RESUMEN
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.
RESUMEN
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.
