员工差旅的碳排放特征与碳减排分析--以某研究所为例

Q2 Energy Energy Informatics Pub Date : 2024-10-02 DOI:10.1186/s42162-024-00407-2
Lan Zhang, Yan Bai, Rui Zhang, Yuexin Ma, Chongwen Shen
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引用次数: 0

摘要

本文采用 "基线情景法 "构建了一个全面的模型来计算和减少员工差旅产生的碳排放,包括通勤和商务旅行的碳排放核算,以及绿色差旅的碳减排评估。研究采用问卷调查和现场访谈等方法,以北京某研究所员工的出行数据为案例进行收集。结果显示,员工的通勤方式多种多样,地铁是主要的出行方式;然而,商务旅行产生的碳排放量较高,尤其是在受教育程度较高的员工中。研究认为,本文提出的模型为初步碳排放估算提供了一个框架,但要提高估算的准确性,还需要考虑更多的变量和因素,并指出了模型的局限性。研究结果对政策和制度实践具有重要意义,建议采取更有针对性的措施,减少高碳排放出行方式的使用,鼓励使用绿色出行方式。随着未来数据收集技术的不断进步,将有可能进一步建立更加完善的碳排放核算模型,获得更加准确和全面的出行数据,从而为制定更加有效的碳减排战略和政策提供坚实的数据支持。
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Carbon emission characteristics and carbon reduction analysis of employee travel-taking a research institute as an example

This paper adopts the “baseline scenario method” to construct a comprehensive model for calculating and reducing carbon emissions generated by employee travel, including the accounting of carbon emissions from commuting and business travel, as well as the assessment of green travel for carbon reduction. The study employs methods such as questionnaires and on-site interviews to collect travel data from employees of a research institute in Beijing as a case study. The results show that employees’ commuting methods are diverse, with the subway being the primary mode of travel; however, business travel generates higher carbon emissions, particularly among employees with higher education levels. The research concludes that the model proposed in this paper provides a framework for preliminary carbon emission estimation, but to improve the accuracy of the estimates, more variables and factors need to be considered, and the limitations of the model are pointed out. The research findings have significant implications for policy and institutional practices, suggesting the adoption of more targeted measures to reduce the use of high-carbon-emission travel methods and to encourage the use of green travel options. With the continuous advancement of data collection technologies in the future, it will be possible to further establish a more refined carbon emission accounting model and obtain more accurate and comprehensive travel data, thereby providing solid data support for the development of more effective carbon reduction strategies and policies.

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来源期刊
Energy Informatics
Energy Informatics Computer Science-Computer Networks and Communications
CiteScore
5.50
自引率
0.00%
发文量
34
审稿时长
5 weeks
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