Quantifying the impacts of inter-city transport on air quality in the Yangtze River Delta urban agglomeration, China: Implications for regional cooperative controls of PM2.5 and O3

The analysis of ozone pollution in urban agglomerations of the Sichuan basin based on the scale decomposition-synthesis method

This study investigates the recent trends in ozone (O3) pollution in the Sichuan Basin, aiming to identify the contributions of meteorological and anthropogenic factors to ozone concentration. Using meteorological data and pollutant concentration data from 17 cities in Sichuan between 2016 and 2022, we analyzed the spatiotemporal distribution characteristics of ozone concentration in the basin. The Kolmogorov-Zurbenko (KZ) filter was applied to decompose the meteorological characteristics, daily maximum 8-h average ozone concentration (MDA8-O3), nitrogen dioxide (NO2), and PM2.5 concentrations into different scales. The Least Absolute Shrinkage and Selection Operator (LASSO) method was used to select feature variables at each scale, and Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) algorithms were employed for scale-specific modeling. By synthesizing the scaled series, MDA8-O3 models for each city were established. SHAP value analysis revealed the contribution patterns and influence levels of different feature variables across various time scale components for each city. The results showed that: ①In the 17 cities, meteorological factors contributed more to MDA8-O3 fluctuations than emission factors, with the meteorological-to-emission contribution ratio ranging from 19:1 to 16:9. ②The multi-scale decomposition-synthesis prediction method outperformed direct prediction using the original series, and the prediction accuracy of the XGBoost algorithm was superior to that of the RF algorithm. ③For the original series, short-term components, seasonal components, and long-term components, the factors contributing most positively to MDA8-O3 were convective available potential energy, mid-level cloud cover, sunshine duration, and ultraviolet intensity, respectively. Additionally, the contributions of PM2.5 and NO2 to MDA8-O3 varied significantly across different scales.

Quantitative impacts of meteorology and emissions on the long-term trend of O3 in the Yangtze River Delta (YRD), China from 2015 to 2022

Extensive spatiotemporal analyses of long-trend surface ozone in the Yangtze River Delta (YRD) region and its meteorology-related and emission-related have not been systematically analyzed. In this study, by using 8-year-long (2015-2022) surface ozone observation data, we attempted to reveal the variation of multiple timescale components using the Kolmogorov-Zurbenko filter, and the effects of meteorology and emissions were quantitatively isolated using multiple linear regression with meteorological variables. The results showed that the short-term, seasonal, and long-term components accounted for daily maximum 8-hr average O3 (O3-8 hr) concentration, 46.4%, 45.9%, and 1.0%, respectively. The meteorological impacts account for an average of 71.8% of O3-8 hr, and the YRD's eastern and northern sections are meteorology-sensitive areas. Based on statistical analysis technology with empirical orthogonal function, the contribution of meteorology, local emission, and transport in the long-term component of O3-8 hr were 0.21%, 0.12%, and 0.6%, respectively. The spatiotemporal analysis indicated that a distinct decreasing spatial pattern could be observed from coastal cities towards the northwest, influenced by the monsoon and synoptic conditions. The central urban agglomeration north and south of the YRD was particularly susceptible to local pollution. Among the cities studied, Shanghai, Anqing, and Xuancheng, located at similar latitudes, were significantly impacted by atmospheric transmission-the contribution of Shanghai, the maximum accounting for 3.6%.

Urbanization exacerbates disparities in exposure to air pollution in China

Prolonged exposure to fine particulate matter (PM2.5) is associated with harmful impacts on human health and population growth in urban areas has exacerbated this exposure. In this study, we compare the exposure between cities at a national level and between different regions within cities considering the population in situ. We estimate the impacts of pollution and population on exposure by spatial and time series analysis from 2000 to 2018 based on 1-km grid data. Our results show that the exposure significantly increases with an increase in city size but is not necessarily related to higher PM2.5 concentrations. Notably, nonurban areas within most prefecture cities have a higher exposure than urban areas. The exposure follows an inverted U-shaped pattern over time across all cities, which are at varying stages within this trend. Nationally, it grows by 0.9 billion person-levels/year during the increasing stage and reduces by 1.0 billion person-levels/year during the decreasing stage. For urban areas, population growth is the dominant factor that determines the exposure during the increasing phase, while changes in air pollution dominate during the decreasing phase. In nonurban areas, however, the change in air pollution plays a more decisive role during both stages. Understanding the spatial distribution and the driving process of exposure provided directions for the country and each prefecture city to balance the benefits of air pollution control, mitigation costs, addressing disparities, and increasing national welfare.

A forecasting tool for optimized emission control strategies to achieve short-term air quality attainment

Optimizing an emergency air pollution control strategy for haze events presents a significant challenge due to the extensive computational demands required to quantify the complex nonlinearity associated with controls on diverse air pollutants and regional sources. In this study, we developed a forecasting tool for emergency air pollution control strategies based on a predictive response surface model that quantifies PM2.5 responses to emission changes from different pollutants and regions. This tool is equipped to assess the effectiveness of emergency control measures corresponding to various air pollution alerts and to formulate an optimized control strategy aimed at specific PM2.5 targets. A case study in the Yangtze River Delta demonstrates that our tool can conduct assessments and generate optimized control strategies for the forthcoming seven to ten days within a 6-h window. Results indicate that the haze event on November 3rd, 2017, was predominantly attributable to regional transport, while the episode on November 7th-8th resulted more from local emissions. The optimized control strategy for November 3rd involves coordinated control from 17 cities along the northwest regional transport pathway, whereas 9 cities around Shanghai should implement emergency emission reductions for PM2.5 attainment in Shanghai on November 7th-8th. Additionally, the intensity of air pollution alerts is higher in the optimized strategy for November 3rd. The forecasting tool developed in this study can quickly and accurately assess the effectiveness of pollution emergency reduction plans and formulate optimal control strategies in advance, which is of great significance for enhancing the emergency response capabilities of authorities to address short-term air pollution events effectively.

