A new approach of air pollution regionalization based on geographically weighted variations for multi-pollutants in China.

Air pollution regionalization is a key and necessary action to identify pollution regions for implementing control measures. Here we present a new approach called Geographically Weighted Rotation Empirical Orthogonal Function (GWREOF) for air pollution regionalization in China. Compared with previous methods, such as EOF, REOF, and K-mean, GWREOF better accounts for the variability of air pollution conditions driven by emission patterns and meteorology with centralized spatial locations. We apply GWREOF to multiple air pollutants (such as PM2.5, O3, and other monitored air pollutants) and air quality metrics using their measured spatial and temporal variations in 337 Chinese cities over 2015-2020. We find that the regionalization results for different air pollutants are highly similar, primarily determined by topography and meteorological conditions in China. Therefore, we propose an integrated regionalization result, which identifies 18 air pollution control regions in China and can be applied to multiple pollutants and different years. We further analyze PM2.5, O3, and OX (O3 + NO2) pollution levels and their correlations in these regions. PM2.5 and O3 correlations are generally strongly positive in southern China while negative in northern China. However, PM2.5 and OX correlations are broadly positive in China, reflecting the crucial role of atmospheric oxidizing capacity. Regional-specific and coordinated control measures are in need as China's air pollution strategy transits from PM2.5-focused to PM2.5-O3 synergic control.

Modeling study on the roles of the deposition and transport of PM2.5 in air quality changes over central-eastern China.

The role of PM2.5 (particles with aerodynamic diameters ≤ 2.5 µm) deposition in air quality changes over China remains unclear. By using the three-year (2013, 2015, and 2017) simulation results of the WRF/CUACE v1.0 model from a previous work (Zhang et al., 2021), a non-linear relationship between the deposition of PM2.5 and anthropogenic emissions over central-eastern China in cold seasons as well as in different life stages of haze events was unraveled. PM2.5 deposition is spatially distributed differently from PM2.5 concentrations and anthropogenic emissions over China. The North China Plain (NCP) is typically characterized by higher anthropogenic emissions compared to southern China, such as the middle-low reaches of Yangtze River (MLYR), which includes parts of the Yangtze River Delta and the Midwest. However, PM2.5 deposition in the NCP is significantly lower than that in the MLYR region, suggesting that in addition to meteorology and emissions, lower deposition is another important factor in the increase in haze levels. Regional transport of pollution in central-eastern China acts as a moderator of pollution levels in different regions, for example by bringing pollution from the NCP to the MLYR region in cold seasons. It was found that in typical haze events the deposition flux of PM2.5 during the removal stages is substantially higher than that in accumulation stages, with most of the PM2.5 being transported southward and deposited to the MLYR and Sichuan Basin region, corresponding to a latitude range of about 24°N-31°N.

Multi-scale analysis of the impacts of meteorology and emissions on PM2.5 and O3 trends at various regions in China from 2013 to 2020 3. Mechanism assessment of O3 trends by a model.

A multiscale analysis of meteorological trends was carried out to investigate the impacts of the large-scale circulation types as well as the local-scale key weather elements on the complex air pollutants, i.e., PM2.5 and O3 in China. Following accompanying papers on synoptic circulation impact and key weather elements and emission contributions (Gong et al., 2022a; Gong et al., 2022b), an emission-driven Observation-based Box Model (e-OBM) was developed to study the impact mechanisms on O3 trend and quantitatively assess the effects of variation in the emissions control over 2013-2020 for Beijing, Chengdu, Guangzhou and Shanghai. Compared with the original OBM, the e-OBM not only improves the performance to simulate the hourly O3 peak concentration in daytime, but also reasonably reproduces the maximum daily 8-hour average (MDA8) O3 concentrations in the four cities. Based upon the sensitivity experiments, it is found that the meteorology is the dominant driver for the MDA8 O3 trend, contributing from about 32 % to 139 % to the variations. From the mechanistic point of view, the variations of meteorology lead to the enhancement of atmospheric oxidation capacity and the acceleration of O3 production. Further evaluation to the emission changes in four cities shows that the O3-precursors relationships of the four cities have been changed from the VOC-limited regime in 2013 to the transition regime or near-transition regime in 2020. Though the NOx/VOCs ratios have been obviously decreased, the emission reductions up to 2020 were still not enough to mitigate O3 pollution in these cities. It is emphasized in this study that the strengthened control measures with maintaining a certain ratio of NOx and VOCs should be implemented to further curb the increasing trend of O3 in urban areas.

