Spatiotemporal assessment of health burden and economic losses attributable to short-term exposure to ground-level ozone during 2015-2018 in China

Coordinated analysis of groundwater spatiotemporal chemical characteristics, water quality, and potential human health risks with sustainable development in semi-arid regions

The emergence of large-scale time-series data and advancements in computational power have opened new avenues for analyzing the spatiotemporal evolution of groundwater chemistry, water quality, and human health risks. This paper utilizes hydrogeochemical methods to elucidate the controlling factors of water chemical components based on the test results of 124 groundwater samples collected from 31 monitoring wells in Fuxin City, Liaoning Province, China, from 2018 to 2021. By integrating the Random Forest and Enhanced Water Quality Index methods for water quality assessment and employing the Human Health Risk Assessment (HHRA) model to analyze human health risks, our findings indicate that the groundwater is mildly alkaline, with SO4·Cl-Ca·Mg and HCO3-Ca·Mg as the dominant hydrochemical types, primarily derived from the dissolution of carbonate and silicate minerals such as dolomite, limestone, and andesite, and cation exchange reactions. The EI_RF water quality evaluation model reveals that the overall water quality in the study area is poor, with Class I and II water quality zones mainly located in the northeastern and central parts of the study area, showing a gradual transition from Class I and II in the northeast to Classes IV and V in the southwest, significantly influenced by NO3-, TH, TDS, and SO42-. The HHRA model results indicate that the potential non-carcinogenic risk of groundwater nitrates has a severe impact on infants, with the spatial distribution being low in the northeast and high in the southwest. Due to industrial activities, agricultural practices, and population growth, certain areas in developing countries such as China and India exhibit nitrate concentrations significantly higher than those in most international regions, highlighting global environmental and public health challenges. This underscores the importance of enhancing groundwater monitoring and implementing measures to mitigate pollution. These research outcomes hold significant implications for the government in formulating rational protection and management measures to ensure the sustainable utilization of groundwater resources.

Long-term ambient ozone exposure and incident cardiovascular diseases: National cohort evidence in China

BACKGROUND

Long-term ozone (O3) exposure has been associated with cardiovascular disease (CVD) mortality in mounting cohort evidence, yet its relationship with incident CVD was poorly understood, especially in low- and middle-income countries (LMICs) experiencing high ambient air pollution.

METHODS

We carried out a nationwide perspective cohort study from 2010 through 2018 by dynamically enrolling 36948 participants across Chinese mainland. Warm-season (April-September) O3 concentrations were estimated using satellite-based machine-learning models with national coverage. Cox proportional hazards model with time-varying exposures was employed to evaluate the association of long-term O3 exposure with incident CVD (overall CVD, hypertension, stroke, and coronary heart disease [CHD]). Assuming causality, a counterfactual framework was employed to estimate O3-attributable CVD burden based on the exposure-response (E-R) relationship obtained from this study. Decomposition analysis was utilized to quantify the contributions of four key direct driving factors (O3 exposure, population size, age structure, and incidence rate) to the net change of O3-related CVD cases between 2010 and 2018.

RESULTS

A total of 4428 CVD, 2600 hypertension, 1174 stroke, and 337 CHD events were reported during 9-year follow-up. Each 10-μg/m³ increase in warm-season O3 was associated with an incident risk of 1.078 (95% confidence interval [CI]: 1.050-1.106) for overall CVD, 1.098 (95% CI: 1.062-1.135) for hypertension, 1.073 (95% CI: 1.019-1.131) for stroke, and 1.150 (95% CI: 1.038-1.274) for CHD, respectively. We observed no departure from linear E-R relationships of O3 exposure with overall CVD (Pnonlinear= 0.22), hypertension (Pnonlinear= 0.19), stroke (Pnonlinear= 0.70), and CHD (Pnonlinear= 0.44) at a broad concentration range of 60-160 µg/m3. Compared with rural dwellers, those residing in urban areas were at significantly greater O3-associated incident risks of overall CVD, hypertension, and stroke. We estimated 1.22 million (10.6% of overall CVD in 2018) incident CVD cases could be attributable to ambient O3 pollution in 2018, representing an overall 40.9% growth (0.36 million) compared to 2010 (0.87 million, 9.7% of overall CVD in 2010). This remarkable rise in O3-attributable CVD cases was primary driven by population aging (+24.0%), followed by increase in O3 concentration (+10.5%) and population size (+6.7%).

CONCLUSIONS

Long-term O3 exposure was associated with an elevated risk and burden of incident CVD in Chinese adults, especially among urban dwellers. Our findings underscored policy priorities of implementing joint control measures for fine particulate matter and O3 in the context of accelerated urbanization and population aging in China.

