Spatial spillover effect of non-fossil fuel power generation on carbon dioxide emissions across China's provinces

Yang

et al. 2021

Environ Sci Pollut Res

The paper aims to investigate the influencing factors that drive the temporal and spatial differences of CO2 emissions for the transportation sector in China. For this purpose, this study adopts a Logistic Mean Division Index (LMDI) model to explore the driving forces of the changes for the transport sector’s CO2 emissions from a temporal perspective during 2000–2017 and identifies the key factors of differences in the transport sector’s CO2 emissions of China’s 15 cities in four key years (i.e., 2000, 2005, 2010, and 2017) using a multi-regional spatial decomposition model (M-R). Based on the empirical results, it was found that the main forces for affecting CO2 emissions of the transport sector are not the same as those from temporal and spatial perspectives. Temporal decomposition results show that the income effect is the dominant factor inducing the increase of CO2 emissions in the transport sector, while the transportation intensity effect is the main factor for curbing the CO2 emissions. Spatial decomposition results demonstrate that income effect, energy intensity effect, transportation intensity effect, and transportation structure effect are important factors which result in enlarging the differences in city-level CO2 emissions. In addition, the less-developed cities and lower energy efficiency cities have greater potential to reduce CO2 emissions of the transport sector. Understanding the feature of CO2 emissions and the influencing factors of cities is critical for formulating city-level mitigation strategies of the transport sector in China. Overall, it is expected that the level of economic development is the main factor leading to the differences in CO2 emissions from a spatial-temporal perspective.

Section: Methodology Study Area and Datamentioning

confidence: 99%

Driving forces of temporal-spatial differences in CO2 emissions at the city level for China’s transport sector

Yang

et al. 2021

Environ Sci Pollut Res

“…For example, the embodied carbon intensity of Mexico's exports to the United States increases from 0.07 kg/USD in 2000 to 0.12 kg/USD in 2014, and exports to China also increase from 0.06 kg/USD in 2000 to 0.10 kg/USD in 2014. This shows that the export of ICT products may not reduce the carbon intensity to achieve emission reduction due to technical restrictions, which has caused the significant spillover effect 2 of export carbon emissions (Liu and Liu, 2019;Wang and Li, 2019). Relatively speaking, the embodied carbon intensities of European countries, such as Spain, France, and the United Kingdom, are at the low level.…”

Section: Embodied Carbon Intensity Flowsmentioning

confidence: 99%

Assessing Embodied Carbon Emission and Its Intensities in the ICT Industry: The Global Case

2021

With the intensification of globalization, the information and communication technologies (ICT) sector, as one of the emerging industrial sectors, has played an important role in reducing carbon emissions in regional trade and improving the energy efficiency of traded products. This article uses a multi-regional input-output (MRIO) model to explore the flow of embodied carbon emissions and embodied carbon emission intensities in the ICT sector triggered by trade in 15 major economies around the world from 2000 to 2014. The article further discusses the emission-reduction strategies of each ICT sector. The results show that: (1) The overall embodied carbon emissions of ICT have demonstrated a significant downward trend, but the proportion of embodied carbon emissions caused by trade is increasing; (2) The embodied carbon emissions in the ICT sector of most developed countries in 2014 are significantly lower than in 2000, but in developing countries such as China and India they show an upward trend during this period; (3) The ICT sector’s export embodied carbon emission intensity in Indonesia is much higher than that of other countries, and the embodied carbon emissions of ICT exported by Mexico have increased significantly; (4) The manufacture of computer, electronic and optical products (S1) is the main contributor to the ICT sector’s embodied carbon emissions, while import embodied carbon emission intensities among publishing activities (S2) are increasing significantly in most countries. The conclusion of this paper has important implications for how to reduce ICT’s embodied carbon emissions of major countries.

“…The ESDA method is introduced to measure the characteristics of spatial and temporal distributions of CO 2 emission. Moran's I index is used to examine the spatial agglomeration characteristics of regional carbon emission [48][49][50]. The calculations are as follows:…”

Section: Calculation Of Co 2 Emissionmentioning

confidence: 99%

Social and Economic Factors of Industrial Carbon Dioxide in China: From the Perspective of Spatiotemporal Transition

Li¹,

Cheng²,

Diao³

et al. 2021

Sustainability

The reduction of CO2 emission has become one of the significant tasks to control climate change in China. This study employs Exploratory Spatial Data Analysis (ESDA) to identify the provinces in China with different types of spatiotemporal transition, and applies the Logarithmic Mean Divisia Index (LMDI) to analyze the influencing factors of industrial CO2 emissions. Spatial autocorrelation of provincial industrial CO2 emissions from 2003 to 2017 has been demonstrated. The results are as follows: (1) 30 provinces in China are categorized into 8 types of spatiotemporal transition, among which 24 provinces are characterized by stable spatial structure and 6 provinces show significant spatiotemporal transition; (2) For all types of spatiotemporal transition, economic scale effect is mostly contributed to industrial CO2 emission, while energy intensity effect is the most crucial driving force to reduce industrial carbon dioxide emission; (3) provinces of type HH-HH, HL-HL and HL-HH are most vital for CO2 emission reduction, while the potential CO2 emission increase of developing provinces in LL-LL, LH-LH and LL-LH should also be taken into account. Specific measures for CO2 emission reduction are suggested accordingly.