Spatial and Temporal Characteristics of Environmental Air Quality and Its Relationship with Seasonal Climatic Conditions in Eastern China during 2015-2018

The effect of air pollutants on COPD-hospitalized patients in Lanzhou, China (2015-2019)

Background

Lanzhou is the largest heavy industrial city in northwest China and it is a typical geographical valley-like city. However, there are few studies on the relationship between air pollutants and COPD, and their respective sample sizes are small, resulting in inconsistent results. The aim of this study is to analyze the effects of air pollutants on COPD hospitalizations in Lanzhou, China.

Methods

An ecological time series study with distributed lag non-linear model (DLNM) was used for analysis. Daily COPD hospitalization data in Lanzhou from 1 January 2015 to 31 December 2019 were collected from 25 hospitals, as well as air pollutant data and meteorological data.

Results

A total of 18,275 COPD hospitalizations were enrolled. For 10 μg/m3 increase in PM2.5, PM10, SO2, NO2, and 1 mg/m3 increase in CO at lag 07 day, the RR95%CI of COPD hospitalizations were 1.048 (1.030, 1.067), 1.008 (1.004, 1.013), 1.091 (1.048, 1.135), 1.043 (1.018, 1.068), and 1.160 (1.084, 1.242), respectively. The exposure-response curves between air pollutants (except O3-8h) and COPD hospitalizations were approximately linear with no thresholds. Female, and the harmful effect of PM on aged <65 years, the effect of gaseous pollutant on those aged ≥65 years, were stronger, particularly in the cold season. Exposure to air pollutants (except O3-8h) might increase the risk of COPD hospitalizations. O3-8h has a weak and unstable effect on COPD.

Conclusion

Exposure to air pollutants (except O3-8h) increases the risk of COPD hospitalizations. O3-8h has a weak and unstable effect on COPD hospital admissions. The harmful effect of gaseous pollutants (except O3-8h) on COPD-hospitalized patients was stronger than that of PM.

First temporal distribution model of ambient air pollutants (PM2.5, PM10, and O3) in Yangon City, Myanmar during 2019-2021

Air pollution has emerged as a significant global concern, particularly in urban centers. This study aims to investigate the temporal distribution of air pollutants, including PM2.5, PM10, and O3, utilizing multiple linear regression modeling. Additionally, the research incorporates the calculation of the Air Quality Index (AQI) and Autoregressive Integrated Moving Average (ARIMA) time series modeling to predict the AQI for PM2.5 and PM10. The concentrations and AQI values for PM2.5 ranged from 0 to 93.6 μg/m3 and 0 to 171, respectively, surpassing the Word Health Organization's (WHO) acceptable threshold levels. Similarly, concentrations and AQI values for PM10 ranged from 0.1 to 149.27 μg/m3 and 2-98 μg/m3, respectively, also exceeding WHO standards. Particulate matter pollution exhibited notable peaks during summer and winter. Key meteorological factors, including dew point temperature, relative humidity, and rainfall, showed a significant negative association with all pollutants, while ambient temperature exhibited a significant positive correlation with particulate matter. Multiple linear regression models of particulate matter for winter season demonstrated the highest model performance, explaining most of the variation in particulate matter concentrations. The annual multiple linear regression model for PM2.5 exhibited the most robust performance, explaining 60% of the variation, while the models for PM10 and O3 explained 45% of the variation in their concentrations. Time series modeling projected an increasing trend in the AQI for particulate matter in 2022. The precise and accurate results of this study serve as a valuable reference for developing effective air pollution control strategies and raising awareness of AQI in Myanmar.

Association of air pollutants and hospital admissions for respiratory diseases in Lanzhou, China, 2014-2019

The aim of this study was to assess the effects of air pollutants on hospital admissions for respiratory disease (RD) by using distributed lag nonlinear model (DLNM) in Lanzhou during 2014-2019. In this study, the dataset of air pollutants, meteorological, and daily hospital admissions for RD in Lanzhou, from January 1st, 2014 to December 31st, 2019, were collected from three national environmental monitoring stations, China meteorological data service center, and three large general hospitals, respectively. A time-series analysis with DLNM was used to estimate the associations between air pollutants and hospital admissions for RD including the stratified analysis of age, gender, and season. The key findings were expressed as the relative risk (RR) with a 95% confidence interval (CI) for single-day and cumulative lag effects (0-7). A total of 90, 942 RD hospitalization cases were identified during the study period. The highest association (RR, 95% CI) of hospital admissions for RD and PM_2.5 (1.030, 1.012-1.049), and PM₁₀ (1.009, 1.001-1.015), and NO₂ (1.047, 1.024-1.071) were observed at lag 07 for an increase of 10 μg/m³ in the concentrations, and CO at lag07 (1.140, 1.052-1.236) for an increase of 1 mg/m³ in the concentration. We observed that the RR estimates for gaseous pollutants (e.g., CO and NO₂) were larger than those of particulate matter (e.g., PM_2.5 and PM₁₀). The harmful effects of PM_2.5, PM₁₀, NO₂, and CO were greater in male, people aged 0-14 group and in the cold season. However, no significant association was observed for SO₂, O₃8h, and total hospital admissions for RD. Therefore, some effective intervention strategies should be taken to strengthen the treatment of the ambient air pollutants, especially gaseous pollutants (e.g., CO and NO₂), thereby, reducing the burden of respiratory diseases.