Projecting non-communicable diseases attributable to air pollution in the climate change era: a systematic review

OBJECTIVES

Climate change is a major global issue with significant consequences, including effects on air quality and human well-being. This review investigated the projection of non-communicable diseases (NCDs) attributable to air pollution under different climate change scenarios.

DESIGN

This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 flow checklist. A population-exposure-outcome framework was established. Population referred to the general global population of all ages, the exposure of interest was air pollution and its projection, and the outcome was the occurrence of NCDs attributable to air pollution and burden of disease (BoD) based on the health indices of mortality, morbidity, disability-adjusted life years, years of life lost and years lived with disability.

DATA SOURCES

The Web of Science, Ovid MEDLINE and EBSCOhost databases were searched for articles published from 2005 to 2023.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

The eligible articles were evaluated using the modified scale of a checklist for assessing the quality of ecological studies.

DATA EXTRACTION AND SYNTHESIS

Two reviewers searched, screened and selected the included studies independently using standardised methods. The risk of bias was assessed using the modified scale of a checklist for ecological studies. The results were summarised based on the projection of the BoD of NCDs attributable to air pollution.

RESULTS

This review included 11 studies from various countries. Most studies specifically investigated various air pollutants, specifically particulate matter <2.5 µm (PM2.5), nitrogen oxides and ozone. The studies used coupled-air quality and climate modelling approaches, and mainly projected health effects using the concentration-response function model. The NCDs attributable to air pollution included cardiovascular disease (CVD), respiratory disease, stroke, ischaemic heart disease, coronary heart disease and lower respiratory infections. Notably, the BoD of NCDs attributable to air pollution was projected to decrease in a scenario that promotes reduced air pollution, carbon emissions and land use and sustainable socioeconomics. Contrastingly, the BoD of NCDs was projected to increase in a scenario involving increasing population numbers, social deprivation and an ageing population.

CONCLUSION

The included studies widely reported increased premature mortality, CVD and respiratory disease attributable to PM2.5. Future NCD projection studies should consider emission and population changes in projecting the BoD of NCDs attributable to air pollution in the climate change era.

PROSPERO REGISTRATION NUMBER

CRD42023435288.

Urban-rural disparities in the association of nitrogen dioxide exposure with cardiovascular disease risk in China: effect size and economic burden

BACKGROUND

Together with rapid urbanization, ambient nitrogen dioxide (NO2) exposure has become a growing health threat. However, little is known about the urban-rural disparities in the health implications of short-term NO2 exposure. This study aimed to compare the association between short-term NO2 exposure and hospitalization for cardiovascular disease (CVD) among urban and rural residents in Shandong Province, China. Then, this study further explored the urban-rural disparities in the economic burden attributed to NO2 and the explanation for the disparities.

METHODS

Daily hospitalization data were obtained from an electronic medical records dataset covering a population of 5 million. In total, 303,217 hospital admissions for CVD were analyzed. A three-stage time-series analytic approach was used to estimate the county-level association and the attributed economic burden.

RESULTS

For every 10-μg/m3 increase in NO2 concentrations, this study observed a significant percentage increase in hospital admissions on the day of exposure of 1.42% (95% CI 0.92 to 1.92%) for CVD. The effect size was slightly higher in urban areas, while the urban-rural difference was not significant. However, a more pronounced displacement phenomenon was found in rural areas, and the economic burden attributed to NO2 was significantly higher in urban areas. At an annual average NO2 concentration of 10 μg/m3, total hospital days and expenses in urban areas were reduced by 81,801 (44,831 to 118,191) days and 60,121 (33,002 to 86,729) thousand CNY, respectively, almost twice as much as in rural areas. Due to disadvantages in socioeconomic status and medical resources, despite similar air pollution levels in the urban and rural areas of our sample sites, the rural population tended to spend less on hospitalization services.

CONCLUSIONS

Short-term exposure to ambient NO2 could lead to considerable health impacts in either urban or rural areas of Shandong Province, China. Moreover, urban-rural differences in socioeconomic status and medical resources contributed to the urban-rural disparities in the economic burden attributed to NO2 exposure. The health implications of NO2 exposure are a social problem in addition to an environmental problem. Thus, this study suggests a coordinated intervention system that targets environmental and social inequality factors simultaneously.

