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A new long-term emission inventory called the Inversed Emission Inventory for Chinese Air Quality (CAQIEI) was developed in this study by assimilating surface observations from the China National Environmental Monitoring Centre (CNEMC) using the ensemble Kalman filter (EnKF) and the Nested Air Quality Prediction Modeling System (NAQPMS). This inventory contains the constrained monthly emissions of NOx, SO2, CO, primary PM2.5, primary PM10, and NMVOCs in China from 2013 to 2020, with a horizontal resolution of 15 km × 15 km. This paper documents detailed descriptions of the assimilation system and the evaluation results for the emission inventory. The results suggest that CAQIEI can effectively reduce the biases in the a priori emission inventory, with the normalized mean biases ranging from -9.1% to 9.5% in the a posteriori simulation, which are significantly reduced from the biases in the a priori simulations (-45.6% to 93.8%). The calculated RMSEs (0.3 mg/m³ for CO and 9.4-21.1 µg/m³ for other species, on the monthly scale) and correlation coefficients (0.76-0.94) were also improved from the a priori simulations, suggesting that CAQIEI can reasonably reproduce the magnitude and variation of emissions of different air pollutants in China. Based on CAQIEI, we estimated China's total emissions (including both natural and anthropogenic emissions) of the 6 species in 2015 to be as follows: 25.2 Tg of NOx, 17.8 Tg of SO2, 465.4 Tg of CO, 15.0 Tg of PM2.5, 40.1 Tg of PM10, and 46.0 Tg of NMVOCs. From 2015 to 2020, the total emissions reduced by 54.1% for SO2, 44.4% for PM2.5, 33.6% for PM10, 35.7% for CO, and 15.1% for NOx, but increased by 21.0% for NMVOCs. Larger emission reductions were achieved during the 2018-2020 action plan than during the 2013-2017 action plan for most species. In particular, NOx and NMVOC emissions were shown to increase during the 2013-2017 action plain, and there were obvious emission increases in the Fengwei Plain area over the Central China region. However, NOx and NMVOC emissions declined during the 2018-2020 action plan, and the emissions over the Fengwei Plain area also decreased. This suggests that the emission control policies were improved in the 2018-2020 action plan. We also compared CAQIEI with previous inventories, which verified our inversion results in terms of total emissions of NOx, SO2 and NMVOCs, and more importantly identified the potential uncertainties in our current understanding of China's air pollutant emissions. Firstly, CO emissions in China may be substantially underestimated by current inventories, with the CO emissions estimated by CAQIEI (426.8 Tg) being more than twice the amount in previous inventories (120.7-237.7 Tg). Significant underestimations for other air pollutant emissions may also exist over western and northeastern China. In addition, the NMVOC emissions were shown to be substantially underestimated over northern China but overestimated in southern China. Secondly, the emission reduction rates during 2015-2018 estimated by CAQIEI are generally smaller than those estimated by previous inventories, especially for NOx, PM10 and NMVOCs, suggesting that the mitigation effects of the air pollution control may be overestimated currently. In particular, China's NMVOC emissions were shown to have increased by 26.6% from 2015 to 2018, especially over the North China Plain by 38.0%), Northeast China (by 38.3%), and Central China (60.0%). In contrast, the emissions reduction rate of CO may be underestimated. Overall, our emissions inventory sheds new light on the complex variations of air pollutant emissions in China during its two recent clean air action periods, which could significantly improve our understanding of air pollutant emissions and related changes in air quality in China. [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]

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]

