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Ecological footprint is a way of measuring urban and regional ecological impacts and guides communities toward sustainability. This Technique measures how much land is required to supply our living and lifestyle including food, housing, energy/fuel, transport, and consumer goods and services along with their corresponding energy requirements. This...
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Using China as a case study, the questions addressed in this chapter are: (a) what are the factors behind the development of the housing market and how is this major emerging economy managing its real estate (RE) market? and (b) what will be the effect of a downturn in the housing market and in turn its impact on the construction industry and the r...
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... Moreover, most of the previous studies evaluate the relation of ecological degradation and economic development at the level of a single city or group of countries e.g., Ref [18][19][20][21]. For the studies at the city level, data availability and reliability are most significant problems [22], while studies on groups might fail to catch some important local realities that are crucial for both precise scientific assessment and finding a solution for environmental problems [15]. ...
... Moreover, most of the previous studies evaluate the relation of ecological degradation and economic development at the level of a single city or group of countries e.g., Ref [18][19][20][21]. For the studies at the city level, data availability and reliability are most significant problems [22], while studies on groups might fail to catch some important local realities that are crucial for both precise scientific assessment and finding a solution for environmental problems [15]. ...
This study investigates how structural changes and economic activities impact on the environment in Japan. Instead of using traditional economic and environmental factors, the authors used economic complexity and ecological footprint as key factors. Taking into account the dynamic nature of the relationship between economic activities and the environment, the recently developed Quantile ARDL (QARDL) model is employed. The results of the Quantile Granger-causality show bidirectional causality between economic growth, economic complexity, and ecological footprint in low and high quantiles. Likewise, QARDL findings reveal that there is asymmetric positive relation between economic growth and environment both in the short-run and long-run. Therefore, the long run cointegration and causality between economic complexity and ecological footprint suggest that policy efforts towards product diversification hold the potential to solve ecological problem.
... In addition to Global Footprint Network's regular publication of EF estimates for more than 250 countries, several studies have been carried out either on a smaller scale (local community level) or on a larger scale (regional level) estimating EF values for one or more years (Ming et al. 2006;Bagliani et al. 2003;Hopton and Berland 2015;Wu and Liu 2016;Santoso et al. 2018;Khan and Uddin 2018;Shakil et al. 2014). Furthermore, ecological footprint estimates have been investigated with an aim to evaluate ecological impact and resource productivity, support environmental hypotheses, and promote food security, sustainable waste management and sustainable transportation system (Tavallai and Sasanpour 2009;Fu et al. 2015;Bagliani et al. 2008;Bala and Hossain 2010;Salequzzaman et al. 2006;Labib et al. 2013). ...
In an era of environmental degradation, resource extraction needs to be restricted in proportion to natural capital’s regenerative capacity to nullify ecological overshoot. An investigation into spatial heterogeneity of ‘Ecological Footprint of Production’ (EFp) helps to examine spatial variation of human demand on nature due to production purposes. This study focuses on spatial variation in environmental impact of resource extraction by estimating EFp values for all 64 districts of Bangladesh. EFp is spatially varied across six land types in the following ranges 0.016–0.502 gha/capita for cropland; 0.016–0.637 gha/capita for grazing land; 0.004–0.194 gha/capita for fishing ground; 0.000–0.187 gha/capita for forest land; 0.00009–0.011 gha/capita for built-up land; and 0.000–1.192 gha/capita for carbon uptake land. Moreover, in this study, regions are delineated based on EFp values of six land types using ArcGIS-based standard deviation classification method. The region having the highest total EFp is located at the central-east part of Bangladesh. Among six types of land uses, cropland, grazing land and carbon uptake land contributed most in total EFp. Multiple linear regression modeling showed that population employed in service sector drives total EFp (gha) in negative direction and district population drives it in positive direction. Spatially segregated policy directions are recommended for restricting EFp to ensure reduced environmental degradation and increased production-based sustainability. Therefore, to promote sustainable sectoral enhancement plans and policies, this investigation facilitates regional policy guidelines based on sectoral magnitude of resource extraction.
