Energy-climate-manufacturing nexus: New insights from the regional and global supply chains of manufacturing industries

Applied Energy

Volumn 184, Issue , 2016, Pages 889-904

  Kucukvar, Murat ^a   Cansev, Bunyamin ^a   Egilmez, Gokhan ^b   Onat, Nuri C ^c   Samadi, Hamidreza ^a  

^a ISTANBUL SEHIR UNIVERSITY   (Turkey)

^b UNIVERSITY OF NEW HAVEN   (United States)

^c ARIZONA STATE UNIVERSITY   (United States)

Author keywords

Energy climate manufacturing nexus; Global supply chains; Multi region input output analysis; Sustainable manufacturing; World input output database

Indexed keywords

CARBON FOOTPRINT; CLIMATE CHANGE; COMMERCE; EMISSION CONTROL; ENERGY UTILIZATION; GAS INDUSTRY; NUCLEAR FUELS; PETROLEUM REFINING; SALES; SUPPLY CHAIN MANAGEMENT; WATER SUPPLY;

ENERGY-CLIMATE-MANUFACTURING NEXUS; GLOBAL SUPPLY CHAIN; MANUFACTURING INDUSTRIES; OUTPUT ANALYSIS; SUSTAINABILITY ASSESSMENT; SUSTAINABLE MANUFACTURING; SUSTAINABLE SUPPLY CHAINS; TURKISH MANUFACTURING INDUSTRIES;

INDUSTRIAL RESEARCH;

CARBON EMISSION; CARBON FOOTPRINT; DATABASE; ENERGY USE; GLOBAL CLIMATE; GLOBAL ECONOMY; INPUT-OUTPUT ANALYSIS; MANUFACTURING; POLICY MAKING; RETAILING; SUPPLY CHAIN MANAGEMENT; SUSTAINABILITY;

CHINA; TURKEY; UNITED STATES;

EID: 84961962717     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2016.03.068     Document Type: Article

References (108)

