资源科学 ›› 2021, Vol. 43 ›› Issue (9): 1794-1807.doi: 10.18402/resci.2021.09.07
收稿日期:
2020-11-20
修回日期:
2021-01-18
出版日期:
2021-09-25
发布日期:
2021-11-25
通讯作者:
王红瑞,男,河南新乡人,教授,主要从事水资源系统分析方面研究。E-mail: henrywang@bnu.edu.cn作者简介:
洪思扬,女,辽宁辽阳人,助理研究员,主要从事资源经济方面研究。E-mail: hongsy@mail.bnu.edu.cn
基金资助:
HONG Siyang1,2(), CHENG Tao3,4, WANG Hongrui2(
)
Received:
2020-11-20
Revised:
2021-01-18
Online:
2021-09-25
Published:
2021-11-25
摘要:
经济发展与水资源和能源密不可分,研究水和能源两种资源在宏观经济系统各部门之间的流通特征,挖掘其内在规律,对地区水与能源的高效及可持续利用至关重要。本文以长江经济带为例,运用复杂网络理论创建资源网络模型,从水资源-能源的双重节约和双向节约的新视角发掘资源网络特征。结果表明:①长江经济带水-能源相关要素资源网络具备小世界性及无标度性,网络中关键部门的变化将显著影响整个网络。②江苏的化学产品业、金属冶炼和延加工业、建筑业等部门因具备较大点强度而对长江经济带的水-能源的双重节约作用显著。江苏的化学产品业、金属冶炼和延加工业、电气机械和器材业以及湖北和湖南的电力、热力的生产和供应等部门的节水带来的节能效应和节能带来的节水效应可快速传播至其他部门,对水-能源双向节约作用显著。③研究区内各省市资源流通量大体与经济发展水平呈正相关,江苏、湖南和湖北地区资源流通量较大,云南、贵州和重庆资源流通量相对较小。④对重庆(交通运输、仓储和邮政业)→重庆(租赁和商务服务业)、重庆(建筑业)→重庆(其他服务业)、四川(建筑业)→四川(其他服务业)3条贸易路径中的部门进行合理的资源调控可以显著影响整个网络的资源流通量,从而实现资源节约。本文探究地区水-能源网络特征,旨在为资源高效利用提供有益参考。
洪思扬, 程涛, 王红瑞. 长江经济带水资源-能源网络特征[J]. 资源科学, 2021, 43(9): 1794-1807.
HONG Siyang, CHENG Tao, WANG Hongrui. Characteristics of the water-energy network in the Yangtze River Economic Belt[J]. Resources Science, 2021, 43(9): 1794-1807.
表2
部门名称缩写
编号 | 部门名称 | 缩写 | 编号 | 部门名称 | 缩写 |
---|---|---|---|---|---|
1 | 农林牧渔业 | Ag | 16 | 通用、专用设备制造业 | Ge |
2 | 煤炭采选业 | Cm | 17 | 交通运输设备制造业 | Tr |
3 | 石油和天然气开采业 | Pe | 18 | 电气机械和器材业 | El |
4 | 金属矿采选业 | Mm | 19 | 通信设备、计算机和其它电子设备制造业 | Ec |
5 | 非金属矿和其它矿采选业 | No | 20 | 仪器仪表业 | In |
6 | 食品和烟草业 | Fo | 21 | 其它制造业 | Ot |
7 | 纺织业 | Te | 22 | 电力、热力的生产和供应业 | Eh |
8 | 纺织服装鞋帽皮革羽绒及其制品业 | Cl | 23 | 燃气及水的生产供应业 | Ga |
9 | 木材加工和家具制造业 | Wo | 24 | 建筑业 | Co |
10 | 造纸印刷和文教体育用品业 | Pa | 25 | 交通运输、仓储和邮政业 | Ts |
11 | 石油、炼焦产品和核燃料加工业 | Pr | 26 | 批发和零售业 | Wh |
12 | 化学产品业 | Ch | 27 | 住宿和餐饮业 | Ho |
