Air Quality In China Research Articles

High-speed rail, technological improvement, and PM2.5: Evidence from China

This study estimated the effects and mechanisms of high-speed rail (HSR) connectivity on the city air quality in China. The Difference-in-Difference model are used to explore the effects, we found that on average, the city's PM2.5 concentration declined by 2.8 % after the opening of HSR, however, this impact varies depending on whether the city is part of the Ecological Economic Zone and the marketization degree. We further explored that HSR can affect local PM2.5 concentrations by changing firm's technical level. In instrumental variables regression and robustness testing, the conclusion remains unchanged. The results highlight the significance of considering firm responses to HSR in understanding the spatial patterns of air pollution in China.

Impacts of coal use phase-out in China on the atmospheric environment: (1) emissions, surface concentrations and exceedance of air quality standards

Coal combustion is one of the main sources of greenhouse gases and various air pollutants. Gradually reducing the use of coal is an important strategy for controlling air pollution and achieving the goal of “carbon neutrality” in China. This study originally extracts the proportion of coal sources from emission inventories of key pollutants from different sectors and quantifies the emissions from coal sources in China during 2015. Additionally, it evaluates the peak potential impacts on the concentrations of key pollutants and overall air quality in China resulting from ceasing coal usage with the Community Earth System Model version 2 (CESM2). The results show that the emissions of sulfur dioxide (SO2), nitric oxide (NO) and black carbon (BC) from coal sources account for more than half of the total anthropogenic emissions in China. After the phase-out of coal use, the concentrations of SO2, nitrogen oxides (NOx), carbon monoxide (CO) and 2.5-μm Particulate Matter (PM2.5) could markedly decrease by approximately 30∼50%, accounting for 50–80% of anthropogenic sources and even more than 80% in individual provinces. The exceedance of SO2, nitrogen dioxide (NO2), CO and PM2.5 under the air quality standard of China is also greatly reduced. Only the concentration and exceedance of ozone (O3) increase significantly in certain parts of China and in some seasons. Sensitivity analysis also shows that most air pollutants decrease linearly or nearly linearly with the increase of coal-ban proportion. Therefore, this study suggests that the strength of coal removal needs to be gradually enhanced. And the emissions from other kinds of fossil fuels should also be controlled during the process of ending coal use to reduce the pollution levels of CO, Volatile Organic Compounds (VOCs), O3 and organic aerosols. This research thoroughly assesses the ultimate limit of contributions of coal usage to the air pollution of China, which could serve as a valuable reference for future policy formulation.

Significant Reductions in Secondary Aerosols after the Three-Year Action Plan in Beijing Summer.

Air quality in China has continuously improved during the Three-Year Action Plan (2018-2020); however, the changes in aerosol composition, properties, and sources in Beijing summer remain poorly understood. Here, we conducted real-time measurements of aerosol composition in five summers from 2018 to 2022 along with WRF-Community Multiscale Air Quality simulations to characterize the changes in aerosol chemistry and the roles of meteorology and emission reductions. Largely different from winter, secondary inorganic aerosol and photochemical-related secondary organic aerosol (SOA) showed significant decreases by 55-67% in summer, and the most decreases occurred in 2021. Comparatively, the decreases in the primary aerosol species and gaseous precursors were comparably small. While decreased atmospheric oxidation capacity as indicated by ozone changes played an important role in changing SOA composition, the large decrease in aerosol liquid water and small increase in particle acidity were critical for nitrate changes by decreasing gas-particle partitioning substantially (∼28%). Analysis of meteorological influences demonstrated clear and similar transitions in aerosol composition and formation mechanisms at a relative humidity of 50-60% in five summers. Model simulations revealed that emission controls played the decisive role in reducing sulfate, primary OA, and anthropogenic SOA during the Three-Year Action Plan, while meteorology affected more nitrate and biogenic SOA.