... Country City Methodology Year City Footprint value (gha) Reference Australia Sydney Top-down 2001 5.92 (ha) (Lenzen, 2008) Brazil Curitiba Top-down 2009 2.6 (Global Footprint Network, 2010) Canada Calgary Top-down 2001 9.86 (Wilson and Anielski, 2005) Calgary Bottom-up 2007 9.5–9.9 (Global Footprint Network, 2007) [ 2 3 3 _ T D $ D I F F ] Edmonton Top-down 2001 9.45 (Wilson and Anielski, 2005) Edmonton Top-down 2008 8.56 (Anielski, 2010) Québec City Top-down 2001 6.89 (Wilson and Anielski, 2005) Toronto Top-down 2001 7.36 (Wilson and Anielski, 2005) Vancouver Bottom-up 2006 4.7 (Moore et al., 2013) Vancouver Top-down 2001 7.71 (Wilson and Anielski, 2005) Chile Santiago de Chile Top-Down 1998 2.6 (Wackernagel, 1998) China Chongqing Top-down 2009 2.2 (WWF, 2012) Hong Kong Top-down 2008 4.3 ([ 1 9 0 _ T D $ D I F F ] Global Footprint Network and WWF, 2013[ 1 9 1 _ T D $ D I F F ] ) Shanghai Top-down 2009 3.8 (WWF, 2012) Shenyang Bottom-up 2009 1.8 (Geng et al., 2014) Tianjin Top-down 2009 2.7 (WWF, 2012) Ecuador Quito Top-down 2006 2.4 ([ 1 9 2 _ T D $ D I F F ] Moore and Stechbart, 2010) Iran Isfahan Bottom-up 2007 1.22 (Shayesteh et al., 2015) Tehran Bottom-up 2005 3.79 (Tavallai and Sasanpour, 2009) Israel Beer-Sheva Bottom-up 2007 3.98 (Zeev et al., 2014) Ra'anana Bottom-up 2002 4.0 (Kissinger and Haim, 2008) Italy Piacenza Bottom-up 2002 3.79 (Scotti et al., 2009) Siena (and its Province) Bottom-up 1999 5.80 (Bagliani [ 1 9 3 _ T D $ D I F F ] et al., 2008) Japan Kawasaki Bottom-up 2009 5.1 (Geng et al., 2014) Norway Oslo Bottom-up 2000 7.76 (Aall and Norland, 2002) Philippines Manila Top-down 2009 1.82 (Global Footprint Network and Laguna Lake Development Authority, 2013) Spain Barcelona Bottom-up 1996 3.23 (Relea and Prat, 1998) an ecological deficit since 1961 (Galli et al., 2015). During the period 1961–2010, per capita biocapacity decreased by 21%, while the Ecological Footprint of an average Mediterranean resident increased by 54%. ...
The Ecological Footprint is an accounting tool that has been used by resource managers and widely
communicated to the public over the last 20 years. The National Footprint Accounts (NFA) are a system of
national-level Ecological Footprint accounts that can be geographically scaled to derive Footprint values
for major consumption categories at the household level for a given region, province, city or urban
agglomeration. A number of city Footprint assessments have been undertaken during the last two
decades. However, these studies have used different approaches, rendering comparability challenging.
Here we present a top-down approach to consistently track the Ecological Footprint of 19 coastal cities in
the Mediterranean region. Valletta, Athens, and Genoa are the cities with the highest per capita Ecological
Footprint, ranging between 5.3 and 4.8 gha per person; Tirana, Alexandria and Antalya have the lowest
Ecological Footprint, ranging between 2.1 and 2.7 gha per capita. Most cities’ Footprints exceed that of
their countries with the exception of Thessaloniki, Tel Aviv, Venice, Palermo and Naples. This analysis
provides a macro-level indication of the overall resource demands by cities, their drivers and leverage
point. The main Footprint drivers are food consumption, transportation and consumption of
manufactured goods. Differences among cities’ Ecological Footprint values are most likely driven by
socio-economic factors, such as disposable income, infrastructure, and cultural habits. City level
Footprint findings can be used to help design sustainability policies and positively reinforce collective
public achievements so far.