13 | 非金属矿物制品业 | Np | 28 | 租赁和商务服务业 | Le |
14 | 金属冶炼和压延加工业 | Me | 29 | 科学研究和技术服务业 | Sc |
15 | 金属制品业 | Mp | 30 | 其它服务业 | Os |
表5
4类资源网络中入强度排名前10名的部门
隐含水网络/亿m3 | 隐含能源网络/TJ | 能源耗水网络/亿m3 | 水耗能源网络/TJ | |||||||
---|---|---|---|---|---|---|---|---|---|---|
部门 | 入强度 | 部门 | 入强度 | 部门 | 入强度 | 部门 | 入强度 | |||
2-Ch | 174.45 | 2-Ch | 4.72E+06 | 2-Me | 13.10 | 2-Ch | 1.58E+05 | |||
2-Fo | 145.43 | 2-Me | 4.60E+06 | 9-Eh | 12.32 | 2-Me | 1.54E+05 | |||
6-Fo | 135.48 | 3-Ch | 3.64E+06 | 2-Ch | 11.44 | 2-El | 1.11E+05 | |||
2-Te | 112.81 | 2-El | 3.47E+06 | 6-Co | 11.35 | 2-Ec | 1.01E+05 | |||
2-Me | 87.48 | 2-Co | 3.07E+06 | 6-Ch | 10.82 | 2-Co | 9.58E+04 | |||
9-Fo | 86.61 | 3-Eh | 3.07E+06 | 6-Eh | 10.46 | 6-Co | 8.76E+04 | |||
2-Co | 78.49 | 2-Ec | 2.93E+06 | 11-Eh | 10.05 | 5-Me | 8.52E+04 | |||
7-Fo | 77.54 | 2-Ge | 2.51E+06 | 2-El | 9.93 | 6-Ch | 8.50E+04 | |||
4-Fo | 75.91 | 2-Eh | 2.50E+06 | 3-Ch | 9.48 | 2-Ge | 8.22E+04 | |||
2-Os | 73.87 | 2-Tr | 2.24E+06 | 9-Co | 9.15 | 2-Os | 7.85E+04 |
表6
4类资源网络中出强度排名前10名的部门
隐含水网络/亿m3 | 隐含能源网络/TJ | 能源耗水网络/亿m3 | 水耗能源网络/TJ | |||||||
---|---|---|---|---|---|---|---|---|---|---|
部门 | 出强度 | 部门 | 出强度 | 部门 | 出强度 | 部门 | 出强度 | |||
2-Ag | 254.48 | 2-Me | 6.75E+06 | 6-Eh | 36.33 | 2-Eh | 3.25E+05 | |||
2-Eh | 172.60 | 2-Eh | 6.28E+06 | 9-Eh | 32.01 | 6-Eh | 2.13E+05 | |||
2-Ch | 169.84 | 3-Eh | 6.22E+06 | 11-Eh | 24.31 | 2-Me | 1.95E+05 | |||
6-Ag | 126.64 | 2-Ch | 5.91E+06 | 2-Me | 20.36 | 2-Ch | 1.72E+05 | |||
7-Ag | 126.23 | 3-Ch | 3.94E+06 | 3-Eh | 18.08 | 1-Eh | 1.46E+05 | |||
6-Eh | 114.30 | 10-Cm | 3.44E+06 | 10-Eh | 16.16 | 7-Eh | 1.30E+05 | |||
2-Me | 113.21 | 4-Cm | 3.26E+06 | 2-Eh | 14.28 | 5-Eh | 1.19E+05 | |||
9-Ag | 111.61 | 7-Cm | 2.89E+06 | 7-Eh | 14.22 | 4-Eh | 1.13E+05 | |||
4-Ag | 110.03 | 4-Eh | 2.55E+06 | 2-Ch | 14.10 | 10-Eh | 1.04E+05 | |||
