Exploring urban energy-water nexus embodied in domestic and international trade: A case of Shanghai

Journal of Cleaner Production 223 (2019) 522e535

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Exploring urban energy-water nexus embodied in domestic and international trade: A case of Shanghai Asim Nawab a, Gengyuan Liu a, c, *, Fanxin Meng b, d, **, Yan Hao a, b, Yan Zhang a, b, Yuanchao Hu c, Marco Casazza e a

State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing, 100875, China Research Center for Eco-Environmental Engineering, Dongguan University of Technology, Dongguan, 523808, China Beijing Engineering Research Center for Watershed Environmental Restoration & Integrated Ecological Regulation, Beijing, 100875, China d School of Environment and Energy, South China University of Technology, Guangzhou, Guangdong, 510006, China e University of Naples ‘Parthenope’, Department of Science and Technology, Centro Direzionale, Isola C4, 80143, Naples, Italy b c

a r t i c l e i n f o

a b s t r a c t

Article history: Received 9 June 2018 Received in revised form 16 January 2019 Accepted 11 March 2019 Available online 15 March 2019

Rapid urban expansion and economic development has led to severe demands of energy and water resources, which poses serious challenges to sustainability and environment. Previous studies have taken more consideration of one resource flow ignoring the interconnectedness between energy and water. In this paper, an urban energy-water nexus framework is constructed considering both domestic and international trade, based on the environmentally extended multi-scale input-output (EE-MSIO) model. This method allows us to trace energy and water flows in a multi-scale economic system from production and consumption perspectives. In basis of that, the nexus strengthen indicator is constructed to evaluate the energy-water nexus of the trading regions with Shanghai city in the domestic and international trade to present the integrated environmental pressure externalized in Shanghai’s rapid economic development. Findings indicate that Shanghai is a net importer of energy and water flow. This result is compatible with the fact that Shanghai is a consumer city. Additionally, the seven domestic regions in China are net exporters toward Shanghai, supporting around 55.10% of energy and 70.56% of water import flows driven by city’s final demand. Shanghai largely imports flows of energy and water from Mainland China and developing regions across the globe, whereas export little to developed nations. Nexus results indicate that from consumption perspective, Hebei and Shandong are of the highest nexus strength embodied in domestic trade with Shanghai, with nearly equal contribution for both energy and water. While USA is the largest energy-water nexus node embodied in international trade with Shanghai, around 60% energy and 40% water contributed to the nexus. During these tradeoffs, Shanghai is the major beneficiary, being able to externalize environmental pressures by consumption of domestic and international exported goods and services. The study outcomes suggest that a higher coordination, together with a rearrangement of the regional trade structure, should be the key leverages for an effective management of resources and environment. © 2019 Elsevier Ltd. All rights reserved.

Keywords: EE-MSIO Consumption-based Production-based Energy-water nexus Trade

1. Introduction

* Corresponding author. State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing, 100875, China. ** Corresponding author. Research Center for Eco-Environmental Engineering, Dongguan University of Technology, Dongguan, 523808, China. E-mail addresses: [email protected] (G. Liu), [email protected] (F. Meng). https://doi.org/10.1016/j.jclepro.2019.03.119 0959-6526/© 2019 Elsevier Ltd. All rights reserved.

In today’s globalized world, economic development and urban expansion pose significant challenges in securing adequate energy and water supplies to meet demand at regional, national and supra national level. Energy and water policies at various levels have several interwoven challenges, such as resources access, environmental impacts and specific national priorities (Chen et al., 2018). Huge quantity of water is needed directly and indirectly for energy production and supply (e.g. coal mining,

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electricity), while energy is consumed for ground water extraction, distribution and waste water treatment. Tracing energy and water flows among regions and determining their mutual dependencies are important for an affordable energy and water balance accounting (IEA, 2016). With this respect, the nexus concept is a useful metaphor to highlight energy water interlinkages and their twisted conversion pathways in supply chains (Chen and Chen, 2015). In recent years, researchers have extended the study scope, investigating energy-water nexus at multiple scales. For example, Rambo et al. (2017) constructed the first nation-wide Sankey diagram to reveal the embedded interlinks in water treatment and energy generation in Saudi Arabia. Dubreuil et al. (2013) built a water model used to evaluate an optimal water energy mix considering prospects for water recycle and use in water deprived Middle East region. Zhu et al. (2015) analyzed the virtual water flows parallel with electricity flows within China power system. To analyze virtual water in electricity sector in China, Guo et al. (2016) applied ecological network analysis and proposed an indicator to measure the impact of virtual water flows. In addition, Fang and Chen (2017) used linkage analysis to identify synergetic effects of energy-water use and exchanges within economic sectors of Beijing. Wang and Chen (2016) inventoried energy consumed for water, water used for energy, embodied energy use and embodied water use, developing a hybrid framework for nexus system in JingJin-Ji region. Chen and Chen (2016) developed a system-based framework to evaluate energy water nexus in different urban sectors. For studying energy-water nexus, specific tools and methods were implemented. For nexus analysis, the general practice is to focus on parallel relationship of both elements: water use for energy production and energy consumption for water provision. Most researchers used bottom-up methods to evaluate nexus (Okadera et al., 2014). Yang and Chen (2016) conducted a nexus analysis for wind power generation systems, estimated water use for power generation and energy cost of water provision using life cycle assessment (LCA). Santana et al. (2014) studied to what extent influent water quality impacts drinking water treatment operations and consequently embodied energy of drinking water using LCA at city scale. In these studies, requirements of a product or substance through whole supply chain and complete process-based estimations are provided to ensure accuracy of material flow analysis (MFA) and LCA, thereby tracking resource flows (i.e. water and energy) individually within the systems with required help of available databases. Due to different data availability at different levels, the top down approaches are considered more feasible than bottom up ones (Zhang et al., 2018). The input output analysis (IOA) can be applied to calculate both direct and indirect resource flows to account the quantity needed for generating products and services, based on sectoral linkages in a complex system (Arto et al., 2016). Chen and Chen (2016) proposed a system-based framework for urban energy-water nexus using ecological network and input-output analysis. Wang and Chen (2016) constructed a network model for urban agglomeration energy-water nexus based on multiregional input output (MRIO) and ecological network analysis. Further, multi-regional input output (MRIO) accounting was applied to analyze regional characteristic and sectoral disparities. This approach revealed the differences in national and international production technologies (Zhang et al., 2016). MRIO analysis depends on regional input-output (IO) tables and trade data, that can trace resource flows from source (produced in one region) to destination (consumed in another region). Moreover, it can be often applied to energy and water system of urban centers also focusing on single aspects such as virtual water (Tian et al., 2018)