... Lisbon 2003 1 1 0 In average 2004 1 1 0 In average 2005 1 1 0 In average 2006 1 1 0 In average 2007 1 1 0 In average 2008 1 1 0 In average 2009 1 1 0 In average Niza et al. (2009) and Rosado (2014) Lisbon Average 2002- 2009 0 0 1 Barles (2009) Paris 2006 1 0 1 MFA was not broken down into different consumption categories Swilling (2006) Cape Town 2006 1 1 1 Sahely (2003) Toronto 1987 0 0 1 Sahely (2003) Toronto 1999 0 0 1 Pina and Martinez (2013) Bogota 2010 1 1 1 Barrett (2002) York 2000 1 1 1 Emenegger (2002) Geneva 2000 1 1 1 Moore (2014) Vancouver 2013 1 1 1 Best Foot Forward (2002) London 2000 1 1 1 Ngo and Pataki (2008) Los Angeles 1990 0 0 1 MFA only covered water and food Ngo and Pataki (2008) Los Angeles 2000 0 0 1 MFA only covered water and food Metzger (2013) Durham 2000 0 0 1 MFA was not broken down into different consumption categories Forkes (2007) Toronto 1990 0 0 1 MFA only covered food Forkes (2007) Toronto 2001 0 0 1 MFA only covered food Forkes (2007) Toronto 2004 0 0 1 MFA only covered food Newman (2000) Melbourne 1990 0 0 1 MFA was not broken down into different consumption categories Codoban (2008) Toronto 2008 0 0 1 MFA was not broken down into different consumption categories Chavez (2012) Delhi, IN 2009 0 0 1 Complete MFA not published, but food consumption given Reddy (2013) Mumbai, IN 2010 0 0 1 Masses of fuels not presented. Hoornweg (2012) Manila, PH 2010 0 0 1 Assessment not broken down into clear UM drivers Total - - 19 18 25 Table S1 -Included mass foodprint studies Table S2 -CF Studies Study City Year In Figure 2A In Figure 2B Figure 3B Reason for Discrepancy Ramaswami (2008) Denver 2005 1 1 1 Wu (2011) Beijing 2006 1 1 1 Heinonen (2011) Helsinki 2006 1 0 1 Food not disaggregated into own consumption category Chavez (2012) Delhi 2009 1 0 1 CF was not broken down into different consumption categories Hillman (2010) Colorado 2000 1 1 1 Boulder 2000 1 1 1 Fort Worth 2000 1 1 1 Arvada 2000 1 1 1 Portland 2000 1 1 1 Seattle 2000 1 1 1 Minneapolis 2000 1 1 1 Austin 2000 1 1 1 Dias (2014) Aveiro 2005 1 1 1 Cardiff Council (2001) Cardiff 2001 1 1 1 Best Foot Forward (2002) London 2000 1 1 1 Li (2013) Macao 2005 1 0 1 CF was not broken down into different consumption categories 2006 1 0 1 2007 1 0 1 2008 1 0 1 2009 1 0 1 20 13 20 Table S2 -Included MFA foodprint studies Table S3 -EF Studies Study City Year In Figure 2A In Figure 2B Figure 3C Reason for Discrepancy Klinksy et al. (2009) Montreal Early 2000s 1 1 1 Tavallai (2009) Tehran 2005 1 1 1 Zhang et al. (2013) ...
... According to Wackernagel's law, which states that a hectare of land absorbs 1.8 tons of carbon, the amount of producing CO 2 was converted to the physical area (hectares). Considering the consumption of electricity, natural gas, water, Tavallai and Sasanpour (2009) used the land useconsumption matrix. Transportation, consumer goods, housing, and services were accounted for, and crop land, grazing land, built-up land, fishing grounds, and energy land were evaluated. ...
