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Predicting cardiometabolic health and air pollution in future transportation landscapes using agent-based models
This project will assess the impacts of future urban transportation landscapes on cardiometabolic health through novel exposure estimation together with air quality modeling of traffic-related air pollution (TRAP). Exposures will be associated with markers of cardiovascular diseases using an existing population-based cohort in Augsburg, Germany. Findings will be then scaled up to the whole study area population (Munich metropolitan area), and eventually all of Germany. Various transportation scenarios will be evaluated, such as those related to transport infrastructure, technological advancements, and pricing policies.
Background and objectives:
Ambient air pollution is among the top five risk factors for the global disease burden, with compelling evidence linking fine particulate matter (PM2.5) to various health issues.. Particles from mobile sources (traffic-related air pollution, TRAP) are strongly linked to cardiometabolic disease exacerbation, likely due to their small size (mostly in the ultrafine range below 100 nm) and chemical composition (e.g., trace metal, black carbon). However, our understanding of the effects of non-tailpipe emissions (brake and tire wear) is still inconclusive. Additionally, the impacts of future changes in the transportation landscape on cardiometabolic health are understudied.
Methods and approach:
We develop an advanced exposure model from a combination of comprehensive urban-scale air quality modeling using the Parallelized Large-Eddy Simulation Model (PALM) with a representation of human activity using the Multi-Agent Transport Simulation (MATsim) agent-based model. This exposure model is linked to strong epidemiological evidence, allowing us to use an existing population cohort (Cooperative Health Research in the Region of Augsburg, KORA) to estimate individual health effects, focusing on clinical and subclinical markers of cardiometabolic disease. Personal Exposure Monitors (PEMs) are used, amongst other sources, for model evaluation.
Results and findings:
We detail a mobility questionnaire recently administered to the KORA cohort participants. The use and calibration of PEMs is outlined. Additionally, we present the setup and configuration of the PALM model for Augsburg and its surroundings. The methods to link traffic emissions from agent-based estimates with air quality modeling are presented. Furthermore, we discuss how we link agent-based model results with evidence from the KORA cohort.
Conclusions and interpretation:
Research within the TRANSCAPE project has started, and first results are presented here. Gathering ground truth from the KORA cohort is ongoing. Model setups are converging, and integration has begun.
