区域规划环境评价的空间尺度效应——对上海高桥镇和浦东新区的案例研究

Spatial scale of regional plan environmental impact assessment:the Gaoqiao Town and Pudong New District cases in Shanghai, China

区域规划环境评价的空间特性决定其对空间尺度的敏感性。本文从理论层面对区域规划环评中空间尺度与基础数据的关系、空间尺度与显著环境因子识别以及评价指标体系的关系、空间尺度与大气环境影响预测的关系进行了初步探讨。并以"上海高桥镇区域规划环境影响评价"(2005年)和"上海浦东新区国民经济与社会发展规划战略环境评价"(2010年)为例,通过对比方法,进一步说明空间尺度与显著环境因子识别和评价指标体系以及与环境影响预测的关系。结果表明:基础数据收集、汇总是区域规划环评中极为重要的环节,由于不同类型的基础数据表现出不同的空间特征,需要根据评价区域的实际和评价要求,合理选择数据所涵盖的空间范围和空间分辨率。区域规划环境评价应根据本身的层次、涉及范围,筛选出合理的显著环境因子,并建立相应的评价指标体系。大尺度上环境空气质量预测评价的结果侧重于总体描述、解释污染物散布的宏观空间格局和趋势,而在小尺度上则更有利于揭示局地精细化的污染扩散规律。

The spatial characteristics of Regional Plan Environmental Impact Assessment(RPEIA) determine its sensitivity to spatial scale. Spatial scale of RPEIA is not only a technical issue, but also related to the important questions that RPEIA needs to answer and elaborate. This article discusses the relationship between spatial scale and basic data, the screening of significant environmental factors, and evaluation indicators, as well as the relationship between spatial scale and prediction of atmospheric environmental impact. It then examines two cases: the RPEIA of Gaoqiao Town(2005) and the Strategic Environmental Impact Assessment of the economic and social development plan of Pudong New District, Shanghai(2010) for further elaboration. This article concludes that data collection and integration is a very important step in RPEIA. Different types of basic data posses different spatial characteristics, their spatial scope and resolution should be determined according to the requirements of the RPEIA and regional conditions. The main environmental concerns vary considerably at different spatial scales and they affect the selection of significant environmental factors directly, which in turn affects the corresponding evaluation indicator system. This article also indicates that atmospheric environmental impact prediction and evaluation at large spatial scale focus on the macroscopic description, revealing the general spatial patterns and trends of the spread of air pollutants, while at the local scale is more conducive to explain localized pollution patterns. Emission inventory also emphasizes different spatial characteristics for prediction and evaluation at different scales.