... In 2008, the ecological footprint of Tehran citizens with regard to transportation, consumer goods, housing, and services, and by evaluation of cropland, grazing land, forest land, fishing ground, built-up land, and energy land was estimated as 3.78 global hectares (Tavallai and Sasanpour, 2009.) This indicates that the ecological footprint, which examines the effects of consumption by communities on the environment, is higher in the cities where consumption is high due to higher income, population, technology, and general welfare. ...
The human society cannot be considered in isolation from nature; and
human activities are always in need of environmental analyses. Therefore,
communities require tools for determining the biosphere dynamics and the
biophysical limitations of earth in order to assess the systems subdued
by humans. The ecological footprint is among the most important tools in
this regard. It evaluates the relationship between humans and resources and
is defined as the total area of land and water in different ecological levels,
needed to produce all the resources that people consume, and absorb the
wastes they produce. The ecological footprint calculation is in fact the
expansion of a quantitative method to illustrate the importance of
investigating the effects the inhabitants’ consumption has on the productive
and non-productive land systems. This method can be employed in any area
with comparable results. In this study, the ecological footprint of Isfahan was
estimated considering the five basic factors of urban life: food, shelter,
transportation, goods, and services. In 2011, the per capita ecological
footprint was calculated as 3.9 global hectares. This means that, the
productive land and sea required for providing the needed resources and the
sinks to absorb the waste resulting from the activities of each Isfahan citizen
is 3.9 global hectares.
... Tavallai and Sasanpour [28] provide an ecological footprint for Tehran (Table 4) measuring "how much land is required to supply our living and lifestyle including food, housing, energy/fuel, transport, and consumer goods and services along with their corresponding energy requirements". According to Tavallai and Sasanpour [28] Tehran metropolitan require 22 million hectares (2.9 ha compared to world average of 1.5 ha) in order to meet the relevant energy requirements. ...
... According to Sabetghadam [26] Iran is "one of the highest carbon emission-intensive countries in the world" (Figure 6). Total CO2 emissions in 1990 were 201.8 MMT, which has increased rapidly at an average annual rate of 5. [28]) Figure 6: CO2 emissions (after [26]) The high emissions rate is mainly due to economic growth and increase of national wealth increasing wealth as shown in Figure 7; GDP has been rising since the start of construction era and the 5 Year Development Plans (the 5 th Plan will start in 2010). However there are other reasons for this high rate [26]: -low energy efficiency of many sectors; and to the over-consumption of energy as the result of cheap energy prices سومین فاضالب و آب ملی همایش رویکرد (با مصرف الگوی اصالح ) Third National Water and Wastewater Conference, Changing Consumption patterns; Jan 2010 Figure 7: Real GDP and GDP Per Capita, 1967-2003, in 1997) ...
This paper argues that assessment of water availability to a growing population may be addressed by using an integrated assessment program at city-scale within the context of socio-economic and climate change scenarios. There is a need for an integrated research and assessment agenda and a new ‘Blueprint’ to provide tools for decision-makers and policy-makers and provide evidence for policy issues such as urban development, water resources availability, climate change mitigation and adaptation and sustainable energy and so forth. London’s integrated assessment case study can be transferred to a Tehran City setting since it is based on commonalties of challenges of urban areas.
The interconnection of urbanization trends and environmental pressures, are due to the rising demand for resource consumption, waste production and greenhouses gas emissions. Taking into consideration the massive reduction of natural resources, the deprivation of the life quality and the climate change, the scientific community indicates the necessity to emphasis and understand the relationship between cities and the environment as a dynamic concept. Consequently, cities are facing the challenge to implement alternative strategies towards more sustainable management of urban resources. This research aims to shed light on the concept of urban metabolism, the methods that are been used to gauge urban metabolism (i.e Emergy Analysis, Material Flow Analysis, Ecological Footprint etc.), as well as the assessment of the proposed methodologies through SWOT analysis and Analytical Hierocracy Process, considering multi-criteria analysis and how those reflect to Circular Economy and European Green Deal Strategy. The results showed that, the existing methodologies needs refreshment to cover the needs for the cities of tomorrow and a new hybrid approach which will include new set of Key Performed Indicators is essential. Furthermore, the results could serve as a beneficial reference point for policy makers, consultants, rural developers as the new hybrid approach can be used to measure and assess the level of metabolism in one area in order to prevent future expansion.
