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首页> 外文期刊>Science of the total environment >Spatial patterns and influencing factors of sewage treatment plants in the Guangdong-Hong Kong-Macau Greater Bay Area, China
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Spatial patterns and influencing factors of sewage treatment plants in the Guangdong-Hong Kong-Macau Greater Bay Area, China

机译:广东港澳大湾区污水处理厂的空间模式及影响因素

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摘要

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.
机译:在过去的几年里,中国广东港 - 澳门大湾区(GHMB)的废物和污水排放增加,对生态保护施加了大量压力。在这项研究中,我们专注于实现污水处理厂的平衡空间布局,以揭示GHMB中污水处理厂的区域差异和空间模式,并确定影响空间模式的关键因素。特别是,我们使用POI(兴趣点)地理数据来评估使用探索性空间数据分析(ESDA)在GHMB中污水处理厂的空间模式和聚集状态。然后,我们使用地理加权回归模型(GWR)探索所确定的空间模式的原理影响因素。结果表明:(1)中西部地区的污水处理厂的绝对数量是最高的,而污水处理厂的人均在西北部和西南地区明显地聚集; (2)污水处理厂的绝对数量呈现出比人均值更大的空间异常值,主要分布在江门,佛山,肇庆西部GHMB中的肇庆和低矮的群集中的高高集群类型西部珠江三角洲(PRD)河口; (3)关键的影响因素被确定为人均GDP,主要和二级行业的产值和工业用水量。四个影响因素的高回归系数波动的区域在珠江省河口和邻近地区的集中中央集。建议包括优化污水处理设备布局,提高现有污水处理厂的服务能力潜力,提高产业结构,以促进GHMB中污水处理厂的空间均衡配置。

著录项

  • 来源
    《Science of the total environment》 |2021年第20期|148430.1-148430.11|共11页
  • 作者单位

    Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds Guangzhou 510006 PR China Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) Guangzhou 511458 PR China Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education Guangzhou 510006 PR China;

    School of Environmental Science and Engineering Guangdong University of Technology Guangzhou 510006 PR China;

    Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds Guangzhou 510006 PR China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Sewage treatment plant; Spatial patterns; Cluster type; Driving force; Spatial equilibrium configuration; Guangdong-Hong Kong-Macau Greater Bay Area;

    机译:污水处理厂;空间模式;集群类型;推动力;空间均衡配置;广东港 - 澳门大湾区;

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