Study of Reciprocal Effects between Mandatory Pollutant Emissions Reduction Policy and Structural Change within the Manufacturing Sector in a Chinese Coastal Area.

We develop a multicriteria decision-making model coupled with scenario analysis to quantitatively elucidate the reciprocal effect between a mandatory pollutant emissions reduction policy and industrial structure change within the manufacturing sector on the basis of an in-depth study of a well-developed coastal area in East China, Ningbo City, toward 2020. First, 18 two-digit level industries (TDLIs) in the manufacturing sector are screened out due to intensive emissions of the four pollutants (COD, NH3-N, SO2, and NOx). Second, a model is established to identify the optimal solution for the industrial structure adjustment of the 18 TDLIs under two scenarios, the "business-as-usual" scenario and the "industrial structure adjustment" scenario. Both scenarios are expanded into three subscenarios. Quantitative constraint conditions and two criteria are formulated to screen out the optimal solutions. We propose a coefficient of industrial structure adjustment, Ki, which could clearly reflect the policy preference in terms of industrial development and reallocate the quota of the four-pollutant emission among the 18 TDLIs with regards to the different expectations of economy development in 2020. The model will help local authorities make tailored policies to reduce pollution emissions effectively through industrial structure change by delicately allocating the pollutant emission quota and setting reasonable targets of emission intensity reduction among TDLIs. [ABSTRACT FROM AUTHOR]