Spatial patterns and influencing factors of sewage treatment plants in the Guangdong-Hong Kong-Macau Greater Bay Area, China

Over the past few years the discharge of waste and sewage in the Guangdong-Hong Kong-Macau Greater Bay Area (GHMB) of China has increased, exerting a great amount of pressure on ecological protection. In this study, we focus on achieving a balanced spatial layout of sewage treatment plants in order to reveal the regional differences and spatial patterns of sewage treatment plants in the GHMB and identify the key factors influencing the spatial patterns. In particular, we employ POI (point of interest) geographical data to evaluate the spatial patterns and agglomeration status of sewage treatment plants in the GHMB using Exploratory Spatial Data Analysis (ESDA). We then explore the principle influencing factors of the determined spatial patterns using the geographical weighted regression model (GWR). Results demonstrate that: (1) the absolute number of sewage treatment plants is highest in the central and western regions, while the per capita of sewage treatment plants is clearly clustered in the northwest and southwest regions; (2) the absolute number of sewage treatment plants exhibits larger spatial dissimilarity than that of the per capita values, with High-High cluster types principally distributed in the conjunction areas of Jiangmen, Foshan and Zhaoqing in western GHMB and Low-Low clusters in the western Pearl River Delta (PRD) estuary; and (3) the key influencing factors are identified as GDP per capita, the output value of the primary and secondary industries and industrial water consumption. Regions with high regression coefficient fluctuations of the four influencing factors are centralized within the PRD estuary and adjacent regions. Policy recommendations including optimizing the sewage treatment plant layout, enhancing the service capacity potential of the existing sewage treatment plants and upgrading the industrial structure are proposed to promote a spatial equilibrium configuration of sewage treatment plants in the GHMB. (c) 2021 Elsevier B.V. All rights reserved.