Analysis of the air pollution reduction and climate change mitigation effects of the Three-Year Action Plan for Blue Skies on the "2+26" Cities in China

Machine learning analysis of socioeconomic drivers in urban ozone pollution in Chinese cities

The escalation of ground-level ozone (O3) pollution presents a significant challenge to the sustainable growth of Chinese cities. This study utilizes advanced machine learning algorithms to investigate the intricate interplay between urban socioeconomic growth and O3 levels. Surpassing traditional environmental chemistry, it assesses the effectiveness of these algorithms in interpreting socioeconomic and environmental data, while elucidating urban development's environmental impacts from a novel socioeconomic perspective. Key findings indicate that factors such as urban infrastructure, industrial activities, and demographic dynamics significantly influence O3 pollution. The study highlights the particular sensitivity of urban public transportation and population density, each exerting a unique and substantial effect on O3 levels. Additionally, the research identifies nuanced interactions among these factors, indicating a complex web of influences on urban O3 pollution. These interactions suggest that the impact of individual socioeconomic elements on O3 pollution is interdependent, being either amplified or mitigated by other factors. The study emphasizes the crucial need to integrate socioeconomic variables into urban O3 pollution strategies, advocating for policies tailored to each city's distinct characteristics, informed by the detailed analysis provided by machine learning. This approach is essential for developing effective and nuanced urban pollution management strategies.

Development of a greenhouse gas - air pollution interactions and synergies model for Korea (GAINS-Korea)

This study aimed to create Greenhouse Gas - Air Pollution Interactions and Synergies (GAINS)-Korea, an integrated model for evaluating climate and air quality policies in Korea, modeled after the international GAINS model. GAINS-Korea incorporates specific Korean data and enhances granularity for enabling local government-level analysis. The model includes source-receptor matrices used to simulate pollutant dispersion in Korea, generated through CAMx air quality modeling. GAINS-Korea's performance was evaluated by examining different scenarios for South Korea. The business as usual scenario projected emissions from 2010 to 2030, while the air quality scenario included policies to reduce air pollutants in line with air quality and greenhouse gas control plans. The maximum feasible reduction scenario incorporated more aggressive reduction technologies along with air quality measures. The developed model enabled the assessment of emission reduction effects by both greenhouse gas and air pollutant emission reduction policies across 17 local governments in Korea, including changes in PM2.5 (particulate matter less than 2.5 μm) concentration and associated benefits, such as reduced premature deaths. The model also provides a range of visualization tools for comparative analysis among different scenarios, making it a valuable resource for policy planning and evaluation, and supporting decision-making processes.

Multiscale levels CO2 decouple reinforcement in China

Decoupling economic growth from CO2 emissions is imperative for China. Meanwhile, establishing a consistent and comprehensive decoupling inventory that includes national (N), regional and provincial (RP), and city and county (CC) levels is essential for further policy formulation. This research aims to investigate the decoupling status using the "N-RP-CC" approach while considering changes in decoupling trends at the different levels. A combination of the Tapio decoupling model and cluster analysis is employed to study the decoupling's spatiotemporal characteristics and trends. The study first calculates the decoupling value for "national, 7; regions, 30; provinces, 1501 CCs" in China, 2006-2017. The results show that there continues to be an improvement in the decoupling trend at the national level. Conversely, the regional scale exhibits a more vulnerable decoupling trend compared to the national level, with weak and extended negative decoupling observed in northeastern and northern China. Moreover, provincial heterogeneities are increasingly evident, with poor decoupling statuses appearing in Jilin, Heilongjiang, Liaoning, and Xinjiang, as well as many central provinces. Additionally, although more than half of CCs exhibit weak decoupling during most years, seven different states of decoupling were also identified during the time frame. These findings further indicate that spatiotemporal heterogeneities extend beyond RP scales within CCs. Taking the Yangtze River as a boundary line reveals a severe situation in northern areas along with rapid development trends observed in southern regions. Finally, we clustered 1414 CCs based on their industrial proportions for 2017 which further highlights increasingly prominent heterogeneities that should be carefully considered. Based on these findings, policy recommendations such as spatial organization and optimization and technique investment are proposed to achieve CO2 emission decoupling under the N-RP-CC levels.