Effect of urban form on PM2.5 concentrations in urban agglomerations of China: Insights from different urbanization levels and seasons

Planned urban form has become an important strategy to improve air quality in urban agglomerations (UAs), especially pollution due to PM_2.5, but the influencing mechanisms are not yet clear. This study explores the relationship between four metrics of urban form (size, fragmentation, shape, and dispersion) as determined by analysis of remotely sensed images at 30-m resolution and PM_2.5 concentrations in 19 Chinese UAs. The influence of level of urban development and season is examined. Five control variables, including population density, temperature, precipitation, wind speed, and the normalized difference vegetation index (NDVI) are selected for use in multiple linear regression models. Size, fragmentation, and shape of urban form, but not dispersion, were found to have significant effects on PM_2.5 concentrations of different urbanization-level UAs. Urban size and fragmentation have stronger impacts on PM_2.5 concentrations in UAs with lower urbanization levels while urban shape has a greater impact in higher-level UAs. In terms of seasonal variation in all UAs, urban form is more pronouncedly associated with PM_2.5 concentrations during spring and autumn than summer and winter. Urban size and fragmentation are positively associated with PM_2.5 concentrations whereas urban shape and dispersion are on the contrary. The relationships between urban form and PM_2.5 uncovered here underscore the importance of urban planning as a tool to minimize PM_2.5 pollution. Specifically, local government should encourage polycentric urban form with lower fragmentation in urban agglomerations. UAs with lower urbanization levels should control the disordered expansion of construction land and higher-level UAs should promote the mix of green land and construction land. Moreover, measures to control air pollution from anthropogenic activities in spring, autumn and winter are likely to be more effective in decreasing PM_2.5 concentrations in UAs.

Ambient gaseous pollutant exposure and incidence of visual impairment among children and adolescents: findings from a longitudinal, two-center cohort study in China

Evidence on the effects of exposure to ambient gaseous pollutants on children's vision was consistently scarce. We aimed to explore the effect of ambient gaseous pollutant exposure on the incidence of visual impairment (VI) in children. From 2005 to 2018, a total of 340,313 children without VI participated in a longitudinal and two-center dynamic cohort. The logMAR acuity was used to assess visual function. The space-time extremely randomized trees model was used to estimate SO₂ and CO exposures levels. The association between SO₂ and CO and VI risks among children was assessed using a proportional hazards model with a restricted cubic spline. Subgroup analyses stratified by gender and grades were used to investigate the differences in an association of SO₂ and CO exposures with childhood VI. A total of 158381 (46.54%) children experienced an new incident VI. A ten-unit (10 μg/m³) increase in SO₂ exposure concentrations was significantly associated with a 1.70 times higher risk of childhood VI. In addition, a 0.1-unit (0.1 mg/m³) increase in CO exposure was significantly associated with a 1.22 times higher risk of childhood VI. The positive association between ambient gaseous pollutants (including SO₂ and CO exposures) and childhood VI risks remained even after adjusting for other environmental variables. An increase in the incidence of VI in children was positively linked to SO₂ and CO exposure. Such evidence might aid governments in developing strategies to interfere with children's eyesight by decreasing air pollution and changing school curricula.

Associations between long-term exposure to ambient air pollution and renal function in Southwest China: The China Multi-Ethnic Cohort (CMEC) study

BACKGROUND

Limited studies have examined associations between air pollutants exposure and renal function, especially in China, with the most extensive chronic kidney disease (CKD) disease burden worldwide.

OBJECTIVES

This study examines associations between long-term exposure to ambient PM_2.5, NO₂, CO, O₃, SO₂ and renal function.

METHODS

We included 80,225 participants aged 30-79 years from the baseline data of the China Multi-Ethnic Cohort (CMEC) study. Three-year average concentrations of PM_2.5, NO₂, CO, O₃, and SO₂ were estimated using satellite-based spatiotemporal models. Renal function is determined by the estimated glomerular filtration rate (eGFR) using Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. After adjusting for covariates, generalized propensity scores (GPS) weighting regression was used to estimate associations between ambient air pollutants and renal function.

RESULTS

An increase of 0.1 mg/m³ CO (OR [odds ratio] =1.20 95% CI [confidence interval], 1.05-1.37) was positively associated with CKD. An increase of 1 μg/m³ in SO₂ (1.07, 1.00-1.14) concentration was positively associated with CKD. An increase of 10 μg/m³ in PM_2.5 (1.17, 0.99-1.38), NO₂ (1.12, 0.83-1.51) and O₃ (1.10, 0.81-1.50) concentration was not associated with CKD. These effects are stronger in those younger than 65, smoking and with low BMI.

CONCLUSIONS

In this study, we found that long-term exposure to ambient CO and SO₂ were positively associated with CKD. Gaseous pollutants should also arouse the concern of relevant departments.

