Impacts of COVID-19 on Air Quality through Traffic Reduction

Association between traffic-related air pollution and osteoporotic fracture hospitalizations in inland and coastal areas: evidences from the central areas of two cities in Shandong Province, China

Our result showed that short-term exposure to traffic-related air pollutants (TRAPs) might increase the risk of hospitalizations for osteoporotic fractures. It was suggested that government should formulate emission reduction policies to protect the health of citizens.

INTRODUCTION

As the main source of urban air pollution in China, exhaust emissions of motor vehicles have been linked to adverse health outcomes, but evidence of the relationship between short-term exposure to TRAPs and osteoporotic fractures is still relatively rare.

METHODS

In this study, a total of 5044 inpatients from an inland city (Jinan) and a coastal city (Qingdao), two cities with developed transportation in Shandong Province, were included. A generalized additive model (GAM) was used to investigate the association between TRAPs and hospitalizations for osteoporotic fractures. The stratified analyses were performed by gender and age.

RESULTS

Positive associations between TRAPs and osteoporotic fracture hospitalizations were observed. We found that short-term exposure to TRAPs was associated with increased numbers of hospitalizations for osteoporotic fractures. PM2.5 and PM10 were statistically significant associated with hospitalizations for osteoporotic fractures at both single-day and multiday lag structures only in Qingdao, with the strongest associations at lag06 and lag07 [RR=1.0446(95%CI: 1.0018,1.0891) for PM2.5, RR=1.0328(95%CI: 1.0084,1.0578) for PM10]. For NO2 and CO, we found significant associations at lag4 in the single lag structure in Jinan [RR=1.0354 (95%CI: 1.0071, 1.0646) for NO2, RR=1.0014 (95%CI: 1.0002, 1.0025) for CO], while only CO at lag4 was significantly associated with hospitalizations for osteoporotic fractures in Qingdao [1.0038 (1.0012, 1.0063)]. Stratified analyses indicated that the associations were stronger in females and older individuals (65 + years).

CONCLUSION

This study implied that short-term exposure to TRAPs pollution was associated with an increased risk of hospitalizations for osteoporotic fractures. Female patients and patients aged 65 + years appeared to be more vulnerable to TRAPs, suggesting that poor air quality is a modifiable risk factor for osteoporotic fractures.

Evaluation of roadside air quality using deep learning models after the application of the diesel vehicle policy (Euro 6)

Euro 6 is the latest vehicle emission standards for pollutants such as CO, NO2 and PM, that all new vehicles must comply, and it was introduced in September 2015 in South Korea. This study examined the effect of Euro 6 by comparing the measured pollutant concentrations after 2016 (Euro 6-era) to the estimated concentrations without Euro 6. The concentration without Euro 6 was estimated by first modeling the air quality using various environmental factors related to diesel vehicles, meteorological conditions, temporal information such as date and precursors in 2002-2015 (pre-Euro 6-era), and then applying the model to predict the concentration after 2016. In this study, we used both recurrent neural network (RNN) and random forest (RF) algorithms to model the air quality and showed that RNN can achieve higher R2 (0.634 ~ 0.759 depending on pollutants) than RF, making it more suitable for air quality modeling. According to our results, the measured concentrations during 2016-2019 were lower than the concentrations predicted using RNN by - 1.2%, - 3.4%, and - 4.8% for CO, NO2 and PM10. Such reduction can be attributed to the result of Euro 6.

COVID-19 Pandemic, Air Quality, and PM2.5 Reduction-Induced Health Benefits: A Comparative Study for Three Significant Periods in Beijing

Previous studies have estimated the influence of control measures on air quality in the ecological environment during the COVID-19 pandemic. However, few have attached importance to the comparative study of several different periods and evaluated the health benefits of PM2.5 decrease caused by COVID-19. Therefore, we aimed to estimate the control measures' impact on air pollutants in 16 urban areas in Beijing and conducted a comparative study across three different periods by establishing the least squares dummy variable model and difference-in-differences model. We discovered that restriction measures did have an apparent impact on most air pollutants, but there were discrepancies in the three periods. The Air Quality Index (AQI) decreased by 7.8%, and SO2, NO2, PM10, PM2.5, and CO concentrations were lowered by 37.32, 46.76, 53.22, 34.07, and 19.97%, respectively, in the first period, while O3 increased by 36.27%. In addition, the air pollutant concentrations in the ecological environment, including O3, reduced significantly, of which O3 decreased by 7.26% in the second period. Furthermore, AQI and O3 concentrations slightly increased compared to the same period in 2019, while other pollutants dropped, with NO2 being the most apparent decrease in the third period. Lastly, we employed health effects and environmental value assessment methods to evaluate the additional public health benefits of PM2.5 reduction owing to the restriction measures in three periods. This research not only provides a natural experimental basis for governance actions of air pollution in the ecological environment, but also points out a significant direction for future control strategies.