The general framework of the bottom-up approach for modeling mobile emissions and energy use involves the following major components: (1) quantifying traffic flow and (2) calculating emission and energy consumption factors. In most cases, researchers deal with complex and arduous tasks, especially when conducting actual surveys in order to calculate traffic flow. In this regard, the authors are introducing a novel method in estimating mobile emissions and energy use from road traffic flow utilizing crowdsourced data from Google Maps. The method was applied on a major highway in the Philippines commonly known as EDSA. Results showed that a total of 370,855 vehicles traveled along EDSA on average per day in June 2019. In comparison to a government survey, only an 8.63% error was found with respect to the total vehicle count. However, the approximation error can be further reduced to 4.63% if cars and utility vehicles are combined into one vehicle category. The study concludes by providing the limitations and opportunities for future work of the proposed methodology.
Continuous measurements of transport emissions are considered key issues for air pollution management in the transportation sector. In some instances, researchers may come across difficulties in doing transport emissions modeling such as overcomplexities and laborious methodologies. In this regard, the authors are introducing a novel method of doing a transport emissions modeling by utilizing Google Maps data. By getting the average travel time of a road segment and the corresponding length, the average speed can be obtained. This speed will be used to identify the flow of vehicles in terms of Passenger Car Unit (PCU) through a speed-flow curve on the basis of a Roadside Frictions Index (RSFI). PCU percentages are derived from the actual counting of vehicles using the street view features of Google Maps. Once the PCU count and the PCU percentages are established, the actual number of vehicle flow per type can now be determined. Consequently, emissions loads are calculated by multiplying the vehicle flow and road length to emissions factors derived from reliable sources.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.