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[[File:Turbid runoff.JPG|300px|thumb|alt=image turbid runoff|<font size=3>Suspended sediment in stormwater runoff</font size>]]
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<table class="infobox" style="border:3px; border-style:solid; border-color:#FF0000; text-align: right; width: 300px; font-size: 100%">
 
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<th><center><font size=3>'''Rapid Screening Procedure for Siting Infiltration Practices'''</font size></center></th>
 
</tr>
 
<tr>
 
<td>The University of Minnesota has developed a rapid screening tool for siting infiltration stormwater control measures. The screening procedure consists of the following steps.
 
* step 1
 
* step 2
 
*etc
 
For more information ,see or contact XXXX
 
</td>
 
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</table>
 
</div>
 
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Because of the expense and difficulty of monitoring stormwater runoff, we often rely on published information to estimate pollutant loading associated with runoff. Models or other tools are often used to predict pollutant loading. These models and tools require information on the pollutant concentration in runoff. For example, the Simple Method, which is commonly used to estimate pollutant loading, utilizes the following equation
 
Because of the expense and difficulty of monitoring stormwater runoff, we often rely on published information to estimate pollutant loading associated with runoff. Models or other tools are often used to predict pollutant loading. These models and tools require information on the pollutant concentration in runoff. For example, the Simple Method, which is commonly used to estimate pollutant loading, utilizes the following equation
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:P = Rainfall depth per year (inches);
 
:P = Rainfall depth per year (inches);
 
:P<sub>j</sub> = Fraction of rainfall events that produce runoff;
 
:P<sub>j</sub> = Fraction of rainfall events that produce runoff;
:R<sub>v</sub> = Runoff coefficient, which expresses the fraction of rainfall which is converted into runoff. Rv = 0.05 + 0.009(I);
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:R<sub>v</sub> = <span title="The runoff coefficient (C) is a dimensionless coefficient relating the amount of runoff to the amount of precipitation received. It is a larger value for areas with low infiltration and high runoff (pavement, steep gradient), and lower for permeable, well vegetated areas (forest, flat land)."> [https://stormwater.pca.state.mn.us/index.php?title=Runoff_coefficients_for_5_to_10_year_storms '''Runoff coefficient''']</span>, which expresses the fraction of rainfall which is converted into runoff. Rv = 0.05 + 0.009(I);
 
:I = Site imperviousness (i.e., I = 75 if site is 75% impervious);
 
:I = Site imperviousness (i.e., I = 75 if site is 75% impervious);
:C = Flow-weighted mean concentration of the pollutant in urban runoff (mg/l); and
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:C = <span title="A flow-weighted mean is the mean of a quantity after it is weighted proportional to a corresponding flow rate."> '''[https://ncwqr.files.wordpress.com/2017/06/d-time-weighted-and-flow-weighted-mean-concentrations.pdf Flow-weighted mean concentration]'''</span> of the pollutant in urban runoff (mg/l); and
 
:A = Area of the development site (acres).
 
:A = Area of the development site (acres).
  
This page provides a discussion of pollutant concentrations in stormwater runoff, including a review of literature and recommended values to use
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This page provides a discussion of pollutant concentrations in stormwater runoff, including a review of literature and links recommended values to use.
  
 
==Factors affecting actual and measured storm concentrations==
 
==Factors affecting actual and measured storm concentrations==
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*duration and intensity of runoff,
 
*duration and intensity of runoff,
 
*characteristics of the pollutant,
 
*characteristics of the pollutant,
*season, and
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*season,
*connectedness of impervious surfaces.
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*extent of exposed soils, such as with construction sites, and
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*extent of <span title="a subset of impervious cover, which is directly connected to a drainage system or a water body via continuous impervious surfaces."> '''connected impervious surfaces'''</span>.
  
In addition, the measured concentration varies with these factors and factors related to measurement, including but not limited to
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In addition, the measured concentration varies with factors related to measurement, including but not limited to
 
*type of sampling equipment and sample collection,
 
*type of sampling equipment and sample collection,
 
*location of sampling,
 
*location of sampling,
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In the absence of monitoring data for a specific study or location, we often use event mean concentrations (emc). The emc represents the average pollutant concentration for a given stormwater event, expressed in units of mass per volume (e.g., mg/L). Given the number of factors affecting pollutant concentration, determining an appropriate emc is challenging.
 
