scholarly journals Human appropriation of natural capital: A comparison of ecological footprint and water footprint analysis

2009 ◽  
Vol 68 (7) ◽  
pp. 1963-1974 ◽  
Author(s):  
A.Y. Hoekstra
Keyword(s):  
Ecological Footprint ◽  
Water Footprint ◽  
Natural Capital ◽  
Footprint Analysis

scholarly journals Fairness analysis and compensation strategy in the Triangle of Central China  driven by water-carbon-ecological footprints

2021 ◽  
Author(s):  
Yizhong Chen ◽  
Hongwei Lu ◽  
Jing Li ◽  
Youfeng Qiao ◽  
Pengdong Yan ◽  
...  
Keyword(s):  
Regional Development ◽  
Ecological Footprint ◽  
Water Footprint ◽  
Natural Capital ◽  
Three Dimensional ◽  
Evaluation Framework ◽  
Central China ◽  
Ecological Compensation ◽  
Carbon Footprints ◽  
Ecological Footprints

Abstract This study proposes water–carbon–ecological footprints to form footprint family indicators for identifying the ecological compensation and regional development equilibrium in the Triangle of Central China (TOCC). The occupation of natural capital stock and flow consumption can be illustrated through a three-dimensional ecological footprint model, and Gini coefficient is integrated into the evaluation framework for fairness measurement from various aspects. Quantificational ecological compensation standards can be given with concerns of ecological resource conversion efficiency and willingness to pay indicators. Results reveal that there exit rising trends in ecological and carbon footprints in the TOCC from 2000 to 2015, while its water footprint presents a fluctuating trend. A majority of average Gini coefficients exceed the warning value (i.e., 0.4) under different footprints, implying a relatively poor overall fairness of regional development. In terms of water footprint, the relatively higher compensation expenses exist in Jingmen, Xiangtan, and Yichun, while Yichang, Zhuzhou, and Fuzhou have higher received compensation values as compared with other cities. When it comes to carbon footprint, Wuhan, Loudi, and Xinyu should pay higher compensation expenses due to their overuse of biological resources. The highest amounts of compensation expense appear in Nanchang and Wuhan from the perspective of ecological footprint.

scholarly journals Temporal-Spatial Evolution of the Urban Ecological Footprint Based on Net Primary Productivity: A Case Study of Xuzhou Central Area, China

2019 ◽  
Vol 11 (1) ◽  
pp. 199 ◽  
Author(s):  
Yao Lu ◽  
Xiaoshun Li ◽  
Heng Ni ◽  
Xin Chen ◽  
Chuyu Xia ◽  
...  
Keyword(s):  
Ecological Footprint ◽  
Net Primary Productivity ◽  
Natural Capital ◽  
Net Primary Production ◽  
Central Area ◽  
Human Occupation ◽  
Ecological Capacity ◽  
Xuzhou City ◽  
Footprint Analysis ◽  
Per Capita

The urbanization process all over the world has caused serious ecological and environmental problems which have recently become a focus for study. Ecological footprint analysis, which is widely used to assess the sustainability of regional development, can quantitatively measure the human occupation of natural capital. In this study, the ecological footprint based on net primary production (EF-NPP) and MODIS data were used to measure the ecological footprint in Xuzhou central area from 2005 to 2014. The results showed that from 2005 to 2014, the per capita ecological footprint increased from 1.06 to 1.17 hm2/person; the per capita ecological capacity decreased from 0.10 to 0.09 hm2/person; the per capita ecological deficit increased from −0.96 to −1.09 hm2/person; and the ecological pressure index increased from 6.87 to 11.97. The composition of the ecological footprint showed that grassland contributed most to the ecological footprint and deficit, and cultivated land contributed most to the ecological capacity. The spatial distribution of the ecological footprint changed significantly, especially in the expansion of the area of lower value. The ecological capacity and deficit changed little. The ecological situation in Xuzhou central area was unbalanced. Based on this study, Xuzhou city was recommended to control the increase of the ecological footprint, improve the ecological capacity and balance the ecological pattern for sustainable development.

