Characteristics of ambient ozone (O3) pollution and health risks in Zhejiang Province

A time-series analysis of short-term ambient ozone exposure and hospitalizations from acute myocardial infarction in Henan, China

Epidemiological studies in recent years have identified an association between exposure to air pollutants and acute myocardial infarction (AMI); however, the association between short-term ozone (O3) exposure and AMI hospitalization remains unclear, particularly in developing countries. Therefore, this study collected information on 24,489 AMI patients, including daily air pollutant and meteorological data in Henan, China, between 2016 and 2021. A distributed lagged nonlinear model combined with a Poisson regression model was used to estimate the nonlinear lagged effect of O3 on AMI hospitalizations. We also quantified the effects of O3 on the number of AMI hospitalizations, hospitalization days, and hospitalization costs. The results showed that single- and dual-pollution models of O3 at lag0, lag1, and lag (01-07) were risk factors for AMI hospitalizations, with the most significant effect at lag03 (RR = 1.132, 95% CI:1.083-1.182). Further studies showed that males, younger people (15-64 years), warm seasons, and long sunshine duration were more susceptible to O3. Hospitalizations attributable to O3 during the study period accounted for 11.66% of the total hospitalizations, corresponding to 2856 patients, 33,492 hospital days, and 90 million RMB. Maintaining O3 at 10-130 µg/m3 can prevent hundreds of AMI hospitalizations and save millions of RMB per year in Henan, China. In conclusion, we found that short-term exposure to O3 was significantly associated with an increased risk of hospitalization for AMI in Henan, China, and that further reductions in ambient O3 levels may have substantial health and economic benefits for patients and local healthcare facilities.

Indoor air concentrations of carbon dioxide (CO2), nitrogen dioxide (NO2), and ozone (O3) in multiple healthcare facilities

This study evaluates indoor air concentrations of CO₂, NO₂, and O₃ and their relationship to other indoor environmental factors in facilities with occupants susceptible to air contaminants, such as hospitals, senior specialized hospitals, elderly care facilities, and postnatal care centers. Indoor air samples were collected from 82 indoor facilities in South Korea and organized by region. Spearman's correlation and Kruskal-Wallis analyses were employed to examine the relationship among and differences between contaminants in the indoor facilities and indoor/outdoor differences of NO₂ and O₃ concentrations. Significant correlations were found between CO₂ and NO₂ concentrations (r² = 0.176, p < 0.01), as well as NO₂ and O₃ concentrations (r² = - 0.289, p < 0.0001). The indoor/outdoor concentration ratios in the indoor facilities were 0.73 for NO₂ and 0.25 for O₃. CO₂ and NO₂ displayed the highest mean concentrations during spring, while O₃ displayed the highest and lowest mean concentrations during fall and summer, respectively. The calculated hazard quotient (HQ) for NO₂ was higher than the acceptable level of 1 in postnatal care centers, thus posing a health risk for children. Study results indicate that efficient ventilation is required to reduce indoor contaminants in multiple healthcare facilities. This study provides a novel approach toward health risk assessment for indoor facilities with susceptible occupants on a large geographical scale.

Maternal ambient air pollution exposure with spatial-temporal variations and preterm birth risk assessment during 2013-2017 in Zhejiang Province, China

Preterm birth (PTB) can give rise to significant neonatal morbidity and mortality, as well as children's long-term health defects. Many studies have illustrated the associations between ambient air pollution exposure during gestational periods and PTB risks, but most of them only focused on one single air pollutant, such as PM_2.5. In this population-based environmental-epidemiology study, we recruited 6275 pregnant mothers in Zhejiang Province, China, and evaluated their gestational exposures to various air pollutants during 2013-2017. Time-to-event logistic regressions were performed to estimate risk associations after adjusting all confounders, and Quasi-AQI model and PCA-GLM analysis were applied to resolve the collinearity issues in multi-pollutant regression models. It was found that gestational exposure to ambient air pollutants was significantly associated with the occurrence of PTB, and SO₂ was the largest contributor with a proportion of 29.4%. Three new variables, prime factor (a combination of PM_2.5, PM₁₀, SO₂, and NO₂), carbon factor (CO), and ozone factor (O₃), were generated by PCA integration, contributing 63.4%, 17.1%, and 19.5% to PTB risks, respectively. The first and third trimester was the most crucial exposure window, suggesting the pregnant mothers better to avoid severe air pollution exposures during these sensitive periods.

