Recent Progress in Atmospheric Chemistry Research in China: Establishing a Theoretical Framework for the "Air Pollution Complex".

Atmospheric chemistry research has been growing rapidly in China in the last 25 years since the concept of the "air pollution complex" was first proposed by Professor Xiaoyan TANG in 1997. For papers published in 2021 on air pollution (only papers included in the Web of Science Core Collection database were considered), more than 24 000 papers were authored or co-authored by scientists working in China. In this paper, we review a limited number of representative and significant studies on atmospheric chemistry in China in the last few years, including studies on (1) sources and emission inventories, (2) atmospheric chemical processes, (3) interactions of air pollution with meteorology, weather and climate, (4) interactions between the biosphere and atmosphere, and (5) data assimilation. The intention was not to provide a complete review of all progress made in the last few years, but rather to serve as a starting point for learning more about atmospheric chemistry research in China. The advances reviewed in this paper have enabled a theoretical framework for the air pollution complex to be established, provided robust scientific support to highly successful air pollution control policies in China, and created great opportunities in education, training, and career development for many graduate students and young scientists. This paper further highlights that developing and low-income countries that are heavily affected by air pollution can benefit from these research advances, whilst at the same time acknowledging that many challenges and opportunities still remain in atmospheric chemistry research in China, to hopefully be addressed over the next few decades.

Study on the variation of air pollutant concentration and its formation mechanism during the COVID-19 period in Wuhan.

To prevent the spread of COVID-19 (2019 novel coronavirus), from January 23 to April 8 in 2020, the highest Class 1 Response was ordered in Wuhan, requiring all residents to stay at home unless absolutely necessary. This action was implemented to cut down all unnecessary human activities, including industry, agriculture and transportation. Reducing these activities to a very low level during these hard times meant that some unprecedented naturally occurring measures of controlling emissions were executed. Ironically, however, after these measures were implemented, ozone levels increased by 43.9%. Also worthy of note, PM2.5 decreased 31.7%, which was found by comparing the observation data in Wuhan during the epidemic from 8th Feb. to 8th Apr. in 2020 with the same periods in 2019. Utilizing CMAQ (The Community Multiscale Air Quality modeling system), this article investigated the reason for these phenomena based on four sets of numerical simulations with different schemes of emission reduction. Comparing the four sets of simulations with observation, it was deduced that the emissions should decrease to approximately 20% from the typical industrial output, and 10% from agriculture and transportation sources, attributed to the COVID-19 lockdown in Wuhan. More importantly, through the CMAQ process analysis, this study quantitatively analyzed differences of the physical and chemical processes that were affected by the COVID-19 lockdown. It then examined the differences of the COVID-19 lockdown impact and determined the physical and chemical processes between when the pollution increased and decreased, determining the most affected period of the day. As a result, this paper found that (1) PM2.5 decreased mainly due to the reduction of emission and the contrary contribution of aerosol processes. The North-East wind was also in favor of the decreasing of PM2.5. (2) O3 increased mainly due to the slowing down of chemical consumption processes, which made the concentration change of O3 pollution higher at about 4 p.m.-7 p.m. of the day, while increasing the concentration of O3 at night during the COVID-19 lockdown in Wuhan. The higher O3 concentration in the North-East of the main urban area also contributed to the increasing of O3 with unfavorable wind direction.

Drivers for the poor air quality conditions in North China Plain during the COVID-19 outbreak.

