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10.1108/IJESM-08-2020-0009

Originality/value Given the major role of China in global climate change mitigation, significant future reductions in China’s CO2 emissions will require transformation toward low-carbon energy systems.

Direct and indirect contributions of energy consumption structure to carbon emission intensity

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10.3390/SU13084417

This enabled us to predict the peak path of China’s CO2 emissions, select the path values that would achieve the CEPT with the year 2030 as the constraint condition, construct a multi-objective and multi-constraint input/output optimization model, employ the genetic algorithm to solve the model, and explore the industrial structure optimization and low-carbon transformation of Chinese industry.

Industrial Structure Optimization and Low-Carbon Transformation of Chinese Industry Based on the Forcing Mechanism of CO2 Emission Peak Target

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10.1007/s11356-021-15926-8

We use input-output analysis and Levinson’s structural decomposition method to measure China’s CO2 emissions under the no-trade hypothesis, to calculate how international trade affects China’s emissions.

International trade, CO2 emissions, and re-examination of “Pollution Haven Hypothesis” in China

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10.1016/j.jclepro.2020.123637

As economy grows, China’s CO2 emissions grows rapidly correspondingly.

Panel estimation for the impact factors on carbon dioxide emissions: A new regional classification perspective in China

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10.1007/s11356-020-12217-6

Motivated by this issue, the study examines the effect of energy use, economic policy uncertainty, and economic growth on China’s CO2 emissions from 1970 to 2018 by employing a novel dynamic ARDL simulation model.

Do energy use and economic policy uncertainty affect CO2 emissions in China? Empirical evidence from the dynamic ARDL simulation approach

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10.1007/s11356-021-12736-w

A new method for forecasting the future development of China’s CO2 emissions from fuel combustion is proposed in this paper by using grey forecasting theory.

Forecasting fuel combustion-related CO2 emissions by a novel continuous fractional nonlinear grey Bernoulli model with grey wolf optimizer

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10.1007/s11356-021-14540-y

The robustness of outcomes is checked through the Granger causality test, impulse response function (IRF), and variance decomposition method (VDM) suggesting that fossil fuel usage in the agriculture production process is mainly accountable for China’s CO2 emissions.

Towards long-term sustainable environment: does agriculture and renewable energy consumption matter?

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10.1016/J.IJGGC.2021.103328

As 41 % of China’s CO2 emission comes from coastal provinces and cities, permanent sequestration of anthropogenic CO2 in offshore sediments is a priority to achieve China’s national goal of net zero by 2060.

CO2 storage potential in major oil and gas reservoirs in the northern South China Sea

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10.3390/JRFM14030093

According to the Paris Agreement, it is estimated that China’s CO2 emissions will reach its peak by 2030.

Environmental Kuznets Curve Hypothesis on CO2 Emissions: Evidence for China

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10.1016/j.jclepro.2020.125453

(1) 2015 is a turning point for China’s CO2 emission mitigation progress, because the previously increasing embodied CO2 begins to decrease from 2015 to 2017.

Sector-level evaluation of China’s CO2 emissions: Trend evolution and index ranking

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10.1007/s11356-021-16595-3

With the rapid development of China, urbanization has become an important research topic of China’s CO2 emissions.

Study on the impact of comprehensive urbanization on urban civil building CO2 emissions in China

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Chinas Co2 - Originality/value Given the major role of China in global climate change mitigation, significant future reductions in China’s CO2 emissions will require transformation toward low-carbon energy systems. [1] This enabled us to predict the peak path of China’s CO2 emissions, select the path values that would achieve the CEPT with the year 2030 as the constraint condition, construct a multi-objective and multi-constraint input/output optimization model, employ the genetic algorithm to solve the model, and explore the industrial structure optimization and low-carbon transformation of Chinese industry. [2] We use input-output analysis and Levinson’s structural decomposition method to measure China’s CO2 emissions under the no-trade hypothesis, to calculate how international trade affects China’s emissions. [3] As economy grows, China’s CO2 emissions grows rapidly correspondingly. [4] Motivated by this issue, the study examines the effect of energy use, economic policy uncertainty, and economic growth on China’s CO2 emissions from 1970 to 2018 by employing a novel dynamic ARDL simulation model. [5] A new method for forecasting the future development of China’s CO2 emissions from fuel combustion is proposed in this paper by using grey forecasting theory. [6] The robustness of outcomes is checked through the Granger causality test, impulse response function (IRF), and variance decomposition method (VDM) suggesting that fossil fuel usage in the agriculture production process is mainly accountable for China’s CO2 emissions. [7] As 41 % of China’s CO2 emission comes from coastal provinces and cities, permanent sequestration of anthropogenic CO2 in offshore sediments is a priority to achieve China’s national goal of net zero by 2060. [8] According to the Paris Agreement, it is estimated that China’s CO2 emissions will reach its peak by 2030. [9] (1) 2015 is a turning point for China’s CO2 emission mitigation progress, because the previously increasing embodied CO2 begins to decrease from 2015 to 2017. [10] With the rapid development of China, urbanization has become an important research topic of China’s CO2 emissions. [11]