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This study closes the gap by running two macroscopic traffic simulations of New York City in PTV VISUM. It evaluates on-demand meal delivery emissions by OD-pairs (trip level) and by network links (street level), showing delivery impacts on detours, congestion, and vehicle emissions per kilometer across the entire network.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/emission-estimation-of-on-demand-meal-delivery-services-a-macroscopic-simulation/401927/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/emission-estimation-of-on-demand-meal-delivery-services-a-macroscopic-simulation/401927.png","ImageObject",300,407,{"name":92,"@type":93},"Emma Wilson","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-29","2026-09-27",true,{"@type":102,"interactionType":103,"userInteractionCount":8},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why is integrating last-mile delivery into macroscopic traffic simulations important?","Question",{"text":112,"@type":113},"Because evaluating only the delivery service can ignore how delivery activities change city traffic flow, which directly affects emissions.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does the study evaluate emissions for on-demand meal delivery?",{"text":117,"@type":113},"It compares two approaches in PTV VISUM: emission evaluation per OD-pair (each trip) and emission evaluation per network link (each street).",{"name":119,"@type":110,"acceptedAnswer":120},"What traffic effects does the study highlight as consequences of on-demand meal delivery?",{"text":121,"@type":113},"It reports impacts on travelled distance (detours), congestion levels, and emissions per kilometer for every vehicle in the network, not only delivery vehicles.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},401927,1790673421,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":8,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},3848291630094,"https://eur-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45","Article  \nEmission Estimation of On-Demand Meal Delivery Services Using a Macroscopic Simulation  \nMaren Schnieder *, Chris Hinde  and Andrew West  \nCitation: Schnieder, M.; Hinde, C.; West, A. Emission Estimation of On-Demand Meal Delivery Services Using a Macroscopic Simulation. Int.  \nJ. Environ. Res. Public Health 2022, 19, 11667. [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)ijerph191811667  \nAcademic Editor: Paul B. Tchounwou  \nReceived: 17 August 2022  \nAccepted: 14 September 2022  \nPublished: 16 September 2022  \nPublisher's Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.  \nCopyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) .  \nThe Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, UK  \n* [Correspondence: m.schnieder@lboro.ac.uk](Correspondence: m.schnieder@lboro.ac.uk)  \nAbstract: While macroscopic simulations of passenger vehicle traffic within cities are now common practice, the integration of last mile delivery into a macroscopic simulation to evaluate the emissions has seldomly been achieved. In fact, studies focusing solely on last mile delivery generally focus on evaluating the delivery service itself. This ignores the effect the delivery service may have on the traffic flow in cities, and therefore, on the resulting emissions. This study fills this gap by presenting the results of two macroscopic traffic simulations of New York City (NYC) in PTV VISUM: (i) ondemand meal delivery services, where the emissions are evaluated for each OD-Pairs (i.e., each trip) and (ii) on-demand meal delivery services, where the emissions are evaluated for each link of the network (i.e., street) . This study highlights the effect on-demand meal delivery has on the travelled distance (i.e., detours), congestion and emissions per km of every vehicle in the network, not just the delivery vehicles.  \nKeywords: PTV VISUM; macroscopic traffic simulation; on-demand meal delivery; collection and delivery points  \n1. Introduction  \nFreight transport has often been ignored in urban policies [1] . One reason given is the lack of quantitative knowledge [1], especially a lack of information about the flow of goods [2] . While macroscopic traffic simulations of urban passenger transport are common practice, macroscopic simulations considering urban goods transport are still comparatively few [3] . Studies combining macroscopic traffic and emission simulations are rare for freight transport. On the other hand, the literature on combined macroscopic traffic and emission simulations for passenger transport is extensive [4] . However, urban goods transport isone of the causes of air pollution in residential areas [5–7] and the city centre [8–10] . The concerns about air pollution are becoming increasingly newsworthy, especially in urban environments due to the adverse effects on human health. The pollution levels in many cities around the world are considered dangerous [11] . The effect of pollution caused by traffic is more severe compared with the pollution caused by industry due to the close proximity of people to the source of transport pollution [12] .  \nSchnieder et al. [13] have illustrated that the results of emission simulations are extremely sensitive to changing the simulation assumptions (e.g., road gradient, temperature, parking duration) or pollutants (e.g., CO2, PM 10 exhaust, PM10 non-exhaust, and Well-to-Wheel emissions) . The study presented in this paper adds to this narrative by highlighting the fact that delivery activities may also affect the emissions of other traffic within ","cbCaihiT4OrfUj6k","https://ap.wps.com/l/cbCaihiT4OrfUj6k","pdf",9140275,17,"English","# Introduction\n## Urban freight and air pollution context\n## Linking emissions to congestion and simulation assumptions","[{\"question\":\"Why is integrating last-mile delivery into macroscopic traffic simulations important?\",\"answer\":\"Because evaluating only the delivery service can ignore how delivery activities change city traffic flow, which directly affects emissions.\"},{\"question\":\"How does the study evaluate emissions for on-demand meal delivery?\",\"answer\":\"It compares two approaches in PTV VISUM: emission evaluation per OD-pair (each trip) and emission evaluation per network link (each street).\"},{\"question\":\"What traffic effects does the study highlight as consequences of on-demand meal delivery?\",\"answer\":\"It reports impacts on travelled distance (detours), congestion levels, and emissions per kilometer for every vehicle in the network, not only delivery vehicles.\"}]","Emission Estimation of On-Demand Meal Delivery Services - A Macroscopic Simulation | PDF",1790525170,43]