Citation map · Study

SZodixStudyAcademic Library

Shelves Open access

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

Decomposition and prediction of China's carbon emission intensity towards carbon neutrality: From perspectives of national, regional and sectoral level

12 references·3 citing·55 second hopsampled

FromToDepth

this work references cited by second hop· second hop is a sample of the most-cited connections

References

2006ARIMA forecasting of primary energy demand by fuel in Turkey622 cited
2017Drivers of carbon emission intensity change in China445 cited
2016Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey302 cited
2007Decomposition of aggregate CO2 emissions: A production-theoretical approach294 cited
2015Driving forces of Spain׳s CO2 emissions: A LMDI decomposition approach253 cited
2017Energy and carbon intensity in China during the urbanization and industrialization process: A panel VAR approach222 cited
2017How to achieve the 2030 CO 2 emission-reduction targets for China's industrial sector: Retrospective decomposition and prospective trajectories214 cited
2016Decomposition of intensity of energy-related CO 2 emission in Chinese provinces using the LMDI method212 cited
2018How does information and communication technology affect China's energy intensity? A three-tier structural decomposition analysis190 cited
2021Analysis and forecast of China's energy consumption structure176 cited
2019Decomposition analysis of China's CO2 emissions (2000–2016) and scenario analysis of its carbon intensity targets in 2020 and 2030171 cited
2021China's carbon intensity factor decomposition and carbon emission decoupling analysis168 cited

Cited by

2022Regional inequality in the carbon emission intensity of public buildings in China

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

88 cited

2022Regional disparities and evolution trend of city-level carbon emission intensity in China88 cited

2023Industrial carbon emission forecasting considering external factors based on linear and machine learning models82 cited