Decoupling Water Consumption and Environmental Impact on Textile Industry by Using Water Footprint Method: A Case Study in China

Li, Yi; Lu, Linyi; Tan, Yingxi; Wang, Laili; Shen, Manhong

doi:10.3390/w9020124

Cited by 43 publications

(24 citation statements)

References 35 publications

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“…Compared to other decomposition methods, the LMDI method does not leave a residual term and is especially suitable for models with time-series data, so it has been recommended for general use [30]. In recent years, research on water resources has been conducted using the LMDI model, and a few studies have applied it to analyze the WF of agriculture [31][32][33][34][35]. In this study, we used this method to decompose the WF of crops into eight major grain-producing areas in Northwest China.…”

Section: Lmdi Methodologymentioning

confidence: 99%

Spatial-Temporal Differences in Water Footprints of Grain Crops in Northwest China: LMDI Decomposition Analysis

Shi¹,

Wang²,

Zhang³

et al. 2019

Water

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Agriculture and crop production is the sector with the highest water demand, and because of water shortages and an unbalanced distribution of natural resources in China, improving the efficiency of agricultural water use is essential. In this study, we quantified the total water footprint (WF) of major crop products in Northwest China using the Penman–Monteith formula. The logarithmic mean divisor index (LMDI) was used to explain the four factors driving the spatial and temporal differences in the WFs of the major crops in five provinces and regions in Northwest China. The results showed that from 2006 to 2015, the total WF of the major crops was increasing overall. From a temporal perspective, the crop area and yield effects, which were the factors driving the overall increase in the WF, positively impacted the overall change in the WF of the major crops in Northwest China. The effects of the virtual water content (VWC) and crop structure were both volatile. The effect of the crop structure made a relatively small contribution, while the effect of the VWC played a significant role in changing the overall WF. From a spatial perspective, the changes in the VWC and crop structure negatively inhibited the increase of the WF, widening the difference between these provinces and regions and Shanxi. The increased yields in Xinjiang most clearly increased the WF, followed by those in Ningxia, Qinghai, and Gansu. In comparison with Shanxi, in all the provinces and regions except Xinjiang, the change in cultivated area was less effective in promoting the WF. Therefore, scientific planting plans should be developed for adapting to climate change, considering the differences in natural features among various provinces and regions. Water conservation and advanced agricultural technology should be promoted to enhance the sustainability of agricultural development.

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Section: Lmdi Methodologymentioning

confidence: 99%

Spatial-Temporal Differences in Water Footprints of Grain Crops in Northwest China: LMDI Decomposition Analysis

Shi¹,

Wang²,

Zhang³

et al. 2019

Water

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“…Decoupling is a term that refers to the status when the relationship between energy consumption and economic growth begins to break up [39]. Decoupling can be further divided into two/three/six/eight subcategories [38], and all were used in earlier studies [9,[40][41][42]. Compared with other methods, the 8-min state classification method is more detailed and helpful for the analysis of the study.…”

Section: Tapio Decoupling Indicatormentioning

confidence: 99%

Factorial Decomposition of the Energy Footprint of the Shaoxing Textile Industry

et al. 2020

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To present great environmental pressure from energy consumption during textile production, this paper calculates the energy footprint (EFP) of Shaoxing’s textile industry, from 2005 to 2018. Moreover, this study analyzes the relationship between Shaoxing’s textile industry energy consumption and economic development by using decoupling theory. Furthermore, the Logarithmic Mean Divisia Index decomposition method was employed to investigate the main factors that affect the EFP of Shaoxing’s textile industry. Research results show the following: (1) The growth rate of the total output value of Shaoxing’s textile industry was greater than the growth rate of the EFP, from 2005 to 2007. Thus, the decoupling state showed a weak decoupling, and EFP intensity decreased. (2) The EFP and economic growth were mainly based on the strong decoupling of Shaoxing’s textile industry from 2008 to 2015 (except for 2011), and EFP intensity declined further. (3) Economic recession in the textile industry was severe in Shaoxing, from 2016 to 2018, and the EFP also showed a downward trend. The state of decoupling appeared as a recessive decoupling (2016) and a weak negative decoupling (2017 and 2018), and EFP intensity first increased and then decreased. (4) The total effect of the factors affecting the EFP of the textile industry in Shaoxing demonstrated a pulling trend, and industrial scale played a significant role in driving the EFP. The energy consumption intensity effect contributed the largest restraint. This paper fills in the gaps in the environmental regulation means and methods of pillar industrial clusters in specific regions.

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“…Scholars at home and abroad use LCA to calculate and analyze the carbon footprint of agricultural production [26][27][28][29][30][31][32][33][34][35] and suggest countermeasures and suggestions on how to realize the low carbon development of agriculture. A number of them have performed in-depth research on the main sources of agricultural carbon emissions.…”

Section: Introductionmentioning

confidence: 99%

Calculation and Evaluation of Carbon Footprint in Mulberry Production: A Case of Haining in China

Wang

et al. 2020

IJERPH

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Carbon footprint refers to the greenhouse gas emissions of an activity during the whole life cycle or a specific period of time. Mulberry is an important cash crop. Thus, establishing a standardized accounting method for the carbon footprint of mulberry production and analyzing its carbon emission scenarios is important in correctly understanding the impact of mulberry production on the environment. Using the life cycle assessment method and on the basis of the statistical data of mulberry production of urban farmers in Haining City, China, in 2014–2016, this study calculates and evaluates the carbon footprint of mulberry production. Results show the following. (1) Indirect carbon emissions is the main part of total carbon emissions, accounting for 85%–88% of total carbon emission, and industrial inputs (fertilizers and pesticides) are the main cause of carbon emissions. (2) The total carbon emissions per hectare in 2016 (6550.73 kgce/hm2) rose relative to the 2015 data (5617.92 kgce/hm2 at least in 2014) (5729.64 kgce/hm2). The output value of mulberry in spring was greater than that in summer and autumn, and the production efficiency of mulberry carbon in spring was higher than that in summer and autumn. The ecological environment of the mulberry production industry can be improved by increasing the resources of carbon sequestration and reducing the source of production input. (3) In general, the photosynthetic carbon sink of mulberry is greater than the total carbon emission and presents a positive externality to the ecological environment.

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Decoupling Water Consumption and Environmental Impact on Textile Industry by Using Water Footprint Method: A Case Study in China

Cited by 43 publications

References 35 publications

Spatial-Temporal Differences in Water Footprints of Grain Crops in Northwest China: LMDI Decomposition Analysis

Spatial-Temporal Differences in Water Footprints of Grain Crops in Northwest China: LMDI Decomposition Analysis

Factorial Decomposition of the Energy Footprint of the Shaoxing Textile Industry

Calculation and Evaluation of Carbon Footprint in Mulberry Production: A Case of Haining in China

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