| 基于隐患因素的矿业城市生态安全评价研究 |
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| 引用本文： | 王 耕,高红娟,高香玲,丁晓静.基于隐患因素的矿业城市生态安全评价研究[J].资源科学,2010,32(2):331-337. |
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| 作者姓名： | 王 耕 高红娟 高香玲 丁晓静 |
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| 作者单位： | 1. 辽宁师范大学海洋经济与可持续发展中心,大连,116029;辽宁师范大学城市与环境学院,大连,116029
2. 辽宁师范大学城市与环境学院,大连,116029 |
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| 基金项目： | 国家自然科学基金，教育部社会科学基金，辽宁省教育厅资助项目 |
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| 摘 要： | 本文针对矿业城市中各种灾害因素对生态安全的威胁和影响,从生态隐患视角提出生态安全是隐患因素触发概率、损失度和响应能力的函数,并依据隐患因素触发的空间,从大气圈、水圈、岩石圈、生物圈以及人类活动圈层角度,初步确定基于五大圈层结构的生态安全评价指标体系.利用风险度量与模糊优选理论,提出矿业城市生态安全模糊循环迭代评价模型,并同时可以得到方案隶属度和目标权重,最后将其应用于辽宁省矿业城市生态安全评价中.结果表明,铁法市、抚顺市、阜新市、本溪市和鞍山市生态安全性指数较低,均在0.5以下,且为煤炭一冶金型矿业城市,由于经济的高速发展而带来的资源短缺以及采矿活动造成的环境污染和生态破坏造成了生态安全的巨大压力;葫芦岛市、清原县、瓦房店市、宽句县和凤城市等生态安全性指数较高,其矿业生产涉及有色金属和化工等行业,矿产资源开采量较小,生态安全隐患的影响也较小.该模型科学、实用,为解决矿业城市在决策信息不完全确知情况下的生态安全评价问题提供了理论和途径.
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| 关 键 词： | 隐患因素 生态安全 模糊循环迭代模型 矿业城市 辽宁省 |
| 收稿时间： | 6/5/2009 12:00:00 AM |
An Evaluation of Ecological Security of Mineral-Rich Cities Based on Danger Factors |
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| WANG Geng,GAO Hongjuan,GAO Xiangling and DING Xiaojing.An Evaluation of Ecological Security of Mineral-Rich Cities Based on Danger Factors[J].Resources Science,2010,32(2):331-337. |
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| Authors: | WANG Geng GAO Hongjuan GAO Xiangling and DING Xiaojing |
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| Abstract: | The mineral-rich city is a special type of cities characterized by acute contradictions between economic development and resource and environmental protection. Urban ecosystems are becoming more and more vulnerable. Therefore, ecological disasters and ecological safety issues also become increasingly important. Eco-disasters in mineral-rich cities are quite complex due to the combined effects of the environment and human activities. In the present work, the authors analyzed in detail the factors affecting ecological security, with the aim to provide theoretical and practical basis for ecological security construction in mineral-rich cities. Ecological security is a dynamic process and a continuous function of the security status, risk factors, evolution trends, time, space and security principal. During the course of the interaction between human and the environment, environmental insecurity factors of objective threat to human production, living and livelihood security space are all ecological security risks. Given the disaster factors that influence the ecological security of mineral-rich cities, eco-security is consider the function of the probability of risk factors, the loss and the ability to respond from the ecological danger-risk perspectives. An eco-security assessment indicator system was subsequently developed based on the five-sphere structure consisting of the atmosphere, hydrosphere, lithosphere, biosphere and human activity. Risk measurement and fuzzy optimization theory were also used, and a fuzzy iteration model about ecological security of mineral-rich cities, which gives an objective weight and the relative membership degree of alternative, is presented. Liaoning is a province rich in mineral resources and production and has a long mining history. There are 15 mining counties (cities) and districts accounting for 30% of the land and 20% of the GDP of the province. Data with respect to 19 selected indicators in the study areas were obtained through field investigations and risk statistics in 2007. Occurrence frequency data of all kinds of underlying factors from the atmosphere, lithosphere, hydrosphere and biosphere were from records since year 1949. Data concerning human activities such as environmental pollution and water resources were from Statistical Yearbook since year 1990. Results showed that the ecological security index of Tiefa City, Fushun City, Fuxin City, Benxi City and Anshan City were generally lower than 0.5 as a result of rapid economic development as well as environmental pollution and ecological damage caused by mining activities. The ecological security index of Huludao City, Qinyuan County, Wafangdian City, Kuandian County and Fengcheng City were relatively higher. The production of these cities primarily lies in non-ferrous metal mining and chemical industry, showing a small amount of mineral resources exploitation. |
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| Keywords: | Danger factors Ecological security Fuzzy circular iteration model Mineral-rich cities Liaoning Province |
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