1. [1] International Energy Agency (IEA). World energy outlook: energy special report. Available at: < http://www.worldenergyoutlook.org/publications/weo-2013/>; 2013.
2. [2] European Commission. European economy: member states’ energy dependence-an indicator-based assessment; 2013.
3. [3] European Environment Agency. Environmental pressures from european consumption and production; 2013.
4. [4] European Commission. The 2020 climate and energy package. Available at: < http://ec.europa.eu/clima/policies/package/index_en.htm>; 2014.
5. [5] Helm, D., The European framework for energy and climate policies. Energy Policy 64 (2014), 29–35.
6. [6] Turkish Ministry of Environment and Urban Planning. Monitoring and reporting of greenhouse gas emissions. Available at: < http://www.resmigazete.gov.tr/eskiler/2014/07/20140722-5.htm>; 2014.
7. [7] Turkish Ministry of Energy and Natural Resources. Energy efficiency strategy paper. Available at: < http://www.eie.gov.tr/verimlilik/document/Energy_Efficiency_Strategy_Paper.pdf>; 2013.
8. [8] Seuring, S., Müller, M., From a literature review to a conceptual framework for sustainable supply chain management. J Cleaner Prod 16:15 (2008), 1699–1710.
9. [9] Ahi, P., Searcy, C., A comparative literature analysis of definitions for green and sustainable supply chain management. J Cleaner Prod 52 (2013), 329–341.
10. [10] Ayvaz, B., Bolat, B., Aydın, N., Stochastic reverse logistics network design for waste of electrical and electronic equipment. Resour Conserv Recycl 104 (2015), 391–404.
11. [11] Park, Y.S., Egilmez, G., Kucukvar, M., A novel life cycle-based principal component analysis framework for eco-efficiency analysis: case of the United States manufacturing and transportation nexus. J Cleaner Prod 92 (2015), 327–342.
12. [12] Park, Y.S., Egilmez, G., Kucukvar, M., Emergy and end-point impact assessment of agricultural and food production in the United States: a supply chain-linked ecologically-based life cycle assessment. Ecol Ind 62 (2016), 117–137.
13. [13] Sarkis, J., Zhu, Q., Lai, K.H., An organizational theoretic review of green supply chain management literature. Int J Prod Econ 130:1 (2011), 1–15.
14. [14] Seuring, S., A review of modeling approaches for sustainable supply chain management. Decis Support Syst 54:4 (2013), 1513–1520.
15. [15] Soysal, M., Bloemhof-Ruwaard, J.M., van der Vorst, J.G.A.J., Modelling food logistics networks with emission considerations: the case of an international beef supply chain. Int J Prod Econ 152 (2014), 57–70.
16. [16] Egilmez, G., Kucukvar, M., Tatari, O., Sustainability assessment of U.S. manufacturing sectors: an economic input output-based frontier approach. J Cleaner Prod 53 (2013), 91–102.
17. [17] Egilmez, G., Kucukvar, M., Tatari, O., Bhutta, M.K.S., Supply chain sustainability assessment of the U.S. food manufacturing sectors: a life cycle-based frontier approach. Resour Conserv Recycl 82 (2014), 8–20.
18. [18] Feng, K., Chapagain, A., Suh, S., Pfister, S., Hubacek, K., Comparison of bottom-up and top-down approaches to calculating the water footprints of nations. Econ Syst Res 23:4 (2011), 371–385.
19. [19] Bush, R., Jacques, D.A., Scott, K., Barrett, J., The carbon payback of micro-generation: an integrated hybrid input–output approach. Appl Energy 119 (2014), 85–98.
20. [20] Onat, N.C., Gumus, S., Kucukvar, M., Tatari, O., Application of the TOPSIS and intuitionistic fuzzy set approaches for ranking the life cycle sustainability performance of alternative vehicle technologies. Sustain Prod Consumption 6 (2015), 12–25.
21. [21] Onat, N.C., Kucukvar, M., Tatari, O., Conventional, hybrid, plug-in hybrid or electric vehicles? State-based comparative carbon and energy footprint analysis in the United States. Appl Energy 150 (2015), 36–49.
22. [22] Suh, S., Lenzen, M., Treloar, G.J., Hondo, H., Horvath, A., Huppes, G., et al. System boundary selection in life-cycle inventories using hybrid approaches. Environ Sci Technol 38:3 (2004), 657–664.
23. [23] Chen, S., Chen, B., Urban energy consumption: different insights from energy flow analysis, input–output analysis and ecological network analysis. Appl Energy 138 (2015), 99–107.
24. [24] Liu, Z., Geng, Y., Lindner, S., Zhao, H., Fujita, T., Guan, D., Embodied energy use in China's industrial sectors. Energy policy 49 (2012), 751–758.
25. [25] Onat, N.C., Kucukvar, M., Tatari, O., Integrating triple bottom line input–output analysis into life cycle sustainability assessment framework: the case for U.S. buildings. Int J Life Cycle Assess, 2014, 1–18.
