资源环境耗损过程评价方法及其应用

doi:10.18306/dlkxjz.2017.03.011

Abstract

Abstract:

Establishing the mechanism of monitoring and early-warning of resource and environmental carrying capacity is an innovative work of comprehensively deepening reforms in China. An important approach to analyze resource and environmental carrying capacity is to measure the trend of resource and environmental depletion. Based on the three perspectives of resource consumption, environmental damage, and ecological quality change, this study developed an evaluation method of resource and environmental depletion and carried out a trial evaluation in the Beijing-Tianjin-Hebei region. The results show that the developed method is effective to objectively reflect the changing trend of resource and environmental conditions in the Beijing-Tianjin-Hebei region. Trial evaluation shows that in the Beijing-Tianjin-Hebei region, water and soil resource use efficiency is becoming better, 80% units are in the type of high efficiency. Pollutant emission intensity continued to decline in the past decade, but there are also 33% units staying in the type of high intensity. The overall ecological quality is in a state of gradual decline and the average annual rate of decline is 1.2%. From the perspective of indicators combination, units whose water and soil resources utilization efficiency increase at the same time have the largest number. The combination of pollutant emission intensity presents polarization characteristics. Resource and environmental consumption is more intensive in city areas than that in the counties.

Key words: resource and environmental depletion, process evaluation, resource and environmental carrying capacity, evaluation method, Beijing-Tianjin-Hebei region

YU Jianhui, ZHANG Wenzhong, LI Jiaming. Evaluation method of resource and environmental depletion and application[J].PROGRESS IN GEOGRAPHY, 2017, 36(3): 350-358.