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.

Observation of black carbon in Northern China in winter of 2018-2020 and its implications for black carbon mitigation

Enhanced observations of BC in hotspot regions with a high temporal resolution are critical to refining our BC mitigation strategies, which are co-directed by air-quality and climate goals. In this work, the temporal variation and emission sources of BC in Shijiazhuang, Northern China, during the winter of 2018-2020 were investigated on the basis of multi-wavelength Aethalometer BC observations. The average BC concentrations decreased from 9.13 ± 6.63 μg/m³ in the winter of 2018 to 3.51 ± 2.48 μg/m³ in the winter of 2020. The BC source attributions derived from the Aethalometer model showed that the BC concentrations in Shijiazhuang in the winter of 2018 were mainly contributed by biomass burning (53 %). In contrast, during the winter of 2019 and 2020, fossil fuel combustion (BC_ff) exhibited higher contributions, and higher BC concentrations attributed to greater BC_ff contributions. Potential source contribution function (PSCF) analysis suggested that local emissions in Shijiazhuang and transport from highly industrialized regions like central Shanxi and southern Hebei contributed significantly to BC in Shijiazhuang. Concentration weighted trajectory (CWT) analysis revealed that the BC contributions from source regions decreased successively from the winter of 2018 to the winter of 2020. Our results also implied an air quality/climate co-benefit effect of enforcing multi-scale air-quality improvement regulations. Yet, it is still worth noting that some of the measures in favor of reducing BC emissions contradict the measures for reducing CO₂. The synergies of BC to air quality and climate should be considered and addressed by policymakers with the aim of realizing a sustainable environment.

Driving forces and relationship between air pollution and economic growth based on EKC hypothesis and STIRPAT model: evidence from Henan Province, China

The aim of this research is to analyze the main influencing factors and relationship between atmospheric environment and economic society. Using the panel data of 18 cities in Henan Province from 2006 to 2020, this paper employed some advanced econometric estimation included entropy method, extended environmental Kuznets curve (EKC) and STIRPAT model to conduct empirical estimations. The results show that most regions in Henan Province have verified the existence of the EKC hypothesis; and the peak of air pollution level in all cities of Henan Province generally occurred in around 2014. Multiple linear Ridge regression indicated that the positive driving forces of air pollution in most cities in Henan Province are industrial structure and population size; the negative driving forces are urbanization level, technical level and greening degree. Finally, we used the grey GM (1, 1) model to predict the atmospheric environment of Henan Province in 2025, 2030, 2035 and 2040. What should pay close attention to is that air pollution levels in northeastern and central Henan Province will continue to remain high.

Driving Forces of Meteorology and Emission Changes on Surface Ozone in the Huaihe River Basin, China

Surface ozone (O3) pollution in China has become a serious environmental problem in recent years. In the present study, we targeted the HRB, a large region located in China's north-south border zone, to assess the driving forces of meteorology and emission changes on surface ozone. A Kolmogorov-Zurbenko (KZ) filter method was performed on the maximum daily average 8-h (MDA8) concentrations of ozone in the HRB during 2015-2020 to decompose the original time series. The findings demonstrated that the short-term (O3ST), seasonal (O3SN), and long-term components (O3LT) of MDA8 O3 variations accounted for 34.2%, 56.1%, and 2.9% of the total variance, respectively. O3SN has the greatest influence on the daily variation in MDA8 O3, followed by O3ST. In coastal cities, the influence of O3ST was enhanced. The influence of O3SN was stronger in the northwestern HRB. Air temperature is the prevailing variable that influences the photochemical formation of ozone. A clear phase lag (7-34 days) of the baseline component between MDA8 O3 and the atmospheric temperature was found in the HRB. Using multiple linear regression, the effect of temperature on ozone was removed. We estimated that the increase in ozone concentration in the HRB was mainly caused by the emission changes (79.4%), and the meteorological conditions made a small contribution (20.6%). This study suggests that reductions in volatile organic compounds (VOCs) will play an important role in further ozone pollution reduction in the HRB.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11270-023-06345-1.

