High Resolution On-Road Air Pollution Using a Large Taxi-Based Mobile Sensor Network

Traffic-related air pollution (TRAP) was monitored using a mobile sensor network on 125 urban taxis in Shanghai (November 2019/December 2020), which provide real-time patterns of air pollution at high spatial resolution. Each device determined concentrations of carbon monoxide (CO), nitrogen dioxide (NO₂), and PM_2.5, which characterised spatial and temporal patterns of on-road pollutants. A total of 80% road coverage (motorways, trunk, primary, and secondary roads) required 80-100 taxis, but only 25 on trunk roads. Higher CO concentrations were observed in the urban centre, NO₂ higher in motorway concentrations, and PM_2.5 lower in the west away from the city centre. During the COVID-19 lockdown, concentrations of CO, NO₂, and PM_2.5 in Shanghai decreased by 32, 31 and 41%, compared with the previous period. Local contribution related to traffic emissions changed slightly before and after COVID-19 restrictions, while changing background contributions relate to seasonal variation. Mobile networks are a real-time tool for air quality monitoring, with high spatial resolution (~200 m) and robust against the loss of individual devices.

Accident risk analysis based on motorway exposure: an application of benchmarking technique for human safety

Accident risk analysis for human safety and infrastructural improvement are key requirements of the engineering sector. The purpose of this paper is to identify and prioritize problematic segments of roads based upon the risk evaluation concept and to focus on the severity of accidents regarding human life loss and easy manoeuvring. This study includes the concept of considering road segments as decision-making units for application of data envelopment analysis (DEA) technique which has no compulsion of the distribution function and critical assumptions, unlike the multiple regression models. According to the proposed methodology, a section of Motorway (M-2) Lahore-Islamabad has been analyzed. Out of 200 segments under consideration, 99 segments were selected with at least one accident and one injury or fatality. Furthermore, for risk calculation and ranking of road segments, the DEA technique along with the cross-risk matrix method was applied. This optimization technique could not only be helpful in ranking but also technical decision-making and prioritizations for safety improvement, policymaking and budget allocation.