Spatiotemporal patterns of surface ozone exposure inequality in China.

Rising surface ozone (O3) levels in China are increasingly emphasizing the potential threats to public health, ecological balance, and economic sustainability. Using a 1 km × 1 km dataset of O3 concentrations, this research employs subpopulation demographic data combined with a population-weighted quality model. Its aim is to evaluate quantitatively the differences in O3 exposure among various subpopulations within China, both at a provincial and urban cluster level. Additionally, an exposure disparity indicator was devised to establish unambiguous exposure risks among significant urban agglomerations at varying O3 concentration levels. The findings reveal that as of 2018, the population-weighted average concentration of O3 for all subgroups has experienced a significant uptick, surpassing the average O3 concentration (118 µg/m3). Notably, the middle-aged demographic exhibited the highest O3 exposure level at 135.7 µg/m3, which is significantly elevated compared to other age brackets. Concurrently, there exists a prominent positive correlation between educational attainment and O3 exposure levels, with the medium-income bracket showing the greatest susceptibility to O3 exposure risks. From an industrial vantage point, the secondary sector demographic is the most adversely impacted by O3 exposure. In terms of urban-rural structure, urban groups in all regions had higher levels of exposure to O3 than rural areas, with North and East China having the most significant levels of exposure. These findings not only emphasize the intricate interplay between public health and environmental justice but further highlight the indispensability of segmented subgroup strategies in environmental health risk assessment. Moreover, this research furnishes invaluable scientific groundwork for crafting targeted public health interventions and sustainable air quality management policies.

Intricate synergistic effects between air pollution and carbon emission: An emerging evidence from China.

Due to global climate change and intensifying anthropogenic pollution, China confronts the dual challenge of controlling particulate matter 2.5 µm (PM2.5) pollution and reducing carbon emissions. Quantifying the characteristics of PM2.5 concentrations and CO2 emissions, as well as identifying the driving factors and synergistic effects of PM2.5 reduction and CO2 mitigation, are crucial steps in promoting sustainable urban development and achieving the Sustainable Development Goals (SDGs) in China. In this study, we selected 168 cities as our case-study, and quantified spatial characteristics of PM2.5 concentrations and CO2 emissions from 2015 to 2020 in China. Then we analyzed driving factors affecting the spatial heterogeneity of PM2.5 reduction and CO2 mitigation applying Multi-scale Geographically Weighted Regression (MGWR) model. By employing coupling coordination degree (CCD) model, we further detected the spatiotemporal evolution patterns of the synergistic effects between PM2.5 reduction and CO2 mitigation in key Chinese cities. The result showed that: (a) From 2015 to 2020, PM2.5 concentrations experienced a significant reduction from 59.78 µg/m3 to 49.83 µg/m3, while CO2 emissions increased from 44.88 × 106 t in 2015 to 45.77 × 106 t in 2020; (b) Green economy efficiency (gee), government attention (gover), and environmental regulation (envir) demonstrate the most pronounced synergistic effect on pollution reduction and carbon mitigation, with the drivers exhibiting obvious spatial heterogeneity; (c) The overall coupling coordination level of PM2.5 pollution and CO2 emissions in China dropped from 0.49 in 2015 to 0.46 in 2020, and the coupling coordination grade in northern cities was notably higher than that in southern cities. The result enhances our understanding of spatiotemporal patterns of synergistic effects between PM2.5 reduction and CO2 mitigation, and provides the theoretical basis for policy decision-making to realize pollution decrease and carbon neutral and regional environment governance.

Policy implications for synergistic management of PM2.5 and O3 pollution from a pattern-process-sustainability perspective in China.