Effect of vegetation seasonal cycle alterations to aerosol dry deposition on PM2.5 concentrations in China.

The effect of vegetation seasonal cycle alterations to aerosol dry deposition on PM2.5 concentrations (hereafter referred as the VSC effect) in China was investigated using a numerical modelling system (WRF/CUACE). Two simulation experiments using the vegetation parameters in particle dry deposition schemes typical for January and July revealed an absolute increase in surface PM2.5 concentrations of about 2.4 µg/m3 and a 5.5% relative increase in China (within model domain 2). The effect in non-urban areas was more significant than that in urban areas. The increases in PM2.5 concentrations in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), Pearl River Delta (PRD), Sichuan Basin (SCB), and Central China (CC) were calculated as 1.9 µg/m3, 3.4 µg/m3, 3.1 µg/m3, 4.3 µg/m3, and 4.9 µg/m3, respectively, corresponding to relative increases of 2.9%, 4.5%, 5.4%, 5.8%, and 5.9%. These results demonstrate that the effect of decreased particle dry deposition due to reduced vegetation in southern areas was stronger, which was partially attributed to the increased vegetation cover and more significant seasonal changes in those regions. Furthermore, the increased PM2.5 concentrations caused by the VSC effect were transported from north to south via the winter northerly winds, which weakened the effect in North China Plain and enhanced the effect in parts of central and southern China, such as the south of CC. Although the surface PM2.5 concentration was relatively high in North China Plain, the effects of the northerly wind and relatively small dry deposition velocity meant that the removal of PM2.5 in that region was relatively less than in southern areas of China. These results will contribute to understanding of the underlying mechanisms of PM2.5 enhancement during winter in China.

Multi-scale analysis of the impacts of meteorology and emissions on PM2.5 and O3 trends at various regions in China from 2013 to 2020 2. Key weather elements and emissions.

A multiscale analysis of meteorological trends was carried out to investigate the impacts of the large-scale circulation types as well as the local-scale key weather elements on the complex air pollutants, i.e., PM2.5 and O3 in China. Following an accompanying paper on synoptic circulation impact (Gong et al., 2022), using a multi-linear regression model, the trends of key meteorological elements at local scale, i.e., temperature, relative humidity, solar radiation, PBL height, precipitation and wind speed, are analyzed and correlated with the trends of PM2.5 and O3 levels to identify significantly influencing factors in seven Chinese cities. Furthermore, with additional emission surrogates introduced in the regression model, the impacts on the trends by meteorology and emission were separated and quantified. Results show that the increasing trends of O3 at most Chinese cities were largely attributed to the trends of meteorological elements of temperature and solar radiation, while the trends of PM2.5 are mostly contributed by the emission reduction measures of PM2.5 and its precursors. The meteorology alone can explain approximately 57-80% of the O3 variations and only 20-33% of the PM2.5 variations. With the addition of emission surrogates, this explanation percentage is increased to about 57-82% for O3 but significantly enhanced to 71-83% for PM2.5.

Multi-scale analysis of the impacts of meteorology and emissions on PM2.5 and O3 trends at various regions in China from 2013 to 2020 1: Synoptic circulation patterns and pollution.