26. [26] Song, J., Yang, W., Higano, Y., Wang, X.E., Dynamic integrated assessment of bioenergy technologies for energy production utilizing agricultural residues: an input–output approach. Appl Energy 158 (2015), 178–189.
27. [27] Onat, N.C., Kucukvar, M., Tatari, O., Zheng, Q.P., Combined application of multi-criteria optimization and life-cycle sustainability assessment for optimal distribution of alternative passenger cars in US. J Cleaner Prod 112 (2016), 291–307.
28. [28] Kucukvar, M., Tatari, O., Towards a triple bottom-line sustainability assessment of the U.S construction industry. Int J Life Cycle Assess 18:5 (2013), 958–972.
29. [29] Lenzen, M., Errors in conventional and input–output-based life-cycle inventories. J Ind Ecol 4:4 (2000), 127–148.
30. [30] Matthews, H.S., Hendrickson, C.T., Weber, C.L., The importance of carbon footprint estimation boundaries. Environ Sci Technol 42:16 (2008), 5839–5842.
31. 2 emissions and water consumption. Energy Policy 45 (2012), 440–448.
32. [32] Onat, N.C., Kucukvar, M., Tatari, O., Scope-based carbon footprint analysis of U.S. residential and commercial buildings: an input–output hybrid life cycle assessment approach. Build Environ 72 (2014), 53–62.
33. [33] Wiedmann, T., Minx, J., A definition of ‘carbon footprint’. Ecol Econ Res Trends 1 (2008), 1–11.
34. [34] Kucukvar, M., Egilmez, G., Tatari, O., Sustainability assessment of U.S. final consumption and investments: triple-bottom-line input–output analysis. J Cleaner Prod 81 (2014), 234–243.
35. [35] Larsen, H.N., Hertwich, E.G., Implementing carbon footprint based calculation tools in municipal greenhouse gas inventories. J Ind Ecol 14:6 (2010), 965–977.
36. [36] Lin, J., Liu, Y., Meng, F., Cui, S., Xu, L., Using hybrid method to evaluate carbon footprint of Xiamen City, China. Energy Policy 58 (2013), 220–227.
37. [37] Minx, J.C., Wiedmann, T., Wood, R., Peters, G.P., Lenzen, M., Owen, A., et al. Input–output analysis and carbon footprinting: an overview of applications. Econ Syst Res 21:3 (2009), 187–216.
38. [38] Wiedmann, T., A review of recent multi-region input–output models used for consumption-based emission and resource accounting. Ecol Econ 69:2 (2009), 211–222.
39. [39] Hoekstra R. Towards a complete overview of peer-reviewed articles on environmentally input–output analysis (paper presented at the 18th international input–output conference, Sydney, Australia); 2010.
40. [40] Arto, I., Andreoni, V., Rueda Cantuche, J.M., Global impacts of the automotive supply chain disruption following the Japanese Earthquake of 2011. Econ Syst Res 27:3 (2015), 306–323.
41. [41] Peters, G.P., Hertwich, E.G., The application of multi-regional input-output analysis to industrial ecology. Handbook of input–output economics in industrial ecology, 2009, Springer, Netherlands, 847–863.
42. [42] Wiedmann, T., Barrett, J., Policy-relevant applications of environmentally extended MRIO databases–Experiences from the UK. Econ Syst Res 25:1 (2013), 143–156.
43. [43] Tukker, A., Dietzenbacher, E., Global multiregional input–output frameworks: an introduction and outlook. Econ Syst Res 25:1 (2013), 1–19.
44. [44] Dietzenbacher, E., Los, B., Stehrer, R., Timmer, M., de Vries, G., The construction of world input–output tables in the WIOD project. Econ Syst Res 25:1 (2013), 71–98.
45. [45] Ewing, B.R., Hawkins, T.R., Wiedmann, T.O., Galli, A., Ertug Ercin, A., Weinzettel, J., et al. Integrating ecological and water footprint accounting in a multi-regional input–output framework. Ecol Ind 23 (2012), 1–8.
46. [46] Lan, J., Malik, A., Lenzen, M., McBain, D., Kanemoto, K., A structural decomposition analysis of global energy footprints. Appl Energy 163 (2016), 436–451.
47. 2 emissions in China. Energy Policy 35:3 (2007), 1685–1700.
48. 2 emissions. Appl Energy 148 (2015), 196–209.
49. [49] Zhang, B., Qiao, H., Chen, B., Embodied energy uses by China's four municipalities: a study based on multi-regional input–output model. Ecol Model 318 (2015), 138–149.
50. [50] Andrew, R.M., Peters, G.P., A multi-region input–output table based on the global trade analysis project database (GTAP-MRIO). Econ Syst Res 25:1 (2013), 99–121.
51. [51] Lenzen, M., Moran, D., Kanemoto, K., Geschke, A., Building Eora: a global multi-region input–output database at high country and sector resolution. Econ Syst Res 25:1 (2013), 20–49.
52. [52] Moran, D., Wood, R., Convergence between the EORA, WIOD, EXIOBASE, and OPENEU'S consumption-based carbon accounts. Econ Syst Res 26:3 (2014), 245–261.
53. [53] Oita, A., Malik, A., Kanemoto, K., Geschke, A., Nishijima, S., Lenzen, M., Substantial nitrogen pollution embedded in international trade. Nat Geosci 9:2 (2016), 111–115.
