CET Volume 86 DOI: 10.3303/CET2186074 Paper Received: 21 October 2020; Revised: 17 February 2021; Accepted: 1 May 2021 Please cite this article as: Wang X.-C., Klemes J.J., Varbanov P.S., 2021, Water-energy-carbon Network Critical Transmissions: Case Study of China, Chemical Engineering Transactions, 86, 439-444 DOI:10.3303/CET2186074 CHEMICAL ENGINEERING TRANSACTIONS VOL. 86, 2021 A publication of The Italian Association of Chemical Engineering Online at www.cetjournal.it Guest Editors: Sauro Pierucci, Jiří Jaromír Klemeš Copyright © 2021, AIDIC Servizi S.r.l. ISBN 978-88-95608-84-6; ISSN 2283-9216 Water-Energy-Carbon Network Critical Transmissions: Case Study of China Xue-Chao Wanga,b,*, Jiří Jaromír Klemešc, Petar Sabev Varbanovc a State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China. b School of Natural Resources Science and Technology, Faculty of Geographical Science, Beijing Normal University Beijing 100875, China. c Sustainable Process Integration Laboratory - SPIL, NETME Centre, Faculty of Mechanical Engineering, Brno University of Technology - VUT Brno, Technická 2896/2, 616 69, Brno, Czech Republic. xcwang@bnu.edu.cn This study seeks to explore the Energy-Carbon-Water nexus of China, identifying the regional transmissions of embodied energy consumption, CO2 emissions and water consumption in the coastal area of China. Nice provinces are taken into consideration, and the Multi-Region Input-Output model is employed. The critical transmissions of embodied Energy-Carbon-Water among different provinces have been analysed. Results show that: i) Hebei export the most embodied energy and Zhejiang import the most embodied energy; ii) The structure of embodied CO2 emissions transmissions is similar with that of embodied energy consumption; iii) Guangdong benefits the most from the regional embodied water transmissions system, and Jiangsu contributes the most. This study contributes to a better understanding of the regional embodied Energy-Carbon-Water nexus system, providing a reference for future studies of other regions in the world. 1. Introduction Increasing strategies, targets, and policies have been setting up and revolve around water use, energy consumption and CO2 emissions. Regional or sectoral water utilisation, energy consumption, CO2 emissions, etc., are usually employed for showing the environmental performance, however, which is not the complete picture. As three of the most crucial elements of environmental strategies, water, energy and CO2 emissions are profoundly entwined in more complicated and invisible ways (Wang et al., 2020a). The critical transmissions of embodied-water-utilisation, -energy-consumption and -CO2-emissions among multiple economic sectors (Fernando et al., 2021) and multi-region constitute the complicated virtual Energy-CO2-Water (ECW) network (Wang et al., 2020b). Water, energy and low-CO2 emissions offer a foundation for the development of the environment, the economy and society. However, global challenges, including water scarcity, energy crises and increasing global warming, threaten sustainable development in many regions worldwide (Xu et al., 2020). Compared with the Paris Agreement (Sumaila et al., 2019) and the United Nation Framework Convention on Climate Change (UNFCCC) (Roe et al., 2019), the 17 UN Sustainable Development Goals (SDGs) provide a more comprehensive goal (THE 17 GOALS, 2021). The more humanity centric holistic approach of the 17 UN SDGs was proposed by the UN together with political leaders globally, where clean water, affordable and clean energy, and climate actions within the context of a sustainable partnership are spelt out so that a sustainable future for all human beings will be built up equitably and in peace. The key intermedia of the ECW network is inter-regional