A multiscale analysis of meteorological trends was carried out to investigate the impacts of the large-scale circulation types as well as the local-scale key weather elements on the complex air pollutants, i.e. PM2.5 and O3 in China. As the first paper in the series, the relationship between synoptic circulation patterns and pollution was investigated. Six types of circulation patterns are defined and clustered to correlate with the observed pollutant levels, resulting in the identification of the impact similarity and difference of circulations on PM2.5 and O3 for three regions in China, i.e., the BTH (Beijing, Tianjin and Hebei), YRD (Yangtze River Delta) and PRD (Peral River Delta), from 2013 to 2020. It is found that the six clustered circulation patterns were able to classify the circulation patterns that influence the pollutants and yield significant correlations with O3 and PM2.5 in three regions. The major circulation patterns governing the heavy PM2.5 and O3 were identified separately for each region and found to show inter-annual variabilities. Composite analysis indicated that there were some circulation patterns that caused the dual-highs of PM2.5 and O3 with about 13%, 8% and 3% occurrences during the period of 2013 to 2020 in Beijing, Shanghai and Guangzhou, respectively. The key weather elements for each type of circulation pattern were also identified. A detailed study of the impacts of key weather elements and emissions on the PM2.5 and O3 trends will accompany this paper (Gong et al., 2022).

Development and application of an automated air quality forecasting system based on machine learning.

As one of the most concerned issues in modern society, air quality has received extensive attentions from the public and the government, which promotes the continuous development and progress of air quality forecasting technology. In this study, an automated air quality forecasting system based on machine learning has been developed and applied for daily forecasts of six common pollutants (PM2.5, PM10, SO2, NO2, O3, and CO) and pollution levels, which can automatically find the best "Model + Hyperparameters" without human intervention. Five machine learning models and an ensemble model (Stacked Generalization) were integrated into the system, supported by a knowledge base containing the meteorological observed data, pollutant concentrations, pollutant emissions, and model reanalysis data. Then five-year data (2015-2019) of Beijing, Shanghai, Guangzhou, Chengdu, Xi'an, Wuhan, and Changchun in China, were used as an application case to study the effectiveness of the automated forecasting system. Based on the analysis of seven evaluation criteria and pollution level forecasts, combined with the forecasting results for the next 3-days, it is found that the automated system can achieve satisfactory forecasting performance, better than most of numerical model results. This implied that the developed system unveils a good application prospect in the field of environmental meteorology.

Impact of Arctic Oscillation anomalies on winter PM2.5 in China via a numerical simulation.

The impact of Arctic Oscillation (AO) anomalies on winter PM2.5 variability in China was investigated using a numerical modeling system (WRF-CUACE). The model results showed that the influence of AO anomalies on winter PM2.5 concentration was mainly concentrated in eastern China, especially in Central China (CEN), Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), and Pearl River Delta (PRD) and was mostly consistent with the conclusions of a previous analysis using haze data. Winter PM2.5 concentrations in CEN and BTH increased under abnormally high AO and decreased under abnormally low AO due to the subsequent changes in specific meteorological conditions, such as temperature, wind speed, and boundary layer height. Winter PM2.5 decreased in the YRD and PRD in both abnormally high and low AO years due to more favorable vertical transport conditions and regional transport capacity compared with those of other regions. In addition to meteorological factors, AO anomalies also impacted PM2.5 depositions in winter, with more apparent effects in southern China. It is found that AO had a larger impact on dry deposition than on wet deposition, and dry deposition was a dominant factor affecting PM2.5 concentrations in CEN.

A new parameterization of uptake coefficients for heterogeneous reactions on multi-component atmospheric aerosols.