Seasonal quantification of the inter-city transport of PM2.5 in the Yangtze River Delta region of China based on a source-oriented chemical transport model and the Michaelis-Menten equation

Regional transport plays a crucial role in the pollution of fine particulate matter (PM2.5) over the Yangtze River Delta region (YRD). A practical joint regional emission control strategy requires quantitative assessment of the contribution of regional transport. In this study, the contribution of inter-city transport to PM2.5 among the 41 cities in the YRD region were quantitatively estimated using a source-oriented chemical transport model, and then the relationship between the cumulative contribution of regional transport and the distance was examined using the Michaelis-Menten equation. The results show that the Michaelis-Menten equation is suitable to represent the relationship between the cumulative contribution and transport distance. The coefficient of determination (r2) of the fittings is greater than 0.9 in 71 % of the cases in the six subregions and four seasons in YRD. Two key parameters in the Michaelis-Menten eq. K1, indicating the maximum contribution of regional transport, and K2, indicating the distance to which the regional transport contribution reach half the maximum contribution, show substantial regional and seasonal variations. The average K1 is 73.6 %, with lower values observed in the northern part of the YRD and higher values in central Jiangsu. K2 is larger in northern Jiangsu, as well as central and southern Zhejiang. The local contribution in autumn and winter is lower than that in spring and summer in the northern part of the YRD. Particularly in northern Jiangsu, the local contribution reaches 90.4 % in summer but drops to 53.0 % in autumn and winter, illustrating significant impacts of regional transport to PM2.5 in autumn and winter in this area. K2 is larger on polluted days, compared to clean days, indicating greater contributions from regional transport to PM2.5 in YRD. The results can serve as a scientific foundation for implementing regional joint prevention and control measures in the YRD region.

Exploring efficient strategies for air quality improvement in China based on its regional characteristics and interannual evolution of PM2.5 pollution

Fine particulate matter (PM2.5) harms human health and hinders normal human life. Considering the serious complexity and obvious regional characteristics of PM2.5 pollution, it is urgent to fill in the comprehensive overview of regional characteristics and interannual evolution of PM2.5. This review studied the PM2.5 pollution in six typical areas between 2014 and 2022 based on the data published by the Chinese government and nearly 120 relevant literature. We analyzed and compared the characteristics of interannual and quarterly changes of PM2.5 concentration. The Beijing-Tianjin-Hebei region (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) made remarkable progress in improving PM2.5 pollution, while Fenwei Plain (FWP), Sichuan Basin (SCB) and Northeast Plain (NEP) were slightly inferior mainly due to the relatively lower level of economic development. It was found that the annual average PM2.5 concentration change versus year curves in the three areas with better pollution control conditions can be merged into a smooth curve. Importantly, this can be fitted for the accurate evaluation of each area and provide reliable prediction of its future evolution. In addition, we analyzed the factors affecting the PM2.5 in each area and summarize the causes of air pollution in China. They included primary emission, secondary generation, regional transmission, as well as unfavorable air dispersion conditions. We also suggested that the PM2.5 pollution control should target specific industries and periods, and further research need to be carried out on the process of secondary production. The results provided useful assistance such as effect prediction and strategy guidance for PM2.5 pollution control in Chinese backward areas.

Elucidating transport dynamics and regional division of PM2.5 and O3 in China using an advanced network model

Air pollution exhibits significant spatial spillover effects, complicating and challenging regional governance models. This study innovatively applied and optimized a statistics-based complex network method in atmospheric environmental field. The methodology was enhanced through improvements in edge weighting and threshold calculations, leading to the development of an advanced pollutant transport network model. This model integrates pollution, meteorological, and geographical data, thereby comprehensively revealing the dynamic characteristics of PM2.5 and O3 transport among various cities in China. Research findings indicated that, throughout the year, the O3 transport network surpassed the PM2.5 network in edge count, average degree, and average weighted degree, showcasing a higher network density, broader city connections, and greater transmission strength. Particularly during the warm period, these characteristics of the O3 network were more pronounced, showcasing significant transport potential. Furthermore, the model successfully identified key influential cities in different periods; it also provided detailed descriptions of the interprovincial spillover flux and pathways of PM2.5 and O3 across various time scales. It pinpointed major pollution spillover and receiving provinces, with primary spillover pathways concentrated in crucial areas such as the Beijing-Tianjin-Hebei (BTH) region and its surrounding areas, the Yangtze River Delta, and the Fen-Wei Plain. Building on this, the model divided the O3, PM2.5, and synergistic pollution transmission regions in China into 6, 7, and 8 zones, respectively, based on network weights and the Girvan Newman (GN) algorithm. Such division offers novel perspectives and strategies for regional joint prevention and control. The validity of the model was further corroborated by source analysis results from the WRF-CAMx model in the BTH area. Overall, this research provides valuable insights for local and regional atmospheric pollution control strategies. Additionally, it offers a robust analytical tool for research in the field of atmospheric pollution.

A new scheme of PM2.5 and O3 control strategies with the integration of SOM, GA and WRF-CAMx

Previous air pollution control strategies didn't pay enough attention to regional collaboration and the spatial response sensitivities, resulting in limited control effects in China. This study proposed an effective PM2.5 and O3 control strategy scheme with the integration of Self-Organizing Map (SOM), Genetic Algorithm (GA) and WRF-CAMx, emphasizing regional collaborative control and the strengthening of control in sensitive areas. This scheme embodies the idea of hierarchical management and spatial-temporally differentiated management, with SOM identifying the collaborative subregions, GA providing the optimized subregion-level priority of precursor emission reductions, and WRF-CAMx providing response sensitivities for grid-level priority of precursor emission reductions. With Beijing-Tianjin-Hebei and the surrounding area (BTHSA, "2 + 26" cities) as the case study area, the optimized strategy required that regions along Taihang Mountains strengthen the emission reductions of all precursors in PM2.5-dominant seasons, and strengthen VOCs reductions but moderate NOx reductions in O3-dominant season. The spatiotemporally differentiated control strategy, without additional emission reduction burdens than the 14th Five-Year Plan proposed, reduced the average annual PM2.5 and MDA8 O3 concentrations in 28 cities by 3.2%-8.2% and 3.9%-9.7% respectively in comparison with non-differential control strategies, with the most prominent optimization effects occurring in the heavily polluted seasons (6.9%-18.0% for PM2.5 and 3.3%-14.2% for MDA8 O3, respectively). This study proposed an effective scheme for the collaborative control of PM2.5 and O3 in BTHSA, and shows important methodological implications for other regions suffering from similar air quality problems.

