High-Frequency Estimation and Prediction of Carbon Emissions in Chinese Municipalities: A Case Study of 14 Municipalities in Guangxi Province

In October 2024, the National Development and Reform Commission (NDRC) and other departments released the “Work Plan for Improving the Carbon Emission Statistics and Accounting System”, which explicitly proposed the promotion of municipal-level energy balance tables and the development of carbon emi...

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Main Authors: Chunli Zhou, Haoyang Ji, Bin Liu, Huizhen Tang, Huaying Zhang, Junyi Shi
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Energies
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Online Access:https://www.mdpi.com/1996-1073/18/6/1382
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author Chunli Zhou
Haoyang Ji
Bin Liu
Huizhen Tang
Huaying Zhang
Junyi Shi
author_facet Chunli Zhou
Haoyang Ji
Bin Liu
Huizhen Tang
Huaying Zhang
Junyi Shi
author_sort Chunli Zhou
collection DOAJ
description In October 2024, the National Development and Reform Commission (NDRC) and other departments released the “Work Plan for Improving the Carbon Emission Statistics and Accounting System”, which explicitly proposed the promotion of municipal-level energy balance tables and the development of carbon emission prediction and early warning models. Currently, China has not yet released municipal-level energy balance tables, making it impossible to directly estimate municipal carbon emissions using the IPCC inventory-based method. This paper draws on the electricity–energy–carbon model at the industry level and conducts high-frequency carbon emission estimation for 14 municipalities in Guangxi as a case study. Based on this, the Prophet model is introduced, incorporating planned electricity consumption data to construct a carbon emission prediction and early warning model, enabling long-term carbon emission forecasting at the municipal level. The results indicate the following: First, among the 14 municipalities in Guangxi, Baise has the highest share of carbon emissions (27%), followed by Liuzhou (13%). In terms of carbon emission intensity, six municipalities exceed the regional average, including Baise, Chongzuo, and Fangchenggang. Second, the total carbon emissions in Guangxi (from energy consumption) are expected to peak by 2030, and all 14 municipalities are expected to achieve peak carbon emissions from energy consumption before 2030.
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spelling doaj-art-fe88cd55b73b4e5b96e9689176b270562025-08-20T03:43:30ZengMDPI AGEnergies1996-10732025-03-01186138210.3390/en18061382High-Frequency Estimation and Prediction of Carbon Emissions in Chinese Municipalities: A Case Study of 14 Municipalities in Guangxi ProvinceChunli Zhou0Haoyang Ji1Bin Liu2Huizhen Tang3Huaying Zhang4Junyi Shi5Guangxi Power Grid Co., Ltd., Nanning 530004, ChinaSchool of Economics, Peking University, Beijing 100871, ChinaChina Energy Engineering Group Guangxi Electric Power Design Institute Co., Ltd., Nanning 530023, ChinaGuangxi Power Grid Co., Ltd., Nanning 530004, ChinaChina Energy Engineering Group Guangxi Electric Power Design Institute Co., Ltd., Nanning 530023, ChinaSchool of Statistics, Beijing Normal University, Beijing 100875, ChinaIn October 2024, the National Development and Reform Commission (NDRC) and other departments released the “Work Plan for Improving the Carbon Emission Statistics and Accounting System”, which explicitly proposed the promotion of municipal-level energy balance tables and the development of carbon emission prediction and early warning models. Currently, China has not yet released municipal-level energy balance tables, making it impossible to directly estimate municipal carbon emissions using the IPCC inventory-based method. This paper draws on the electricity–energy–carbon model at the industry level and conducts high-frequency carbon emission estimation for 14 municipalities in Guangxi as a case study. Based on this, the Prophet model is introduced, incorporating planned electricity consumption data to construct a carbon emission prediction and early warning model, enabling long-term carbon emission forecasting at the municipal level. The results indicate the following: First, among the 14 municipalities in Guangxi, Baise has the highest share of carbon emissions (27%), followed by Liuzhou (13%). In terms of carbon emission intensity, six municipalities exceed the regional average, including Baise, Chongzuo, and Fangchenggang. Second, the total carbon emissions in Guangxi (from energy consumption) are expected to peak by 2030, and all 14 municipalities are expected to achieve peak carbon emissions from energy consumption before 2030.https://www.mdpi.com/1996-1073/18/6/1382electricity–energy–carbon modelmunicipal carbon emissionshigh-frequencypredictionprophet model
spellingShingle Chunli Zhou
Haoyang Ji
Bin Liu
Huizhen Tang
Huaying Zhang
Junyi Shi
High-Frequency Estimation and Prediction of Carbon Emissions in Chinese Municipalities: A Case Study of 14 Municipalities in Guangxi Province
Energies
electricity–energy–carbon model
municipal carbon emissions
high-frequency
prediction
prophet model
title High-Frequency Estimation and Prediction of Carbon Emissions in Chinese Municipalities: A Case Study of 14 Municipalities in Guangxi Province
title_full High-Frequency Estimation and Prediction of Carbon Emissions in Chinese Municipalities: A Case Study of 14 Municipalities in Guangxi Province
title_fullStr High-Frequency Estimation and Prediction of Carbon Emissions in Chinese Municipalities: A Case Study of 14 Municipalities in Guangxi Province
title_full_unstemmed High-Frequency Estimation and Prediction of Carbon Emissions in Chinese Municipalities: A Case Study of 14 Municipalities in Guangxi Province
title_short High-Frequency Estimation and Prediction of Carbon Emissions in Chinese Municipalities: A Case Study of 14 Municipalities in Guangxi Province
title_sort high frequency estimation and prediction of carbon emissions in chinese municipalities a case study of 14 municipalities in guangxi province
topic electricity–energy–carbon model
municipal carbon emissions
high-frequency
prediction
prophet model
url https://www.mdpi.com/1996-1073/18/6/1382
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