Journal articles: 'Ecological footprint'

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CAIRD, SALLY, and ROBIN ROY. "HOUSEHOLD ECOLOGICAL FOOTPRINTS — DEMOGRAPHICS AND SUSTAINABILITY." Journal of Environmental Assessment Policy and Management 08, no. 04 (December 2006): 407–29. http://dx.doi.org/10.1142/s1464333206002591.

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How do demographic factors influence the environmental impacts of households? A major two year study used the ecological footprint technique to measure the environmental impacts of over 1000 UK households. Energy and transport were the biggest contributors to the 'footprint' of households. Rural, and adult households and households with few members had significantly larger per capita ecological footprints than urban/suburban households, households with children and households with several members. Although 11% of these UK households could be regarded as environmentally sustainable, the majority would require a reduction of 60% in ecological footprint to achieve a globally sustainable footprint per person. Consideration is given to the policy implications of demographic influences on household ecological footprints, including personal carbon allowances and house planning and design.

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Li, Ying, Ting Ting Guo, and Pan Pan Li. "Evaluation Analysis of Ecological Footprint Model." Applied Mechanics and Materials 99-100 (September 2011): 487–90. http://dx.doi.org/10.4028/www.scientific.net/amm.99-100.487.

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The conception and calculation of ecological footprint model were concluded. On this basis, the key issue of ecological footprint's calculation was proposed. Advantages and disadvantages of ecological footprint model when it applied in ecological assessment was also proposed. This provides references for application of ecological footprint model's assessment methods.

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Rosenberg, J. ""Ecological Footprint"." Science 275, no. 5303 (February 21, 1997): 1049h—1053. http://dx.doi.org/10.1126/science.275.5303.1049h.

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Lee, Yung-Jaan. "Ecological Footprint and Water Footprint of Taipei." Sustainability 11, no. 20 (October 16, 2019): 5714. http://dx.doi.org/10.3390/su11205714.

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Taiwan suffers from many natural disasters and is vulnerable to climate change. A continuous increase in its ecological footprint (EF) would pose numerous threats to the city. Taipei is Taiwan’s most densely populated city. Whether its citizens are consuming more resources because of their high income and high degree of urbanization, thereby burdening the environment, warrants study. In contrast to most top-down EF analyses, in this study, 445 residents were surveyed to calculate their carbon, built-up land and water footprints. Gender, occupation, age, education level, personal annual income and socio-economic background do not influence water footprint or EF. Moreover, an individual’s water footprint is not correlated with his or her EF. The built-up land footprint that is obtained in this bottom-up study is similar to that in Taiwan’s top-down national footprint account. However, the personal carbon footprint found herein is smaller than that in the national footprint account, because this study asked respondents’ only about consumption related to everyday activities. Since Taipei residents have a high income and high daily consumption, the water footprint herein is larger than the top-down water footprint. This bottom-up EF analysis reflects residents’ daily consumption patterns and can be used in future urban decision-making.

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Zakari, Rozana, Samaneh Zolfagharian, Mehdi Nourbakhsh, Rosli Mohammad Zin, and Masoud Gheisari. "Ecological Footprint of Different Nations." International Journal of Engineering and Technology 4, no. 4 (2012): 464–67. http://dx.doi.org/10.7763/ijet.2012.v4.411.

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Jóhannesson, Sigurður E., Jukka Heinonen, and Brynhildur Davíðsdóttir. "Data accuracy in Ecological Footprint’s carbon footprint." Ecological Indicators 111 (April 2020): 105983. http://dx.doi.org/10.1016/j.ecolind.2019.105983.

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Liu, Xiaoman, Jingying Fu, Dong Jiang, Jianwu Luo, Chenxi Sun, Huiming Liu, Ruihong Wen, and Xuefeng Wang. "Improvement of Ecological Footprint Model in National Nature Reserve Based on Net Primary Production (NPP)." Sustainability 11, no. 1 (December 20, 2018): 2. http://dx.doi.org/10.3390/su11010002.

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An increasing number of nature reserves are being invaded by various development and construction activities, such as energy, resources, and transportation facilities. The ecological footprint model, which enables a quantitative assessment of ecological sustainability, can assess whether human consumption at various spatial scales falls within the regenerative capacity of the biosphere. Based on the traditional ecological footprint evaluation model: the Global Agro-Ecological Zone (EF-GAEZ model), this study proposes an improved ecological footprint model based on net primary productivity (EF-NPP model) and its validations. In this study, the status of ecological footprints and the ecological carrying capacities of 319 national nature reserves in 2010 is explored, and the changes in ecological surpluses and ecological deficits from 2000 to 2010 are analyzed. The ecological footprint per capita and the ecological carrying capacity per capita calculated by the two models were mostly consistently at the same level (more than 68%), which indicated that the ecological footprint per capita and the ecological carrying capacity per capita of the two models followed the same rule. The EF-NPP model can reflect the change in the global climate, the degradation of the soil, and the progress of the technology.

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Vallianatos, E. G. "Humanity's Ecological Footprint." Mediterranean Quarterly 17, no. 3 (July 1, 2006): 65–85. http://dx.doi.org/10.1215/10474552-2006-016.

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Yousaf, Hazrat, Azka Amin, Waqar Ameer, and Muhammad Akbar. "Investigating the determinants of ecological and carbon footprints. Evidence from high-income countries." AIMS Energy 10, no. 4 (2022): 831–43. http://dx.doi.org/10.3934/energy.2022037.

