A Review of Building Carbon Emission Accounting and Prediction Models

Buildings, Journal Year: 2023, Volume and Issue: 13(7), P. 1617 - 1617

Published: June 26, 2023

As an industry that consumes a quarter of social energy and emits third greenhouse gases, the construction has important responsibility to achieve carbon peaking neutrality. Based on Web Science, Science-Direct, CNKI, accounting prediction models emissions from buildings are reviewed. The emission factor method, mass balance actual measurement method analyzed. top-down bottom-up their subdivision introduced Individual building assessments generally adopt physical model, while urban economic input-output model. Most current studies follow path “exploring influencing factors then putting forward based factors”. driving mainly use Stochastic Impacts by Regression Population, Affluence, Technology (STIRPAT) Logarithmic Mean Divisia Index (LMDI) grey correlation degree other models. model is realized regression system dynamics mathematical models, as well Artificial Neural Network (ANN) Support Vector Machine (SVM) machine learning At present, research individual focuses operational consumption, for stages should become focus in future research.

Language: Английский

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Carbon trading price forecasting in digitalization social change era using an explainable machine learning approach: The case of China as emerging country evidence

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 200, P. 123178 - 123178

Published: Jan. 3, 2024

Language: Английский

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Carbon emissions accounting and prediction in urban agglomerations from multiple perspectives of production, consumption and income

Applied Energy, Journal Year: 2023, Volume and Issue: 348, P. 121445 - 121445

Published: July 5, 2023

Language: Английский

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Study on the spatial network structure of energy carbon emission efficiency and its driving factors in Chinese cities

Applied Energy, Journal Year: 2024, Volume and Issue: 371, P. 123689 - 123689

Published: June 14, 2024

Language: Английский

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A factorial-analysis-based Bayesian neural network method for quantifying China's CO2 emissions under dual-carbon target

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 920, P. 170698 - 170698

Published: Feb. 9, 2024

Language: Английский

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Modelling monthly-gridded carbon emissions based on nighttime light data

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 354, P. 120391 - 120391

Published: Feb. 15, 2024

Language: Английский

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Enhancing sustainability integration in Sustainable Enterprise Resource Planning (S-ERP) system: Application of Transaction Cost Theory and case study analysis

International Journal of Information Management Data Insights, Journal Year: 2024, Volume and Issue: 4(2), P. 100243 - 100243

Published: April 23, 2024

Environmental stewardship and sustainability have become critical priorities in the contemporary business environment. Corporations are integrating sustainable practices at process level via Sustainable Enterprise Resource Planning (S-ERP). However, a recognised shortfall of S-ERP systems lies their potential inability to integrate metrics across all functions holistically. To navigate this limitation, our study introduces application Transaction Cost Theory (TCT). By treating processes as input-output systems, we apply theory quantify likelihood overall losses. This novel approach bridges gap, allowing for comprehensive integration processes. The essence methodology is leverage static input data collected by regarding environmental impact extrapolate provide broader understanding losses gains. We've tested validated through two case studies; one about product design development, other evaluation modular versus conventional construction methods. results inform formulation robust policies akin S-ERP, paving way more practices.

Language: Английский

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A graph-factor-based random forest model for assessing and predicting carbon emission patterns - Pearl River Delta urban agglomeration

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 469, P. 143220 - 143220

Published: July 20, 2024

Language: Английский

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The contribution of carbon capture and storage to Canada's net-zero plan

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 404, P. 136901 - 136901

Published: March 28, 2023

Language: Английский

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The evolution of research at the intersection of industrial ecology and artificial intelligence

Journal of Industrial Ecology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 8, 2025

Abstract The intersection of artificial intelligence (AI) and industrial ecology (IE) is gaining significant attention due to AI's potential enhance the sustainability production consumption systems. Understanding current state research in this field can highlight covered topics, identify trends, reveal understudied topics warranting future research. However, few studies have systematically reviewed intersection. In study, we analyze 1068 publications within IE–AI domain using trend factor analysis, word2vec modeling, top2vec modeling. These methods uncover patterns topic interconnections evolutionary trends. Our results 71 trending terms selected publications, 69 which, such as “deep learning,” emerged past 8 years. analysis shows that application various AI techniques increasingly integrated into life cycle assessment circular economy. suggests employing predict optimize indicators related products, waste, processes, their environmental impacts an emerging trend. Lastly, propose fine‐tuning large language models better understand process data specific IE, along with deploying real‐time collection technologies sensors, computer vision, robotics, could effectively address challenges data‐driven decision‐making domain.

Language: Английский

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