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EM: Plankton response to sudden polychlorinated biphenyls pollution on a Reservoir of North China based on AQUATOX model (EM-1054)
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Expand AllEM Identity and Description
EM Identification
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EM ID
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EM-1054 |
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EM Short Name
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Aquatox, chemical pollutant model, China |
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EM Full Name
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Plankton response to sudden polychlorinated biphenyls pollution on a Reservoir of North China based on AQUATOX model |
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EM Source or Collection
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None |
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EM Source Document ID
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501 |
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Document Author
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Yan, J., Li, H., Liu, C., Liu, C. and Xing, T. |
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Document Year
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2025 |
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Document Title
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Plankton response to sudden polychlorinated biphenyls pollution on a Reservoir of North China based on AQUATOX model |
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Document Status
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Peer reviewed and published |
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Comments on Status
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Published journal manuscript |
Software and Access
| https://www.epa.gov/hydrowq/aquatox-32-download-page | |
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Contact Name
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Jinxia Yan |
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Contact Address
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Henan Key Laboratory of Water Environment Simulation and Treatment, School of Environmental and Municipal Engineering, North China University of Water Resources and Electric Power, 450046 Zhengzhou, China |
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Contact Email
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yanjinxia@ncwu.edu.cn |
EM Description
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Summary Description
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Emergency management research on sudden organic pollution accidents in urban water sources is of great significance. In the study, AQUATOX, coupled water quality and water quantity based on food web, was implemented to simulate and predict the effects of sudden Polychlorinated biphenyls (PCBs) pollution under different concentrations scenario on water quality and dominant biological populations in Panshitou Reservoir, China. The model was used to quantify how the biomass changes of the modelled taxa in the reservoir food web deviated from natural conditions due to varying concentration inputs of the PCBs. Also, no observed effect concentrations (NOECs) were derived using AQUATOX model. The results showed that the contents of DO, TN, TP and NH4+-N increased slightly with the concentration increase of PCBs, and the comprehensive water quality indexes (WQI) decreased little. The biomass of dominant biological populations did not show significant changes in the previous week, but the changes gradually increased, and the ecological risk rose correspondingly. The NOEC levels of PCBs for primary producers, such as diatom, green algae, blue-green algae and cryptoalgae, were about 1.89μg/L, 0.66μg/L, 0.81μg/L and 0.45μg/L, respectively; consumers such as water fleas, planktonic predators, and oligochaetes were around 3.4μg/L, 2.6 μg/L, and 0.81 μg/L, respectively. Compared with benchmarks of NOEC from the PCB Residue Effects Database of USEPA, threshold concentration computed using AQUATOX model were generally of the same order of magnitude in Panshitou Reservoir ecosystem. Our findings indicated that ecosystem models could be a useful tool in the assessment of organic chemical sudden impact on reservoir ecosystems as a whole. |
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Specific Policy or Decision Context Cited
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None identified |
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Biophysical Context
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Panshitou Reservoir, Qihe Riverin Haihe River Basin |
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EM Scenario Drivers
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PCB concentration |
EM Relationship to Other EMs or Applications
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Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) View EM Runs |
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New or Pre-existing EM?
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New or revised model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
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Document ID for related EM
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None |
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EM ID for related EM
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None |
EM Modeling Approach
EM Relationship to Time
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EM Temporal Extent
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2018 |
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EM Time Dependence
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time-dependent |
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EM Time Reference (Future/Past)
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past time |
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EM Time Continuity
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discrete |
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EM Temporal Grain Size Value
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1 |
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EM Temporal Grain Size Unit
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Day |
EM Spatial Extent
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Bounding Type
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Watershed/Catchment/HUC |
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Spatial Extent Name
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Panshitou Reservoir |
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Spatial Extent Area (Magnitude)
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100-1000 km^2 |
Spatial Distribution of Computations
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EM Spatial Distribution
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spatially distributed (in at least some cases) |
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Spatial Grain Type
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other (specify), for irregular (e.g., stream reach, lake basin) |
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Spatial Grain Size
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Irregular segments of resrvoir |
EM Structure and Computation Approach
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EM Computational Approach
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Analytic |
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EM Determinism
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deterministic |
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Statistical Estimation of EM
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Model Checking Procedures Used
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Model Calibration Reported?
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Yes |
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Model Goodness of Fit Reported?
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Yes |
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Goodness of Fit (metric| value | unit)
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Model Operational Validation Reported?
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Yes |
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Model Uncertainty Analysis Reported?
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Unclear |
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Model Sensitivity Analysis Reported?
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Unclear |
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Model Sensitivity Analysis Include Interactions?
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Not applicable |
EM Locations, Environments, Ecology
Location of EM Application
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
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| None |
Centroid Lat/Long (Decimal Degree)
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Centroid Latitude
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39.49 |
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Centroid Longitude
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113.85 |
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Centroid Datum
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WGS84 |
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Centroid Coordinates Status
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Estimated |
Environments and Scales Modeled
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EM Environmental Sub-Class
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Lakes and Ponds |
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Specific Environment Type
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Tributary reservoir |
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EM Ecological Scale
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Ecological scale corresponds to the Environmental Sub-class |
Scale and taxa of organisms modeled
Scale of differentiation of organisms modeled
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EM Organismal Scale
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Guild or Assemblage |
Taxonomic level and name of organisms or groups identified
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EnviroAtlas URL
em.detail.enviroAtlasURLHelp
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| National Hydrography Dataset Plus (NHD PlusV2), Average Annual Precipitation, Waterbody area, Total Annual Reduced Nitrogen Deposition |
EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system
CICES v 4.3 - Common International Classification of Ecosystem Services (Section > Division > Group > Class)
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(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
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EM Variable Names (and Units)
Predictor
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Intermediate
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Intermediate (Computed) Variables (and Units)
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None |
Response
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Observed Response Variables (and Units)
view details (4 variables)
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Computed Response Variables (and Units)
view details (12 variables)
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