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<abstract> <p>High-income countries have experienced rapid economic growth, urbanization, consumption of renewable and non-renewable energy, increased trade dependency, and the attainment and maintenance of higher living standards over the last four decades, while also experiencing an increasing trend in environmental degradation. These experiences have fueled our desire to learn more about the factors that influence the ecological footprint and carbon footprint of high-income countries. The purpose of the present study is to investigate the effects of natural resources, urbanization, GDP per capita, population, and fossil fuels on ecological and carbon footprint for 34 high-income countries over the period 2003–2015. Using the STIRPAT model, the results confirm the environmental Kuznets curve hypothesis in the case of total ecological footprint while the link between economic growth and carbon footprint is in U-shape. In terms of total ecological footprint determinants, population reduction as well as efficient urban design, are viable solutions. The findings support the positive and statistically significant influence of population, urbanization, and fossil fuels on total ecological footprint, as well as the negative impact of ecological efficiency. The findings of the carbon footprint suggest that reduction in coal and oil consumption, as well as increasing the use of gas as a source of energy, are all viable choices to mitigate carbon footprint. Furthermore, increasing ecological efficiency could be a viable policy option for reducing high-income countries' footprints.</p> </abstract>

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He, Cheng Long, Wen Li Liu, Xin Guo Wu, and Wei Luo. "Regional Environmental Capacity Study for Jiaxing City." Advanced Materials Research 610-613 (December 2012): 961–64. http://dx.doi.org/10.4028/www.scientific.net/amr.610-613.961.

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Jiaxing is listed experiment city of the national ecological civilization construction in 2012. Correctly understand and evaluate the supply of resources and environmental carrying capacity is an important prerequisite of ecologically-civilized city construction. The article structures emergy ecological footprint model combination emergy analysis theory and ecological footprints model.It can quantitative analysis environmental carrying capacity of Jiaxing through comparing ecological carrying capacity and the ecological footprint occupancy. By empirical study, in the rapid development of Jiaxing economy at the same time, ecological deficit has happened in the regions of Jiaxing, total deficit is 3.15 times of the urban area. It shows that industrial structure adjusting of Jiaxing is in a very stressful situation. From ecological deficit proportion of five counties and two districts in Jiaxing to see, Pinghu constitutes 37.63% and Haiyan constitutes 24.65%，the sum up of two counties (city) is to 62.28%. They are the priority counties of the industry structure adjustment.

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Lynch, Michael J., Michael A. Long, Paul B. Stretesky, and Kimberly L. Barrett. "Measuring the Ecological Impact of the Wealthy: Excessive Consumption, Ecological Disorganization, Green Crime, and Justice." Social Currents 6, no. 4 (May 15, 2019): 377–95. http://dx.doi.org/10.1177/2329496519847491.

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Ecological disorganization stemming from conspicuous consumption practices is understudied in the social sciences. In this analysis, we study conspicuous consumption and its implications for environmental sociology, ecological footprint analysis, and green criminology. We examine the issue of conspicuous consumption through the study of items that increase the ecological footprint considerably, that is, through the consumption of “luxury commodities.” Specifically, we draw attention to assessing aspects of ecological footprints of super yachts, super homes, luxury vehicles, and private jets. Taken together, the construction and use of these items in the United States alone is likely to create a CO2 footprint that exceeds those from entire nations. These results are not necessarily surprising but suggest that excessive consumption practices of the wealthy may need to be reinterpreted as criminal when they disrupt the normal regeneration and reproduction of ecosystems by generating excessive ecological disorganization.

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Kaewhao, Sapphasit. "Ecological Footprint Affecting the Pro-environmental Behavior of Undergraduates of Rajabhat Mahasarakham University." Asia Social Issues 15, no. 6 (August 3, 2022): 253995. http://dx.doi.org/10.48048/asi.2022.253995.

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The research objectives were to study Ecological Footprint for Shelter, Ecological Footprint for Food, Ecological Footprint for Transportation, Ecological Footprint for Cloth, Ecological Footprint for Medicine, and Ecological Footprint for Housing and Pro-environmental Behavior levels and to study the independent variables comprise of Ecological Footprint for Shelter, Ecological Footprint for Food, Ecological Footprint for Transportation, Ecological Footprint for Cloth, Ecological Footprint for Medicine and Ecological Footprint for Housing affecting dependent variable of Pro-environmental Behavior of undergraduates. This survey used a questionnaire to gather 400 undergraduates and 10,757 undergraduates of Rajabhat Mahasarakham University in the first semester of the academic year of 2021. The Multi-Stage sampling technique was employed to collect the sample. Multiple Regression Analysis was used to determine the relationship between independent and dependent variables. The results illustrated that in a holistic view of Ecological Footprint for Shelter, Ecological Footprint for Food, Ecological Footprint for Transportation, Ecological Footprint for Cloth, Ecological Footprint for Medicine, and Ecological Footprint for Housing and Pro-environmental Behavior were most levels. Moreover, independent variables of Ecological Footprint for Shelter, Ecological Footprint for Food, Ecological Footprint for Transportation, Ecological Footprint for Cloth, Ecological Footprint for Medicine, and Ecological Footprint for Housing can predict the variation of the dependent variable of Pro-environmental behavior with 65.90 percent of power prediction (Adjusted R2 = 0.659). Ecological Footprint for Food was the highest effect with 0.248.

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Kang, Yan Yan, Jia Lin Wang, and Xiao Dan Yu. "Sustainable Development Analysis of Resources Based City Based on Ecological Footprint Model: Shandong Dongying City." Advanced Materials Research 1010-1012 (August 2014): 1297–300. http://dx.doi.org/10.4028/www.scientific.net/amr.1010-1012.1297.

