Sustainable Development Potential Assessment of Ninghai County Using an Emergy Ecological Footprint Analysis
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摘要: 应用能值生态足迹模型开展区域可持续发展研究可有效避免传统生态足迹评估方法的不足，更准确地反映地区生态安全状态及可持续发展潜力.以国家“两山”基地——浙江省宁海县为例，利用能值生态足迹模型和生态安全评价模型，通过测算2003—2017年宁海县不同账户/用地类型生态足迹、人均生态足迹盈余/赤字、生态压力指数和生态可持续指数的变化及演变趋势来研究可持续发展潜力变化，旨在为国家“两山”基地生态安全评估和可持续发展提供指导.结果表明：2003—2017年宁海县能源账户人均能值生态足迹变化幅度远大于生物资源账户，各用地类型人均生态足迹占比大小表现为化石能源用地>水域>建设用地>草地>耕地>林地.2003—2017年宁海县人均生态承载力介于2.293~3.571 hm2之间；人均生态足迹介于1.148~4.070 hm2之间，并呈逐渐下降趋势；除2007—2010年外，研究期间其余年份均处于生态盈余状态.生态压力指数和生态可持续指数评估和预测结果表明，宁海县生态系统处于轻度不安全至较安全状态和弱可持续状态，表明近年来宁海县生态状况总体处于安全水平，经济社会发展给当地资源发展带来了一定压力，但生态可持续发展水平不断提升.因此，下一步应坚持生态优先不动摇，建立统一的生态价值核算方法和绿色生态价值考核指标体系；推进地区生态经济政策，促进生态价值的市场化；拓宽“两山”转化路径，提高产业化绿色水平，切实提升宁海县等国家“两山”基地生态环境承载力和可持续发展水平.Abstract: The emergy ecological footprint model is an effective way to avoid the deficiency of traditional ecological footprint methods and accurately assess regional sustainable development potential. As one of the 'Two Mountains' bases, the characteristics and dynamics of sustainable development of Ninghai County in Zhejiang Province have attracted widespread attention. Therefore, the sustainable development potential was assessed through the emergy ecological footprint analysis and based on parameters of the ecological footprint of different accounts/land types, per capita ecological footprint surplus/deficit, ecological pressure index and ecological sustainability index from 2003 to 2017 to provide guidance for the sustainable development of national 'Two Mountains' base. The results showed that, from 2003 to 2017, the per capita ecological footprint of energy account presented greater fluctuations than the biological resource account. Moreover, the ecological footprint per capita of different land use types was ranked as: fossil energy land > water land > construction land > grassland > cultivated land > forestland. From 2003 to 2017, the per capita ecological carrying capacity of Ninghai County was ranged from 2.293 hm2 to 3.571 hm2; the per capita ecological footprint was ranged from 1.148 hm2 to 4.070 hm2, accompanied by a downward trend; totally, the research year studied all in the state of ecological surplus except the year from 2007 to 2010. The ecological pressure index and sustainability index evaluation demonstrated that the ecosystem of Ninghai County was in a slightly unsafe to relatively safe and weakly sustainable state, indicating that the ecological security of the research region has been in a safe state in recent years, while the economic and social development in recent years still have brought some pressure on the local resources and environment, with the ecological sustainability level keeps rising. Therefore, the next step should be aimed at adhering to the ecological priority principle and establishing a unified ecological value evaluation method and a green ecological value assessment index system; promoting regional eco-economic policies and enhancing the marketization of ecological value; broadening the 'Two Mountains' base conversion pathways and optimizing industrial green level, and earnestly enhancing the carrying capacity and sustainable development level of the 'Two Mountains' base ecological environment in Ninghai County and other bases.
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图 1 2003—2017年宁海县产业发展模式及人口数量变化
Figure 1. Industrial development model and population dynamics in Ninghai County from 2003 to 2017
图 2 2003—2017年宁海县不同账户及用地类型生态足迹和人均生态足迹盈余/赤字动态变化分析
Figure 2. Dynamic changes of ecological footprint of different accounts, land use types and per capita ecological surplus/deficit of Ninghai County from 2003 to 2017
图 3 2003—2017年宁海县生态压力指数动态变化
Figure 3. Ecological pressure index dynamics of Ninghai County from 2003 to 2017
图 4 2003—2017年宁海县生态可持续指数动态变化
Figure 4. Ecological sustainability index dynamics of Ninghai County from 2003 to 2017
图 5 基于指数平滑法的2021—2025年宁海县生态压力和可持续指数预测分析
Figure 5. Simulations of ecological pressure index and sustainability index in Ninghai County from 2021 to 2025 based on the exponential smoothing method
可更新资源种类 有效能计算方法 能值转化率/(sej/J) 太阳辐射能 SE = SA×SR 1.00 风能 WE = SA×WS×AH×AD×AS×HG×JK×AM 6.63×102 雨水化学能 CE = SA×AP×GE 1.54×104 雨水势能 PE = SA×H×AP×WD×g 8.89×103 地球旋转能 EE = SA×HF 2.90×104 注：SE、WE、CE、PE、EE分别为太阳辐射能、风能、雨水化学能、雨水势能、地球旋转能，J; SA为研究区面积，m2；SR为太阳光平均辐射量，J/m2；WS为平均风速，m/s; AH为空气层高度，m；AD为空气密度，kg/m3；AS为空气比热，kcal/(kg ·K)；HG为水平温度梯度，K/m；JK为焦耳/千卡比热，J/kcal；AM为年间秒量，s/a；AP为年降雨量，mm；GE为吉布斯自由能，J/kg；H为平均海拔高度，m；WD为雨水密度，kg/m3；g为重力加速度，m/s2；HF为热通量，J/(m2 ·a). 
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表 2 不同用地类型主要产品消费项及相应能值转化率
Table 2. Emergy conversion rates of main product consumption items at different land use types
项目 能值转化率/(sej/J) 用地类型 粮食 8.30×104 耕地 油料 6.90×105 耕地 甘蔗 8.49×104 耕地 蔬菜 2.70×104 耕地 水果 5.30×105 林地 茶叶 2.00×105 林地 油茶籽 6.90×105 林地 笋干 2.70×104 林地 板栗 2.86×105 林地 木材 3.49×104 林地 毛竹 3.49×104 林地 杂竹 3.49×104 林地 肉类 1.70×106 草地 奶类 1.71×106 草地 禽蛋类 2.00×106 草地 水产品 2.00×106 水域 煤炭 3.98×104 化石能源用地 汽油 6.60×104 化石能源用地 柴油 6.60×104 化石能源用地 天然气 4.80×104 化石能源用地 电力 1.59×105 建设用地
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