China's lockdown to control COVID-19 brought significant declines in air pollutant emissions, but haze was still a serious problem in North China Plain (NCP) during late-January to mid-February of 2020. We seek the potential causes for the poor air quality in NCP combining satellite data, ground measurements and model analyses. Efforts to constrain COVID-19 result in a drop-off of primary gaseous pollutants, e.g., -42.4% for surface nitrogen dioxide (NO2) and -38.9% for tropospheric NO2 column, but fine particulate matter (PM25) still remains high and ozone (O3) even increases sharply (+84.1%). Stagnant weather during COVID-19 outbreak, e.g., persistent low wind speed, frequent temperature inversion and wind convergence, is one of the major drivers for the poor air quality in NCP. The surface PM2.5 levels vary between -12.9~+15.1% in NCP driven by the varying climate conditions between the years 2000 and 2020. Besides, the persistent PM2.5 pollution might be maintained by the still intensive industrial and residential emissions (primary PM2.5), and increased atmospheric oxidants (+26.1% for ozone and +29.4% for hydroxyl radical) in response to the NO2 decline (secondary PM2.5). Further understanding the nonlinear response between atmospheric secondary aerosols and NOx emissions is meaningful to cope with the emerging air pollution problems in China.

Changes of air quality and its associated health and economic burden in 31 provincial capital cities in China during COVID-19 pandemic.

With outbreak of the novel coronavirus disease (COVID-19), immediate prevention and control actions were imposed in China. Here, we conducted a timely investigation on the changes of air quality, associated health burden and economic loss during the COVID-19 pandemic (January 1 to May 2, 2020). We found an overall improvement of air quality by analyzing data from 31 provincial cities, due to varying degrees of NO2, PM2.5, PM10 and CO reductions outweighing the significant O3 increase. Such improvement corresponds to a total avoided premature mortality of 9410 (7273-11,144) in the 31 cities by comparing the health burdens between 2019 and 2020. NO2 reduction was the largest contributor (55%) to this health benefit, far exceeding PM2.5 (10.9%) and PM10 (23.9%). O3 instead was the only negative factor among six pollutants. The period with the largest daily avoided deaths was rather not the period with strict lockdown but that during February 25 to March 31, due to largest reduction of NO2 and smallest increase of O3. Southwest, Central and East China were regions with relatively high daily avoided deaths, while for some cities in Northeast China, the air pollution was even worse, therefore could cause more deaths than 2019. Correspondingly, the avoided health economic loss attributable to air quality improvement was 19.4 (15.0-23.0) billion. Its distribution was generally similar to results of health burden, except that due to regional differences in willingness to pay to reduce risks of premature deaths, East China became the region with largest daily avoided economic loss. Our results here quantitatively assess the effects of short-term control measures on changes of air quality as well as its associated health and economic burden, and such information is beneficial to future air pollution control.

Atmospheric mercury in an eastern Chinese metropolis (Jinan).

Urban emissions are a major contributor to atmospheric Hg budgets. Continuous measurements of total gaseous mercury (TGM) and particulate-bound mercury (PHg) in PM2.5 were conducted from October 2015 to July 2016 in a metropolis, Jinan, in eastern China. Average TGM and PHg concentrations were 4.91 ± 3.66 ng m-3 and 451.9 ± 433.4 pg m-3, respectively, in the entire study period. During the winter heating period (HP), mean concentrations of TGM and PHg were 5.79 ng m-3 and 598.7 pg m-3, respectively, twice higher than those during the non-heating periods (NHPs). During the HP, TGM exhibited a distinct diurnal pattern with a peak in the morning and a minimum in the afternoon on less polluted days but a singular peak at midday on heavily polluted days. The diurnal variation of TGM during the NHPs was predominantly influenced by the variation in boundary layer height while during the HP by anthropogenic emissions. The ratio of PHg/PM2.5 in Jinan was one to two orders of magnitude larger than those elsewhere worldwide and those in soil and coal, which suggested the high enrichment of PHg in PM2.5 in Jinan. Correlation and principle component analysis results suggested that PHg and TGM had common combustion sources during the HP, whereas PHg resulted mainly from biomass burning and meteorological variations during the NHPs. High Hg concentrations in Jinan were mostly caused by emissions from coal-fired power plants, especially for those situated east of the sampling site. In addition, TGM and PHg concentrations significantly increased during haze and fog episodes, but decreased during a dust episode due possibly to strong ventilation conditions combined with partitioning of Hg between adsorption to PM2.5 and coarse dust particles.

