Assessing the health impacts attributable to PM2.5 and ozone pollution in 338 Chinese cities from 2015 to 2020

Spatio-temporal distribution and source contributions of the ambient pollutants in Lucknow city, India

Clean air is imperative to the survival of all life forms on the planet. However, recent times have witnessed enormous escalation in urban pollution levels. It is therefore, incumbent upon us to decipher measures to deal with it. In perspective, the present study was carried out to assess PM10 and PM2.5 loading, metallic constituents, gaseous pollutants, source contributions, health impact and noise level of nine-locations, grouped as residential, commercial, and industrial in Lucknow city for 2019-21. Mean concentrations during pre-monsoon for PM10, PM2.5, SO2 and NO2 were: 138.2 ± 35.2, 69.1 ± 13.6, 8.5 ± 3.3 and 32.3 ± 7.4 µg/m3, respectively, whereas post-monsoon concentrations were 143.0 ± 33.3, 74.6 ± 14.5, 12.5 ± 2.1, and 35.5 ± 6.3 µg/m3, respectively. Exceedance percentage of pre-monsoon PM10 over National Ambient Air Quality Standards (NAAQS) was 38.2% while that for post-monsoon was 43.0%; whereas corresponding values for PM2.5 were 15.2% and 24.3%. Post-monsoon season showed higher particulate loading owing to wintertime inversion and high humidity conditions. Order of elements associated with PM2.5 is Co < Cd < Cr < Ni < V < Be < Mo < Mn < Ti < Cu < Pb < Se < Sr < Li < B < As < Ba < Mg < Al < Zn < Ca < Fe < K < Na and that with PM10 is Co < Cd < Ni < Cr < V < Ti < Be < Mo < Cu < Pb < Se < Sr < Li < B < As < Mn < Ba < Mg < Al < Fe < Zn < K < Na < Ca. WHO AIRQ + ascertained 1654, 144 and 1100 attributable cases per 0.1 million of population to PM10 exposure in 2019-21. Source apportionment was carried out using USEPA-PMF and resolved 6 sources with highest percent contributions including road dust re-entrainment, biomass burning and vehicular emission. It is observed that residents of Lucknow city regularly face exposure to particulate pollutants and associated constituents making it imperative to develop pollution abetment strategies.

Relationship between ozone and air temperature in future conditions: A case study in sichuan basin, China

The Sichuan Basin (SCB) is located in southwestern China and has a unique topography where ozone (O3) pollution is frequent during summer. Few studies have clarified the relationship between O3 and air temperature in SCB. Here, the SCB was divided into four major urban agglomerations. The weather research and forecasting model-community multiscale air quality model (WRF-CMAQ) was used to analyze the meteorology, spatial distribution characteristics of pollutants, and interactions among the urban agglomerations in the SCB. WRF-CMAQ was used to study the historical changes in the climate penalty factor (CPF) from 2015 to 2020 and the climate pathways under the SSP2-4.5 CPF in values in 2030 for the ambitious pollution NDC-goal scenario (NDC) and current-goals scenario (Current). The results show that the SCB is warmer in the summer months with prevailing northeasterly winds. Ozone accumulated in the western part of the SCB, and a high CPF of O3 concentration was most prominent in NW urban agglomeration, where the O3 concentration increased by 4.12-5.40 ppb for every 1 °C increase in air temperature. The observed CPF in the SCB in 2020 averaged 3.64 ppb/°C. The average CPF in the SCB in 2030 was 1.152 ppb/°C under the NDC scenario and 1.269 ppb/°C under the current scenario. This study is critical for understanding the relationship between O3 concentration and air temperature in China.

Characterization of summertime single aerosol particles in Chengdu (China): Interannual evolution and impact of COVID-19 lockdown

To investigate the interannual evolution of air pollution in summer and the impact of the COVID-19 lockdown on local pollution in Chengdu, China, single aerosol particles were continuously measured in three summer periods: the regular period in 2020 (RP2020); the regular period in 2022 (RP2022); and the lockdown period in 2022 (LP2022). It was found that, from RP2020 to RP2022, the mass concentrations of PM2.5, PM10, SO2 and NO2 decreased by 25.6 %, 24.7 %, 28.8 % and 38.5 %, respectively, while the concentration of O3 increased by 11.0 %. Affected by regional transport, there was no significant decrease in the concentrations of various pollutants during LP2022. All single aerosol particles could be classified into seven categories: vehicle emissions (VE), dust, biomass burning (BB), coal combustion (CC), K mixed with sulfate (KSO4), K mixed with nitrate (KNO3) and K mixed with sulfate and nitrate (KSN) particles. From RP2020 to RP2022, the contributions of BB and CC particles decreased by 12.1 % and 0.9 %, respectively, while VE and dust particles increased by 3.6 % and 2.5 %, respectively; and compared to RP2022, the contributions of VE, dust and CC particles in LP2022 decreased by 22.2 %, 11.0 % and 12.7 %, respectively. The high PM2.5 pollution events in RP2020 and RP2022 were mainly caused by combustion sources (BB and CC, 51.6 %) and VE (38.3 %) particles, respectively, while the pollution event in LP2022 was contributed by BB (27.0 %) and secondary inorganic (KSO4, KNO3 and KSN, 60.2 %) particles. The formation mechanisms of different pollution events were further validated by WRF-Chem results. Although the potential source areas of particles showed a shrinking trend from RP2020 to RP2022, regional transport still caused high PM2.5 pollution events during LP2022. Photochemical processes dominated the formation of KSO4 particles, while the KNO3 and KSN particles were mainly generated by liquid-phase reactions, and this effect increased year by year.