Development and evaluation of an online monitoring single-particle optical particle counter with polarization detection

We developed a single-particle optical particle counter with polarization detection (SOPC) for the real-time measurement of the optical size and depolarization ratio (defined as the ratio of the vertical component to the parallel component of backward scattering) of atmospheric particles, the polarization ratio (DR) value can reflect the irregularity of the particles. The SOPC can detect aerosol particles with size larger than 500 nm and the maximum particle count rate reaches ∼1.8 × 105 particles per liter. The SOPC uses a modulated polarization laser to measure the optical size of particles according to forward scattering signal and the DR value of the particles by backward S and P signal components. The sampling rate of the SOPC was 106 #/(sec·channel), and all the raw data were processed online. The calibration curve was obtained by polystyrene latex spheres with sizes of 0.5-10 µm, and the average relative deviation of measurement was 3.96% for sub 3 µm particles. T-matrix method calculations showed that the DR value of backscatter light at 120° could describe the variations in the aspect ratio of particles in the above size range. We performed insitu observations for the evaluation of the SOPC, the mass concentration constructed by the SOPC showed good agreement with the PM2.5 measurements in a nearby state-controlled monitoring site. This instrument could provide useful data for source appointment and regulations against air pollution.

WITHDRAWN: Insights into the source contributions to the elevated fine particulate matter in Nigeria using a source-oriented chemical transport model

This paper has been withdrawn.

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.

Effects of VOC emissions from chemical industrial parks on regional O3-PM2.5 compound pollution in the Yangtze River Delta

Ozone (O3) and fine particulate matter (PM2.5) compound pollution has emerged as a primary form of air pollution in Chinese urban. Volatile organic compounds (VOCs), as common precursors of O3 and PM2.5, play a significant role in air pollution control. Chemical industrial parks (CIPs) are crucial emission sources of VOCs and have garnered significant attention. This study focused on 142 CIPs located in the Yangtze River Delta (YRD) to investigate the characteristics of VOC emissions from CIPs and their impact on O3-PM2.5 compound pollution, considering the enhanced atmospheric oxidation capacity (AOC). The Comprehensive Air Quality Model with Extensions (CAMx) model was employed for this analysis. The results show that VOC emissions from CIPs contributed significantly to regional O3 and secondary organic aerosol (SOA), accounting for 17.1 % and 18.18 % of the anthropogenic sources, respectively. Regions exhibiting the highest contributions were located along the Hangzhou Bay. Compared with 2014, an elevation in the contribution of VOC emissions from CIPs to the annual average concentrations of MDA8 O3 and SOA in the YRD in 2017 by 0.069 μg/m3 and 0.007 μg/m3, respectively. During episodes of compound pollution, the concentration of atmospheric oxidant (HOx + NO3) was 28.65 % higher than during clean days, and significant positive correlations were observed between hydrogen oxygen radicals (HOx) and maximum daily 8-h average (MDA8 O3) as well as between HOx and SOA, exhibiting correlation coefficients of 0.86 and 0.48, respectively. Effective control measures for VOC emissions, particularly from the pharmaceutical and petrochemical industry parks located along Hangzhou Bay, are essential in curtailing the production rate of HOx and in regulating AOC levels in the YRD. Maintaining the daily average HOx concentration below 10 ppt would be a valuable strategy in achieving coordinated control of O3 and SOA, thus aiding in the alleviation of O3-PM2.5 compound pollution in the YRD.

Insights into quantitative evaluation technology of PM2.5 transport at multi-perspective and multi-spatial and temporal scales in the north China plain

Cross-border transport is a crucial factor affecting air quality, while how to quantify the transport contribution through different technologies at multi-perspective and multi-scale have not been fully understood. This study established three quantification techniques, and conducted a systematic assessment of PM2.5 transport over the North China Plain (NCP) based on numerical simulations and vertical observations. Results suggested that the annual local emissions, inter-urban and outer-regional transport contributed 44.5%-64.6%, 15.2%-27.9% and 18.0%-28.2% of total surface PM2.5 concentrations, respectively, with transport intensity stronger in July and April, yet weaker in January and October. The southwest-northeast, northeast-southwest, and southeast-northwest were three prevailing transport directions near the surface. By comparison, the annual PM2.5 transport contribution below the atmospheric boundary layer height increased by 16.8%-24.5% in Beijing, Tianjin and Shijiazhuang, with inter-urban and outer-regional contribution of 29.8%-32.1% and 18.5%-23.1%. Furthermore, observed fluxes from fixed-point and vehicle-based mobile lidar were in good agreement with the simulated flux. PM2.5 net flux intensity varied with height, with generally larger at the middle- and high-altitude layer than that of low-altitude layer. In the early, during and late period of haze peak formation (Stage Ⅰ, Ⅱ, Ⅲ, respectively), the largest absolute flux intensity on average was Stage Ⅱ (566.7 t/d), followed by Stage Ⅲ (307.0 t/d) and Ⅰ (191.4 t/d). Besides, external transport may dominate the second concentration peak, while local emissions may play a more vital role in the first and third peaks. It has been noted that joint prevention and control measures should be proposed 1-2 days before reaching PM2.5 extremes. These findings could improve our understanding of transport influence mechanism of PM2.5 and propose effective emission reduction measures in the NCP region.

Impacts of synoptic circulation on surface ozone pollution in a coastal eco-city in Southeastern China during 2014-2019

The coastal eco-city of Fuzhou in Southeastern China has experienced severe ozone (O₃) episodes at times in recent years. In this study, three typical synoptic circulations types (CTs) that influenced more than 80% of O₃ polluted days in Fuzhou during 2014-2019 were identified using a subjective approach. The characteristics of meteorological conditions linked to photochemical formation and transport of O₃ under the three CTs were summarized. Comprehensive Air Quality Model with extensions was applied to simulate O₃ episodes and to quantify O₃ sources from different regions in Fuzhou. When Fuzhou was located to the west of a high-pressure system (classified as "East-ridge"), more warm southwesterly currents flowed to Fuzhou, and the effects of cross-regional transport from Guangdong province and high local production promoted the occurrence of O₃ episodes. Under a uniform pressure field with a low-pressure system occurring to the east of Fuzhou (defined as "East-low"), stagnant weather conditions caused the strongest local production of O₃ in the atmospheric boundary layer. Controlled by high-pressure systems over the mainland (categorized as "Inland-high"), northerly airflows enhanced the contribution of cross-regional transport to O₃ in Fuzhou. The abnormal increases of the "East-ridge" and "Inland-high" were closely related to O₃ pollution in Fuzhou in April and May 2018, resulting in the annual maximum number of O₃ polluted days during recent years. Furthermore, the rising number of autumn O₃ episodes in 2017-2019 was mainly related to the "Inland-high", indicating the aggravation of cross-regional transport and highlighting the necessity of enhanced regional collaboration and efforts in combating O₃ pollution.

