Driving determinants and prospective prediction simulations on carbon emissions peak for China's heavy chemical industry

Unprecedented huge mitigation task should be associated with profound efforts in facilitating emission reduction process over the globe. As the largest CO2 emitting country, China has been strenuously promoting the mitigation resilient development pathways in conjunction with the 2030 carbon emission peak commitment from Nationally Determined Contribution document which submitted under the Paris Agreement. Based on the peaking objective, carbon emission in heavy chemical industry should be received most attentions in terms of its large proportion with respect to the emission sources from other sectors. Particle swarm optimization (PSO) algorithm optimized back propagation neural network (BP) model is employed to predict future carbon emission for heavy chemical industry with the timeframe of 2017-2035 on the basis of the previous data. The significant magnitude of each carbon emission driving force is acquired in terms of the absolute influence coefficient method. The results indicated that, carbon emission in heavy chemical industry and its corresponding sub-sectors could be achieved peak under the implementation of the predetermined mitigation scenarios. The proportion of carbon emission in energy processing industry, steel industry, and building material industry is accounted for a larger fraction over the cumulative carbon emission in heavy chemical industry during the simulation period upon 2035. (C) 2019 Elsevier Ltd. All rights reserved.