Regional joint PM2.5-O3 control policy benefits further air quality improvement and human health protection in Beijing-Tianjin-Hebei and its surrounding areas

Characteristics and Health Risks of Trace Metals in PM2.5 Before and During the Heating Period over Three Years in Shijiazhuang, China

To explore the characteristics of PM2.5 and assess the health risks to residents in Shijiazhuang before and during the heating period in 2019, 2020 and 2021, the hourly concentrations of PM2.5 and its nine selected trace elements were determined. The results showed that the mass concentrations of PM2.5 were 80.32 ± 50.21 μg m-3 (2019), 69.97 ± 41.91 μg m-3 (2020) and 58.70 ± 41.97 μg m-3 (2021) during the heating period, representing greatly improved air quality. The PM2.5 levels in the heating period were 1.04~1.60 times greater than those before the heating period, while the total selected trace element concentrations were about 1.44~1.97 times higher, indicating that strict control for PM2.5 in the heating period should be imposed. The overall hazard quotient (HQ) of the nine selected trace elements in the heating period were 1.08~1.42 times higher than those before the heating period, while the total cancer risks (CR) were decreased by 29.04% (2020) and 3.50% (2021). There were high health risks not only in local areas, but also in the south of Hebei, the north of Henan, and southern and central Shanxi. The health risks increased by 1.21~2.26 times from clean levels to heavy pollution levels. The leading element of HQ was Mn, while the dominant elements of CR varied from As to Co. Increases in PM2.5 concentrations and HQ from before the heating period to during the heating period were observed, and there was even an inverse CR change between before the heating period and during the heating period, further identifying that air pollution control was efficient.

A modeling approach to dynamically estimating local photochemistry process and its contribution to surface O3 pollution

Ozone (O3) pollution in city level is a complex issue that arises not only from local photochemistry process but also involves mid- or long-range O3 transport. In this study, we developed a modeling approach to dynamically quantifying local photochemical process (indicated as Chem_O3) and estimating its role in surface O3 pollution in city level. The work was conducted on North BTH of China for summer of 2022 and mainly focused on the urban areas, in which surface O3 usually as the most dominant air pollutants to harm population health. The method was constructed via establishing the hourly response of locally-formed O3 to locally-released NOx (RO3-NO2, ppb·ppb-1) based on ISAM simulations and then combining RO3-NO2 and ambient NO2 levels to quantify time-varying Chem_O3. The results showed that the monthly mean of Chem_O3 and its proportion to actual O3 (Chem%) was 17.9-26.0 ppb and 46.7%-62.6% in major urban areas of North BTH, following the order of mega-city > industrialized city > normal city > forest city. Moreover, daily Chem% presented the different trend with daily O3 in these study areas, slight-positive for mega-cities, but moderate or strong-negative for most other cities. Specially, our developed method could additionally disentangling O3 physical transport among the studied cities, and we found the inflow of O3 was much lower than the outflow of O3 for two mega-cities, while it was opposite in other cities. We think this method could clearly point out the role of local photochemistry control in O3 reduction, which could help city environment managers to develop scientific and effective policy strategies to cope with ozone-related problems.

Related health burden with the improvement of air quality across China

BACKGROUND

Substantial progress in air pollution control has brought considerable health benefits in China, but little is known about the spatio-temporal trends of economic burden from air pollution. This study aimed to explore their spatio-temporal features of disease burden from air pollution in China to provide policy recommendations for efficiently reducing the air pollution and related disease burden in an era of a growing economy.

METHODS

Using the Global Burden of Disease method and willingness to pay method, we estimated fine particulate matter (PM 2.5 ) and/or ozone (O 3 ) related premature mortality and its economic burden across China, and explored their spatio-temporal trends between 2005 and 2017.

RESULTS

In 2017, we estimated that the premature mortality and economic burden related to the two pollutants were RMB 0.94 million (68.49 per 100,000) and 1170.31 billion yuan (1.41% of the national gross domestic product [GDP]), respectively. From 2005 to 2017, the total premature mortality was decreasing with the air quality improvement, but the economic burden was increasing along with the economic growth. And the economic growth has contributed more to the growth of economic costs than the economic burden decrease brought by the air quality improvement. The premature mortality and economic burden from O 3 in the total loss from the two pollutants was substantially lower than that of PM 2.5 , but it was rapidly growing. The O 3 -contribution was highest in the Yangtze River Delta region, the Fen-Wei Plain region, and some western regions. The proportion of economic burden from PM 2.5 and O 3 to GDP significantly declined from 2005 to 2017 and showed a decreasing trend pattern from northeast to southwest.

