摘要
我国在未来的20~30年仍将保持工业化的快速发展,这意味着我国许多地区将长期面临十分严峻的工业污染压力。由于在区域工业发展的规划阶段新增企业的空间布局具有显著的不确定性,从而形成了空间分布不确定的区域污染压力。仅依靠工艺改造和末端治理的策略满足不了这种区域工业污染防治的需要,而应在战略环境评价(SEA)层面上考虑依靠土地利用规划控制,以及产业、环境政策调控等策略,从源头上有效进行污染防治。
本论文建立了一套基于风险评估的战略环境评价方法,能够对不确定的区域工业发展空间布局及污染排放进行定量化的模拟,从而识别区域污染压力的风险特征,并分析如何借助土地利用规划调整和有关政策调控策略来进行风险控制。其中的模拟系统以对于政府管理下的企业主体的工业项目投资、空间选址、污染排放行为的微观模拟为核心,考虑了一系列工业发展规划、政策信息对微观主体的影响。模拟系统采用Monte-Carlo方法对微观主体行为进行随机模拟,自下而上地累加得到区域未来工业发展的空间布局及污染排放的大样本情景。
本论文以四川德阳市为研究案例,根据其近五年的历史数据,对微观模拟系统的模型参数进行了识别。将此参数取值作为基准情景模拟的设置条件;在此参数取值基础上进行扰动作为行业内经济结构、工业集中发展布局、环境管理政策调控情景模拟的设置条件,分别生成重点行业未来五年新增工业的空间布局和COD污染排放的大样本情景,基于COD需减排量的概率分布识别了区域污染压力的风险特征。各情景风险特征的差异体现了政策调控策略的风险控制效果;通过限制工业用地规模规避环境不安全的样本和污染压力较重的样本,则实现了土地利用规划调整策略的风险控制效用。
The fast industriliazation in China will last for the next 20~30 years, bring about the severe pollution pressure that many regions in the country have to face. During the planning of regional industrial development, the new invested enterprises’spatial distribution is of big uncertainty. It forms the uncertain spatial distribution of regional pollution pressure. It is not enough that only relying on the processing technology modification or end-pipe treatment to fulfill the demand of controlling this type of regional industrializing pollution pressure. However, measures on the level of Strategic Environmental Assessment (SEA) such as landuse planning and industrial, environmental policies should be considered, for a source control of pollution.
The thesis establishs a methodology for SEA based on the risk evaluation. It quantatively simulates the uncertain spatial distribution of regional industrial development and pollution emission, identifies the risk characteristics of pollution pressure. After that, landuse planning and policy adjustment measures are analyzed for risk control. The core of the simulation system is the micro-simulation of the industrial enterprises’investment, location choice and pollution emission behaviors under the government’s regulation. Series of plans and policies’impact on the micro agents are involved. By the Monte-Carlo method, the system randomly simulates the micro agents’behaviors, which are aggregated in a bottom-up way to raise a large sampling of regional industrial development’s spatial distribution and pollution emission in the future.
Deyang city in Sichuan Province is the case study area. Based on its historic data in the past five years, the parameters of the models in the micro-simulation system were calibrated. This group of parameters’value is set for the the baseline scenario simulation. The parameters’value for baseline scenario was disturbed for policy adjustment scenarios of inner-sectoral economic structure, industrial concerntrated development, and environmental regulation. The simulated output is the large sampling of the major industrial sectors’spatial distribution and COD emission in the future five years. The regional pollution pressure’s risk characteristics are identified based on the probability distribution of the required COD emission reduction. The difference among the scenarios’simulation outputs indicates the risk control effect of policies’adjustment measures. By restricting the indusrial land use to avoid environmental insecure and high emission-loaded samples, the land use planning measure works for the pollution risk control.
引文
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