Improving the accuracy of O3 prediction from a chemical transport model with a random forest model in the Yangtze River Delta region, China

Due to inherent errors in the chemical transport models, inaccuracies in the input data, and simplified chemical mechanisms, ozone (O₃) predictions are often biased from observations. Accurate O₃ predictions can better help assess its impacts on public health and facilitate the development of effective prevention and control measures. In this study, we used a random forest (RF) model to construct a bias-correction model to correct the bias in the predictions of hourly O₃ (O₃-1h), daily maximum 8-h O₃ (O₃-Max8h), and daily maximum 1-h O₃ (O₃-Max1h) concentrations from the Community Multi-Scale Air Quality (CMAQ) model in the Yangtze River Delta region. The results show that the RF model successfully captures the nonlinear response relationship between O₃ and its influence factors, and has an outstanding performance in correcting the bias of O₃ predictions. The normalized mean biases (NMBs) of O₃-1h, O₃-Max8h, and O₃-Max1h decrease from 15.8%, 20.0%, and 17.0.% to 0.5%, -0.8%, and 0.1%, respectively; correlation coefficients increase from 0.78, 0.90, and 0.89 to 0.94, 0.95, and 0.94, respectively. For O₃-1h and O₃-Max8h, the original CMAQ model shows an obvious bias in the central and southern Zhejiang region, while the RF model decreases the NMB values from 54% to -1% and 34% to -4%, respectively. The O₃-1h bias is mainly caused by the bias of nitrogen dioxide (NO₂). Relative humidity and temperature are also important factors that lead to the bias of O₃. For high O₃ concentrations, the temperature bias and O₃ observations are the major reasons for the discrepancy between the model and the observations.

Understanding the nocturnal ozone increase in Nanjing, China: Insights from observations and numerical simulations

Surface ozone (O₃) is mainly photochemically formed by nitrogen oxides (NO_X) and volatile organic compounds (VOCs), and therefore O₃ usually has a distinct diurnal variation with high concentrations in the afternoon and low values at night. However, eight nocturnal O₃ increase (NOI) events were identified in Nanjing in June 2021. To understand the mechanism of NOI events, we selected two events (June 6-7, and 24-25) for observational data analysis. The Community Multiscale Air Quality (CMAQ) model was employed for the process analysis (PA) and regional transport of O₃. By analyzing the O₃ observation data and meteorological factors, we found that there were clear southeastward O₃ transport paths. The O₃ peak clearly moved from the upwind to the downwind cities in both events. Model simulations showed that when nocturnal O₃ enhancement occurred, horizontal transport resulted in a negative to positive net O₃ production rate. O₃ continued to get accumulated in Nanjing. Nocturnal O₃ in the first event was dominated by long-range transport, with the top two contributing cities being Huzhou (5.6 %) and Jiaxing (4.7 %). NOI during the second event was from the nearby upwind cities. The top three contributing cities were Shanghai (18.3 %), Wuxi (9.1 %), and Suzhou (8.8 %). We conclude that the June NOI events in Nanjing were mainly driven by the horizontal transport of southeasterly winds. This study provides scientific support for O₃ prevention and control in Nanjing in the summer.

Assessment of factors affecting the diurnal variations of atmospheric PAHs based on a numerical simulation

Atmospheric polycyclic aromatic hydrocarbons (PAHs) are a type of organic pollutants that seriously endanger human health. Obtaining the diurnal variations of PAHs and clarifying their impact mechanisms are significant for the government to formulate targeted prevention and control measures. However, the influencing factors that dominate the diurnal variations of common PAHs are currently unclear. In order to solve this problem, 16 PAHs selected by the United States Environmental Protection Agency (EPA) as priority-controlled pollutants were simulated with high resolution. The simulation results were validated based on diurnal observations in the vertical direction. Although the model underestimated the particle-phase concentrations of most components, it captured their diurnal variations fairly well. In addition, we assessed the factors affecting the diurnal variations of PAHs with sensitivity tests, including chemical reactions and atmospheric diffusion. The results showed that the transforming ratios of PAHs by oxidants were higher during the day than that at night due to the dominant reactions with OH radical. Atmospheric dispersion affected the vertical distribution of PAHs, which resulted in higher day/night ratios at high altitudes than near the ground. We also compared the strength of atmospheric diffusion and chemical reaction on the diurnal trends of PAHs. Near the ground, atmospheric diffusion was the most dominant factor in determining their diurnal trends. At high altitudes, their diurnal trends were determined by a combination of atmospheric diffusion and chemical reactions. These findings can provide a comprehensive understanding of the diurnal variations of common PAHs, which are informative for the prevention and control of PAHs pollution.

Public Concern about Haze and Ozone in the Era of Their Coordinated Control in China

In China, due to the implementation of the Action Plan for Prevention and Control of Air Pollution (APPCAP), the concentrations of PM_2.5 (fine particulate matter) and severe haze in most cities have decreased significantly. However, at present, haze pollution in China has not been completely mitigated, and the problem of O₃ (ozone) has become prominent. Therefore, the prevention and control of haze and O₃ pollution have become important and noticeable issues in the field of atmospheric management. We used the Baidu search indices of "haze" and "ozone" to reflect public concerns about air quality and uncover different correlations between level of concern and level of pollution, and then we identified regions in China that require public attention. The results showed that (1) over the last decade, the search index of haze had a rapid trend of variation in line with changes in haze pollution, but that of O₃ had a relatively slowly increasing trend; (2) the lag days between the peaks of public concern and the peaks of air pollution became increasingly shorter according to daily data analysis; and (3) 96 polluted cities did not receive sufficient public attention. Although periods of heavily haze-polluted weather, which affects visibility, have generated much public concern, periods of slight pollution have not received enough public attention. Public health protection and environmental participation regarding these periods of slight pollution in China deserve appropriate levels of attention.

Synergetic PM2.5 and O3 control strategy for the Yangtze River Delta, China

PM_2.5 concentrations have dramatically reduced in key regions of China during the period 2013-2017, while O₃ has increased. Hence there is an urgent demand to develop a synergetic regional PM_2.5 and O₃ control strategy. This study develops an emission-to-concentration response surface model and proposes a synergetic pathway for PM_2.5 and O₃ control in the Yangtze River Delta (YRD) based on the framework of the Air Benefit and Cost and Attainment Assessment System (ABaCAS). Results suggest that the regional emissions of NOx, SO₂, NH₃, VOCs (volatile organic compounds) and primary PM_2.5 should be reduced by 18%, 23%, 14%, 17% and 33% compared with 2017 to achieve 25% and 5% decreases of PM_2.5 and O₃ in 2025, and that the emission reduction ratios will need to be 50%, 26%, 28%, 28% and 55% to attain the National Ambient Air Quality Standard. To effectively reduce the O₃ pollution in the central and eastern YRD, VOCs controls need to be strengthened to reduce O₃ by 5%, and then NOx reduction should be accelerated for air quality attainment. Meanwhile, control of primary PM_2.5 emissions shall be prioritized to address the severe PM_2.5 pollution in the northern YRD. For most cities in the YRD, the VOCs emission reduction ratio should be higher than that for NOx in Spring and Autumn. NOx control should be increased in summer rather than winter when a strong VOC-limited regime occurs. Besides, regarding the emission control of industrial processes, on-road vehicle and residential sources shall be prioritized and the joint control area should be enlarged to include Shandong, Jiangxi and Hubei Province for effective O₃ control.

