Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO2 and PM2.5 Pollution in Urban Areas

Abstract

To evaluate the effectiveness of alternative policies and measures to reduce air pollution effects on urban citizen’s health, population exposure assessments are needed. Due to road traffic emissions being a major source of emissions and exposure in European cities, it is necessary to account for differentiated transport environments in population dynamics for exposure studies. In this study, we applied a modelling system to evaluate population exposure in the urban area of Hamburg in 2016. The modeling system consists of an urban-scale chemistry transport model to account for ambient air pollutant concentrations and a dynamic time-microenvironment-activity (TMA) approach, which accounts for population dynamics in different environments as well as for infiltration of outdoor to indoor air pollution. We integrated different modes of transport in the TMA approach to improve population exposure assessments in transport environments. The newly developed approach reports 12% more total exposure to NO2 and 19% more to PM2.5 compared with exposure estimates based on residential addresses. During the time people spend in different transport environments, the in-car environment contributes with 40% and 33% to the annual sum of exposure to NO2 and PM2.5, in the walking environment with 26% and 30%, in the cycling environment with 15% and 17% and other environments (buses, subway, suburban, and regional trains) with less than 10% respectively. The relative contribution of road traffic emissions to population exposure is highest in the in-car environment (57% for NO2 and 15% for PM2.5). Results for population-weighted exposure revealed exposure to PM2.5 concentrations above the WHO AQG limit value in the cycling environment. Uncertainties for the exposure contributions arising from emissions and infiltration from outdoor to indoor pollutant concentrations range from −12% to +7% for NO2 and PM2.5. The developed “dynamic transport approach” is integrated in a computationally efficient exposure model, which is generally applicable in European urban areas. The presented methodology is promoted for use in urban mobility planning, e.g., to investigate on policy-driven changes in modal split and their combined effect on emissions, population activity and population exposure.

Integrating in situ Measurements and City Scale Modelling to Assess the COVID–19 Lockdown Effects on Emissions and Air Quality in Athens, Greece

“…In this study, the meteorological component of TAPM was used to perform nested simulations with 4 domains centered at 38 • 2 N, 23 • 43 E, with a horizontal grid spacing of 12 km (parent domain), 4 km, 3 km and 1 km (innermost domain) and a common vertical structure of 30 terrain-following layers (first layer at 10 m, vertical top height at 8 km). Urban area (with the same horizontal resolution), line and point source emissions were produced by a newly developed disaggregation algorithm, successfully tested in Athens [57] and Hamburg (Germany) [58]. The algorithm exploits the regional CAMS-REG-AP emission inventory, re-griding it using contemporary, high-resolution spatial proxies, suitable for each source type and sector.…”

The UrbEm Hybrid Method to Derive High-Resolution Emissions for City-Scale Air Quality Modeling

“…3 solely for the Berlin urban area and NO X , we apply this factor as a default factor to increase road traffic emissions for all pollutants in any European urban center before downscaling regional road traffic emissions to the urban scale. This approach was used by Ramacher and Karl [29] in the city of Hamburg and resulted in good agreements with measured values of NO X , PM 10 , and PM 2.5 . Nevertheless, the default correction factor is very likely to vary from city to city and especially for each pollutant, which is why there is a simple option to adjust the factor in the UrbEm approach software application.…”

“…For both NO 2 and PM 2.5 , it is expectable that the concentrations peaks are in the city center and the port area, which is additionally a hotspot for industrial activities. For further discussion of air pollutant concentration for Hamburg in 2016 as derived from emissions downscaled with an early version of the UrbEm, we refer to Ramacher and Karl (2020) [29].…”

COVID-19 and air pollution: the worst is yet to come

“…In addition to the probable increase in air pollution to fight against the 2-month lockdown in relation to the economy, individual behavior will also increase air pollution. Fearing the contagion in mass transit, people are more frequently using their individual cars for commuting (Smargiassi et al 2020)-taking into account that traffic involves around 70% of air pollutants in urban areas (Ramacher and Karl 2020). There is also a noticeable upsurge in the use of disposable plastic, in line with mass media disseminating the survival of SARS-Cov-2 on inert surfaces (Otter et al 2016).…”