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

Ambient fine particulate matter (PM2.5) 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 PM2.5 and attributable premature mortality across mainland China. In 2016, about 60% of China's population lived in areas with PM2.5 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 PM2.5 exposure in winter, while industrial sources contributed the most (29-51%) in the remaining seasons. The three major sectoral contributors to PM2.5-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.

Reliability and accuracy analysis of time-weighted average exposure to heavy metals based on personal exposure.

Time-weighted average (TWA) exposure has been used as a surrogate for personal air exposure in some large-scale studies. However, the uncertainties of TWA exposure remain to be determined, although its boundedness has been widely recognized. This study aims to evaluate the reliability and accuracy of TWA exposure based on personal exposure. A total of 180 combined indoor-outdoor-personal air samples were collected of six cities during the non-heating and heating periods. The personal exposure levels of Hg, As, Cd, and Pb were 0.16, 21.20, 0.74, and 34.47 ng/m3 in the non-heating period, respectively, but were 0.20, 34.53, 3.45, and 18.59 ng/m3 in the heating period, respectively. The ratios of TWA and personal exposure of heavy metal(loid)s ranged from 0.91 to 1.53. Indoor pollution was the most significant factor of TWA exposure, accounting for 78.3-97.6% and 88.4-98.6% in the heating and non-heating period, respectively. Based on the results of redundancy analysis and risk assessment by TWA exposure, we concluded that TWA exposure could be used for qualitative investigation, as a substitute for personal exposure, but it may result in large bias when used for quantitative investigation. Larger sample size and more exposure scenarios can reduce the estimation error of TWA.

Short-term effects of ambient air pollution and meteorological factors on tuberculosis in semi-arid area, northwest China: a case study in Lanzhou.

To investigate the short-term effects of ambient air pollution and meteorological factors on daily tuberculosis (TB), semi-parametric generalized additive model was used to assess the impacts of ambient air pollutants and meteorological factors on daily TB case from 2005 to 2010 in Chengguan District, Lanzhou, China. Then a non-stratification parametric model and a stratification parametric model were applied to study the interactive effect of air pollutants and meteorological factors on daily TB. The results show that sulfur dioxide (SO2), nitrogen dioxide (NO2), and particulate matter with aerodynamic diameter less than 10µm (PM10) were positively correlated with daily TB case; the excess risk (ER) and 95% confidence interval (CI) were 1.79% (0.40%, 3.20%), 3.86% (1.81%, 5.96%), and 0.32% (0.02%, 0.62%), respectively. Daily TB case was positively correlated with maximum temperature, minimum temperature, average temperature, vapor pressure, and relative humidity, but negatively correlated with atmospheric pressure, wind speed, and sunshine duration. The association with average temperature was the strongest, whose ER and 95% CI were 4.43% (3.15%, 5.72%). In addition, there were significant interaction effects between air pollutants and meteorological factors on daily TB case.