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Applying ecological footprint model to calculate the ecological footprint and ecological carrying capacity of Dongying ,a typical oil city between the year 2005-2009,the results showed that ecological footprint was deficit in recent years, and the trend had been exacerbated. The economic development of Dongying was in an ecologically unsustainable condition. Measures are put forward to facilitate the sustainable development in two aspects: the reduction of the ecological footprint demand such as industrial structure adjustment, low carbon industry system construction and green life pattern formation; the increase of ecological carrying capacity supply, such as rationally utilizing land and making full use of marine resources.

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Mancini, Maria Serena, Alessandro Galli, Valentina Niccolucci, David Lin, Simone Bastianoni, Mathis Wackernagel, and Nadia Marchettini. "Ecological Footprint: Refining the carbon Footprint calculation." Ecological Indicators 61 (February 2016): 390–403. http://dx.doi.org/10.1016/j.ecolind.2015.09.040.

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Giannetti, Biagio F., Rose Reis De Souza, Marcos J. Alves-Pinto, Cecília M. V. B. Almeida, Feni Agostinho, and Luca Coscieme. "The Ecological Footprint of Happiness: A Case Study of a Low-Income Community in the City of São Paulo, Brazil." Sustainability 14, no. 19 (September 23, 2022): 12056. http://dx.doi.org/10.3390/su141912056.

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An ecological footprint is an accounting tool that reports the balance between resource supply and demand to assess environmental sustainability. Among the many available indicators of social progress, happiness reflects how a person feels about their quality of life. We combined these two approaches to assess the ecological efficiency of social performance in the low-income community of Felicidade, in São Paulo, Brazil, in 2019. We assessed the ecological footprint and gross domestic happiness (GDH) through questionnaires. We found that the community has a lower environmental footprint than higher-income communities in Brazil. However, the per capita ecological footprint in the community is still above what is available per person globally. We found that the community has a high level of life satisfaction (GDH = 0.86) and that the main contributor to happiness is health, time use, psychological wellbeing, education, good governance, and community vitality. The results suggest that other contributors unrelated to income are more robust determinants of happiness. In Brazil, despite higher footprints characterizing higher-income communities, further efforts in low-income communities are needed to reduce environmental footprints, ensure dignified income, and nurture the underlying conditions for high levels of happiness and social capital.

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van Noordwijk, Meine, Thuy T. Pham, Beria Leimona, Lalisa A. Duguma, Himlal Baral, Nikhmatul Khasanah, Sonya Dewi, and Peter A. Minang. "Carbon footprints, informed consumer decisions and shifts towards responsible agriculture, forestry, and other land uses?" Carbon Footprints 1, no. 1 (2022): 4. http://dx.doi.org/10.20517/cf.2022.02.

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The urgent global reduction of greenhouse gas emissions depends on political commitments to common but differentiated responsibility. Carbon footprints as a metric of attributable emissions reflect individually determined contributions within, and aggregated national contributions between, countries. Footprints per unit product (e.g., of food, feed, fuel, or fiber) require a lifecycle analysis and support individual decisions on consumption and lifestyles. This perspective presents a framework for analysis that connects the various operationalizations and their use in informing consumer and policy decisions. Footprints show geographical variation and are changing as part of political-economic and social-ecological systems. Articulation of footprints may trigger further change. Carbon footprints partially correlate with water and biodiversity footprints as related ecological footprint concepts. The multifunctionality of land use, as a solution pathway, can be reflected in aggregated footprint metrics. Credible footprint metrics can contribute to change but only if political commitments and social-cultural values and responsibilities align.

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Zhang, Jinting, F. Benjamin Zhan, Xiu Wu, and Daojun Zhang. "Partial Correlation Analysis of Association between Subjective Well-Being and Ecological Footprint." Sustainability 13, no. 3 (January 20, 2021): 1033. http://dx.doi.org/10.3390/su13031033.

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A spatial-temporal panel dataset was collected from 101 countries during 2006–2016. Using partial correlation (PC) and ordinary correlation (OR) analyses, this research examines the relationship between ecological footprint (EF) and subjective well-being (SWB) to measure environmental impacts on people’s happiness. Gross domestic product (GDP), urbanization rate (UR), literacy rate (LR), youth life expectancy (YLE), wage and salaried workers (WSW), political stability (PS), voice accountability (VA) are regarded as control variables. Total bio-capacity (TBC), ecological crop-land footprints (ECL), ecological grazing-land footprint (EGL), and ecological built-up land footprint (EBL) have significant positive influences on SWB, but ecological fish-land (EFL) has significant negative influences on SWB. Ecological carbon footprint (ECF) is significantly negatively related to SWB in developed countries. An increase in the amount of EF factors is associated with a country’s degree of development. Political social–economic impacts on SWB disguised environmental contribution on SWB, especially CBF impacts on SWB. The use of PC in examining the association between SWB and EF helps bridge a knowledge gap and facilitate a better understanding of happiness.

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Zhang, Xiao Juan. "Research on Sustainable Development Capacity of Yellow River Wetland Based on the Ecological Footprint Model - A Case of Dongying." Advanced Materials Research 749 (August 2013): 110–17. http://dx.doi.org/10.4028/www.scientific.net/amr.749.110.

