Fossil fuel vehicles, emitting air toxics into the atmosphere, impose a heavy burden on the economy through additional health care expenses and ecological degradation. Air pollution is responsible for millions of deaths and chronic and acute health problems every year, such as asthma and chronic obstructive pulmonary disease. The fossil-fuel-based transportation system releases tons of toxic gases into the atmosphere putting human health at risk, especially in urban areas. This analysis aims to determine the economic burden of environmental and health impacts caused by Highway 401 traffic. Due to the high volume of vehicles driving on the Toronto Highway 401 corridor, there is an annual release of 3771 tonnes of carbon dioxide equivalent (CO₂e). These emissions are mainly emitted onsite through the combustion of gasoline and diesel fuel. The integration of electric and hydrogen vehicles shows maximum reductions of 405–476 g CO₂e per vehicle-kilometer. Besides these carbon dioxide emissions, there is also a large amount of hazardous air pollutants. To examine the impact of air pollution on human health, the mass and concentrations of criteria pollutants of PM_2.5 and NO_x emitted by passenger vehicles and commercial trucks on Highway 401 were determined using the MOVES2014b software. Then, an air dispersion model (AERMOD) was used to find the concentration of different pollutants at the receptor’s location. The increased risk of health issues was calculated using hazard ratios from literature. Finally, the health cost of air pollution from Highway 401 traffic was estimated to be CAD 416 million per year using the value of statistical life, which is significantly higher than the climate change costs of CAD 55 million per year due to air pollution.

This study presents a new method that incorporates modern air dispersion models allowing local terrain and land–sea breeze effects to be considered along with political and natural boundaries for more accurate mapping of air quality zones (AQZs) for coastal urban centers. This method uses local coastal wind patterns and key urban air pollution sources in each zone to more accurately calculate air pollutant concentration statistics. The new approach distributes virtual air pollution sources within each small grid cell of an area of interest and analyzes a puff dispersion model for a full year’s worth of 1-hr prognostic weather data. The difference of wind patterns in coastal and inland areas creates significantly different skewness (S) and kurtosis (K) statistics for the annually averaged pollutant concentrations at ground level receptor points for each grid cell. Plotting the S-K data highlights grouping of sources predominantly impacted by coastal winds versus inland winds. The application of the new method is demonstrated through a case study for the nation of Kuwait by developing new AQZs to support local air management programs. The zone boundaries established by the S-K method were validated by comparing MM5 and WRF prognostic meteorological weather data used in the air dispersion modeling, a support vector machine classifier was trained to compare results with the graphical classification method, and final zones were compared with data collected from Earth observation satellites to confirm locations of high-exposure-risk areas. The resulting AQZs are more accurate and support efficient management strategies for air quality compliance targets effected by local coastal microclimates. Implications: A novel method to determine air quality zones in coastal urban areas is introduced using skewness (S) and kurtosis (K) statistics calculated from grid concentrations results of air dispersion models. The method identifies land–sea breeze effects that can be used to manage local air quality in areas of similar microclimates.

Air toxic emissions from on-road mobile sources are significant contributors to the degradation of air quality in urban and dense population centers. Research led by the United States Environmental Protection Agency (EPA) identified more than 1162 hazardous air pollutants (HAPs) in the exhaust and evaporative emissions from on-road mobile sources. However, less than 70 hazardous air pollutants are monitored by regulatory agencies. HAPs emitted from Mobile Sources are known as Mobile Source Air Toxics (MSATs). The EPA estimates that approximately half of the cancer risk and 74% of noncancer health impacts from air toxics is attributed to mobile sources. The quantification of the risk associated with MSATs exposure remains limited to date, and only a few MSATs have ambient air quality standards to protect human health and welfare. This work presents a novel and validated methodology to quantify the myriad health risks associated with exposure to on-road mobile emissions. This methodology is introduced in the form of a pipelined analysis process, which may be employed in existing and new transportation projects. The proposed new methodology integrates results from three different types of models: on-road vehicle emissions inventory models such as MOVES and IVE, air dispersion models such as AERMOD and SCIPUFF, and risk estimate models for human and ecological receptors such as the 2005 Final U.S. EPA Human Health Risk Assessment Protocol for Hazardous Waste Combustion Facilities. The result of this research work is a new methodology that provides regulators and risk analysts with a more detailed awareness of the health impacts of MSATs. A case study of Saint Paul, Minnesota, validated the air dispersion modeled results against monitored data, and the agreement was acceptable (i.e., the estimates were within a factor of two of the observations). Three high-population locations in the Saint Paul area were evaluated for human health risk, with the observation that at two of these locations, the Saint Paul—Ramsey Health Center and Anderson Office Building, the calculated cancer risk is in excess of the target risk level of 1.0E-05 for benzo(a)pyrene. The methodology presented in this paper allows regulators, risk analysts, and air quality engineers to better estimate multi-pathway cancer and noncancer risk associated with acute and chronic exposure to MSATs. Moreover, this work provides a science-based aid to policy decision makers when considering factors that most significantly affect population health and ecology.