54. [54] Peters, G.P., Andrew, R., Lennox, J., Constructing an environmentally-extended multi-regional input–output table using the GTAP database. Econ Syst Res 23:2 (2011), 131–152.
55. [55] Tukker, A., Poliakov, E., Heijungs, R., Hawkins, T., Neuwahl, F., Rueda-Cantuche, J., et al. Towards a global multi-regional environmentally extended input–output database. Ecol Econ 68:7 (2009), 1928–1937.
56. [56] Galli, A., Weinzettel, J., Cranston, G., Ercin, E., A footprint family extended MRIO model to support Europe's transition to a one planet economy. Sci Total Environ 461 (2013), 813–818.
57. [57] Weber, C.L., Matthews, H.S., Quantifying the global and distributional aspects of American household carbon footprint. Ecol Econ 66:2 (2008), 379–391.
58. [58] Kucukvar, M., Egilmez, G., Onat, N.C., Samadi, H., A global, scope-based carbon footprint modeling for effective carbon reduction policies: lessons from the Turkish manufacturing. Sustain Prod Consumption 1 (2015), 47–66.
59. [59] Kucukvar, M., Samadi, H., Linking national food production to global supply chain impacts for the energy-climate challenge: the cases of the EU-27 and Turkey. J Cleaner Prod 108 (2015), 395–408.
60. [60] Yu, Y., Hubacek, K., Feng, K., Guan, D., Assessing regional and global water footprints for the UK. Ecol Econ 69:5 (2010), 1140–1147.
61. [61] Yu, Y., Feng, K., Hubacek, K., Sun, L., Global implications of China's future food consumption. J Ind Ecol, 2016 [in press].
62. 2 emissions embodied in trade: a multi-region model for China. Appl Energy 114 (2014), 377–384.
63. [63] Wiedmann, T.O., Chen, G., Barrett, J., The concept of city carbon maps: a case study of Melbourne, Australia. J Ind Ecol, 2015 [in press].
64. [64] Andrew, R., Peters, G.P., Lennox, J., Approximation and regional aggregation in multi-regional input–output analysis for national carbon footprint accounting. Econ Syst Res 21:3 (2009), 311–335.
65. [65] Hertwich, E.G., Peters, G.P., Carbon footprint of nations: a global, trade-linked analysis. Environ Sci Technol 43:16 (2009), 6414–6420.
66. [66] Wiedmann, T., Wood, R., Minx, J.C., Lenzen, M., Guan, D., Harris, R., A carbon footprint time series of the UK–results from a multi-region input–output model. Econ Syst Res 22:1 (2010), 19–42.
67. [67] Arto, I., Rueda-Cantuche, J.M., Peters, G.P., Comparing the GTAP-MRIO and WIOD databases for carbon footprint analysis. Econ Syst Res 26:3 (2014), 327–353.
68. [68] Miller, R.E., Blair, P.D., Input–output analysis: foundations and extensions. 2009, Cambridge University Press.
69. [69] Rueda-Cantuche, J.M., Beutel, J., Neuwahl, F., Mongelli, I., Loeschel, A., A symmetric input–output table for EU27: latest progress. Econ Syst Res 21:1 (2009), 59–79.
70. [70] Wiedmann, T., Wilting, H.C., Lenzen, M., Lutter, S., Palm, V., Quo Vadis MRIO? methodological, data and institutional requirements for multi-region input–output analysis. Ecol Econ 70:11 (2011), 1937–1945.
71. [71] Zhang, B., Qiao, H., Chen, Z.M., Chen, B., Growth in embodied energy transfers via China's domestic trade: Evidence from multi-regional input–output analysis. Appl Energy 184 (2016), 1093–1105.
72. [72] Timmer MP. The world input–output database (WIOD): contents, sources and methods. WIOD working paper number 10, downloadable at < http://www.wiod.org/publications/papers/wiod10.pdf>; 2012.
73. [73] EuroStat, Statistical classification of economic activities in the European community. Luxembourg; 2008.
74. [74] Arto, I., Rueda-Cantuche, J.M., Andreoni, V., Mongelli, I., Genty, A., The game of trading jobs for emissions. Energy Policy 66 (2014), 517–525.
75. [75] Leontief, W., Environmental repercussions and the economic structure: an input–output approach. Rev Econ Stat, 1970, 262–271.
76. [76] Bortolamedi, M., Accounting for hidden energy dependency: the impact of energy embodied in traded goods on cross-country energy security assessments. Energy 93 (2015), 1361–1372.
77. [77] MATLAB. Version 7.14.0. Natick. Massachusetts: The Math Works Inc.; 2012.
78. [78] Chaabane, A., Ramudhin, A., Paquet, M., Design of sustainable supply chains under the emission trading scheme. Int J Prod Econ 135:1 (2012), 37–49.
79. [79] Cholette, S., Venkat, K., The energy and carbon intensity of wine distribution: a study of logistical options for delivering wine to consumers. J Cleaner Prod 17:16 (2009), 1401–1413.
80. [80] Egilmez, G., Park, Y.S., Transportation related carbon, energy and water footprint analysis of U.S. manufacturing: an eco-efficiency assessment. Transport Res Part D: Transport Environ 32 (2014), 143–159.
