Country-Wide Ecological Health Assessment Methodology for Air Toxics: Bridging Gaps in Ecosystem Impact Understanding and Policy Foundations
Abstract
:1. Introduction
Literature Review, Objectives, and Additional Contributions
Additional Contributions
- Developing unique food web models tailored to local ecosystems to achieve a country-wide ecological risk assessment. These models incorporate region-specific trophic interactions, allowing for a more accurate and localized risk assessment;
- Extending US EPA methodologies originally created for hazardous waste combustion facilities to include other emission sources like wastewater treatment plants and glycol dehydration units;
- Estimating the country-wide cumulative ecological risk from simultaneous exposure to numerous air toxics such as polycyclic aromatic hydrocarbons originating from multiple industrial sources.
2. Materials and Methods
- (1)
- Develop a country-wide emissions inventory by identifying and quantifying the sources of air toxics;
- (2)
- Perform air dispersion and deposition modeling using current US regulatory models. This step aims to estimate the atmospheric pollutant concentrations and their annual deposition rates, focusing on habitat-specific scenario locations within the defined project area (e.g., country);
- (3)
- Characterize exposure settings for affected habitats within the project area;
- (4)
- Develop habitat-specific food webs based on exposure data and receptor interactions;
- (5)
- Select assessment endpoints within each trophic level of the habitat-specific food web;
- (6)
- Identify measurement receptors to assess air-toxics-related measures of effect, such as toxicity values or receptor-specific chronic no-observed-adverse-effect levels (NOAELs);
- (7)
- Assess exposure via direct uptake and ingestion, targeting both lower- and higher-trophic-level receptors based on their interaction with air toxics;
- (8)
- Evaluate the toxicity of air toxics by identifying toxicity reference values;
- (9)
- Estimate the country-wide cumulative ecological risk from simultaneous exposure to numerous air toxics from multiple industrial sources.
2.1. Emissions Inventory
2.2. Air Dispersion and Deposition Modeling
2.3. Exposure Setting Characterization
2.4. Habitat-Specific Food Web Development
- Within a habitat, potential receptors are identified and grouped based on their feeding habits or guilds;
- The food web structure is organized by trophic levels, such as plants and primary consumers (herbivores);
- An important component involves delineating the feeding relationships among distinct guilds and communities.
2.5. Habitat-Specific Trophic Level Assessment Endpoint Selection
2.6. Measurement Receptor Identification for Measures of Effect Assessment
2.7. Trophic-Level-Specific Exposure Assessment for Air Toxics
2.7.1. Daily Dose (DD) of Air Toxics Ingested by a Measurement Receptor
2.7.2. Bioconcentration Factor (BCF)
2.7.3. Food-Chain Multiplier (FCM)
2.8. Toxicity Assessment for Air Toxics
2.9. Ecological Risk Characterization
3. Analysis of Results
3.1. Case Study
Food Web Models
3.2. Cumulative Risk Results
3.2.1. Coastal Air Quality Zone
3.2.2. Inland Air Quality Zone
3.2.3. Production Air Quality Zone
3.3. Ecological Risk Driver Analysis
3.4. Assumptions and Limitations of EHAM in the Kuwait Case Study
- (1)
- Bioavailability of Air Toxics: This study presumes that air toxics in food items and environmental media are fully bioavailable to ecological receptors. “Bioavailable” here means the fraction of a substance that is readily absorbed and can influence biological processes;
- (2)
- Presence of Sensitive Life Stages: This study assumes that the most sensitive life stages of measurement receptors are present within the assessment area, resulting in a more protective ecological health risk assessment;
- (3)
- Conservative Estimates: This study utilizes conservative estimates for body weights and food ingestion rates of measurement receptors;
- (4)
- Equal Exposure Across Species: This study operates under the assumption that each species within any given ecological guild or community is equally exposed to the air toxics;
- (5)
- Contaminated Food and Media: This study assumes that 100 percent of the food items and media ingested by receptors are contaminated, implying exclusive feeding within the assessment area;
- (6)
- Cross-Interaction of Air Toxics: The current assessment assumes independent effects of each air toxic, without considering potential cross-interactions, such as synergistic, antagonistic, or additive effects, that might occur when multiple pollutants coexist.
