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Based on the Moran Index (MI), which reflects the relationship between pollution status and the geographic and spatial characteristics of pollution. This study further discussed the impact of changes in financial and economic structure, pollution and spatial characteristics on urban sewage discharge. The results showed that when the pollution is highly correlated with spatial characteristics, the scale of urban sewage discharge would be larger, and the overall environmental regulatory status of the city would be worse. In terms of regional differences, the distance between cities in the central region and provincial capitals had a negative impact on the efficiency of sewage discharge. Finally, quantile regression found that when the efficiency of urban sewage discharge was in the higher quantile, the growth of labor disposable income and GDP would further enhance the discharge efficiency.

Based on the Moran Index (MI), which reflects the relationship between pollution status and the geographic and spatial characteristics of pollution. This study further discussed the impact of changes in financial and economic structure, pollution and spatial characteristics on urban sewage discharge. The results showed that when the pollution is highly correlated with spatial characteristics, the scale of urban sewage discharge would be larger, and the overall environmental regulatory status of the city would be worse. In terms of regional differences, the distance between cities in the central region and provincial capitals had a negative impact on the efficiency of sewage discharge. Finally, quantile regression found that when the efficiency of urban sewage discharge was in the higher quantile, the growth of labor disposable income and GDP would further enhance the discharge efficiency. [ABSTRACT FROM AUTHOR]

Highlights: [•] We propose the use of a new method named KM-sPC to management class delimitation. [•] KM-sPC uses a multivariate algorithm that takes into account spatial correlation. [•] The new method relies on fuzzy k-means clustering of spatial principal components. [•] Management classes were identified using KM-sPC and unconstrained fuzzy k-means method. [•] Differences in yield data between delineated classes were better shown by KM-sPC. [ABSTRACT FROM AUTHOR]