Analysis of in-vehicle air quality and load factor as environmental and social dimensions of sustainable urban mobility: A case study from Kathmandu valley, Nepal

Pooja Bhusal; Suman Man Shrestha; Narayan Babu Dhital; Gauri Shankar Bhandari; Bhupendra Das; Rishav Pandit

doi:10.18502/japh.v9i1.15078

Pooja Bhusal Central Department of Environmental Science, Tribhuvan University, Kathmandu, Nepal
Suman Man Shrestha Central Department of Environmental Science, Tribhuvan University, Kathmandu, Nepal
Narayan Babu Dhital Patan Multiple Campus,Tribhuvan University, Kathmandu, Nepal
Gauri Shankar Bhandari Resources Himalaya Foundation, Naya bato, Lalitpur, Nepal
Bhupendra Das Nepal Energy and Environment Development Services (NEEDS), Lalitpur, Nepal
Rishav Pandit Institute of Agriculture and Animal Science, Tribhuvan University, Kathmandu, Nepal

DOI: https://doi.org/10.18502/japh.v9i1.15078

Keywords: In-vehicle air quality; Particulate matter (PM); Carbon dioxide (Co ); Sustainable, urban mobility

Abstract

Introduction: Assessing in-vehicle air pollution and load factor is crucial in developing countries like Nepal within the environmental and social aspects of sustainable urban mobility.

Materials and methods: In this study in-vehicle air quality of public vehicles in Kathmandu valley was monitored for three road sections based on vehicle density i.e. Ring Road Section (RRS), Urban Commercial Route 1 (UCR1), and Urban Commercial Route 2 (UCR2) using Air Visual Pro N1 Model for which validationand was done with reference Particulate Matter (PM) values obtained from the GRIMM EDM 180 analyzer. The quantitative count method was used to sample passenger load. Particulate Matter (PM1, PM2.5, PM10) were monitored along with indoor-outdoor ratio for PM2.5 to know therelationship between indoor and outdoor air quality

Results: A higher positive correlation between PM 2.5 and PM10 showed common sources of pollution such as road dust, and vehicle exhaust and a ratio study between them showed the dominance of coarser particles in both ambient and in-vehicle environments. RRS recorded the highest PM₁₀ and PM2.5 exposure, possibly due to the inadequate road conditions from Kalanki to Gongabu and loose sediment deposition from roadside activities. A significant difference is observed for peak and non-peak hours due to the difference in mobility of vehicles on two different hours. Higher load factors on UCR1 and UCR2 showed the higher transportation demand on urban commercial sections for both weekdays and weekends in comparison to RRS.

Conclusion: Both in-vehicle air quality and load factor for sections under study were not satisfactory and cannot be counted under sustainable urban mobility practices.