4. Conclusions
- (1)
- Substantial Ecological Risk in the Coastal Zone: This study demonstrates significant ecological risks in Kuwait’s coastal zone, particularly for carnivorous birds, with cumulative ESQ values reaching 3.12 × 103. This highlights the substantial impact of air toxics in this ecologically sensitive area, driven largely by the process of biomagnification;
- (2)
- Negligible Risks in the Inland and Production Zones: In contrast, both the inland and production air quality zones exhibit negligible ecological risks, as indicated by the consistently low ESQ values across various species. This suggests the effective control of air toxics levels in these zones, protecting the ecological health of diverse species;
- (3)
- Benzo(a)pyrene as a Primary Ecological Risk Driver: Similar to findings in human health risk, benzo(a)pyrene is identified as a key risk driver in the coastal zone, due to its high bioconcentration factors and potential for bioaccumulation, underlining its significant ecological threat. This analysis highlights the importance of assessing specific toxicological profiles in ecological risk assessments, especially for air toxics like benzo(a)pyrene that exhibit high bioconcentration factors;
- (4)
- Development of Tailored Food Web Models for Local Ecosystems: This study’s unique models, customized for Kuwait’s ecosystems, offered a representative ecological risk assessment;
- (5)
- Importance of Diet Type and Trophic Level in Ecological Risk Assessments: This analysis highlights the importance of considering both the diet type and trophic level in assessing ecological risks due to air toxics exposure;
- (6)
- Need for Regular Ecological Risk Assessments: This study underscores the importance of conducting regular ecological risk assessments. These are important for adapting to environmental and industrial changes, ensuring that air quality standards continue to protect ecological health;
- (7)
- Informing Policy and Management Decisions: The findings and methodologies developed in this study offer valuable insights for environmental management strategies and policy decisions. These can guide actions to mitigate ecological risks, such as adjusting existing policies or implementing targeted mitigation efforts in high-risk areas.
5. Future Work
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Nomenclature
API | American Petroleum Institute |
BAF | Bioaccumulation Factor |
BCF | Bioconcentration Factor |
EFSA | European Food Safety Authority |
EHAM | Ecological Health Assessment Methodology |
ESQ | Ecological Screening Quotient |
ECOTOX | Ecotoxicology Knowledgebase |
EEL | Estimated Exposure Level |
FCM | Food-chain Multiplier |
FIFRA | Federal Insecticide, Fungicide, and Rodenticide Act |
kg | Kilogram (unit of weight) |
octanol–water partition coefficient | |
L | Liter (unit of volume) |
LULC | Land Use Land Cover |
mg | Milligram (unit of weight) |
NOAELs | No-Observed-Adverse-Effect Levels |
PAHs | Polycyclic Aromatic Hydrocarbons |
POPs | Persistent Organic Pollutants |
SLERAP | Screening Level Ecological Risk Assessment Protocol |
TL1, TL2, TL3, TL4 | First, Second, Third, Fourth Trophic level(s) |
TRV | Toxicity Reference Value |
US EPA | United States Environmental Protection Agency |
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Terrestrial Ecosystems | Ref. | Aquatic Ecosystems | Ref. | |
---|---|---|---|---|
Entry Mechanisms | Dry deposition | [10,11] | Rainfall | [21,22,23] |
Wet deposition | [10,11] | Tidal activities | [24,25,26] | |
Direct inhalation | [12,13] | Direct uptake from water | [27,28,29] | |
Plant–soil interactions | [14,15] | Watershed loading (surface runoff, point source discharge, atmospheric deposition, and riverine input) | [30,31,32] | |