81. [81] Elhedhli, S., Merrick, R., Green supply chain network design to reduce carbon emissions. Transport Res Part D: Transport Environ, 2012.
82. [82] Halldórsson, Á., Kovács, G., The sustainable agenda and energy efficiency: logistics solutions and supply chains in times of climate change. Int J Phys Distrib Logist Manage 40:1/2 (2010), 5–13.
83. [83] Soysal, M., Bloemhof-Ruwaard, J.M., Meuwissen, M.P., van der Vorst, J.G., A review on quantitative models for sustainable food logistics management. Int J Food Syst Dynam 3:2 (2012), 136–155.
84. [84] Bouchery, Y., Ghaffari, A., Jemai, Z., Dallery, Y., Including sustainability criteria into inventory models. Eur J Oper Res 222:2 (2012), 229–240.
85. [85] Hua, G., Cheng, T.C.E., Wang, S., Managing carbon footprints in inventory management. Int J Prod Econ 132:2 (2011), 178–185.
86. [86] Benjaafar, S., Li, Y., Daskin, M., Carbon footprint and the management of supply chains: insights from simple models. IEEE Trans Autom Sci Eng 10:1 (2013), 99–116.
87. [87] Kissinger, M., Rees, W.E., An interregional ecological approach for modelling sustainability in a globalizing world—reviewing existing approaches and emerging directions. Ecol Model 221:21 (2010), 2615–2623.
88. [88] Moser, S.C., Communicating climate change: history, challenges, process and future directions. Wiley Interdiscipl Rev: Climate Change 1:1 (2010), 31–53.
89. [89] Sterman, J.D., Communicating climate change risks in a skeptical world. Climatic Change 108:4 (2011), 811–826.
90. [90] Sterman, J.D., Sweeney, L.B., Understanding public complacency about climate change: adults’ mental models of climate change violate conservation of matter. Climatic Change 80:3–4 (2007), 213–238.
91. [91] Arto, I., Dietzenbacher, E., Drivers of the growth in global greenhouse gas emissions. Environ Sci Technol 48:10 (2014), 5388–5394.
92. [92] Lenzen, M., Aggregation versus disaggregation in input–output analysis of the environment. Econ Syst Res 23:1 (2011), 73–89.
93. 2 multipliers in multiregional input–output analyses. Econ Syst Res 26:3 (2014), 284–302.
94. [94] Lenzen, M., Wood, R., Wiedmann, T., Uncertainty analysis for multi-region input–output models–a case study of the UK's carbon footprint. Econ Syst Res 22:1 (2010), 43–63.
95. [95] Okadera, T., Watanabe, M., Xu, K., Analysis of water demand and water pollutant discharge using a regional input–output table: an application to the City of Chongqing, upstream of the Three Gorges Dam in China. Ecol Econ 58:2 (2006), 221–237.
96. [96] Elkington J. Cannibals with forks. The triple bottom line of 21st century; 1997.
97. [97] Clift, R., Metrics for supply chain sustainability. Technological choices for sustainability, 2004, Springer Berlin Heidelberg, 239–253.
98. [98] Seuring, S., Sarkis, J., Müller, M., Rao, P., Sustainability and supply chain management–an introduction to the special issue. J Cleaner Prod 16:15 (2008), 1545–1551.
99. [99] Foran, B., Lenzen, M., Dey, C., Bilek, M., Integrating sustainable chain management with triple bottom line accounting. Ecol Econ 52:2 (2005), 143–157.
100. [100] Wiedmann, T., Lenzen, M., Unravelling the impacts of supply chains—a new triple-bottom-line accounting approach and software tool. Environmental management accounting for cleaner production, 2009, Springer, Netherlands, 65–90.
101. [101] Balancing the G20’s Global Impacts. Available at: < http://www.csu.edu.au/research/ilws/publications/technical-reports/g20s-global-impact>; 2014.
102. [102] Egilmez, G., Tatari, O., A dynamic modeling approach to highway sustainability: strategies to reduce overall impact. Transport Res Part A: Policy Practice 46:7 (2012), 1086–1096.
103. [103] Onat, N.C., Egilmez, G., Tatari, O., Towards greening the U.S. residential building stock: a system dynamics approach. Build Environ 78 (2014), 68–80.
104. [104] Sterman JD. Business Dynamics: system thinking and modeling for a complex world. Boston; 2000.
105. [105] Onat, N.C., Kucukvar, M., Tatari, O., Egilmez, G., Integration of system dynamics approach toward deepening and broadening the life cycle sustainability assessment framework: a case for electric vehicles. Int J Life Cycle Assess, 2016, 1–26.
106. [106] Davies EGR. An integrated system dynamics model for analyzing behaviour of the social-economic-climatic system: model description and model use guide; 2008.
107. [107] Sterman, J.D., Weinstein, M.P., Turner, R.E., (eds.) Sustainability science, 2012, Springer New York, New York, NY.
108. [108] U.S. EPA, Inventory of U.S. Greenhouse gas emissions and sinks: 1990–2011. 2013, Office of Global Warming, Washington, DC.