Impact of Economic and Environmental Factors on O3 Concentrations in the Yangtze River Delta Region of China

The concentration of atmospheric ozone (O3) pollution is showing a rapid growing tendency, and O3 pollution has become one of the bottleneck issues that restrict the continuous improvement of air quality in China. In this study, we first identified the primary factors based on the source apportionment of O3, then used factor analysis to divide these selected factors into economic and environmental categories. The geographical detector model was used to analyze the impact of factors and their interactions on O3 concentration in 41 cities in the Yangtze River Delta (YRD) region in 2020. The results showed that forest coverage ranked first among all the detected factors, suggesting a strong relationship between the regional O3 concentration and forest coverage. The driving factors of economic activity were ranked as follows: actual utilization of foreign capital (0.400) > gross domestic product (GDP) per capita (0.387) > proportion of tertiary industry (0.360) > urbanization rate (0.327) > per capita consumption expenditure (0.194) > research and development (R&D) of full-time equivalents of industrial enterprises above designated size (0.182) > number of industrial enterprises (0.126). The interaction between any two factors enhanced their influence on O3 concentration more than any single factor, indicating that the variability of regional O3 concentration was an outcome of a combination of multiple factors. This study could provide recommendations for the prevention and control of O3 pollution and the development of ecological integration in the YRD region.

Measuring and modeling investigation of the net photochemical ozone production rate via an improved dual-channel reaction chamber technique

Abstract. Current process-based research mainly uses box models to evaluate photochemical ozone production and destruction rates, and it is unclear to what extent the photochemical reaction mechanisms are elucidated. Here, we modified and improved a net photochemical ozone production rate (NPOPR, P(O3)net) detection system based on the current dual-channel reaction chamber technique, which makes the instrument applicable to different ambient environments, and its various operating indicators were characterized, i.e., “airtightness”, light transmittance, wall losses of the reaction and reference chambers, conversion rate of O3 to NO2, air residence time, and performance of the reaction and reference chambers. The limits of detection of the NPOPR detection system were determined to be 0.07, 1.4, and 2.3 ppbv h−1 at sampling flow rates of 1.3, 3, and 5 L min−1, respectively. We further applied the NPOPR detection system to field observations at an urban site in the Pearl River Delta (China). During the observation period, the maximum value of P(O3)net was 34.1 ppbv h−1, which was ∼ 0 ppbv h−1 at night within the system detection error and peaked at approximately noon local time. The daytime (from 06:00–18:00 LT) average value of P(O3)net was 12.8 (± 5.5) ppbv h−1. We investigated the detailed photochemical O3 formation mechanism in the reaction and reference chambers of the NPOPR detection system using a zero-dimensional box model. We found that the photochemical reactions in the reaction chamber were very close to those in ambient air, but there was not zero chemistry in the reference chamber because the reaction related to the production and destruction of RO2 (= HO2 + RO2) continued in the reference chamber, which led to a small amount of P(O3)net. Therefore, the P(O3)net measured here can be regarded as the lower limit of the real P(O3)net in the atmosphere; however, the measured P(O3)net was still ∼ 7.5 to 9.3 ppbv h−1 higher than the modeled P(O3)net value depending on different modeling methods, which may be due to the inaccurate estimation of HO2 / RO2 radicals in the modeling study. Short-lived intermediate measurements coupled with direct P(O3)net measurements are needed in the future to better understand O3 photochemistry. Our results show that the NPOPR detection system can achieve high temporal resolution and continuous field observations, which helps us to better understand photochemical O3 formation and provides a key scientific basis for continuous improvement of air quality in China.

Ozone Pollution and Acute Exacerbation of Asthma in Residents of China: An Ecological Study.

The evidence for a causal relationship between high-level ozone (O3) exposure and acute exacerbation of asthma among adults is limited, and the conclusions are less definitive. Here we collected the daily data on asthma cases, O3 exposure, and meteorological factors from 2010 to 2016 in Shijiazhuang, China. We investigated the risk of asthma exacerbation associated with high-level ozone exposure using a polynomial distributed lag model (PDLM). Using a generalized additive model (GAM), we estimated the interactive effects between O3 and other pollutants as well as meteorological factors on asthma exacerbation. A total of 7270 patients with asthma were enrolled from 22 governmental hospitals in 13 counties. Each 10 μg/m3 increase in O3 concentration on the exacerbation of asthma was associated with a 1.92% (95% CI = 0.80-3.03%) higher risk of asthma exacerbation on day lag 7. The cumulative risk of O3 on asthma exacerbation increased by 18.9% (95% CI = 12.8-25.4%) on the 14th day. High consecutive levels of O3 increase the risk of asthma exacerbation, and the interactive effect of O3 and sulfur dioxide (SO2) appears before the exacerbation onset. These findings suggested that O3 should be an important risk factor for asthma exacerbation, and health benefits in reducing asthma exacerbation risk would be gained with continued efforts to improve the air quality in China.