5-Ag | 95.83 | 9-Cm | 2.48E+06 | 3-Ch | 9.92 | 5-Me | 9.23E+04 |
表7
4类资源网络中权重排名前10名的关键边
隐含水/亿m3 | 隐含能源/TJ | 能源耗水/亿m3 | 水耗能源/TJ | |||||||
---|---|---|---|---|---|---|---|---|---|---|
源→目标 | 权重 | 源→目标 | 权重 | 源→目标 | 权重 | 源→目标 | 权重 | |||
2-Ag→2-Fo | 116.56 | 2-Ch→2-Ch | 2.81E+06 | | 6-Eh→6-Eh | 8.87 | 2-Ch→2-Ch | 8.19E+04 | ||
2-Ch→2-Ch | 80.56 | 3-Eh→3-Eh | 2.53E+06 | 11-Eh→11-Eh | 8.80 | 2-Me→2-Me | 5.53E+04 | |||
6-Ag→6-Fo | 75.76 | 3-Ch→3-Ch | 1.92E+06 | 9-Eh→9-Eh | 8.30 | 2-Eh→2-Me | 5.52E+04 | |||
9-Ag→9-Fo | 60.54 | 2-Me→2-Me | 1.92E+06 | 3-Eh→3-Eh | 7.35 | 6-Eh→6-Eh | 5.21E+04 | |||
7-Ag→7-Fo | 54.26 | 10-Cm→10-Cm | 1.35E+06 | 10-Eh→10-Eh | 7.02 | 5-Me→5-Me | 5.09E+04 | |||
4-Ag→4-Fo | 51.07 | 2-Me→2-El | 1.25E+06 | 2-Ch→2-Ch | 6.73 | 1-Eh→1-Eh | 5.06E+04 | |||
6-Fo→6-Fo | 46.03 | 2-Ec→2-Ec | 1.16E+06 | 2-Me→2-Me | 5.80 | 2-Eh→2-Eh | 4.80E+04 | |||
2-Te→2-Te | 44.98 | 5-Me→5-Me | 1.15E+06 | 3-Ch→3-Ch | 4.89 | 10-Eh→10-Eh | 4.52E+04 | |||
2-Ag→2-Te | 43.80 | 7-Cm→7-Eh | 1.07E+06 | 6-Eh→6-Ch | 4.86 | 6-Ch→6-Ch | 4.20E+04 | |||
3-Ch→3-Ch | 34.36 | 9-Cm→9-Eh | 1.07E+06 | 6-Ch→6-Ch | 4.53 | 2-Ec→2-Ec | 4.18E+04 |
表8
4类资源网络中累计权重排名前10位的关键路径
隐含水网络 | 隐含能源网络 |
---|---|
2-Ag→2-Fo | 2-Cm→2-Eh→2-Me→2-El→2-Ec |
6-Ag→6-Fo | 2-Eh→2-Me→2-El→2-Ec |
4-Ag→4-Fo→2-Ch→2-Ec→2-El | 4-Cm→4-Eh→4-Ch→4-Os→4-Wh→4-Fo→2-Ch→2-Ec→2-El |
9-Cm→9-Eh→9-Ch→9-Ag→9-Fo | 2-Mp→2-Me→2-El→2-Ec |
9-Fo→9-Ag→9-Fo | 2-Mm→2-Me→2-El→2-Ec |
9-Eh→9-Ch→9-Ag→9-Fo | 9-Cm→9-Eh→9-Ch→9-Ag→9-Fo |
9-Ch→9-Ag→9-Fo | 2-Ot→2-Me→2-El→2-Ec |
7-Te→7-Cl→7-Ch→7-Ag→7-Fo | 2-Me→2-El→2-Ec |
9-Ag→9-Fo | 4-No→4-Np→4-Co→4-Os→4-Wh→4-Fo→2-Ch→2-Ec→2-El |
7-Cl→7-Ch→7-Ag→7-Fo | 4-Np→4-Co→4-Os→4-Wh→4-Fo→2-Ch→2-Ec→2-El |
能源耗水网络 | 水耗能源网络 |
9-Cm→9-Eh→9-Ch→9-Ag→9-Fo | 2-Cm→2-Eh→2-Me→2-El→2-Ec |
