Correction: Wang, L.; Dai, S. Carbon Footprint Accounting and Verification of Seven Major Urban Agglomerations in China Based on Dynamic Emission Factor Model. Sustainability 2024, 16, 9817

Sustainability, Journal Year: 2025, Volume and Issue: 17(2), P. 462 - 462

Published: Jan. 9, 2025

The authors would like to make the following corrections published paper [...]

Language: Английский

Life Cycle Carbon Emissions Accounting of China’s Physical Publishing Industry

Sustainability, Journal Year: 2025, Volume and Issue: 17(4), P. 1664 - 1664

Published: Feb. 17, 2025

The publishing industry, a major contributor to greenhouse gas emissions, produced approximately 730 Mt CO2eq globally in 2020 during the paper production phase alone. Unlike other sectors, decarbonization requires systematic reforms across supply chain, efficiency, energy transitions, consumption patterns, and recycling processes, as reliance on renewable alone is insufficient. This study focuses China’s physical developing comprehensive, high-resolution carbon emissions dataset that spans multiple publication types, stages, processes. It reveals emission characteristics life cycle, aiming quantify accurately address lack of life-cycle-based research. explores efficient, replicable, scalable strategies facilitate industry’s low-carbon transformation sustainable development. findings are follows. (1) Books primary source, contributing 77.05% total while journals newspapers account for 13.20% 9.75%, respectively. (2) Annual accounting life-cycle identifies printing most carbon-intensive responsible about 85% emissions. (3) In terms efforts, reductions 347,000 t per year can be achieved through measures such waste plastic packaging recycling, second-hand exchanges, recovery from incineration.

Language: Английский

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

Sustainability, Journal Year: 2024, Volume and Issue: 16(24), P. 11014 - 11014

Published: Dec. 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

Language: Английский