Elucidating drivers of severe wintertime fine particulate matter pollution episodes in the Yangtze River Delta region of eastern China.

Understanding the causes and sources responsible for severe fine particulate matter (PM2.5) pollution episodes that occur under conducive synoptic weather patterns (SWPs) is essential for regional air quality management. The Yangtze River Delta (YRD) region in eastern China has experienced recurrent severe PM2.5 episodes during the winters from 2013 to 2017. In this study, we employed an objective classification approach, the self-organizing map, to investigate the underlying impact of predominant SWPs on PM2.5 pollution in the YRD. We further conducted a series of source apportionment simulations using the Particulate Source Apportionment Technology (PSAT) tool integrated within the Comprehensive Air Quality Model with Extensions (CAMx) to quantify the source contributions to PM2.5 pollution under different SWPs. Here we identified six predominant SWPs over the YRD that are robustly connected to the evolution of the Siberian High. Considering the regional average PM2.5 anomalies, our results show that polluted SWPs favourable for the occurrence of regional PM2.5 pollution account for 61-78 %. The most conducive SWP, associated with the highest regional exceedance (46 %) of PM2.5 levels, is characterized by noticeable cyclonic anomalies at 850 hPa and stagnant surface weather conditions. Our source apportionment analysis emphasizes the pivotal role of local emissions and intra-regional transport within the YRD in shaping PM2.5 pollution in representative cities. Local emissions have the most significant impact on PM2.5 levels in Shanghai (32-48 %), while PM2.5 pollution in Nanjing, Hangzhou, and Hefei is more influenced by intra-regional transport (33-61 %). Industrial and residential emissions are the dominant sources, contributing 32-41 % and 24-38 % to PM2.5, respectively. Under specific SWPs associated with a stronger influence of inter-regional transport from northern China, there is a synchronously remarkable enhancement in the contribution of residential emissions. Our study pinpoints the opportunities for future air quality planning that would benefit from quantitative source attribution linked to prevailing SWPs.

Anthropogenically and meteorologically modulated summertime ozone trends and their health implications since China's clean air actions.

Elevated ozone (O3) has emerged as the major air quality concern since China's clean air actions, offsetting the health benefits gained from improved air quality. Given the shifted ozone chemical regimes and recently boosted extreme weather in China, it's essential to rethink the O3 trends since 2013 for evaluations of air pollution mitigation policy. Here, we examine the anthropogenically and meteorologically modulated summertime O3 trends across China at different stages of the clean air actions using multi-source observations combined with multi-model calculations. Ozone increases steadily in China between 2013-2022, with a fast increase rate of 4.4 µg m-3 yr-1 in Phase I and a much smaller 0.6 µg m-3 yr-1 in Phase II of Action Plan. Results highlight that the deteriorative O3 pollution in Phase I and early Phase II is dominated by the nonlinear O3-emission response. Persistent decline in O3 precursors has shifted its chemical regime in urban areas and began to show a positive influence on ozone mitigation in recent years. Meteorological influence on O3 variations is minor until 2019 (∼10%), but it greatly accelerates or relieves the O3 pollution after then, showing comparable contribution to emissions. Epidemiological model predicts totally 0.8-3.0 thousand yr-1 more deaths across China with altered anthropogenic emissions since clean air actions, and additional health burdens by -1.5-0.3 thousand yr-1 from perturbated meteorology. This study calls for stringent emission control and climate adaptation strategies to attain the ozone pollution mitigation in China.

Particle-ozone complex pollution under diverse synoptic weather patterns in the Yangtze River Delta region: Synergistic relationships and the effects of meteorology and chemical compositions.