Harm from Residential Indoor Air Contaminants

This study presents a health-centered approach to quantify and compare the chronic harm caused by indoor air contaminants using disability-adjusted life-year (DALY). The aim is to understand the chronic harm caused by airborne contaminants in dwellings and identify the most harmful. Epidemiological and toxicological evidence of population morbidity and mortality is used to determine harm intensities, a metric of chronic harm per unit of contaminant concentration. Uncertainty is evaluated in the concentrations of 45 indoor air contaminants commonly found in dwellings. Chronic harm is estimated from the harm intensities and the concentrations. The most harmful contaminants in dwellings are PM2.5, PM10-2.5, NO2, formaldehyde, radon, and O3, accounting for over 99% of total median harm of 2200 DALYs/105 person/year. The chronic harm caused by all airborne contaminants in dwellings accounts for 7% of the total global burden from all diseases.

Specific analysis of PM2.5-attributed disease burden in typical areas of Northwest China

Background

Frequent air pollution events in Northwest China pose a serious threat to human health. However, there is a lack of specific differences assessment in PM2.5-related disease burden. Therefore, we aimed to estimate the PM2.5-related premature deaths and health economic losses in this typical northwest region, taking into account disease-specific, age-specific, and region-specific factors.

Methods

We utilized the WRF-Chem model to simulate and analyze the characteristics and exposure levels of PM2.5 pollution in Gansu Province, a typical region of Northwest China. Subsequently, we estimated the premature mortality and health economic losses associated with PM2.5 by combining the Global Exposure Mortality Model (GEMM) and the Value of a Statistical Life (VSL).

Results

The results suggested that the PM2.5 concentrations in Gansu Province in 2019 varied spatially, with a decrease from north to south. The number of non-accidental deaths attributable to PM2.5 pollution was estimated to be 14,224 (95% CI: 11,716-16,689), accounting for 8.6% of the total number of deaths. The PM2.5-related health economic loss amounted to 28.66 (95% CI: 23.61-33.63) billion yuan, equivalent to 3.3% of the regional gross domestic product (GDP) in 2019. Ischemic heart disease (IHD) and stroke were the leading causes of PM2.5-attributed deaths, contributing to 50.6% of the total. Older adult individuals aged 60 and above accounted for over 80% of all age-related disease deaths. Lanzhou had a higher number of attributable deaths and health economic losses compared to other regions. Although the number of PM2.5-attributed deaths was lower in the Hexi Corridor region, the per capita health economic loss was higher.

Conclusion

Gansu Province exhibits distinct regional characteristics in terms of PM2.5 pollution as well as disease- and age-specific health burdens. This highlights the significance of implementing tailored measures that are specific to local conditions to mitigate the health risks and economic ramifications associated with PM2.5 pollution.

Assessing the effect of COVID-19 pandemic on air quality change and human health outcomes in a capital city, southwestern Iran

The aimsof this study were to assess the spatial variation of PM2.5, NO2, and O3 between 2019 (before) and 2020 (during COVID-19 pandemic); and calculation the health outcomes of exposure to these pollutants. The daily PM2.5, NO2, and O3 concentrations were applied to assess health effects by relative risk, and baseline incidence. The annual PM2.5 and NO2 mean concentrations exceeded the WHO guideline values, while O3 did not exceed. The restrictive measures associated to COVID-19 led to reduction at the annual means of PM2.5 and NO2 by -25.5% and -23.1%, respectively, while the annual mean of O3 increased by +7.9%. The number of M-CVD and M-RD (-25.6%, -26.1%) related to PM2.5 exposure, and HA-COPD and HA-RD >65 years old (-21% and -3.84%) related to NO2 exposure were reduced in 2020, and O3 exposure-related M-CVD (+30.1%) and HA-RD >65 years old (+23.4%) increased compared to the previous year 2019.

Measuring the urban-rural and spatiotemporal heterogeneity of the drivers of PM2.5-attributed health burdens in China from 2008 to 2021 using high-resolution dataset

Urbanization has been considered a driver of PM2.5 pollution and the attributed health burden. This study systematically measured the spatiotemporal and urban-rural heterogeneity of PM2.5-attributed health burden drivers, including income, population, baseline mortality rate, and PM2.5 level. The results reveal the significantly positive contribution of disposable income and the periodical and urban-rural differentiation of population contribution to PM2.5-attributed health burden. The difference in driver performance due to socioeconomic development and urbanization stages might be an important determinant for different or even opposite results of previous studies. Policymaking for mitigating PM2.5-attributed health risk could incorporate the re-assessment and driver determination for PM2.5-attributed health burden into the construction and development plan from the overall urbanization perspective. The urbanization-perspective driver decomposition could be synergized with the flow analysis, equality evaluation, and policy benefit estimation to achieve further direction-determining and quantitative assessment of the urban-rural PM2.5 health risk management strategies.

