Bin He

TL;DR: Suggestions on future research and major meteorological approaches for mitigating PM2.5 pollution are made and causality analysis methods are found more suitable for extracting the influence of individual meteorological factors whilst statistical models are good at quantifying the overall effect of multiple meteorological Factors on PM 2.5.

TL;DR: In this paper, the authors proposed a more precise spherical area-based statistical method to identify the world's severely drought-prone areas, given that the corresponding ground area for a 0.5-degree grid in different latitudes is different.

TL;DR: In this article, the authors assessed vegetation changes both temporally and spatially in the areas under the Beijing-Tianjin Sand Source Control Program from 2000 to 2010 with the Moderate-resolution Imaging Spectroradiometer (MODIS) monthly Normalized Difference Vegetation Index (NDVI) data and trend analysis method.

TL;DR: Wang et al. as mentioned in this paper employed the CCM (convergent cross-mapping) method to understand the influence of individual meteorological factors on local PM2.5 concentrations in 188 monitoring cities across China.

TL;DR: Based on the monthly precipitation data for the period 1960-2008 from 616 rainfall stations and the phenology data of main grain crops, the spatial characteristics of drought hazard in China were investigated at a 10 km×10 km grid-cell scale using a GIS-based drought hazard assessment model, which was constructed by using 3-month Standard Precipitation Index (SPI) as mentioned in this paper.