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The ecological footprint demand and ecological capacity for the six types of productive land during 2005~2010 are calculated using the ecological footprint model in this paper by taking Dongying City as the example, and the ecological deficit of Dongying City is thereby figured out. Based on this, the indicators such as the ecological footprint of 10k yuan GDP, the ecological pressure index, the ecological diversity index, and the social economic development index, etc representing the sustainable development are calculated and analyzed, to learn that it is not allowed to be optimistic about the ecological environment in Dongying in recent years, as the ecological deficit has increased year after year, and the ecological pressure has become heavier and heavier. However, it is learned through analysis of the ecological footprint of 10k yuan GDP and the social economic development index that under the situation when the ecological pressure on economic growth in the ecological economic system of Dongying is increased, a tendency exists for the consumptive and extensive economic growth pattern to gradually step towards the ecologically intensive pattern, but it is still required to make more efforts in the aspects of reducing the ecological footprint demand and improving the ecological capacity.

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Lawton, Graham. "Your pet's ecological footprint." New Scientist 244, no. 3259 (December 2019): 24. http://dx.doi.org/10.1016/s0262-4079(19)32312-7.

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Galli, Alessandro, Mario Giampietro, Steve Goldfinger, Elias Lazarus, David Lin, Andrea Saltelli, Mathis Wackernagel, and Felix Müller. "Questioning the Ecological Footprint." Ecological Indicators 69 (October 2016): 224–32. http://dx.doi.org/10.1016/j.ecolind.2016.04.014.

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Daferera, Maria, Mariam Abaskharoun, and Evangelia Theodoratou. "The Ecological Footprint Nowadays." Open Schools Journal for Open Science 1, no. 3 (May 20, 2019): 60. http://dx.doi.org/10.12681/osj.19737.

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This assessment refers to the ecological footprint which is a way to measure the impacts of human activities on Earth. It basically calculates the demand and consumption that measures the needs of a society, as well as the waste and greenhouse gases that generates daily in productive sea and fertile land areas. Moreover, it measures all the natural resources needed to support the material needs of a population or person through the technology, lifestyle and habits of each country. Subsequently we are going to examine the advantages and disadvantages of the phenomenon that human activities provoke and the ways to eliminate the caused problem. The world-average ecological footprint in 2013 was 2.8 global hectares per person and the average per country ranges from over 10 to under 1 global hectares per person. There is also a high variation within countries, based on individual lifestyle and economic possibilities that we also examine. Summarizing all those effects we are going to analyze open international data as far as the metabolism of the ecological footprint concerns in our word but especially in our country to form prospects for our planet the principles of life cycle assessments with the aid of statistics and charts.

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Venetoulis, Jason, and John Talberth. "Refining the ecological footprint." Environment, Development and Sustainability 10, no. 4 (January 5, 2007): 441–69. http://dx.doi.org/10.1007/s10668-006-9074-z.

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Hussain, Anwar, and Umar Hayat. "A COMPARATIVE ANALYSIS OF ECOLOGICAL FOOTPRINT OF RURAL-URBAN HOUSEHOLDS IN DISTRICT SWAT." Pakistan Journal of Social Research 04, no. 02 (June 30, 2022): 1097–117. http://dx.doi.org/10.52567/pjsr.v4i2.605.

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Ecological footprint (EF) measure how much productive land area is required for producing the products and resources consumed and the waste generated by humans. The problem of ecological overshooting is being faced by many developing countries like Pakistan. According to the Global Footprint Network, Pakistan is one of the ecologically in deficit countries list i.e we are consuming more than the available biocapacity with us. The ecological footprint of Pakistan in 2012 was 0.8 Gha per capita and biocapacity 0.4 Gha per capita. This is high time to think that whether we are living within our ecological limits and how fast humans are depleting the earth’s biosphere. With this background, the present study aims to estimate the ecological footprints at households’ level taking into account the food, housing, transportation, consumer goods and services in district Swat. Besides, the drivers of the ecological footprint and their impact on the ecological footprint was also estimated. This study used primary data which was collected through questionnaire designed by the Stockholm Environment Institute (SEI). To support the analysis, additional information has also been collected through the self-designed questionnaire. The information obtained were converted into EF though calculator of SEI. The analysis was extended to rural and urban areas of district Swat. The study used a sample of 1063 households from 7 tehsils of district Swat. The sample size was proportionally allocated to rural and urban areas of the each tehsil. Accordingly, 744 and 319 households were selected from rural and urban areas respectively. The descriptive statistics alongwith regression model was used for the analysis. The findings revealed that carbon footprint is the major contributor to total EF. The rural households have higher EF than urban households. However, the ecological overshooting is observed in both rural and urban areas. The major influencing factors of the EF in district Swat are income, household size, education, location, (rural or urban), type of food used, fuel consumption, renewable sources of energy, solid waste, home type and size. Based on findings, it is recommended that the households should be encouraged to use renewable sources of energy in homes to reduce their EF. Particularly, the use of solar energy in the large houses should be ensured. The resources use needs to be monitored to reduce ecological overshooting. The waste generated needs to be properly recycled. The increasing carbon footprint should be controlled through sustainable practices in vehicles use and electric appliances at home. The households should be given environmental awareness and education through various means to reduce EF. Keywords:Ecological footprint

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Putri, Nurilla Elysa, Nukmal Hakim, and M. Yamin. "Analisis Jejak Ekologi dan Biokapasitas untuk Pengendalian Banjir di Sumatera Selatan." MIMBAR, Jurnal Sosial dan Pembangunan 32, no. 1 (June 25, 2016): 58. http://dx.doi.org/10.29313/mimbar.v32i1.1729.