523

energy (Chen and Wu, 2017) and carbon footprint (Lin et al., 2017). Studies related to energy-water nexus mostly focused on particular production processes (e.g.: water treatment, power generation or biofuel production) whereas limited attention was given to explore this issue from an economic system perspective. As the physical flows of water and energy are hidden in traded goods, it would be logical to use embodied energy or virtual water to explore energy-water use in an economic system, as to identify how resources in one country are used to support consumption in another country. In order to provide a holistic picture of resource transfers, researchers now use both production-based and consumptionbased accounting approaches (PBA and CBA). PBA flows are generated by domestic activities comprising exports (Peters, 2008), ignoring indirect flows embodied in supply chain outside the boundary. On the other hand, CBA embodied flows are caused by consumption activities, that consist of imports embodied in goods trade but ignore exports (Brizga et al., 2017). Such analysis reveals the characteristic and detect key locations of resource consumption. Then, it becomes possible to focus on these locations for saving resources and environmental degradation. Therefore, it is vital to differentiate between energy and water trade flows at different levels. In this regard, MSIO model, derived from MRIO, can provide a detailed investigation, capturing mutual dependencies of the world economic system, while maintaining regional differences (Bachmann et al., 2015; Wiedmann, 2009). To the best of our knowledge, studies relating to urban nexus issues and energy and water transfers via trade from production and consumption perspectives are still limited. Previous studies on resource flows mainly focused on a single scale. Taking Shanghai as a case (referred to year 2010), this study proposes a nexus framework, based on the environmentally extended multi-scale inputoutput (EE-MSIO) model, to quantify the flows and interdependencies of energy and water at different levels. The nexus focus relates to the combined resources usage resulting from economic activities. A nexus strength indicator is developed, aimed at showing the intensity of resources usage in a system. This study aims at identifying the key points of combined resources supply and use within the urban economic system, gaining new insights into urban production-based and consumption-based energy and water flows. Thus, by applying energy-water nexus approach, the relevant connections, competing both inland and global resources demand and the associated environmental pressures in Shanghai’s transnational and inter-regional trade, were investigated. The second part of this work provides a brief description of Shanghai. The following section details the method and the data collected for this study. The fourth section presents the analysis of obtained results. Then, results are discussed and compared with previous research, considering also their limitations. Finally, conclusion of the study is presented in the sixth section. 2. Case study Shanghai, located on Yangtze river delta, is considered among the most advanced mega cities in the world, serving as a financial center of China. The city has 17 districts, covering an area of about 6340 km2. Its population reached 23.02 million in 2010, being 1.8 percent of the national Chinese population. The city grew in importance because of its economic potential related to the key commercial and industrial hub in the country. Since China’s reform and opening up, Shanghai has experienced rapid development, with the GDP reaching 1716.6 billion CNY in 2010 from 27.3 billion CNY in 1978, with an average growth rate of 13.82% (SMSB, 2011; NBSC, 2011). Heavy industrial activities, such as ship construction,

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Global Economy National Economy

Consumption Urban Economic System

Flow Analysis

Energy

Trade Water

Nexus Strength Indicator

Production

Fig. 1. Framework of urban energy-water nexus embodied in domestic and international trade in a multi-scales economy.

steel and car manufacturing, continue to be key part of its economy (Yang et al., 2018b). For Shanghai city, its ratio of the ‘three-industry structure’1 was 1:42:57 in 2010. The contribution rate for economic growth of the tertiary industries reached 31.2% of the total increase. Its urbanization ratio has reached 88.86% in 2010 ranking the first in China, which has caused unprecedented environmental stress. In 2010, Shanghai’s per capita energy consumption is 446.28 kg coal equivalent (kgce) nearly 1.76 times of that in national average level (254.2 kgce). In the case of water, Shanghai’s per capita water use was 559.7 m3 more than the average value of 450.2 m3 water use per capita in China. Notably, Shanghai’s per capita water resource was 163.1 m3, accounting for just 7% of the national average value (2310.4) in 2010 (NBSC and MEP, 2011). Overall, Shanghai, as a municipality with fewer water resources and less energy production, but possesses a huge demand for both resources (Yang et al., 2018a). Shanghai as an international port city has closer relationships with many economies around the world (domestic trade), including mainland China regions and foreign countries (international trade). Therefore, there is a strong demand for a systematic and comprehensive evaluation on the urban energy-water nexus embodied in domestic and international trade in a multi-scales economy for Shanghai city.

perspectives (Meng et al., 2018). Basically, it connects Multi Regional Input-Output Table (MRIOT) of Chinese regions (2010) to World Input-Output Table (WIOT), based on World Input-Output Database (WIOD). Researcher already used such linkages in several studies (e.g., Feng et al., 2014; Mi et al., 2017; Meng et al., 2018). Peters et al. (2011) presented the key linking method in more detail. In EE-MSIO model, the world is divided into 41 countries/regions, while 35 economic sectors per country/region (1435 sectors) are considered in the WIOD (Dietzenbacher et al., 2013; Timmer et al., 2015). In WIOD, China is among the 41 regions. The Chinese IO table in WIOD is disaggregated into 30 regions, according to MRIO model of China. It mainly consists of 30 provinces (4-municipalities and 26 provinces), excluding Taiwan and Tibet. Liu et al. (2014) compiled the Chinese MRIOT and has been widely used in previous studies. According to domestic trade exchanges in China’s MRIOT, international exports and imports matrices for China in WIOD are disaggregated and allocated to the 30 provinces. In each province, foreign exports for every sector are circulated between importing sectors in international regions at equal proportion as total exports of China. This process is accounted according to the following formula:

3. Method

T Cs ij T ps ¼PP ij

3.1. Framework design and EE-MSIO model The urban energy-water nexus framework is constructed and applied for modeling the complex flows of energy and water embodied in the domestic and international trade in a multi-scales economy, as shown in Fig. 1. It is in basis of the EE-MSIO model, which has been constructed at three scales (i.e. city-nationalglobal) relies on MRIO table and describes trade flows in multi scale economic system from both production and consumption

1 The ‘three-industry structure’ is the unit of measurement that the Chinese government uses to track economic activity across various sectors. The three industries are primary, secondary, and tertiary industries. Primary industries include agriculture, forestry, livestock husbandry, and fisheries; secondary industries include heavy industry (mining and quarrying, manufacturing, electricity, gas and water production, and supply industries, etc.) and construction; and tertiary industries include other industries not covered by the primary and secondary categories, mainly referring to the service sector.