In the absence of monitoring data for a specific study or location, we often use event mean concentrations (emc). The emc represents the average pollutant concentration for a given stormwater event, expressed in units of mass per volume (e.g., mg/L). Given the number of factors affecting pollutant concentration, determining an appropriate emc is challenging.
  
Despite challenges in accurately determining emcs, they are widely used in stormwater applications. Emcs are used in many stormwater water quality models and calculations of pollutant loading. They are therefore fundamental to understanding pollutant loads and how to address reducing pollutant loads in stormwater runoff.
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Despite challenges in accurately determining emcs, they are widely used in stormwater applications. Emcs are used in many stormwater water quality <span title="a tool to simulate natural processes and estimate the expected volume, rate, or quality of stormwater"> [https://stormwater.pca.state.mn.us/index.php?title=Introduction_to_stormwater_modeling '''models''']</span> and calculations of pollutant loading. They are therefore fundamental to understanding pollutant loads and how to address reducing pollutant loads in stormwater runoff.
 
 
<!--
 
expected concentration in typical runoff event. The remainder of this page focuses on emcs, but it is important to identify situations when using the emc is likely not appropriate.
 
*Estimating the loading from a specific runoff event, such as phosphorus concentrations in Fall runoff from residential areas. Emcs may be used if they represent runoff water quality for this time period (e.g. use of seasonal emcs).
 
*Assessing the impacts of runoff on receiving water receptors. For example, chloride concentrations in late winter runoff from areas receiving high inputs of deicer chemicals may exceed acute water quality standards by more than an order of magnitude. These excessive concentrations may adversely impact stream biota during this time period. Maximum concentrations should be used in situations like these.
 
*If the focus is on water quality of specific hydrologic events, such as low intensity or high intensity events.-->
 
  
 
==Calculating emcs==
 
==Calculating emcs==
[[File:EMC example 2.png|300px|thumb|alt=image for emcs|<font size=3>Example of how emcs can be calculated using concentration and flow data taken at discrete time intervals. In the top example, assume all time intervals are 30. In the lower graph, intervals 1 and 2 from the top graph are combined and Q and C average, while the remaining intervals are left at 30. The emc for the top graph is 69.1 mg/L and 76.0 mg/L for the lower graph, even though the data are the same.</font size>]]
 
 
 
Emcs should represent the flow proportional concentration of a given pollutant parameter during storm events. The simplest way to calculate and emc is therefore to divide the total mass of a pollutant by the total runoff volume. Emcs can also be calculated as the sum, over multiple discrete time intervals within an event, of volume times the concentration for the time interval, divided by the total volume for the event
 
Emcs should represent the flow proportional concentration of a given pollutant parameter during storm events. The simplest way to calculate and emc is therefore to divide the total mass of a pollutant by the total runoff volume. Emcs can also be calculated as the sum, over multiple discrete time intervals within an event, of volume times the concentration for the time interval, divided by the total volume for the event
  
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[http://stormwaterbook.safl.umn.edu/pollutant-removal/analysis-individual-storm-events Erickson et al.] provide detailed discussion and examples for calculating pollutant loading from stormwater runoff. The emc calculated for a specific event is a function of the sampling method. Erickson et al. discuss the following methods for sampling.
 
[http://stormwaterbook.safl.umn.edu/pollutant-removal/analysis-individual-storm-events Erickson et al.] provide detailed discussion and examples for calculating pollutant loading from stormwater runoff. The emc calculated for a specific event is a function of the sampling method. Erickson et al. discuss the following methods for sampling.
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[[File:EMC example 2.png|300px|thumb|alt=image for emcs|<font size=3>Example of how emcs can be calculated using concentration and flow data taken at discrete time intervals. In the top example, assume all time intervals are 30. In the lower graph, intervals 1 and 2 from the top graph are combined and Q and C average, while the remaining intervals are left at 30. The emc for the top graph is 69.1 mg/L and 76.0 mg/L for the lower graph, even though the data are the same.</font size>]]
 +
 
*Flow-weighted discrete samples: "When samples are collected based on a user-specified constant incremental volume of discharge (e.g., every 1000, 2000, or 5000 gallons) that passes the sampler, the samples are defined as flow-weighted. Each flow-weighted sample is assumed to represent the average pollutant concentration for the entire incremental volume of water to which it corresponds. Each discrete sample is stored in an individual container, and the contents of each container are analyzed separately."
 
