A large-scale analytical residential parcel delivery model evaluating greenhouse gas emissions, COVID-19 impact, and cargo bikes

IF 4.3 Q2 TRANSPORTATION
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引用次数: 0

Abstract

The e-commerce industry has experienced significant growth in the past decade, particularly post-COVID. To accommodate such growth, the parcel delivery sector has also grown rapidly. However, there is a lack of study that properly evaluates its social and environmental impacts at a large scale. A model is proposed to analyze such impacts. A parcel generation process is presented to convert public data into parcel volumes and stops. A continuous approximation model is fitted to estimate the length of parcel service tours. A case study is conducted using New York City (NYC) data. The parcel generation is shown to be a valid fit. The continuous approximation model parameters have R2 values of 98% or higher. The model output is validated against UPS truck trips. Application of the model to 2021 suggests residential parcel deliveries contributed to 0.05% of total daily vehicle-kilometer-traveled (VKT) in NYC corresponding to 14.4 metric tons of carbon equivalent (MTCE) emissions per day. COVID-19 contributed to an increase in parcel deliveries that led to up to 1 064.3 MTCE of annual greenhouse gas (GHG) emissions in NYC (which could power 532 standard US households for a year). The existing bike lane infrastructure can support the substitution of 17% of parcel deliveries by cargo bikes, which would reduce VKT by 11%. Adding 3 km of bike lanes to connect Amazon facilities can expand their cargo bike substitution benefit from a VKT reduction of 5% up to 30%. If 28 km of additional bike lanes are made, parcel delivery substitution citywide could increase from 17% to 34% via cargo bike and save an additional 2.3 MTCE per day. Cargo bike priorities can be set to reduce GHG emissions for lower-income neighborhoods including Harlem, Sunset Park, and Bushwick.
评估温室气体排放、新冠肺炎影响和货运自行车的大型分析住宅包裹交付模型
在过去十年中,电子商务行业经历了显著增长,尤其是在经历了《电子商 务发展协议》(COVID)之后。为了适应这种增长,包裹递送行业也迅速发展。然而,目前还缺乏对其大规模的社会和环境影响进行适当评估的研究。本文提出了一个模型来分析这种影响。本文提出了一个包裹生成过程,将公共数据转换为包裹数量和停靠站点。采用连续近似模型来估算包裹服务巡视的长度。利用纽约市(NYC)的数据进行了案例研究。结果表明,包裹生成的拟合是有效的。连续近似模型参数的 R2 值达到 98% 或更高。模型输出与 UPS 卡车行程进行了验证。该模型在 2021 年的应用表明,住宅包裹递送量占纽约市日车辆行驶总公里数(VKT)的 0.05%,相当于每天 14.4 公吨碳当量(MTCE)的排放量。COVID-19 促使包裹递送量增加,导致纽约市每年温室气体排放量高达 1 064.3 公吨碳当量(GHG)(可供 532 个标准美国家庭使用一年)。现有的自行车道基础设施可以支持用货运自行车替代 17% 的包裹运送,这将减少 11% 的总运输量。增加 3 公里的自行车道连接亚马逊设施,可将货运自行车的替代效益从减少 5% 的 VKT 提高到 30%。如果增加 28 公里的自行车道,全市范围内通过货运自行车运送包裹的替代率可从 17% 提高到 34%,每天可额外节省 2.3 MTCE。货运自行车的优先级可设定为减少哈莱姆区、日落公园和布什威克等低收入社区的温室气体排放。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Transportation Science and Technology
International Journal of Transportation Science and Technology Engineering-Civil and Structural Engineering
CiteScore
7.20
自引率
0.00%
发文量
105
审稿时长
88 days
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