s

Cs j Tij

XX ps Tij i

(1)

j

where, T ps , taken from the world MRIO table, describes the monij etary flow (export) from sector i in region p to sector j in region s. In WIOD, T Cs ij is total monetary flow (export) from mainland China to region s. Once EE-MSIO model is calculated, a coordinate matrix is applied to get 20 aggregated sectors from two different MRIOTs (Oita et al., 2016). As a result, we get an EE-MSIO model with 70 regions and 1400 (20 sectors region) sectors in total, with four Chinese cities included. A detailed list of regions is given in Table 1. Key to abbreviations: Mainland China (MC); European Union (EU); other European countries outside of the EU (Non-EU); Main North American countries (NAFTA); Japan, Korea and Taiwan, China (as East Asia); Brazil, Russia, India, Indonesia, Australia, and Turkey (BRIIAT); Rest of the world (RoW). Production-based and Consumption-based urban energy and water flows in the multi-scale economic system can be evaluated by the trade relationship in the EE-MSIO model, considering the

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Table 1 Regions studied in the EE-MSIO model. Regions

Areas covered

Mainland China

Beijing Tianjin, Hebei, Shandong Heilongjiang, Jilin, Liaoning Henan, Shanxi, Anhui, Jiangxi, Hubei, Hunan Shanghai, Jiangsu, Zhejiang

Beijing North Northeast Central Central coast South coast Southwest Northwest World regions EU Non-EU EA BRIIAT NAFTA RoW

Fujian, Guangdong, Hainan Guangxi, Chongqing, Sichuan, Guizhou, Yunnan Inner Mongolia, Shannxi, Gansu, Qinghai, Ningxia, Xinjiang Austria, Belgium, Cyprus, Estonia, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Malta, Netherlands, Portugal, Slovakia, Slovenia and Spain Bulgaria, Czech Rep, Denmark, Hungary, Latvia, Lithuania, Poland, Romania, Sweden, the UK, Japan, Korea, and Taiwan Brazil, Russia, India, Indonesia, Australia, and Turkey Canada, Mexico, and the USA Other countries (except the above) in the world

sectoral interconnections inside a city and abroad. Applied equations for calculation in EE-MSIO model are taken from the literature (Liang et al., 2017; Lin et al., 2017). The key input output balance is represented through the following matrix:

0

0

1 A11 x1 B x2 C B A21 B C B B x3 C ¼ B B B C B A31 @ « A @ « xm Am1

A12 A22 A32 « Am2

A13 A23 A33 « Am3

… … … 1 …

0 X 1s 1 y C 1 BX B s 2s C A1m x1 B C y CB 2 C B C A2m C Bx C BX C s C 3m CB x3 C þ B 3s C A y B B C C C@ A B C A « « B s C m B C « mm X x @ A A yms 10

(2)

s

where, coefficient matrix A show intermediate input matrix across sectors and regions. The vector x is the total output of each economic sector in each region. The embodied environmental impacts can be mathematically presented as follows:

E ¼ Re ðI  AÞ1 Y

(3)

W ¼ Rw ðI  AÞ1 Y

(4)

where, E and W represent the embodied energy and water matrix induced by the final demand of the whole economic system, respectively. Re and Rw are the diagonal matrix representing the pressure coefficient of energy consumption and water consumption, respectively. The diagonal elements are direct water consumption coefficient (Rwi) and direct energy consumption coefficient (Rci). (I-A)1 is the Leontief inverse matrix. Y is a diagonal matrix, while the diagonal element Yj represents the final demands of products and services in sector j. 3.2. Nexus strength indicator The word “nexus” derives from the Latin verb nectere, which means “to connect”. In particular, it represents the relationships between two or more resources, though the term nexus still lacks of a clear definition (De Laurentiis et al., 2016). In scientific literature, the nexus concept is considered as a new thinking and promising approach (Ringler et al., 2013), supportive to ensure a sustainable use of resources (Saladini et al., 2018). For understanding nexus issues, researchers described their unique perspective about

resource interactions and provided suggestions regarding drivers and impacts. Earlier studies applied a number of performance indicators mainly from consumption and intensity aspects, in order to evaluate nexus, like the energy intensity of water use (Kahrl and Roland-Holst, 2008) or the energy return on water invested (Voinov and Cardwell, 2009). Furthermore, some systems-based indicators commenced to focus on the betweenness and dependence of social economic system (Wang and Chen, 2016; Zimmerman et al., 2016). Nonetheless, it did not differentiate the significance among the different ecological elements. In fact, all the ecological elements were seen as equally significant, ignoring their differences, like resource quality, scarcity, price and so on. Moreover, the qualitative evaluation on the correlation between multiple ecological elements was absent. For understanding, suppose that region/country A uses 10 units of energy and 5 units of water while region/country B uses 5 units of energy and 10 units of water. How to evaluate the nexus strength of ecological elements in each region largely depends on two factors: how to decide the importance of different ecological elements, and how to carry the unified accounting for all the ecological elements with different units. It is commonly associated with the concept of environmental multidimensionality or incommensurability. In this study, we assess the nexus strength of the trading regions with Shanghai city in the domestic and international trade to present the integrated environmental pressure externalized in Shanghai’s rapid economic development. The nexus strength is defined and constructed according to the flows of energy and water calculated by the EE-MSIO model. Using the concept of ecological footprint, widely applied in sustainability assessments (Rees, 1992), the nexus strength indicator provides an integrated accounting of multiple ecological resources (energy and water in this study) usage in a multi-scales economy. To determine nexus strength of a specific trading region or country with Shanghai city, two steps should be performed: one is the standardization for energy-water flows embodied in domestic and international trade by “current flow/maximum flow” in both production and consumption perspectives; another step is the weighting scheme for energy and water. In this study, we assign equal weights (1/2 each) to energy and water, representing that energy and water of each trading region has the same importance. Finally, the nexus strength is based on a metric range from 0 (no use of resources) to 1 (maximum use for all resources). Mathematically, the summation of nexus strength for each region can be formulated as follows:

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Nexus strength ¼ pw dw;c þ pe de;c with c2C; C ¼ f1; …:; ng o n gw;c dw;c ¼ ; gw ¼ max gw;c c2C gw o n ge;c de;c ¼ ; ge ¼ max ge;c c2C ge n X

(5)

