Search

China’s “carbon peaking and carbon neutrality” goal relies greatly on the low-carbon transition of the power system, but the existing research rarely explores the low-carbon transition of the regional power system. By using the intergovernmental panel on climate change (IPCC) greenhouse gas inventory compilation method and the network model analysis, the carbon emissions caused by the power generation and the power consumption in Guangdong-Hong Kong-Macao Greater Bay Area (the Greater Bay Area) was quantified. The logarithmic mean Divisia index (LMDI) method was used to quantify the influence of socio-economic factors on the electricity-related carbon emissions in the Greater Bay Area. The results show that Hong Kong and Macao have made slow progress in the low-carbon transition of the power system, and Guangdong’s share of the low-carbon power continues to increase. The rapidly expanding economic scale and the power demand were the most important drivers of the emissions growth in the Greater Bay Area. The low-carbon electricity imported from outside regions and the improved efficiency in the sectoral electricity consumption offset part of the emission growth.

To mirror an important aspect of ultra-high voltage network development, the remarkable amount of energy cost and carbon emissions of a typical ultra-high voltage transformer substation in China is revealed, in light of the hybrid method as the integration of input-output analysis and process analysis. By inclusively inventorying all the input items as products of the economy, the study differs from previous studies that simply treat the input items as some primary materials. The results show that the total energy cost and carbon emissions of 1000 kV transformer substation are 6.82E+09 MJ and 7.12E+05 t CO 2 eq., respectively. Equipment purchasing contributes more than 80% to the overall energy cost and carbon emissions, followed by construction engineering, additional service and installation engineering. From the sectoral perspective, Manufacture of equipment for power transmission and distribution and control sector (Sector 78) dominates the energy cost and carbon emissions induced by 1000 kV transformer substation, followed by Construction industry (Sector 95). The comparison and analysis between current research and previous studies in different countries and different voltages is clearly discussed. This study not only enhances our understanding about the impact of ultra-high voltage network on energy and environment, but also provides insights for energy conservation and low carbon development. [ABSTRACT FROM AUTHOR]

Rapid urbanization drives the expansion of urban power girds, which involves enormous energy intensive products such as steel and concrete and inevitably results in a great quantity of carbon emissions. However, little has been done to investigate urban power girds' impact on carbon emissions. To solve this problem, this study makes efforts to calculate the carbon emissions of urban power grid in Jing-Jin-Ji region, one of the most populous and economically dynamic regions in China, in light of the hybrid method. Moreover, the depreciation life of urban power grids is taken into consideration for the first time, which avoids the underestimation of the accumulated carbon emissions of urban power grid due to depreciation. The results show that the accumulated carbon emissions of urban power grid in Jing-Jin-Ji region are 2.71E+06 t CO 2 eq. in 1993. When it comes to 2014, this figure increases by over 7.2 times. The majority of the carbon emissions by typical urban substations and transmission line projects are contributed by electrical equipment, steel and construction industries. 4 scenarios are set to predict the future carbon emissions by power grids in Jing-Jin-Ji region. The highest accumulated carbon emissions in 2020 are projected to be 7.63E+07 t CO 2 eq. under the condition shortest depreciation life (SDL) in the First Year Finished (FYF) scenario. Regression analysis is also carried out to show some influential factors such GDP's influence on power grids' carbon emissions, suggesting that the correlation between carbon emissions and regional economic development becomes more significant after Power System Reform Plan in 2002. This study not only draws a holistic picture of power grid but also bears significance to policies and actions in urban regions. [ABSTRACT FROM AUTHOR]

Quantifying the economic benefits and environmental costs brought about by trade can help reveal the environmental inequalities behind regional trade. There have been many studies on the accounting of greenhouse gas emissions and pollutants embodied in regional trade, but there are insufficient studies analyzing the imbalance between the economic benefits and environmental costs embodied in trade. Electricity-related carbon emissions are the main contributor to global warming, explaining more than 40% of carbon emissions both globally and in China. This study uses the network approach and multiregional input-output (MRIO) model to quantify the electricity-related carbon emissions and value added embodied in China's interprovincial trade from 2007 to 2012 and also applies the regional environmental inequality (REI) index to measure the imbalance of electricity-related carbon emissions and economic benefits embodied in such trade. The results show that 20–80% of the electricity-related carbon emissions and 15–70% of the value added of a province's final demand are outsourced to other provinces. The major directions of the net value added and electricity-related carbon emissions embodied in China's interprovincial trade were from north to south and from the center to the east. Unequal bilateral interprovincial trade mainly occurred between inland provinces and developed provinces, and western provinces (such as Guizhou, Gansu, and Ningxia) suffered economic and environmental losses from interprovincial trade. This study can promote understanding of the distribution impacts of domestic trade on environmental costs and economic benefits and provide a reference for China's cross-provincial carbon emission mitigation policies. • The electricity-related carbon emissions in China's domestic trade were quantified. • The value added embodied in China's domestic trade was quantified. • The spatial characteristics of the emissions and value added flows were analyzed. • The regional environmental inequality (REI) index of trade was calculated. • Guizhou, Gansu, etc. suffered economic and environmental losses from trade. [ABSTRACT FROM AUTHOR]