Distribution, chemical fractionation, and potential environmental risks of Hg, Cr, Cd, Pb, and As in wastes from ultra-low emission coal-fired industrial boilers in China

This study conducted a comprehensive investigation of the distribution, chemical fractionation, and potential environmental risks of Hg, Cd, Cr, Pb, and As in waste based on new data from five ultra-low emission (ULE) coal-fired industrial boilers (CFIBs). The results showed that fly ash was enriched with Cd, Pb, As, and Hg, while its Cr contents were not invariably higher than those of slag. Fly ash was the predominant output flow for Hg, Cd, Cr, Pb, and As in the tested ULE boilers, with higher proportions of HTEs in the fly ash and lower proportions of HTEs in the flue gas than in the non-ULE boilers. The average proportions of residual Hg, Cd, Cr, Pb, and As in wastes revealed the following order: slag > fly ash > flue gas desulfurization (FGD) by-products. The potential environmental risks of Hg, Cd, Cr, Pb, and As in the fly ash, slag, and FGD by-products of CFIBs at the county level in the Beijing-Tianjin-Hebei Air Pollution Transmission Channel Cities ("2 +26 cities") region showed spatial heterogeneity. It is predicted that the potential release of Pb, Cr, and Cd in the fly ash would increase and that of the FGD by-products would decrease after the implementation of the ULE retrofitting of all CFIBs.

Association analysis between socioeconomic factors and urban ozone pollution in China

Ozone pollution in China has gradually increased, attracting extensive attention. Existing studies on ozone pollution typically take environmental and chemical perspectives. As air pollution is closely related to social and economic activities, it is also important to study ozone pollution from a socioeconomic perspective. Using the association rule mining technique, we uncovered hidden patterns between ozone variance and socioeconomic factors in macro-, meso-, and micro-scenarios in 297 Chinese cities. We found that the acceleration of urbanization and industrialization has indeed aggravated urban ozone pollution. The supply of water and power resources may be a significant factor influencing urban ozone pollution. Transportation hub cities with more developed economies and industries are more likely to suffer from ozone pollution in summer and autumn. Human behavior is a critical factor influencing the weekly variance in ozone concentration during weekdays and weekends. The influence of plant-derived VOC emissions on the formation of ozone cannot be overlooked. Our results deepen the understanding of ozone pollution in Chinese cities, and we provide corresponding policy recommendations to alleviate ozone pollution and improve air quality.

Drivers and Decoupling Effects of PM2.5 Emissions in China: An Application of the Generalized Divisia Index

Although economic growth brings abundant material wealth, it is also associated with serious PM_2.5 pollution. Decoupling PM_2.5 emissions from economic development is important for China's long-term sustainable development. In this paper, the generalized Divisia index method (GDIM) is extended by introducing innovation indicators to investigate the main drivers of PM_2.5 pollution in China and its four subregions from 2008 to 2017. Afterwards, a GDIM-based decoupling index is developed to examine the decoupling states between PM_2.5 emissions and economic growth and to identify the main factors leading to decoupling. The obtained results show that: (1) Innovation input scale and GDP are the main drivers for increases in PM_2.5 emissions, while innovation input PM_2.5 intensity, emission intensity, and emission coefficient are the main reasons for reductions in PM_2.5 pollution. (2) China and its four subregions show general upward trends in the decoupling index, and their decoupling states turn from weak decoupling to strong decoupling. (3) Innovation input PM_2.5 intensity, emission intensity, and emission coefficient contribute largely to the decoupling of PM_2.5 emissions. Overall, this paper provides valuable information for mitigating haze pollution.