2-Cm→2-Eh→2-Me→2-El→2-Ec | 2-Eh→2-Me→2-El→2-Ec |
2-Eh→2-Me→2-El→2-Ec | 2-Mp→2-Me→2-El→2-Ec |
11-Cm→11-Eh→11-Me→11-Co→11-Os | 2-Mm→2-Me→2-El→2-Ec |
6-Cm→6-Eh→6-Ch→6-Tr→6-Ge | 2-Ot→2-Me→2-El→2-Ec |
6-Eh→6-Ch→6-Tr→6-Ge | 2-Me→2-El→2-Ec |
2-Mp→2-Me→2-El→2-Ec | 6-Cm→6-Eh→6-Ch→6-Tr→6-Ge |
9-Eh→9-Ch→9-Ag→9-Fo | 6-Eh→6-Ch→6-Tr→6-Ge |
11-Eh→11-Me→11-Co→11-Os | 6-No→6-Np→6-Co→6-Os |
2-Mm→2-Me→2-El→2-Ec | 6-Np→6-Co→6-Os |
表9
4类资源网络的关键路径中出现频率最高的10条边
隐含水网络 | 隐含能源网络 | 能源耗水网络 | 水耗能源网络 | |||||||
---|---|---|---|---|---|---|---|---|---|---|
源→目标 | 次数 | 源→目标 | 次数 | 源→目标 | 次数 | 源→目标 | 次数 | |||
8-Os→8-Le | 23 | 8-Os→8-Le | 24 | 8-Os→8-Le | 23 | 8-Os→8-Le | 24 | |||
8-Co→8-Os | 20 | 8-Co→8-Os | 20 | 8-Co→8-Os | 20 | 8-Co→8-Os | 21 | |||
9-Co→9-Os | 15 | 9-Co→9-Os | 15 | 9-Co→9-Os | 15 | 9-Co→9-Os | 15 | |||
9-Os→9-Co | 9 | 9-Os→9-Co | 9 | 9-Os→9-Co | 9 | 9-Os→9-Co | 9 | |||
6-Os→6-Co | 8 | 6-Co→6-Os | 9 | 6-Os→6-Co | 8 | 8-Ts→8-Co | 6 | |||
6-Co→6-Os | 7 | 6-Os→6-Co | 8 | 8-Ts→8-Co | 6 | 9-Me→9-Co | 5 | |||
8-Ts→8-Co | 6 | 8-Ts→8-Co | 6 | 9-Me→9-Co | 5 | 6-Os→6-Co | 5 | |||
9-Me→9-Co | 5 | 9-Me→9-Co | 5 | 9-Ag→9-Fo | 4 | 9-Ag→9-Fo | 4 | |||
9-Ag→9-Fo | 5 | 7-Ag→7-Fo | 5 | 8-Tr→8-Ts | 4 | 8-Tr→8-Ts | 4 | |||
8-Tr→8-Ts | 4 | 9-Ag→9-Fo | 4 | 7-Ag→7-Fo | 4 | 7-Ag→7-Fo | 4 |
[1] | 杨静, 荆平, 高蝶, 等. 京津冀城市群水资源循环经济发展的障碍因子分析[J]. 中国农村水利水电, 2020, (10):131-136. |
[ Yang J, Jing P, Gao D, et al. An analysis of the development obstacle factors of water resource recycling economy in Beijing-Tianjin-Hebei urban agglomeration[J]. China Rural Water and Hydropower, 2020, (10):131-136.] | |
[2] |
Yannopoulos S, Giannopoulou I, Kalafa-Saropoulou M. Investigation of the current situation and prospects for the development of rainwater harvesting as a tool to confront water scarcity worldwide[J]. Water, 2019, 11(10):2168.