Estimation of personal PM2.5 and BC exposure by a modeling approach - Results of a panel study in Shanghai, China

BACKGROUND

Epidemiologic studies of PM_2.5 (particulate matter with aerodynamic diameter ≤2.5 μm) and black carbon (BC) typically use ambient measurements as exposure proxies given that individual measurement is infeasible among large populations. Failure to account for variation in exposure will bias epidemiologic study results. The ability of ambient measurement as a proxy of exposure in regions with heavy pollution is untested.

OBJECTIVE

We aimed to investigate effects of potential determinants and to estimate PM_2.5 and BC exposure by a modeling approach.

METHODS

We collected 417 24 h personal PM_2.5 and 130 72 h personal BC measurements from a panel of 36 nonsmoking college students in Shanghai, China. Each participant underwent 4 rounds of three consecutive 24-h sampling sessions through December 2014 to July 2015. We applied backwards regression to construct mixed effect models incorporating all accessible variables of ambient pollution, climate and time-location information for exposure prediction. All models were evaluated by marginal R² and root mean square error (RMSE) from a leave-one-out-cross-validation (LOOCV) and a 10-fold cross-validation (10-fold CV).

RESULTS

Personal PM_2.5 was 47.6% lower than ambient level, with mean (±Standard Deviation, SD) level of 39.9 (±32.1) μg/m³; whereas personal BC (6.1 (±2.8) μg/m³) was about one-fold higher than the corresponding ambient concentrations. Ambient levels were the most significant determinants of PM_2.5 and BC exposure. Meteorological and season indicators were also important predictors. Our final models predicted 75% of the variance in 24 h personal PM_2.5 and 72 h personal BC. LOOCV analysis showed an R² (RMSE) of 0.73 (0.40) for PM_2.5 and 0.66 (0.27) for BC. Ten-fold CV analysis showed a R² (RMSE) of 0.73 (0.41) for PM_2.5 and 0.68 (0.26) for BC.

CONCLUSION

We used readily accessible data and established intuitive models that can predict PM_2.5 and BC exposure. This modeling approach can be a feasible solution for PM exposure estimation in epidemiological studies.

Ambient air pollution of particles and gas pollutants, and the predicted health risks from long-term exposure to PM2.5 in Zhejiang province, China

In recent years, ambient air has been severely contaminated by particulate matters (PMs) and some gas pollutants (nitrogen dioxide (NO₂) and sulfur dioxide (SO₂)) in China, and many studies have demonstrated that exposure to these pollutants can induce great adverse impacts on human health. The concentrations of the pollutants were much higher in winter than those in summer, and the average concentrations in this studied area were lower than those in northern China. In the comparison between high-resolution emission inventory and spatial distribution of PM_2.5, significant positive linear correlation was found. Though the pollutants had similar trends, NO₂ and SO₂ delayed with 1 h to PM_2.5. Besides, PM_2.5 had a lag time of 1 h to temperature and relative humidity. Significant linear correlation was found among pollutants and meteorological conditions, suggesting the impact of meteorological conditions on ambient air pollution other than emission. For the 24-h trend, lowest concentrations of PM_2.5, NO₂, and SO₂ were found around 15:00-18:00. In 2015, the population attributable fractions (PAFs) for ischemic heart disease (IHD), cerebrovascular disease (stroke), chronic obstructive pulmonary disease (COPD), lung cancer (LC), and acute lower respiratory infection (ALRI) due to the exposure to PM_2.5 in Zhejiang province were 25.82, 38.94, 17.73, 22.32, and 31.14%, respectively. The population-weighted mortality due to PM_2.5 exposure in Zhejiang province was lower than the average level of the whole country-China.