Figures/Tables 14

Tab.1

Tab.2

Fig.1

Fig.2

Fig.3

Tab.3

Tab.4

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

Tab.5

Tab.6

References 21

[1]	陈祖海, 雷朱家华. 2015. 中国环境污染变动的时空特征及其经济驱动因素[J]. 地理研究, 34(11): 2165-2178. doi: 10.11821/dlyj201511015
	[Chen Z H, Lei Z J H.2015. The spatial-temporal characteristics and economic drivers of environmental pollution changes in China[J]. Geographical Research, 34(11): 2165-2178.]
[2]	樊杰, 王亚飞, 汤青, 等. 2015. 全国资源环境承载能力监测预警(2014版)学术思路与总体技术流程[J]. 地理科学, 35(1): 1-10.
	[Fan J, Wang Y F, Tang Q, et al.2015. Academic thought and technical progress of monitoring and early-warning of the national resources and environment carrying capacity (V 2014)[J]. Scientia Geographica Sinica, 35(1): 1-10.]
[3]	郭轲, 王立群. 2015. 京津冀地区资源环境承载力动态变化及其驱动因子[J]. 应用生态学报, 26(12): 3818-3826.
	[Guo K, Wang L Q.2015. Change of resource environmental bearing capacity of Beijing-Tianjin-Hebei region and its driving factors[J].Chinese Journal of Applied Ecology, 26(12) : 3818-3826.]
[4]	胡志强, 苗健铭, 苗长虹. 2016. 中国地市尺度工业污染的集聚特征与影响因素[J]. 地理研究, 35(8): 1470-1482. doi: 10.11821/dlyj201608006
	[Hu Z Q, Miao J M, Miao C H.2016. Agglomeration characteristics of industrial pollution and their influencing factors on the scale of cities in China[J]. Geographical Research, 35(8): 1470-1482.]
[5]	刘晓丽, 方创琳. 2008. 城市群资源环境承载力研究进展及展望[J]. 地理科学进展, 27(5): 35-42. doi: 10.11820/dlkxjz.2008.05.005
	[Liu X L, Fang C L.2008. Progress and prospect of study on carrying capacity of resource and environment of city clusters[J]. Progress in Geography, 27(5): 35-42.]
[6]	彭文斌, 吴伟平, 邝嫦娥. 2013. 中国工业污染空间分布格局研究[J]. 统计与决策, 28(20): 115-117.
	[Peng W B, Wu W P, Kuang C E.2013. Zhongguo gongye wuran kongjian fenbu geju yanjiu[J]. Statistics & Decision, 28(20): 115-117.]
[7]	屈小娥. 2017. 陕西省水资源承载力综合评价研究[J]. 干旱区资源与环境, 31(2):91-97.
	[Qu X E.2017. Comprehensive evaluation of water resources carrying capacity in Shaanxi Province[J]. Journal of Arid Land Resources and Environment, 31(2): 91-97.]
[8]	汪自书, 苑魁魁, 吕春英, 等. 2016. 资源环境约束下的北京市人口承载力研究[J]. 中国人口·资源与环境, 26(5): 351-354.
	[Wang Z S, Yuan K K, Lv C Y, et al.2016. Research of population carrying capacity of Beijing based on the resources ＆ environment constraints[J]. China Population, Resources And Environment, 26(5): 351-354.]
[9]	吴玉鸣, 田斌. 2012. 省域环境库兹涅茨曲线的扩展及其决定因素: 空间计量经济学模型实证[J]. 地理研究, 31(4): 627-640. doi: 10.11821/yj2012040006
	[Wu Y M, Tian B.2012. The extension of regional environmental Kuznets Curve and its determinations: An empirical research based on spatial econometrics model[J]. Geographical Research, 31(4): 627-640.]
[10]	向秀容, 潘韬, 吴绍洪, 等. 2016. 基于生态足迹的天山北坡经济带生态承载力评价与预测[J]. 地理研究, 35(5):875-884. doi: 10.11821/dlyj201605006
	[Xiang X R, Pan T, Wu S H, et al.2016. Assessment and prediction of ecological carrying capacity for the Northern Slope Economic Belt of Tianshan Mountains. Geographical Research, 35(5): 875-884.]
[11]	叶文, 王会肖, 许新宜, 等. 2015. 资源环境承载力定量分析: 以秦巴山水源涵养区为例[J]. 中国生态农业学报, 23(8): 1061-1072. doi: 10.13930/j.cnki.cjea.150190
	[Ye W, Wang H X, Xu X Y, et al.2015. Quantitative analysis of resource and environment carrying capacity for water conservation area in Qin-Ba Mountains[J]. Chinese Journal of Eco-Agriculture, 23(8): 1061-1072.]
[12]	于广华, 孙才志. 2015. 环渤海沿海地区土地承载力时空分异特征[J]. 生态学报, 35(14): 4860-4870. doi: 10.5846/stxb201311302853
	[Yu G H, Sun C Z.2015. Land carrying capacity spatiotemporal differentiation in the Bohai sea coastal areas[J]. Acta Ecologica Sinica, 35(14): 4860-4870.]
[13]	张静. 2015. 京津冀一体化政府环境责任问题研究[J]. 法制博览, (8): 136-137.
	[Zhang J.2015. Jingjinji yitihua zhengfu huanjing zeren wenti yanjiu[J]. Legality Vision, (8): 136-137.]
[14]	张燕, 徐建华, 曾刚, 等. 2009. 中国区域发展潜力与资源环境承载力的空间关系分析[J]. 资源科学, 31(8): 1328-1334. doi: 10.3321/j.issn:1007-7588.2009.08.010
	[Zhang Y, Xu J H, Zeng G, et al.2009. The Spatial relationship between regional development potential and resource & environment carrying capacity[J]. Resources Science, 31(8): 1328-1334.]
[15]	张志卫, 丰爱平, 李培英, 等. 2012. 基于能值分析的无居民海岛承载力: 以青岛市大岛为例[J]. 海洋环境科学, 31(4): 572-575, 585. doi: 10.3969/j.issn.1007-6336.2012.04.024
	[Zhang Z W, Feng A P, Li P Y, et al.2012. Carrying capacity of uninhabited island based on energy evaluation: A case of Da Island[J]. Marine Environmental Science, 31(4): 572-575, 585.]
[16]	张子龙, 陈兴鹏, 焦文婷, 等. 2011. 基于能值理论的环境承载力定量评价方法探讨及其应用[J]. 干旱区资源与环境, 25(8): 18-23.
	[Zhang Z L, Chen X P, Jiao W T, et al.2011. Quantitative measure method for environmental carrying capacity and its application: Based on emergy theory[J]. Journal of Arid Land Resources and Environment, 25(8): 18-23.]
[17]	Fang C L, Liu X L.2010. Comprehensive measurement for carrying capacity of resources and environment of city clusters in central China[J]. Chinese Geographical Science, 20(3) :281-288. doi: 10.1007/s11769-010-0281-z
[18]	Grossman G M, Krueger A B.1995. Economic growth and the environment[J]. The Quarterly Journal of Economics, 110(2): 353-377.
[19]	Shen J Y2006. A simultaneous estimation of environmental Kuznets Curve: Evidence from China[J]. China Economic Review, 17(4): 383-394. doi: 10.1016/j.chieco.2006.03.002
[20]	Shi Y S, Wang H F, Yin C Y.2013. Evaluation method of urban land population carrying capacity based on GIS: A case of Shanghai, China[J]. Computers, Environment and Urban Systems, (39): 27-38. doi: 10.1016/j.compenvurbsys.2013.02.002
[21]	Stern D I, Common M S.2001. Is there an environmental Kuznets curve for sulfur[J]. Journal of Environmental Economics and Management, 41(2): 162-178.