Although air quality guidelines generally use the atmospheric concentration of fine particulate matter (PM 2.5) as a metric for air pollution evaluation and management, the fact cannot be ignored that different particle toxicities are unequal and significantly related to their sources and chemical compositions. Therefore, judging the most harmful source and identifying the toxic component would be helpful for optimizing air quality standards and prioritizing targeted PM 2.5 control strategies to protect public health more effectively. Since the combustions of fuels, including oil, coal, and biomass, are the main anthropogenic sources of environmental PM 2.5 , their discrepant contributions to health risks of mixed ambient aerosol pollution dominated by the respective emission intensity and unequal toxicity of chemical components need to be identified. In order to quantify the differences between these combustion primary emissions, 10 types of PM 2.5 from each typical source group, i.e., vehicle exhaust, coal combustion, and plant biomass (domestic biofuel) burning, were collected for comparative study with toxicological mechanisms. In total, 30 types of individual combustion samples were intercompared with representative urban ambient air PM 2.5 samples, whose chemical characteristics and biological effects were investigated by component analysis (carbon, metals, soluble ions) and in vitro toxicity assays (cell viability, oxidative stress, inflammatory response) of human lung adenocarcinoma epithelial cells (A549). Carbonaceous fractions were plenteous in automobile exhaust and biomass burning, while heavy metals were more plentiful in PM 2.5 from coal combustion and automobile exhaust. The overall ranking of mass-normalized cytotoxicity for source-specific PM 2.5 was automobile exhaust > coal combustion > domestic plant biomass burning > ambient urban air, possibly with differential toxicity triggers, and showed that the carbonaceous fractions (organic carbon, OC; elemental carbon, EC) and redox-active transition metals (V, Ni, Cr) assisted by water-soluble ions (Ca 2+ , Mg 2+ , F - , Cl -) might play important roles in inducing cellular reactive organic species (ROS) production, causing oxidative stress and inflammation, resulting in cell injury and apoptosis, and thus damaging human health. Coupled with the source apportionment results of typical urban ambient air PM 2.5 in eastern China, reducing toxic PM 2.5 from these anthropogenic combustions will be greatly beneficial to public health. In addition to the air pollution control measures that have been implemented, like strengthening the vehicle emission standards, switching energy from coal to gas and electricity, and controlling the open incineration of agricultural straws, further methods could be considered, especially by preferentially reducing the diesel exhaust, lessening the coal combustion by replacement with low-ash clean coals, and depressing the rural crop straw biomass burning emissions. [ABSTRACT FROM AUTHOR]

China has been conducting a series of actions on air quality improvement for the past decades, and air pollutant emissions have been changing swiftly across the country. Provinces are an important administrative unit for air quality management in China; thus a reliable provincial-level emission inventory for multiple years is essential for detecting the varying sources of pollution and evaluating the effectiveness of emission controls. In this study, we selected Jiangsu, one of the most developed provinces in China, and developed a high-resolution emission inventory of nine species for 2015–2019, with improved methodologies for different emission sectors, best available facility-level information on individual sources, and real-world emission measurements. Resulting from implementation of strict emission control measures, the anthropogenic emissions were estimated to have declined 53 %, 20 %, 7 %, 2 %, 10 %, 21 %, 16 %, 6 %, and 18 % for sulfur dioxide (SO 2), nitrogen oxides (NO x), carbon monoxide (CO), non-methane volatile organic compounds (NMVOCs), ammonia (NH 3), inhalable particulate matter (PM 10), fine particulate matter (PM 2.5), black carbon (BC), and organic carbon (OC) from 2015 to 2019, respectively. Larger abatement of SO 2 , NO x , and PM 2.5 emissions was detected for the more developed region of southern Jiangsu. During the period from 2016 to 2019, the ratio of biogenic volatile organic compounds (BVOCs) to anthropogenic volatile organic compounds (AVOCs) exceeded 50 % in the month of July, indicating the importance of biogenic sources for summer O 3 formation. Our estimates in annual emissions of NO x , NMVOCs, and NH 3 were generally smaller than the national emission inventory, MEIC (the Multi-resolution Emission Inventory for China), but larger for primary particles. The discrepancies between studies resulted mainly from different methods of emission estimation (e.g., the procedure-based approach for AVOC emissions from key industries used in this work) and inconsistent information of emission source operation (e.g., the penetration and removal efficiencies of air pollution control devices). Regarding the different periods, more reduction of SO 2 emissions was found between 2015 and 2017 and of NO x , AVOCs, and PM 2.5 between 2017 and 2019. Among the selected 13 major measures, the ultra-low-emission retrofit in the power sector was the most important contributor to the reduced SO 2 and NO x emissions (accounting for 38 % and 43 % of the emission abatement, respectively) for 2015–2017, but its effect became very limited afterwards as the retrofit had been commonly completed by 2017. Instead, extensive management of coal-fired boilers and the upgrade and renovation of non-electrical industry were the most important measures for 2017–2019, accounting collectively for 61 %, 49 %, and 57 % reduction of SO 2 , NO x , and PM 2.5 , respectively. Controls on key industrial sectors were the most effective for AVOC reduction in the two periods, while measures relating to other sources (transportation and solvent replacement) have become more important in recent years. Our provincial emission inventory was demonstrated to support high-resolution air quality modeling for multiple years. Through scenario setting and modeling, worsened meteorological conditions were found from 2015 to 2019 for PM 2.5 and O 3 pollution alleviation. However, the efforts on emission controls were identified to largely overcome the negative influence of meteorological variation. The changed anthropogenic emissions were estimated to contribute 4.3 and 5.5 µ g m -3 of PM 2.5 concentration reduction for 2015–2017 and 2017–2019, respectively. While O 3 was elevated by 4.9 µ g m -3 for 2015–2017, the changing emissions led to 3.1 µ g m -3 of reduction for 2017–2019, partly (not fully though) offsetting the meteorology-driven growth. The analysis justified the validity of local emission control efforts on air quality improvement and provided a scientific basis to formulate air pollution prevention and control policies for other developed regions in China and worldwide. [ABSTRACT FROM AUTHOR]

