The impact of urbanization and consumption patterns on China's black carbon emissions based on input-output analysis and structural decomposition analysis

Assessment of black carbon exposure level and health economic loss in China

Based on the geographic information system (GIS) software and the application of the black carbon (BC) and fine particulate matter ([Formula: see text]) ratio method, this paper analyzed and calculated the national BC distribution from 2015 to 2017 and evaluated the national human exposure to BC. The results showed that from 2015 to 2017, 2/3 of the national land area and nearly half of the population were exposed to 1-3 [Formula: see text], and the area and population exposed to a concentration less than 2 [Formula: see text] increased yearly, while the area and population exposed to a concentration higher than 9 [Formula: see text] decreased yearly. The estimated economic loss showed that 77.3% of the targeted districts or counties claimed a loss per square kilometer of 50 million Chinese Yuan (CNY) or less from the perspective of annual changes, and districts and counties in Beijing-Tianjin-Hebei and Hunan with annual losses between 50 and 500 million CNY showed an increasing trend. The BC ratio (the proportion of BC economic loss to GDP) of Beijing-Tianjin-Hebei and Hunan also showed an increasing trend yearly.

An input-output structural decomposition analysis of changes in China's renewable energy consumption

Governments actively encourage renewable energy use to deal with climate change and achieve carbon emission reduction targets. It is crucial to find out the driving factors that affect the utilization of renewable energy. Therefore, based on China's 2010-2016 input-output table, this paper uses the input-output model and structural decomposition analysis (SDA) to analyze the driving factors of renewable energy changes in the production end, household end, and the aggregate economy. The results show that the changes in the consumption structure (F) is the most crucial factor for renewable energy use, followed by technology progress (T) and final demand per capita (V). Sector SEHW (supply of electric power, heat power, and water) and MCRP (manufacture of coke and refined petroleum products) are the two vital sectors to achieve China's energy transition of the production level. However, as for households, the proportion of renewable energy has been declining. Hence, the government should promote renewable energy use and achieve the green transition in production and household levels.

A Calculation and Decomposition Method Embedding Sectoral Energy Structure for Embodied Carbon: A Case Study of China’s 28 Sectors

The measurement and allocation of carbon emission responsibilities is a fundamental issue in China’s low-carbon development. However, existing studies of embodied carbon do not sufficiently consider the sectoral energy structure. In this work, we developed a high-resolution calculation method for embodied carbon that embeds the sectoral energy structure into traditional input–output methods, thus expanding the driving factors of SDA decomposition. Based on this method, we calculated the quantity, final consumption structure, and energy structure of embodied carbon in China’s 28 sectors from 2002 to 2018, drew a carbon emissions allocation Sankey diagram of China in 2018, and calculated the SDA decomposition results for 2002–2010 and 2010–2018. The results indicate that fixed capital formation was still the top contributor of embodied carbon, and it caused more coal consumption. “Construction for fixed capital formation” and “other services for domestic consumption” were the two most important drivers of carbon emissions. The final consumption quantity and energy intensity were the main factors that promoted and inhibited the growth of embodied carbon, respectively, while the effects of the input–output structure, sectoral energy structure, and carbon emission coefficient on reducing carbon emissions were obvious after 2010. This also revealed that policymakers should formulate differentiated emission reduction strategies according to the carbon emission characteristics of key sectors.