Impacts of the differences in PM2.5 air quality improvement on regional transport and health risk in Beijing-Tianjin-Hebei region during 2013-2017

Unveiling the health impacts of air pollution transport in China

The transport of atmospheric pollutants plays a pivotal role in regional air pollution, highlighting critical concerns over the unequal health outcomes that arise from such transport. While previous researches predominantly focused on key areas in the battle against air pollution, the intensification of control measures necessitates a national perspective to comprehend the health impacts due to pollution transport. Our study establishes an integrated assessment framework that combine an emission-concentration response surface model with a health impact evaluation model to analyse the nationwide health impacts of PM2.5 and O3 pollution transport across China's 31 provinces. We found that, interprovincial transport of PM2.5 and O3 contributed to 747,000 and 110,000 deaths respectively in 2017, which amounts to 38% and 48% of deaths caused by total anthropogenic emissions. North, East, and Central China together contribute 82% and 69% to the health impacts caused by regional PM2.5 and O3 transport respectively, and the transport among these three regions is also significant. The analysis of interprovincial health impact transport shows that, for PM2.5, the top contributors are Hebei, Shandong, Henan, Anhui, and Jiangsu, with the most affected being Henan, Shandong, Jiangsu, Hebei, and Guangdong. Regarding O3, Shandong, Hebei, Henan, Jiangsu, and Anhui contribute the most, while Henan, Shandong, Hebei, Jiangsu, and Anhui are the most affected. This study can shed lights on regional control strategies by prioritizing control areas based on the health impact of air pollution transport in China.

Fine particle trace elements at a mountain site in southern China: Source identification, transport, and health risks

Trace elements in atmospheric particulate matter play a significant role in air quality, human health, and biogeochemical cycles. In this study, the trace elements (Ca, Al, K, Fe, Na, Mg, Zn, Pb, Mn, Ti, Cu, Cr, Sr, Ni) in PM2.5 samples collected at the summit of Mt. Lushan were analyzed to quantify their abundance, source, transport, and health risks. During the whole sampling period, the major trace elements was Ca, Al, and K. While the trace metals with the lowest concentrations were Sr, Ni, Rb, and Cd. The trace elements were influenced by air mass transport routes, exhibiting an increasing trend of crustal elements in the northwesterly airmass and anthropogenic elements (Zn, Mn, Cu, and Ni) in the easterly air masses. Construction dust, coal + biomass burning, vehicle emission, urban nitrate-rich + urban waste incineration emissions, and soil dust + industry emissions were common sources of PM2.5 on Mt. Lushan. Different air mass transport routes had various source contribution patterns. These results indicate that trace elements at Mt. Lushan are influenced by regional anthropogenic emissions and monsoon-dominated trace element transport. The total resulting cancer risk value that these elements posed were below the acceptable risk value of 1 × 10-6, while the non-carcinogenic risk value (1.72) was higher than the safety level, suggesting that non-carcinogenic effects due to these trace elements inhalation were likely to occur. Vehicle emission and coal + biomass burning were the common dominant sources of non-cancer risks posed by trace elements at Mt. Lushan.

Modeling of secondary organic aerosols (SOA) based on two commonly used air quality models in China: Consistent S/IVOCs contribution but large differences in SOA aging

