Tackling air pollution inequalities through integrated assessment models: a pathway to environmental justice

INTRODUCTION

Air pollution remains a critical challenge in urban environments, as it exacerbates health inequities and disproportionately affects marginalized communities. Although Integrated Assessment Models (IAMs) have advanced in recent years, they still struggle to capture the urban and social dimensions of air quality. This research addresses that gap by integrating detailed spatiotemporal and socio-economic data into an urban-scale modeling platform. The aim is to highlight pollution-driven disparities and guide policies that foster environmental justice.

 

METHODS

This work relies on an integrated modeling approach centered on the OLYMPUS model (Elessa Etuman et al., 2018, 2023), designed to simulate urban air pollution exposure at high resolution and evaluate associated socio-environmental impacts.

 

First, demographic data from large-scale surveys are used to build a synthetic population, reflecting socio-economic and spatial heterogeneities. Next, transportation patterns—including both passenger and freight—are derived through mobility matrices that combine national surveys with FRETURB-SIMTURB modeling. These results inform the energy demand assessment, which accounts for building use and daily schedules to estimate sector-specific energy consumption.

 

Using these outputs, an emissions inventory is established following European Environment Agency standards, with refined spatial and temporal allocation achieved through advanced statistical scaling techniques. The CHIMERE model (Menut et al., 2013) then simulates air quality at neighborhood scale. Finally, a detailed exposure assessment links emissions data to individuals by merging high-resolution pollution maps with daily mobility patterns and demographic profiles. This step identifies vulnerable subpopulations based on socio-economic status, residential location, and travel habits.

 

RESULTS

By pinpointing the underlying drivers of air pollution inequalities, this study underscores the need for urban policies that explicitly consider social diversity and personal habits. Drawing on integrated modeling results, we see that targeted interventions—such as improving access to clean public transport, restructuring mobility habits —can lower exposure risks. These strategies become most powerful when they address the specific needs of vulnerable populations, thereby reducing environmental health disparities.

 

CONCLUSIONS

Addressing air pollution inequalities is vital for achieving environmental justice and sustainable urban development. By incorporating socio-economic and spatial heterogeneities into a comprehensive modeling framework, this research demonstrates that policies shaped around individuals’ real-world practices offer the most promising path to fairer and more effective outcomes. Ensuring that each policy is designed to both reduce overall pollution and narrow social gaps will help advance healthier, more equitable urban environments.

 

REFERENCES

Benoussaïd, T., 2023. Analyse socio-spatiale de l’exposition des populations à la pollution atmosphérique en zone urbaine, par une approche de modélisation dynamique basée sur l’individu et intégrant les pratiques de mobilité.

Elessa Etuman, A., Coll, I., 2018. OLYMPUS v1.0: Development of an integrated air pollutant and GHG urban emissions model - Methodology and calibration over the greater Paris. Geoscientific Model Development Discussions, 1‑29. 

Elessa Etuman, A., Coll, I. 2023. Integrated air quality modeling for urban policy: A novel approach with OLYMPUS-CHIMERE. Atmospheric Environment, 315: 120134.

Menut, L., et al. 2013. CHIMERE 2013: a model for regional atmospheric composition modelling. Geosci. Model Dev., 6(4): 981‑1028.