Effect of Vehicular Electrification on Transportation Emissions in Florida
type: CreativeWork
description: Vehicular emissions from fuel-based passenger cars emit an array of gases and particles that are detrimental for human health and the environment. In that regard, electric vehicles (EVs) present a viable, sustainable solution. This study investigated the impact of electrification of passenger cars on air quality in Florida, in five major urban counties namely Miami-Dade, Duval, Hillsborough, Orange, and Leon. Between 2018 and 2022, these counties experienced a significant increase of 219.50 ± 52.32% in EV adoption, coupled with a 11.55 ± 6.13% decrease in fuel-based vehicle usage. Herein, we characterize five pollutants primarily generated from fuel-based passenger vehicles- carbon monoxide (CO), nitrogen dioxide (NO2), particulate matter (PM2.5 and PM10), and carbon dioxide (CO2)- over a five-year period (2018 – 2022). Hourly traffic data counts and their corresponding emissions were analyzed using the U.S. Environmental Protection Agency’s (EPA) MOtor Vehicle Emission Simulator (MOVES) software using the county scale. The shift from fuel-based vehicles to EVs has led to significant reductions in emissions across the five counties. By comparing data in 2022 to 2018, average reductions of 21.96 ± 21.43 %, 14.73 ± 14.98 %, 43.38 ± 43.66 %, 43.19 ± 43.52 %, and 11.19 ± 12.72 % were observed for CO, CO2, NO2, PM2.5, and PM10, respectively. Generally, Leon County (located in northern Florida and home for the state’s capital) experienced the highest reduction followed by Miami-Dade County (located in southern Florida), likely due to their high population densities. A Random Forest (RF) Regression model was developed to forecast future population and emissions in 2025, 2035 and 2050. The forecasted data were then adjusted based on EV adoption scenarios aligned with Paris Agreement recommendations and U.S. projections (25% EV adoption by 2025, 80% by 2035, and 100% by 2050). By comparing predicted values with the adjusted emissions based on the EV adoption scenarios, avera…
abstract: Vehicular emissions from fuel-based passenger cars emit an array of gases and particles that are detrimental for human health and the environment. In that regard, electric vehicles (EVs) present a viable, sustainable solution. This study investigated the impact of electrification of passenger cars on air quality in Florida, in five major urban counties namely Miami-Dade, Duval, Hillsborough, Orange, and Leon. Between 2018 and 2022, these counties experienced a significant increase of 219.50 ± 52.32% in EV adoption, coupled with a 11.55 ± 6.13% decrease in fuel-based vehicle usage. Herein, we characterize five pollutants primarily generated from fuel-based passenger vehicles- carbon monoxide (CO), nitrogen dioxide (NO2), particulate matter (PM2.5 and PM10), and carbon dioxide (CO2)- over a five-year period (2018 – 2022). Hourly traffic data counts and their corresponding emissions were analyzed using the U.S. Environmental Protection Agency’s (EPA) MOtor Vehicle Emission Simulator (MOVES) software using the county scale. The shift from fuel-based vehicles to EVs has led to significant reductions in emissions across the five counties. By comparing data in 2022 to 2018, average reductions of 21.96 ± 21.43 %, 14.73 ± 14.98 %, 43.38 ± 43.66 %, 43.19 ± 43.52 %, and 11.19 ± 12.72 % were observed for CO, CO2, NO2, PM2.5, and PM10, respectively. Generally, Leon County (located in northern Florida and home for the state’s capital) experienced the highest reduction followed by Miami-Dade County (located in southern Florida), likely due to their high population densities. A Random Forest (RF) Regression model was developed to forecast future population and emissions in 2025, 2035 and 2050. The forecasted data were then adjusted based on EV adoption scenarios aligned with Paris Agreement recommendations and U.S. projections (25% EV adoption by 2025, 80% by 2035, and 100% by 2050). By comparing predicted values with the adjusted emissions based on the EV adoption scenarios, avera…
author: Sapkota Dhakal, Shreya
keywords: electric vehicles (EVs), vehicular emissions, criteria pollutants, greenhouse gases (GHGs), air quality, MOVES, machine learning, Heidi SQL, sustainability, UN Sustainable Development Goals (SDGs), Paris Agreement and US projection., Environmental Engineering, Transportation Engineering
date published: 2025-07-01T07:00:00Z
date modified: 2026-07-27T19:26:16Z
provider: Embry Riddle Aeronautical University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Embry Riddle Aeronautical University