4.8 Article

Regional risk assessment approaches to land planning for industrial polluted areas in China: The Hulunbeier region case study

期刊

ENVIRONMENT INTERNATIONAL
卷 65, 期 -, 页码 16-32

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.envint.2013.12.004

关键词

Spatial regional risk assessment; Industrial pollution; Regional land planning

资金

  1. European Union [269233 - GLOCOM]

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The rapid industrial development and urbanization processes that occurred in China over the past 30 years has increased dramatically the consumption of natural resources and raw materials, thus exacerbating the human pressure on environmental ecosystems. In result, large scale environmental pollution of soil, natural waters and urban air were recorded. The development of effective industrial planning to support regional sustainable economy development has become an issue of serious concern for local authorities which need to select safe sites for new industrial settlements (i.e. industrial plants) according to assessment approaches considering cumulative impacts, synergistic pollution effects and risks of accidental releases. In order to support decision makers in the development of efficient and effective regional land-use plans encompassing the identification of suitable areas for new industrial settlements and areas in need of intervention measures, this study provides a spatial regional risk assessment methodology which integrates relative risk assessment (RRA) and socioeconomic assessment (SEA) and makes use of spatial analysis (GIS) methodologies and multicriteria decision Analysis (MCDA) techniques. The proposed methodology was applied to the Chinese region of Hulunbeier which is located in eastern Inner Mongolia Autonomous Region, adjacent to the Republic of Mongolia. The application results demonstrated the effectiveness of the proposed methodology in the identification of the most hazardous and risky industrial settlements, the most vulnerable regional receptors and the regional districts which resulted to be the most relevant for intervention measures since they are characterized by high regional risk and excellent socio-economic development conditions. (C) 2013 Elsevier Ltd. All rights reserved.

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