There is considerable academic interest in the particle-ozone synergistic relationship (PO) between fine particulate matter (PM2.5) and ozone (O3). Using various synoptic weather patterns (SWPs), we quantitatively assessed the variations in the PO, which is relevant to formulating policies aimed at controlling complex pollution in the air. First, based on one-year sampling data from March 2018 to February 2019, the SWPs classification of the Yangtze River Delta (YRD) was conducted using the sum-of-squares technique (SS). Five dominant SWPs can be found in the YRD region, including the Aleutian low under SWP1 (occurring 45 % of the year), a tropical cyclone under SWP2 (21 %), the tropical cyclone and western Pacific Subtropical High (WPSH) under SWP3 (15.4 %), the WPSH under SWP4 (6.9 %), and a continental high pressure under SWP5 (3.1 %). The phenomenon of a "seesaw" between PM2.5 and O3 concentrations exhibited significant spatial heterogeneity, which was influenced by meteorological mechanisms. Second, the multi-linear regression (MLR) model and the partial correlation (PCOR) analysis were employed to quantify the effects of dominant components and meteorological factors on the PO. Meteorological variables could collectively explain only 33.0 % of the PM2.5 variations, but 58.0 % for O3. O3 promoted each other with low concentrations of PM2.5 but was inhibited by high concentrations of PM2.5. High relative humidity (RH) was conducive to the generation of PM2.5 secondary components and enhanced the radiative effects of aerosols and the negative correlation of PO. In addition, attention should be paid to assessing the combined effects of precursor levels, weather, and chemical reactions on the particle-ozone complex pollution. The control of O3 pollutants should be intensified in summer, while the focus should be on reducing PM2.5 pollutants in winter. Prevention and control measures need to reflect the differences in weather conditions and pollution characteristics, with a focus on RH and secondary components of PM2.5.

Coping with the concurrent heatwaves and ozone extremes in China under a warming climate.

Intensive human activity has brought about unprecedented climate and environmental crises, in which concurrent heatwaves and ozone extremes pose the most serious threats. However, a limited understanding of the comprehensive mechanism hinders our ability to mitigate such compound events, especially in densely populated regions like China. Here, based on field observations and climate-chemistry coupled modelling, we elucidate the linkage between human activities and the climate system in heat-related ozone pollution. In China, we have observed that both the frequency and intensity of heatwaves have almost tripled since the beginning of this century. Moreover, these heatwaves are becoming more common in urban clusters with serious ozone pollution. Persistent heatwaves during the extremely hot and dry summers of 2013 and 2022 accelerated photochemical ozone production by boosting anthropogenic and biogenic emissions, and aggravated ozone accumulation by suppressing dry deposition due to water-stressed vegetation, leading to a more than 30% increase in ozone pollution in China's urban areas. The sensitivity of ozone to heat is demonstrated to be substantially modulated by anthropogenic emissions, and China's clean air policy may have altered the relationship between ozone and temperature. Climate model projections further highlight that the high-emission climate-socioeconomic scenario tends to intensify the concurrent heat and ozone extremes in the next century. Our results underscore that the implementation of a strict emission strategy will significantly reduce the co-occurrence of heatwaves and ozone extremes, achieving climate and environmental co-benefits.

Deciphering the seasonal dynamics of multifaceted aerosol-ozone interplay: Implications for air quality management in Eastern China.

