Development of multidimensional water poverty in the Yangtze River Economic Belt, China

Yuan, Liang; Yang, Dongquan; Wu, Xin; He, Weijun; Kong, Yang; Ramsey, Thomas Stephen; Degefu, Dagmawi Mulugeta

doi:10.1016/j.jenvman.2022.116608

Cited by 42 publications

(15 citation statements)

References 59 publications

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“…The article used the gray prediction model GM (1.1) to predict the decoupling relationship between agricultural pollution reduction and economic growth in the YRD from 2021 to 2030. The BP neural network model was combined to train the prediction results with unqualified PLOS ONE accuracy until they were qualified [63,64] Specifically, in 2021, the agricultural carbon reduction effect was negatively decoupled from economic growth in Chuzhou, Fuyang, Huainan, Huangshan, Suzhou and Wuhu, the…”

Section: Predicted Decoupling Of Agricultural Pollution and Carbon Re...mentioning

confidence: 99%

Decoupling agriculture pollution and carbon reduction from economic growth in the Yangtze River Delta, China

Yuan

Xu²,

Kong³

2023

PLoS ONE

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Agriculture is the foundation of the national economy, and agricultural nonpoint source pollution and carbon emissions are the main environmental problems limiting the development of the agricultural economy. This study takes the Yangtze River Delta as the research object and measures agricultural carbon emissions and nonpoint source pollution in the study area from 2010 to 2020 respectively. The Tapio decoupling model is used to study types of decoupling between agricultural pollution and carbon reduction and economic growth in the Yangtze River Delta from 2010 to 2020, and the GM (1,1) model is used to predict the decoupling relationship between the agricultural environment and economic growth over the next ten years. The results show the following: (1) Agricultural COD emissions come mainly from livestock and poultry breeding, dropped from 1,130,120 tons in 2010 to 908,460 tons in 2020. Agricultural TN and TP emissions come mainly from plantations. Agricultural TN emissions dropped from 892,310 tons in 2010 to 788,020 tons in 2020. Agricultural TP emissions dropped from 149,590 tons in 2010 to130,770 tons in 2020. Agricultural carbon emissions dropped from 17,115,900 tons in 2010 to 15,786,600 tons in 2020, and come mainly from agricultural fertilizer and diesel fuel and pig breeding. (2) The decoupling effect of agricultural pollution reduction and carbon reduction in the Yangtze River Delta and economic growth has been in a long-term state, with negative decoupling occurring in a few regions, mainly in 2011, 2014 and 2020. (3) In the next ten years, except for 2021, when the coordination between agricultural pollution reduction and economic growth is poor, the two show good decoupling in the remaining years. Based on the results, this study makes recommendations on how to carry out comprehensive environmental management and promote green agricultural development.

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Section: Predicted Decoupling Of Agricultural Pollution and Carbon Re...mentioning

confidence: 99%

Decoupling agriculture pollution and carbon reduction from economic growth in the Yangtze River Delta, China

Yuan

Xu²,

Kong³

2023

PLoS ONE

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“…Step (1): Initialize the parameters, set the population size N, the maximum number of iterations max, and the position of the fruit fly population X_axis, Y_axis, and give the random direction and distance of each fruit fly individual; then the fruit fly individual begins to search for food using the sense of smell [36][37][38]:…”

Section: Fruit Fly Optimization Algorithmmentioning

confidence: 99%

Combined Forecasting Model of Precipitation Based on the CEEMD-ELM-FFOA Coupling Model

Zhang

2023

Water

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Precipitation prediction is an important technical mean for flood and drought disaster early warning, rational utilization, and the development of water resources. Complementary ensemble empirical mode decomposition (CEEMD) can effectively reduce mode aliasing and white noise interference; extreme learning machines (ELM) can predict non-stationary data quickly and easily; and the fruit fly optimization algorithm (FFOA) has better local optimization ability. According to the multi-scale and non-stationary characteristics of precipitation time series, a new prediction approach based on the combination of complementary ensemble empirical mode decomposition (CEEMD), extreme learning machine (ELM), and the fruit fly optimization algorithm (FFOA) is proposed. The monthly precipitation data measured in Zhengzhou City from 1951 to 2020 was taken as an example to conduct a prediction experiment and compared with three prediction models: ELM, EMD-HHT, and CEEMD-ELM. The research results show that the sum of annual precipitation predicted by the CEEMD-ELM-FFOA model is 577.33 mm, which is higher than the measured value of 572.53 mm with an error of 4.80 mm. The average absolute error is 0.81 and the average relative error is 1.39%. The prediction value of the CEEMD-ELM-FFOA model can closely follow the changing trend of precipitation, which shows a better prediction effect than the other three models and can be used for regional precipitation prediction.

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“…With the deepening of the reform and opening-up policy, China has gradually developed into the world's second-largest economy, its international infuence is increasing, and its economic and social development has entered a new normal. However, with economic and social development, China still faces many difculties and challenges such as the severe ecological and environmental situation, unbalanced regional development, and the difcult task of industrial transformation and upgrading [24]. In the face of uncertain disturbance factors, the development level of urban resilience will be afected by the regional development background, leading to diferences in the infuencing factors of urban resilience in diferent regions.…”

Section: Study Design and Data Selectionmentioning

confidence: 99%

The Driving Path of China’s Urban Resilience Enhancement in the Digital Economy Era

Tang

Jiang

Zhang

et al. 2023

Discrete Dynamics in Nature and Society

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Promoting the development of China’s digital economy and the level of urban disaster reduction and governance is of great significance for accelerating the improvement of China’s urban resilience and promoting the coordinated development of regional cities. This paper analyzed the spatial and temporal distribution characteristics and driving paths of urban resilience in 31 Chinese provinces, autonomous regions, and municipalities directly under the central government and proposed relevant measures to promote urban resilience. First, the urban resilience evaluation system was constructed and the entropy value method was applied to calculate the urban resilience index of each region. Second, the spatial distribution of urban resilience was explored based on the urban resilience index of each region. Finally, a qualitative comparative analysis method was used to explore the driving paths of urban resilience enhancement. The study showed that there were large regional differences in the urban resilience index, with an overall spatial pattern of “good in the east, middle in the center, and low in the west” and an overall trend of gradual increase. There are five configuration paths to generate a high urban resilience index, which can be specifically digital industry-driven path, technology factor-driven path, government input- and talent pool-driven path under market factors, technology factor- and government factor-driven path, and government investment- and infrastructure-driven path under market factors, and it is found that the digital industry-driven path is a more common path of digital economy-driven urban resilience improvement in China. The finding of this study reveals the nature of complex interactions among drivers in the process of urban resilience enhancement in China, which breaks through the limitations of traditional statistical analysis methods and provides a new perspective for the study of urban resilience issues.

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Development of multidimensional water poverty in the Yangtze River Economic Belt, China

Cited by 42 publications

References 59 publications

Decoupling agriculture pollution and carbon reduction from economic growth in the Yangtze River Delta, China

Decoupling agriculture pollution and carbon reduction from economic growth in the Yangtze River Delta, China

Combined Forecasting Model of Precipitation Based on the CEEMD-ELM-FFOA Coupling Model

The Driving Path of China’s Urban Resilience Enhancement in the Digital Economy Era

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