doi: 10.3390/w11102168 |
[3] | 周伟, 周旭, 李兆碧, 等. 京津冀地区清洁能源供暖对雾霾的影响[J]. 重庆交通大学学报(自然科学版), 2020, 39(4):98-103. |
[ Zhou W, Zhou X, Li Z B, et al. Impact of clean energy heating on fog and haze in Beijing-Tianjin-Hebei urban agglomeration[J]. Journal of Chongqing Jiaotong University (Natural Science), 2020, 39(4):98-103.] | |
[4] | 李毅, 胡宗义, 刘亦文, 等. 碳强度约束政策对中国城市空气质量的影响[J]. 经济地理, 2019, 39(8):21-28. |
[ Li Y, Hu Z Y, Liu Y W, et al. Impact of carbon intensity constraint policy on urban air quality in China[J]. Economic Geography, 2019, 39(8):21-28.] | |
[5] | 王雷, 朱吉茂, 高俊莲. 能源与水资源的纽带关系研究: 以鄂尔多斯市为例[J]. 生态经济, 2020, 36(9):158-163. |
[ Wang L, Zhu J M, Gao J L. Research on the energy-water nexus: A case study of ordos[J]. Ecological Economy, 2020, 36(9):158-163.] | |
[6] |
施海洋, 罗格平, 郑宏伟, 等. 基于“水-能源-食物-生态”纽带因果关系和贝叶斯网络的锡尔河流域用水分析[J]. 地理学报, 2020, 75(5):1036-1052.
doi: 10.11821/dlxb202005011 |
[ Shi H Y, Luo G P, Zheng H W, et al. Water use analysis of Syr Darya River basin: Based on “Water-Energy-Food-Ecology” nexus and Bayesian network[J]. Acta Geographica Sinica, 2020, 75(5):1036-1052.] | |
[7] | 周露明, 谢兴华, 余丽, 等. 水资源管理中的水-能源-经济耦合关系[J]. 水电能源科学, 2019, 37(4):144-147. |
[ Zhou L M, Xie X H, Yu L, et al. Water-energy-economy coupling relationship in water resources management[J]. Water Resources and Power, 2019, 37(4):144-147.] | |
[8] |
Liu G Y, Hu J M, Chen C C, et al. LEAP-WEAP analysis of urban energy-water dynamic nexus in Beijing (China)[J]. Renewable and Sustainable Energy Reviews, 2021, DOI: 10.1016/j.rser.2020.11 0369.
doi: 10.1016/j.rser.2020.11 0369 |
[9] |
Zaman K, Awan U, Islam T, et al. Econometric applications for measuring the environmental impacts of biofuel production in the panel of worlds’ largest region[J]. International Journal of Hydrogen Energy, 2016, 41(7):4305-4325.
doi: 10.1016/j.ijhydene.2016.01.053 |
[10] |
Duan C C, Chen B. Energy-water nexus of international energy trade of China[J]. Applied Energy, 2017, 194:725-734.
doi: 10.1016/j.apenergy.2016.05.139 |
[11] | Wang S G, Fath B, Chen B. Energy-water nexus under energy mix scenarios using input-output and ecological network analyses[J]. Applied Energy, 2019, 233:827-839. |
[12] |
Nhamo L, Mabhaudhi T, Mpandeli S, et al. An integrative analytical model for the water-energy-food nexus: South Africa case study[J]. Environmental Science and Policy, 2020, DOI: 10.1016/j.envsci.2020.04.010.
doi: 10.1016/j.envsci.2020.04.010 |
[13] |
Wang S G, Chen B. Energy-water nexus of urban agglomeration based on multiregional input-output tables and ecological network analysis: A case study of the Beijing-Tianjin-Hebei region[J]. Applied Energy, 2016, 178:773-783.
doi: 10.1016/j.apenergy.2016.06.112 |
[14] |
Khan H F, Yang Y C E, Xie H, et al. A coupled modeling framework for sustainable watershed management in transboundary river basins[J]. Hydrology and Earth System Sciences Discussions, 2017, DOI: 10.5194/hess-2017-480.
doi: 10.5194/hess-2017-480 |
[15] |
Chen C F, Feng K L, Ma H W. Uncover the interdependent environmental impacts associated with the water-energy-food nexus under resource management strategies[J]. Resources Conservation and Recycling, 2020, DOI: 10.1016/j.resconrec.2020.104909.