trade. A massive amount of embodied water utilisation, energy consumption and carbon emissions are transferred (Liu et al., 2017) with the products and services during the inter-sectoral and inter-regional trades (Chen et al., 2019). The accumulation amount of sectoral or regional embodied material consumption or emissions might be much larger or lower than the direct value. For example, the direct water consumption of the agriculture sector is much more than that of embodied amount. Conversely, heavy industry and light industry have much higher values of embodied water and energy consumption (Wang et al., 2021). The resources availability and embodied resources consumption of a specific 439 region can be different or even contradictory as well (Lu et al., 2018). It demonstrates that the results from the sectoral-based and supply-chain-based perspectives can be significantly different. Although the embodied ECW net export countries can benefit a lot in terms of economic gain, they significantly bear the consequences of environmental pressure, including water consumption, energy consumption and carbon emissions (Wang et al., 2020b). Conversely, the embodied ECW net import countries can benefit from the inter-regional trade in terms of environmental impacts. The results might be uplifting if from the global perspective as the complicated ECW network contributes to reducing the consumption of water and energy and the CO2 emissions. For example, while contributing to the equivalent annual economic output, the EU27 consume 6.5 × 1010 t less water and 4.9 × 1018 J less energy and emit 1.4 × 109 t less CO2 compared to the rest of the world, which significantly contributes to relieving the environmental pressure (Wang et al., 2020b). The importance is to balance the mutual benefits among all stakeholders. It is crucial to measure the sectoral and regional environmental performance from the supply chain perspective and identify the impact factors (Liang et al., 2016), however, which still needs more in-depth exploration. As the largest developing, the ECW network is propped up by economic supply chains, which have been properly identified by existing works (Li et al., 2021). Inter-regional and inter-sectoral trades result in major displacements of environmental impacts, accompanying by the transmissions of a large amount of flows of embodied water utilisation, energy consumption and CO2 emissions (Wiedmann and Lenzen, 2018). The embodied materials have been increasingly transferred from developing to developed countries because of the booming international trade (Peters et al., 2011). Inter-regional trade can well explain the regional consumption of water and energy and CO2 emissions, standing for the importance of identifying the regional or even global shaping factors and critical transmissions of the ECW network. It is crucial for accurately recognising the key impact factors of shaping the sectoral and regional environmental performance (Zhang et al., 2020). It is also important for identifying the key nodes to improve production efficiency and reduce the environmental impacts from the supply chain perspective. However, sectors that serve as shaping factors and intermedia in the embodied ECW network are usually overlooked. As a result of the large population, along with the rapid economic development, China is facing different kinds of environmental pressure, such as intensive CO2 emissions, water scarcity, water uneven distribution and energy crisis (Wang et al., 2021). China contributes to 27 % of global CO2 emissions, which is higher than any of other single country (Ritchie and Roser, 2017). China aims to hit peak emissions by 2030 and pledges to go carbon emissions neutral by 2060 (Climate Change, 2021). Reducing CO2 emissions or mitigating