Digital technology is an effective way to realize the carbon neutrality target in China. Therefore, based on panel data at the city level in China from 2006 to 2016, we take the e-commerce pilot policy as a quasi-natural experiment, using the staggered difference-in-differences (DID) method to explore the effect of digital technology development on carbon emissions and its transmission mechanism. The conclusion of this paper shows that (ⅰ) the e-commerce pilot policy has significantly reduced carbon emissions. After a series of robustness tests, this empirical conclusion is still valid. (ⅱ) The inhibitory effect of different waves of e-commerce pilot cities on carbon emissions sequentially decreases. The e-commerce pilot policy has a greater effect on reducing carbon emissions in non-old industrial based cities and non-resource-based cities. (ⅲ) Implementing the e-commerce pilot city policy mainly reduces urban carbon emissions by optimizing resource allocation, reducing energy consumption and upgrading the industrial structure. (ⅳ) In addition, implementing the e-commerce pilot city policy has a significant positive carbon-reducing linkage effect with the carbon trading pilot policy and the low-carbon city pilot policy. The findings of this paper provide empirical evidence for carbon emission reduction, which has implications for upgrading urban construction patterns and promoting green urban development. • The construction of national e-commerce pilot cities has significantly reduced the carbon emission of cities. • The inhibitory effect of different batches of e-commerce pilot cities on carbon emissions sequentially decreases. • Playing more significant effect in non-old industrial based cities and non-resource-based cities. • Reducing urban carbon emissions by optimizing resource allocation and reducing energy consumption. • Having a significant positive carbon-reducing linkage effect with carbon emissions mitigation policies. [ABSTRACT FROM AUTHOR]

• Beijing's multiperspective electricity-related carbon emissions are accounted for. • Beijing had a large amount of net inflow of electricity-related carbon emissions. • Hebei and Inner Mongolia contributed most of Beijing's emission net inflow. • The driving forces of Beijing's electricity-related carbon emissions are analyzed. Cities are the main consumers of electricity, and the environmental impact of electricity use in cities has received increasing attention; however, relevant studies focus mainly on carbon emissions from urban power generation and urban direct electricity consumption, and carbon emissions induced by urban indirect electricity consumption are largely ignored. Using the Intergovernmental Panel on Climate Change (IPCC) carbon inventory method, the network approach and the environmentally extended multiregional input–output model, our study quantifies Beijing's production-, supply- and consumption-based electricity-related carbon emissions in 2007–2015. Additionally, methods of decomposition analysis are used to assess the impacts of the driving factors. The results show the following: (1) In 2015, Beijing obtained 45.6 million tons and 38.9 million tons of net inflow of electricity-related carbon emissions through electricity trade and regional trade, respectively. (2) Beijing obtained a large amount of electricity-related carbon emissions by purchasing heavy industrial products from Hebei, while Beijing's electricity-related carbon emissions flowing to Tianjin and Hebei consisted mainly of service industry products. (3) The fuel structure and energy efficiency contributed to the decline in Beijing's production-based emissions. Interprovincial electricity transmission offset the growth of supply-based emissions in Beijing. Improved electricity efficiency and production technology helped reduce consumption-based emissions, and the consumption volume was the major driver of the growth in consumption-based emissions. This study not only enhances our understanding of the environmental impacts associated with urban electricity consumption but also provides a basis for cross-regional environmental responsibility allocation. [ABSTRACT FROM AUTHOR]

The power sector plays a significant role in China's energy transition and emission reduction strategy. Considering that the aggregation of the power sector from different sources in input-output (IO) tables will lead to the "aggregation bias problem", it is vital that we disaggregate the power sector using IO tables when analyzing and comparing the driving forces of embodied carbon emission changes in the power sector. This paper first disaggregates the power sector into seven subsectors; then, it uses structural decomposition analysis (SDA) to analyze the driving forces of embodied carbon emission changes in each subsector and allocates embodied emissions that occur from 2007 to 2015 according to the demand categories. The results show that the embodied carbon emissions from each clean energy sector were relatively lower than those from thermal power during the study period. Consumption volume was the main driving factor for the embodied carbon emission increments. From 2012 to 2015, the production structure was mainly responsible for the embodied emission increases in each clean energy sector, indicating that the embodied carbon emissions caused by power equipment updates or reconstruction processes should receive more attention. In addition, the embodied carbon emission changes induced by urban residential consumption on the thermal power showed a plateaued trend from 2007 to 2015. This paper provides support for the formulation of emission reduction measures and the low-carbon structural transformation of the power sector. [ABSTRACT FROM AUTHOR]