Diesel vehicle (engine) control is the key to continuous improvement of air quality in China

Diesel vehicle (engine) control is the key to continuous improvement of air quality in China

Atmospheric Oxidation Capacity and Its Impact on the Secondary Inorganic Components of PM2.5 in Recent Years in Beijing: Enlightenment for PM2.5 Pollution Control in the Future

In recent years, the concentrations of PM2.5 in urban ambient air in China have been declining; however, the strong atmospheric oxidation capacity (AOC) represents challenges to the further reduction of PM2.5 concentration and the continuous improvement of ambient air quality in China in the future, since the overall AOC is still at a high level. For this paper, based on ground observation data recorded in Beijing from 2016 to 2019, the variation in AOC was characterized according to the concentration of odd oxygen (OX = O3 + NO2). The concentrations of the primary and secondary components of PM2.5 were analyzed using empirical formulas, the correlation between AOC and the concentrations of secondary PM2.5 and the secondary inorganic components (SO42−, NO3−, NH4+, and SNA) in Beijing were explored, the impact of atmospheric photochemical reaction activity on the generation of atmospheric secondary particles was evaluated, and the impact of atmospheric oxidation variations on PM2.5 concentrations and SNA in Beijing was investigated. The results revealed that OX concentrations reached their peak in 2016 and reached their lowest point in 2019. The OX concentrations followed a descending seasonal trend of summer, spring, autumn, and winter, along with a spatial descending trend from urban observation stations to suburban stations and background stations. The degree of photochemical activity and the magnitude of the AOC have a large influence on the production of atmospheric secondary particles. When the photochemical reaction was more active and the AOC was stronger, the mass concentrations of the secondary generated PM2.5 fraction were higher and accounted for a higher proportion of the total PM2.5 mass concentrations. In the PM2.5 fraction, SNA accounted for 50.7% to 94.4% of the total mass concentrations of water-soluble inorganic ions in the field observations. Higher concentrations of the atmospheric oxidant OX in ambient air corresponded to a higher sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR), suggesting that the increase in AOC could promote the increase of PM2.5 concentration. Based on a relationship analysis of SOR, NOR, and OX, it was inferred that the relationship between OX and SOR and the relationship between OX and NOR were both nonlinear. Therefore, when establishing PM2.5 control strategies in Beijing in the future, the impact of the AOC on PM2.5 generation should be fully considered, and favorable measures should be taken to properly regulate the AOC, which would be more effective when carrying out further control measures regarding PM2.5 pollution.

Superimposed effects of typical local circulations driven by mountainous topography and aerosol–radiation interaction on heavy haze in the Beijing–Tianjin–Hebei central and southern plains in winter

Abstract. Although China's air quality has substantially improved in recent years due to the vigorous emissions reduction, the Beijing–Tianjin–Hebei (BTH) region, especially its central and southern plains at the eastern foot of the Taihang Mountains, has been the most polluted area in China, with persistent and severe haze in winter. Combining meteorology–chemistry coupled model simulations and multiple observations, this study explored the causes of several heavy haze events in this area in January 2017, focusing on local circulations related to mountain terrain. The study results showed that on the weather scale, the configuration of the upper, middle, and lower atmosphere provided favorable weather and water vapor transport conditions for the development of haze pollution. Under the weak weather-scale systems, local circulation played a dominant role in the regional distribution and extreme values of PM2.5. Influenced by the Taihang and Yanshan mountains, vertical circulations and wind convergence zone were formed between the plain and mountain slopes. The vertical distribution of pollutants strongly depended on the intensity and location of the circulation. The circulation with high intensity and low altitude was more unfavorable for the vertical and horizontal diffusion of near-surface pollutants. More importantly, we found that the aerosol–radiation interaction (ARI) significantly amplified the impacts of local vertical circulations on heavy haze by two mechanisms. First, the ARI strengthened the vertical circulations at the lower levels, with the zonal wind speeds increasing by 0.3–0.8 m s−1. Meanwhile, the ARI could cause a substantial downward shift in the vertical circulations (∼ 100 m). Second, the ARI weakened the horizontal diffusion of pollutants by reducing the westerly winds and enhancing wind convergence and southerly winds. Under these two mechanisms, pollutants could only recirculate in a limited space. This superposition of the typical local circulation and the ARI eventually contributed to the accumulation of pollutants and the consequent deterioration of haze pollution in the region.