climate change have been at the core of all strategies and measures of China. China is also facing the serious challenge of water resource shortage due to uneven water distribution and water scarcity. The proportion of the population facing water shortages has increased fourfold worldwide during the past two centuries (Kummu et al., 2016), and around one-third of the population in China are residing in the areas with serious water stress under the increasing national water demand (Wang et al., 2019). For narrowing the research gaps mentioned above, this paper aims at exploring the regional transmissions of embodied water-energy-carbon system, taking the coastal area of China as a case. The critical transmissions of embodied water consumption, energy consumption and carbon emissions have been identified among different regions in the coastal area of China. 2. Data In this study, nine provinces in the coastal area of China are involved, including Liaoning, Hebei, Tianjin, Shandong, Jiangsu, Shanghai, Zhejiang, Fujian and Guangdong. All data used in this study are consistent with the year 2015, as the latest Multi-Region Input-Output (MRIO) database of China is of 2015 (CEADs, 2021). The energy consumption, CO2 emissions and water consumption data of different regions were collected and processed from the China Statistical Yearbook of the Environment (National Bureau of Statistics of China, 2021) and the CEADs database (CEADs, 2021). All data used in this study are public and are available from China's National Bureau of Statistics. All data can be downloaded for free. 3. Method The Multi-Region Input-Output (MRIO) is used in this study. Although the MRIO depends on big sets of consistent and systematic data, which are usually slightly lagging, it is a widely used and effective method with good robustness for handling economic and environmental data from the supply chain perspective. It is a useful tool for solving similar issues. The framework is shown in Figure 1, where Ind means Industries, Com is commodities, FD is final demand, VA means value added (also called primary inputs), Indicators are from satellite indicator accounts of the MRIO model, documenting nonmonetary inputs to production, IIOT is the Industry by Industry input-output (IO) tables; CIOT means the Commodity by Commodity IO table. 440 Figure 1: The framework of the MRIO model Nine regions and 42 economic sectors are considered in this study. Based on the MRIO model, the following equations are employed in this study. The water-relevant indicators, 𝜀 and 𝜀 , are took as examples to show the calculating processes, and introduce the following notations: 𝐿 𝜀 ⋯ 𝜀 ⋯ 𝜀 ⋯ 𝜀 (1) 𝐸 𝑒 ⋯ 𝑒 ⋯ 𝑒 ⋯ 𝑒 , (2) 𝑍 ⎣ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎡ 𝑧 , , ⋯ 𝑧 , , ⋮ ⋱ ⋮ 𝑧 , , ⋯ 𝑧 , , ⋯ 𝑧 , , ⋯ 𝑧 , , ⋮ ⋱ ⋮ 𝑧 , , ⋯ 𝑧 , , ⋮ ⋱ ⋮ 𝑧 , , ⋯ 𝑧 , , ⋮ ⋱ ⋮ 𝑧 , , ⋯ 𝑧 , , ⋯ 𝑧 , , ⋯ 𝑧 , , ⋮ ⋱ ⋮ 𝑧 , , ⋯ 𝑧 , , ⎦ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎤ (3) 𝑌 ⎣ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎡ ⎝ ⎜ ⎜ ⎜ ⎛ 𝑧 , , 𝑓 , , ⋱ 𝑧 , , 𝑓 , , ⎠ ⎟ ⎟ ⎟ ⎞ ⋱ ⎝ ⎜ ⎜ ⎜ ⎛ 𝑧 , , 𝑓 , , ⋱ 𝑧 , , 𝑓 , , ⎠ ⎟ ⎟ ⎟ ⎞ ⎦ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎤ (4) where 𝜀 indicates the embodied water intensity of sector j in province s, 𝑧 , , indicates the intermediate flow from sector j in province r to sector i in province s, 𝑓 , , means the final demand of term k in the province s from sector i in province r, (k = 1, 2, 3, 4, 5, indicate final consumption expenditures by households, non-profit organisations 441 serving households and government, as well as changes in inventories and valuables and the gross fixed capital formation). Based on the MRIO model, there is a balance in the MRIO table: 𝐸 𝐿𝑍 𝐿𝑌 (5) Then the import embodied water consumption (𝐼𝐸𝑊 ) and export embodied water