Secondary organic aerosol (SOA) is an important component of atmospheric fine particulate matter (PM2.5), with contributions from anthropogenic and biogenic volatile organic compounds (AVOC and BVOC) and semi- (SVOC) and intermediate volatility organic compounds (IVOC). Policymakers need to know which SOA precursors are important but accurate simulation of SOA magnitude and contributions remain uncertain. Findings from existing SOA modeling studies have many inconsistencies due to differing emission inventory methodologies/assumptions, air quality model (AQM) algorithms, and other aspects of study methodologies. To address some of the inconsistencies, we investigated the role of different AQM SOA algorithms by applying two commonly used models, CAMx and CMAQ, with consistent emission inventories to simulate SOA concentrations and contributions for July and November 2018 in China. Both models have a volatility basis set (VBS) SOA algorithm but with different parameters and treatments of SOA photochemical aging. SOA generated from BVOC (i.e., BSOA) is found to be more important in southern China. In contrast, SOA generated from anthropogenic precursors is more prevalent in the North China Plain (NCP), Yangtze River Delta (YRD), Sichuan Basin and Central China. Both models indicate negligible SOA formation from SVOC emissions compared to other precursors. In July, when BVOC emissions are abundant, SOA is predominantly contributed by BSOA (except for NCP), followed by IVOC-SOA (i.e., SOA produced from IVOC) and ASOA (i.e., SOA produced from anthropogenic VOC). In contrast, in November, IVOC became the leading SOA contributor for all selected regions except PRD, illustrating the important contribution of IVOC emissions to SOA formation. While both models generally agree in terms of the spatial distributions and seasonal variations of different SOA components, CMAQ tends to predict higher BSOA, while CAMx generates higher ASOA concentrations. As a result, CMAQ results suggest that BSOA concentration is always higher than ASOA in November, while CAMx emphasizes the importance of ASOA. Utilizing a conceptual model, we found that different treatment of SOA aging between the two models is a major cause of differences in simulated ASOA concentrations. The step-wise SOA aging scheme implemented in the CAMx VBS (based on gas-phase reactions with OH radical and similar to other models) exhibits a strong enhancement effect on simulated ASOA concentrations, and this effect increases with the ambient organic aerosol (OA) concentrations. The CMAQ aerosol module implements a different SOA aging scheme that represents particle-phase oligomerization and has smaller impacts on total OA. Different structures and/or parameters of the SOA aging schemes are being used in current models, which could greatly affect model simulations of OA in ways that are difficult to anticipate. Our results indicate that future control policies should aim at reducing IVOC emissions as well as traditional VOC emissions. In addition, aging schemes are the major driver in CMAQ vs. CAMx treatments of ASOA and their resulting predicted mass. More sophisticated measurement data (e.g., with resolved OA components) and/or chamber experiments (e.g., investigating how aging influences SOA yields) are needed to better characterize SOA aging and constrain model parameterizations.

Health burden evaluation of industrial parks caused by PM2.5 pollution at city scale

Industrial park is an important emission sector of PM2.5 pollution. Previous studies have provided valuable information on the impact of PM2.5 from industrial parks on human health, but relevant studies at city scale are limited. In this study, the health burden of industrial parks was evaluated based on PM2.5-related premature deaths and economic contributions. The premature deaths were calculated in terms of a novel research model by integrating the Bayesian maximum entropy (BME) model, weighted concentration-weighted trajectory (WCWT), and integrated exposure-response function (IER). Take Tianjin City for example, it was found that since the main diffusion direction of PM2.5 in Tianjin is from south to north, the industrial parks in the south of Tianjin and close to the central city with high population density have high health burden. These industrial parks need to be focused on or even relocated in the future. The research model can provide scientific basis for the health burden evaluation of industrial parks at city scale, so as to help local governments optimize the layout of industrial parks and formulate environmental responsibility management policies for industrial parks.

Effects of air pollution control policies on intracerebral hemorrhage mortality among residents in Tianjin, China

BACKGROUND

Exposure to air pollution is an important risk factor for intracerebral hemorrhage (ICH), which is a major cause of death worldwide. However, the relationship between ICH mortality and air quality improvement has been poorly studied. This study aims to evaluate the impact of the air pollution control policies in the Beijing-Tianjin-Hebei region on ICH mortality among Tianjin residents.

METHODS

This study used an interrupted time series analysis. We fitted autoregressive integrated moving average (ARIMA) models to assess the changes in ICH deaths before and after the interventions of air pollution control policies based on the data of ICH deaths in Tianjin collected by the Tianjin Center for Disease Control and Prevention.

RESULTS

Between 2009 and 2020, there were 63,944 ICH deaths in Tianjin, and there was an overall decreasing trend in ICH mortality. The intervention conducted in June 2014 resulted in a statistically significant (p = 0.03) long-term trend change, reducing the number of deaths from ICH by 0.69 (95% confidence interval [CI]: -1.30 to -0.07) per month. The intervention in October 2017 resulted in a statistically significant (p = 0.04) immediate decrease of 25.74 (95% CI: -50.62 to -0.85) deaths from ICH in that month. The intervention in December 2017 caused a statistically significant (p = 0.04) immediate reduction of 26.58 (95% CI: -52.02 to -1.14) deaths from ICH in that month. The intervention in March 2018 resulted in a statistically significant (p = 0.02) immediate decrease of 30.40 (95% CI: -56.41 to -4.40) deaths from ICH in that month. No significant differences were observed in the changes of male ICH mortality after any of the four interventions. However, female ICH deaths showed statistically significant long-term trend change after the intervention in June 2014 and immediate changes after the interventions in December 2017 and March 2018. Overall, the interventions prevented an estimated 5984.76 deaths due to ICH.

CONCLUSION

During the study period, some interventions of air pollution control policies were significantly associated with the reductions in the number of deaths from ICH among residents in Tianjin. ICH survivors and females were more sensitive to the protective effects of the interventions. Interventions for air pollution control can achieve public health gains in cities with high levels of air pollution.