The needs of coastal and marine tourism, especially in small island continues to rise. But tourism have risk unsustainable if not planned properly and not based on carrying capacity (CC). The aims of this study are to identify degree of use and coastal resources management, estimated suitability and opportunity for sustainable tourism, and measure ecological CC and sustainable tourism management on Sepanjang Island. This study uses a hybrid analysis method that include Participatory Rural Appraisal (PRA), tourism suitability index, Recreation Opportunities Spectrum (ROS) and Touristic Ecological Footprint (TEF). The results of this study indicate that the degree of resources use of Sepanjang Island is still low and management on resources not yet optimal, although Sepanjang Island has been set as Marine Protected Area (MPA) since 2010. Sepanjang Island has suitability resources for tourism of beach 26.35 km, mangrove 3,319.75 ha, seagrass 85.06 ha, snorkeling 134.95 ha and diving 107.36 ha. Sepanjang Island is divided into 6 classes of ROS are urban 557.1260 ha (0.92%), Rural 3,086.6240 ha (19%), Frontcountry 4,104.0390 ha (6.75%), Backcountry 26,018.7110 ha (42.80%), Remote 26,997.9960 ha (44.41%) and Wilderness 33.7920 ha (0.06%). Whereas TEF values Sepanjang Island is 0.162504 ha with CC is 159,743 capita.
Small islands have limited natural resources, isolated and remote from mainland as territorial areas, and exposed to natural disasters, so that, they have special characteristics and vulnerabilities to global, regional and local influences. Therefore, the resilience, vulnerability and carrying capacity of the area are important to understand as the basis for forming appropriate management and sustainable. The study aims to assess spatial resilience in small islands, with an integrated social-ecological system (SES) framework using the analysis methods of vulnerability, carrying capacity, adaptive capacity and adaptive cycles based on historical and model approaches.
The results of study showed that the spatial changes affected the dynamics of the spatial resilience variables on the Gili Matra Islands, both for biocapacity (BC), spatial ecological footprint (SEF), connectivity index (CI) and spatial heterogeneity (SH). The Gili Matra Islands had a resilient level from moderate to non-resilient, and had adaptive capacity from high to moderate (one to six years). The variables that had good adaptive capacity were CI and SH variables, although the BC variable also indicated good adaptive capacity. Based on the assessment and simulation, the total value of resilience in Gili Ayer Island ranged from 0.566551 to 0.51322 (moderate), Gili Meno Island ranged from 0.604796 to 0.608992 (resilient) and Gili Trawangan Island ranged from 0.326409 to 0.142658 (low resilient to non-resillent).
Based on the value of resilience variables, the Gili Matra Islands were in the reorganization phase for Gili Ayer Island and Gili Meno Island, and exploitation phase for Gili Trawangan Island in adaptive resilience cycles. This condition confirms that Gili Ayer and Meno Island ware re-arranging spatial structures and existing development directions, namely small island tourism, which showed the development activities, while for Gili Trawangan Island described the development and growth of intensive tourism. Therefore, management efforts must be carried out so that the existing phases can be passed, so the system does not focus on the exploitation phase alone, without passing through the conservation, release and reorganization phases, so that the spatial system can be resilient and sustainable development can be achieved.
Generally, the study can be concluded that the Gili Matra Region have vulnerability level from low into moderate, however, with the bad conditions of Coastal Water Quality Indeks (CWQI), the high of EF and the low of BC, and the results of land changes simulation, then a vulnerability status will immediately increases from time to time. They are approved by adaptive capacity assessment, which is relatively small and need a long time from tipping point, and are confirmed by resilience assessment results, that is low.