Empirical analysis of air quality in Shanghai based on multiple linear regression model

In recent years, with the rapid development of social and economic development, scientific and technological progress, human production and living standards have achieved tremendous improvement, at the same time, a large number of exhaust gases and soot emissions have become important sources of pollution, industrial energy consumption and urban construction, etc. make China's air environment pollution problem increasingly serious. The air quality in China gradually presents regional pollution, especially in the Yangtze River Delta, Pearl River Delta, and Beijing-Tianjin-Hebei regions. This paper takes Shanghai as the research object and empirically analyzes the main influencing factors of its air quality, which can provide reference not only for managing the air quality of this city, but also for the air quality management of similar cities. This paper empirically investigates the influencing factors of air quality in Shanghai based on the Shanghai air quality monitoring data, including AQI (Air Quality Index) and PM2.5, PM10, NO2, CO, SO2 and O3 pollutant concentrations, released by the Shanghai Bureau of Ecology and Environment from January 2015 to October 2021. This paper uses the knowledge of econometrics to establish a multiple linear regression model with the help of RStudio, which is continuously estimated, tested and improved on the basis of the primary model to analyze the degree of influence of pollutants on AQI, and also to analyze the main pollutants affecting air quality by testing. The statistical results show that the primary air pollutants in Shanghai are O3 and NO2. Based on the analysis results, this paper puts forward corresponding suggestions about improving the air quality and protecting the ecological environment in Shanghai.

Energy and air? The impact of energy efficiency improvement on air quality in China.

The global economic growth is hindered by resources shortage, energy demand, air pollution and climate. Energy efficiency can reduce some pollutants while potentially increase others. This study refers to sulfur dioxide (SO2), nitrogen oxides (NOx), and dust and smoke (DS) as primary pollutants to distinguish it from secondary ones. The influence of energy efficiency, socioeconomic, and natural climatic factors on air quality is analyzed under the theory of STIRPAT. It is highly coupled between energy efficiency and the spatial distribution of air quality. Increased energy efficiency can improve air quality by reducing SO2 and NOx, but the impact on DS is insignificant. Air pollutants decrease by about 0.531% for every 1% increase in temperature and 0.105% for every 1% increase in precipitation. Consumption will reduce air pollution, and there is an inverted U-shaped relationship between population density, economic scale, urbanization, technology innovation, and air pollution. It is worth mentioning that this work adds temperature and precipitation to the STIRPAT as natural climatic factors, analyzing the impact of energy efficiency on air pollution under the two-factor restrictions of socioeconomic and natural climatic factors. Finally, management suggestions are made to improve air quality.

Drivers of alleviated PM2.5 and O3 concentrations in China from 2013 to 2020

Since 2013, the Chinese Government implemented “Clean Air Action” Phase I (2013–2017) and Phase II (2018–2020) consecutively to improve air quality. However, it remains unclear how these policies have impacted air quality since most studies merely focus on Phase I. In this study, we applied the Community Multiscale Air Quality (CMAQ) model to investigate variations of air quality in China during “Clean Air Action” Phases I and Phase II (2013–2020). Results show that PM2.5 is significantly reduced (-40%) across China except in summer. O3 concentration also decreases, but a 3% increase is found in the Beijing-Tianjin-Hebei (BTH) region. Emission changes play a dominant role in the reduction of PM2.5 (over 95%). The contributions from meteorology and emissions to O3 reduction are 46% and 54%, respectively. Our results suggest that a more effective emission abatement strategy should be formulated, aiming to control O3 and PM2.5 synergistically.