CONCLUSION

The disease burden from O 3 is lower than that of PM 2.5 , the O 3 -contribution has a significantly increasing trend with the growth of economy and O 3 concentration.

Assessment of ozone pollution on rice yield reduction and economic losses in Sichuan province during 2015-2020

In recent years, there has been a significant increase in surface ozone (O3) concentrations in the troposphere. Ozone pollution has significant adverse effects on ecosystems, human health, and climate change, particularly on crop growth and yield. This study utilized the observational hourly O3 data, cumulative O3 concentration over 40 ppb per h (AOT40), and the mean daytime 7-h O3 concentration (M7) to analyze the spatiotemporal distributions of relative yield losses (RYLs) and evaluate the yield reduction and economic losses of rice in Sichuan province from 2015 to 2020. The results indicated that the average O3 concentration during the growing rice season ranged from 55.4 to 69.3 μg/m3, with the highest O3 concentration observed in 2017, and the AOT40 ranged from 4.5 to 8.7 ppm h from 2015 to 2020. At the county level, the O3 concentration, AOT40, and the relative yield loss (RYL) of rice based on AOT40 exhibited clear spatiotemporal differences in Sichuan. The RYLs of AOT40 were 4.9-9.2% from 2015 to 2020. According to AOT40 and M7 metrics, the yield loss and economic losses attributed to O3 pollution amounted to 78.75-150.36 (9.74-21.54) ten thousand tons, and 2079.08-4149.89 (257.25-594.45) million Yuan, respectively. Rice yield and economic losses were relatively large in the Chengdu Plain, southern Sichuan, and northeast Sichuan. These findings will contribute to a deeper understanding of the detrimental effects of elevated surface O3 concentrations on rice crops. It is imperative to implement more stringent O3 reduction measures aimed at lowering O3 concentrations, enhancing rice quality, and safeguarding food security in Sichuan.

Determination of major drive of ozone formation and improvement of O3 prediction in typical North China Plain based on interpretable random forest model

O3 pollution in China has become prominent in recent years, and it has become one of the most challenging issues in air pollution control. We used data on atmospheric pollutants and meteorology from 2019 to 2021 to build an interpretable random forest (RF) model, applying this model to predict O3 concentration in 2022 in five cities in the Southwest North China Plain. The model was also used to identify and explain the influence of various factors on O3 formation. The correlation coefficient R2 between the predicted O3 concentration and observed O3 concentration was 0.82, the MAE was 15.15 μg/m3, and the RMSE was 20.29 μg/m3, indicating that the model can effectively predict O3 concentration in the studying area. The results of correlation analysis, feature importance, and the driving factor analysis from SHapley Additive exPlanations (SHAP) model indicated that temperature (T), NO2, and relative humidity (RH) are the top three features affecting O3 prediction, while the weights of wind speed and wind direction were relatively low. Thus, O3 in the southwestern North China Plain may mainly come from the formation of local photochemical activities. The dominant factors behind O3 also varied in different seasons. In spring and autumn, O3 pollution is more likely to occur under high NO2 concentration and high-temperature conditions, while in summer, it is more likely to occur under high-temperature and precipitation-free weather. In winter, NO2 is the dominant factor in O3 formation. Finally, the interpretable RF model is used to predict future O3 concentration based on features provided by Community Multiscale Air Quality (CMAQ) and Weather Research & Forecast (WRF) model, and the simulation performance of CMAQ on O3 concentration is enhanced to a certain extent, improving the prediction of future O3 pollution situations and guiding pollution control.

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.

