title: [Study on strategies of pollution prevention in coastal city of Zhejiang Province based on scenario analysis].
abstract: Scenario analysis was used to study the environmental burden in a coastal city of Zhejiang province under different patterns of economic development. The aim of this research is to propose advices on decision making by illustrating how to make emissions reduced by transforming the pattern of economic development in a developed coastal area, which had acquired the level of 70 000 yuan GDP per cap. At first, 18 heavy pollution industries were screened out, by referencing total emissions of chemical oxygen demand, ammonia-nitrogen, sulfur dioxide, and nitrogen oxide. Then, a model of scenario analysis and the back-up calculation program were designed to study the sustainable development of the heavy pollution industries. With 2008 and 2015 as the reference year and the target year respectively, emissions of four pollutants mentioned above in the 18 heavy pollution industries in the city were analyzed under six scenarios. The total emissions of 4 pollutants should be reduced to an expectant degree, which is set as the constraint prerequisite of the scenario analysis. At last, some suggestions for decision-making are put forward, which include maintaining a moderate increase rate of GDP around 7%, strengthening the adjustment of economic structure, controlling the increasing rate of industrial added value of the industries with heavy pollution, optimizing the structure of industries with heavy pollution, decreasing the intensity of waste emission by implementing cleaner production to reduce emission produce at the source, and strengthening regulations on the operation of waste treatment plants to further promote the efficiency of waste treatment. Only by implementing such measures mentioned above, can the total emissions of chemical oxygen demand, ammonia-nitrogen, sulfur dioxide, and nitrogen oxide of the 18 industries with heavy pollution in the city be reduced by a 10%, 10%, 5%, and 15% respectively based on the reference year.
authors.affiliation: School of Environment, Tsinghua University, Beijing 100084, China. tianjp@tsinghua.edu.cn
authors.forename: Jin-Ping
authors.initials: JP
authors.lastname: Tian
authors.forename: Lü-Jun
authors.initials: LJ
authors.lastname: Chen
authors.forename: Peng-Fei
authors.initials: PF
authors.lastname: Du
authors.forename: Yi
authors.initials: Y
authors.lastname: Qian
mesh_terms: D002681:China; D002947:Cities; D003661:Decision Support Techniques; D004787:Environmental Pollution / Q000032:analysis / Q000517:prevention & control*; D007220:Industrial Waste / Q000032:analysis / Q000517:prevention & control*; D008962:Models, Theoretical; D010934:Planning Techniques; D018505:Waste Management
chemical_list: D007220:Industrial Waste