Highlights W-E-F nexus in water and energy footprint for China tourism were investigated. The food supply group contributed largest indirect tourism water footprint. The tourism direct sectors produced largest direct tourism energy footprint. The tourism expenditure is the top driver for water and energy increments. Intensity and economic structure effects can offset water and energy increments.

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The mismatch between trade-embodied economic benefits and CO 2 emissions causes carbon inequality, which is seldom analyzed from the intracountry level, especially across a long-term period. This study applied an environmentally extended multiregional input−output model to trace this mismatch and measure the carbon inequality quantitatively within China during 2007−2017. The results show that during the past decade, China's national carbon inequality was continuously worsening with carbon Gini coefficients rising regardless of production-(0.21− 0.30) or consumption-based (0.12−0.18) accounting. The regional carbon inequality was deteriorating, where less developed provinces with 20% of total value-added emitted 32.9% of total CO 2 emissions in 2007, while this figure rose to 42.6% in 2017. The eastern provinces (Jiangsu and Shanghai) had entered into net economic and carbon beneficiaries keeping high trade advantages, by contrast the northwest provinces (Ningxia and Xinjiang) were trapped in a lose−lose situation with trade benefits declining by 68%. The southwest provinces (Yunnan and Guangxi) shifted from being net carbon and value-added exporters to net importers, stepping into the earlier development mode of eastern provinces. This hidden and exacerbated carbon inequality calls for regional-specific measures to avoid the dilemma of economic development and CO 2 mitigation, which also gives a good reminder for the rising economies, like India.

Leontief’s input–output model (IOM) is a widely applied method for tracing energy or emissions embodied in economic activities. The economic IOM used in environmental science has aroused broad concerns from both economists and environmentalists. The aim of this study is to review the hotspots of application of IOM in the energy and environmental science fields based on a bibliometric method by using co-words network analysis. All 4938 publications in this study were retrieved from Science Citation Index, Social Science Citation Index, Conference Proceedings Citation Index – Science, and Conference Proceedings Citation Index – Social Science & Humanities. The keywords and frequently cited articles were studied to reveal the evolution of hot spots related to IOM applications in the field of energy and environment from 1998 to 2016. The features of the co-words network analysis of keywords were analyzed by four network indicators including modularity, number of clusters, closeness coefficient, and average path length. The results showed that “energy”, “CO2 emissions”, “GHG”, “LCA”, “industrial ecology”, “carbon footprint”, “China”, and “international trade” were the major application fields of IOM. In different stages the boundary of hot spots became overlapped and the whole network tightness became stronger. According to the analysis of frequently cited articles, we found those articles on CO2 or GHG emissions embodied in trade had been the most frequently cited articles since 2007 with negotiations on climate change. Based on our findings, using IOM to analyze important environmental problems is the key point to popularize IOM applications. Future research opportunities exist to apply IOM to wider environment issues, such as combined emissions and resources.

Previous studies investigated greenhouse gas (GHG) emissions embodied in the trade of large groups of products by using the input-output model. However, very little attention was paid from the product's perspective via the bottom-up process-based life cycle assessment (LCA) model. In this paper via the process-based LCA approach, GHG emissions embodied in the computer trade between China and its major trade partners were examined over the period 2002 to 2013. Results revealed that China has been the largest net exporter of GHG emissions related to computers over the last decade, where portable computer products made up the main share. In 2002, the largest trade flow of GHG emissions embodied in computers was from Taiwan to the USA, while in 2013 it was from China to the USA. Moreover, technological innovation and geographical variability were taken into consideration as emission factors of computers, as well as the uncertainty analysis. This study found that the main driver of computer-related emissions embodied in international trade is industry transfer. The actual production of computers has shifted steadily away from the USA, firstly to Taiwan and ASEAN, but now almost entirely to China. Results of this study suggest that reduction of carbon emission is destined to be a global responsibility.