Temporal and spatial assessment of natural resource use in China using ecological footprint method

Chen, Min; Wang, Rusong; Zhang, Lijun; Xu, Chonggang

doi:10.1080/13504500609469677

Cited by 10 publications

(5 citation statements)

References 23 publications

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“…Control variable: In addition to independent variables, there are other factors affecting environmental sustainability. Following Chen et al [56], Zheng et al [57], Ünal and Aktu g [58], Hassan et al [59], and Galli et al [60], bio-capacity is introduced in this paper. Following Eregha et al [61] and Liu et al [62], economic growth is also introduced in this paper.…”

Section: Variable Descriptionmentioning

confidence: 99%

Renewable and Non-Renewable Energy Consumption and Trade Policy: Do They Matter for Environmental Sustainability?

2022

Energies

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In the extant literature, there are numerous discussions on China’s environmental sustainability. However, few scholars have considered renewable energy consumption and trade policy simultaneously to debate environmental sustainability. Therefore, this paper attempts to examine how renewable and non-renewable energy consumption, bio-capacity, economic growth, and trade policy dynamically affect the ecological footprint (a proxy for environmental sustainability). Using the data from 1971 to 2017 and employing the auto-regressive distributed lag model to perform an empirical analysis, the results demonstrate that renewable energy consumption and trade policy are conducive to environmental sustainability because of their negative impacts on the ecological footprint. However, the results also indicate that bio-capacity, non-renewable energy consumption, and economic growth are putting increasing pressure on environmental sustainability due to their positive impacts on the ecological footprint. Moreover, to determine the direction of causality between the highlighted variables, the Yoda-Yamamoto causality test was conducted. The results suggest a two-way causal relationship between renewable energy consumption and ecological footprint, non-renewable energy consumption and ecological footprint, and economic growth and ecological footprint. Conversely, the results also suggest a one-way causal relationship running from bio-capacity and trade policy to the ecological footprint.

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Section: Variable Descriptionmentioning

confidence: 99%

Renewable and Non-Renewable Energy Consumption and Trade Policy: Do They Matter for Environmental Sustainability?

2022

Energies

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“…Sustainable development has become an important goal around the world since the Rio Earth Summit (Wackernagel et al, 2004;Chen et al, 2006). So far, a variety of models, methods and indicators have been put forward to evaluate sustainable development quantitatively at regional scales.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the major drivers of the ecological footprint using the STIRPAT model and the PLS method—A case study in Henan Province, China

Jia

Deng

Duan

et al. 2009

Ecological Economics

122

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Taking Henan Province of China as an example, we computed and analyzed the ecological footprint (EF) in . The results showed that the EF in Henan Province quadrupled in the 23 years, but its ecological carrying capacity (EC) was rather low and was in a state of slow decline, indicating that Henan's ecological deficit (ED) had become a remarkable social problem. Therefore, the major drivers of the EF's change were analyzed. According to the simulations with STIRPAT model, the major drivers of Henan's EF were human population (P), GDP per capita (A 1 ), quadratic term of GDP per capita (A 2 ), percent of economy excluded in the service sector (Ta 1 ) and percent of urban population (Tb 1 ). However, these drivers themselves had strong collinearity, which might produce some uncertain impact to the final results. In order to avoid the impact of collinearity, the method of partial least squares (PLS) was used. The results showed that the major drivers of EF were P, A 1 , A 2 and Tb 1 . Ta 1 was excluded. Compared with the results by the STIRPAT model, which showed that P is the most dominant driver and the effect of the other drivers could almost be ignored, the results by PLS method were considered as more reasonable and acceptable because the impacts of the A (Affluence) and T (Technology) conditions to the regional EF were still too important to be ignored. In addition, the results acquired by both methods showed that the curvilinear relationship between economic development and ecological impact (EF) or the classical EKC hypothesis didn't exist in Henan Province.

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“…However for many years there was less work on UHIs in tropical cities than in temperate zones. UHI research was conducted in 1964 by Nieuwolt (1966) in Singapore's southern urban area (Chen et al ., 2006b; Roth et al ., 2012). In the early 1980s, climatologists used the UHI study's energy and water balance processes to calculate urban heat storage (Oke & Cleugh, 1987).…”

Section: Introductionmentioning

confidence: 99%

“…The UHI distribution is responsible for urban ecological degradation, local climate change, micro‐level biodiversity, and ecological imbalance. The physical features of LULC are one of the central derivations of urban ecological footprints (Wackernagel et al ., 2002; Holden, 2004; Chen et al ., 2006b) associated with urban metabolism and urban sustainability. Hence, UHI assessment is imperative for ecological conservation and sustainability in urban expansion.…”

Section: Introductionmentioning

confidence: 99%

Remote sensing‐based geostatistical hot spot analysis of Urban Heat Islands in Dhaka, Bangladesh

Hussain,

Ahmed,

Shumi

2023

Singap J Trop Geogr

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Urban Heat Island (UHI) refers to a phenomenon whereby urban areas experience higher temperatures compared to the surrounding areas. Remote sensing‐based Land Surface Temperature (LST) measurements can be utilized to measure UHI. This study emphasized on geostatistical remote sensing‐based hot spot analysis () of UHI in Dhaka, Bangladesh as a way of examining the influences of Land Use Land Cover (LULC) on UHI from 1991 to 2015. Landsat 5 and 7 satellite‐based remote sensing indices were used to explore LULC, UHI and environmental footprints during the study period. The Urban Compactness Ratio (CoR) was used to calculate the urban form and augmented characteristics. The Surface Urban Heat Island (SUHI) intensity (ΔT) was also used to explore the effects of UHI on the surrounding marginal area. Based on our investigations into LULC, we discovered that around 71.34 per cent of water bodies and 71.82 percent of vegetation cover decreased from 1991 to 2015 in Dhaka city. Contrastingly, according to CoR readings, 174.13 km2 of urban areas expanded by 249.77 per cent. Our hot spot analysis also revealed that there was a 93.73 per cent increase in hot concentration zones. Furthermore, the average temperature of the study area had increased by 3.26°C. We hope that the methods and results of this study can contribute to further research on urban climate.

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Temporal and spatial assessment of natural resource use in China using ecological footprint method

Cited by 10 publications

References 23 publications

Renewable and Non-Renewable Energy Consumption and Trade Policy: Do They Matter for Environmental Sustainability?

Renewable and Non-Renewable Energy Consumption and Trade Policy: Do They Matter for Environmental Sustainability?

Analysis of the major drivers of the ecological footprint using the STIRPAT model and the PLS method—A case study in Henan Province, China

Remote sensing‐based geostatistical hot spot analysis of Urban Heat Islands in Dhaka, Bangladesh

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