Regional Differences, Distribution Dynamics, and Convergence of Air Quality in Urban Agglomerations in China

The urban agglomeration (UA), with a high concentration of population and economy, represents an area with grievous air pollution. It is vital to examine the regional differences, distribution dynamics, and air quality convergence in UAs for sustainable development. In this study, we measured the air quality of ten UAs in China through the Air Quality Index (AQI). We analyzed regional differences, distribution dynamics, and convergence using Dagum’s decomposition of the Gini coefficient, kernel density estimation, and the convergence model. We found that: the AQI of China’s UAs shows a downward trend, and the index is higher in northern UAs than in southern UAs; the differences in air quality within UAs are not significant, but there is a gap between them; the overall difference in air quality tends to decrease, and regional differences in air quality are the primary contributor to the overall difference; the overall distribution and the distribution of each UA move rightward; the distribution pattern, ductility, and polarization characteristics are different, indicating that the air quality has improved and is differentiated between UAs; except for the Guanzhong Plain, the overall UA and each UA have obvious σ convergence characteristics, and each UA presents prominent absolute β convergence, conditional β convergence, and club convergence.

Interaction of PM2.5 and pre-pregnancy body mass index on birth weight: A nationwide prospective cohort study

BACKGROUND

Fine particulate matter (PM_2.5), one of the most common air pollutants worldwide, has been associated with many adverse birth outcomes in some studies. Pre-pregnancy body mass index (BMI) is an important indicator of maternal obesity that may also contribute to a wide range of birthweight outcomes. Both PM_2.5 and maternal obesity have been found associated with issues on neonatal birthweight respectively, and more attentions and interests are focusing on their combined effect on pregnancy outcomes.

PURPOSE

To explore the modifying effect of pre-pregnancy BMI on the association between gestational PM_2.5 and birthweight; to investigate the interactive effect between gestational PM_2.5 and pre-pregnancy BMI on birthweight among pregnant women during three trimesters and the whole pregnancy.

METHODS

This nationwide cohort study used the National Free Preconception Health Examination Project (NFPHEP) data collected from January 1, 2010, to December 31, 2012. A total population of 248,501 Chinese women from 220 counties registered this project. Pre-pregnancy BMI as a common anthropometric examination was collected during preconception investigation, and gestational PM_2.5 was derived from a hindcast model for historical PM_2.5 estimation from satellite-retrieved aerosol optic depth. Subgroup analysis was conducted to explore a potential modifying effect on the association between PM_2.5 and birthweight during pregnancy by four pre-pregnancy BMI subgroups. Interaction analysis by introducing product terms to multivariable linear regression was also used to examine whether there was an interactive relationship between PM_2.5 and pre-pregnancy BMI.

RESULTS

Totally, 193,461 participants were included in our study. The average concentration of PM_2.5 was 75.33 μg/m³. Higher exposure of PM_2.5 during the entire pregnancy was associated with higher birthweight (17.15 g per 10 μg/m3; 95% CI:16.15, 18.17). Each 10 μg/m³ increase in PM_2.5 during the first, second, and third trimesters was associated with increases in birthweight by 14.93 g (95%CI: 13.96, 15.89), 13.75 g (95% CI: 12.81, 14.69), and 8.79 g (95% CI: 8.09, 9.49), respectively. Higher pre-pregnancy BMI per kg/m² was associated with an increase of birthweight by 7.012 g (95% CI: 6.121, 7.902). Product terms between PM_2.5 and pre-pregnancy BMI were significant for the first, second trimesters, and the entire duration of pregnancy.

CONCLUSIONS

Our results found both gestational PM_2.5 exposure and pre-pregnancy BMI respectively correlated with the increase of birthweight. A negative interaction between pre-pregnancy BMI and gestational PM_2.5 was discovered in term of birthweight gain. Avoidance of high-dose exposure to PM_2.5 during the early and middle stages of pregnancy and pre-pregnancy overweight/obesity may help prevent high birthweight.

Evaluation of the Policy Effect of China's Environmental Interview System for Effective Air Quality Governance

The Ministry of Ecology and Environment of the People's Republic of China formally proposed an environmental interview system in May 2014, which applies pressure on local governments to fulfill their responsibility toward environmental protection by conducting face-to-face public interviews with their officials. In this paper, 48 cities that were publicly interviewed from 2014-2020 were considered the experimental group and 48 cities surrounding them were the control group. First, the dynamic panel model is applied to initially determine the effect of the policy. Then, a regression discontinuity method (Sharp RD) is used to analyze the short-term and long-term effects and compare the reasons for the differences observed among the estimates of various types of samples. Finally, a series of robustness tests were also conducted. The results show that the environmental interview system can improve air quality. However, because an emergency short-term local governance system exists at present, the governance effect is not long-term and, therefore, not sustainable. Therefore, it suggests that the government should continue to improve the environmental interview system, establish an optimal environmental protection incentive mechanism, and encourage local governments to implement environmental protection policies effectively in the long term. The results of the research are of great significance to the environmental impact assessment system of the world, especially in countries with similar economic systems, which are facing a trade-off between economic growth and environmental sustainability.