Air pollution has emerged as a pressing global issue in recent decades. While criteria pollutants and greenhouse gases contribute to the problem, this article explicitly addresses hazardous air pollutants (HAPs). This work estimates the country-wide cumulative human health impacts from exposure to HAPs. Kuwait is used as the case study due to data availability and non-fragmentation of data. At present, the evaluation of multi-pathway human health risks arising from exposure to HAPs is incomplete, as indirect pathways have not been considered. Furthermore, only a few HAPs, such as benzene, have established ambient air quality standards specifically intended to safeguard human health, leaving many HAPs unregulated. This study considers several pathways (both direct and indirect) and various environmental media (air, water, plants, soil, and animal tissue). The findings indicate that cumulative health risks in the coastal air quality zone are within acceptable limits but are notably higher when compared to the other air quality zones. For cancer risks, only the Ahmadi Hospital, with a cancer risk of 1.09 × 10⁻⁵ for the resident adult exposure scenario, slightly exceeds the acceptable risk level of 1 × 10⁻⁵. The proposed methodology integrates the results from a country-wide emissions inventory composed of different air quality zones, air dispersion and deposition modeling, multi-pathway transport-and-fate analysis, exposure quantification, and health risk and hazard characterization. It also extends and adapts EPA methodologies initially designed for hazardous waste combustion facilities to additional emission sources and provides a case study for a region seldom subjected to such human health risk assessments.

Mobile source air toxics (MSATs) are major contributors to urban air pollution, especially near high-traffic roadways, where populations face elevated pollutant exposures. Traditional human health risk assessments, based on deterministic methods, often overlook variability in exposure and the vulnerabilities of sensitive subpopulations. This study introduces and applies a new stochastic modeling approach, utilizing Monte Carlo simulations to evaluate cumulative cancer risks from MSATs exposure through inhalation and ingestion pathways. This method captures variability in exposure scenarios, providing detailed health risk assessments, particularly for vulnerable groups such as children and the elderly. This approach was demonstrated in a case study conducted in Saint Paul, Minnesota, using 2019 traffic data. Deterministic models estimated cumulative cancer risks for adults at 6.24E-02 (unitless lifetime cancer risk), while stochastic modeling revealed a broader range, with the 95th percentile reaching 4.98E-02. The 95th percentile, used in regulatory evaluations, identifies high-risk scenarios overlooked by deterministic methods. This research advances the understanding of MSATs exposure risks by integrating spatiotemporal dynamics, identifying high-risk zones and vulnerable subpopulations, and supporting resource allocation for targeted pollution control measures. Future applications of this methodology include expanding stochastic modeling to evaluate ecological risks from mobile emissions.

Amid the growing concerns about air toxics from pollution sources, much emphasis has been placed on their impacts on human health. However, there has been limited research conducted to assess the cumulative country-wide impact of air toxics on both terrestrial and aquatic ecosystems, as well as the complex interactions within food webs. Traditional approaches, including those of the United States Environmental Protection Agency (US EPA), lack versatility in addressing diverse emission sources and their distinct ecological repercussions. This study addresses these gaps by introducing the Ecological Health Assessment Methodology (EHAM), a novel approach that transcends traditional methods by enabling both comprehensive country-wide and detailed regional ecological risk assessments across terrestrial and aquatic ecosystems. EHAM also advances the field by developing new food-chain multipliers (magnification factors) for localized ecosystem food web models. Employing traditional ecological multimedia risk assessment of toxics’ fate and transport techniques as its foundation, this study extends US EPA methodologies to a broader range of emission sources. The quantification of risk estimation employs the quotient method, which yields an ecological screening quotient (ESQ). Utilizing Kuwait as a case study for the application of this methodology, this study’s findings for data from 2017 indicate a substantial ecological risk in Kuwait’s coastal zone, with cumulative ESQ values reaching as high as 3.12 × 10³ for carnivorous shorebirds, contrasted by negligible risks in the inland and production zones, where ESQ values for all groups are consistently below 1.0. By analyzing the toxicity reference value (TRV) against the expected daily exposure of receptors to air toxics, the proposed methodology provides valuable insights into the potential ecological risks and their subsequent impacts on ecological populations. The present contribution aims to deepen the understanding of the ecological health implications of air toxics and lay the foundation for informed, ecology-driven policymaking, underscoring the need for measures to mitigate these impacts.