We employed an enhanced WRF-Chem to investigate the discrete mechanisms of aerosol-radiation-feedback (ARF), extinction-photochemistry (AEP), and heterogeneous-reactions (AHR) across different seasons in eastern China, aiming to assess the synergistic effects arising from the simultaneous operation of multiple processes on O3 and PM2.5. Our findings demonstrated that ARF fostered the accumulation of pollutants and moisture, initiating two distinct feedback mechanisms concerning O3. The elevation in the NO/NO2 ratio amplified O3 consumption. Increased near-surface moisture diminished upper-level cloud formation, thereby enhancing photolysis rates and O3 photochemical production. The pronounced impact of heightened NO/NO2 on O3 led to a decrease of 0.1-2.7 ppb. When decoupled from ARF, AEP led to a more significant reduction in photolysis rates, resulting in declines in both O3 and PM2.5, except for an anomalous increase observed in summer, with O3 increasing by 1.6 ppb and PM2.5 by 2.5 µg m-3. The heterogeneous absorption of hydroxides in spring, autumn, and winter predominantly governed the AHR-induced variation of O3, leading to a decrease in O3 by 0.7-1 ppb. Conversely, O3 variations in summer were primarily dictated by O3-sensitive chemistry, with heterogeneous absorption of NOy catalyzing a decrease of 2.4 ppb in O3. Furthermore, AHR accentuated PM2.5 by facilitating the formation of fine sulfates and ammonium while impeding nitrate formation. In summer, the collective impact of ARF, AEP, and AHR (ALL) led to a substantial reduction of 6.2 ppb in O3, alleviating the secondary oxidation of PM2.5 and leading to a decrease of 0.3 µg m-3 in PM2.5. Conversely, albeit aerosol substantially depleted O3 by 0.4-4 ppb through their interactions except for summer, aerosol feedback on PM2.5 was more pronounced, resulting in a significant increase of 1.7-6.1 µg m-3 in PM2.5. Our study underscored the seasonal disparities in the ramifications of multifaceted aerosol-ozone interplay on air quality.

[Review of UAV-based Atmospheric Fine Particulate Matter and Ozone Pollution Detection and Source Localization].

In recent years, the management of atmospheric fine particulate matter(PM2.5) pollution in China has achieved staged success, but ozone(O3) pollution has increased rapidly. Detection and source localization of atmospheric pollutants is the basis and key to controlling the combined pollution of PM2.5 and O3. With the rapid development of UAV technology and sensor technology, air pollution detection based on UAV platforms can effectively obtain the structural characteristics of PM2.5 and O3 near the surface and accurately trace the source of air pollution events by applying the computer algorithms, with the characteristics of high timeliness, flexibility, and spatial and temporal resolution. This will help researchers understand the distribution, changes, and sources of regional pollutants and provide a scientific basis for the synergistic control of combined air pollution. This study reviewed the traditional air pollution detection methods, summarized the types of UAV platforms and detection instruments commonly used in pollution detection, concluded the applications of UAV-based PM2.5 and O3 pollution detection and the algorithms of pollution source localization, and discussed the future trends of UAV-based air pollution detection.

Assessment of HCHO in Beijing during 2009 to 2020 using satellite observation and numerical model: Spatial characteristic and impact factor.

Formaldehyde (HCHO) is an air pollutant that has a detrimental effect on human health and atmospheric environment. Until now, satellite observation has been increasingly a valuable source for monitoring the unconventional atmospheric pollutants due to the limited availability of ground-based HCHO data. Here, we used Ozone Monitoring Instrument (OMI) and the weather research and forecasting with chemistry (WRF-Chem) model to synergistically analyze the spatiotemporal variations of tropospheric HCHO in Beijing during 2009-2020, and the response of O3 to HCHO and NO2 in hotspots. We also discuss the multiple factors influencing the variation of HCHO and identify potential source area. The results indicated that HCHO column concentration is higher in eastern Beijing, and peaking in 2018 (16.68 × 1015 mol/cm2). O3 shows a good response to HCHO, with higher HCHO and NO2 photolysis leading to O3 increase in summer. In winter, decreasing HCHO and increasing NO2 inhibits the formation of O3. Transportation emissions contributed the most to HCHO, followed by the industrial sector, while residential sources have long-term effects. Isoprene produced by plants is one of the main sources of HCHO, whereas meteorological conditions can affect production efficiency. Biomass burning contributes less. Moreover, HCHO in Beijing is affected by the combined effects of local emission and external transport, and Hebei is the potential source area. This study reveals HCHO has a great accumulation potential in cities and highlights the dominant role of anthropogenic emissions, but also need to consider the influence of natural factors and regional transport.

[Pollution Characteristics and Source Apportionment of Volatile Organic Compounds in Lishui Area of Nanjing].

