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Indexed by:期刊论文

Date of Publication:2018-01-01

Journal:RESOURCES CONSERVATION AND RECYCLING

Included Journals:SCIE

Volume:128

Page Number:143-154

ISSN No.:0921-3449

Key Words:Green growth; System dynamics; Scenario analysis; Industrial regions; Liaoning province

Abstract:Green growth is considered a new growth mode to achieve sustainable development worldwide. There are existing studies that analyze the question of how to effectively configure resources, and balance economic development and environmental protection to achieve green growth. However, these studies are mainly focused on discussing effects of three elements on green growth, namely, economy, resources, and environment, without considering dependent interactions among the three elements themselves, and other essential elements, such as population, policy and so on. This paper develops a system dynamics model integrated with five subsystems including economy, population, resources, environment, and policy to investigate pathways towards green growth in a typical Chinese traditional industrial region, Liaoning province. Based on the current policy tools, five path scenarios are considered for policy makers, namely, business as usual scenario, technical innovation scenario, environmental regulations and management scenario, growth demand management scenario, and comprehensive optimization path scenario. Considering respective development objectives of these scenarios, this paper summarizes and analyzes characteristics of the five scenarios by examining long-term prospects of green GDP, energy consumption, and CO2 emissions. According to the ranking results for these five scenarios, with respect to energy consumption per GDP, energy consumption mix, CO2 emissions per GDP, cost of resources and environment, and green GDP per capita, the comprehensive optimization path scenario is identified as the most appropriate and effective to achieve green growth in Liaoning province. Finally, policy implications are offered based on the simulation results. (C) 2016 Elsevier B.V. All rights reserved.