@article {26293,
	title = {An integrated assessment for achieving the 2 degrees C target pathway in China by 2030},
	journal = {Journal of Cleaner Production},
	volume = {268},
	year = {2020},
	note = {Xie, Yang Liu, Xiaorui Chen, Qi Zhang, Shaohui1879-1786},
	month = {Sep},
	abstract = {China submitted the Greenhouse gas emission reduction target in the form of Nationally Determined Contributions (NDC) to the Paris Agreement. To reduce the negative impact of global warming, a tighter target is needed, such as the 2-degree target. This study investigated how China could reach its emissions peak and decarbonize its economy through different key countermeasures in various sectors in line with the NDC and 2 degrees C targets by 2030. A dynamic CGE model is used to develop ten scenarios that contain two dimensions consisting of two stringency levels of carbon emission limitation and the availability of different low-carbon options. We found that in the baseline scenario, China\&$\#$039;s total CO2 emissions in 2030 would reach 14.7 Gt. To meet China\&$\#$039;s NDC target, it is essential to develop non-fossil fuel energy, restrict the over-expansion of energy-intensive industries and improve end-use efficiency. Meanwhile, the global 2 degrees C target poses higher requirements for China to develop various non-fossil technologies both in electricity production and demand sectors, and vigorously promote low-carbon consumption pattern. Furthermore, we estimated the economic impacts and found that if low-carbon measures are adopted properly, the mitigation cost in 2030 could decline by 92 and 226 USD/ton-CO2 under the NDC target and 2 degrees C target, respectively. Accordingly, GDP loss could fall from 3.8\% to barely 0.004\% under the NDC target, and from 11.6\% to 1.6\% under the 2 degrees C target. The welfare will almost not be affected significantly under all scenarios. Moreover, carbon reduction will also bring co-benefits on the air pollution improvement in China. (c) 2020 Elsevier Ltd. All rights reserved.},
	isbn = {0959-6526},
	author = {Xie, Y. and Liu, X. R. and Q. Chen and Zhang, SH}
}