Drivers of ozone-related premature mortality in China: Implications for historical and future scenarios

Long-term exposure to ambient ozone (O3) poses a severe public health threat in China. However, the drivers of premature mortality caused by O3 pollution are still poorly constrained, despite being prerequisites for addressing the threat. Here, we demonstrate the contributions of historical and future changes in peak-season O3, population size, age structure, and baseline mortality to China's O3-related mortality using decomposition analysis. From 2013 to 2021, O3-related mortality decreased dramatically from 78.8 (40.8-124.6) to 68.7 (36.0-107.2) thousand, especially in densely populated areas with high pollution. Variations in peak-season O3, population size, age structure, and baseline mortality led to changes in O3-related mortality of +27.3 (14.8-41.3), +2.6 (1.4-4.1), +22.3 (11.5-35.2), and -40.3 (20.9-63.7) thousand, respectively. The influence of peak-season O3 on O3-related mortality shifted from positive during 2013-2019 (+8.4% per year) to negative during 2019-2021 (-8.8% per year), which highly regulated the interannual trend of mortality. From 2021 to 2035, O3-related mortality is expected to increase by 31% in the current context of peak-season O3 levels, primarily caused by increased aging. Even reducing peak-season O3 to the WHO interim target 1 (IT-1) would only reduce O3-related mortality by 3.9%, while a more rigorous standard (IT-2) would prevent 83.7% of mortality. These findings suggest that improving ambient O3 can lead to significant health benefits, but substantial mitigation strategies are merited given the future trend of population aging.

Estimation of health risk and economic loss attributable to PM2.5 and O3 pollution in Jilin Province, China

Ambient pollutants, particularly fine particulate matter (PM2.5) and ozone (O3), pose significant risks to both public health and economic development. In recent years, PM2.5 concentration in China has decreased significantly, whereas that of O3 has increased rapidly, leading to considerable health risks. In this study, a generalized additive model was employed to establish the relationship of PM2.5 and O3 exposure with non-accidental mortality across 17 districts and counties in Jilin Province, China, over 2015-2016. The health burden and economic losses attributable to PM2.5 and O3 were assessed using high-resolution satellite and population data. According to the results, per 10 µg/m3 increase in PM2.5 and O3 concentrations related to an overall relative risk (95% confidence interval) of 1.004 (1.001-1.007) and 1.009 (1.005-1.012), respectively. In general, the spatial distribution of mortality and economic losses was uneven. Throughout the study period, a total of 23,051.274 mortalities and 27,825.015 million Chinese Yuan (CNY) in economic losses were attributed to O3 exposure, which considerably surpassing the 5,450.716 mortalities and 6,553,780 million CNY in economic losses attributed to PM2.5 exposure. The O3-related health risks and economic losses increased by 3.75% and 9.3% from 2015 to 2016, while those linked to PM2.5 decreased by 23.33% and 18.7%. Sensitivity analysis results indicated that changes in pollutant concentrations were the major factors affecting mortality rather than baseline mortality and population.

Estimation of surface ozone concentration over Jiangsu province using a high-performance deep learning model

Recently, the global background concentration of ozone (O₃) has demonstrated a rising trend. Among various methods, groun-based monitoring of O₃ concentrations is highly reliable for research analysis. To obtain information on the spatial characteristics of O₃ concentrations, it is necessary that the ground monitoring sites be constructed in sufficient density. In recent years, many researchers have used machine learning models to estimate surface O₃ concentrations, which cannot fully provide the spatial and temporal information contained in a sample dataset. To solve this problem, the current study utilized a deep learning model called the Residual connection Convolutional Long Short-Term Memory network (R-ConvLSTM) to estimate daily maximum 8-hr average (MDA8) O₃ over Jiangsu province, China during 2020. In this research, the R-ConvLSTM model not only provides the spatiotemporal information of MDA8 O₃, but also involves residual connection to avoid the problem of gradient explosion and gradient disappearance with the deepening of network layers. We utilized the TROPOMI total O₃ column retrieved from Sentinel-5 Precursor, ERA5 reanalysis meteorological data, and other supplementary data to build a pre-trained dataset. The R-ConvLSTM model achieved an overall sample-base cross-validation (CV) R² of 0.955 with root mean square error (RMSE) of 9.372 µg/m³. Model estimation also showed a city-based CV R² of 0.896 with RMSE of 14.029 µg/m³, the highest MDA8 O₃ in spring being 122.60 ± 31.60 µg/m³ and the lowest in winter being 69.93 ± 18.48 µg/m³.