consumption (𝐸𝐸𝑊 ) of sector i in province r can be given as: 𝐼𝐸𝑊 ∑ 𝜀 𝑧 , , , 𝑟 𝑠 (6) 𝐸𝐸𝑊 ∑ 𝜀 𝑧 , , , 𝑟 𝑠 (7) The import embodied water consumption (𝐼𝐸𝐸 ) and export embodied water consumption (𝐸𝐸𝐸 ) of province r can be obtained: 𝐼𝐸𝑊 ∑ 𝐼𝐸𝑊 (8) 𝐸𝐸𝑊 ∑ 𝐸𝐸𝑊 (9) 4. Results 4.1 Regional Transmissions of Embodied Energy Consumption Table 1 shows the regional transmissions of embodied energy consumption in the coastal area of China. Hebei exports the most embodied energy at 1,975 PJ, followed by Jiangsu and Shandong. Hebei is the largest steel- producing province in China, accounting for around one-third of iron and steel products in China and one-eighth of worldwide (Wang et al., 2021). A huge amount of steel products is transported from Hebei to other regions in China or even the world. Regarding the total import amounts, Zhejiang province import the most embodied energy, which is 1,861 PJ, followed by Guangdong and Jiangsu. These three provinces have an import value that higher than 1,000 PJ. they are big economic provinces in China and have higher GDP than most other regions. They import the most embodied energy from Hebei province main because of the steel production trade. Table 1: Regional Transmissions of Embodied Energy Consumption, (PJ) Tianjin HebeiLiaoning ShanghaiJiangsu ZhejiangFujian Shandong Guangdong Total Export Tianjin 27 34 50 97 87 14 40 104 454 Hebei 78 113 166 575 537 55 102 349 1,975 Liaoning 52 63 156 181 233 22 66 149 922 Shanghai 20 49 47 109 181 33 65 187 691 Jiangsu 95 83 161 219 411 77 44 517 1,608 Zhejiang 32 29 39 101 127 23 38 117 507 Fujian 17 14 23 63 58 79 23 93 369 Shandong 41 77 72 149 262 228 39 229 1,096 Guangdong 26 30 39 81 114 104 21 33 448 Total Import 362 371 529 983 1,524 1,861 284 411 1,745 4.2 Regional Transmissions of Embodied CO2 Emissions Water Consumption Table 2 presents the regional transmissions of embodied CO2 emissions across the coastal provinces of China. The structure of embodied CO2 emissions transmissions is similar to that of embodied energy consumption, as energy consumption related activities are the main contributors of CO2 emissions. Regions of Zhejiang, Guangdong and Jiangsu, lead the list of total embodied CO2 emissions import at 164 Mt, 156 Mt and 142 Mt. The main embodied CO2 import source of them is Hebei province, importing 44 Mt, 29 Mt and 48 Mt. This is mainly due to importporing a large number of steel products from Hebei. During the regional trade, they transfer significant environmental pressure to Hebei as well. Regarding the total export amount, Hebei, Jiangsu and Shandong export the most embodied CO2 emissions at 166 Mt, 147 Mt and 122 Mt. They export lots of products to other regions and benefit from the economy; however, they are also under big environmental pressure. 442 Table 2: Regional Transmissions of Embodied CO2 emissions, (Mt) Tianjin HebeiLiaoning ShanghaiJiangsu ZhejiangFujian Shandong Guangdong Total Export Tianjin 2.3 3.0 4.2 8.7 7.3 1.3 3.4 8.7 38.9 Hebei 6.9 9.6 14.0 48.2 44.6 4.7 9.1 29.2 166.3 Liaoning 5.4 5.4 13.7 14.5 18.1 1.7 8.2 12.1 79.0 Shanghai 1.7 4.2 3.8 9.8 14.9 2.8 5.3 15.3 57.7 Jiangsu 8.7 7.5 14.6 20.1 37.5 7.0 4.3 47.4 147.1 Zhejiang 3.8 2.9 3.6 11.1 12.3 2.2 6.4 10.7 52.9 Fujian 2.0 1.4 2.0 6.4 5.1 6.8 3.4 8.1 35.3 Shandong 4.3 8.5 7.7 16.6 31.4 24.8 4.5 24.6 122.4 Guangdong 3.3 3.4 3.9 9.1 11.9 10.3 2.1 5.4 49.4 Total Import 36.2 35.6 48.1 95.2 141.8 164.3 26.3 45.5 156.0 4.3 Regional Transmissions of Embodied Water Consumption Table 3 shows the regional transmissions of embodied water consumption. Different from the patterns of embodied energy consumption and CO2 emissions, Guangdong import the most embodied water from other regions, at 63×108 m3, followed by Zhejiang and Jiangsu at 54×108 m3 and 36×108 m3. Guangdong has the biggest GDP