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Planning is the beginning of development activities towards sustainable environmental urgently needed and by integrating ecological footprint into development planning in the region, especially the Spatial Plan (RTRW) that is effective and has a strong tenure. This research aims to analyze existing ecological footprint in South Sumatra, to be able to note the condition of regions ecological footprint. Data analysis is carried out through a quantitative analysis, such as calculating where Ecological Footprint (EFA) and Counting Biocapacity (BC). Results of the analysis obtained EF EF = 0.967 and 1.088 that BC = EF <BC which means undershoot, which needs space do not exceed the space available to support the population lives in the region of South Sumatra. Recommendations are given in integrating Ecologicall Footprint in South Sumatra RTRW is making patterns of spatial use directives that integrate the needs of consumption and waste disposal populations, both individually and as a community.

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Gao, Hui Qiao, and Li Na Guo. "The Urban Ecological Footprint Research Based on the Energy Analysis." Advanced Materials Research 518-523 (May 2012): 5631–35. http://dx.doi.org/10.4028/www.scientific.net/amr.518-523.5631.

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On the basis of ecological footprint, the energy analysis theory is used to establish the urban ecological footprint model , the model is used to calculate the ecological footprint of Yantai and measure the regional sustainable development status.The influense that the international trade to the regional ecological footprint is considered in the article.The improved model is applied to analyse the enviroment status of eco-economic system of Yantai in 2008.The results indicate the ecological footprint of Yantai is 12.9082hm2, and the aquatic prdouct is 7.57 hm2occupying 58.6% of the total footprint, the ecological footprint is 0.477 hm2, the ecological footprint is bigger than the ecological capacity.

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Neagu, Olimpia, and Mădălin-Ioan Neagu. "The Environmental Kuznets Curve revisited: economic complexity and ecological footprint in the most complex economies of the world." Studia Universitatis „Vasile Goldis” Arad – Economics Series 32, no. 1 (January 24, 2022): 78–99. http://dx.doi.org/10.2478/sues-2022-0005.

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Abstract The paper examines the Environmental Kuznets Curve (EKC) model in the panel of the most complex economies in the world by considering the ecological footprint as an indicator of environmental degradation and economic complexity - as a variable of interest and expression of structural changes in the economy. The study includes the first 48 complex economies in the world, with positive averages of the Economic Complexity Index (ECI) for 1995-2017. The model of cointegrating polynomial regression (CPR) includes also variables with impact on ecological footprints such as globalization, energy intensity and urbanization. The EKC model is validated in the panel of the 48 complex economies, suggesting that these countries have already reached a development stage enabling them to curb the increasing pollution expressed by ecological footprint. Globalization has a mitigating effect while urbanization and energy intensity have an extension effect on ecological footprint. Policy implications are also included.

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Lustigová, L., and P. Kušková. "Ecological footprint in the organic farming system ." Agricultural Economics (Zemědělská ekonomika) 52, No. 11 (February 17, 2012): 503–9. http://dx.doi.org/10.17221/5057-agricecon.

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This text aims to introduce the results of the ecological footprint (EF) calculations in the system of organic agriculture (OA). The EF is an alternative indicator of the human activity impact on the environment. It is not calculated in monetary units but in hectares as an area needed for resourcing certain production or activity. OA is an agricultural system which respects natural cycles in ecosystems. It is based on old traditions and nowadays, with regard to environmental degradation, comes again forward. The text contains as well the results of some other researches studying mainly energy consumption in agriculture, which is further converted into the EF. The results, however, need to be compared very carefully, since the procedures of calculations as well as the organic farming rules in various countries or particular farms conditions and quality of input data of the mentioned studies may significantly differ. The authors cite them mainly because of illustrative reasons.  

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Yuan, Qing Min, Jun Liu, and Jing Qiu. "Dynamic Analysis of Energy Consumption and Energy Productivity of Tianjin." Advanced Materials Research 869-870 (December 2013): 362–65. http://dx.doi.org/10.4028/www.scientific.net/amr.869-870.362.

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This paper based on ecological footprint model, by using 2001-2011 years of historical statistical data, calculated and dynamic analyzed the energy status of Tianjin. In the process of analysis, the use of energy ecological footprint represents energy consumption, the value of energy ecological footprint and energy ecological footprint intensity indicates energy productivity. The results showed that: During the study period, energy ecological footprint and the value of energy ecological footprint showed an increasing trend, energy ecological footprint intensity is on the decline. These suggests that energy productivity enhances unceasingly. But due to the rapid economic growth, energy consumption for the ecological environment pressure increased. Besides, coal-dominated energy consumption structure is not conducive to achieving sustainable development in Tianjin.

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Ou, Guo Liang, and Shui Kui Tan. "Study on Sustainable Use of Land Based on Ecological Footprint Model: a Case of Shenzhen." Applied Mechanics and Materials 295-298 (February 2013): 2551–56. http://dx.doi.org/10.4028/www.scientific.net/amm.295-298.2551.

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Reasonable use of land or not, directly related to the sustainable development of a country or region. This paper introduced the basic concept, calculation formula and method of the ecological footprint. We calculated the ecological footprint of Shenzhen by application of the ecological footprint model. The results showed that the per capita ecological footprint in Shenzhen in 2011 was approximately 2.486 hm2, while the per capita ecological capacity was approximately 0.0597 hm2, the per capita ecological deficit was approximately -2.433 hm2, and the ecological footprint is about 47.33 times greater than the ecological capacity. Finally, we discussed the limitations of applying the ecological footprint model to judge the sustainable use of land in this paper.