ðpn Þ ¼ 1; R ¼ fw; eg

R

where, w, e stand for water and energy respectively; c stand for country/regions; C represents the set of all regions; Taking water as an example, gw,c represents the production-based or consumptionbased water flows of country/region c; gw represents the largest regional production-based or consumption-based water flows among all regions; dw,c represents the deviation between the regional largest water flows and water flows of region c both for production or consumption perspectives; p is a weight that determines the relative importance of a given resource; pw represents the weight of water resource, 0.5 is fixed for both energy and water in this study. 3.3. Data sources In this study, the environmental satellite account includes direct energy consumption and water consumption from Shanghai, domestic regions and international regions in a multi-scales economy, namely 70 regions with 20 industries each. For 30 regions (including Shanghai) in China, the energy consumption each region was estimated on the basis of the Provincial Energy Balance Table and Energy Statistical Yearbook in China 2011 (research year 2010). In this study, the fraction of energy consumption only includes the one used for production purposes, while fossil fuel is only considered in our research. All the energy data metrics are unified as ton standard coal equivalent (tce). Energy used for energy processing and conversion are accounted within electricity production sector, while electricity and heating consumption in the final consumption sectors are not accounted to avoid double counting. For 30 regions (including Shanghai) in China, the water consumption data are not officially published annually for each economic sector. Thus, detailed data processing and sources for water consumption needed to be defined. Collection and estimation of water consumption data involve several steps and rely on the ‘water footprint’ concept (Hoekstra et al., 2011). The green water and blue water are accounted, while grey water is not included. Water consumption is accounted according to different methods for agriculture sector, secondary industrial sector, construction sector, services sector. The detailed method was introduced in the previous research (Meng et al., 2019). The direct energy and water consumption data for the 40 WIOD global regions are from WIOD database. And the scope for water and energy consumption is consistent with that for 30 regions in China. 4. Results 4.1. General flow analysis In this study, an EE-MSIO model was employed to trace the energy and water flows of Shanghai city in 2010 based on PBA and CBA. The PBA approach can account for flows of energy and water embodied in goods produced locally and distinguish its destination

for local consumption, domestic exports and international exports. The CBA approach can account for energy and water flows embodied in goods consumed locally and distinguish its origin for local production, domestic imports and international imports. The overall flow pattern for energy and water can be observed in Fig. 2 (a)-(b). In particular, Fig. 2 (a) presents that production related flows of energy in urban territorial boundaries were 91.61Mtce, out of that 38% flowed in the city by virtue of local consumption, 32% flowed into domestic regions and 30% flowed into international regions by exports. Consumption related flows of energy were 125.55 Mtce (about 1.37 times more than production-based energy flows). Out of that, 28% flowed in the city because of local production and 72% flowed beyond city border. Focusing on Fig. 2 (b), water-related production flows in urban territorial boundaries were 10697.54 Mt. Out of that, 53% flowed in the city by virtue of local consumption, 23% flowed into domestic regions and 24% flowed into international regions by exports. Water-related consumption flows were 44651.13 Mt (about 4.17 times more than production-based water flows). Out of that, 13% flowed in the city because of local production and 87% flowed beyond city limits. These findings indicate that Shanghai imported huge quantity of embodied energy and water for local consumption and externalize environmental impacts by consumption of goods and services produced elsewhere. Also, it highlights that traditional territorial accounting method may underestimate actual resources consumed. To broaden our understanding, detailed domestic and international flow structure can be seen below. (i) For energy Fig. 3 shows the energy flows embodied in domestic goods and service exchanges, are traced and quantified in domestic regions in China. The North (6.88 Mtce), Central (6.25 Mtce) and Northwestern China (4.08 Mtce) were the three largest regions for domestic energy outflows. This gives an indication, that transferring of energy flows from these domestic regions were undertaken by Shanghai, accounting for 58% of domestic exported energy flows taking place inside Shanghai borders. The Central (21.17 Mtce), North (15.06 Mtce) and Central Coast (11.45 Mtce) were the three largest regions for domestic energy inflow, accounted for about 69% of the energy flows from domestic imports. These regions provide strong support for Shanghai economic development. After that, energy flows embodied in foreign goods and service exchanges are traced and quantified in international regions. NAFTA (7.33Mtce), RoW (6.51Mtce) and EU (4.26Mtce) were top three regions for foreign energy outflows. Consequently, about 67% of foreign exported energy flows taking place in Shanghai geographical limits were transferred from these three international consumers to Shanghai. The Row (9.37 Mtce), East Asia (4.91 Mtce) and BRIIAT (3.14 Mtce) were the top three regions for foreign energy inflows, accounted for about 82% of the energy flows from foreign imports. (ii) For water Fig. 4 shows the water flows embodied in domestic goods and service exchanges, are traced and quantified in domestic regions in China. The Central (570.98 Mt), North (504.65 Mt) and Northwestern China (365.96 Mt) were the three largest regions for domestic water outflows. This provides an indication, that transferring of water flows from these inland regions were undertaken by Shanghai, accounting for 58% of domestic exported water flows taking place inside Shanghai borders. The North

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(a) International (21.29) 17% Local (35.06) 38%

Domestic (69.19) 55%

(b)

Production-based

Domestic (29.61) 32%

International (7510.48) 17%

International (2563.23) 24%

Water (Mt)

Domestic (2500.87) 23%

Local (5633.43) 13%

Consumption-based

International (26.93) 30%

Energy (Mtce)

Local (35.06) 28%

Local (5633.43) 53% Domestic (31507.21) 70%

Fig. 2. Energy and water flows features of Shanghai in 2010 based on PBA and CBA.

(10245.00 Mt), Central (7232.94 Mt) and Northeast China (4722.72 Mt) were the three leading regions for domestic water inflow, accounted for about 70% of the water flows from domestic imports. After that, water flows embodied in foreign goods and service exchanges are traced and quantified in international regions. NAFTA (724.51 Mt), RoW (589.67 Mt) and EU (412.83 Mt) were the top three foreign water outflows. Consequently, around 67% of foreign exported water flows taking place in Shanghai geographical limits were transferred from these three international consumers to Shanghai. The RoW (3984.65 Mt), BRIIAT (2033.85 Mt) and NAFTA (1265.51 Mt) were the top three regions for foreign water inflows, accounted for about 97% of the water flows from foreign imports. The four municipalities in China are all embodied water recipients along supply chain, and embodied water transfers aggravated the regional water use imbalance and to some extent the water use efficiency of China as a whole (Li and Han, 2018). In consideration of the growing trading exchanges among cities and

regions, ignoring resource transfers embodied in trade will lead to failure in presenting actual water demands. 4.2. Inter-regional flow analysis Deepening the data analysis, Table A1, available in appendix, lists energy and water production and consumption related flows across all the 29 domestic regions in China (excluding Tibet and Taiwan). However, to make comparisons simple the trade flows statistics of only top 5 provinces are displayed graphically in Fig. 5 (a)-(b). This can provide greater insights into sources and pattern of Shanghai inter-regional virtual exports and imports flows of energy and water. Fig. 5(a) shows that Tianjin (2.66 Mtce), Henan (2.66 Mtce), Jiangsu (2.10 Mtce), Guangdong (1.97 Mtce) and Hebei (1.86Mtce) were the largest consuming provinces, importing 38% of domestic embodied energy flows from Shanghai. Apart from Henan and Hebei, other provinces are economically stable areas, import high

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Fig. 3. Shanghai production and consumption related energy flows in trade (width represent the amount of flows).

Fig. 4. Shanghai production and consumption related water flows in trade (width represent the amount of flows).