Co-effect assessment on regional air quality: A perspective of policies and measures with greenhouse gas reduction potential

Clean air policies have achieved remarkable air quality improvement in China for the last decade. However, as more importance was attached to climate issues and further improvement of air quality, policies with greenhouse gas (GHG) reduction potential were supposed to play a significant role. Here, we designed a conventional legislation pathway scenario (CLP) and an enhanced greenhouse gas reduction scenario (EGR), to estimate the co-effects of policies effective in GHG reduction on air pollutant control and air quality improvement in the Yangtze River Delta (YRD) region from 2014 to 2020, adopting a measure-specific evaluation method and an integrated WRF-CAMx model simulation. Results showed that: 1) With the implementation of enhanced measures with GHG reduction potential, emissions of SO₂, NO_x, PM_2.5, PM₁₀, VOC_s and NH₃ decreased by 16.4 %, 21.6 %, 18.6 %, 16.5 %, 23.9 % and 15.4 % in EGR scenario respectively, compared with CLP scenario. And the annual mean simulated concentrations of PM_2.5, SO₂ and NO₂ of the YRD decreased by 11.2 %, 15.4 % and 20.6 %, respectively. 2) The average 8-h maxima (MDA8) concentration of O₃ presented a slightly increasing trend under the impacts of measures with GHG reduction potential, which might be on account of the unbalanced control of NO_x and VOC_s, the two major precursors of O₃. 3) Based on the source apportionment analysis, major partition of total ozone in the four receptors in YRD was from regional transportation, rather than local formation. And the major sectors contributing to ozone were industry and transportation sector. This study quantitatively assessed the co-benefits of GHG-control-effective policies and specific measures on air quality improvement, which would help to provide implications for future policy-making to achieve air pollution and climate change co-control.

Modelling driving factors of PM2.5 concentrations in port cities of the Yangtze River Delta

PM_2.5 is one of the major air pollutants in port cities of the Yangtze River Delta (YRD) of China. Understanding the driving factors of PM_2.5 is essential to guide air pollution prevention and control. We selected 17 major port cities in YRD to study the driving factors of PM_2.5 in 2019 and 2020. Generalized Additive Models were built to model the non-linear effects of single, multiple and interactions of driving factors on the variations of PM_2.5. NO₂, SO₂ and the day of year are most strongly associated with the variation of PM_2.5 concentration when used alone. Anthropogenic emissions play complicated roles in regulating PM_2.5 concentration. Although the effect of cargo throughput (CT) on PM_2.5 concentration is non-monotonic, higher PM_2.5 levels are found to be associated with higher levels of SO₂ and CT. This work can potentially provide a scientific basis for formulating PM_2.5 prevention and control policies in the region.

Attributing Increases in Ozone to Accelerated Oxidation of Volatile Organic Compounds at Reduced Nitrogen Oxides Concentrations

Surface ozone (O3) is an important secondary pollutant affecting climate change and air quality in the atmosphere. Observations during the COVID-19 lockdown in urban China show that the co-abatement of nitrogen oxides (NOx) and volatile organic compounds (VOCs) caused winter ground-level O3 increases, but the chemical mechanisms involved are unclear. Here we report field observations in the Shanghai lockdown that reveals increasing photochemical formation of O3 from VOC oxidation with decreasing NOx. Analyses of the VOC profiles and NO/NO2 indicate that the O3 increases by the NOx reduction counteracted the O3 decreases through the VOC emission reduction in the VOC-limited region, and this may have been the main mechanism for this net O3 increase. The mechanism may have involved accelerated OH-HO2-RO2 radical cycling. The NOx reductions for increasing O3 production could explain why O3 increased from 2014 to 2020 in response to NOx emission reduction even as VOC emissions have essentially remained unchanged. Model simulations suggest that aggressive VOC abatement, particularly for alkenes and aromatics, should help reverse the long-term O3 increase under current NOx abatement conditions.

Regional demarcation of synergistic control for PM2.5 and ozone pollution in China based on long-term and massive data mining

Implementing an inter-regional synergistic control policy for fine particulate matter (PM_2.5) and ground-level ozone (O₃) could improve regional air quality. However, little is known about the effectiveness and accuracy of synergistic control region delineation. This study aimed to construct a network model and apply it to a case study of regional delineation in China at different scales to quantify the interactions between regions. Firstly, the Cumulative Risk Index (CRI) was proposed and quantified from a health risk perspective based on the daily mean PM_2.5 and daily maximum 8-h average O₃ concentrations from 2015 to 2020 in China. Then, the complex network topology parameters were introduced to determine the optimal threshold for different network constructions, and the Girvan-Newman (GN) algorithm was used to divide the network into independent regions. Results showed that the correlation between cities is more robust than that between provinces. There are four-seven major provincial-scale regions with strong synchronicity in CRI, suggesting that PM_2.5 and O₃ synergistic control policies shall be implemented jointly within these demarcated regions. Moreover, urban-scale CRI network analysis indicated that the existing key control areas (2 + 26 cities) need to be expanded to 40-50 cities and refined into seven independent urban regions. Meanwhile, the Fen-Wei Plain can be focused on six cities: Xi'an, Baoji, Xianyang, Weinan, Yuncheng, and Tongchuan. This study could improve our understanding of the synergistic control regions for PM_2.5 and O₃ pollution, and the results could be used to develop joint control policies for both pollutants.

