Research and Prediction Analysis of Key Factors Influencing the Carbon Dioxide Emissions of Countries Along the “Belt and Road” Based on Panel Regression and the A-A-E Coupling Model DOI Open Access

Xiangdong Feng,

Xiaolin Wang, Wen Li

и другие.

Sustainability, Год журнала: 2024, Номер 16(24), С. 11014 - 11014

Опубликована: Дек. 16, 2024

With the in-depth implementation of China’s “Belt and Road” strategic policy, member countries along Belt Road have gained enormous economic benefits. Thus, it is important to accurately grasp factors that affect carbon emissions coordinate relationship between development environmental protection, which can impact living environment people worldwide. In this study, researchers gathered data from World Bank database, identified key indicators significantly impacting emissions, employed Pearson correlation coefficient random forest model perform dimensionality reduction on these indicators, subsequently assessed refined using a panel regression examine significance across various country types. To ensure stability results, three prediction models were selected for coupling analysis: adaptive neuro-fuzzy inference system (ANFIS) field machine learning, autoregressive integrated moving average (ARIMA) model, exponential smoothing method (ES) time series prediction. These used assess 54 2021 2030, formula was defined integrate results. The findings demonstrated amalgamates forecasting traits approaches, manifesting remarkable stability. error analysis also indicated short-term results are satisfactory. This has substantial practical implications China in terms fine-tuning its foreign considering entire situation planning accordingly, advancing energy conservation emission

Язык: Английский

China carbon emission accounts 2020-2021 DOI Creative Commons

Jinghang Xu,

Yuru Guan, Jonathan D. Oldfield

и другие.

Applied Energy, Год журнала: 2024, Номер 360, С. 122837 - 122837

Опубликована: Фев. 16, 2024

In the past a few years, outbreak of COVID-19 epidemic has significantly changed global emission patterns and increased challenges in reduction. However, comprehensive analysis most recent trends China's carbon emissions not been conducted due to lack up-to-date accounts by regions sectors. This study compiles latest CO2 inventories for China its 30 provinces during (2020−2021), following administrative-territorial approach from International Panel on Climate Change (IPCC). Our cover energy-related 17 types fossil fuel combustion cement production across 47 economic To provide holistic view patterns, we esitamted consumption-based China. We find that led 50% reduction growth rate territorial 2020 compared 2019. trend then reversed 2021 as lockdown measures gradually relaxed. reveals impact rapid expansion exports, driven prevention materials "stay-at-home economy" products widening differences between territorial- emissions. offers timely blueprint designing strategies towards peak neutrality, especially context sustainable recoveries mitigation post-pandemic.

Язык: Английский

Процитировано

106

Low-carbon efficiency analysis of rail-water multimodal transport based on cross efficiency network DEA approach DOI

Weipan Zhang,

Xianhua Wu, Jihong Chen

и другие.

Energy, Год журнала: 2024, Номер 305, С. 132348 - 132348

Опубликована: Июль 6, 2024

Язык: Английский

Процитировано

15

Integrated Benefits of Synergistically Reducing Air Pollutants and Carbon Dioxide in China DOI

Shengyue Li,

Shuxiao Wang, Qingru Wu

и другие.

Environmental Science & Technology, Год журнала: 2024, Номер 58(32), С. 14193 - 14202

Опубликована: Авг. 1, 2024

China's advancements in addressing air pollution and reducing CO2 emissions offer valuable lessons for collaborative strategies to achieve diverse environmental objectives. Previous studies have assessed the mutual benefits of climate policies control measures on one another, lacking an integrated assessment synergistic attributed refined measures. Here, we comprehensively used coupled emission inventory response models evaluate synergy degrees various pollutants China during 2013–2021. Results indicated that implemented yielded value at 6.7 (2.4–12.6) trillion Chinese Yuan. The top five contributors, accounting 55%, included promoting non-thermal power, implementing end-of-pipe technologies power plants iron steel industry, replacing residential scattered coal, saving building energy. Measures demonstrating high synergies per unit reduction (e.g., green traffic promotion) low mainly due their application, which are expected gain greater implementation prioritization future. Our findings provide insights into effectiveness limitations aimed joint control. By ranking these based synergy, guidance policy development other nations with similar needs.

Язык: Английский

Процитировано

10

Parameters optimization for decontamination and fine physical regeneration pathways of polypropylene plastics from waste lunchboxes DOI
Lipeng Dong,

Wenwu Zhi,

Weijun Li

и другие.

Journal of Hazardous Materials, Год журнала: 2024, Номер 470, С. 134247 - 134247

Опубликована: Апрель 9, 2024

Язык: Английский

Процитировано

6

The synergic impacts of air pollution control policies on pollutants and carbon emissions DOI
Zhuanzhuan Ren, Jiali Zheng,

Lianyang Jiao

и другие.

Journal of Environmental Management, Год журнала: 2024, Номер 370, С. 122730 - 122730

Опубликована: Окт. 11, 2024

Язык: Английский

Процитировано

4

Impact of household size and structure on carbon emissions in China DOI Creative Commons
Kun Yang,

Wu Jun,

Ling Li

и другие.

Structural Change and Economic Dynamics, Год журнала: 2025, Номер unknown

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Research on statistical measure under double carbon target - Self-moving regression model of grey prediction based on entropy weight method DOI Creative Commons

Sanglin Zhao,

Hao Deng,

Jackon Steve

и другие.

F1000Research, Год журнала: 2025, Номер 14, С. 437 - 437

Опубликована: Май 6, 2025

Background At the 2020 UN General Assembly, China pledged to peak carbon emissions before 2030 and achieve neutrality by 2060. However, traditional social development model has led increasing annually, highlighting need resolve contradiction between reduction. This study examines relationship emissions, economy, population, energy consumption in a specific region support goals. Methods A comprehensive indicator system was established, encompassing economic, consumption, indicators. The analyzed these factors during 12th 13th Five Year Plans, comparing total 2010 across plans, assessing trends. It also comprehensively relationships mutual influences among factors. identified main challenges achieving neutrality. Using Kaya various factor models, it calculated times for three scenarios: baseline (2022), natural (2036), ambitious (2021). These findings provide basis dual path planning. Result research results indicate that are closely related consumption. prediction shows future trend of is controllable. Suggestions planning proposed empirical policy formulation. Under scenario, expected occur around 2022; circumstances, will be postponed 2036; In time can advanced 2021. Conclusion crucial reduction targets sustainable used formulate targeted policies promote regional China’s commitments.

Язык: Английский

Процитировано

0

Towards decoupling in chemical industry: Input substitution impacted by technological progress DOI

Xiaojun Sun,

Yee Van Fan, Yalin Lei

и другие.

Journal of Cleaner Production, Год журнала: 2024, Номер 452, С. 142040 - 142040

Опубликована: Март 30, 2024

Язык: Английский

Процитировано

3

Balancing through agglomeration: A third path to sustainable development between common prosperity and carbon neutrality in China DOI
Mengxue Zhao, Hon S. Chan

Technological Forecasting and Social Change, Год журнала: 2024, Номер 208, С. 123737 - 123737

Опубликована: Сен. 8, 2024

Язык: Английский

Процитировано

3

Impact of COVID-19 pandemic on microplastic occurrence in aquatic environments: A three-year study in Taihu Lake Basin, China DOI
Jiannan Ding,

Yi Peng,

Xiaojun Song

и другие.

Journal of Hazardous Materials, Год журнала: 2024, Номер 478, С. 135530 - 135530

Опубликована: Авг. 14, 2024

Язык: Английский

Процитировано

2