Non-methane short-lived climate forcers (SLCFs), including aerosols, ozone, and their precursors, are important climate forcings and primary air pollutants. Future stringent SLCF emissions controls to mitigate air pollution will substantially impact regional climate change. Here, we investigate the changes in future climate extremes and resulting population exposure risks in Asia during 2031–2050 in response to non-methane SLCF emissions reductions using multi-model ensemble (MME) simulations under two shared socioeconomic pathway (SSP) scenarios with the same greenhouse gas (GHG) emissions but weak (SSP3-7.0) and strong (SSP3-7.0-lowNTCF) air quality control measures from the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP), which is endorsed by the Coupled Model Intercomparison Project phase 6 (CMIP6). The MME results show that future reductions in non-methane SLCF emissions lead to an increase of 0.23 ± 0.16 W m -2 in global annual mean effective radiative forcing, thereby magnifying the GHG-induced global surface warming by 0.19 ± 0.1 K during 2031–2050. In terms of the entire study area of Asia, the additional warming caused by the non-methane SLCF reductions increases the temperature of the hottest days (TXx) by 0.3 ± 0.1 K, the percentage of warm days (TX90p) by 4.8 ± 2.2 %, the number of tropical nights (TR) by 1.7 ± 0.8 d, the warm-spell duration (WSDI) by 1.0 ± 0.4 d, the number of heavy precipitation days (R10) by 1.0 ± 0.5 d, the maximum consecutive 5 d precipitation (RX5day) by 1.0 ± 0.3 mm, and the total wet-day precipitation (R95p) by 16.4 ± 7.3 mm during 2031–2050. In terms of sub-regional changes in temperature extremes, the largest regional increases in TXx, TX90p, and WSDI occur in northern India (NIN) and northern China (NC). Relatively large increases in TR are projected in NC and the Sichuan Basin (SCB), reaching 5.1 ± 2.5 d and 4.9 ± 3.3 d, respectively. For precipitation extremes, the regional changes are greatest in southern China (SC), particularly southwestern China (SWC), where reductions in non-methane SLCF emissions increase R10 by 2.5 ± 1.9 d, RX5day by 2.5 ± 1.5 mm, and R95p by 37.5 ± 22.6 mm. Moreover, the populations exposed to temperature and precipitation extremes increase most sharply in NIN, reaching (32.2 ± 11.4) × 10 7 person-days and (4.6 ± 6.1) × 10 6 person-days during 2031–2050, respectively, followed by NC and SCB. Our results highlight the significant impacts of non-methane SLCF reductions on future climate extremes and related exposure risks in eastern and southern Asia, which are comparable to the impact associated with increased GHG forcing in some regions. [ABSTRACT FROM AUTHOR]

Dust is an important aerosol affecting air quality in China in the winter and spring seasons. Dust in China is potentially influenced by the interannual climate variability associated with El Niño. Here, the impacts of El Niño with different temporal and spatial types on dust pollution in boreal winter and spring in China and the potential mechanisms are investigated using a state-of-the-art Earth system model (E3SMv1). We find that the eastern Pacific (EP) and central Pacific (CP) El Niño both increase wintertime dust concentrations by 5–50 µ g m -3 over central-eastern China. Due to a stronger wind and lower relative humidity, which favor dust emissions near sources, and a strengthened northwesterly and reduced precipitation, which are conducive to dust transport, dust concentrations during the CP El Niño are 5–20 µ g m -3 higher in northern China than during the EP El Niño, although the changes are mostly insignificant. El Niño with a short duration (SD) increases boreal winter dust concentrations by 20–100 µ g m -3 over northern China relative to the climatological mean, while there is a decrease of 5–50 µ g m -3 during the long-duration (LD) El Niño, which is also related to the El Niño-induced changes in atmospheric circulation, precipitation, and relative humidity. In the following spring season, all types of El Niño events enhance dust over northern China, but only the increase during the LD El Niño is statistically significant, suggesting that the weaker intensity but longer duration of the LD El Niño events can significantly affect spring dust in China. Our results contribute to the current knowledge of the influence of El Niño on dust pollution, which has profound implications for air pollution control and dust storm prediction. [ABSTRACT FROM AUTHOR]

