentrations over recent years. As the emission- and meteorology-related long-term PM2.5 components over the THB were identified, the meteorological contribution to the declining PM2.5 trend presented a distinct spatial pattern over the THB with northern positive rates up to 61.92 % and southern negative rates down to - 24.93 %. The opposite effects of meteorology on PM2.5 pollution could accelerate and offset the effects of emission reductions in the northern and southern THB, which is attributed to the upwind diffusion and downward accumulation of air pollutants over receptor regions in regional PM2.5 transport. It is noteworthy that the increasing conversion efficiencies of SO2 and NO2 to sulfate and nitrate for secondary PM2.5 could have offset the effect of PM2.5 emission reduction on air pollution in the THB during recent years, revealing the enhancing contribution of gaseous precursor emissions to PM2.5 concentrations under control of anthropogenic emissions of PM2.5 and the gaseous precursors over receptor regions in the regional transport of air pollutants. Our results highlight the effects of emission mitigation and meteorological changes on the source–receptor relationship of the regional transport of air pollutants with the implication of long-range transport of air pollutants for regional and global environment changes. [ABSTRACT FROM AUTHOR]

Coordinated control of fine particulate matter (PM 2.5) and ozone (O 3) has become a new and urgent issue for China's air pollution control. Biogenic volatile organic compounds (BVOCs) are important precursors of O 3 and secondary organic aerosol (SOA) formation. China experienced a rapid increase in BVOC emissions as a result of increased vegetation biomass. We applied WRF-Chem3.8 coupling with MEGAN2.1 to conduct long-term simulations for impacts of BVOC emissions on O 3 and SOA during 1981–2018, using the emission factors extrapolated by localized emission rates and annual vegetation biomass. In summer 2018, BVOC emissions were 9.91 Tg (in June), which led to an average increase of 8.6 ppb (16.75 % of the total) in daily maximum 8 h (MDA8) O 3 concentration and 0.84 µgm -3 (73.15 % of the total) in SOA over China. The highest contribution to O 3 is concentrated in the Great Khingan Mountains, Qinling Mountains, and most southern regions while in southern areas for SOA. Isoprene has the greatest contribution to O 3 , while monoterpene has the largest SOA production. BVOC emissions have distinguished impacts in different regions. The Chengdu–Chongqing (CC) region has the highest O 3 and SOA generated by BVOCs, while the Beijing–Tianjin–Hebei (BTH) region has the lowest. From 1981 to 2018, the interannual variation of BVOC emissions caused by increasing leaf biomass resulted in O 3 concentration increasing by 7.38 % at an average rate of 0.11 ppb yr -1 and SOA increasing by 39.30 % at an average rate of 0.008 µgm -3 yr -1. Due to the different changing trends of leaf biomass by region and vegetation type, O 3 and SOA show different interannual variations. The Fenwei Plain (FWP), Yangtze River Delta (YRD), and Pearl River Delta (PRD) regions have the most rapid O 3 increment, while the increasing rate of SOA in CC is the highest. BTH has the smallest enhancement in O 3 and SOA concentration. This study will help to recognize the impact of historical BVOC emissions on O 3 and SOA and further provide a reliable scientific basis for the precise prevention and control of air pollution in China. [ABSTRACT FROM AUTHOR]

Surface O3 pollution has become one of the most severe air pollution problems in China, which makes it of practical importance to understand O3 variability. A south–north dipole pattern of summer-mean O3 concentration in the east of China (DP- O3), which was centered in North China (NC) and the Pearl River Delta (PRD), has been identified from the simulation of a global 3-D chemical transport model for the period 1980–2019. Large-scale anticyclonic (cyclonic) and cyclonic (anticyclonic) anomalies over NC and the PRD resulted in a sharp contrast of meteorological conditions between the above two regions. The enhanced (restrained) photochemistry in NC and restrained (enhanced) O3 production in the PRD contributed to the DP- O3. Decreased sea ice anomalies near Franz Josef Land and associated warm sea surface in May enhanced the Rossby wave source over northern Europe and West Siberia, which eventually induced an anomalous Eurasia-like pattern to influence the formation of the DP- O3. The thermodynamic signals of the southern Indian Ocean dipole were stored in the subsurface and influenced the spatial pattern of O3 pollution in the east of China mainly through the Hadley circulation. The physical mechanisms behind the modulation of the atmospheric circulations and related DP- O3 by these two climate anomalies at different latitudes were evidently verified by large-scale ensemble simulations of the Earth system model. [ABSTRACT FROM AUTHOR]