amount in China, with the most developed economy. It imports a large number of products from the other regions of China every year, with a large amount of embodied water. Regarding the total export amount, Jiangsu export the most embodied water at 74.7×108 m3, and the biggest gainer is Guangdong at 22.4×108 m3, followed by Zhejiang at 17.3×108 m3. The 2nd place of total export list is Shandong province at 37.1×108 m3, which is much less than that of Jiangsu. Table 3: Regional Transmissions of Embodied Water consumption, (108 m3) Tianjin HebeiLiaoning ShanghaiJiangsu ZhejiangFujian Shandong Guangdong Total Export Tianjin 0.8 1.2 1.2 2.7 2.0 0.8 0.7 3.2 12.6 Hebei 3.2 2.2 2.9 8.4 8.1 1.3 10.5 9.8 46.5 Liaoning 1.9 1.9 2.4 3.6 4.7 0.6 6.6 5.1 26.6 Shanghai 0.6 1.3 1.3 2.9 4.5 0.9 1.6 4.8 18.0 Jiangsu 5.1 4.1 7.0 8.8 17.3 3.3 6.8 22.4 74.7 Zhejiang 1.2 1.0 1.5 2.8 4.1 0.8 1.5 4.1 17.1 Fujian 1.0 0.9 2.1 2.6 2.8 4.5 1.3 5.8 21.0 Shandong 2.3 2.3 4.0 4.3 7.3 7.6 1.4 7.8 37.1 Guangdong 1.5 1.6 2.9 3.8 5.1 5.4 1.0 1.3 22.6 Total Import 16.8 13.8 22.0 28.8 36.9 54.1 10.1 30.3 63.2 5. Conclusions This study identified the regional transmissions of embodied energy-carbon-water system, taking the coastal area china as cases. The critical transmissions of embodied energy consumption, CO2 emissions and water consumption among nine provinces have been calculated. Main contributions include: (i) Hebei exports the most embodied energy at 1,975 PJ, as it is the largest steel-producing province in China, accounting for around one-third of iron and steel products in China and one-eighth of worldwide. It exports a large number of steel products to other regions every year. Regarding the total import amounts, Zhejiang province benefits the most, importing 1,861 PJ of energy, followed by Guangdong and Jiangsu. These three provinces have an import value that higher than 1,000 PJ. Hebei province is their biggest contributor. (ii) The structure of embodied CO2 emissions transmissions is similar to that of embodied energy consumption, which is because that energy consumption related activities are the main contributors of carbon emissions. Zhejiang, Guangdong, and Jiangsu import the most embodied CO2 emissions at 164 Mt, 156 Mt and 142 Mt. They transfer big environmental pressures to the upstream regions from the supply chain perspective. Hebei is the biggest contributor as a large number of steel products are traded from Hebei to these three provinces. Hebei, Jiangsu and Shandong export the most embodied CO2 emissions. (iii) The pattern of embodied water consumption transmission is different from that of energy consumption and CO2 emissions. Guangdong import the most embodied water at 63×108 m3, followed by Zhejiang and Jiangsu at 54×108 m3 and 36×108 m3. They are with the most developed economy in China, importing a large number of products from the other regions of China Jiangsu export the most embodied water at 74.7×108 m3, and the biggest gainer is Guangdong at 22.4×108 m3. 443 References Chen S., Tan Y., Liu Z., 2019, Direct and embodied energy-water-carbon nexus at an inter-regional scale, Applied Energy 251, 113401. DOI: 10.1016/j.apenergy.2019.113401. Climate change: China aims for “carbon neutrality by 2060”, 2021, , accessed 4.24.2021. CEADs, Input-Output Tables, 2021, , accessed 5.7.2021. Kummu M., Guillaume J.H.A., de Moel H., Eisner S., Flörke M., Porkka M., Siebert S., Veldkamp T.I.E., Ward P.J., 2016, The world’s road to water scarcity: shortage and stress in the 20th century and pathways towards sustainability, Scientific Reports, 6, 38495. doi: 10.1038/srep38495. Fernando W.L.R., Karunathilake H.P., Gamage J.R., 2021, Strategies to reduce energy and metalworking fluid consumption for the sustainability of turning operation: A review, Cleaner Engineering