Long-Term Air Pollution Characteristics and Multi-scale Meteorological Factor Variability Analysis of Mega-mountain Cities in the Chengdu-Chongqing Economic Circle

Currently, air quality has become central to global environmental policymaking. As a typical mountain megacity in the Cheng-Yu region, the air pollution in Chongqing is unique and sensitive. This study aims to comprehensively investigate the long-term annual, seasonal, and monthly variation characteristics of six major pollutants and seven meteorological parameters. The emission distribution of major pollutants is also discussed. The relationship between pollutants and the multi-scale meteorological conditions was explored. The results indicate that particulate matter (PM), SO2 and NO2 showed a "U-shaped" variation, while O3 showed an "inverted U-shaped" seasonal variation. Industrial emissions accounted for 81.84%, 58% and 80.10% of the total SO2, NOx and dust pollution emissions, respectively. The correlation between PM2.5 and PM10 was strong (R = 0.98). In addition, PM only showed a significant negative correlation with O3. On the contrary, PM showed a significant positive correlation with other gaseous pollutants (SO2, NO2, CO). O3 is only negatively correlated with relative humidity and atmospheric pressure. These findings provide an accurate and effective countermeasure for the coordinated management of air pollution in Cheng-Yu region and the formulation of the regional carbon peaking roadmap. Furthermore, it can improve the prediction accuracy of air pollution under multi-scale meteorological factors, promote effective emission reduction paths and policies in the region, and provide references for related epidemiological research.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s11270-023-06279-8.

Exploring the contributions of major emission sources to PM2.5 and attributable health burdens in China

Ambient fine particulate matter (PM_2.5) pollution is the principal environmental risk factor for health burdens in China. Identifying the sectoral contributions of pollutant emissions sources on multiple spatiotemporal scales can help in the formulation of specific strategies. In this study, we used sensitivity analysis to explore the specific contributions of seven major emission sources to ambient PM_2.5 and attributable premature mortality across mainland China. In 2016, about 60% of China's population lived in areas with PM_2.5 concentrations above the Chinese Ambient Air Quality Standard of 35 μg/m³. This percentage was expected to decrease to 35% and 39% if industrial and residential emissions were fully eliminated. In densely populated and highly polluted regions, residential sources contributed about 50% of the PM_2.5 exposure in winter, while industrial sources contributed the most (29-51%) in the remaining seasons. The three major sectoral contributors to PM_2.5-related deaths were industry (247,000 cases, 35%), residential sources (219,000 cases, 31%), and natural sources (87,000, 12%). The relative contributions of the different sectors varied in the different provinces, with industrial sources making the largest contribution in Shanghai (65%), while residential sources predominated in Heilongjiang (63%), and natural sources dominated in Xinjiang (82%). The contributions of the agricultural (11%), transportation (6%), and power (3%) sources were relatively low in China, but emissions mitigation was still effective in densely populated areas. In conclusion, to effectively alleviate health burdens across China, priority should be given to controlling residential emissions in winter and industrial emissions all year round, taking additional measures to curb emissions from other sources in urban hotspots, and formulating air pollution control strategies tailored to local conditions.

Modification effects of ambient temperature on associations of ambient ozone exposure before and during pregnancy with adverse birth outcomes: A multicity study in China

BACKGROUND

Epidemiological studies suggest that both ambient ozone (O₃) and temperature were associated with increased risks of adverse birth outcomes. However, very few studies explored their interaction effects, especially for small for gestational age (SGA) and large for gestational age (LGA).

OBJECTIVES

To estimate the modification effects of ambient temperature on associations of ambient O₃ exposure before and during pregnancy with preterm birth (PTB), low birth weight (LBW), SGA and LGA based on multicity birth cohorts.

METHODS

A total of 56,905 singleton pregnant women from three birth cohorts conducted in Tianjin, Beijing and Maoming, China, were included in the study. Maximum daily 8-h average O₃ concentrations of each pregnant woman from the preconception period to delivery for every day were estimated by matching their home addresses with the Tracking Air Pollution in China (TAP) datasets. We first applied the Cox proportional-hazards regression model to evaluate the city-specific effects of O₃ exposure before and during pregnancy on adverse birth outcomes at different temperature levels with adjustment for potential confounders, and then a meta-analysis across three birth cohorts was conducted to calculate the pooled associations.

RESULTS

In pooled analysis, significant modification effects of ambient temperature on associations of ambient O₃ with PTB, LBW and LGA were observed (P_interaction < 0.05). For a 10 μg/m³ increase in ambient O₃ exposure at high temperature level (> 75^th percentile), the risk of LBW increased by 28 % (HR: 1.28, 95% CI: 1.13-1.46) during the second trimester and the risk of LGA increased by 116% (HR: 2.16, 95%CI: 1.16-4.00) during the entire pregnancy, while the null or weaker association was observed at corresponding low (≤ 25^th percentile) and medium (> 25^th and ≤ 75^th percentile) temperature levels.

CONCLUSION

This multicity study added new evidence that ambient high temperature may enhance the potential effects of ambient O₃ on adverse birth outcomes.

Tracking long-term population exposure risks to PM2.5 and ozone in urban agglomerations of China 2015-2021