In recent years, the pattern of air pollution in China has changed profoundly, and PM2.5 and surface ozone (O3) have become the main air pollutants affecting the air quality of cities and regions in China. The synergistic control of the two has become the key to the sustainable improvement of air quality in China. In this study, we investigated and analyzed the spatial and temporal distribution patterns, exposure health risks, key drivers, and sustainable characteristics of PM2.5 and O3 concentrations in China from 2013 to 2022 at the national and city cluster scales by combining methodological models such as spatial statistics, trend analysis, exposure-response function, Hurst index, and multi-scale geographically weighted regression (MGWR) model. Ultimately, a synergistic management system for PM2.5 and O3 pollution was proposed. The results showed that: (1) The PM2.5 concentration decreased at a rate of 1.45 µg/m3 per year (p < 0.05), while the O3 concentration increased at a rate of 2.54 µg/m3 per year (p < 0.05). The trends of the two concentrations showed significant differences in spatial distribution. (2) Population exposure risks to pollutants showed an increasing trend, with PM2.5 and O3 increasing by 55.1 % and 42.7 %, respectively. The annual deaths associated with exposure to PM2.5 and O3 demonstrated a decreasing and inverted U-shaped trend, respectively, with annual average deaths of 1.312 million and 98,000. Significant regional disparities in health risks from these pollutants were influenced by socio-economic factors such as industrial activities and population density. In the future, it is expected that more than half of China's regions will be exposed to rising risks of PM2.5 and O3 population exposure. (3) Key drivers of regional exacerbation in PM2.5 and O3 levels include the number of industrial enterprises above designated size (NSIE) and population agglomeration (PA), while the disposable income of urban residents (URDI), technological innovation (TI), and government attention level (GAL) emerged as primary factors in controlling pollution hotspots, ranked in order of influence from greatest to least as TI > GAL > URDI. Overall, this study sheds light on the current status of air pollution and health risk sustainability in China and enhances the understanding of future air pollution dynamics in China. The results of the study may help to develop effective targeted control measures to synergize the management of PM2.5 and O3 in different regions.

Toward Better and Healthier Air Quality: Global PM2.5 and O3 Pollution Status and Risk Assessment Based on the New WHO Air Quality Guidelines for 2021.

To reduce the high burden of disease caused by air pollution, the World Health Organization (WHO) released new Air Quality Guidelines (AQG) on September 22, 2021. In this study, the daily fine particulate matter (PM2.5) and surface ozone (O3) data of 618 cities around the world is collected from 2019 to 2022. Based on the new AQG, the number of attainment days for daily average concentrations of PM2.5 (≤ 15 µg m-3) and O3 (≤ 100 µg m-3) is approximately 10% and 90%, respectively. China and India exhibit a decreasing trend in the number of highly polluted days (> 75 µg m-3) for PM. Every year over 68% and 27% of cities in the world are exposed to harmful PM2.5 (> 35 µg m-3) and O3 (> 100 µg m-3) pollution, respectively. Combined with the United Nations Sustainable Development Goals (SDGs), it is found that more than 35% of the world's cities face PM2.5-O3 compound pollution. Furthermore, the exposure risks in these cities (China, India, etc.) are mainly categorized as "High Risk", "Risk", and "Stabilization". In contrast, economically developed cities are mainly categorized as "High Safety", "Safety", and "Deep Stabilization." These findings indicate that global implementation of the WHO's new AQG will minimize the inequitable exposure risk from air pollution.

Black carbon pollution in China from 2001 to 2019: Patterns, trends, and drivers.

Based on a near real-time 10 km × 10 km resolution black carbon (BC) concentration dataset, this study investigated the spatial patterns, trend variations, and drivers of BC concentrations in China from 2001 to 2019 with spatial analysis, trend analysis, hotspot clustering, and multiscale geographically weighted regression (MGWR). The results indicate that Beijing-Tianjin-Hebei, the Chengdu-Chongqing agglomeration, Pearl River Delta, and East China Plain were the hotspot centers of BC concentration in China. From 2001 to 2019, the average rate of decline in BC concentrations across China was 0.36 µg/m3/year (p < 0.001), with BC concentrations peaking around 2006 and sustaining a decline for the next decade or so. The rate of BC decline was higher in Central, North, and East China than in other regions. The MGWR model revealed the spatial heterogeneity of the influences of different drivers. A number of enterprises had significant effects on BC in East, North, and Southwest China; coal production had strong effects on BC in Southwest and East China; electricity consumption had better effects on BC in Northeast, Northwest, and East China than in other regions; the ratio of secondary industries had the greatest effects on BC in North and Southwest China; and CO2 emissions had the strongest effects on BC in East and North China. Meanwhile, the reduction of BC emissions from the industrial sector was the dominant factor in the decrease of BC concentration in China. These findings provide references and policy prescriptions for how cities in different regions can reduce BC emissions.