and Technology, 3, 100100, doi: 10.1016/j.clet.2021.100100. Li K., Feng C., Liang Y., Qi J., Li Y., Li H., Liang S., Yang Z., 2021. Critical transmission sectors for provincial food-water nexus in China, Journal of Cleaner Production, 279, 123886, doi: 10.1016/j.jclepro.2020.123886. Liu X., Klemeš, J.J., Varbanov P.S., Čuček L., Qian Y., 2017, Virtual carbon and water flows embodied in international trade: a review on consumption-based analysis, Journal of Cleaner Production, 146, 20-28. doi: 10.1016/j.jclepro.2016.03.129. Liang S., Qu S., Xu M., 2016. Betweenness-Based Method to Identify Critical Transmission Sectors for Supply Chain Environmental Pressure Mitigation, Environmental Science & Technology, 50, 1330–1337, doi: 10.1021/acs.est.5b04855. Lu N., Wei H., Fan W., Xu Z., Wang X., Xing K., Dong X., Viglia S., Ulgiati S., 2018. Multiple influences of land transfer in the integration of Beijing-Tianjin-Hebei region in China, Ecological Indicators, 90, 101–111, doi: 10.1016/j.ecolind.2018.02.057. National Bureau of Statistics of China, 2021. , accessed 5.7.2021. Peters G.P., Minx J.C., Weber C.L., Edenhofer O., 2011. Growth in emission transfers via international trade from 1990 to 2008, Proceedings of the National Academy of Sciences 108, 8903–8908, doi: 10.1073/pnas.1006388108. Ritchie H., Roser M., 2017. CO₂ and Greenhouse Gas Emissions (Last revised in December 2019), Our World in Data, , accessed 07.05.2021. Roe S., Streck C., Obersteiner M., Frank S., Griscom B., Drouet L., Fricko O., Gusti M., Harris N., Hasegawa T., Hausfather Z., Havlík P., House J., Nabuurs G.-J., Popp A., Sánchez M.J.S., Sanderman J., Smith P., Stehfest E., Lawrence D., 2019. Contribution of the Land Sector to a 1.5 °C World. Nature Climate Change, 9, 817–828, doi: 10.1038/s41558-019-0591-9. Sumaila U.R., Tai T.C., Lam V.W.Y., Cheung W.W.L., Bailey M., Cisneros-Montemayor A.M., Chen O.L., Gulati S.S., 2019. Benefits of the Paris Agreement to ocean life, economies, and people, Science Advances, 5, eaau3855, doi: 10.1126/sciadv.aau3855. THE 17 GOALS | Sustainable Development, 2021. UN Department of Economic and Social Affairs , accessed 4.20.2021. Wang C., Wang R., Hertwich E., Liu Y., Tong F., 2019. Water scarcity risks mitigated or aggravated by the inter- regional electricity transmission across China, Applied Energy, 238, 413–422, doi: 10.1016/j.apenergy.2019.01.120. Wang X.-C., Klemeš J.J., Long X., Zhang P., Varbanov P.S., Fan W., Dong X., Wang Y., 2020a. Measuring the environmental performance of the EU27 from the Water-Energy-Carbon nexus perspective. Journal of Cleaner Production, 265, 121832, doi: 10.1016/j.jclepro.2020.121832. Wang X.-C., Klemeš J.J., Ouyang X., Xu Z., Fan W., Wei H., Song W., 2021. Regional embodied Water-Energy- Carbon efficiency of China, Energy, 224, 120159, doi: 10.1016/j.energy.2021.120159. Wang X.-C., Klemeš J.J., Wang Y., Foley A., Huisingh D., Guan D., Dong X., Varbanov P.S., 2020b. Unsustainable imbalances and inequities in Carbon-Water-Energy flows across the EU27. Renewable and Sustainable Energy Reviews, 138, 110550, doi: 10.1016/j.rser.2020.110550. Wiedmann T., Lenzen M., 2018. Environmental and social footprints of international trade. Nature Geoscience, 11, 314–321, doi: 10.1038/s41561-018-0113-9. Xu Z., Chen X., Liu J., Zhang Y., Chau S., Bhattarai N., Wang Y., Li Y, Connor T., Li Y, 2020. Impacts of irrigated agriculture on food–energy–water–CO2 nexus across metacoupled systems. Nature Communications, 11, 5837, doi: 10.1038/s41467-020-19520-3. Zhang C., He G., Zhang Q., Liang S., Zipper S.C., Guo R., Zhao X., Zhong L., Wang J., 2020. The evolution of virtual water flows in China’s electricity transmission network and its driving forces. Journal of Cleaner Production, 242, 118336, doi: 10.1016/j.jclepro.2019.118336. 444