doi: 10.1016/j.resconrec.2020.104909 |
[16] | Arora M, Aye L, Malano H, et al. Water-Energy-GHG emissions accounting for urban water supply: A case study on an urban redevelopment in Melbourne[J]. Water Utility Journal, 2013, 6:9-18. |
[17] |
Zhang X D, Vesselinov V V. Integrated modeling approach for optimal management of water, energy and food security nexus[J]. Advances in Water Resources, 2017, 101:1-10.
doi: 10.1016/j.advwatres.2016.12.017 |
[18] |
Wu N N, Xu Y J, Liu X, et al. Water-Energy-Food nexus evaluation with a social network group decision making approach based on hesitant fuzzy preference relations[J]. Applied Soft Computing, 2020,DOI: 10.1016/j.asoc.2020.106363.
doi: 10.1016/j.asoc.2020.106363 |
[19] | 丁宁, 逯馨华, 杨建新, 等. 煤炭生产的水足迹评价研究[J]. 环境科学学报, 2016, 36(11):4228-4233. |
[ Ding N, Lu X H, Yang J X, et al. Water footprint of coal production[J]. Acta Scientiae Circumstantiae, 2016, 36(11):4228-4233.] | |
[20] |
Ding N, Liu J R, Yang J X, et al. Water footprints of energy sources in China: Exploring options to improve water efficiency[J]. Journal of Cleaner Production, 2018, 174:1021-1031.
doi: 10.1016/j.jclepro.2017.10.273 |
[21] | 朱永霞. 社会水循环全过程能耗评价方法研究[D]. 北京: 中国水利水电科学研究院, 2017. |
[ Zhu Y X. Research on Energy Consumption of Whole Process of Social Water Cycle[D]. Beijing: China Institute of Water Resources and Hydropower Research, 2017.] | |
[22] | 姜珊. 水-能源纽带关系解析与耦合模拟[D]. 北京: 中国水利水电科学研究院, 2017. |
[ Jiang S. Scientific Concept of Water-Energy Nexus and Coupling Simulation[D]. Beijing: China Institute of Water Resources and Hydropower Research, 2017.] | |
[23] | Zhang P P, Zhang L X, Chang Y, et al. Food-energy-water (FEW) nexus for urban sustainability: A comprehensive review[J]. Resources, Conservation & Recycling, 2019, 142:215-224. |
[24] | 李桂君, 李玉龙, 贾晓菁, 等. 北京市水-能源-粮食可持续发展系统动力学模型构建与仿真[J]. 管理评论, 2016, 28(10):11-26. |
[ Li G J, Li Y L, Jia X J, et al. Establishment and simulation study of system dynamic model on sustainable development of water-energy-food nexus in Beijing[J]. Management Review, 2016, 28(10):11-26.] | |
[25] |
Dargin J, Daher B, Mohtar R H. Complexity versus simplicity in water energy food nexus (WEF) assessment tools[J]. Science of the Total Environment, 2019, 650:1566-1575.
doi: 10.1016/j.scitotenv.2018.09.080 |
[26] | 洪思扬, 王红瑞, 来文立, 等. 我国能源耗水空间特征及其协调发展脱钩分析[J]. 自然资源学报, 2017, 32(5):800-813. |
[ Hong S Y, Wang H R, Lai W L, et al. Spatial analysis and coordinated development decoupling analysis of energy-consumption water in China[J]. Journal of Natural Resources, 2017, 32(5):800-813.] | |
[27] |
Deng C Y, Wang H R, Gong S X, et al. Effects of urbanization on food-energy-water systems in mega-urban regions: A case study of the Bohai MUR, China[J]. Environmental Research Letters, 2020, 15(4):044014.
doi: 10.1088/1748-9326/ab6fbb |
[28] | Giampietro M, Aspinall R, Bukkens S G F, et al. An Innovative Accounting Framework for the Food-Energy-Water Nexus: Application of the MuSIASEM Approach to Three Case Studies[R]. Rome: Environment and Natural Resources Working Paper No. 56, 2013. |
[29] | Karlberg L, Hoff H, Amsau T, et al. Tackling complexity: Understanding the food-energy-environment nexus in Ethiopia’s Lake Tana Sub-basin[J]. Water Alternatives, 2015, 8(1):710-734. |
[30] | Baskaran T, Blochl F, Bruck T, et al. The Heckscher-Ohlin model and the network structure of international trade[J]. International Review of Economics & Finance, 2011, 20(2):135-145. |
[31] |
Kaluza P, Kolzsch A, Gastner M T, et al. The complex network of global cargo ship movements[J]. Journal of the Royal Society, Interface, 2010, 7(48):1093-1103.