Based on laboratory studies and field observations, a new parameterization of uptake coefficients for heterogeneous reactions on multi-component aerosols is developed in this work. The equivalent ratio (ER) of inorganic aerosol is used to establish the quantitative relationship between the heterogeneous uptake coefficients and the composition of aerosols. Incorporating the new ER-dependent scheme, the WRF-CUACE model has been applied to simulate sulfate mass concentrations during December 2017 in the Beijing-Tianjin-Hebei region and evaluate the role of aerosol chemical components played in the sulfate formation. Simulated temporal variations and magnitudes of sulfate show good agreement with the observations by using this new scheme. From clean to polluted cases, although both dominant cations and anions increase significantly, the equivalent ratio decreases gradually and is closer to unity, representing the variation of aerosol compositions, which inhibits the heterogeneous uptake of SO2, with the uptake coefficient decreasing from 1 × 10-4 to 5.3 × 10-5. Based on this phenomenon, a self-limitation process for heterogeneous reactions with the increasing secondary inorganic aerosol from clean to polluted cases is proposed.

Temporal and spatial discrepancies of VOCs in an industrial-dominant city in China during summertime.

Ozone (O3) pollution is currently problematic to cities across the globe. Many non-methane hydrocarbons (NMHCs) are efficient O3 precursors. In this study, target volatile organic compounds (VOCs), including oxygenated VOCs (known as carbonyls), were monitored at eight sampling sites distributed in urban and suburban in the typical and industrial-dominant city of Shaoxing, Zhejiang province, China. At the suburban sites, C8-C12 alkanes, aromatics with lower reactivity (kOH <13 × 10-12 cm3 mol-1 s-1) and acetonitrile were more abundant than urban ones due to higher emissions from diesel-fueled trucks and biomass burning. In general, higher abundances of total quantified NMHCs (ΣNMHC) were found on high O3 (HO) days. The increments of formaldehyde (C1) and O3 were higher in urban than suburban, while a reverse trend was seen for acetaldehyde (C2). Substantial and local biogenic inputs of C2 were found in suburban in the afternoon when both temperature and light intensity reached maximum of the day. In urban, higher increment was found for O3 than the carbonyls, representing that the secondary formation of O3 was more efficient. Distance decay gradient of most representative NMHCs were positively correlated to the distances from a westernmost industrial origin located at the upwind location. The net loss rates of the NMHCs ranged from -0.009 to -0.11 ppbv km-1, while the higher rates were seen for the most reactive species like C2-C4 alkenes. The results and interpretation of this study are informative to establish efficient local control measures for O3 and the related percussors for the microscale industrial cities in China.

Source apportionment of particulate matter based on numerical simulation during a severe pollution period in Tangshan, North China.

Facing serious air pollution problems, the Chinese government has taken numerous measures to prevent and control air pollution. Understanding the sources of pollutants is crucial to the prevention of air pollution. Using numerical simulation method, this study analysed the contributions of the total local emissions and local emissions from different sectors (such as industrial, traffic, resident, agricultural, and power plant emissions) to PM2.5 concentration, backward trajectory, and potential source regions in Tangshan, a typical heavy industrial city in north China. The impact of multi-scale meteorological conditions on source apportionment was investigated. From October 2016 to March 2017, total local emissions accounted for 46.0% of the near-surface PM2.5 concentration. In terms of emissions from different sectors, local industrial emissions which accounted for 23.1% of the near-surface PM2.5 concentration in Tangshan, were the most important pollutant source. Agricultural emissions were the second most important source, accounting for 10.3% of the near-surface PM2.5 concentration. The contributions of emissions from power plants, traffic, residential sources were 2.0%, 3.0%, and 7.2%, respectively. The contributions of total local emissions and emissions from different sectors depended on multi-scale meteorological conditions, and static weather significantly enhanced the contribution of regional transport to the near-surface PM2.5 concentration. Eight cluster backward trajectories were identified for Tangshan. The PM2.5 concentration for the 8 cluster trajectories significantly differed. The near-surface PM2.5 in urban Tangshan (receptor point) was mainly from the local emissions, and another important potential source region was Tianjin. The results of the source apportionment suggested the importance of joint prevention and control of air pollution in some areas where cities or industrial regions are densely distributed.

Air pollution characteristics and their relation to meteorological conditions during 2014-2015 in major Chinese cities.