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value-added goods and services from Shanghai to meet their final demands and generated environmental pressures in Shanghai. While Shandong (6.82 Mtce), Hebei (6.10 Mtce), Hubei (6.09 Mtce), Henan (5.91 Mtce) and Jiangsu (5.78 Mtce) were the largest provinces exporting 45% of embodied energy flows to Shanghai. For this, the first reason can be their geographical location as comparatively to others, these are near to Shanghai city and second is the provinces economic structure. For instance, Shandong, Hebei and Jiangsu have great economic strength and industrial base. Shanghai transfers embodied energy pressure triggered by final demand to these neighboring provinces by importing products and raw materials. (ii) For water Fig. 5(b) shows that Henan (249.01 Mt), Guangdong (168.55 Mt), Jiangsu (167.61 Mt), Hebei (147.98 Mt) and Zhejiang (147.63 Mt) were the largest consuming provinces, importing 36% of domestic embodied water flows from Shanghai. While Hebei (5375.19 Mt), Shandong (4641.05 Mt), Anhui (2613.15 Mt), Heilongjiang (2526.65 Mt) and Henan (2153.21 Mt) were the largest provinces exporting 55% of embodied water flows to Shanghai. To meet its local consumer demand, Shanghai imported large amount of water embodied in goods and services transferring virtual water pressure to other domestic regions which can have negative environmental implications.

4.3. International flow analysis Table A2, available as appendix, lists energy and water production and consumption flows across the 39 international regions

(plus RoW region). However, to make comparisons simple, the trade flows statistics of only top 5 countries are displayed graphically in Fig. 6 (a)-(b) which can be helpful in understanding origin and pattern of Shanghai transnational inter-regional (i.e. outside of national boundaries) virtual imports and exports flows of energy and water. Fig. 6(a) shows that USA (6.13 Mtce), Japan (2.31 Mtce), Germany (1.40 Mtce), Korea (1.00 Mtce) and Australia (0.90 Mtce) were the largest consumers, importing 44% of international embodied energy flows from Shanghai. While Korea (2.27 Mtce), USA (1.56 Mtce), Russia (1.47 Mtce), Japan (1.40 Mtce) and Taiwan (1.23 Mtce) were the largest countries exporting 38% of embodied energy flows to Shanghai. Among the top five importing and exporting countries, the common trade economies were USA, Japan and Korea which indicates that a close relationship of energy flows is present between Shanghai and three mentioned countries. Also, Shanghai exported embodied energy flows to Germany and Australia, which provides indication that the two countries depend on goods and services from Shanghai to satisfy their domestic energy demand. (ii) For water Fig. 6(b) shows that USA (606.83 Mt), Japan (216.92 Mt), Germany (134.56 Mt), Korea (91.29 Mt) and India (84.64 Mt) were largest consumers, importing 44% of international embodied water flows from Shanghai. While USA (1053.93 Mt), Brazil (993.20 Mt), India (360.17 Mt), Russia (244.75 Mt) and IDN (224.25 Mt) were the largest countries exporting 38% of embodied water flows to Shanghai. Basically, Shanghai externalize environmental impacts by importing water intensive commodities produced in foreign countries.

Fig. 5. Top domestic regional flows of energy and water induced by exports and imports of Shanghai. (i) For energy

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Top Five Importers

Top Five Exporters

(a)

Australia Taiwan

0.9

Korea

1 1.4 2.31 6.13 8

6

4

2

1.23

Japan

1.4

Germany Russia

1.47

Japan

USA

1.56

USA

Korea

0

2.27 0

Energy (Mtce)

(b)

84.64

India

91.29

Korea

606.83 600

300

Indonesia

Germany

216.92

900

4

6

8

Energy (Mtce)

134.56

1200

2

Russia

244.75

India

Japan

Brasil

USA

USA

0

224.25

360.17 993.2 1053.93 0

Water (Mt)

300

600

900

1200

Water (Mt)

Fig. 6. Top international regional flows of energy and water induced by exports and imports of Shanghai. (i) For energy

4.4. Nexus strength and embodied trade flows This section presents the results for the urban resource nexus, based on the proposed nexus strength indicator for energy and water. To calculate the results, an average weighing scheme method is used (considering energy and water as equally important) for each of the resource. The nexus strength of Shanghai, domestic regions of China and world economic system is evaluated from production (associated with production activity) and consumption (caused by final demand) perspectives. The nexus strength relates to the energy and water use relative to Shanghai. Thus, a nexus is strong when the simultaneous use of at least two resources is significant with respect to the urban maximum resource use. Key regions with high nexus strength are analyzed. The nexus strength results for the top 10 provinces and countries induced by Shanghai interregional and international virtual import and export flows of energy and water are presented in Fig. 7. From the consumption perspective, Hebei and Shandong showed a high nexus strength, as combined usage of energy and water was large. Consequently, these provinces consumed a great amount of nexus resources within their territory to satisfy the consumers demand in Shanghai. The results show that Shanghai

mainly externalized virtual environmental pressures by importing energy and water intensive commodities produced in the neighboring provinces. In addition, the nexus strength results were different from the two perspectives revealing an uneven spatial distribution of nexus resources. From production perspective, Henan and Tianjin showed high nexus strength. A great resource use exhibits a strong nexus and a low efficiency, that threatens resource security. As trade may accelerate depletion of natural resources, it is essential that prevailing economic development and trade agreements must not ignore the sustainability considerations. (ii) For international countries From consumption perspective, USA showed high nexus strength followed by Brazil. Some countries, in particular from consumption perspective, were mostly dependent on single resource use. In the case of USA, about 60% energy and 40% water contributed to the energy-water nexus respectively. For Brazil, water was the most frequent resource node contributing about 88%, while for Korea energy was the most common resource node contributing about 98% towards the nexus. From the PB standpoint, USA showed high nexus strength followed by Japan. Among the top

A. Nawab et al. / Journal of Cleaner Production 223 (2019) 522e535

531

Fig. 7. Nexus Strength of top ten countries induced by exports and imports of Shanghai. (i) For domestic provinces

ten importing and exporting countries, the common top trading economy was USA, indicating the close relationship of nexus resource trade flows exist between Shanghai and US economy. 5. Discussion Globalization

has

increased

the

interconnectedness

and

consumption of energy and water resources. A main concern in quantifying resource efficiency of production and consumption activities exists in selecting appropriate accounting method. CBA, commonly based on macroeconomic models and Input-Output models, allows to account for direct and indirect energy and water flows from local production, domestic and foreign imports (Miller and Blair, 2009). Instead, PBA does not permit to understand