Affected Trophic Levels | Herbivores | [16,17] | Benthic organisms | [33,34,35] |
Omnivores | [16,17] | Intermediate consumers | [36,37,38] | |
Predators (via bioaccumulation) | [16,17] | Larger aquatic predators (via bioaccumulation) | [16,17,24] | |
Inter-ecosystem Interactions | Watershed loading affects adjacent aquatic ecosystems | [18,19,20] | Watershed loading affects adjacent terrestrial ecosystems | [18,19,20] |
Ecological Health Impact | Ref. |
---|---|
Amphibian (Common Frog): Increased embryonic mortality rate | [39] |
Bird (Pied Flycatchers): Habitat degradation; impaired reproductive success | [40,41] |
Fish (African Catfish): Decreased sperm motility | [42] |
Fish (Common Carp): Increased lipid peroxidation; DNA damage; elevated micronuclei frequency in blood, gill, and liver | [43] |
Fish (European Perch): Decline in sperm performance; sperm structural damage affecting flagella, plasma membrane, and axoneme; decreased sperm ATP content leading to inhibited motility; damage to sperm’s midpiece and mitochondria during prolonged exposure; disruption in sperm activation due to plasma membrane damage | [44] |
Fish (Lake Trout, Largemouth Bass, Northern Pike, Walleye): Behavioral alterations; changes in gene expression; impacts on growth | [45] |
Fish (Norwegian Waters): Induction of phase-I enzymes; development of DNA adducts; formation of neoplastic lesions | [46] |
Fish (Peacock Blenny): Circulatory issues in gills; liver damage comprising reduction in cell size, loss of cellular integrity, and architectural disruptions | [47] |
Fish (Trahira): Electrophysiological changes in retinal horizontal cells | [48] |
Fish (Zebrafish): Changes in lipid metabolism and cellular transport; gonadal damage; oxidative stress in the testis; altered sex hormone levels impairing reproduction | [49,50] |
Mammal (Mink): Reproductive failure | [51] |
Mesozooplankton: Accumulation of air toxics in tissues, fecal pellets, and eggs; potential transfer to higher trophic levels affecting pelagic and benthic communities | [52] |
Phytoplankton: Disruption to growth and photosynthesis; induction of oxidative stress | [53,54] |
# | Literature (Year) | Country-Wide | Source | Pathway | Receiver | Ref. |
---|---|---|---|---|---|---|
1 | A Procedure for Performing Population-Level Ecological Risk Assessments (2000) | No | Land/water | Land to local ecosystems | Quail, shrew, fish | [57] |
2 | Potential Long-Term Ecological Impacts Caused by Disturbance of Contaminated Sediments: A Case Study (2002) | No | Water | Release from disturbed sediments to water column | Mummichog, blue crab, polychaete, striped bass | [58] |
3 | An Ecological Risk Assessment for Spinosad Use on Cotton (2002) | No | Land | Terrestrial insecticide application to cotton crops | Groundwater, mourning dove, field sparrow, blue tit, bees, bluegill, rainbow trout, carp, grass shrimp, eastern oyster, freshwater diatom, Sharkey soil | [59] |
4 | Ecological Risk Assessment of Contaminated Soils Through Direct Toxicity Assessment (2005) | No | Land | Leaching of contaminants from soil | Plants, earthworm, Daphnia, algae, fish | [60] |
5 | Probabilistic Ecological Risk Assessment of 1,2,4-Trichlorobenzene at a Former Industrial Contaminated Site (2005) | No | Land | Leaching from soil to groundwater | Aquatic invertebrates, microbial soil population, plants | [61] |
6 | A Screening-Level Assessment of Lead, Cadmium, and Zinc in Fish and Crayfish from Northeastern Oklahoma, USA (2006) | No | Water | Runoff from land to water bodies | Humans, carp, catfish, bass, crappie, carnivorous wildlife, crayfish | [62] |
7 | Anthropogenic Input of Selected Heavy Metals in the Aquatic Sediments of Hochiminh City, Vietnam (2006) | No | Water | Industry and agricultural runoff | Aquatic sediments in rivers and canals | [63] |