China has experienced severe air pollution in the past decade, especially PM2.5 and emerging ozone pollution recently. In this study, we comprehensively analyzed long-term population exposure risks to PM2.5 and ozone in urban agglomerations of China during 2015-2021 regarding two-stage clean-air actions based on the Ministry of Ecology and the Environment (MEE) air monitoring network. Overall, the ratio of the population living in the regions exceeding the Chinese National Ambient Air Quality Standard (35 μg/m3) decreases by 29.9 % for PM2.5 from 2015 to 2021, driven by high proportions in the Middle Plain (MP, 42.3 %) and Lan-Xi (35.0 %) regions. However, this ratio almost remains unchanged for ozone and even increases by 1.5 % in the MP region. As expected, the improved air quality leads to 234.7 × 103 avoided premature mortality (ΔMort), mainly ascribed to the reduction in PM2.5 concentration. COVID-19 pandemic may influence the annual variation of PM2.5-related ΔMort as it affects the shape of the population exposure curve to become much steeper. Although all eleven urban agglomerations share stroke (43.6 %) and ischaemic heart disease (IHD, 30.1 %) as the two largest contributors to total ΔMort, cause-specific ΔMort is highly regional heterogeneous, in which ozone-related ΔMort is significantly higher (21 %) in the Tibet region than other urban agglomeration. Despite ozone-related ΔMort being one order of magnitude lower than PM2.5-related ΔMort from 2015 to 2021, ozone-related ΔMort is predicted to increase in major urban agglomerations initially along with a continuous decline for PM2.5-related ΔMort from 2020 to 2060, highlighting the importance of ozone control. Coordinated controls of PM2.5 and O3 are warranted for reducing health burdens in China during achieving carbon neutrality.

Assessing the contribution of open crop straw burning to ground-level ozone and associated health impacts in China and the effectiveness of straw burning bans

In recent years, ozone pollution in China has been shown to increase in frequency and persistence despite the concentrations of fine particulate matter (PM_2.5) decreasing steadily. Open crop straw burning (OCSB) activities are extensive in China and emit large amounts of trace gases during a short period that could lead to elevated ozone concentrations. This study addresses the impacts of OCSB emissions on ground-level ozone concentration and the associated health impact in China. Total VOCs and NOx emissions from OCSB in 2018 were 798.8 Gg and 80.6 Gg, respectively, with high emissions in Northeast China (31.7%) and North China (23.7%). Based on simulations conducted for 2018, OCSB emissions are estimated to contribute up to 0.95 µg/m³ increase in annual averaged maximum daily 8-hour (MDA8) ozone and up to 1.35 µg/m³ for the ozone season average. The significant impact of OCSB emissions on ozone is mainly characterized by localized and episodic (e.g., daily) changes in ozone concentration, up to 20 µg/m³ in North China and Yangtze River Delta region and even more in Northeast China during the burning season. With the implementation of straw burning bans, VOCs and NOx emissions from OCSB dropped substantially by 46.9%, particularly over YRD (76%) and North China (60%). Consequently, reduced OCSB emissions result in an overall decrease in annual averaged MDA8 ozone, and reductions in monthly MDA8 ozone could be over 10 µg/m³ in North China. The number of avoided premature death due to reduced OCSB emissions (considering both PM_2.5 and ozone) is estimated to be 6120 (95% Confidence Interval: 5320-6800), with most health benefits gained over east and central China. Our results illustrate the effectiveness of straw burning bans in reducing ozone concentrations at annual and national scales and the substantial ozone impacts from OCSB events at localized and episodic scales.

Ambient PM2.5 and O3 pollution and health impacts in Iranian megacity

The main objectives of this study were to (i) assess variation within fine particles (PM_2.5) and tropospheric ozone (O₃) time series in Khorramabad (Iran) between 2019 (before) and 2020 (during COVID-19 pandemic); (ii) assess relationship between PM_2.5 and O₃, the PM_2.5/O₃ ratio, and energy consumption; and (iii) estimate the health effects of exposure to ambient PM_2.5 and O₃. From hourly PM_2.5 and O₃ concentrations, we applied both linear-log and integrated exposure-response functions, city-specific relative risk, and baseline incidence values to estimate the health effects over time. A significant correlation was found between PM_2.5 and O₃ (r =-0.46 in 2019, r =-0.55 in 2020, p < 0.05). The number of premature deaths for all non-accidental causes (27.5 and 24.6), ischemic heart disease (7.3 and 6.3), chronic obstructive pulmonary disease (17 and 19.2), and lung cancer (9.2 and 6.25) attributed to ambient PM_2.5 exposure and for respiratory diseases (4.7 and 5.4) for exposure to O₃ above 10 µg m^-3 for people older than 30-year-old were obtained in 2019 and 2020. The number of years of life lost declined by 11.6% in 2020 and exposure to PM_2.5 reduced the life expectancy by 0.58 and 0.45 years, respectively in 2019 and 2020. Compared to 2019, the restrictive measures associated to COVID-19 pandemic led to reduction in PM_2.5 (-25.5%) and an increase of O₃ concentration (+ 8.0%) in Khorramabad.

Tracking short-term health impacts attributed to ambient PM2.5 and ozone pollution in Chinese cities: an assessment integrates daily population

Joint and synergistic control of PM_2.5 and ozone pollution is an urgent need in China and a global-widely concerned issue. Health impact assessment could provide a comprehensive perspective for PM_2.5-ozone coordinated control strategies. For a detailed understanding of the seasonality and regionality of the health impacts attributed to PM_2.5 and ozone in China, this study extended the classic health impact function by daily population and assessed the short-term (daily) health impacts in 335 Chinese cities in 2021. Population migration indexes from Baidu were introduced to estimate the cities' daily population. Using this method, we quantitatively investigated the influence of population on short-term health impact assessment and identified which was significant in the Pearl River Delta (PRD) region and other populous cities. Although the annual sums of PM_2.5- and ozone-related daily health impacts were close for all Chinese cities, the PM_2.5-related health impact was equivalent to 333.96% and 32.07% of that ozone-related, during the cold and warm periods. The correlation and local spatial association analysis found significant city-specific and city-cluster associations of daily health impacts during the warm period and in Beijing-Tianjin-Hebei and surrounding regions (BTHS) and the Yangtze River Delta (YRD). Policymakers could promote period- and pollutant-targeted control actions for the major city groups, especially the BTHS, YRD, and PRD. Our methods and findings investigated the various influences of the population on short-term health impact assessment and proposed the PM_2.5-ozone collaborative control idea for key regions and city groups.