Contributors to reductions of PM2.5-bound heavy metal concentrations and health risks in a Chinese megacity during 2013, 2016 and 2019: An advanced method to quantify source-specific risks from various directions

PM_2.5-bound heavy metals were measured in a Chinese megacity (Tianjin) in 2013, 2016 and 2019, and analyzed by a new RSDA method (source directional apportionment of risks). Through combining the receptor model, cluster analysis of back trajectories, and risk assessment, the RSDA was developed in this work to quantify source-specific risks from each direction. Concentrations of PM_2.5 and most species (especially for heavy metals) underwent various reductions, and the incremental lifetime cancer risk (ILCR) and non-cancer risk (HQ) declined by more than 80% from 2013 to 2019. Pb was the highest contributor to the reduction of HMs mass concentration (58.6%), while Cr (85.5% for cancer risk) and As (26.0% for non-cancer risk) were more prominent for the reduction of HM risks. The coal combustion and industrial emissions were vital contributors to the reduction of both PM_2.5 mass concentrations (contributed 34.0% and 7.8% to the reduction respectively) and health risks (contributed 36.1% and 25.7% to the cancer risk reduction respectively). Although the percentage mass contribution of traffic emissions increased (7.7% in 2013 and 21.9% in 2019), the associated risks decreased (contributed 26.8% to the cancer risk reduction). Furthermore, the results of RSDA consistently implied that coal combustion, industrial emissions and traffic emissions controls in the northeast/north-northeast, south and southwest of the studied area played important roles in the risk reductions, which mainly due to the risk reduction of air masses from NE/NNE, S and SW, and their strong influence to Tianjin. The RSDA method can quantify the health risks from different sources and directions, and the evaluation of contributors to the reductions of risks in this work would provide a meaningful reference for policy maker to control PM_2.5 emissions and protect population health.

Spatiotemporal characteristics of air pollution in Chengdu-Chongqing urban agglomeration (CCUA) in Southwest, China: 2015-2021

Studying the spatiotemporal characteristics of air pollutants in urban agglomerations and their response factors will help to improve the quality of urban living. In combining air quality monitoring data and wavelet analysis from the Chengdu-Chongqing urban agglomeration (CCUA), this study assessed the spatiotemporal distribution characteristics and influential factors of air pollutants on daily, monthly and annual scales. The results showed that the concentration of air pollutants in the CCUA has decreased year by year, and air quality has improved. Except for O₃, pollutants in autumn and winter were higher than those in summer. The spatial distribution of air pollutants was obvious distributed in Chengdu, Chongqing, Zigong and Dazhou. Pollution incidents were mainly concentrated in winter. The 6 air pollutants and air quality index (AQI) have dominant periods on multiple time scales. AQI showed positive coherence with PM_2.5 and PM₁₀ on multiple time scales, and obvious positive coherence with SO₂, CO, NO₂ and O₃ in the short term scale. AQI was not strongly correlated with the fire point, but exhibited obvious negative coherence in the long term scale. In addition, AQI showed an obvious positive correlation with temperature and sunshine hours in short term, and a clear negative correlation with humidity and rainfall. The research results of this paper will provide a reference for pollution prevention and control in the CCUA.

Changes in Air Quality and Drivers for the Heavy PM2.5 Pollution on the North China Plain Pre- to Post-COVID-19

Under the clean air action plans and the lockdown to constrain the coronavirus disease 2019 (COVID-19), the air quality improved significantly. However, fine particulate matter (PM2.5) pollution still occurred on the North China Plain (NCP). This study analyzed the variations of PM2.5, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) during 2017-2021 on the northern (Beijing) and southern (Henan) edges of the NCP. Furthermore, the drivers for the PM2.5 pollution episodes pre- to post-COVID-19 in Beijing and Henan were explored by combining air pollutant and meteorological datasets and the weighted potential source contribution function. Results showed air quality generally improved during 2017-2021, except for a slight rebound (3.6%) in NO2 concentration in 2021 in Beijing. Notably, the O3 concentration began to decrease significantly in 2020. The COVID-19 lockdown resulted in a sharp drop in the concentrations of PM2.5, NO2, SO2, and CO in February of 2020, but PM2.5 and CO in Beijing exhibited a delayed decrease in March. For Beijing, the PM2.5 pollution was driven by the initial regional transport and later secondary formation under adverse meteorology. For Henan, the PM2.5 pollution was driven by the primary emissions under the persistent high humidity and stable atmospheric conditions, superimposing small-scale regional transport. Low wind speed, shallow boundary layer, and high humidity are major drivers of heavy PM2.5 pollution. These results provide an important reference for setting mitigation measures not only for the NCP but for the entire world.