概念层	类别层	指标层	指标数据
资源环境耗损指数	资源利用效率变化	城镇土地资源利用效率变化农村土地资源利用效率变化水资源利用效率变化能矿资源利用效率变化	单位GDP建设用地面积变化率单位GDP耕地面积变化率单位GDP用水量变化率单位GDP标准煤耗变化率
	污染物排放强度变化	水污染物排放强度变化大气污染物排放强度变化固体废弃物排放强度变化	单位GDP化学需氧量（COD）排放强度变化率单位GDP二氧化硫（SO₂）排放强度变化率单位GDP固体废弃物排放强度变化率
	生态质量变化	林草质量变化湿地质量变化物种多样性变化气候适宜度变化	林草覆盖变化率湿地面积变化率物种丰富度变化率年平均气温变化率

概念层	类别层	指标层(关键指标)	数据层
资源环境耗损指数	资源利用效率变化	土地资源利用效率变化(建设用地)	10年年均变化率
	资源利用效率变化	水资源利用效率变化(用水量)	10年年均变化率
	污染物排放强度变化	水污染物排放强度变化(COD)	10年年均变化率
	污染物排放强度变化	大气污染物排放强度变化(SO₂)	10年年均变化率
	生态质量变化	林草覆盖率变化	10年年均变化率

指标	类别	指向	阈值标准
资源利用效率变化	低效率类	变化趋差	两类效率变化指标均低于全国平均水平
资源利用效率变化	高效率类	变化趋良	除上述情况外的其他情况
污染物排放强度变化	高强度类	变化趋差	两类强度变化指标均高于全国平均水平
污染物排放强度变化	低强度类	变化趋良	除上述情况外的其他情况
生态质量变化	低质量类	变化趋差	林草覆盖率年均变化率低于全国平均水平
生态质量变化	高质量类	变化趋良	林草覆盖率年均变化率不低于全国平均水平

指数名称	类别	分类标准
资源环境耗损指数	加剧型	三类指数变化中有至少两项均趋向差的方向
资源环境耗损指数	趋缓型	除上述情况外的其他情况

资源环境耗损指数	污染物排放强度变化	资源利用效率变化	生态质量变化	区县个数	占比/%
加剧型	低强度类	低效率类	低质量类	7	23.3
	高强度类	低效率类	低质量类	4	13.3
	高强度类	低效率类	高质量类	10	33.3
	高强度类	高效率类	低质量类	9	30.0
	合计			30	100.0
趋缓型	低强度类	低效率类	高质量类	20	11.6
	低强度类	高效率类	低质量类	33	19.1
	低强度类	高效率类	高质量类	75	43.4
	高强度类	高效率类	高质量类	45	26.0
合计				173	100.0

Evaluation method of resource and environmental depletion and application

RichHTML

PDF (PC)

Like

Knowledge

Cited

Abstract

Cite this article

share this article

Figures/Tables 14

References 21

Related Articles 15

Metrics

Comments

Recommended 0

区域类别	土地面积	年末总人口	第二产业增加值	年末单位从业人员数	固定资产投资
加剧型地区占比/%	11.9	22.0	23.2	18.1	18.0
趋缓型地区占比/%	88.1	78.0	76.8	81.9	82.0

