A multi-model assessment of energy and emissions for India's transportation sector through 2050
A multi-model assessment of energy and emissions for India's transportation sector through 2050
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DOI：
10.1016/j.enpol.2018.01.037
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发表时间：
2018-05-01
期刊：
影响因子：
9
通讯作者：
Wilson, Sangeetha Ann
中科院分区：
文献类型：
--
作者：
Paladugula, Anantha Lakshmi;Kholod, Nazar;Wilson, Sangeetha Ann
本文重点比较了印度交通部门到2050年的能源消耗和排放的框架和预测。为了了解道路运输在能源需求和排放中的作用，五个建模团队为印度的交通部门制定了基线预测，作为美国-印度能源对话可持续增长工作组（SGWG）的模型间比较工作的一部分。基于建模结果，我们探讨了印度的客运和货运公路运输的发展，包括模式转变的变化以及由此产生的能源消耗，二氧化碳（CO2）和颗粒物（PM2.5）排放的变化。我们发现基准年数据和未来预测参数存在重大差异，即一般运输和模式的能源消耗，客运和货运的服务需求。建模团队之间建模假设的差异反映了不同建模团队之间的意见差异，这反过来又反映了关键假设的潜在不确定性。我们已经确定了我们对印度交通部门发展的认识中的几个重要数据差距。印度决策者可以利用这一模型间研究的结果来制定运输部门减排的量化目标。
This paper focuses on comparing the framework and projections of energy consumption and emissions from India's transportation sector up to 2050. To understand the role of road transport in energy demand and emissions, five modeling teams developed baseline projections for India's transportation sector as part of inter model comparison exercise under the Sustainable Growth Working Group (SGWG) of the US-India Energy Dialog. Based on modeling results, we explore the developments in India's passenger and freight road transport, including changes in the modal shift and the resulting changes in energy consumption, carbon dioxide (CO2) and particulate matter (PM2.5) emissions. We find significant differences in the base-year data and parameters for future projections, namely energy consumption by transport in general and by mode, service demand for passenger and freight transport. Variation in modeling assumptions across modeling teams reflects the difference in opinion among the different modeling teams which in turn reflects the underlying uncertainty with respect to key assumptions. We have identified several important data gaps in our knowledge about the development of the transportation sector in India. The results of this inter-model study can be used by Indian policy makers to set quantified targets in emission reductions from the transportation sector.