8 | Potential Importance of Inhalation Exposures for Wildlife Using Screening-Level Ecological Risk Assessment (2006) | No | Air | Airborne contaminants inhaled by wildlife | Small mammals | [64] |
9 | Environmental Risk Assessment of Pharmaceutical Residues in Wastewater Effluents, Surface Waters, and Sediments (2006) | No | Water | Wastewater and surface water contamination | Aquatic organisms | [65] |
10 | Bioconcentration of Dioxins and Furans in Vegetation (2007) | No | Land | Soil-to-vegetation contamination | Vegetation including grass and clover | [66] |
11 | Predicting Pesticide Environmental Risk in Intensive Agricultural Areas. II: Screening Level Risk Assessment of Complex Mixtures in Surface Waters (2009) | No | Land | Pesticide drift and runoff | Algae, Daphnia, fish | [67] |
12 | Evidence of impacts from DDT in pelican, cormorant, stork, and egret eggs from KwaZulu-Natal, South Africa (2019) | No | Land | Aerial transport and aquatic ecosystems | African openbill, pelican, molluscan, piscivorous birds, pink-backed pelican, egrets, white-breasted cormorant | [68] |
13 | DSS-OSM: An Integrated Decision Support System for Offshore Oil Spill Management (2021) | No | Water | Spread of oil in marine environments | Marine organisms | [69] |
14 | This Work (2023) | Yes | Air | Atmospheric dispersion and deposition of air toxics | Terrestrial and aquatic species across various trophic levels |
Parameters | Sources | Remarks |
---|---|---|
Ingestion Rates for Measurement Receptors | US EPA Wildlife Exposure Factors Handbook [80] | Data on ingestion rates across species. |
Food-chain Multiplier | Great Lakes Water Quality Initiative Technical Support Document for the Procedure to Determine Bioaccumulation Factors [81] | Provides standardized FCM values. |
Bioaccumulation Factor Model | Gobas [82] | Models for calculating BAF. |
# | Receptor Group | Diet | Cumulative ESQ (Unitless) | ESQ Above 1.0 (Y = Yes/N = No) |
---|---|---|---|---|
1 | Carnivorous Bird | Equal | 3.02 × 102 | Y |
Exclusive (Detailed Breakdown Below) | - | - | ||
Carnivorous Fish | 6.06 × 101 | Y | ||
Herbivorous Bird | 1.15 × 101 | Y | ||
Herbivorous Mammal | 1.18 × 101 | Y | ||
Omnivorous Bird | 1.01 × 103 | Y | ||
Omnivorous Fish | 4.15 × 101 | Y | ||
Omnivorous Mammal | 6.77 × 102 | Y | ||
2 | Carnivorous Mammal | Equal | 2.66 × 10 | Y |
Exclusive (Detailed Breakdown Below) | - | - | ||
Carnivorous Fish | 4.65 × 10−1 | N | ||
Herbivorous Bird | 1.84 × 10−2 | N | ||
Herbivorous Mammal | 2.11 × 10−2 | N | ||
Omnivorous Bird | 9.07 × 10 | Y | ||
Omnivorous Fish | 2.91 × 10−1 | N | ||
Omnivorous Mammal | 6.06 × 10 | Y | ||
3 | Carnivorous Shorebird | Equal | 9.04 × 102 | Y |
Exclusive (Detailed Breakdown Below) | - | - | ||
Benthic Invertebrates | 1.08 × 103 | Y | ||
Omnivorous Bird | 3.12 × 103 | Y | ||
Omnivorous Fish | 1.40 × 102 | Y | ||
Planktivore Fish | 5.59 × 101 | Y | ||
Water Invertebrates | 1.27 × 102 | Y | ||
Benthic Invertebrates | 1.08 × 103 | Y | ||
4 | Herbivorous Bird | Equal | 1.87 × 101 | Y |
Exclusive (Detailed Breakdown Below) | - | - | ||
Algae | 3.30 × 101 | Y | ||
Aquatic Vegetation | 4.39 × 10 | Y | ||
5 | Herbivorous Mammal | Equal | 6.42 × 10−1 | N |
Exclusive (Detailed Breakdown Below) | - | - | ||
Algae | 1.17 × 10 | Y | ||
Aquatic Vegetation | 1.11 × 10−1 | N | ||
6 | Omnivorous Bird | Equal | 5.15 × 102 | Y |
Exclusive (Detailed Breakdown Below) | - | - | ||
Algae | 1.66 × 102 | Y | ||
Aquatic Vegetation | 3.32 × 101 | Y | ||
Benthic Invertebrates | 1.71 × 103 | Y | ||
Water Invertebrates | 1.51 × 102 | Y | ||
7 | Omnivorous Mammal | Equal | 1.59 × 10 | Y |
Exclusive (Detailed Breakdown Below) | - | - | ||
Algae | 7.11 × 10−1 | N | ||
Aquatic Vegetation | 8.03 × 10−2 | N | ||
Benthic Invertebrates | 8.04 × 10 | Y | ||