Aerosol acidity plays a key role in regulating the chemistry and toxicity of atmospheric aerosol particles. The trend of aerosol pH and its drivers is crucial in understanding the multiphase formation pathways of aerosols. Here, we reported the first trend analysis of aerosol pH from 2011 to 2019 in eastern China, calculated with the ISORROPIA model based on observed gas and aerosol compositions. The implementation of the Air Pollution Prevention and Control Action Plan led to -35.8 %, -37.6 %, -9.6 %, -81.0 % and 1.2 % changes of PM 2.5 , SO42- , NHx , non-volatile cations (NVCs) and NO3- in the Yangtze River Delta (YRD) region during this period. Different from the drastic changes of aerosol compositions due to the implementation of the Air Pollution Prevention and Control Action Plan, aerosol pH showed a minor change of -0.24 over the 9 years. Besides the multiphase buffer effect, the opposite effects from the changes of SO42- and non-volatile cations played key roles in determining this minor pH trend, contributing to a change of +0.3 8 and -0.35 , respectively. Seasonal variations in aerosol pH were mainly driven by the temperature, while the diurnal variations were driven by both temperature and relative humidity. In the future, SO2 , NOx and NH3 emissions are expected to be further reduced by 86.9 %, 74.9 % and 41.7 % in 2050 according to the best health effect pollution control scenario (SSP1-26-BHE). The corresponding aerosol pH in eastern China is estimated to increase by ∼0.19 , resulting in 0.04 less NO3- and 0.12 less NH4+ partitioning ratios, which suggests that NH3 and NOx emission controls are effective in mitigating haze pollution in eastern China. [ABSTRACT FROM AUTHOR]

Exposure to high concentration levels of fine particle matter with diameter ≤2.5 µ m (PM 2.5) can lead to great threats to human health in the east of China. Air pollution control has greatly reduced the PM 2.5 concentration and entered a crucial stage that required support like fine seasonal prediction. In this study, we analyzed the contributions of emission predictors and climate variability to seasonal prediction of PM 2.5 concentration. The socioeconomic PM 2.5 , isolated by atmospheric chemical models, could well describe the gradual increasing trend of PM 2.5 during the winters of 2001–2012 and the sharp decreasing trend since 2013. The preceding climate predictors have successfully simulated the interannual variability in winter PM 2.5 concentration. Based on the year-to-year increment approach, a model for seasonal prediction of gridded winter PM 2.5 concentration (10 km × 10 km) in the east of China was trained by integrating emission and climate predictors. The area-averaged percentage of same sign was 81.4 % (relative to the winters of 2001–2019) in the leave-one-out validation. In three densely populated and heavily polluted regions, the correlation coefficients were 0.93 (North China), 0.95 (Yangtze River Delta) and 0.87 (Pearl River Delta) during 2001–2019, and the root-mean-square errors were 6.8, 4.2 and 4.7 µ g m -3. More important, the significant decrease in PM 2.5 concentration, resulting from the implementation of strict emission control measures in recent years, was also reproduced. In the recycling independent tests, the prediction model developed in this study also maintained high accuracy and robustness. Furthermore, the accurate gridded PM 2.5 prediction had the potential to support air pollution control on regional and city scales. [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]

A multi-model simulation system for street-level circulation and pollutant tracking (S-TRACK) has been developed by integrating the Weather Research and Forecasting (WRF), the STAR-CCM+ (computational fluid dynamics model – CFD), and the Flexible Particle (FLEXPART) models. The winter wind environmental characteristics and the potential contribution of traffic sources to nearby receptor sites in a city district of China are analysed with the system for January 2019. It is found that complex building layouts change the structure of the wind field and thus have an impact on the transport of pollutants. The wind speed inside the building block is lower than the background wind speed due to the dragging effect of dense buildings. Ventilation is better when the dominant airflow is in the same direction as the building layout. Influenced by the building layout, the local circulations show that the windward side of the building is mostly the divergence zone, and the leeward side is mostly the convergence zone, which is more obvious for high buildings. With the hypothesis that the traffic sources are uniformly distributed on each road and with identical traffic intensity, the potential contribution ratios (PCRs) of four traffic sources to certain specific sites under the influence of the street-level circulations are estimated with the method of residence time analysis. It is found that the contribution ratio varies with the height of the receptor site. As a result of the generally upward motion in the airflow, the position with the greatest PCR from the four road traffic sources is located at a certain height which is commonly influenced by the distance of this location from the traffic source and the background wind field (about 15 m in this study). The potential contribution of a road to one of the receptor sites is also investigated under different wind directions. The established system and the results can be used to understand the characteristics of urban wind environment and to help the air pollution control planning in urban areas. [ABSTRACT FROM AUTHOR]