Powerful Computer

Research & Initiatives

AQMEL research efforts include 4-D regional air pollution model development and applications, source apportionment, low-cost monitoring, personal exposure assessment, resilience planning, and environmental disparities mitigation. We welcome correspondence regarding potential collaborations, funding opportunities, or constructive feedback.

AQMEL Research Thrusts

Thrust 1: Human Interactions and Air Quality Disparities

Air pollution and air quality is does not impact all populations equally, and the disproportionate impacts are driven by political, economic, and social forces. We explore air pollution exposure disparities through the lenses of individual mobility [1], science communication, socioeconomics [2], and historical political structures [3]

[1] Do et al., JAS, 2021           

[2] Sasser, et al., JESEE, 2021

[3] Ivey, Nature, 2020           

Contributors: Riverside City College, University of California, Riverside, University of Central Florida

Sponsors: California Air Resources Board, Center for Social Innovation, Environmental Protection Agency, Social Science Research Council

Thrust 2: Air Quality and Meteorology

Air pollutant formation and persistence is highly influenced by anthropogenic emissions, as well as meteorological conditions. We investigate the impact of extreme meteorology on air quality in U.S. metropolitan areas that are susceptible to weather-exacerbated air pollution  episodes [4-6].

[4] Gao et al., Env Poll, 2022

[5] Ivey et al., ChemRxiv, 2020

[6] Ivey et al., Atm Env, 2019  

Contributors: Envair, Georgia Institute of Technology, University of Utah

Sponsors: National Institute of Environmental Health Sciences, South Coast Air Quality Management District

Thrust 3: Sustainable Mobility and Air Quality

As part of multiple synergistic activities with transportation and mobility experts, we leverage state-of-the-science traffic metrics to detrend and analyze ambient air pollution drivers. This research is critical for future human and goods movement planning for highly populated urban centers [7].

[7] Tanvir et al., 2022

Contributors: Cal Poly San Luis Obispo, Center for Environmental Research and Technology

Sponsors: National Center for Sustainable Transportation, University of California Institute of Transportation Studies

Thrust 4: Computational Methods

As part of our fundamental modeling research, we explore the power of advanced computational methods and predictive algorithms to improve the speed and accuracy of large-scale air pollution predictions.

Contributors: University of California, Riverside; George Delic, Hiperism Consulting

Sponsors: National Science Foundation

Individual Exposures
Extreme ozone
Diurnal Pollution
Regression Tree
Computer Programming