Quantifying and predicting the Water-Energy-Food-Economy-Society-Environment Nexus based on Bayesian networks - A case study of China

Chai, Jian; Shi, Huiting; Lu, Quanying; Hu, Yi

doi:10.1016/j.jclepro.2020.120266

Cited by 71 publications

(25 citation statements)

References 36 publications

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“…In fact, as Figure 3 shows, the WEF nexus debate was driven by water-centrism and other dominant topics such as sustainable development, climate change, resource governance, water-energy, water-food or energy-food, and different research scales, including watersheds, cities, and urban areas, as well as methods and models, such as the WEF nexus tool 2.0 (Daher and Mohtar, 2015), hybrid input-output (IO) frameworks (Bellezoni et al, 2018;Tabatabaie and Murthy, 2021;Vats et al, 2021), life cycle assessment (LCA) (Mannan et al, 2018;Batlle-Bayer et al, 2020;Li and wen Ma, 2020), qualitative models (Lazaro et al, 2021a), system dynamics modeling (Tan and Yap, 2019;Sušnik et al, 2021), network analysis (Kurian et al, 2018;, coordinated coupling model (Han et al, 2020;Liu et al, 2020), agent-based model (Haltas et al, 2017;Bazzana et al, 2020;Falconer et al, 2020), Institutional Analysis and Development (IAD) (Villamayor-Tomas et al, 2015), topic modeling (Benites- Lazaro et al, 2018), and Bayesian network method (Chai et al, 2020;Shi et al, 2020;Wang et al, 2021).…”

Section: Resultsmentioning

confidence: 99%

Ten Years of Research on the Water-Energy-Food Nexus: An Analysis of Topics Evolution

et al. 2022

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This study explores how the concept and research on the water-energy-food (WEF) nexus has evolved over time. The research uncovers the key terms underpinning the phenomenon, maps the interlinkages between WEF nexus topics, and provides an overview of the evolution of the concept of WEF nexus. We analyzed published academic literature from the Scopus database and performed both qualitative and quantitative analyses using Natural Language Processing method. The findings suggest that the nexus approach is increasingly evolving into an integrative concept, and has been incorporating new topics over time, resulting in different methods for WEF nexus research, with a focus on interdisciplinary and inter-sectoral analyses. Through the five periods outlined, we have identified the nexus approach debate focused on the following predominant topics: i) Trend 1 (2012–2016) debates on WEF nexus for water management and natural resource security, ii) Trend 2 (2017–2018) linkages between the nexus, the sustainable development goals and green economy, iii) Trend 3 (2019) WEF nexus governance and policy integration, iv) Trend 4 (2020) application of the nexus concept on different scales, including regions, countries, watersheds, urban areas as well as other components coupled to the WEF nexus, and, v) Trend 5 (2021) climate change and urban nexus challenges.

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Section: Resultsmentioning

confidence: 99%

Ten Years of Research on the Water-Energy-Food Nexus: An Analysis of Topics Evolution

et al. 2022

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“…In [31], Aragon used the Bayesian networks to investigate the probability of prevalence of financial stability of households in Mexico. Chai et al quantified the causality between the water-energy-foodeconomy-society-environment nexus in China [32]. From the above researches, we find that the Bayesian network can be adopted to investigate the causality path between factors, and it could be useful in the area of economic research.…”

Section: Related Workmentioning

confidence: 99%

The Dynamic Relationship between Macroeconomy and Stock Market in China: Evidence from Bayesian Network

2021

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As the most important component of the capital market, the stock market has always been regarded as the “barometer” of the macroeconomy. However, many researchers have found that the stock market and macroeconomy are operating separately. This paper uses the dynamic Bayesian network method to study the dynamic relationship between the Chinese macroeconomic system and the stock market. The study found that the correlation between the macroeconomic system and the stock market is not consistent in different time periods. For most of the time, the stock system and the macroeconomic system are relatively independent. However, several macroeconomic factors such as Purchase Management Index could affect the stock market through some industries. A conclusion is drawn that the “barometer” function of the stock market is weak and easy to be damaged by factors such as the irrational sentiment of investors.

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“…The Bayesian network consists of three steps: (1) identify the nodes 2) create link between the nodes; 3) creat probabilities relation to each node (Chai et al, 2020). In present research was employed software package Netica for modelling Bayesian network.…”

Section: Bayesian Networkmentioning

confidence: 99%

Assessing Agri-Environmental Indicators and Pollution Impacts on Environmental Performance Index and Agri-Economic Indicators in EU and ME countries: A Bayesian Network Based Model

Firoozzare¹,

Naghavi²

2021

Preprint

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Agricultural sector has a key role in relation to poverty reduction and improving food security.One of important challenges in the agriculture sector is to feed population that is increasing in the world. Agriculture has significant and negative impacts on the environment and earth ecosystems.The agricultural sector growth has made pollution and pollution has restricted increasing production in agricultural. Climate change has led researchers to pay close attention to environmental performance. Bayesian networks are relatively well recognized to be an advantageous method for different types of environmental model. This study was designed a Bayesian network model to investigate the relation between agri-economic-environmental indicators and Environmental performance Index in the EU countries compared to Middle East countries, in 2018. we showed relations between variables of model based on expert interview and previous researches. The results indicated land productivity is directly affected by node Agriculture area certified organic.We predicted with developing Agriculture area certified organic and conservation agricultural area, and productivity can be increased in EU Countries. Also, our findings showed with decreasing N2O and CH4 emissions indicators, increased Enivironmental performance index in EU countries and decreasesd in Middle East countries.Terefore, EU countries is improved agricultural practices and pesticides and fertilizer, But ME countries have not been successful in improving the environmental performance index and sustainable development objectives. Modelling of agri-environmental indicators can help to policymakers about the changes of agro-ecosystem and can use for international reviews.

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Quantifying and predicting the Water-Energy-Food-Economy-Society-Environment Nexus based on Bayesian networks - A case study of China

Cited by 71 publications

References 36 publications

Ten Years of Research on the Water-Energy-Food Nexus: An Analysis of Topics Evolution

Ten Years of Research on the Water-Energy-Food Nexus: An Analysis of Topics Evolution

The Dynamic Relationship between Macroeconomy and Stock Market in China: Evidence from Bayesian Network

Assessing Agri-Environmental Indicators and Pollution Impacts on Environmental Performance Index and Agri-Economic Indicators in EU and ME countries: A Bayesian Network Based Model

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