Unraveling the dynamics, heterogeneity, determinants of eco-efficiency in Beijing-Tianjin-Hebei urban agglomeration, China

Eco-efficiency has been considered a valuable gauge for evaluating how efficient economic activities are in regard to resource inputs and eco-environmental pressures. Even though Ecosystem services (ESs) are inseparable from sustainable eco-environment, a paucity of literature has considered ESs in eco-efficiency research lines. Therefore, this study aims to construct a novel eco-efficiency evaluation framework by integrating ESs as natural capital input and measure it utilizing the Epsilon-based measure model for the county-level cities in Beijing-Tianjin-Hebei urban agglomeration (BTHUA) during the period 2005-2015. The spatial econometric technique is further performed to acquire quantitative evidence about whether ESs and other determinants impact eco-efficiency. The results revealed that eco-efficiency increased continuously in the whole BTHUA and BTHUA's optimized development functional areas, whereas eco-efficiency of BTHUA's sub-regions showed a significant temporal diversity. The average eco-efficiency values of cities in key development functional areas and restricted development functional areas showed the V-shaped trend (declining before 2010 and then rising). Interestingly, this study found that ESV economic loss may result in eco-efficiency decline for cities located in key development functional areas. From the spatial heterogeneity perspective, the city with high EE is mainly located in eastern BTHUA, whereas cities in the northern plateau areas, southwestern, and western BTHUA have relatively low EE. Furthermore, there existed a significant spatial autocorrelation and a spatial agglomeration heterogeneity, which suggests that the low-low correlation regions gradually being the most dominant spatial pattern. The results of spatial econometric model verified that water yield has the strongest positive effect on EE while soil erosion will lead to declining EE. This paper potentially provides new insights for future policy design of urban agglomeration sustainable deployment.

Responses of nitrogen and sulfur deposition to NH3 emission control in the Yangtze River Delta, China

NH₃ emission control has proven to be of great importance in reducing PM_2.5 concentrations in China, while how it affects nitrogen/sulfur (N/S) deposition is still unclear. This study expanded the response surface model method to quantify the responses of N/S deposition to the emission control of precursors (NO_x, SO₂, NH₃, VOCs and primary PM_2.5) in the Yangtze River Delta, China. NH₃ control was found to have higher efficiency in reducing N/S deposition than NO_x and SO₂ alone. The reduced N deposition response to NH₃ emission control was higher in the northern part of the YRD region, whereas oxidized N deposition decreased sharply in the region with a low N critical load. Synergetic effect was found in reducing N deposition when we controlled the NH₃ and NO_x emissions simultaneously. Compared with the sum effect of individual NH₃ and NO_x emission control, the extra benefits from the synergy controls accounted for 4.4% (1.23 kg N·ha^-1·yr^-1) of the total N deposition, of which 81% came from the oxidized N deposition. The YRD region could receive the largest synergetic effect with a 1:1 ratio of NO_x:NH₃ emission reduction. The NH₃ emission control increases the dry deposition of acid substances and worsens acid rain though it reduces the wet S/oxidized N deposition. These findings highlight the effectiveness of NH₃ emission control and suggest a multi-pollutant control strategy for reducing N/S deposition. The response surface model method for deposition also provides a reference for other regions in China and other countries.

Ozone Pollution in Chinese Cities: Spatiotemporal Variations and Their Relationships with Meteorological and Other Pollution Factors (2016–2020)

With the acceleration of urbanization, ozone (O3) pollution has become increasingly serious in many Chinese cities. This study analyzes the temporal and spatial characteristics of O3 based on monitoring and meteorological data for 366 cities and national weather stations throughout China from 2016 to 2020. Least squares linear regression and Spearman’s correlation coefficient were computed to investigate the relationships of O3 with various pollution factors and meteorological conditions. Global Moran’s I and the Getis–Ord index Gi* were adopted to reveal the spatial agglomeration of O3 pollution in Chinese cities and characterize the temporal and spatial characteristics of hot and cold spots. The results show that the national proportion of cities with an annual concentration exceeding 160 μg·m−3 increased from 21.6% in 2016 to 50.9% in 2018 but dropped to 21.5% in 2020; these cities are concentrated mainly in Central China (CC) and East China (EC). Throughout most of China, the highest seasonal O3 concentrations occur in summer, while the highest values in South China (SC) and Southwest China (SWC) occur in autumn and spring, respectively. The highest monthly O3 concentration reached 200 μg·m−3 in North China (NC) in June, while the lowest value was 60 μg·m−3 in Northeast China (NEC) in December. O3 is positively correlated with the ground surface temperature (GST) and sunshine duration (SSD) and negatively correlated with pressure (PRS) and relative humidity (RHU). Wind speed (WIN) and precipitation (PRE) were positively correlated in all regions except SC. O3 concentrations are significantly differentiated in space: O3 pollution is high in CC and EC and relatively low in the western and northeastern regions. The concentration of O3 exhibits obvious agglomeration characteristics, with hot spots being concentrated mainly in NC, CC and EC.

Informal Environment Regulation, Green Technology Innovation and Air Pollution: Quasi-Natural Experiments from Prefectural Cities in China

Facing informal environment regulation carried out by the environmental protection organizations, we study and judge its inhibitory effect on air pollution and the acting path. Based on panel data of 285 cities in China from 1998 to 2018, a time-varying difference-in-difference model is used to estimate the effect of informal environment regulation on air pollution. The estimation results show that informal environment regulation can inhibit air pollution significantly under different scenarios. Green technology innovation is introduced into the research and a mediating effect model is used to investigate the influencing mechanism. Informal environment regulation strengthens pressure on pollutant emissions. This forces enterprises to enhance the investment and application of green technology innovation during production. Mechanism analysis shows that informal environment regulation inhibits air pollution by encouraging the application of green technology innovation. The above conclusions are still valid after a series of robustness tests, including parallel trend, placebo test and instrumental variables. The research conclusions provide empirical evidence for the construction of a diversified air-pollution control system and demonstrate the practical significance of informal environment regulation to improve air quality.

Spatio-Temporal Heterogeneity of the Relationships Between PM2.5 and Its Determinants: A Case Study of Chinese Cities in Winter of 2020

Fine particulate matter (PM2.5) poses threat to human health in China, particularly in winter. The pandemic of coronavirus disease 2019 (COVID-19) led to a series of strict control measures in Chinese cities, resulting in a short-term significant improvement in air quality. This is a perfect case to explore driving factors affecting the PM2.5 distributions in Chinese cities, thus helping form better policies for future PM2.5 mitigation. Based on panel data of 332 cities, we analyzed the function of natural and anthropogenic factors to PM2.5 pollution by applying the geographically and temporally weighted regression (GTWR) model. We found that the PM2.5 concentration of 84.3% of cities decreased after lockdown. Spatially, in the winter of 2020, cities with high PM2.5 concentrations were mainly distributed in Northeast China, the North China Plain and the Tarim Basin. Higher temperature, wind speed and relative humidity were easier to promote haze pollution in northwest of the country, where enhanced surface pressure decreased PM2.5 concentrations. Furthermore, the intensity of trip activities (ITAs) had a significant positive effect on PM2.5 pollution in Northwest and Central China. The number of daily pollutant operating vents of key polluting enterprises in the industrial sector (VOI) in northern cities was positively correlated with the PM2.5 concentration; inversely, the number of daily pollutant operating vents of key polluting enterprises in the power sector (VOP) imposed a negative effect on the PM2.5 concentration in these regions. This work provides some implications for regional air quality improvement policies of Chinese cities in wintertime.