*Flow-weighted discrete samples: "When samples are collected based on a user-specified constant incremental volume of discharge (e.g., every 1000, 2000, or 5000 gallons) that passes the sampler, the samples are defined as flow-weighted. Each flow-weighted sample is assumed to represent the average pollutant concentration for the entire incremental volume of water to which it corresponds. Each discrete sample is stored in an individual container, and the contents of each container are analyzed separately."
 
*Flow-weighted composite samples: "Flow-weighted composite samples are collected every time a user-specified constant volume of flow passes the sampler and all samples are stored in a single container. To determine pollutant concentration, an aliquot is collected from the composite sample, and the concentration is assumed to represent that of the entire composite sample."
 
*Flow-weighted composite samples: "Flow-weighted composite samples are collected every time a user-specified constant volume of flow passes the sampler and all samples are stored in a single container. To determine pollutant concentration, an aliquot is collected from the composite sample, and the concentration is assumed to represent that of the entire composite sample."
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*Composite grab samples: "Composite grab samples are typically collected at variable time and volume increments and stored in a single sample storage container. Composite grab sampling is not recommended."
 
*Composite grab samples: "Composite grab samples are typically collected at variable time and volume increments and stored in a single sample storage container. Composite grab sampling is not recommended."
  
The sampling method affects the resulting calculation of emc. For example, in the adjacent image, emcs were calculated for the same runoff event. In the top portion of the image, sampling occurred every 30 minutes and the overall emc is 69.1 mg/L. In the lower portion of the image, the first two time intrvals were combined and Q and C averaged over the 60 minute time interval, while the remaining time intervals were 30 minutes each. The overall emc is 76.0 mg/L. The difference is a result of a bias toward higher concentrations in the early portion of the runoff event for the lower graph. This tendency toward higher pollutant concentrations in the early part of a runoff event is called the first flush.
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The sampling method affects the resulting calculation of emc. For example, in the adjacent image, emcs were calculated for the same runoff event. In the top portion of the image, sampling occurred every 30 minutes and the overall emc is 69.1 mg/L. In the lower portion of the image, the first two time intervals were combined and Q and C averaged over the 60 minute time interval, while the remaining time intervals were 30 minutes each. The overall emc is 76.0 mg/L. The difference is a result of a bias toward higher concentrations in the early portion of the runoff event for the lower graph. This tendency toward higher pollutant concentrations in the early part of a runoff event is called the <span title="the initial surface runoff of a rainstorm. During this phase, water pollution entering storm drains in areas with high proportions of impervious surfaces is typically more concentrated compared to the remainder of the storm"> '''first flush'''</span>.
 +
 
 +
[https://fortress.wa.gov/ecy/publications/documents/1810026.pdf Washington State] developed standard operating procedures for measuring pollutant loads, including emcs. They include procedures for addressing seasonality.
  
 
==Factors affecting emcs==
 
==Factors affecting emcs==
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<tr>
 