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A. Nawab et al. / Journal of Cleaner Production 223 (2019) 522e535

full scope of production process as the link between production and the goods and service consumption is missing. Because of this, PBA policies set in recent past were largely held responsible for environmental leakages, giving room to shifting of pollutant activities and resource exploitation from developed to developing countries (Aichele and Felbermayr, 2012). CBA can guide urban managers to broaden and extend their policy options regarding local use, as well as to clarify responsibilities with respect to resource consumption embedded into good and services traded among countries and industrial sectors. Even with these advantages, CBA are affected by some complications, such as the results quality, which primarily depends on availability, accuracy and wholeness of input output models (Boiter, 2012). In addition, the CBA allocation of responsibilities for pollution and resource exploitation generally takes along distributional concerns and political resistance, which needs to be defined at global level through international policy agreements and cooperation (Chen et al., 2017). The application and quantification of energy-water nexus is significant to improve our understanding of resource management across scales. As this study reveals, drivers of energy and water consumption can originate from beyond urban and national boundaries. Shanghai, one of the most important cities in China, is experiencing global energy and water transfer accompanied by commodities and services trade all over the supply chain. The ratio of tertiary industry growth in Shanghai will increase a lot more, being a consumer dominated international city. The present study showed that Shanghai eternalizes the environmental impacts by commodity imports from other regions, policy is helpful in this context to improve local energy and water resources savings. In particular, the urban government would need to look beyond its own geographical control. The study results suggest that realization of energy and water resource saving responsibilities for urban areas can be increased from a consumption perspective. Promoting international cooperation and regional trade policies adjustment should be the key measures to deal with such issues in the future. Comparing current findings with previous studies; Zhang et al. (2018) examined water availability for energy generation from a consumption perspective and used an IO framework to evaluate the water footprint of energy supply (WFES) of Shanghai. Results showed that in 2007 Shanghai WFES was 1.28 billion m3 and the external WFES accounts for 78.6% of the Shanghai total WFES, suggesting that WFES of Shanghai relied mainly on energy goods from domestic provinces and foreign countries than local sources. In particular, 91.2% of the external WFES for energy goods came from other Chinese provinces. The current study shows that Shanghai largely imported flows of energy and water from inland provinces and foreign regions around the globe. In particular, the seven domestic regions of China were net exporters corresponding to Shanghai, supporting around 55.10% of the net energy inflows and 70.56% of net water inflows driven by Shanghai final demand. The results of previous studies agree with current results. In particular; results of both studies indicate that cooperation and adjusting regional trade relationship can promote sustainable utilization of resources. The current study still has some limitations with respect to method and data. The EE-MSIO model is for the year 2010, so the age of the data is an important shortcoming. However, MRIOTChina 2010 is latest accessible dataset. Numerous methods were developed, incorporating multiple scales (for example; global, national and regional), to capture the regional heterogeneity within world economy (Bachmann et al., 2014; Wenz et al., 2014). However, data inaccuracy is the current key shortcoming, because of the disaggregation approximations of trade flows from one area in one country to another area in another country. In the MSIO model, the

major limitation arises from calculation of trade relationships among subnational regions of China and global regions. Recently available trade data are especially missing. Further, in literature the IOA limitations are well documented (Wiedmann, 2009). For instance; data uncertainty due to sectoral aggregation error. In this research, to obtain a greater data consistency, sectors were aggregated into 20, which might decrease results accuracy. As regards to nexus strength, our specific formulation is mainly concentrated on the absolute use of resources. Therefore, it ignores other aspects related to nexus debate, for example resource availability and price. Moreover, the resource use alone does not surely align completely with the significance of a given nexus issue. 6. Conclusions In this paper an urban energy-water nexus framework is constructed in domestic and international trade, based on EE-MSIO model, which is used to trace spatial distribution for origin and destination of Shanghai energy and water flows in multi-scales economy for the year 2010. Energy-water nexus was investigated through an integrated nexus strength indicator to detect the synergetic effects of energy and water use and interactions in economic system. The study results show that consumption-based energy flow is about 1.37 times the production-based flow, while consumption-based water flow is 4.17 times the production-based flow. Shanghai mainly imported flows of energy and water from domestic provinces of China and foreign developing regions whereas export little to developed countries. In parallel, Shanghai externalized environmental pressures by importing energy and water intensive commodities produced elsewhere. The concept that energy and water flows in goods and services has the ability to challenge environmental policies is supported by numerous research investigations. In this regard, our results show that it is possible to evaluate the environmental burdens of production and consumption, differentiating between exports and imports with EE-MSIO model. Compared to production-based approach, this study shows that consumption-based approach is more appropriate to assess the incidence of trade on environmental exploitation; as the energy and water use associated with Shanghai imports was greater than exports. The analysis revealed an uneven spatial distribution of resource flows destinations from both production and consumption perspectives. The quantification of energy-water nexus is essential to improve the understanding of resource management across scales. In fact, this paper confirms that drivers of resource consumption can originate from beyond urban, national and ecosystem boundaries. The nexus strength indicator established that strong nexus, caused by intensive use of energy and water, results in low efficiency, which threatens resource security. This research work sought to show the existing energy-water nexus and trade policy priorities of Shanghai to inform decisions, to manage ecological assets more wisely and get sustainable solutions. The current investigation did not extend to sectoral level. Thus, it should be considered as preliminary. Further research at higher resolution (i.e. sectoral analysis) is necessary to adjust the energy and water consumption structure of city. In this sense, the outcomes of this research will be used to divide the IO tables at the sectoral level, to further analyze the internal dynamics and configurations for industry specific measures to improve resource efficiency. Acknowledgements This work is supported by the Projects of International Cooperation of National Natural Science Foundation (No. 51661125010),

A. Nawab et al. / Journal of Cleaner Production 223 (2019) 522e535

Projects of Sino-Italian Cooperation of China Natural Science Foundation (No. 7171101135) and the Italian Ministry of Foreign Affairs and International Cooperation (MAECI, High Relevance Bilateral Projects), National Natural Science Foundation of China (No. 71673029, 71804023), Projects of China Postdoctoral Science Foundation (2017M622701) and the 111 Project (No. B17005).

533

Appendix A Table A1 and Table A2 are reported here.

