The official air-quality statistic reported that Beijing had a 9.9% decline in the annual concentration of PM in 2016. While this statistic offered some relief for the inhabitants of the capital, we present several analyses based on Beijing's PM data of the past 4 years at 36 monitoring sites along with meteorological data of the past 7 years. The analyses reveal the air pollution situation in 2016 was not as rosy as the 9.9% decline would convey, and improvement if any was rather uncertain. The paper also provides an assessment on the city's PM situation in the past 4 years.

Background Rapid economic and social development in China has resulted in severe air pollution and consequent adverse impacts on society. The health effects of air pollution have been widely studied. Methods Using information from the China Health and Retirement Longitudinal Study (CHARLS) database, we established a hierarchical linear model combining pollution and socioeconomic and psychosocial variables to examine the effects of air pollution on public health in China. Local air pollution was characterized in multiple dimensions. Results The relationship of health to its determinants greatly differed between Eastern and Central/Western China. Higher education, higher income level, better life satisfaction, and long-term marriage were significantly associated with better health status among Chinese. In addition, regional healthcare resources were positively associated with the health of residents. As indicated by the hierarchical model with health as dependent variable, in Central/Western China, longest duration of good air quality in spring/summer was positively associated with health (estimated coefficient = 0.067, standard error = 0.026), while the mean Air Quality Index (AQI) in autumn/winter was inversely associated with health (estimated coefficient = −0.082, standard error = 0.031). Good air quality in the current study is defined as daily average AQI less than 35. Conclusions Duration (in days) of acceptable air quality was particularly important for improving public health. Future policies should target increased duration of good air quality while managing air pollution by controlling or decreasing severe air pollution.

Transfer and active learning have the potential to accelerate the development of new chemical reactions, using prior data and new experiments to inform models that adapt to the target area...

There have been speculations that the severe air pollution experienced in North China was the act of meteorological change in general and a decreasing northerly wind in particular. We conduct a retrospective analysis on 1979–2016 reanalysis data from ERA‐Interim of European Centre for Medium‐Range Weather Forecasts over a region in North China to detect meteorological changes over the 38 years. No significant reduction in the northerly wind within the mixing layer is detected. Statistically significant increases are detected in the surface temperature, boundary layer height and dissipation, and significant decreases in relative humidity in the region between the first and second 19‐year periods from 1979 to 2016. We build regression models of PM2.5 on the meteorological variables using data in 2014, 2015, and 2016 to quantify effects of the meteorological changes between the two 19‐year periods on PM2.5 under the emission scenarios of 2014–2016. It is found that despite the warming, dew point temperature had been largely kept under control as the region had gotten dryer. This made the effects of temperature warming largely favorable to PM2.5 reduction as it enhances boundary layer height and dissipation. It is found that the meteorological changes would lead to 1.29% to 2.76% reduction in annual PM2.5 averages with January, March, and December having more than 4% reduction in the 3 years. Thus, the meteorological change in North China had helped alleviate PM2.5 to certain extent and should not be held responsible for the regional air pollution problem.