To understand the changes in the components of volatile organic compounds(VOCs), the contribution proportion of each component to ozone, and the VOCs sources, we monitored the VOCs for a year in Lishui. The results showed that theρ(TVOC) was 223.46 µg·m-3, ρ(alkanes) was 49.45 µg·m-3(22.3%), ρ(OVOCs) was 50.63 µg·m-3(22.66%), ρ(halogenated hydrocarbons) was 64.73 µg·m-3(28.95%), ρ(aromatic hydrocarbons) was 35.46 µg·m-3(15.87%), ρ(alkenes) was 18.26 µg·m-3(8.19%), and ρ(others) was 4.9 µg·m-3(2.2%). ρ(TVOC) was higher in summer(263.75 µg·m-3) and lower in winter(187.2 µg·m-3), with 246.11 µg·m-3 in spring and 204.77 µg·m-3 in autumn. The daily concentration of VOCs showed two peaks, one from 9:00 to 10:00 and another from 14:00 to 15:00, and the high concentration was mainly found in the urban main road area with dense human activities. The ozone formation potential(OFP) was 278.92 µg·m-3, and those of olefin and aromatic hydrocarbon were 114.47 µg·m-3(41.1%) and 113.49 µg·m-3(40.8%), respectively, contributing over 80%, which was an important precursor of ozone. On the other hand, the ratio of characteristic compounds to toluene/benzene(T/B) was 4.13, which indicated that it was greatly affected by the solvent usage. In the end, the results of positive matrix factorization(PMF) source apportionment showed that VOCs mainly came from solvent usage, industrial production, and traffic emissions. The VOCs pollution had a great influence on ozone, so it was necessary to strengthen the treatment of industrial production, solvent usages, and traffic emissions.

Impacts of meteorological factors and ozone variation on crop yields in China concerning carbon neutrality objectives in 2060.

Carbon neutrality objectives affect meteorology and ozone (O3) concentration in China, both of which would influence crop yields, thus food security. However, the joint impact of these two factors on crop yields in China is not clear. In this study, we investigated future trends in China's maize, rice, soybean, and wheat yields under a carbon-neutral scenario considering both regional emission reduction and global climate change in 2060. By combining a process-based crop model (Agricultural Production Systems sIMulator, APSIM) with O3 exposure equations, the impacts of regional emission reduction and global climate change were studied. The results suggest that regional emission reduction dominated the increase in yield by reducing the O3 concentration, whereas global climate change led to yield loss mainly through meteorological factors. The national yield decreases for the four crops ranged from 1.0% to 38.0% owing to meteorological factors, while O3 reduction resulted in additional yield increases ranging from 2.8% to 7.0%. The combined effect of carbon neutrality, which included both meteorological factors and O3 concentration, resulted in changes to the yields of maize, rice, soybean, and wheat of +4.3%, -7.3%, -24.0%, and -31.7%, respectively. It seems that crop production loss caused by meteorological factors in 2060 would be mitigated by the O3 reduction. Given the advantages of declining O3 concentration, regional emission reduction would likely benefit crop growth. However, global climate change may offset the benefits and threaten food production in China. Therefore, more strict emission reduction policies and global climate change mitigation actions are necessary to ensure food security in China.

The underlying mechanisms of PM2.5 and O3 synergistic pollution in East China: Photochemical and heterogeneous interactions.