Table A1 Embodied energy and water trade of Shanghai with domestic region S. No

Regions

Energy (unit: Mtce)

Water (unit: Mt)

Production based (Outflows)

Consumption based (Inflows)

Production based (Outflows)

Consumption based (Inflows)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 210 22 23 24 25 26 27 28 29 30

Beijing Tianjin Hebei Shanxi Inner Mongolia Liaoning Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan Hubei Hunan Guangdong Guangxi Hainan Chongqing Sichuan Guizhou Yunnan Shannxi Gansu Qinghai Ningxia Xinjiang

1.29 2.66 1.86 1.17 1.79 0.67 0.68 0.94 (0.00) 2.10 1.38 0.94 1.24 0.48 1.07 2.66 0.43 0.57 1.97 0.81 0.11 0.48 0.52 0.36 1.14 1.04 0.15 0.42 0.18 0.50

0.85 1.29 6.10 2.84 4.01 1.77 1.14 1.31 (0.00) 5.78 5.67 3.66 1.08 1.30 6.82 5.91 6.09 1.36 2.29 0.87 0.12 0.53 1.15 1.23 0.89 2.12 1.07 0.25 0.53 1.13

100.93 134.28 147.98 122.80 143.98 57.01 57.26 75.92 (0.00) 167.61 147.63 83.12 80.49 35.30 121.46 249.01 32.22 48.52 168.55 70.84 11.84 47.22 48.69 32.85 93.37 132.07 18.68 19.90 14.06 37.28

102.95 125.80 5375.19 208.12 1368.97 660.43 1535.65 2526.65 (0.00) 1421.83 456.20 2613.15 187.69 770.57 4641.05 2153.21 813.98 673.90 377.55 633.69 41.89 116.67 793.52 329.41 585.70 255.70 277.89 11.12 399.21 2049.52

Table A2 Embodied energy and water trade of Shanghai with international region S. No

Regions

Energy (unit: Mtce)

Water (unit: Mt)

Production based (Outflows)

Consumption based (Inflows)

Production based (Outflows)

Consumption based (Inflows)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 210 22 23 24

Australia Austria Belgium Bulgaria Brazil Canada Cyrus Czech Republic Germany Denmark Spain Estonia Finland France United Kingdom Greece Hungary Indonesia India Ireland Italy Japan S-Korea Lithuania

0.90 0.14 0.19 0.02 0.46 0.79 0.01 0.10 1.40 0.10 0.37 0.01 0.08 0.74 0.82 0.09 0.05 0.46 0.89 0.12 0.63 2.31 1.00 0.01

0.42 0.04 0.11 0.02 0.28 0.31 0.00 0.04 0.52 0.04 0.09 0.01 0.06 0.19 0.17 0.03 0.02 0.42 0.50 0.01 0.15 1.40 2.27 0.01

80.02 13.13 17.63 1.48 43.86 77.09 0.76 9.76 134.56 8.32 37.09 0.66 8.77 70.46 84.57 9.00 4.81 42.01 84.64 13.31 61.04 216.92 91.29 0.87

202.12 7.64 1.73 3.52 993.20 199.09 0.02 3.79 19.25 9.84 12.34 1.45 10.89 31.87 4.80 0.59 5.26 224.25 360.17 1.78 12.88 26.48 15.92 2.21 (continued on next page)

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A. Nawab et al. / Journal of Cleaner Production 223 (2019) 522e535

Table A2 (continued ) S. No

25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

Regions

Luxembourg Latvia Mexico Malta Netherland Poland Portugal Romania Russia Slovakia Slovenia Sweden Turkey Taiwan USA Rest of the world

Energy (unit: Mtce)

Water (unit: Mt)

Production based (Outflows)

Consumption based (Inflows)

Production based (Outflows)

Consumption based (Inflows)

0.01 0.01 0.41 0.00 0.35 0.20 0.05 0.05 0.71 0.04 0.02 0.14 0.34 0.26 6.13 6.51

0.02 0.00 0.09 0.00 0.21 0.07 0.01 0.02 1.47 0.02 0.00 0.07 0.06 1.23 1.56 9.37

0.98 0.48 40.59 0.34 34.98 19.47 4.46 4.38 73.25 3.99 1.66 12.15 32.46 25.47 606.83 589.67

0.09 1.50 12.49 0.00 2.19 6.37 1.75 5.72 244.75 1.88 0.61 12.02 9.37 22.09 1053.93 3984.65

References Aichele, R., Felbermayr, G., 2012. Kyoto and the carbon footprint of nations. J. Environ. Econ. Manag. 63, 336e354. Arto, I., Andreoni, V., Rueda- Cantuche, J.M., 2016. Global use of water resources: a multiregional analysis of water use, water footprint and water trade balance. Water Resour. Econ. 15, 1e14. Bachmann, C., Roorda, M.J., Kennedy, C., 2014. Developing a multi-scale multi-region inpute output model. Econ. Syst. Res. 27, 172e193. Bachmann, C., Roorda, M.J., Kennedy, C., 2015. Developing a multi-scale multi region input output model. Econ. Syst. Res. 27, 172e193. Boiter, B., 2012. CO2 emissions production based accounting vs consumption: insights from the WIOD databases. In: Final WIOD Conference: Causes and Consequences of Globalization. 2012, pp. 1e23. Brizga, J., Feng, K., Hubacek, K., 2017. Household carbon footprints in the Baltic States: a global multi-regional input-output analysis from 1995 to 2011. Appl. Energy 189, 780e788. Chen, B., Chen, S., 2015. Urban metabolism and nexus. Ecol. Inf. 26, 1e2. Chen, G.Q., Wu, X.F., 2017. Energy Overview of globalized world economy: source, supply chain and sink. Renew. Sustain. Energy Rev. 69, 735e749. Chen, J., Cheng, S., Song, M., 2017. Decomposing inequality in energy-related CO2 emissions by source and source increment: the roles of production and residential consumption. Energy Policy 107, 698e710. Chen, P.-C., Alvarado, V., Hsu, S.-C., 2018. Water energy nexus in city and hinterlands: multi-regional physical input output analysis for Hong Kong and South China. Appl. Energy 225, 986e997. Chen, S., Chen, B., 2016. Urban energy water nexus: a network perspective. Appl. Energy 184, 905e914. De Laurentiis, V., Hunt, D.V.L., Rogers, C.D.F., 2016. Overcoming food security challenges within an energy/water/food nexus (EWFN) approach. Sustainability 8 (1), 95. Dietzenbacher, E., Los, B., Stehrer, R., Timmer, M., de Vries, G., 2013. The construction of world input-output tables in the WIOD project. Econ. Syst. Res. 25, 71e98. Dubreuil, A., Assoumou, E., Bouckaert, S., Selosse, S., Maizi, N., 2013. Water modeling in an energy optimization framework. The water scarce middle east context. Appl. Energy 101, 268e279. Fang, D., Chen, B., 2017. Linkage analysis for the water energy nexus of city. Appl. Energy 189, 770e779. Feng, K., Hubacek, K., Sun, L., Liu, Z., 2014. Consumption-based CO2 accounting of China’s megacities: the case of Beijing, Tianjin, Shanghai and Chongqing. Ecol. Indicat. 47, 26e31. Guo, R., Zhu, X., Chen, B., Yue, Y., 2016. Ecological network analysis of the virtual water network within China’s electric power system during 2007-2012. Appl. Energy 168, 110e121. Hoekstra, A.Y., Chapagain, A.K., Aldaya, M.M., Mekonnen, M.M., 2011. The Water Footprint Assessment Manual: Setting the Global Standard Earthscan. London (UK). IEA (International Energy Agency), 2016. World Energy Outlook 2016. IEA/OECD, Paris. Kahrl, F., Roland-Holst, D., 2008. China’s water-energy nexus. Water Pol. 10 (S1), 51e65. Li, Y., Han, M., 2018. Embodied water demands, transfers and imbalance of China’s mega cities. J. Clean. Prod. 172, 1336e1345. Liang, S., Qu, S., Zhu, Z., Guan, D., Xu, M., 2017. Income-based greenhouse gas emissions of nations. Environ. Sci. Technol. 51, 346e355. Lin, J., Hu, Y., Zhao, X., Shi, L., Kang, J., 2017. Developing a city centric global multi-

