The driving factors of water use and its decoupling relationship with economic development: A multi-sectoral perspective DOI Creative Commons

Tianzi Wang,

Shengqi Jian, Huiliang Wang

и другие.

Research Square (Research Square), Год журнала: 2022, Номер unknown

Опубликована: Ноя. 10, 2022

Abstract The water resource situation in China is severe, and conflicts between the supply demand of resources are prominent. Competition for from key sectors, such as agriculture, industry, domestic use, widespread. Yellow River, one longest rivers world, an important economic belt ecological barrier China. This study considered nine provinces along River area three major water-use sectors: research objects. drivers consumption each sector were analyzed using Logarithmic Mean Divisia Index method. Based on this, a decoupling model was used to explore relationship use corresponding level development. It found that intensity development largest negative positive influencing factors sector, respectively, opposite effects two may cause Jevons paradox use. overall agricultural water-saving basin high has large potential. driving effect industrial structure more significant with higher levels. residents' levels rural areas obvious than urban areas. degree per capita worst agricultural, industrial, sectors their Therefore, focusing weak conservation, promoting upgrading, strengthening conservation education areas, guiding habits residents can promote sustainable River. results provide insights into management Basin.

Язык: Английский

An integrated framework for assessing water resource pressure and sustainability based on the total-element agricultural water footprints DOI Creative Commons

Wei Rui,

Xuan Wang,

Guangling Hao

и другие.

Frontiers in Earth Science, Год журнала: 2025, Номер 13

Опубликована: Фев. 20, 2025

The agricultural water footprint (WF) is essential for understanding environmental impacts and managing resources, especially in water-scarce regions. In this study, an integrated framework assessing resource pressure sustainability based on the total-element footprints was developed. Firstly, three types of WFs (i.e., blue, green grey WFs) major crops including wheat maize Beijing area were calculated, spatiotemporal variations analysed. Subsequently, stress index (WSI) this, reliability-resilience-vulnerability (RRV) indices established systematically systems. Finally, driving factors WF analysed using STIRPAT model. results as follows. (1) overall decreased from 22.0 × 10 8 m 3 to 3.9 7 , showing a significant downward trend 1978 2018. (2) WSI values exceeded 1 25 out 35 years, indicating that continued experience frequent shortages. RRV indicated resources had improved recent value 0.35 2018, but remained at low level. (3) Enhancing effectiveness irrigation, increasing machinery density, reducing planting water-intensive can significantly lower WF. This study assessed by combining indices, perspective both quantity quality. approach importance sustainable utilisation management regions, analysis.

Язык: Английский

Процитировано

0
Unveiling the water-energy-food nexus efficiency and influencing factors in China: An integrated EBM and Tobit model analysis DOI

Yangxi Lv,

Shiyu Yan,

Xuanman Lai

и другие.

Ecological Indicators, Год журнала: 2025, Номер 173, С. 113357 - 113357

Опубликована: Март 18, 2025

Язык: Английский

Процитировано

0
Research on agricultural grey water footprint/efficiency and identification of influencing factors in Henan Province DOI
Yanqi Zhao, Zhen Yang, Ying Yang

и другие.

Environmental Science Processes & Impacts, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Agricultural water pollution control is the key to alleviating crisis and promoting regional sustainable development.

Язык: Английский

Процитировано

0
Investigation of the water footprint of denim fabric production at factory scale DOI Creative Commons
Hakan Güney, Selman Türkeş, Bülent Sarı

и другие.

Clean Technologies and Environmental Policy, Год журнала: 2025, Номер unknown

Опубликована: Май 28, 2025

Abstract This study is the first to evaluate and compare water footprints (WFs) of unit denim fabric production in different categories based on consumption amount characteristics wastewater generated a factory producing fabric. In this study, gate-to-gate footprint (WF) assessment was conducted using factory’s data reveal volumetric (blue (WF blue ) gray environmental impacts (water scarcity (WSF), eutrophication eu ), alkalization alk ecotoxicity eco )) use. The evaluation carried out Water Footprint Network (WFN) International Organization for Standardization (ISO) 14,046 methods. WF , WSF, values are calculated as 66.97 m 3 /ton 72.8 50.06 H 2 O eq/ton 7.72 kg PO 4 3− 0.39 OH − 8686.60 Oeq/ton respectively. It concluded that creates more pressure resources due its processes rather than consumed < WSF ). Graphical abstract

Язык: Английский

Процитировано

0
Spatial network and influencing factors of green water use efficiency in the YREB: considering carbon emissions and pollution indicators DOI
Rui Zhang, Lingling Zhang, Zongzhi Wang

и другие.

Environmental Science and Pollution Research, Год журнала: 2024, Номер 31(11), С. 17324 - 17338

Опубликована: Фев. 10, 2024

Язык: Английский

Процитировано

2
Multilevel driving mechanism of ecosystem multidimensional stability in the Yangtze River Economic Belt: A hierarchical linear model approach DOI
Yifei Zhao, Shiliang Liu,

Hua Liu

и другие.

Journal of Cleaner Production, Год журнала: 2024, Номер 449, С. 141513 - 141513

Опубликована: Март 4, 2024

Язык: Английский

Процитировано

2
Decision support framework adapted to local conditions to select technologies for rural domestic sewage treatment in the Yangtze River Economic Belt DOI

Mei-Yun Lu,

Shan-Shan Yang,

Xin-Lei Yu

и другие.

Journal of Cleaner Production, Год журнала: 2023, Номер 426, С. 139067 - 139067

Опубликована: Сен. 28, 2023

Язык: Английский

Процитировано

4
Multifaceted dimensions of greywater recycling in advancing sustainable development goals: a comprehensive review DOI
Om Prakash, Purusottam Tripathy,

A Bagher Zade

и другие.

Environment Development and Sustainability, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 14, 2024

Язык: Английский

Процитировано

1
How industrial water resources green efficiency varies in China: a case study of the Yangtze River Economic Belt considering unexpected output DOI
Dalai Ma, Fengtai Zhang, Yaping Xiao

и другие.

Environment Development and Sustainability, Год журнала: 2022, Номер 26(1), С. 187 - 213

Опубликована: Окт. 28, 2022

Язык: Английский

Процитировано

5
Variation and internal-external driving forces of grey water footprint efficiency in China’s Yellow River Basin DOI Creative Commons
Yun Li, Yu Liu, Lihua Yang

и другие.

PLoS ONE, Год журнала: 2023, Номер 18(3), С. e0283199 - e0283199

Опубликована: Март 22, 2023

Grey water footprint (GWF) efficiency is a reflection of both pollution and the economy. The assessment GWF its conducive to improving environment quality achieving sustainable development. This study introduces comprehensive approach assessing analyzing efficiency. Based on measurement efficiency, kernel density estimation Dagum Gini coefficient method are introduced investigate spatial temporal variation Geodetector also innovatively used internal external driving forces not only revealing effects individual factors, but probing interaction between different drivers. For demonstrating this approach, nine provinces in China's Yellow River Basin from 2005 2020 chosen for study. results show that: (1) basin increases 23.92 yuan/m3 164.87 2020, showing distribution pattern "low western high eastern". Agricultural main contributor GWF. (2) shows rising trend, curve has noticeable left trailing polarization characteristics. fluctuates upwards, accompanied by rise overall 0.25 0.28. Inter-regional primary source variation, with an average contribution 73.39%. (3) forces, economic development driver any two factors enhances explanatory power. capital stock reflects greatest impact. combinations highest q statistics upstream, midstream downstream population density, technological innovation industrial structure respectively.

Язык: Английский

Процитировано

1