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Agent-Based Modeling to Estimate Exposure to Urban Air Pollution from Transportation to Assess Carcinogenic Effect

Doraki, Mohammad Erfan | 2024

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 57469 (46)
  4. University: Sharif University of Technology
  5. Department: Energy Engineering
  6. Advisor(s): Avami, Akram; Boroushaki, Mehrdad; Nahvijou, Azin
  7. Abstract:
  8. Air pollution in major cities has been a concern for over half a century, but its impact on public health has grown significantly in recent years, causing severe physical, mental, and financial harm. This project aims to propose effective policies to mitigate air pollution by focusing on the transportation sector. Transportation demand is analyzed through four scenarios, each addressing changes in public transportation usage, the promotion of cycling and walking culture, the penetration of digital solutions, and flexible working hours. The project, using the Huvaal model, forecasts transportation demand in 2050 under various population and climate conditions, based on artificial population modeling and key factor analysis. The findings suggest that enhancing cycling infrastructure and expanding public transport services could reduce reliance on private vehicles by 46%, while flexible working hours could lower peak traffic congestion by 47%. Data-driven modeling was employed to identify the factors influencing air pollution, considering both annual and daily time windows. The future air quality was then projected under the four transportation scenarios for 2050. Results indicate that, in the best-case scenario, O3 levels could decrease by 0.37 units, and PM2.5 by 3.71 units, whereas in the worst-case scenario, O3 could increase by 0.83 units, and PM2.5 by 8.65 units annually. The health impacts of these outcomes were assessed using relative risk and incidence ratio indices. The study concludes that with targeted policies, enhanced digital infrastructure, and optimized public transportation, it is not only possible to prevent further air quality degradation in Tehran but also to improve it. This would significantly reduce health risks, including a 12% decrease in lung cancer risk and a 6% reduction in bladder cancer risk
  9. Keywords:
  10. Agent Based Modeling ; Air Pollution ; Synthetic Population ; Tehran Transportation Network ; Urban Traffic ; Air Quality ; Public Transport

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