regional input output model (CCG-MRIO) to evaluate urban carbon footprints. Energy Policy 108, 460e466. Liu, W.D., Tang, Z.P., Chen, J., Yang, B., 2014. China’s Interregional Input-Output Tables between 30 Provinces 2010. China Statistics Press, Beijing. Meng, F.X., Liu, G.Y., Hu, Y.C., Su, M.R., Yang, Z.F., 2018. Urban carbon flow and structure analysis in a multi-scales economy. Energy Policy 121, 553e564. Meng, F.X., Liu, G.Y., Chang, Y., Su, M.R., Hu, Y.C., Yang, Z.F., 2019. Quantification of urban water-carbon nexus using disaggregated input-output model: a case study in Beijing (China). Energy. https://doi.org/10.1016/j.energy.2019.01.013. Mi, Z., Meng, J., Guan, D., Shan, Y., Song, M., Wei, Y.M., Liu, Z., Klaus, H., 2017. Chinese CO2 emission flows have reversed since the global financial crisis. Nat. Commun. 8 (1), 1712. Miller, R.E., Blair, P.D., 2009. Input Output Analysis; Foundations and Extensions. Cambridge University Press, Cambridge (UK). NBSC (National Bureau of Statistics of China), 2011. China Statistical Yearbook 2011. China Statistics Press, Beijing. NBSC (National Bureau of Statistics) and MEP (Ministry of Environmental Protection), 2011. China Statistical Yearbook on Environment 2011. China Statistics Press, Beijing. Oita, A., Malik, A., Kanemoto, K., Geschke, A., Nishijima, S., Lenzen, M., 2016. Substantial nitrogen pollution embedded in international trade. Nat. Geosci. 9, 111e115. Okadera, T., Chontanawat, J., Gheewala, S.H., 2014. Water footprint for energy production and supply in Thailand. Energy 77, 49e56. Peters, G.P., 2008. From production-based to consumption-based national emission inventories. Ecol. Econ. 65, 13e23. Peters, G.P., Andrew, R., Lennox, J.A., 2011. Constructing an environment-extended multi-regional input-output table using the GTAP data. Econ. Syst. Res. 23, 131e152. Rambo, K.A., Warsinger, D.M., Shanbhogue, S.J., Lienhard, J.H.V., Ghoniem, A.F., 2017. Water energy nexus in Saudi Arabia. Energy Procedia 105, 3837e3843. Rees, W.E., 1992. Ecological footprints and appropriated carrying capacity: what urban economics leaves out. Environ. Urbanization 4, 121e130. Ringler, C., Bhaduri, A., Lawford, R., 2013. The nexus across water, energy, land and food (WELF): potential for improved resource use efficiency? Curr. Opin. Environ. Sustain. 5, 617e624. Saladini, F., Betti, G., Ferregina, E., Bouraoui, F., Cupertino, S., Canitano, G., Gigliotti, M., Autino, A., Pulselli, F.M., Riccaboni, A., Bidoglio, G., Bastianoni, S., 2018. Linking the water energy food nexus and sustainable development indicators for the Mediterranean region. Ecol. Indicat. 91, 689e697. Santana, M.V.E., Zhang, Q., Mihelcic, J.R., 2014. Influence of water quality on the embodied energy of drinking water treatment. Environ. Sci. Technol. 48, 3084e3091. SMSB (Shanghai Municipal Statistics Bureau), 2011. Shanghai Statistical Yearbook 2011. China Statistics Press, Beijing. Tian, X., Sarkis, J., Geng, Y., Qian, Y., Gao, C., Bleischwitz, R., Xu, Y., 2018. Evolution of China’s water footprint and virtual water trade: a global trade assessment. Environ. Int. 121, 178e188. Timmer, M.P., Dietzenbacher, E., Los, B., Stehrer, R., de Vries, G.J., 2015. An illustrated user guide to the world input output database: the case of global automotive production. Rev. Int. Econ. 23, 575e605. Voinov, A., Cardwell, H., 2009. The energy-water nexus: why should we care? J. Contemp. Water Res. Educ. 143, 17e29. Wang, S., Chen, B., 2016. 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. Appl. Energy 178, 773e783. Wenz, L., Willner, S.N., Radebach, A., Bierkandt, R., Steckel, J.C., Levermann, A., 2014. Regional and sectoral disaggregation of multi-regional inputeoutput tables e a

A. Nawab et al. / Journal of Cleaner Production 223 (2019) 522e535 flexible algorithm. Econ. Syst. Res. 27, 194e212. Wiedmann, T., 2009. A review of recent multi region input output models used for consumption based emission and resource accounting. Ecol. Econ. 69, 211e222. Yang, J., Chen, B., 2016. Energy water nexus of wind power generation systems. Appl. Energy 169, 1e13. Yang, S., Cao, D., Lo, K., 2018a. Analyzing and optimizing the impact of economic restructuring on Shanghai’s carbon emissions using STIRPAT and NSGA-II. Sustain. Cities Soc. 40, 44e53. Yang, X., Wang, Y., Sun, M., Wang, R., Zheng, P., 2018b. Exploring the environmental pressures in urban sectors: an energy water carbon nexus perspective. Appl. Energy 228, 2298e2307. Zhang, F., Zhan, J., Li, Z., Jia, S., Chen, S., 2018. Impacts of urban transformation on

535

water footprint and sustainable energy in Shanghai, China. J. Clean. Prod. 190, 847e853. Zhang, Y., Zheng, H., Yang, Z., Li, Y., Liu, G., Su, M., Yin, X., 2016. Urban energy flow processes in the Beijing- Tianjin-Hebei (Jing-Jin-Ji) urban agglomeration: combining multi-regional input output tables with ecological network analysis. J. Clean. Prod. 114, 243e256. Zhu, X., Guo, R., Chen, B., Zhang, J., Hayat, T., Alsaedi, A., 2015. Embodiment of virtual water of power generation in the electric power system in China. Appl. Energy 151, 345e354. Zimmerman, R., Zhu, Q., Dimitri, C., 2016. Promoting resilience for food, energy and water interdependencies. J. Environ. Soc. Sci. 6, 50e61.