Search

The increases in the construction of coal-fired power plants (CFPP) in China have caused ecological damage and environmental pollution. It is essential to monitor ecological and environmental conditions with various technical methods. However, the current monitoring systems have major operational problems, including low levels of automation, high operating costs, and inefficient spatial and temporal coverage. The timely development in the Internet of Things (IoT) provides an opportunity to improve the effectiveness of environmental data collection and analysis. This research takes Xilingol as the study area, which is rich in coal resources and one of the principal regions for CFPP construction in China. We deployed relevant sensors in the study area to obtain the information regarding the quality of atmosphere, surface water, groundwater, and soil. The recorded data were transmitted to a central system platform via wireless communication networks and a general packet radio service. The system platform had the following functions: monitoring environmental quality, assessing environmental impact, supporting environmental management and decision-making, analyzing ecological efficiency, and responding environmental emergency. The government, especially environmental protection department and relevant companies, could easily obtain ecological and environmental information by using this IoT-based technical system. [ABSTRACT FROM PUBLISHER]

• Ecosystem services supply, demand, match degree and coordination dynamics were assessed at basin scale and county scale. • Spatially correlations between influencing factors and coupling coordination degree were investigated by mixed effects model. • Different development policies at county scale according to local dynamic of coupling coordination degree and total ES supply-demand match degree were formulated. Accurately quantifying the spatiotemporal patterns in ecosystem service (ES) 1 1 ES-Ecosystem service. supply and demand and their coupling coordination dynamics, as well as identifying the spatial heterogeneity of the influencing factors for coupling coordination degree are necessary for regional sustainable development. This study used the Ulansuhai Basin in Inner Mongolia Province of China as a case to quantify the supply, demand, and supply-demand ratio of ES (meat production, grain production, carbon storage, water yield, nitrogen purification, and phosphorus purification) from 2000 to 2020. The synthesized coefficient of ES supply (ESCI) 2 2 ESCI-Synthesized coefficient of ES supply. and demand (ESDI), 3 3 ESDI-Synthesized coefficient of ES demand. the match degree of total supply and demand (MD), 4 4 MD-Match degree of total ES supply and demand. and the coupling coordination degree (CD) 5 5 CD-Coupling coordination degree between total ES supply and demand. were taken as indices to explore the relationship between the ESCI and ESDI and the coordination relationships. A mixed effects model was used to determine the spatial heterogeneity response of CD to different influencing factors. The results showed that the total ES supply in the Ulansuhai Basin always met the demand. The area with the highest ESCI was always observed in the Urad Front Banner, while Linhe district had the highest ESDI. Although incoordination improved from mild to superior from 2000 to 2020 at the basin scale, significant spatial variations were observed at the county scale. In addition, the variation in CD was significantly correlated with population, followed by precipitation, and cropland area. The findings comprehensively explore the match and coordination between ES supply and demand, and the spatial heterogeneity of the effects of the influencing factors on CD. Our study can contribute to the formulation of future policies for regional ecological restoration and sustainable development. [ABSTRACT FROM AUTHOR]