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

Understanding the efficiency and evolution of China's Green Economy: A province-level analysis DOI
Yanyong Hu, Xu‐Chao Zhang, Jiaxi Wu

и другие.

Energy & Environment, Год журнала: 2023, Номер unknown

Опубликована: Сен. 28, 2023

The efficiency level, evolution characteristics, and factors driving the green economy in all provinces regions should be clarified to achieve high-quality economic development meet China's “double carbon” target. This study conducted Super-Effective Slack-Based Model considering unexpected outputs evaluate province-level Green Economic Efficiency (GEE) analysis (including 30 provinces, autonomous regions, municipalities directly under Central Government) China from 2005 2020. Moreover, distribution dynamic trend of GEE was estimated through Kernel density estimation. Besides, its (i.e., industrial structure rationalization [ISR], advancement [ISA], urbanization level [UL]) were examined using a Panel vector autoregressive model that built this study. As indicated by result study, generally displayed “U-shaped” declining, stabilizing, then rising, whereas overall is low, where national average reached 0.6934. regional exhibited significant “ladder” distribution, with highest second lowest east, middle, west, respectively. varied significantly province, most levels at medium level. Notably, 60% had ISR, ISA, UL play roles boosting growth. provides valuable insights into drivers growth guiding policy decisions on achieving sustainable low-carbon economy. strives fulfill ambitious carbon reduction goals, findings highlight significance continuing prioritize provincial

Язык: Английский

Процитировано

1
The Grey Water Footprint of the Guangdong-Hong Kong-Macao Greater Bay Area, China: Spatial Patterns, Driving Mechanism and Implications DOI

Binfen Liu,

Yanhu he,

Qian Tan

и другие.

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

0
Water–carbon–economy multivariate spatial–temporal collaborative relationships and nonlinear projections in urban agglomerations DOI
Pengdong Yan,

Li He,

Tong Sun

и другие.

Journal of Hydrology, Год журнала: 2024, Номер unknown, С. 132040 - 132040

Опубликована: Сен. 1, 2024

Язык: Английский

Процитировано

0
Multi-Dimensional Assessment, Regional Differences, and Influencing Factors of Agricultural Water Pollution from the Perspective of Grey Water Footprint in Zhejiang Province, China DOI Creative Commons
Hua Zhu, Qing Zhang, Hailin You

и другие.

Agriculture, Год журнала: 2024, Номер 14(11), С. 2031 - 2031

Опубликована: Ноя. 12, 2024

The implementation of differentiated governance for agricultural water pollution (AWP) plays a significant role in alleviating the pressure on resources. However, research that comprehensively assesses AWP and its influencing factors from multidimensional perspective remains relatively limited. This study utilized grey footprint (GWF) model to quantify (AGWF), efficiency (AGWFE), intensity (AGWFI), level (AWPL) Zhejiang 2010 2020. Subsequently, we applied standard deviational ellipse (SDE), kernel density estimation (KDE), Dagum Gini coefficient delve into dynamic evolution regional disparities these indicators. Ultimately, leveraged both random forest panel regression identify examine key shaping AGWF-related results show that: (1) From 2020, Zhejiang, AGWF AGWFI exhibit trend first increasing then decreasing, peaking 2012. In contrast, AGWFE has consistently increased over years, reaching an increase 54.56 CNY/m3 by Meanwhile, despite fluctuations, AWPL shows overall gradual decline. (2) centroids relevant indicators are primarily located Jinhua (for AGWFI), Shaoxing AWPL), area where converge. (3) Compared 2010, have shrunk significantly whereas differences some extent. most AGWF, AGWFI, more pronounced Northeastern compared southwestern part. (4) AGWFE, heterogeneity. primary them technological innovation, resource endowment, crop-cultivation methods. Conversely, region, exerting same influence application intensities fertilizers, pesticides, film application. drivers grain yield, availability, crop-planting structure. Notably, do not paper proposes control policies comprehensive multi-dimensional perspective.

Язык: Английский

Процитировано

0
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

Процитировано

1