Evolution and chemical characteristics of organic aerosols during wintertime PM2.5 episodes in Shanghai, China: insights gained from online measurements of organic molecular markers

Abstract. Organic aerosol (OA) is a significant part of urban fine particulate matter (PM2.5), and a lack of detailed knowledge of their sources has increasingly hindered the improvement of air quality in China in recent years, as significant reductions have been achieved in inorganic ion constituents. In this study, a wide range of organic molecular markers in PM2.5 were monitored with a bi-hourly time resolution using a thermal desorption aerosol gas chromatograph system (TAG) in urban Shanghai in winter 2019. The molecular marker data have provided a unique source tracking ability in characterizing the evolution of organic aerosols during nine wintertime episodic events. Episodes primarily influenced by local air masses were characterized with higher proportions in PM2.5 and mass increments of both primary and secondary OA. Rapid increases in both the absolute mass concentration and relative proportion were observed for primary and secondary OA markers, indicative of vehicle emissions (e.g., alkanes, hopanes, and 2,3-dihydroxy-4-oxopentanoic acid) and cooking activities (e.g., saturated and unsaturated fatty acids and C9 acids). In comparison, episodes under significant influences of transported air mass were typically associated with a predominant PM2.5 contribution from secondary inorganic aerosols and enhanced OA contribution from biomass burning activities. The latter was evident from the tracer data (e.g., levoglucosan, aromatic polycarboxylic acids, and nitroaromatic compounds). Secondary OA markers associated with later-generation products of the hydrocarbon oxidation process, such as C3−5 dicarboxylic acids, were the most deficient during local episodes, while notably enhanced during the episodes under the influence of transported air masses, reflecting the different extent and pathways of atmospheric aging processing. The ability to distinguish the variations in the OA evolution during different types of episodes demonstrates the value of online organic molecular measurements for episodic analysis. The results indicate that control of local urban sources such as vehicular and cooking emissions would lessen severity of local episodes, while regional control of precursors for secondary inorganic aerosols and biomass burning activities would reduce PM2.5 episodes under synoptic conditions conducive for regional transport.

A Comparison of the Evaporative Emissions Performance of Light-Duty Vehicles under US Tier 3 and China 6 Test Conditions

To further improve air quality in China, especially ozone and fine particulate matter (PM2.5), additional reductions of volatile organic compounds (VOCs) are needed. Evaporative emissions from internal combustion engines (ICE) and hybrid vehicles are known to be an important source of VOCs in urban cities, which can be efficiently reduced through the introduction of more stringent regulatory standards. The most stringent global standards for evaporative emissions are the U.S. Tier 3 light-duty vehicle standards. This study compares the evaporative emissions of light-duty ICE vehicles designed to China 6 and U.S. Tier 3 regulations for both China and U.S. test conditions. Data are analyzed from manufacturer testing of full vehicle evaporative emissions conducted in the laboratory following U.S. Tier 3 and China 6 certification test methods utilizing Sealed Housing for Evaporative Determination (SHED) chambers equipped with Flame Ionization Detection (FID) analyzers. Vehicles designed to U.S. Tier 3 standards are observed to have 64% lower diurnal and hot soak evaporative emissions and 98% lower canister bleed emissions relative to vehicles designed to China 6 standards. U.S. Tier 3, U.S. Tier 2, and China 6 light-duty evaporative emission certification values submitted by manufacturers are also compared. The average of all current U.S. Tier 3 certifications is, on average, 52.4% lower than the average of all China 6 certifications. The results from the testing and data analysis of five vehicles, with comparison to the certification data, suggest that the introduction of standards equivalent in stringency to U.S. Tier 3 in China can significantly reduce evaporative emissions relative to China 6.