Herbivorous Bird | 2.93 × 10−2 | N | ||
Herbivorous Mammal | 3.66 × 10−2 | N | ||
Water Invertebrates | 6.38 × 10−1 | N |
# | Receptor Group | Diet | Cumulative ESQ (Unitless) | ESQ Above 1.0 (Y = Yes/N = No) |
---|---|---|---|---|
1 | Carnivorous Bird | Equal | 4.55 × 10−6 | N |
Exclusive (Detailed Breakdown Below) | - | - | ||
Herbivorous Bird | 1.49 × 10−7 | N | ||
Herbivorous Mammal | 1.92 × 10−7 | N | ||
Omnivorous Bird | 1.16 × 10−5 | N | ||
Omnivorous Mammal | 6.25 × 10−6 | N | ||
2 | Carnivorous Mammal | Equal | 3.91 × 10−8 | N |
Exclusive (Detailed Breakdown Below) | - | - | ||
Herbivorous Bird | 2.60 × 10−9 | N | ||
Herbivorous Mammal | 2.96 × 10−9 | N | ||
Omnivorous Bird | 9.77 × 10−8 | N | ||
Omnivorous Mammal | 5.31 × 10−8 | N | ||
3 | Herbivorous Bird | Equal | 4.28 × 10−6 | N |
Exclusive (Detailed Breakdown Below) | - | - | ||
Terrestrial Plant | 4.28 × 10−6 | N | ||
4 | Herbivorous Mammal | Equal | 7.00 × 10−8 | N |
Exclusive (Detailed Breakdown Below) | - | - | ||
Terrestrial Plant | 7.00 × 10−8 | N | ||
5 | Omnivorous Bird | Equal | 3.68 × 10−6 | N |
Exclusive (Detailed Breakdown Below) | - | - | ||
Terrestrial Invertebrates | 2.71 × 10−6 | N | ||
Terrestrial Plant | 4.65 × 10−6 | N | ||
6 | Omnivorous Mammal | Equal | 2.82 × 10−8 | N |
Exclusive (Detailed Breakdown Below) | - | - | ||
Herbivorous Bird | 2.71 × 10−9 | N | ||
Herbivorous Mammal | 3.37 × 10−9 | N | ||
Terrestrial Invertebrates | 3.41 × 10−8 | N | ||
Terrestrial Plant | 7.26 × 10−8 | N |
# | Receptor Group | Diet | Cumulative ESQ (Unitless) | ESQ Above 1.0 (Y = Yes/N = No) |
---|---|---|---|---|
1 | Carnivorous Bird | Equal | 7.09 × 10−7 | N |
Exclusive (Detailed Breakdown Below) | - | - | ||
Herbivorous Bird | 2.37 × 10−8 | N | ||
Herbivorous Mammal | 3.11 × 10−8 | N | ||
Omnivorous Bird | 1.81 × 10−6 | N | ||
Omnivorous Mammal | 9.76 × 10−7 | N | ||
2 | Carnivorous Mammal | Equal | 6.09 × 10−9 | N |
Exclusive (Detailed Breakdown Below) | - | - | ||
Herbivorous Bird | 4.09 × 10−10 | N | ||
Herbivorous Mammal | 4.70 × 10−10 | N | ||
Omnivorous Bird | 1.52 × 10−8 | N | ||
Omnivorous Mammal | 8.30 × 10−9 | N | ||
3 | Herbivorous Bird | Equal | 7.17 × 10−7 | N |
Exclusive (Detailed Breakdown Below) | - | - | ||
Terrestrial Plant | 7.17 × 10−7 | N | ||
4 | Herbivorous Mammal | Equal | 1.18 × 10−8 | N |
Exclusive (Detailed Breakdown Below) | - | - | ||
Terrestrial Plant | 1.18 × 10−8 | N | ||
5 | Omnivorous Bird | Equal | 5.97 × 10−7 | N |
Exclusive (Detailed Breakdown Below) | - | - | ||
Terrestrial Invertebrates | 4.20 × 10−7 | N | ||
Terrestrial Plant | 7.75 × 10−7 | N | ||
6 | Omnivorous Mammal | Equal | 2.82 × 10−8 | N |
Exclusive (Detailed Breakdown Below) | - | - | ||
Herbivorous Bird | 4.64 × 10−9 | N | ||
Herbivorous Mammal | 4.30 × 10−10 | N | ||
Terrestrial Invertebrates | 5.43 × 10−10 | N | ||
Terrestrial Plant | 5.31 × 10−9 | N |
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Munshed, M.; Van Griensven Thé, J.; Fraser, R.; Matthews, B.; Elkamel, A. Country-Wide Ecological Health Assessment Methodology for Air Toxics: Bridging Gaps in Ecosystem Impact Understanding and Policy Foundations. Toxics 2024, 12, 42. https://doi.org/10.3390/toxics12010042
Munshed M, Van Griensven Thé J, Fraser R, Matthews B, Elkamel A. Country-Wide Ecological Health Assessment Methodology for Air Toxics: Bridging Gaps in Ecosystem Impact Understanding and Policy Foundations. Toxics. 2024; 12(1):42. https://doi.org/10.3390/toxics12010042
Chicago/Turabian StyleMunshed, Mohammad, Jesse Van Griensven Thé, Roydon Fraser, Bryan Matthews, and Ali Elkamel. 2024. "Country-Wide Ecological Health Assessment Methodology for Air Toxics: Bridging Gaps in Ecosystem Impact Understanding and Policy Foundations" Toxics 12, no. 1: 42. https://doi.org/10.3390/toxics12010042