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Rahman, Mahfujur, Shanjida Chowdhury, Nurul Mohammad Zayed, Md. Ali Imran, Iryna Hanzhurenko, and Vitalii Nitsenko. "Does Globalization Trigger an Ecological Footprint? A Time Series Analysis of Bangladesh." Rocznik Ochrona Środowiska 24 (2022): 141–62. http://dx.doi.org/10.54740/ros.2022.011.

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Climate change has become a pitfall towards economic growth, sustainable development, and ecological balance, not different in Bangladesh. This study investigates the relationship between ecological footprint and globalization of Bangladesh in the 1980-2021. Results of Auto-regressive distributed lag mdel (ARDL) bound test confirms long-run relationship among carbon footprint, ecological footprint, globalization, and other control variables. Long-run and short elasticity confirm globalization, population density, energy consumption along political and economic globalization stimulates ecological footprint. On the other hand, economic growth is a culprit of ecological footprint. It reflects alternative signs with an ecological footprint. On carbon footprint, results are similar to ecological footprint except for energy consumption. As ecological footprint increases, people consume more energy in the short run while less energy in long run. Laws enforced in the last or previous decades regarding environmental issues need more strictness and acceptability to utilize energy through advanced technology and robust inflows from the foreign sector.

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Su, Yin, Qifang Zheng, and Shenghai Liao. "Spatio-Temporal Characteristics of Water Ecological Footprint and Countermeasures for Water Sustainability in Japan." International Journal of Environmental Research and Public Health 19, no. 16 (August 20, 2022): 10380. http://dx.doi.org/10.3390/ijerph191610380.

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Water-related problems are mostly caused by water imbalances between supply and demand. This study adopts the ecological footprint method to conduct an empirical study on the sustainable utilization of water resources in Japan. According to the basic principles and calculation methods of water ecological footprint (WEF), the characteristics of Japan’s water ecological footprint were investigated from the time and space dimensions, and a comparative analysis was made with the water ecological footprint of China. The results show that: from 1980 to 2020, the total water ecological footprint in Japan showed a downward trend in both the traditional account and pollutant account, and its spatial pattern was characterized by the relation that the higher the urbanization rate, the larger the water ecological footprint. In terms of water ecological footprint efficiency, Japan’s agricultural water ecological footprint efficiency was the lowest, and the domestic water ecological footprint efficiency was the highest. The water resources policies and measures that Japan and other developing countries should take to ensure the sustainability of water resources were analyzed separately.

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Deng, Chuxiong, Zhen Liu, Rongrong Li, and Ke Li. "Sustainability Evaluation Based on a Three-Dimensional Ecological Footprint Model: A Case Study in Hunan, China." Sustainability 10, no. 12 (November 29, 2018): 4498. http://dx.doi.org/10.3390/su10124498.

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Under the concept of green development, the promotion of ecological sustainable development capability has become an important policy objective of the Chinese government. Based on the three-dimensional ecological footprint model, this paper analyzes the ecological footprint, ecological carrying capacity, and ecological sustainable development capacity of Hunan province from 2005 to 2015. The results show that the total ecological footprint of Hunan increases from 2005 to 2015, in which the forest land ecological footprint accounts for the largest proportion. The ecological footprint depth is always greater than 1, indicating that Hunan has been in a state of ecological deficit; in the context of the distribution, the ecological pressure of Hunan shows a “high in surround while low in central” pattern. The results about the ecological footprint diversity index show that although the ecosystem of Hunan is stability, the level of eco-economic development ability is low. The ecological efficiency represented by GDP per unit of ecological footprint shows that Hunan’s ecological efficiency increases with an average rate of 13.12% annually during 2005–2015 because of the improvement of the factor substitution.

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Lu, Yao, Xiaoshun Li, Heng Ni, Xin Chen, Chuyu Xia, Dongmei Jiang, and Huiping Fan. "Temporal-Spatial Evolution of the Urban Ecological Footprint Based on Net Primary Productivity: A Case Study of Xuzhou Central Area, China." Sustainability 11, no. 1 (January 3, 2019): 199. http://dx.doi.org/10.3390/su11010199.

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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.

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Yıldırım, Durmuş Çağrı, Seda Yıldırım, Seyfettin Erdoğan, Işıl Demirtaş, Gualter Couto, and Rui Alexandre Castanho. "Time-Varying Convergences of Environmental Footprint Levels between European Countries." Energies 14, no. 7 (March 24, 2021): 1813. http://dx.doi.org/10.3390/en14071813.

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This study proposes the time-varying nonlinear panel unit root test to investigate the convergence of ecological foot prints between the EU and candidate countries. Sixteen European countries (such as Albania, Austria, Belgium, Denmark, France, Germany, Greece, Italy, Luxembourg, Netherlands, Poland, Portugal, Romania, Spain, Sweden and Turkey) and analysis periods are selected according to data availability. This study proposes a cross-sectional Panel KSS with Fourier to test the convergence of the ecological footprints. Then, we combine this methodology with the rolling window method to take into account the time-varying stationarity of series. This study evaluated sub-components of ecological footprints separately and provided more comprehensive findings for the ecological footprint. According to empirical findings, this study proves that convergence or divergence does not show continuity over time. On the other side, this study points out the presence of divergence draws attention when considering the properties of the sub-components in general. As a result, this study shows that international policies by EU countries are generally accepted as successful to reduce ecological footprint, but these are not sufficient as expected. In this point, it is suggested to keep national policies to support international policies in the long term.