<tr>
<td>First flush is a phenomenon in which pollutant concentrations in stormwater runoff are greater in the early portion of a runoff event. First flush is common for relatively uniform land use settings, for winter and early spring runoff events, and for runoff events during fall leaf-drop. During dry periods between runoff events, pollutants build-up on impermeable surfaces. For Type 2 rain events, initial rain intensity is low and increases through a storm before decreasing near the end of the storm. The initial runoff is therefore highly concentrated with pollutants that have accumulated on impermeable surfaces. As runoff volume increases during an event and pollutants become more resistant to being washed off, concentrations decrease and typically reach steady state. First flush is not universally applicable to stormwater runoff, however. For example, if higher pollutant buildup on impermeable surfaces occurs in upper portions of a watershed, as might occur in an area with variable land uses, the peak concentration may be delayed as those higher pollutant loads take time to reach a receiving point. Similarly, some pollutants may be resistant to transport in early stages of an event. In other situations, concentrations in runoff may be uniform throughout an event, particularly if rainfall intensities are uniform and pollutants are soluble (e.g. chloride).
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<td>First flush is a phenomenon in which pollutant concentrations in stormwater runoff are greater in the early portion of a runoff event. First flush is common for relatively uniform land use settings, for winter and early spring runoff events, and for runoff events during fall leaf-drop. During dry periods between runoff events, pollutants build-up on impermeable surfaces. For <span title="A rainfall distribution characterized by short duration, high intensity rainfall"> '''[https://www.wcc.nrcs.usda.gov/ftpref/wntsc/H&H/NEHhydrology/ch4_Sept2015draft.pdf Type 2 rain distribution]'''</span>, initial rain intensity is low and increases through a storm before decreasing near the end of the storm. The initial runoff is therefore highly concentrated with pollutants that have accumulated on impermeable surfaces. As runoff volume increases during an event and pollutants become more resistant to being washed off, concentrations decrease and typically reach steady state. First flush is not universally applicable to stormwater runoff, however. For example, if higher pollutant buildup on impermeable surfaces occurs in upper portions of a watershed, as might occur in an area with variable land uses, the peak concentration may be delayed as those higher pollutant loads take time to reach a receiving point. Similarly, some pollutants may be resistant to transport in early stages of an event. In other situations, concentrations in runoff may be uniform throughout an event, particularly if rainfall intensities are uniform and pollutants are soluble (e.g. chloride).
 
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===Land use===
 
===Land use===
{{:alert|Using an emc for the specific land use being considered is highly recommended. See [[Stormwater event mean concentrations and pollutant loading/export rates for different land uses]] for emcs for different pollutants and land uses.|alert-warning}}
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{{alert|Using an emc for the specific land use being considered is highly recommended. See [[Stormwater event mean concentrations and pollutant loading/export rates for different land uses]] for emcs for different pollutants and land uses.|alert-warning}}
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[[File:Land use image.gif|300px|thumb|alt=image of land uses|<font size=3>Photos of different land uses</font size>]]
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Because of the variability in emcs across different land uses, it is beneficial to consider different land uses when calculating pollutant loads. Compositing emcs across land uses is generally not recommended.
  
 
Some generalizations about pollutant loading as a function of land use include the following.
 
Some generalizations about pollutant loading as a function of land use include the following.
*Commercial, industrial, and transportation land use typically have higher percentages of impervious and directly connected impervious surface, as shown in the accompanying table summarizing curve numbers for different land uses. This results in more efficient delivery of pollutants and runoff compared to other land uses. Consequently, we expect higher emcs from these land uses for smaller runoff events and when pollutant buildup on impermeable surfaces is greater, and lower emcs for larger runoff events when dilution occurs.
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*Commercial, industrial, and transportation land use typically have higher percentages of impervious and directly connected impervious surface, as shown in the accompanying table summarizing <span title="The SCS curve number method is a widely used method for determining the approximate amount of runoff from a rainfall even in a particular area. The curve number is based on the area's hydrologic soil group, land use , treatment and hydrologic condition."> '''curve numbers'''</span> for different land uses. This results in more efficient delivery of pollutants and runoff compared to other land uses. Consequently, we expect higher emcs from these land uses for smaller runoff events and when pollutant buildup on impermeable surfaces is greater, and lower emcs for larger runoff events with greater rainfall intensities as a result of dilution.
*Nutrient (phosphorus, nitrogen) concentrations are greater in residential areas and other land uses that contribute significant amounts of organic material to impermeable surfaces. Dissolved fractions also comprise a greater percent of the total load for these pollutants.
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*Nutrient (phosphorus, nitrogen) concentrations are greater in residential areas and other land uses that contribute significant amounts of <span title="carbon-based compounds, originally derived from living organisms"> '''organic material'''</span> to impermeable surfaces. Dissolved fractions also comprise a greater percent of the total load for these pollutants when the source of the nutrient is organic material.
 