In January 2013, the real-time hourly average concentrations of six pollutants (CO, NO2, O3, PM10, PM2.5 and SO2) based on data from air quality monitoring stations in major Chinese cities were released to the public. That report provided a good opportunity to publicise nationwide temporal and spatial pollution characteristics. Although several studies systematically investigated the temporal and spatial trends of pollutant concentrations, the relation between air pollution and multi-scale meteorological conditions and their spatial variations on a nationwide scale remain unclear. This study analysed the air pollution characteristics and their relation to multi-scale meteorological conditions during 2014-2015 in 31 provincial capital cities in China. The annual average concentrations of six pollutants for 31 provincial capital cities were 1.2 mg m-3, 42.4 µg m-3, 49.0 µg m-3, 109.8 µg m-3, 63.7 µg m-3, and 32.6 µg m-3 in 2014. The annual average concentrations decreased 5.3%, 4.9%, 11.4%, 12.0% and 21.5% for CO, NO2, PM10, PM2.5 and SO2, respectively, but increased 7.4% for O3 in 2015. The highest rate of a major pollutant over China was PM2.5 followed by PM10, O3, NO2, SO2 and CO. Meteorological conditions were the primary factor determining day-to-day variations in pollutant concentrations, explaining more than 70% of the variance of daily average pollutant concentrations over China. Meteorological conditions in 2015 were more adverse for pollutant dispersion than in 2014, indicating that the improvement in air quality was caused by emission controls.

Sources and Processes Affecting Fine Particulate Matter Pollution over North China: An Adjoint Analysis of the Beijing APEC Period.

The stringent emission controls during the APEC 2014 (the Asia-Pacific Economic Cooperation Summit; November 5-11, 2014) offer a unique opportunity to quantify factors affecting fine particulate matter (PM2.5) pollution over North China. Here we apply a four-dimensional variational data assimilation system using the adjoint model of GEOS-Chem to address this issue. Hourly surface measurements of PM2.5 and SO2 for October 15-November 14, 2014 are assimilated into the model to optimize daily aerosol primary and precursor emissions over North China. Measured PM2.5 concentrations in Beijing average 50.3 µg m(-3) during APEC, 43% lower than the mean concentration (88.2 µg m(-3)) for the whole period including APEC. Model results attribute about half of the reduction to meteorology due to active cold surge occurrences during APEC. Assimilation of surface measurements largely reduces the model biases and estimates 6%-30% lower aerosol emissions in the Beijing-Tianjin-Hebei region during APEC than in late October. We further demonstrate that high PM2.5 events in Beijing during this period can be occasionally contributed by natural mineral dust, but more events show large sensitivities to inorganic aerosol sources, particularly emissions of ammonia (NH3) and nitrogen oxides (NOx) reflecting strong formation of aerosol nitrate in the fall season.

Investigation on emission factors of particulate matter and gaseous pollutants from crop residue burning.

Emission factors of particulate matter (PM), element carbon (EC), organic carbon (OC), SO2, NO(x), CO, CO2, and ten ions (Na+, NH4+, K+, Mg2+, Ca2+, F-, Cl-, NO2-, NO3-, SO4(2-)) were estimated from the domestic burning of four types of commonly produced crop residues in rural China: rice straw, wheat straw, corn stover, and cotton stalk, which were collected from the representative regions across China. A combustion tower was designed to simulate the cooking conditions under which the peasants burned their crop residues in rural China, to measure the emission factors. Results showed that wheat straw had the highest emission factor for the total PM (8.75 g/kg) among the four crop residues, whereas, corn stover and wheat straw have the highest emission factor for EC (0.95 g/kg) and OC (3.46 g/kg), respectively. Corn stover also presents as having the highest emission factors of NO, NO(x), and CO2, whereas, wheat straw, rice straw, and cotton stalk had the highest emission factors of NO2, SO2, and CO, respectively. The water-soluble ions, K+ and Cl-, had the highest emission factors from all the crops. Wheat straw had a relatively higher emission factor of cation species and F-, Cl-, NO2- than other residues.