With the implementation of China's top-down CO2 emissions reduction strategy, the regional differences should be considered. As the most basic governmental unit in China, counties could better capture the regional heterogeneity than provinces and prefecture-level city, and county-level CO2 emissions could be used for the development of strategic policies tailored to local conditions. However, most of the previous accounts of CO2 emissions in China have only focused on the national, provincial, or city levels, owing to limited methods and smaller-scale data. In this study, a particle swarm optimization-back propagation (PSO-BP) algorithm was employed to unify the scale of DMSP/OLS and NPP/VIIRS satellite imagery and estimate the CO2 emissions in 2,735 Chinese counties during 1997-2017. Moreover, as vegetation has a significant ability to sequester and reduce CO2 emissions, we calculated the county-level carbon sequestration value of terrestrial vegetation. The results presented here can contribute to existing data gaps and enable the development of strategies to reduce CO2 emissions in China.

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County-level CO2 emissions and sequestration in China during 1997–2017

The role of renewable energy technological innovation on climate change: Empirical evidence from China.

Energy efficiency: The role of technological innovation and knowledge spillover

Heterogeneous impacts of environmental regulations and foreign direct investment on green innovation across different regions in China.

Can urbanization process and carbon emission abatement be harmonious? New evidence from China

The effect of technological factors on China's carbon intensity: New evidence from a panel threshold model

This paper empirically investigates the roles of indigenous and foreign innovations in the development of technology spillovers originating from foreign direct investments, exports and imports on the energy intensity across China's 30 provinces for the period 2000–2013. The Driscoll-Kraay standard error estimator is first used to tackle the problems of heteroscedasticity and serial correlations in the models, and further discussion with a panel cointegration analysis is employed to confirm the estimates. The results indicate that indigenous innovations play a more important effect on energy intensity than foreign innovations. However, the panel threshold analysis indicates that the effects of foreign innovations on the energy intensity across China depend on the technological absorptive capacity affecting factors such as local research and development investment and human capital stock.

Hongyan Lei

Papers

The effect of technological factors on China's carbon intensity: New evidence from a panel threshold model

Indigenous versus foreign innovation and energy intensity in China