A study on energy-water-food-carbon nexus in typical Chinese northern rural households

Nexus(标准) 水能 食物能量 农业经济学 自然资源经济学 碳纤维 中国 地理 业务 环境科学 环境保护 经济 工程类 化学 复合数 生物化学 嵌入式系统 复合材料 考古 材料科学
作者
Gengyuan Liu,Shupan Du,Yuan Gao,Xiaoping Xiong,Ginevra Virginia Lombardi,Fanxin Meng,Yu Chen,Caocao Chen
出处
期刊:Energy Policy [Elsevier BV]
卷期号:188: 114100-114100 被引量:3
标识
DOI:10.1016/j.enpol.2024.114100
摘要

The energy-water-food-carbon nexus of rural households requires different strategies from those of urban households. This study proposes a nexus framework and a quantitative method to analyze the energy, water, food, and carbon of typical northern rural households in China. A system dynamic model of the rural household energy-water-food-carbon nexus was developed. Three scenarios were designed, namely appliance, behavior, and price, with 42 sub scenarios in total to explore the medium to long-term dynamic changes in energy-water-food-carbon in rural households under different scenarios. The results of the appliance scenario show that there is a strong water-gas and food-gas nexus effect in northern rural households. Compared with the BAU scenario, reducing the consumption of meat and dairy by 5% can save 11.89% of gas and reduce 5.64% of carbon. Moreover, the policy simulation results indicate that a policy will affect not only its target subsystem, but also other subsystems, creating a policy nexus. The behavior adjustment scenarios have a strong nexus effect on water and energy, and resource price adjustment scenarios have a good effect on water and food consumption. Therefore, when making policies at the household level, policy makers need to look at each subsystem comprehensively, use the synergistic effect of policies skillfully and avoid the antagonistic effect of policies, in order to optimize the positive effect of policies.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
谦让的莺完成签到,获得积分10
刚刚
せん完成签到,获得积分10
刚刚
yeah完成签到,获得积分10
刚刚
1秒前
脑洞疼应助ROC采纳,获得10
2秒前
共享精神应助WW采纳,获得30
2秒前
jizzy发布了新的文献求助10
3秒前
靓丽红牛完成签到,获得积分10
3秒前
云Qi发布了新的文献求助10
3秒前
3秒前
3秒前
帅气的芷文关注了科研通微信公众号
4秒前
6秒前
猫先生发布了新的文献求助10
8秒前
8秒前
二分发布了新的文献求助10
9秒前
11秒前
12秒前
蘑菇丰收发布了新的文献求助10
13秒前
molihuakai应助JJ采纳,获得10
13秒前
科研通AI6.1应助lqx采纳,获得10
14秒前
王开阔发布了新的文献求助10
14秒前
二分完成签到,获得积分10
15秒前
玉堂堂发布了新的文献求助10
15秒前
cloverdown发布了新的文献求助30
16秒前
在水一方应助ssss采纳,获得10
17秒前
SciGPT应助177采纳,获得30
19秒前
19秒前
今后应助177采纳,获得10
19秒前
在水一方应助177采纳,获得10
19秒前
无花果应助177采纳,获得10
19秒前
CodeCraft应助177采纳,获得10
19秒前
星辰大海应助helwo采纳,获得10
19秒前
细腻的曼柔完成签到,获得积分10
19秒前
AREA4完成签到,获得积分10
20秒前
21秒前
蘑菇丰收完成签到,获得积分10
22秒前
英俊的铭应助Fanny采纳,获得10
23秒前
23秒前
粗心的八宝粥完成签到,获得积分10
24秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Chemistry and Physics of Carbon Volume 18 800
The Organometallic Chemistry of the Transition Metals 800
The formation of Australian attitudes towards China, 1918-1941 640
Signals, Systems, and Signal Processing 610
全相对论原子结构与含时波包动力学的理论研究--清华大学 500
Elevating Next Generation Genomic Science and Technology using Machine Learning in the Healthcare Industry Applied Machine Learning for IoT and Data Analytics 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6443372
求助须知:如何正确求助?哪些是违规求助? 8257256
关于积分的说明 17586014
捐赠科研通 5501953
什么是DOI,文献DOI怎么找? 2900861
邀请新用户注册赠送积分活动 1877922
关于科研通互助平台的介绍 1717521