Table of Contents
Trapodiso
Project Context
This project proposes the integration of three advanced systems — POLARIS, Autonomie, and AERMOD — with the objective of evaluating and mitigating the impacts of air pollutant emissions generated by urban traffic. The approach goes beyond static pollution analysis: it aims to optimize the urban road network based on dynamic vehicular emission data and high-resolution environmental simulations.
General Objective
To develop an integrated platform that enables:
- Simulating urban traffic behavior under various scenarios (using POLARIS);
- Estimating pollutant emissions based on realistic vehicle operation (using Autonomie);
- Modeling the atmospheric dispersion of these emissions (using AERMOD);
- Proposing interventions and road network optimizations based on both environmental and operational results.
System Components
- POLARIS (Planning and Operations Language for Agent-based Regional Integrated Simulation)
A traffic simulation platform based on agent behavior, developed by Argonne National Laboratory. It models urban traffic flows with high granularity, allowing for detailed representation of individual mobility within complex networks.
- Autonomie
A vehicle and energy simulation software that accurately calculates fuel consumption and emissions based on real driving profiles generated by POLARIS. Widely used in energy efficiency research and powertrain development.
- AERMOD (American Meteorological Society/Environmental Protection Agency Regulatory Model)
The regulatory atmospheric dispersion model from the U.S. EPA, which uses meteorological data and terrain characteristics to simulate the spread of air pollutants, identifying areas with higher concentrations and environmental impact.
Integration Strategy
| Stage | Description | Tool | Output |
|---|---|---|---|
| 1 | Urban traffic simulation | POLARIS | Trajectory data, speed, and stop time by road segment |
| 2 | Conversion into vehicle operating profiles and emissions estimation | Autonomie | Specific pollutant estimates (NOₓ, CO₂, PM) |
| 3 | Preparation of data for dispersion modeling | AERMOD | Emission sources as linear/area features in critical zones |
| 4 | Atmospheric dispersion simulation | AERMOD | Dispersion modeling considering meteorology and topography |
| 5 | Impact evaluation and optimization | AERPLOT | Road network optimization proposals (traffic flow, restrictions, low-emission zones) |
In Figure 1, the integration flowchart is illustrated:
Figure 1
Figure 1: Integration flowchart.
Expected Outcomes
- Identification of urban zones with the highest pollutant concentration levels.
- Quantification of the contribution of vehicular traffic to air pollution by road type, time of day, and volume.
- Generation of technical input for sustainable urban mobility policy-making.
- Road reconfiguration proposals that simultaneously reduce congestion and atmospheric emissions.
Potential Applications
- Integrated urban and environmental planning.
- Evaluation of scenarios with electric or hybrid vehicles.
- Definition of zero-emission zones.
- Support for impact modeling in urban environmental licensing studies.