Intraday exposure to ambient ozone and emergency department visits among children: a case-crossover study in southern China

Most existing studies have investigated short-term associations between ozone exposure and acute disease events among children at a daily timescale, which might neglect risk effects happening within several hours after ozone exposure. In this research, we aimed to depict intraday associations between pediatric emergency department visits (PEDVs) and exposure to ozone in order to better detect ultra-short-term effects of ozone exposure on children. We obtained hourly data of all-cause PEDVs, air pollutants, and meteorological factors in Shenzhen and Guangzhou, China, 2015-2018. We applied time-stratified case-crossover design and conditional logistic regression models to estimate odds ratios per 10-μg/m³ rise of ozone concentrations at various exposure periods (e.g., 0-3, 4-6, 7-12, 13-24, 25-48, and 49-72 h) prior to PEDVs, controlling for hourly relative humidity and temperature. Subgroup analyses divided by gender, age, and season were undertaken to identify the potential susceptible population and period. A total of 358,285 cases of PEDVs were included in two cities, and hourly average concentration of ozone was 45.5 μg/m³ in Guangzhou and 58.9 μg/m³ in Shenzhen, respectively. Increased risks of PEDVs occurred within a few hours (0-3 h) after exposure to ozone and remained up to 48 h. Population risks for PEDVs increased by 0.8% (95% confidence interval, 0.6 to 1.0) in Shenzhen and 0.7% (0.5 to 0.9) in Guangzhou for a 10-μg/m³ increase in ozone concentrations at lag 4-6 h and lag 7-12 h, respectively. These findings were robust to co-exposure adjustments in our sensitivity analyses. Significantly greater ozone-associated risks were consistently observed during cold months (October to March of the following year) in both cities, while we did not identify evidence for effect modification of children's age and gender. This study provided novel evidence for increased risks of acute disease events among children within several hours after ozone exposure, highlighting the significant implications for policymakers to establish hourly air quality standards for better protecting children's health.

Increases in ozone-related mortality in China over 2013-2030 attributed to historical ozone deterioration and future population aging

We systematically examine historical and future changes in premature respiratory mortalities attributable to ozone (O₃) exposure (O₃-mortality) in China and identify the leading cause of respective change for the first time. The historical assessment for 2013-2019 is based on gridded O₃ concentrations generated by a multi-source-data-fusion algorithm; the future prediction for 2019-2030 uses gridded O₃ concentrations projected by four Coupled Model Intercomparison Project Phase 6 (CMIP6) models under three Shared Socioeconomic Pathways (SSP) scenarios. During 2013-2019, national annual O₃-mortality is 176.3 thousand (95%CI: 123.5-224.0 thousand) averaged over 2013-2019 with an increasing trend of 14.1 thousand yr^-1 (95%CI: 10.2-17.4 thousand yr^-1); sensitivity experiments show that the O₃-mortality varies at a rate of +12.7 (95%CI: 9.2-15.6), +5.8 (95%CI: 4.0-7.4), +1.0 (95%CI: 0.7-1.2), -5.4 (95%CI: -6.9 to -3.7) thousand yr^-1, owing to changes in O₃ concentration, population age structure, population size, mortality rate for respiratory disease, respectively. The deterioration of O₃ air quality, shown as significant increase in O₃ concentration, is identified as the primary factor which contributes 90.1 % of 2013-2019 O₃-mortality rise. Compared with O₃-mortality estimated in this study, the widely-used O₃-mortality assessment method based on urban-site-dominant O₃ measurements generates close national O₃-mortality but overestimates (underestimates) provincial O₃-mortality in coastal (central) provinces. From 2019 to 2030, national O₃-mortality is projected to increase by 50.4-103.7 thousand under different SSP scenarios. The change in age structure (i.e. population aging) alone will result in significant O₃-mortality rises of 137.9-160.5 thousand. Compared with 2013-2019 rapid O₃ increase (+2.5 μg m^-3 yr^-1 at national level), O₃ concentrations are projected to increase at a lower rate (+0.4 μg m^-3 yr^-1 in SSP5-8.5) or even decrease (-0.7 μg m^-3 yr^-1 in SSP1-2.6) from 2019 to 2030. Therefore, population aging, in place of O₃ air quality deterioration, will become the leading cause of future O₃-mortality rises during the coming decade.