Evaluation of a highly condensed SAPRC chemical mechanism and two emission inventories for ozone source apportionment and emission control strategy assessments in China

The response of summertime O₃ to changes in the nitrogen oxides (NO_x) and volatile organic compounds (VOC) emissions, and contributions of different NO_x and VOC sources to O₃ in China are studied using a highly condensed photochemical mechanism in the Statewide Air Pollution Research Center (SAPRC) family (CS07A) and two popular anthropogenic emission inventories, the Multi-resolution Emission Inventory for China (MEIC) and Regional Emission inventory in ASia (REAS). Although CS07A predicts slightly lower O₃ concentrations than the standard fix-parameter version of the SAPRC-11 mechanism, the two mechanisms predict almost identical relative responses to daily maximum 8-hour O₃ (O₃-8h) due to NO_x and VOC emission reductions. A source-oriented version of the CS07A is applied to determine source contributions of NO_x and VOCs to O₃ using MEIC and REAS. The two inventories lead to similar model performance of O₃, with MEIC predicting higher O₃ in Beijing and Shanghai, especially on high O₃ days. Source apportionment results show that industry and transportation are the top two contributors to non-background O₃ for both inventories, followed by power and biogenic emissions. In general, the two inventories lead to similar source contribution estimations to O₃ attributable to NO_x. However, their estimations of relative contributions to VOC-related O₃ differ for the industrial and transportation sectors. Differences in the source apportionment results are more significant in some urban areas, although both emissions capture the spatial variations in the source contributions. Our results suggest that future emission control policies should be assessed using multiple emission inventories, and the condensed CS07A is suitable for policy applications when a large number of simulations are needed.

Diagnostic analysis of regional ozone pollution in Yangtze River Delta, China: A case study in summer 2020

A regional ozone (O₃) pollution event occurred in the Yangtze River Delta region during August 17-23, 2020 (except on August 21). This study aims to understand the causes of O₃ pollution during the event using an emission-based model (i.e., the Community Multiscale Air Quality (CMAQ) model) and an observation-based model (OBM). The OBM was used to investigate O₃ sensitivity to its precursors during the O₃ pollution, concluding that O₃ formation was limited by volatile organic compounds (VOCs) on August 19, but was co-limited by VOCs and nitrogen oxides (NOx) on other polluted days. Aromatics and alkenes were the two main VOC groups contributing to the O₃ formation, with trans-2-butene and m/p-xylene as the key species among the VOCs measured at the Nanjing urban site. The source apportionment results estimated using the source-oriented CMAQ model suggest that the transportation and industry sources dominated the non-background O₃ production in Nanjing, which were responsible for 52% and 24.7%, respectively. The O₃ concentration attributed to NOx (~70%) was significantly higher than that attributed to VOCs (approximately 30%). The process analysis revealed that vertical mixing increased the O₃ concentrations in the early morning, and photochemical reactions promoted O₃ formation and accumulation during the daytime within the planetary boundary layer. At night, outflow from horizontal transport and nocturnal chemistry jointly resulted the O₃ depletion. The contributions of inter-city transport during the O₃ pollution period in Nanjing were also estimated. The predicted O₃ concentration was largely recorded from long-distance regions, reaching 46%, followed by local sources (38%) and surrounding cities (16%). The results indicate that both NOx and VOCs contributed significantly to O₃ pollution during this event, and the emissions controls of NOx and the key VOC species of aromatics and alkenes from a cooperative regional perspective should be considered to mitigate O₃ pollution.

PM2.5 and O3 relationships affected by the atmospheric oxidizing capacity in the Yangtze River Delta, China

The atmospheric oxidizing capacity (AOC), reflecting the self-cleansing capacity of the atmosphere, plays an important role in the chemical evolution of secondary fine particulate matter (PM_2.5) and ozone (O₃). In this work, the AOC and its relationships with PM_2.5 and O₃ were investigated with a chemical transport model (CTM) in the Yangtze River Delta (YRD) region during the four seasons of 2017. The region-wide average AOC is ~4.5×10^-4 min^-1 in summer and ~ 6.4×10^-5 min^-1 in winter. Hydroxyl (OH) radicals oxidation contributes 55-69% to the total AOC, followed by nitrate (NO₃) radicals and O₃ (accounting for 19-34% and < 10%, respectively). The AOC attains a strong positive correlation with the O₃ level in all seasons. However, it is weakly or insignificantly correlated with PM_2.5 except in summer. Additionally, AOC×(SO₂ + NO₂ + volatile organic compound (VOC)) is well correlated with the PM_2.5 level, and high levels of precursors counteract lower AOC values in cold seasons. Collectively, the results indicate that the abundance of precursors could drive secondary aerosol formation in winter, and aqueous or heterogeneous reactions (not considered in the AOC estimates) are likely of importance at high aerosol loadings in the YRD. The relationship between the daily PM_2.5 and O₃ levels is affected by the AOC magnitude. PM_2.5 and O₃ are strongly correlated when the AOC is relatively high, but PM_2.5 is independent of O₃ under low-AOC (<6.6×10^-5 min^-1, typically in winter) conditions. This work reveals the dependence of PM_2.5-O₃ relationships on the AOC, suggesting that joint PM_2.5 and O₃ reduction could be realized at moderate to high AOC levels, especially in spring and autumn when the cooccurrence of high O₃ and PM_2.5 events is frequently observed.

