Trends of PM2.5 concentrations in China: A long term approach

The fast economic growth of China along the last two decades has created a strong impact on the environment. The occurrence of heavy haze pollution days is the most visible effect. Although many researchers have studied such problem, a high number of spatio-temporal limitations in the recent studies were identified. From our best knowledge the long trends of PM2.5 concentrations were not fully investigated in China, in particular the year-to-year trends and the seasonal and daily cycles. Therefore, in this work the PM2.5 concentrations collected from automatic monitors from five urban sites located in megacities with different climatic zones in China were analysed: Beijing (40 degrees N), Chengdu (31 degrees N), Guangzhou (23 degrees N), Shanghai (31 degrees N) and Shenyang (43 degrees N). For an inter-comparison a meta-analysis was carried out. An evaluation conducted since 1999 demonstrates that PM2.5 concentrations have been reduced until 2008, period which match with the occurrence of the Olympic Games. However, a seasonal analysis highlight that such decrease occurs mostly during warmer seasons than cold seasons. During winter PM2.5 concentrations are typically 1.3 to 2.7 higher than in summer. The average daily cycle shows that the lowest and highest PM2.5 concentrations often occurs in the afternoon and evening hours respectively. Such daily variations are mostly driven by the daily variation of the boundary layer depth and emissions. Although the PM2.5 levels have showing signs of improvement, even during the warming season the values are still too high in comparison with the annual environmental standards of China (35 mu g m(-3)). Moreover, during cold seasons the north regions have values twice higher than this limit. Thus, to fulfil these standards the governmental mitigation measures need to be strongly reinforced in order to optimize the daily living energy consumption, primarily in the north regions of China and during the winter periods. (C) 2017 Elsevier Ltd. All rights reserved.