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Assessing potential reduction in greenhouse gas: An integrated approach

机译:评估温室气体的潜在减少量:综合方法

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Greenhouse gases remain as threat to the environment. Various models employed in greenhouse gases are either to determine the causative factors responsible for emission, forecast emission or to optimize. Integrating these models would reduce the limitations of individual models to better assess possible greenhouse mitigation. This paper addresses the management technique for analyzing, assessing and mitigating industry's carbon dioxide (CO2) emission. The current work offers a different technique based on an integrated model utilizing the functions of Index Decomposition Analysis (IDA), Artificial Neural Network (ANN) and Data Envelopment Analysis (DEA) composed of activity, structure, intensity and energy-mix as inputs responsible for CO2 emission. By considering how the three different models are integrated into one system, it will be demonstrated how much percentage of an industry's CO2 can be reduced. The Canadian industrial sector was analyzed using the integrated model and it was discovered that 3.13% of emitted CO2 from year 1991 to year 2035 could be mitigated. (C) 2016 Elsevier Ltd. All rights reserved.
机译:温室气体仍然是对环境的威胁。温室气体中使用的各种模型要么用于确定造成排放的原因,预测排放,要么进行优化。整合这些模型将减少单个模型的局限性,以便更好地评估可能的温室效应缓解措施。本文介绍了用于分析,评估和缓解行业二氧化碳排放的管理技术。当前的工作提供了一种基于集成模型的不同技术,该模型利用了索引分解分析(IDA),人工神经网络(ANN)和数据包络分析(DEA)的功能,这些数据由活动,结构,强度和能量混合组成,作为负责任的输入用于二氧化碳排放。通过考虑如何将三种不同的模型集成到一个系统中,将证明可以减少多少二氧化碳排放量。使用集成模型对加拿大工业部门进行了分析,发现可以减轻1991年至2035年间3.13%的二氧化碳排放量。 (C)2016 Elsevier Ltd.保留所有权利。

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