Study on the spatiotemporal dynamic of ground-level ozone concentrations on multiple scales across China during the blue sky protection campaign

Surface ozone (O₃), one of the harmful air pollutants, generated significantly negative effects on human health and plants. Existing O₃ datasets with coarse spatiotemporal resolution and limited coverage, and the uncertainties of O₃ influential factors seriously restrain related epidemiology and air pollution studies. To tackle above issues, we proposed a novel scheme to estimate daily O₃ concentrations on a fine grid scale (1 km × 1 km) from 2018 to 2020 across China based on machine learning methods using hourly observed ground-level pollutant concentrations data, meteorological data, satellite data, and auxiliary data including digital elevation model (DEM), land use data (LUD), normalized difference vegetation index (NDVI), population (POP), and nighttime light images (NTL), and to identify the difference of influential factors of O₃ on diverse urbanization and topography conditions. Some findings were achieved. The correlation coefficients (R²) between O₃ concentrations and surface net solar radiation (SNSR), boundary layer height (BLH), 2 m temperature (T2M), 10 m v-component (MVW), and NDVI were 0.80, 0.40, 0.35, 0.30, and 0.20, respectively. The random forest (RF) demonstrated the highest validation R² (0.86) and lowest validation RMSE (13.74 μg/m³) in estimating O₃ concentrations, followed by support vector machine (SVM) (R² = 0.75, RMSE = 18.39 μg/m³), backpropagation neural network (BP) (R² = 0.74, RMSE = 19.26 μg/m³), and multiple linear regression (MLR) (R² = 0.52, RMSE = 25.99 μg/m³). Our China High-Resolution O₃ Dataset (CHROD) exhibited an acceptable accuracy at different spatial-temporal scales. Additionally, O₃ concentrations showed decreasing trend and represented obviously spatiotemporal heterogeneity across China from 2018 to 2020. Overall, O₃ was mainly affected by human activities in higher urbanization regions, while O₃ was mainly controlled by meteorological factors, vegetation coverage, and elevation in lower urbanization regions. The scheme of this study is useful and valuable in understanding the mechanism of O₃ formation and improving the quality of the O₃ dataset.

Machine-Learning-Based Near-Surface Ozone Forecasting Model with Planetary Boundary Layer Information

Surface ozone is one of six air pollutants designated as harmful by National Ambient Air Quality Standards because it can adversely impact human health and the environment. Thus, ozone forecasting is a critical task that can help people avoid dangerously high ozone concentrations. Conventional numerical approaches, as well as data-driven forecasting approaches, have been studied for ozone forecasting. Data-driven forecasting models, in particular, have gained momentum with the introduction of machine learning advancements. We consider planetary boundary layer (PBL) height as a new input feature for data-driven ozone forecasting models. PBL has been shown to impact ozone concentrations, making it an important factor in ozone forecasts. In this paper, we investigate the effectiveness of utilization of PBL height on the performance of surface ozone forecasts. We present both surface ozone forecasting models, based on multilayer perceptron (MLP) and bidirectional long short-term memory (LSTM) models. These two models forecast hourly ozone concentrations for an upcoming 24-h period using two types of input data, such as measurement data and PBL height. We consider the predicted values of PBL height obtained from the weather research and forecasting (WRF) model, since it is difficult to gather actual PBL measurements. We evaluate two ozone forecasting models in terms of index of agreement (IOA), mean absolute error (MAE), and root mean square error (RMSE). Results showed that the MLP-based and bidirectional LSTM-based models yielded lower MAE and RMSE when considering forecasted PBL height, but there was no significant changes in IOA when compared with models in which no forecasted PBL data were used. This result suggests that utilizing forecasted PBL height can improve the forecasting performance of data-driven prediction models for surface ozone concentrations.

Short-term effects of main air pollutants exposure on LOS and costs of CVD hospital admissions from 30,959 cases among suburban farmers in Pingliang, Northwest China

BACKGROUND

Although cardiovascular disease (CVD) has been the major contributor to global mortality and disability especially in undeveloped and developing countries/areas with severer air pollutions, studies are quite limited and evidence is insufficient of short-term main air pollutants exposure on health burden of CVD hospital admissions in those regions particularly through direct costs.

METHOD

Based on an analysis of 30,959 CVD hospital admissions among suburban farmers from 2018 to 2019 through multiple linear regression (MLR), our study evaluated the impact of main air pollutants (PM_2.5, PM₁₀, SO₂, CO, NO₂ and O₃) exposure on number of cases, length of stay (LOS) and costs of CVD hospital admissions in Pingliang, China.

RESULTS

Concentration of SO₂ and O₃ rising from a low level was found to lower the costs, LOS and daily cases of CVD hospital admissions and PM_2.5, PM₁₀, CO and NO₂ were found to aggravate the burden. Besides, the NO₂ could put more economic stress on those CVD patients in Pingliang (China) which implies that some improvements could be done on public medical insurance policy and benefit local suburban farmers by strengthening the supports on specific drugs and therapies.

CONCLUSIONS

More efforts should be made to lower the concentration of air pollution by coordinated control managements even in a low-level scenario. Concentration levels and interactions between main air pollutants may play an important role in air pollution-induced CVD health burden. Future research is needed to explore more evidence in different areas, especially with low-level SO₂ effects.