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区域碳排放演化机制及其预测方法——以中国河北省为例。

Regional carbon emission evolution mechanism and its prediction approach: a case study of Hebei, China.

机构信息

Department of Economics Management, North China Electric Power University, No. 689 Huadian Road, Baoding, 071003, China.

Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing, 102206, China.

出版信息

Environ Sci Pollut Res Int. 2019 Oct;26(28):28884-28897. doi: 10.1007/s11356-019-06021-0. Epub 2019 Aug 5.

DOI:10.1007/s11356-019-06021-0
PMID:31385246
Abstract

Industrialization and urbanization process has brought both economic development and a series of environmental problems. Hebei Province is a high haze area and one of the key areas of China's "Blue Sky Defense" policy. As carbon emission is one of the most important factors causing haze, it is necessary to screen the influencing factors effectively to make quantitative analysis and predict carbon emissions in different degrees of coordination. Faced with the new situation of Beijing-Tianjin-Hebei coordinated development and more environmental constraints, this paper designs a system for predicting carbon emissions in Hebei Province innovatively using the data during 1990-2016. In the first step, 7 influence factors are determined by "graded screening." Then, this paper improved the traditional support vector machine (SVM) by improved gray wolf optimizer (IGWO), and established IGWO-SVM model. Finally, the carbon emissions in Hebei Province from 2017 to 2025 are predicted under three stages of different cooperative development speed of 7 influence factors by the improved intelligent algorithm model. Based on the forecasting results, this paper put forward some pertinent opinions to provide theoretical basis for formulating relevant policies on carbon emissions in Hebei Province to effectively control carbon emissions from the source.

摘要

工业化和城市化进程带来了经济发展和一系列环境问题。河北省是高雾霾地区之一,也是中国“蓝天防御”政策的重点区域之一。由于碳排放是导致雾霾的最重要因素之一,因此有必要有效地筛选影响因素,对不同协调程度的碳排放进行定量分析和预测。面对京津冀协同发展的新局面和更多的环境约束,本文创新性地利用 1990-2016 年的数据,设计了一个河北省碳排放预测系统。在第一步中,通过“分级筛选”确定了 7 个影响因素。然后,本文通过改进的灰狼优化算法(IGWO)对传统支持向量机(SVM)进行了改进,并建立了 IGWO-SVM 模型。最后,利用改进的智能算法模型,根据 7 个影响因素在不同协同发展速度的三个阶段,对 2017-2025 年河北省的碳排放进行预测。基于预测结果,本文提出了一些针对性的意见,为河北省制定碳排放相关政策提供了理论依据,以便从源头有效控制碳排放。

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