The rapid development of Chinese cities is accompanied by air pollution. Although the implementation of air pollution control strategies in recent years has alleviated PM2.5 pollution, O3 pollution and the synergistic pollution of PM2.5 and O3 have become more serious. To understand the underlying chemical interaction mechanisms between PM2.5 and O3, we applied the modified Weather Research and Forecasting model with Chemistry (WRF-Chem) to study the effects of aerosol-photolysis feedback and heterogeneous reactions on the two pollutants and revealed the contribution of different mechanisms in different seasons and regions in Yangtze River Delta (YRD) in eastern China. We found that, through the aerosol-photolysis feedback, PM2.5 decreased the surface photolysis rates JNO2 and JO1D, resulting in a decrease in O3 concentration in the VOC-sensitive area and a slight increase in the NOx-sensitive area. The heterogeneous reactions reduced O3 concentration in the YRD in spring, autumn and winter by consuming HxOy. While in summer, the heterogeneous absorption of NOx decreased O3 in the NOx-sensitive areas and increased O3 in the VOC-sensitive areas. Heterogeneous reactions also promoted the secondary formation of fine sulfate and nitrate aerosols, especially in winter. Through the combined effect of two chemical processes, PM2.5 can lead to a decrease in O3 concentration of -3.3 ppb (-7.6 %), -2.2 ppb (-4.0 %), -2.9 ppb (-6.3 %), and - 5.9 ppb (-18.7 %), in spring, summer, autumn and winter in YRD. Therefore, if the PM2.5 concentration decreases, the weakening effect of PM2.5 on the ozone concentration will be reduced, resulting in the aggravation of ozone pollution. This study is important for understanding the synergistic pollution mechanism and provides a scientific basis for the coordinated control of urban air pollution.

A satellite-driven model to estimate long-term particulate sulfate levels and attributable mortality burden in China.

Ambient fine particulate matter (PM2.5) pollution is a major environmental and public health challenge in China. In the recent decade, the PM2.5 level has decreased mainly driven by reductions in particulate sulfate as a result of large-scale desulfurization efforts in coal-fired power plants and industrial facilities. Emerging evidence also points to the differential toxicity of particulate sulfate affecting human health. However, estimating the long-term spatiotemporal trend of sulfate is difficult because a ground monitoring network of PM2.5 constituents has not been established in China. Spaceborne sensors such as the Multi-angle Imaging SpectroRadiometer (MISR) instrument can provide complementary information on aerosol size and type. With the help of state-of-the-art machine learning techniques, we developed a sulfate prediction model under support from available ground measurements, MISR-retrieved aerosol microphysical properties, and atmospheric reanalysis data at a spatial resolution of 0.1°. Our sulfate model performed well with an out-of-bag cross-validationR2 of 0.68 at the daily level and 0.93 at the monthly level. We found that the national mean population-weighted sulfate concentration was relatively stable before the Air Pollution Prevention and Control Action Plan was enforced in 2013, ranging from 10.4 to 11.5 µg m-3. But the sulfate level dramatically decreased to 7.7 µg m-3 in 2018, with a change rate of -28.7 % from 2013 to 2018. Correspondingly, the annual mean total non-accidental and cardiopulmonary deaths attributed to sulfate decreased by 40.7 % and 42.3 %, respectively. The long-term, full-coverage sulfate level estimates will support future studies on evaluating air quality policies and understanding the adverse health effect of particulate sulfate.

Application of multi-angle spaceborne observations in characterizing the long-term particulate organic carbon pollution in China.

Ambient PM2.5 pollution is recognized as a leading environmental risk factor, causing significant mortality and morbidity in China. However, the specific contributions of individual PM2.5 constituents remain unclear, primarily due to the lack of a comprehensive ground monitoring network for constituents. This issue is particularly critical for carbonaceous species such as organic carbon (OC) and elemental carbon (EC), which are known for their significant health impacts, and understanding the OC/EC ratio is crucial for identifying pollution sources. To address this, we developed a Super Learner model integrating Multi-angle Imaging SpectroRadiometer (MISR) retrievals to predict daily OC concentrations across China from 2003 to 2019 at a 10-km spatial resolution. Our model demonstrates robust predictive accuracy, as evidenced by a random cross-validation R2 of 0.84 and an RMSE of 4.9 µg/m3, at the daily level. Although MISR is a polar-orbiting instrument, its fractional aerosol data make a significant contribution to the OC exposure model. We then use the model to explore the spatiotemporal distributions of OC and further calculate the EC/OC ratio in China. We compared regional pollution discrepancies and source contributions of carbonaceous pollution over three selected regions: Beijing-Tianjin-Hebei, Fenwei Plain, and Yunnan Province. Our model observes that OC levels are elevated in Northern China due to industrial operations and central heating during the heating season, while in Yunnan, OC pollution is mainly contributed by local forest fires during fire seasons. Additionally, we found that OC pollution in China is likely influenced by climate phenomena such as the El Niño-Southern Oscillation. Considering that climate change is increasing the severity of OC concentrations with more frequent fire events, and its influence on OC formation and dispersion, we suggest emphasizing the role of climate change in future OC pollution control policies. We believe this study will contribute to future epidemiological studies on OC, aiding in refining public health guidelines and enhancing air quality management in China.

