Vehicular PM Emissions and Urban Public Health Sustainability: A Probabilistic Analysis for Dhaka City

Abstract

Particulate Matter (PM) pollution is generally considered as a prime indicator of urban air quality and is linked to human health hazards. As vehicles are a vital component of an urban setting, the risks of particulate pollution need to be assessed. An emission modelling is essential for that, and thus stochastic modelling approach involving Monte Carlo simulation technique was applied, aiming to reduce the uncertainty in emission modelling. The risks scenarios for the emissions were generated for 2019 (present state) and 2024 (future), integrating the probability of emissions and the associated AQI (Air Quality Index). Despite the vehicles being a minor source of PM in Dhaka (compared to the contribution from other sources), about one-third of the city is found under high risk due to the exhaust particulate pollution; having the potentiality to cover more than 60% of the city in the coming years, affecting the urban public health sustainability. However, the extent of implementation of planning and management strategies can revert the scenarios for the city, which can plausibly reduce the risk from 80% to 50%, or even to a no-risk state.

Seasonal variations of microbes in particulate matter obtained from Dhaka City in Bangladesh

“…In all the sampling sites, the PM 10 levels were found to be higher than the limit set by the World Health Organization (WHO) guideline which is 50 μg/m 3 for a 24-h period and the Environmental Protection Agency (EPA) limit value which is 150 μg/m 3 for a 24-h period. The high particulate concentrations at the studied locations in Dhaka city may be attributed to biomass burning, brick kilns, diesel-powered and gasoline vehicles, industrial fossil fuel burning, and construction activities in and around the city [26,27]. The highest value recorded in Postogola was presumably due to the presence of higher industrial activities in the area which had already been declared as the metal area of Dhaka city.…”

Sources, Pattern, and Health Impacts of PM2.5 in the Central Region of Bangladesh using PMF, SOM, and Machine Learning Techniques

“…According to (Deters et al 2017), the air and water in the districts are becoming increasingly polluted because of increasing population, decreasing wetland and green spaces, rising multi-storied buildings, and growing commercial real estate developments. The areas also experience higher levels of traffic congestion, unplanned migration, and unplanned urban activities (Begum and Hopke 2019; Rahman et al 2019;Iqbal et al 2020). In addition, the study area also houses industries of ready-made garments, textiles, pharmaceuticals, cements, brickfields, fertilizers, and processing of raw material.…”

The Effect of COVID-19 Pandemic on Emitted PM2.5 in Urban Road Networks: Using Loop Data and Kriging Method for Passenger Cars in the Central Part of the City of Lodz

“…One way to address this issue is to consider the conditions of a certain study area and to define a logical scenario compatible with the available data. A plausible scenario that provides perspectives for planning and has been followed by several studies (e.g., Iqbal et al (2020)) is to model higher concentration values called the worst-case scenario. In this scenario, measurements are conducted based on the highest level of pollution generation rate.…”