Health and economic impacts of ambient air particulate matter (PM2.5) in Karaj city from 2012 to 2019 using BenMAP-CE

The present study aims to estimate the effects of PM_2.5 on the health and economy of Karaj city from 2012 to 2019. In this study, mortality attributed to long-term exposure to PM_2.5 and its spatial distribution in Karaj over the 2012-2019 period were estimated using the Global Exposure Mortality Model (GEMM) concentration-response function and BenMAP software. PM_2.5 hourly concentration data of air quality monitoring stations were used to estimate PM_2.5 for the whole city of Karaj. The economic effects of this pollutant were also assessed using the value of statistical life (VSL) method. The results showed that the annual average PM_2.5 concentration during the studied time increased and was higher than the air quality guideline levels recommended by the World Health Organization. Also, the annual number of deaths attributed to PM_2.5 in adults (older than 25 years) was estimated to be about 1200. The highest to lowest proportions of PM_2.5-related deaths were non-accidental mortality, ischemic heart attack, stroke, acute respiratory tract infection, chronic obstructive pulmonary disease (COPD), and lung cancer, in the order of their appearance. The results showed that the economic loss attributed to this pollutant was estimated at 380 to 504 million USD per year. Due to the effects of PM_2.5 on health and the economy in this city, we suggest conducting special planning to control and reduce the concentration of ambient air particulate matter by improving the public transportation system and updating industrial processes.

Assessment of PM2.5-related health effects: A comparative study using multiple methods and multi-source data in China

In China, PM_2.5 pollution has caused extensive death and economic loss. Thus, an accurate assessment of the spatial distribution of these losses is crucial for delineating priority areas for air pollution control in China. In this study, we assessed the PM_2.5 exposure-related health effects according to the integrated exposure risk function and non-linear power law (NLP) function in 338 prefecture-level cities in China by utilizing online monitoring data and the PM_2.5 Hindcast Database (PHD). Our results revealed no significant difference between the monitoring data and PHD (p value = 0.66 > 0.05). The number of deaths caused by PM_2.5-related Stroke (cerebrovascular disease), ischemic heart disease, chronic obstructive pulmonary disease, and lung cancer at the national level estimated through the NLP function was 0.27 million (95% CI: 0.06-0.50), 0.23 million (95% CI: 0.08-0.38), 0.31 million (95% CI: 0.04-0.57), and 0.31 million (95% CI: 0.16-0.40), respectively. The total economic cost at the national level in 2016 was approximately US$80.25 billion (95% CI: 24.46-132.25). Based on a comparison of Z statistics, we propose that the evaluation results obtained using the NLP function and monitoring data are accurate. Additionally, according to scenario simulations, Beijing, Chongqing, Tianjin, and other cities should be priority areas for PM_2.5 pollution control to achieve considerable health benefits. Our statistics can help improve the accuracy of PM_2.5-related health effect assessments in China.

Interannual variations, sources, and health impacts of the springtime ozone in Shanghai

In spring, ozone (O₃) pollution frequently occurrs in eastern China, but key drivers remain uncertain. In this study, interannual variations in springtime ozone in Shanghai, China, from 2013 to 2021, were investigated to assess the health impacts and the effectiveness of recent air pollution control measures. A combination of ground-level measurements of regulated air pollutants, lidar observations, and backward trajectories of air masses was used to identify the key drivers for enhancing springtime O₃. The results show that external imports of O₃ driven by atmospheric circulation are notable sources of springtime surface O₃. For example, the downward transport from the free troposphere could contribute to over 50% of surface O₃ in the morning. The surface O₃ mixing ratios in spring exhibited an upward trend of 0.93 ppb yr^-1 (p < 0.05) from 2013 to 2021. The change in meteorological variables, particularly the increase in air temperature, could explain nearly 87% of the springtime O₃ upward trend. The change in anthropogenic emissions of precursors only contributed to a small fraction (<13%) of the increase in springtime O₃. The cumulative exposure of urban residents to O₃ in spring also exhibited a significant upward trend (111 ppb yr^-1, p < 0.05). With the rapid increase in surface O₃, premature respiratory mortality attributable to O₃ exposure has fluctuated at approximately 2933 deaths per year since 2016, even though the total deaths from respiratory diseases have significantly declined. Long-term exposure to high O₃ concentrations is a significant contributor to premature respiratory mortality.