Implications of Mitigating Ozone and Fine Particulate Matter Pollution in the Guangdong-Hong Kong-Macau Greater Bay Area of China Using a Regional-To-Local Coupling Model

Ultrahigh-resolution air quality models that resolve sharp gradients of pollutant concentrations benefit the assessment of human health impacts. Mitigating fine particulate matter (PM2.5) concentrations over the past decade has triggered ozone (O3) deterioration in China. Effective control of both pollutants remains poorly understood from an ultrahigh-resolution perspective. We propose a regional-to-local model suitable for quantitatively mitigating pollution pathways at various resolutions. Sensitivity scenarios for controlling nitrogen oxide (NOx) and volatile organic compound (VOC) emissions are explored, focusing on traffic and industrial sectors. The results show that concurrent controls on both sectors lead to reductions of 17%, 5%, and 47% in NOx, PM2.5, and VOC emissions, respectively. The reduced traffic scenario leads to reduced NO2 and PM2.5 but increased O3 concentrations in urban areas. Guangzhou is located in a VOC-limited O3 formation regime, and traffic is a key factor in controlling NOx and O3. The reduced industrial VOC scenario leads to reduced O3 concentrations throughout the mitigation domain. The maximum decrease in median hourly NO2 is >11 μg/m³, and the maximum increase in the median daily maximum 8-hr rolling O3 is >10 μg/m³ for the reduced traffic scenario. When controls on both sectors are applied, the O3 increase reduces to <7 μg/m³. The daily averaged PM2.5 decreases by <2 μg/m³ for the reduced traffic scenario and varies little for the reduced industrial VOC scenario. An O3 episode analysis of the dual-control scenario leads to O3 decreases of up to 15 μg/m³ (8-hr metric) and 25 μg/m³ (1-hr metric) in rural areas.

Spatiotemporal Patterns and Regional Transport of Ground-Level Ozone in Major Urban Agglomerations in China

Ground-level ozone (O3) pollution has become a serious environmental issue in major urban agglomerations in China. To investigate the spatiotemporal patterns and regional transports of O3 in Beijing–Tianjin–Hebei (BTH-UA), the Yangtze River Delta (YRD-UA), the Triangle of Central China (TC-UA), Chengdu–Chongqing (CY-UA), and the Pearl River Delta urban agglomeration (PRD-UA), multiple transdisciplinary methods were employed to analyze the O3-concentration data that were collected from national air quality monitoring networks operated by the China National Environmental Monitoring Center (CNEMC). It was found that although ozone concentrations have decreased in recent years, ozone pollution is still a serious issue in China. O3 exhibited different spatiotemporal patterns in the five urban agglomerations. In terms of monthly variations, O3 had a unimodal structure in BTH-UA but a bimodal structure in the other urban agglomerations. The maximum O3 concentration was in autumn in PRD-UA, but in summer in the other urban agglomerations. In spatial distribution, the main distribution of O3 concentration was aligned in northeast–southwest direction for BTH-UA and CY-UA, but in northwest–southeast direction for YRD-UA, TC-UA, and PRD-UA. O3 concentrations exhibited positive spatial autocorrelations in BTH-UA, YRD-UA, and TC-UA, but negative spatial autocorrelations in CY-UA and PRD-UA. Variations in O3 concentration were more affected by weather fluctuations in coastal cities while the variations were more affected by seasonal changes in inland cities. O3 transport in the center cities of the five urban agglomerations was examined by backward trajectory and potential source analyses. Local areas mainly contributed to the O3 concentrations in the five cities, but regional transport also played a significant role. Our findings suggest joint efforts across cities and regions will be necessary to reduce O3 pollution in major urban agglomerations in China.

Relationships between Long-Term Ozone Exposure and Allergic Rhinitis and Bronchitic Symptoms in Chinese Children

Numerous studies have demonstrated that exposure to ambient ozone (O₃) could have adverse effects on children's respiratory health. However, previous studies mainly focused on asthma and wheezing. Evidence for allergic rhinitis and bronchitic symptoms (e.g., persistent cough and phlegm) associated with O₃ is limited, and results from existing studies are inconsistent. This study included a total of 59,754 children from the seven northeastern cities study (SNEC), who were aged 2 to 17 years and from 94 kindergarten, elementary and middle schools. Information on doctor-diagnosed allergic rhinitis (AR), persistent cough, and persistent phlegm was collected during 2012-2013 using a standardized questionnaire developed by the American Thoracic Society (ATS). Information for potential confounders was also collected via questionnaire. Individuals' exposure to ambient ozone (O₃) during the four years before the investigation was estimated using a satellite-based random forest model. A higher level of O₃ was significantly associated with increased risk of AR and bronchitic symptoms. After controlling for potential confounders, the OR (95% CI) were 1.13 (1.07-1.18), 1.10 (1.06-1.16), and 1.12 (1.05-1.20) for AR, persistent cough, and persistent phlegm, respectively, associated with each interquartile range (IQR) rise in O₃ concentration. Interaction analyses showed stronger adverse effects of O₃ on AR in children aged 7-17 years than those aged 2-6 years, while the adverse association of O₃ with cough was more prominent in females and children aged 7-12 years than in males and children aged 2-6 and 13-17 years. This study showed that long-term exposure to ambient O₃ was significantly associated with higher risk of AR and bronchitic symptoms in children, and the association varies across age and gender. Our findings contribute additional evidence for the importance of controlling O₃ pollution and protecting children from O₃ exposure.

Factors Underlying Spatiotemporal Variations in Atmospheric PM2.5 Concentrations in Zhejiang Province, China

Fine particulate matter in the lower atmosphere (PM2.5) continues to be a major public health problem globally. Identifying the key contributors to PM2.5 pollution is important in monitoring and managing atmospheric quality, for example, in controlling haze. Previous research has been aimed at quantifying the relationship between PM2.5 values and their underlying factors, but the spatial and temporal dynamics of these factors are not well understood. Based on random forest and Shapley additive explanation (SHAP) algorithms, this study analyses the spatiotemporal variations in selected key factors influencing PM2.5 in Zhejiang Province, China, for the period 2000–2019. The results indicate that, while factors influencing PM2.5 varied significantly during the period studied, SHAP values suggest that there is consistency in their relative importance as follows: meteorological factors (e.g., atmospheric pressure) > socioeconomic factors (e.g., gross domestic product, GDP) > topography and land cover factors (e.g., elevation). The contribution of GDP and transportation factors initially increased but has declined in the recent past, indicating that economic and infrastructural development does not necessarily result in increased PM2.5 concentrations. Vegetation productivity, as indicated by changes in NDVI, is demonstrated to have become more important in improving air quality, and the area of the province over which it constrains PM2.5 concentrations has increased between 2000 and 2019. Mapping of SHAP values suggests that, although the relative importance of industrial emissions has declined during the period studied, the actual area positively impacted by such emissions has actually increased. Despite developments in government policy, greater efforts to conserve energy and reduce emissions are still needed. The study further demonstrates that the combination of random forest and SHAP methods provides a valuable means to identify regional differences in key factors affecting atmospheric PM2.5 values and offers a reliable reference for pollution control strategies.