Spatiotemporal characteristics and driving factors of chemical oxygen demand emissions in China’s wastewater: An analysis based on spatial autocorrelation and geodetector

Abstract

The advancement of industrialization and urbanization has exacerbated global water pollution. Chemical Oxygen Demand (COD) serves as a crucial metric for assessing organic contamination in aquatic environments. Consequently, the spatiotemporal characteristics and driving factors of COD emissions have emerged as a significant area of current research interest. This study employs spatial autocorrelation and geodetector methods to rigorously analyze the spatial–temporal patterns and principal drivers of COD emissions in China’s wastewater, drawing on eleven geographic and socio-economic datasets spanning from 2011 to 2019. This study indicates that COD emissions in China’s wastewater have consistently decreased annually between 2011 and 2019, with a marked reduction observed post-2016. Regarding spatial distribution, COD emissions in the eastern region significantly surpass those in the western region, highlighting pronounced regional disparities. The analysis of the global Moran’s Index indicates that the COD emissions across China’s provincial regions demonstrate spatial clustering of similar values, with this clustering intensifying annually. Furthermore, the local Moran’s Index identifies the precise locations of these spatial clusters. Geodetector analysis identified that the consumption of nitrogen fertilizers and the consumption of chemical fertilizers had substantial impacts on COD emissions, whereas the proportion of urban population at year-end and the number of granted inventions exerted lesser effects. Furthermore, the interaction between two factors notably enhances the explanatory power regarding COD emissions. This research underpins the formulation of efficacious pollution control and environmental protection strategies, contributing vital insights for the stewardship of water quality.