Mitigating China's Ozone Pollution with More Balanced Health Benefits

China is confronting the challenge of opposite health benefits (OHBs) during ambient ozone (O₃) mitigation because the same reduction scheme might yield opposite impacts on O₃ levels and associated public health across different regions. Here, we used a combination of chemical transport modeling, health benefit assessments, and machine learning to capture such OHBs and optimize O₃ mitigation pathways based on 121 control scenarios. We revealed that, for the China mainland, Beijing-Tianjin-Hebei and its surroundings ("2 + 26" cities), Yangtze River Delta, and Pearl River Delta, there could be at most 2897, 920, 1247, and 896 additional O₃-related deaths in urban areas, respectively, accompanying 21,512, 3442, 5614, and 642 avoided O₃-related deaths in rural areas, respectively, at the same control stage. Additionally, potential disbenefits during O₃ mitigation were "pro-wealthy", that is, residents in developed regions are more likely to afford additional health risks. In order to avoid OHBs during O₃ abatement, we proposed a two-phase control strategy, whereby the reduction ratio of NO_X (nitrogen oxide) to VOCs (volatile organic compounds) was adjusted according to health benefit distribution patterns. Our study provided novel insights into China's O₃ attainment and references for other countries facing the dual challenges of environmental pollution and associated inequality issues.

New Deep Learning Model to Estimate Ozone Concentrations Found Worrying Exposure Level over Eastern China

Ozone (O3), whose concentrations have been increasing in eastern China recently, plays a key role in human health, biodiversity, and climate change. Accurate information about the spatiotemporal distribution of O3 is crucial for human exposure studies. We developed a deep learning model based on a long short-term memory (LSTM) network to estimate the daily maximum 8 h average (MDA8) O3 across eastern China in 2020. The proposed model combines LSTM with an attentional mechanism and residual connection structure. The model employed total O3 column product from the Tropospheric Monitoring Instrument, meteorological data, and other covariates as inputs. Then, the estimates from our model were compared with real observations of the China air quality monitoring network. The results indicated that our model performed better than other traditional models, such as the random forest model and deep neural network. The sample-based cross-validation R2 and RMSE of our model were 0.94 and 10.64 μg m−3, respectively. Based on the O3 distribution over eastern China derived from the model, we found that people in this region suffered from excessive O3 exposure. Approximately 81% of the population in eastern China was exposed to MDA8 O3 > 100 μg m−3 for more than 150 days in 2020.

Quantifying ecological and health risks of ground-level O3 across China during the implementation of the "Three-year Action Plan for Cleaner Air"

After China implemented the Air Pollution Prevention and Control Action Plan (APPCAP), PM_2.5 concentrations decreased but were still higher than national standards in major areas and ozone (O₃) concentration increased unintentionally. To further decrease PM_2.5 concentrations and reduce days with severe air pollution, the government promulgated the "Three-year (2018-2020) Action Plan for Cleaner Air" (the Three-year Action Plan) in 2018. During the three-year Action Plan, a few studies reported a continuous decline in PM_2.5, but it is unclear whether O₃ and its effects also increase with the decrease of PM_2.5 like during APPCAP. In this study, for the first time, we systematically assessed changes in ground-level O₃ concentrations and related ecological and health risks during the period of the Three-year Action Plan using nationwide O₃ measurements. The national MDA8, Exceedance, and SOMO35 indicators were reduced by 3.8%, 28.5%, and 12.6%, respectively, ecological risk indicators of M12, M7, SUM06, AOT40, and W126 were reduced by 5.4%, 5.6%, 19.5%, 15.4%, and 18.6%, respectively, from 2018 to 2020. Spatially, the greatest reduction in all the indicators except MDA8 occurred in Pearl River Delta, followed by Fen Wei Plains, while Beijing-Tianjin-Hebei, Chengdu-Chongqing, and Yangtze River Delta presented relatively small reductions. Between 2018 and 2020, the production losses caused by O₃ for wheat and rice decreased by 21.4% and 17.6%, respectively. Long-term exposure to O₃ across China over 2020 was estimated to cause about 160,795 (95% CI: 81,515-312,983) for all-cause mortality, 107,128 (95% CI: 36,703-173,823) for cardiovascular mortality, and 34,444 (95% CI: 0-72,609) for respiratory mortality, indicating decreases of 9.93%, 9.86%, and 9.78%, respectively, compared to the year 2018. Taken together, our results provided the first direct evidence for China's efforts to control O₃ pollution in recent years.

A High-Performance Convolutional Neural Network for Ground-Level Ozone Estimation in Eastern China

Having a high-quality historical air pollutant dataset is critical for environmental and epidemiological research. In this study, a novel deep learning model based on convolutional neural network architecture was developed to estimate ground-level ozone concentrations across eastern China. A high-resolution maximum daily average 8-hour (MDA8) surface ground ozone concentration dataset was generated with the support of the total ozone column from the satellite Tropospheric Monitoring Instrument, meteorological data from the China Meteorological Administration Land Data Assimilation System, and simulations of the WRF-Chem model. The modeled results were compared with in situ measurements in five cities that were not involved in model training, and the mean R2 of predicted ozone with observed values was 0.9, indicating the good robustness of our model. In addition, we compared the model results with some widely used machine learning techniques (e.g., random forest) and recently published ozone datasets, showing that the accuracy of our model is higher and that the spatial distributions of predicted ozone are more coherent. This study provides an efficient and exact method to estimate ground-level ozone and offers a new perspective for modeling spatiotemporal air pollutants.