Temporal Trends in Greenhouse Gas Emissions, Water Footprint, and Ecological Footprint of Food Purchases in Brazilian Metropolitan Areas From 1987 to 2017

2020 ◽  
Author(s):  
Jacqueline Tereza da Silva ◽  
Josefa Maria Felleger Garzillo ◽  
Fernanda Rauber ◽  
Alana Marielle Rodrigues Gald Kluczkovski ◽  
Ximena Schmidt ◽  
...  
Keyword(s):  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Ecological Footprint ◽  
Water Footprint ◽  
Metropolitan Areas ◽  
Temporal Trends ◽  
Gas Emissions ◽  
Food Purchases

Emergy-based ecological footprint analysis for a mega-city: The dynamic changes of Shanghai

2019 ◽  
Vol 210 ◽  
pp. 552-562 ◽  
Author(s):  
Hengyu Pan ◽  
Mufan Zhuang ◽  
Yong Geng ◽  
Fei Wu ◽  
Huijuan Dong
Keyword(s):  
Ecological Footprint ◽  
Dynamic Changes ◽  
Footprint Analysis ◽  
Ecological Footprint Analysis

scholarly journals Water footprint analysis of temporary crops produced in São Carlos (SP), Brazil

RBRH ◽  
2020 ◽  
Vol 25 ◽  
Author(s):  
Alan Reis ◽  
Alessandra Campos dos Santos ◽  
Jamil Alexandre Ayach Anache ◽  
Eduardo Mario Mendiondo ◽  
Edson Cezar Wendland
Keyword(s):  
Crop Yields ◽  
Water Footprint ◽  
Statistical Tests ◽  
Correlation Coefficients ◽  
Mean Values ◽  
Monotonic Trend ◽  
Significant Difference ◽  
Footprint Analysis ◽  
Global Mean ◽  
Total Average

ABSTRACT This paper aims to evaluate the water footprint (WF) of temporary crops produced in the municipality of São Carlos, Brazil, between 2004 and 2017. The WF calculation was developed following the Water Footprint Network approach (WFN) and using CROPWAT model. The results were compared with the world averages and other studies that analyzed the same crops. We applied statistical tests to verify data behavior over the years and calculated correlation coefficients between WF components and crop yields. The results indicated low values of total WF for sugarcane (total average of 166.2 m3 ton-1) and tomato (total average of 97.2 m3 ton-1), while rice (total average of 5212.4 m3 ton-1) and groundnut (total average of 3865.8 m3 ton-1) showed the opposite. In general, WF components do not follow a monotonic trend, a normal distribution can be assumed and there is a statistically significant difference when comparing our findings with global mean values. These results ratify the importance of local WF studies, especially in Brazil, considering its importance in global agricultural market and the respective use of water resources.

Energy and carbon coupled water footprint analysis for Kraft wood pulp paper production

2018 ◽  
Vol 96 ◽  
pp. 253-261 ◽  
Author(s):  
Xiaotian Ma ◽  
Xiaoxu Shen ◽  
Congcong Qi ◽  
Liping Ye ◽  
Donglu Yang ◽  
...  
Keyword(s):  
Water Footprint ◽  
Wood Pulp ◽  
Paper Production ◽  
Pulp Paper ◽  
Footprint Analysis

scholarly journals Carbon Footprint and Built-up Land Footprint: Taipei Case Study

2019 ◽  
Vol 118 ◽  
pp. 03052
Author(s):  
Yung-Jaan Lee
Keyword(s):  
Carbon Footprint ◽  
Ecological Footprint ◽  
Water Footprint ◽  
Statistical Correlation ◽  
Socioeconomic Background ◽  
Bottom Up ◽  
Economic Background ◽  
Daily Water

The purpose of this study is to analyze whether the ecological footprint (EF) of Taipei residents differs between districts. In this study, EFs of residents of 12 districts in Taipei were calculated from the bottom-up approach using 445 questionnaires. The EF consists of six categories, and this study focuses only on the carbon footprint and the footprint of the built-up lands. The personal carbon footprint for Taipei residents is 0.0458 gha. The top five districts with the highest personal daily water footprint are Nangang, Wanhua, Neihu, Beitou and Xinyi. The top five districts with the highest daily carbon footprint are Xinyi, Wanhua, Beitou, Nangang and Shilin. The five districts with the highest daily EF are Xinyi, Wanhua, Beitou, Shilin and Nangang. The socioeconomic background of the respondents does not relate to the size of the water footprint and ecological footprint. Moreover, there is no statistical correlation between the individual’s daily water footprint and daily EF. The socio-economic background of the respondents does not exhibit correlations with the size of the EFs.

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