AirFormer: Predicting Nationwide Air Quality in China with Transformers

Air pollution is a crucial issue affecting human health and livelihoods, as well as one of the barriers to economic growth. Forecasting air quality has become an increasingly important endeavor with significant social impacts, especially in emerging countries. In this paper, we present a novel Transformer termed AirFormer to predict nationwide air quality in China, with an unprecedented fine spatial granularity covering thousands of locations. AirFormer decouples the learning process into two stages: 1) a bottom-up deterministic stage that contains two new types of self-attention mechanisms to efficiently learn spatio-temporal representations; 2) a top-down stochastic stage with latent variables to capture the intrinsic uncertainty of air quality data. We evaluate AirFormer with 4-year data from 1,085 stations in Chinese Mainland. Compared to prior models, AirFormer reduces prediction errors by 5%∼8% on 72-hour future predictions. Our source code is available at https://github.com/yoshall/airformer.

Long-term PM2.5 pollution over China: Identification of PM2.5 pollution hotspots and source contributions

Fine particulate matter, with an aerodynamic diameter ≤ 2.5 μm (PM2.5), is a severe problem in China. The lack of ground-based measurements and its sparse distribution obstruct long-term air pollution impact studies over China. Therefore, the present study used newly updated Global Estimates (V5. GL.02) of monthly PM2.5 data from 2001 to 2020 based on Geographically Weighted Regression (GWR) by Washington University. The GWR PM2.5 data were validated against ground-based measurements from 2014 to 2020, and the validation results demonstrated a good agreement between GWR and ground-based PM2.5 with a higher correlation (r = 0.95), lower error (8.14), and lower bias (−3.10 %). The long-term (2001−2020) PM2.5 data were used to identify pollution hotspots and sources across China using the potential source contribution function (PSCF). The results showed highly significant PM2.5 pollution hotspots in central (Henan, Hubei), North China Plain (NCP), northwest (Taklimakan), and Sichuan Basin (Chongqing, Sichuan) in China, with the most severe pollution occurring in winter compared to other seasons. During the winter, PM2.5 was in the range from 6.08 to 93.05 μg/m3 in 33 provinces, which is 1.22 to 18.61 times higher than the World Health Organization (WHO) Air Quality Guidelines (AQG-2021; annual mean: 5 μg/m3). In 26 provinces, the reported PM2.5 was 1.07 to 2.66 times higher than the Chinese Ambient Air Quality Standard (AAQS; annual mean: 35 μg/m3). Furthermore, provincial-level trend analysis shows that in most Chinese provinces, PM2.5 increased significantly (3–43 %) from 2001 to 2012, whereas it decreased by 12–94 % from 2013 to 2020 due to the implementation of air pollution control policies. Finally, the PSCF analysis demonstrates that China's air quality is mainly affected by local PM2.5 sources rather than by pollutants imported from outside China.

Regional Representativeness Analysis of Ground-Monitoring PM2.5 Concentration Based on Satellite Remote Sensing Imagery and Machine Learning Techniques

The issue of urban air quality in China has become increasingly significant due to industrialization and rapid urbanization. Although PM2.5 is the major air pollutant in most cities of northern China and has a direct negative impact on human health, there is a problem of under-representativeness at Chinese monitoring stations. In some cities, due to the relatively fewer national control stations and the fact that the stations are located closer to pollution sources, under the current assessment system, the monitoring data are not sufficient for the fairness of air quality assessment in different cities. In this article, the multispectral data of Landsat 8 data, air quality data, and meteorological data from ground monitoring stations have been integrated together and imported to different PM2.5-estimation models established based on the multi-layer back propagation neural network (MLBPN), support vector regression (SVR), and random forest (RF), respectively. According to the evaluation indices of R2, RMSE, and ME, the estimation model based on the MLBPN revealed the best PM2.5 estimation results and was therefore employed for the regional representativeness analysis in the study area of Xi’an, Shaanxi, China. The annual average PM2.5 concentration in the study area is depicted after error correction using Kriging interpolation, which can be further used to evaluate and analyze the representativeness of monitoring stations in Xi’an. By calculating the difference between the actual station annual average and the annual average of estimated PM2.5 concentration in the whole region, it can be found that the regional annual average value of PM2.5 in Xi’an is overestimated. To sum up, this article proposes a feasible method for the spatial positioning of the air quality monitoring stations to be established.

