No abstract

Alteration in Land Use/Cover (LULC) considered a major challenge over the recent decades, as it plays an important role in diminishing biodiversity, altering the macro and microclimate. Therefore, the current study was designed to examine the past 30 years (1987–2017) changes in LULC and Land Surface Temperature (LST) and also simulated for next 30 years (2047). The LULC maps were developed based on maximum probability classification while the LST was retrieved from Landsat thermal bands and Radiative Transfer Equation (RTE) method for the respective years. Different approaches were used, such as Weighted Evidence (WE), Cellular Automata (CA) and regression prediction model for the year 2047. Resultantly, the LULC classification showed increasing trend in built-up and bare soil classes (13 km2 and 89 km2), and the decreasing trend in vegetation class (−144 km2) in the study area. In the next 30 years, the built-up and bare soil classes would further rise with same speed (25 km2 and 36.53 km2), and the vegetation class would further decline (−147 km2) until 2047. Similarly for LST, the temperature range for higher classes (27 -< 30 °C) increased by about 140 km2 during 1987–2017, which would further enlarge (409 km2) until 2047. The lower LST range (15 °C to <21 °C) showed a decreasing trend (−54.94 km2) and would further decline to (−20 km2) until 2047 if it remained at the same speed. Prospective findings will be helpful for land use planners, climatologists and other scientists in reducing the increasing LST associated with LULC changes.

Ambient fine particulate matter (PM2.5) can cause respiratory and heart diseases, which have a great negative impact on human health. While, as a fast-developing region, the Belt and Road (B&R) has suffered serious air pollution, more detailed information has not been revealed. This study aims to investigate the evolutionary relationships between PM2.5 air pollution and its population-weighted exposure level (PWEL) over the B&R based on satellite-derived PM2.5 concentration and to identify the key regions for exposure control in the future. For this, the study focused on the B&R region, covering 51 countries, ranging from developed to least developed levels, extensively evaluated the different development levels of PM2.5 concentrations during 2000–2020 by spatial-temporal trend analysis and bivariate spatial correlation, then identified the key regions with high risk under different levels of Air Quality Guidelines (AQG). Results show that the overall PM2.5 and PWEL of PM2.5 concentration remained stable. Developing countries presented with the heaviest PM2.5 pollution and highest value of PWEL of PM2.5 concentration, while least developed countries presented with the fastest increase of both PM2.5 and PWEL of PM2.5 concentration. Areas with a high level and rapid increase PWEL of PM2.5 concentration were mainly located in the developing countries of India, Bangladesh, Nepal, and Pakistan, the developed country of Saudi Arabia, and least developed countries of Yemen and Myanmar. The key regions at high risk were mainly on the Indian Peninsula, Arabian Peninsula, coastal area of the Persian Gulf, northwestern China, and North China Plain. The findings of this research would be beneficial to identify the spatial distributions of PM2.5 concentration exposure and offer suggestions for formulating policies for the prevention and control PM2.5 air pollution at regional scale by the governments.