Interannual relationship between displacement and intensity of East Asian jet stream and haze over eastern China in winter.

A recent case study indicated that the weakening of the East Asian subtropical jet was an important cause of the severe haze in North China in the winter of 2015. However, the interannual relationship between two key features, the displacement and the intensity of the East Asian jet stream (EAJS) and the haze days over eastern China (HDEC), remains unclear. Observed data, ERA-Interim reanalysis, and Community Earth System Model Large Ensemble Numerical Simulation(CESM-LENS) were used to investigate the interannual relationship between the EAJS and HDEC during the winter season from 1980 to 2017 and its possible associated atmospheric mechanisms. The results show that the northward movement of the EAJS is conducive to more HDEC by weakening synoptic-scale transient eddy activities (STEA) and baroclinicity, forming an upper-level anticyclonic anomaly over eastern China (EC). The local meteorological conditions (e.g., stronger temperature inversion potential, higher relative humidity, descending motion) are favorable for the accumulation of HDEC, showing consistent variations in more haze in the entire region of EC. The southward movement of the EAJS has the opposite effect. The strong East Asian subtropical jet (weak polar-front jet) could result in the distribution of the meridional dipole with less haze in north EC and more haze in south EC. The mean flow loses energy to the STEA over north EC and increases the baroclinicity, which is favorable for dispersing HDEC. However, the configuration of upper-level cyclonic and low-level southwest wind anomalies that appeared in south EC weakened the STEA, which favored the accumulation of HDEC. The observed results were further verified by CESM-LENS.

Assessment of long-term particulate nitrate air pollution and its health risk in China.

Air pollution is a major environmental and public health challenge in China and the Chinese government has implemented a series of strict air quality policies. However, particulate nitrate (NO3 -) concentration remains high or even increases at monitoring sites despite the total PM2.5 concentration has decreased. Unfortunately, it has been difficult to estimate NO3 - concentration across China due to the lack of a PM2.5 speciation monitoring network. Here, we use a machine learning model incorporating ground measurements and satellite data to characterize the spatiotemporal patterns of NO3 -, thereby understanding the disease burden associated with long-term NO3 - exposure in China. Our results show that existing air pollution control policies are effective, but increased NO3 - of traffic emissions offset reduced NO3 - of industrial emissions. In 2018, the national mean mortality burden attributable to NO3 - was as high as 0.68 million, indicating that targeted regulations are needed to control NO3 - pollution in China.

Visual range trends in the Yangtze River Delta Region of China, 1981-2005.

Visual range (VR) data from 1981 to 2005 were examined for 20 meteorological monitoring sites in the Yangtze River Delta Region of China. Cumulative percentile analysis was used to construct VR trend. The 25-yr average domain-average 50% VR was approximately 21.9 +/- 1.9 km. Domain-average 50% VR decreased from 1981 to 2005 with a trend of -2.41 km/decade. The worst 20% and 50% and best 20% VR and variation rates for the 20 sites were analyzed. The 50% VR of the town, county-level city, and prefecture-level city sites were 24.1, 21.5, and 19.4 km, respectively. The best 20% VR decreased fastest with a rate of -3.5 km/decade. Regional median VR decreased from the coastal sites to the inland sites. Ridit analysis and cumulative percentile were adopted to study the VR variation properties between economically developed areas (e.g., Nanjing and Hangzhou) and remote areas (e.g., Lvsi). The two analyses show that VR decreased in Nanjing and Hangzhou but remained constant in Lvsi from 1981 to 2005.