Despite the growing interest in understanding haze formation in Chinese megacities, air pollution has been largely overlooked for the Harbin–Changchun (HC) metropolitan area, located in the severe cold climate region in northeast China. In this study, we unfolded significant variations of fine particulate matter (PM 2.5) in HC's central city (Harbin) during two sequential heating seasons of 2018–2019 and 2019–2020, and we explored major drivers for the observed variations. The two campaigns showed comparable organic carbon (OC) levels but quite different OC sources. The biomass burning (BB) to OC contribution decreased substantially for 2019–2020, which was attributed primarily to the transition of local policies on agricultural fires, i.e., from the "legitimate burning" policy released in 2018 to the "strict prohibition" policy in 2019. Meanwhile, the contribution of secondary OC (OC sec) increased significantly, associated with the much more frequent occurrences of high relative humidity (RH) conditions during the 2019–2020 measurement period. Similar to OC sec , the major secondary inorganic ions, i.e., sulfate, nitrate and ammonium (SNA), also exhibited RH-dependent increases. Given the considerable aerosol water contents predicted for the high-RH conditions, heterogeneous reactions were likely at play in secondary aerosol formation even in the frigid atmosphere in Harbin (e.g., with daily average temperatures down to below - 20 ∘ C). In brief, compared to 2018–2019, the 2019–2020 measurement period was characterized by a policy-driven decrease of biomass burning OC, a RH-related increase of OC sec and a RH-related increase of SNA, with the first two factors generally offsetting each other. In addition, we found that open burning activities were actually not eliminated by the strict prohibition policy released in 2019, based on a synthesis of air quality data and fire count results. Although not occurring during the 2019–2020 measurement period, agricultural fires broke out within a short period before crop planting in spring of 2020, and this resulted in off-the-charts air pollution for Harbin, with 1 h and 24 h PM 2.5 concentrations peaking at ∼ 2350 and 900 µ g/m 3 , respectively. This study indicates that sustainable use of crop residues remains a difficult challenge for the massive agricultural sector in northeast China. [ABSTRACT FROM AUTHOR]

Air pollution is substantially modulated by meteorological conditions, and especially their diurnal variations may play a key role in air quality evolution. However, the behaviors of temperature diurnal cycles along with the associated atmospheric condition and their effects on air quality in China remain poorly understood. Here, for the first time, we examine the diurnal cycles of day-to-day temperature change and reveal their impacts on winter air quality forecasting in mountain-basin areas. Three different diurnal cycles of the preceding day-to-day temperature change are identified and exhibit notably distinct effects on the day-to-day changes in atmospheric-dispersion conditions and air quality. The diurnal cycle with increasing temperature obviously enhances the atmospheric stability in the lower troposphere and suppresses the development of the planetary boundary layer, thus deteriorating the air quality on the following day. By contrast, the diurnal cycle with decreasing temperature in the morning is accompanied by a worse dispersion condition with more stable atmosphere stratification and weaker surface wind speed, thereby substantially worsening the air quality. Conversely, the diurnal cycle with decreasing temperature in the afternoon seems to improve air quality on the following day by enhancing the atmospheric-dispersion conditions on the following day. The findings reported here are critical to improve the understanding of air pollution in mountain-basin areas and exhibit promising potential for air quality forecasting. [ABSTRACT FROM AUTHOR]

An accurate emission inventory is a crucial part of air pollution management and is essential for air quality modelling. One source in an emission inventory, an industrial source, has been known with high uncertainty in both location and magnitude in China. In this study, a new reallocation method based on blue-roof industrial buildings was developed to replace the conventional method of using population density for the Chinese emission development. The new method utilized the zoom level 14 satellite imagery (i.e. Google®) and processed it based on hue, saturation, and value (HSV) colour classification to derive new spatial surrogates for province-level reallocation, providing more realistic spatial patterns of industrial PM 2.5 and NO 2 emissions in China. The WRF-CMAQ-based PATH-2016 model system was then applied with the new processed industrial emission input in the MIX inventory to simulate air quality in the Greater Bay Area (GBA) area (formerly called Pearl River Delta, PRD). In the study, significant root mean square error (RMSE) improvement was observed in both summer and winter scenarios in 2015 when compared with the population-based approach. The average RMSE reductions (i.e. 75 stations) of PM 2.5 and NO 2 were found to be 11 µ g m -3 and 3 ppb, respectively. Although the new method for allocating industrial sources did not perform as well as the point- and area-based industrial emissions obtained from the local bottom-up dataset, it still showed a large improvement over the existing population-based method. In conclusion, this research demonstrates that the blue-roof industrial allocation method can effectively identify scattered industrial sources in China and is capable of downscaling the industrial emissions from regional to local levels (i.e. 27 to 3 km resolution), overcoming the technical hurdle of ∼ 10 km resolution from the top-down or bottom-up emission approach under the unified framework of emission calculation. [ABSTRACT FROM AUTHOR]

We developed incremental reactivity (IR) scales for 116 volatile organic compounds (VOCs) in a Chinese megacity (Guangzhou) and elucidated their application in calculating the ozone (O3) formation potential (OFP) in China. Two sets of model inputs (emission-based and observation-based) were designed to localize the IR scales in Guangzhou using the Master Chemical Mechanism (MCM) box model and were also compared with those of the US. The two inputs differed in how primary pollutant inputs in the model were derived, with one based on emission data and the other based on observed pollutant levels, but the maximum incremental reactivity (MIR) scales derived from them were fairly similar. The IR scales showed a strong dependence on the chemical mechanism (MCM vs. Statewide Air Pollution Research Center), and a higher consistency was found in IR scales between China and the US using a similar chemical mechanism. With a given chemical mechanism, the MIR scale for most VOCs showed a relatively small dependence on environmental conditions. However, when the NOx availability decreased, the IR scales became more sensitive to environmental conditions and the discrepancy between the IR scales obtained from emission-based and observation-based inputs increased, thereby implying the necessity to localize IR scales over mixed-limited or NOx -limited areas. This study provides recommendations for the application of IR scales, which has great significance for VOC control in China and other countries suffering from serious O3 air pollution. [ABSTRACT FROM AUTHOR]