[1]	ZHANG Feng, CHEN Yanguang, LIU Peng. Spatiotemporal relationships between urban system and water system in the Beijing-Tianjin-Hebei region [J]. PROGRESS IN GEOGRAPHY, 2020, 39(3): 377-388.
[2]	LIU Hanchu, FAN Jie, ZHANG Haipeng, Wang Fuyuan. Dynamics of manufacturing industry and change of its spatial pattern in the Pearl River Delta urban agglomeration [J]. PROGRESS IN GEOGRAPHY, 2020, 39(2): 195-206.
[3]	LIU Xiaoxiao, WU Kang. Change of industrial investment networks in the central core area of the Beijing-Tianjin-Hebei region under the background of non-capital function dispersal [J]. PROGRESS IN GEOGRAPHY, 2020, 39(12): 1972-1984.
[4]	FU Hui, LIU Yanjun, SUN Hongri, ZHOU Guolei. Spatiotemporal characteristics and dynamic mechanism of cultivated land use transition in the Beijing-Tianjin-Hebei region [J]. PROGRESS IN GEOGRAPHY, 2020, 39(12): 1985-1998.
[5]	NIU Qiang, SHEN Yingjie, ZHOU Yi, HUANG Jingnan, WANG Pan. Effect and lag period of urban agglomeration construction land growth on economic growth based on lagged variable model:A case study of the Beijing-Tianjin-Hebei urban agglomeration [J]. PROGRESS IN GEOGRAPHY, 2020, 39(10): 1656-1666.
[6]	Xiaoxue SHI, Daoyi GONG, Yihong HU. Regional strong winter wind events over Beijing-Tianjin-Hebei and the associated atmospheric circulation changes during 1979-2017 [J]. PROGRESS IN GEOGRAPHY, 2019, 38(7): 1069-1079.
[7]	Dan CUI, Hao WU, Dianting WU. A review and prospect of regional governance in the Beijing-Tianjin-Hebei region [J]. PROGRESS IN GEOGRAPHY, 2019, 38(1): 1-14.
[8]	Linshan HUANG, Yanguang CHEN, Shuangcheng LI. Multifractal spectral analysis of land use structure of the Beijing-Tianjin-Hebei urban system [J]. PROGRESS IN GEOGRAPHY, 2019, 38(1): 50-64.
[9]	Feng ZHANG, Yanguang CHEN, Xiaosong LI. Radial dimension analysis of growth and form of cities in the Beijing-Tianjin-Hebei region [J]. PROGRESS IN GEOGRAPHY, 2019, 38(1): 65-76.
[10]	Jingtian ZHAO, Yanguang CHEN, Shuangcheng LI. Bi-fractal structure and evolution of the Beijing-Tianjin-Hebei region urban land-use patterns [J]. PROGRESS IN GEOGRAPHY, 2019, 38(1): 77-87.
[11]	Yuqing LONG, Yanguang CHEN. Multi-scaling allometric analysis of the Beijing-Tianjin-Hebei urban system based on nighttime light data [J]. PROGRESS IN GEOGRAPHY, 2019, 38(1): 88-100.
[12]	Lixin SU, Changchun FENG. A comparative study on the regional governance models of the Beijing-Tianjin-Hebei region and several foreign metropolitans [J]. PROGRESS IN GEOGRAPHY, 2019, 38(1): 15-25.
[13]	Qian LI, Haiyang YU, Ting LI, Shuang LONG, Wei SHAO, Ying WANG, Yingjun XU. Hazard assessment of typhoons affecting the Beijing-Tianjin-Hebei region based on Gumbel distribution [J]. PROGRESS IN GEOGRAPHY, 2018, 37(7): 933-945.
[14]	Xiao LI, Yuming SHEN, Ling QIU. Correlation analysis of producer services in the Beijing-Tianjin-Hebei region [J]. PROGRESS IN GEOGRAPHY, 2018, 37(2): 299-307.
[15]	Jie FAN, Kan ZHOU, Yafei WANG. Basic points and progress in technical methods of early-warning of the national resource and environmental carrying capacity (V 2016) [J]. PROGRESS IN GEOGRAPHY, 2017, 36(3): 266-276.