High-resolution estimation of near-surface ozone concentration and population exposure risk in China

Considering the spatial and temporal effects of atmospheric pollutants, using the geographically and temporally weighted regression and geo-intelligent random forest (GTWR-GeoiRF) model and Sentinel-5P satellite remote sensing data, combined with meteorological, emission inventory, site observation, population, elevation, and other data, the high-precision ozone concentration and its spatiotemporal distribution near the ground in China from March 2020 to February 2021 were estimated. On this basis, the pollution status, near-surface ozone concentration, and population exposure risk were analyzed. The findings demonstrate that the estimation outcomes of the GTWR-GeoiRF model have high precision, and the precision of the estimation results is higher compared with that of the non-hybrid model. The downscaling method enhances estimation results to some extent while addressing the issue of limited spatial resolution in some data. China's near-surface ozone concentration distribution in space shows obvious regional and seasonal characteristics. The eastern region has the highest ozone concentrations and the lowest in the northeastern region, and the wintertime low is higher than the summertime high. There are significant differences in ozone population exposure risks, with the highest exposure risks being found in China's eastern region, with population exposure risks mostly ranging from 0.8 to 5.

Impact of spatial scales of control measures on the effectiveness of ozone pollution mitigation in eastern China

Ozone (O3) pollution is becoming the primary air pollution issue with the large decrease in fine particulate concentrations in eastern China. The development of widely recognized policies for controlling O3 pollution episodes is urgent. This study aims to provide actionable and comprehensive suggestions for O3 control policy development, with an emphasis on the precursor emission reductions. Here, we compared the impacts of different spatial scale reductions on a widespread O3 pollution episode in eastern China by a state-of-the-art regional air quality model. We find that region-scale joint control (in >30 cities) is much more effective than city-scale sporadic reduction in reducing O3 concentration. Sporadic controls only reduce the maximum daily 8-h average (MDA8) O3 by ∼1 μg/m3 in the controlled city, whereas regional controls lead to a MDA8 O3 decrease of ∼8 μg/m3 in the controlled region. In addition, the emission reduction effectiveness increased by 2.6 times from <5 cities to >30 cities. Continuous reductions have a cumulative effect on the decrease of MDA8 O3, showing the strongest effects within 24 h and diminishing after 48 h, which underscores the importance of reducing emissions 24 h prior to an episode. Moreover, the effect of control measures on MDA8 O3 varies spatially depending on the ratio of volatile organic compounds (VOCs) to nitrogen oxides (NOx) (VOCs/NOx). Both the reductions of VOC and NOx emissions have a positive effect on the decrease of MDA8 O3 in summer, but the effects of VOC reductions are 1.2 to 1.7 times higher than those of NOx reductions. The residential sector, due to its high VOCs/NOx emission ratio, exhibits the highest efficiency in the reduction of O3 concentrations. Our results highlight the importance of regional joint control and synergistic reduction of VOCs and NOx in eastern China.

Quantifying the scale-dependent relationships of PM2.5 and O3 on meteorological factors and their influencing factors in the Beijing-Tianjin-Hebei region and surrounding areas

To investigate the variations of PM2.5 and O3 and their synergistic effects with influencing factors at different time scales, we employed Bayesian estimator of abrupt seasonal and trend change to analyze the nonlinear variation process of PM2.5 and O3. Wavelet coherence and multiple wavelet coherence were utilized to quantify the coupling oscillation relationships of PM2.5 and O3 on single/multiple meteorological factors in the time-frequency domain. Furthermore, we combined this analysis with the partial wavelet coherence to quantitatively evaluate the influence of atmospheric teleconnection factors on the response relationships. The results obtained from this comprehensive analysis are as follows: (1) The seasonal component of PM2.5 exhibited a change point, which was most likely to occur in January 2017. The trend component showed a discontinuous decline and had a change point, which was most likely to appear in February 2017. The seasonal component of O3 did not exhibit a change point, while the trend component showed a discontinuous rise with two change points, which were most likely to occur in July 2018 and May 2017. (2) The phase and coherence relationships of PM2.5 and O3 on meteorological factors varied across different time scales. Stable phase relationships were observed on both small- and large-time scales, whereas no stable phase relationship was formed on medium scales. On all-time scales, sunshine duration was the best single variable for explaining PM2.5 variations and precipitation was the best single variable explaining O3 variations. When compared to single meteorological factors, the combination of multiple meteorological factors significantly improved the ability to explain variations in PM2.5 and O3 on small-time scales. (3) Atmospheric teleconnection factors were important driving factors affecting the response relationships of PM2.5 and O3 on meteorological factors and they had greater impact on the relationship at medium-time scales compared to small- and large-time scales.

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.