doi: 10.1098/rsif.2009.0495 pmid: 20086053 |
[32] | 高湘昀, 安海忠, 刘红红. 原油期货与现货价格联动性的复杂网络拓扑性质[J]. 物理学报, 2011, 60(6):843-852. |
[ Gao X Y, An H Z, Liu H H. Analysis on the topological properties of the linkage complex network between crude oil future price and spot price[J]. Acta Physica Sinica, 2011, 60(6):843-852.] | |
[33] |
Gao C X, Su B, Sun M, et al. Interprovincial transfer of embodied primary energy in China: A complex network approach[J]. Applied Energy, 2018, 215:792-807.
doi: 10.1016/j.apenergy.2018.02.075 |
[34] |
Gao C X, Sun M, Shen B. Features and evolution of international fossil energy trade relationships: A weighted multilayer network analysis[J]. Applied Energy, 2015, 156:542-554.
doi: 10.1016/j.apenergy.2015.07.054 |
[35] |
Shi J L, Li H J, Guan J H, et al. Evolutionary features of global embodied energy flow between sectors: A complex network approach[J]. Energy, 2017, 140:395-405.
doi: 10.1016/j.energy.2017.08.124 |
[36] |
Hong S Y, Wang H R, Cheng T. Circulation characteristic analysis of implied water flow based on a complex network: A case study for Beijing, China[J]. Water, 2018, 10(7):834-834.
doi: 10.3390/w10070834 |
[37] |
Watts D J, Strogatz S H. Collective dynamics of “small-world” networks[J]. Nature, 1998, 393(6684):440-442.
doi: 10.1038/30918 |
[38] |
Chen G Q, Chen Z M. Carbon emissions and resources use by Chinese economy 2007: A 135-sector inventory and input-output embodiment[J]. Communications in Nonlinear Science and Numerical Simulation, 2010, 15:3647-3732.
doi: 10.1016/j.cnsns.2009.12.024 |
[39] | 邵玲. 体现水的多尺度投入产出分析及其工程应用[D]. 北京: 北京大学, 2014. |
[ Shao L. Multi-scale Input-output Analysis of Embodied Water and its Engineering Applications[D]. Beijing: Peking University, 2014.] | |
[40] | Hong S Y, Yang H, Wang H R, et al. Water and energy circulation characteristics and their impacts on water stress at the provincial level in China[J]. Stochastic Environmental Research and Risk Assessment, 2019: 147-164. |
[41] |
Wang S G, Liu Y T, Chen B. Multiregional input-output and ecological network analyses for regional energy-water nexus within China[J]. Applied Energy, 2018, 227:353-364.
doi: 10.1016/j.apenergy.2017.11.093 |
[42] | 中国城镇供水排水协会. 城市供水统计年鉴[M]. 北京: 中国统计出版社, 2013. |
[China Urban Water Supply and Drainage Association. Urban Water Supply Statistical Yearbook[M]. Beijing: China Statistics Press, 2013.] | |
[43] | 孙晓奇. 基于投入产出网络的全球隐含能源流格局演化研究[D]. 北京: 中国地质大学, 2018. |
[ Sun X Q. Evolution of Global Embodied Energy Flow Patterns Based on Input-Output Network[D]. Beijing: China University of Geosciences, 2018.] | |
[44] | 朱亮峰, 朱学义. 煤炭行业去产能、调整资产结构对煤炭经济的撬动效应[J]. 资源科学, 2021, 43(2):316-327. |
[ Zhu L F, Zhu X Y. Economic prying effect of de-capacity and asset structure adjustment in the coal industry[J]. Resources Science, 2021, 43(2):316-327.] |
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