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Brinzan*, Oana, Eugenia Tigan, and Lucian Halmagean. "ENVIRONMENTAL MONITORING THROUGH ECOLOGICAL FOOTPRINT." Environmental Engineering and Management Journal 4, no. 2 (2005): 229–36. http://dx.doi.org/10.30638/eemj.2005.025.

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Lee, Yung-Jaan. "Hybrid Ecological Footprint of Taipei." Sustainability 14, no. 7 (April 3, 2022): 4266. http://dx.doi.org/10.3390/su14074266.

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The Ecological Footprint (EF) has been effectively used at the global, national and regional levels, but the local EF accounting methods are lacking. The hybrid EF has been developed to calculate the local EF. It combines a “top-down” approach to determining national EF (five components other than Carbon Footprint, CF) with a “bottom-up” approach to determining local CF (food, housing, transportation). The use of the hybrid EF is cost-effective. The hybrid EF reflects the local context and can be used to measure the progress of local sustainable development and as a basis for environmental responsibility. This study uses statistical databases for Taiwan and Taipei to calculate the hybrid EF of Taipei in 2018. The hybrid EF of Taipei was 4.797 global hectares (gha) in that year, of which the top-down national EF was 0.613 gha and the bottom-up local CF was 4.184 gha. The hybrid EF is lower than Taiwan’s EF (6.460 gha), but the local CF is higher than Taiwan’s CF (3.890 gha), reflecting the urban nature and characteristics of Taipei, which has a high density, high income and high consumption expenditure. With respect to the local CF of Taipei, food is associated with the largest component of CF (2.806 gha), and transportation is associated with the second largest component thereof (1.133 gha). Housing is associated with the smallest component (0.245 gha). Based on these results, five refinements of hybrid EF accounting and two application dimensions are proposed. First, whether the hybrid EF captures the lifestyle of the real situation in Taipei warrants further investigation. Second, the components of national EF that are associated with food should be used to accommodate regional differences by applying a scaling factor. Third, Taiwan’s CF in 2018 accounted for 60.2% of its national EF, but Taipei’s CF accounted for 87.2% of its hybrid EF. Fourth, Taipei’s CF associated with housing is low (0.245 gha/person), while the values for eastern European cities are high (3.140 gha/person). Fifth, Taipei citizens have a fairly high CF associated with private vehicles, warranting a follow-up review of urban sustainable transportation policies.

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Lee, Yung-Jaan, Po-Shu Wu, and Lei Chai. "Taiwan’s Ecological Footprint, 2012-2018." E3S Web of Conferences 237 (2021): 04039. http://dx.doi.org/10.1051/e3sconf/202123704039.

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The Ecological Footprint (EF) is a measurement broadly adopted by the international community to measure the progress toward sustainability. Taiwan’s EF methods refer to the annual reports of the Global Footprint Network (GFN). Therefore, the calculation method closely follows international trends and is updated accordingly. Since the first calculation of Taiwan’s EF in 1998, Taiwan’s EF has been revised several times. At present, the EF from 1994 to 2011 can be obtained. The purpose of this study is to update Taiwan’s EF from 2012 to 2018. This study divides the biologically productive lands into six categories. Since there are two different data sources for fishing grounds and carbon emissions, Taiwan’s EF can be calculated with four different results. Overall, Taiwan’s EF shows a slow downward trend from 2012 to 2018. Furthermore, Taiwan’s carbon footprint accounted for about 70% of the EF, followed by the cropland footprint, which accounted for about 20% of the EF. Compared with global trends, Taiwan’s carbon footprint is about 10% higher than the global carbon footprint, indicating that Taiwan’s carbon emissions are higher than the global average. With the global emphasis on carbon reduction, Taiwan needs to focus on improving carbon emissions.

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Stergiou, Eirini, and Stefanos Armakolas. "Ecological Footprint and Sustainable Behavior." International Journal of Smart Education and Urban Society 13, no. 1 (January 2022): 1–15. http://dx.doi.org/10.4018/ijseus.297065.

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Concerns about environmental problems due to rapid economic growth have been undoubtedly increased the past few decades. The conservation of the natural environment and the satisfaction of human needs have attracted a lot of attention from individuals to policymakers. The aim of this paper is to evaluate the effects of environmental education, knowledge, information and lifestyles on ecological behavior and sustainability goals. More specifically, the emergence of a possible relationship between environmental education and sustainability and the correlation of lifestyle and individual attitude with ecological behavior constitute the research questions of our study. The researchers conducted a quantitative analysis by collecting data from 116 questionnaires. The results indicate a lack of knowledge diffusion on environment from schools whilst even though people's emotional commitment and attitude towards environment are significantly augmented, their ecological behavior is erratic in particular occasions.

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Lee, Yung-Jaan, and Li-Pei Peng. "Taiwan’s Ecological Footprint (1994–2011)." Sustainability 6, no. 9 (September 10, 2014): 6170–87. http://dx.doi.org/10.3390/su6096170.

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Dietz, Thomas, Eugene A. Rosa, and Richard York. "Driving the human ecological footprint." Frontiers in Ecology and the Environment 5, no. 1 (February 2007): 13–18. http://dx.doi.org/10.1890/1540-9295(2007)5[13:dthef]2.0.co;2.

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Amin, Samir. "Capitalism and the Ecological Footprint." Monthly Review 61, no. 6 (November 2, 2009): 19. http://dx.doi.org/10.14452/mr-061-06-2009-10_2.