Fast Secondary Aerosol Formation in Residual Layer and Its Impact on Air Pollution Over Eastern China

AbstractThough China's air quality has been improved in the past decade, haze still engulfs megacities in winter with fast increasing secondary aerosol like nitrate. Given that aerosol and its precursors exhibit great vertical heterogeneity, we conducted airship measurements at Shanghai in December 2017 to understand the critical drivers for the rapidly increased secondary pollution. By integrating in‐situ observations and model simulations, we found that cold front favors the long‐range transport of pollutants, during which chemical formation of nitrate in residual layer was faster than near the surface due to concentrated precursors and sufficient oxidation. The nitrate aloft would be entrained down once the daytime convective boundary layer develops, thereby deteriorating near‐surface air pollution. It is shown that the local surface‐level chemical production played a minor role, whereas the synoptic weather and boundary layer evolution largely contributed to enhanced secondary aerosol pollution (>60%). This study demonstrates that weather systems, boundary layer evolution, and chemical processes could jointly shape secondary aerosol production, highlighting the importance of a vertical understanding of haze pollution.

Spatiotemporal evolution characteristics and prediction analysis of urban air quality in China

To describe the spatiotemporal variations characteristics and future trends of urban air quality in China, this study evaluates the spatiotemporal evolution features and linkages between the air quality index (AQI) and six primary pollution indicators, using air quality monitoring data from 2014 to 2022. Seasonal autoregressive integrated moving average (SARIMA) and random forest (RF) models are created to forecast air quality. (1) The study’s findings indicate that pollution levels and air quality index values in Chinese cities decline annually, following a “U”-shaped pattern with a monthly variation. The pollutant levels are high in winter and low in spring, and low in summer and rising in the fall (O3 shows the opposite). (2) The spatial distribution of air quality in Chinese cities is low in the southeast and high in the northwest, and low in the coastal areas and higher in the inland areas. The correlation coefficients between AQI and the pollutant concentrations are as follows: fine particulate matter (PM2.5), inhalable particulate matter (PM10), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) values are correlated at 0.89, 0.84, 0.54, 0.54, 0.32, and 0.056, respectively. (3) In terms of short-term AQI predictions, the RF model performs better than the SARIMA model. The long-term forecast indicates that the average AQI value in Chinese cities is expected to decrease by 0.32 points in 2032 compared to the 2022 level of 52.95. This study has some guiding significance for the analysis and prediction of urban air quality.

The integrating sphere system plus in-situ absorption monitoring: A new scheme to study absorption enhancement of black carbon in ambient aerosols

Black carbon (BC) is the strongest light-absorbing aerosol in the atmosphere. The coating process causes lensing effects to enhance the BC absorption. The reported BC absorption enhancement values (Eabs) significantly differ partly due to the measurement methods used. The biggest difficulty in measuring the Eabs values is how to denude the coated particles so that the true value of absorption without coatings can be distinguished from lensing effects. In this study, we proposed a new approach based on an integrating sphere (IS) system plus in-situ absorption monitoring instrument to study Eabs in ambient aerosols. This approach is capable of (i) “de-lensing through solvent dissolution and solvent de-refraction”, by which the absorption coefficient of denuded BC is acquired, and (ii) monitoring in-situ absorption with photoacoustic spectroscopy. With the help of the EC concentration measured by a thermal/optical carbon analyser, the Eabs values were calculated as the quotient of in-situ mass absorption efficiency divided by denude mass absorption efficiency. We applied this new approach to measure the Eabs values of four seasons in Beijing and found an annual mean of 1.90 ± 0.41 in 2019. More importantly, a previous assumption that BC absorption efficiency may be progressively enhanced by increased air pollution was validated and quantified using a logarithmic relationship of Eabs = 0.6 ln (PM2.5 ̶ 3.59) ̶ 0.43 (R2 = 0.99). This signals a continued drop of Eabs for future ambient aerosols with the sustained improvement in local air quality in China, meriting serious attention to its influences in climate, air quality, and atmospheric chemistry.