Temporal change in India’s imbalance of carbon emissions embodied in international trade

Abstract

In India, rapid industrialization and reorganization of the global supply chain are driving economic growth, accompanied by increasing exports and carbon emissions. India is poised to succeed China as the next world manufactory, which will lead to huge emissions in the country. To formulate appropriate emission mitigation measures, it is necessary to further understand the temporal change in India's emissions at the sectoral level from both the production and consumption perspectives. However, existing studies that have estimated emissions in India have paid less attention to the link among original emitters, final producers and final consumers and to its temporal change. Based on an emission inventory compiled in this study, we trace emission flows from original emitters to final producers and then to final consumers through the international supply chain by using an environmentally extended multi-regional input-output model. This study finds that both production-based and consumption-based emissions in India increased constantly from 2000 to 2014, and production-based emissions had higher growth rates due to the increased coal share. The major receivers of India's exported emissions were developed countries (e.g., the European Union and the United States), while the main sources of India's imported emissions were developing countries (e.g., China and Russia). From 2011 to 2014, India's net exported emissions increased by 29.2% because of the decrease of imported emissions. Moreover, intermediate products (63% and 73.7%) were the major contributors to exported and imported emissions, most of which were embodied in manufacturing products (48.8% and 65.7%, respectively). Therefore, international cooperation to optimize the energy and trade structure and to improve energy efficiency can be effective in mitigating carbon emissions in India.

Kazakhstan's CO2 emissions in the post-Kyoto Protocol era: Production- and consumption-based analysis

“…Consumption-based emissions in Kazakhstan include demand-driven emissions in 57 socioeconomic sectors embodied in local commodities that are consumed locally and emissions embodied in international imports that are produced in other countries. Environmentally Extended Input-output Analysis (EEIO) is widely used in trailing economic drivers of regional and global CO 2 emissions accounting (Wang et al, 2018;Mi et al, 2016;Meng et al, 2018). EEIO is generated based on the classic IO model and is built upon intersectional flows in intermediate demand and final demand.…”

“…Owen et al (2017) compared energy-extracted and energy-used vectors in the consumption-based calculation and encouraged MRIO model databases for both of them. Due to the disadvantaged status of developing countries in international emission reduction from the production perspective (Wang et al, 2018), many scholars tried to construct a fairer shared emission responsibility system. Numerous studies estimated the CO 2 emissions embedded in domestic and international trade at both national and local levels (Wang et al, 2018;Mi et al, 2016;Meng et al, 2018).…”

“…Due to the disadvantaged status of developing countries in international emission reduction from the production perspective (Wang et al, 2018), many scholars tried to construct a fairer shared emission responsibility system. Numerous studies estimated the CO 2 emissions embedded in domestic and international trade at both national and local levels (Wang et al, 2018;Mi et al, 2016;Meng et al, 2018). Other related studies also demonstrated the advantages of consumption-based accounting and provide a better understanding of different driving forces for carbon or other pollution emissions (Chen and Zhang, 2010;Guan et al, 2014;Meng et al, 2016Meng et al, , 2017Zhao et al, 2015;Akbota and Baek, 2018).…”

Dynamic Driving Forces of India's Emissions From Production and Consumption Perspectives

“…Based on the multiregional input‐output table with m countries and n sectors, the emissions transferred from country q to country p ( p , q = 1, 2 … m ) can be calculated as follows: where D p represents the matrix of direct emission intensity of country p , L represents the Leontief inverse matrix, and Y q represents the matrix of final demand in country q . For more detailed information, please see our previous studies (Meng et al, 2016; Wang et al, 2018). Therefore, theoretically change of E in Equation 1 can be expressed as follows: …”

An Input-Output Model for Analyzing Carbon Emissions in the Urban Agglomeration of the Three Northeastern Provinces in China

“…primary energy (coal burning). Moreover, according to Global Carbon Project publications, China is the largest carbon emitter with 10 billion tons of carbon emissions [4], while the TNP, as one of the largest carbon emitters within China, has reached 900 million tons [3]. Reducing carbon emissions within the TNP is therefore critical for the reduction of China's emissions and improvement of the global environment.…”