Literature DB >> 24361570

Assessment of water ecological carrying capacity under the two policies in Tieling City on the basis of the integrated system dynamics model.

Shuo Wang1, Ling Xu1, Fenglin Yang2, He Wang3.   

Abstract

Considering the limitation of the traditional method to assess the ecological carrying capacity and the complexity of the water ecological system, we used system dynamics, ANN, and CA-Markov to model a water ecological system. The social component was modeled according to Granger causality test by system dynamics. The natural component consists of the water resource and water environmental capacity, which were forecasted through the prediction of precipitation and change in land use cover. The interaction of the social component and the natural component mainly reflected environmental policies, such as the imposition of an environmental fee and environmental tax based on their values. Simulation results showed the different assessments on water ecological carrying capacity under the two policies. The population grew (2.9 million), and less pollution (86,632.37 t COD and 2854.5 t NH4N) was observed with the imposition of environmental tax compared with the imposition of an environmental fee (2.85 million population, 10,8381 t COD and 3543 t NH4N) at the same GDP level of 585 billion CNY in 2030. According to the causality loop, we discussed the different states under the policies and the reasons that caused the differences in water ecological carrying capacity state. According to game theory, we explained the limitation of the environmental fee policy on the basis of marginal benefit and cost. The externality was cleared up by the environmental tax policy.
Copyright © 2013 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Carrying capacity; Environmental tax; LULC; System dynamics; Tieling City; Water resource

Mesh:

Year:  2013        PMID: 24361570     DOI: 10.1016/j.scitotenv.2013.11.115

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  6 in total

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