A Health Impact and Economic Loss Assessment of O3 and PM2.5 Exposure in China From 2015 to 2020

China is in a critical air quality management stage. Rapid industrial development and urbanization has resulted in non-ignorable air pollution, which seriously endangers human health. Assessment of the health impacts and economic losses of air pollution is essential for the prevention and control policy formulation. Based on ozone (O₃) and fine particulate matter concentration (PM_2.5) monitoring data in 331 Chinese cities from 2015 to 2020, this study evaluated the health effects and the corresponding economic losses of O₃ and PM_2.5 pollution on three health endpoints. The ratio of population exposed to O₃ levels that exceeded the Chinese Ambient Air Quality Standards (CAAQS) increased from 13.35% in 2015 to 14.15% in 2020, which resulted in 133,415 (2015) - 156,173 (2020) all-cause deaths, 88,941 (2015) - 104,051 (2020) cardiovascular deaths, and 28,614 (2015) - 33,456 (2020) respiratory deaths. The ratio of population exposed to PM_2.5 levels that exceeded the CAAQS decreased, but in many regions, especially in North China and the Yangtze River Delta, the PM_2.5 concentration remained high. By 2020, nearly half of the population in China was still exposed to PM_2.5 levels that exceeded the CAAQS, and the corresponding economic losses reached CNY 3.46 and 3.05 billion, respectively. These results improved the understanding of the spatial-temporal variation trends of major air pollutants at city scale in China, and emphasize the continued coordination urgently needed for controlling O₃ and PM_2.5 following the implementation of the 2013 policy to mitigate air pollution to protect human health.

The lanthanide doping effect on toluene catalytic oxidation over Pt/CeO2 catalyst

The present work was undertaken to know the lanthanide doping effect on the physicochemical properties of Pt/CeO₂ catalysts and their catalytic activity for toluene oxidation. A series of lanthanide ions (La, Pr, Nd, Sm and Gd) were incorporated into ceria lattice by hydrothermal method, and the Pt nanoparticles with equal quality were successfully loaded on various ceria-based supports. Their catalytic performance toward toluene oxidation shows a remarkable lanthanide-doping effect, and the activity is much dependent on the ion radius and valence state of dopants. Owing to smaller ion radius and low valence state, the dopant of Gd would form more Gd-Ce complex and less GdO₈-type complex, generating more oxygen vacancies and then promoting oxygen replenishment. Furthermore, the high concentration of oxygen vacancy would drive electrons to transfer from support to metal, and thus electron-rich and under-coordinated Pt particles that are favorable for toluene adsorption and dissociation are obtained. Attributing to above positive factors, the doping of Gd would effectively enhance the catalytic oxidation of toluene over Pt/CeO₂ catalyst. In addition, the Pt/CeGdO₂ sample exhibits an excellent reaction stability and resistance of concentration impact.

Temporal and Spatial Analysis of PM2.5 and O3 Pollution Characteristics and Transmission in Central Liaoning Urban Agglomeration from 2015 to 2020

The central Liaoning urban agglomeration is an important heavy industry development base in China, and also an important part of the economy in northeast China. The atmospheric environmental problems caused by the development of heavy industry are particularly prominent. Trajectory clustering, potential source contribution (PSCF), and concentration weighted trajectory (CWT) analysis are used to discuss the temporal and spatial pollution characteristics of PM2.5 and ozone concentrations and reveal the regional atmospheric transmission pattern in central Liaoning urban agglomeration from 2015 to 2020. The results show that: (1) PM2.5 in the central Liaoning urban agglomeration showed a decreasing trend from 2015 to 2020. The concentration of PM2.5 is the lowest in 2018. Except for Benxi (34.7 µg/m3), the concentrations of PM2.5 in other cities do not meet the standard in 2020. The ozone concentration in Anshan, Liaoyang, and Shenyang reached the peaks in 2017, which are 68.76 µg/m3, 66.27 µg/m3, and 63.46 µg/m3 respectively. PM2.5 pollution is the highest in winter and the lowest in summer. The daily variation distribution of PM2.5 concentration showed a bimodal pattern. Ozone pollution is the most serious in summer, with the concentration of ozone reaching 131.14 µg/m3 in Shenyang. Fushun is affected by Shenyang intercity pollution, and the ozone concentration is high. (2) In terms of spatial distribution, the high values of PM2.5 are concentrated in monitoring stations in urban areas. On the contrary, the concentration of ozone in suburban stations is higher. The high concentration of ozone in the northeast of Anshan, Liaoyang, Shenyang to Tieling, and Fushun extended in a band distribution. (3) Through cluster analysis, it is found that PM2.5 and ozone in Shenyang are mainly affected by short-distance transport airflow. In winter, the weighted PSCF high-value area of PM2.5 presents as a potential contribution source zone of the northeast trend with wide coverage, in which the contribution value of the weighted CWT in the middle of Heilongjiang is the highest. The main potential source areas of ozone mass concentration in spring and summer are coastal cities and the Bohai Sea and the Yellow Sea. We conclude that the regional transmission of pollutants is an important factor of pollution, so we should pay attention to the supply of industrial sources and marine sources of marine pollution in the surrounding areas of cities, and strengthen the joint prevention and control of air pollution among regions. The research results of this article provide a useful reference for the central Liaoning urban agglomeration to improve air quality.