This paper firstly explores the space-time evolution of city-level PM 2.5 concentrations showed a very significant seasonal cycle type fluctuation during the period between 13 May 2014 and 30 May 2017. The period from October to April following each year was a heavy pollution period, whereas the phase from April to October of the current year was part of a light pollution period. The average monthly PM 2.5 concentrations in mainland China based on ground monitoring, employing a descriptive statistics method and a Bayesian spatiotemporal hierarchy model. Daily and weekly average PM 2.5 concentrations in 338 cities in mainland China presented no significant spatial difference during the severe polluti...
The air quality in China, particularly the PM2.5 (particles less than 2.5 μm in aerodynamic diameter...
According to the monthly comprehensive air index ranking in China in 2016, Beijing ranked in the bot...
With the explosive economic development of China over the past few decades, air pollution has become...
This paper firstly explores the space-time evolution of city-level PM 2.5 concentratio...
Haze pollution has become a severe environmental problem in the daily life of the people in China. P...
With the rapid industrial development and urbanization in China over the past three decades, PM2.5 p...
PM2.5 is a main source of China’s frequent air pollution. Using real-time monitoring of PM2.5 ...
High-intensity human socioeconomic activities in Xi’an have caused fine particulate matter (PM2.5) p...
Air pollution, which accompanies industrial progression and urbanization, has become an urgent issue...
Ambient particulate matter (PM) pollution of China has become a global concern and has great impact ...
High PM2.5 concentrations and frequent air pollution episodes during late autumn and winter in Jilin...
To investigate the spatiotemporal patterns of fine particulate matter (PM2.5) under years of control...
Air pollution in the form of fine particulate matter, or PM2.5, can decrease human life expectancy a...
National Natural Science Foundation of China 41301380 41371016;Research on PM2.5 Remote Sensing mon...
As China's political and economic centre, the Beijing-Tianjin-Hebei (BTH) urban agglomeration experi...
The air quality in China, particularly the PM2.5 (particles less than 2.5 μm in aerodynamic diameter...
According to the monthly comprehensive air index ranking in China in 2016, Beijing ranked in the bot...
With the explosive economic development of China over the past few decades, air pollution has become...
This paper firstly explores the space-time evolution of city-level PM 2.5 concentratio...
Haze pollution has become a severe environmental problem in the daily life of the people in China. P...
With the rapid industrial development and urbanization in China over the past three decades, PM2.5 p...
PM2.5 is a main source of China’s frequent air pollution. Using real-time monitoring of PM2.5 ...
High-intensity human socioeconomic activities in Xi’an have caused fine particulate matter (PM2.5) p...
Air pollution, which accompanies industrial progression and urbanization, has become an urgent issue...
Ambient particulate matter (PM) pollution of China has become a global concern and has great impact ...
High PM2.5 concentrations and frequent air pollution episodes during late autumn and winter in Jilin...
To investigate the spatiotemporal patterns of fine particulate matter (PM2.5) under years of control...
Air pollution in the form of fine particulate matter, or PM2.5, can decrease human life expectancy a...
National Natural Science Foundation of China 41301380 41371016;Research on PM2.5 Remote Sensing mon...
As China's political and economic centre, the Beijing-Tianjin-Hebei (BTH) urban agglomeration experi...
The air quality in China, particularly the PM2.5 (particles less than 2.5 μm in aerodynamic diameter...
According to the monthly comprehensive air index ranking in China in 2016, Beijing ranked in the bot...
With the explosive economic development of China over the past few decades, air pollution has become...