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Carrera-Gómez, Gema, Pablo Coto-Millán, Juan Luis Doménech, Vicente Inglada, Miguel Angel Pesquera González, and Juan Castanedo-Galán. "The Ecological Footprint of Ports." Transportation Research Record: Journal of the Transportation Research Board 1963, no. 1 (January 2006): 71–75. http://dx.doi.org/10.1177/0361198106196300110.

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Lauer, Michelle. "Reducing Health Careʼs Ecological Footprint." AJN, American Journal of Nursing 109, no. 2 (February 2009): 56–58. http://dx.doi.org/10.1097/01.naj.0000345439.68228.a0.

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Cornelia, Piciu Gabriela. "True Cost Economics: Ecological Footprint." Procedia Economics and Finance 8 (2014): 550–55. http://dx.doi.org/10.1016/s2212-5671(14)00127-0.

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Galli, Alessandro, Mathis Wackernagel, Katsunori Iha, and Elias Lazarus. "Ecological Footprint: Implications for biodiversity." Biological Conservation 173 (May 2014): 121–32. http://dx.doi.org/10.1016/j.biocon.2013.10.019.

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熊, 炳桥. "Ecological Footprint of Tianmen City." Sustainable Development 05, no. 03 (2015): 57–66. http://dx.doi.org/10.12677/sd.2015.53009.

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Dakhia, Karima, and Ewa Berezowska‐Azzag. "Urban institutional and ecological footprint." Management of Environmental Quality: An International Journal 21, no. 1 (January 5, 2010): 78–89. http://dx.doi.org/10.1108/14777831011010874.

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Popławski, Łukasz, and Małgorzata Rutkowska. "The ecological footprint of consumption." Studia i Prace WNEiZ 47 (2017): 241–49. http://dx.doi.org/10.18276/sip.2017.47/1-20.

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Liu, Hua, Dan-Yang Li, Rong Ma, and Ming Ma. "Assessing the Ecological Risks Based on the Three-Dimensional Ecological Footprint Model in Gansu Province." Sustainability 14, no. 24 (December 19, 2022): 16995. http://dx.doi.org/10.3390/su142416995.

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It has become a hot topic in sustainable development to determine how to use data series to predict the trajectory of ecological footprints (EFs), precisely map biocapacity (BC), and effectively analyze regional sustainability. The sustainability of the ecological system in Gansu province must be investigated because the province is situated in western China and serves as a significant economic and transportation hub. We used the EF model to compute the per capita EF and BC of Gansu province from 2010 to 2020. We created a three-dimensional ecological footprint (EF3D) model by incorporating the ecological footprint size (EFsize) and ecological footprint depth (EFdepth) into the EF model and the EF3D of Gansu province from 2010 to 2020 was measured. The EF3D value was estimated using the gray GM (1, 1) prediction model in order to determine the sustainability condition of Gansu province during the next ten years. Finally, the risk of ecosystem loss in the province of Gansu was ultimately assessed using an ecological risk model (EVR). The results show that Gansu province’s per capita EF and BC displayed generally rising trends and the province is experiencing unsustainable development. The region’s projected future consumption of natural capital was estimated by the results, and the EF3D of Gansu province is expected to increase significantly in the future. These findings have a certain reference value for adjusting the industrial structure and utilizing resources in Gansu province. Furthermore, these findings will assist Gansu province in achieving sustainable development policy recommendations.

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Zhang, Shuhui, Fuquan Li, Yuke Zhou, Ziyuan Hu, Ruixin Zhang, Xiaoyu Xiang, and Yali Zhang. "Using Net Primary Productivity to Characterize the Spatio-Temporal Dynamics of Ecological Footprint for a Resource-Based City, Panzhihua in China." Sustainability 14, no. 5 (March 6, 2022): 3067. http://dx.doi.org/10.3390/su14053067.

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An ecological footprint is a primary indicator in measuring the sustainability of regional development, especially in resource-based cities. Here, we built an ecological footprint-based framework to assess the sustainability for a resource-based city of Panzhihua, in China. In this framework, a suite of long-term ecological parameters (2000–2020), essentially including Net Primary Productivity (NPP), land cover, as well as social statistical data, was used as the input indices of a provincial hectare ecological footprint model. The model outputs are composed of the ecological footprint (EF), ecological footprint per capita (PEF), ecological capacity (EC), ecological capacity per capita (PEC), ecological deficit/surplus (ED/S), and per capita ecological deficit/surplus (PED/S). Then the sustainable development capability of the city was comprehensively evaluated using a suite of ecological indices, including the ecological pressure index (EPI), ecological footprint per ten thousand GDP (EFG), ecological sustainability index (ESI), and ecological coordination index (ECI). The study reveals that, from 2000–2020, (1) PEC and PED/S presented an increasing trend (0.2401 hm2/person and 2.1421 hm2/person, respectively), while PEF decreased by 1.9 hm2/person. In the case of the ecological deficit, fossil energy land and forest were the dominant land types in controlling the ecological footprint and ecological capacity, (2) EPI and EFG decreased by 6.6381 hm2/person and 2.2462 hm2/person, respectively, and ESI and ECI increased by 0.3436 hm2/person and 0.2897 hm2/person, respectively. These indices also reflect that the utilization rate of natural resources in Panzhihua City has been improved, with enhanced sustainability, as well as a decline in ecological pressure. This ecological footprint-based framework could work as a template for evaluating the sustainability of resource-based cities from positive and negative ecological footprint indices.

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Journal articles on the topic 'Ecological footprint'

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