*Concentrations of metals increase as road density and traffic volume increase.
 
*Concentrations of metals increase as road density and traffic volume increase.
*Concentrations of petroleum-related compounds and polycyclic aromatic hydrocarbons (PAHs) increase as road density and traffic volume increase.
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*Concentrations of petroleum-related compounds and <span title="a class of chemicals that occur naturally in coal, crude oil, and gasoline. They also are produced when coal, oil, gas, wood, garbage, and tobacco are burned."> '''polycyclic aromatic hydrocarbons'''</span> (PAHs) increase as road density and traffic volume increase.
*Concentrations of total suspended solids (TSS) may be similar across different land uses, but the characteristics of the TSS varies. Organic fractions make up a larger percent of TSS in residential areas and other land uses where there are sources of organic material to impermeable surfaces.
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*Concentrations of total suspended solids (TSS) may be similar across different land uses, but the characteristics of the TSS varies. Organic fractions make up a larger percent of TSS in residential areas and other land uses where there are sources of organic material to impermeable surfaces, while inorganic fractions (e.g. sand, silt) comprise the majority of TSS in settings with low inputs of organic material.
 
*Bacteria concentrations are typically greater in residential areas due to greater inputs from domestic animals (e.g. dogs), birds, and other animals. Studies also suggest irrigated lawns and leaves/organic material on impermeable surfaces contribute to bacteria loads.
 
*Bacteria concentrations are typically greater in residential areas due to greater inputs from domestic animals (e.g. dogs), birds, and other animals. Studies also suggest irrigated lawns and leaves/organic material on impermeable surfaces contribute to bacteria loads.
*In cold climates where deicers are applied, chloride concentrations are a function of deicer application rates. Chloride concentrations are therefore highly variable in areas where deicers are applied.
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*In cold climates where deicers are applied, chloride concentrations are a function of deicer application rates. Chloride concentrations are therefore highly variable in areas where deicers are applied. Also note that within a land use receiving high inputs of chloride-deicers, chloride emcs vary with season.
*Oxygen demand
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*<span title="The 5 day biochemical oxygen demand, or BOD5, is water quality parameter. BOD5 measures the quantity of biodegradable organic matter contained in water. This biodegradable organic matter is evaluated using the oxygen consumed by the microorganisms involved in natural purification mechanisms."> '''Oxygen demand'''</span> is typically related to the amount of organic carbon in runoff. Thus, land uses with greater inputs of organic material (e.g. residential) will have greater oxygen demand.
*Concentrations of several organic chemicals, such as pesticides and chlorinated compounds, varies. Factors affecting concentrations include industrial sources, presence of contaminated sites, and historic use of these materials, and atmospheric deposition.
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*Concentrations of several organic chemicals, such as pesticides and chlorinated compounds, varies. Factors affecting concentrations include industrial sources, presence of contaminated sites, historic use of these materials, and atmospheric deposition.
 
*Although the potential for nutrient and bacteria loads is greater in lower density residential areas, the lower amount of directly connected impervious surface typically results in lower emcs for lower density residential land use.
 
*Although the potential for nutrient and bacteria loads is greater in lower density residential areas, the lower amount of directly connected impervious surface typically results in lower emcs for lower density residential land use.
 
*Pollutant concentrations in open, forested, and park areas are lower, primarily due to reduced impervious surface.
 
*Pollutant concentrations in open, forested, and park areas are lower, primarily due to reduced impervious surface.
 
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*There is limited information on many of the newer chemicals, such as commercial-consumer compounds, veterinary and human pharmaceuticals, lifestyle and personal care compounds, and others. These chemicals, generically labeled as contaminants of emerging concern (CEC), have variable sources, including industry, sediment, and atmospheric deposition. For more information, see [https://www.researchgate.net/profile/Richard_Kiesling/publication/326916617_Contaminants_of_emerging_concern_in_urban_stormwater_Spatiotemporal_patterns_and_removal_by_iron-enhanced_sand_filters_IESFs/links/5b85452192851c1e12372f0f/Contaminants-of-emerging-concern-in-urban-stormwater-Spatiotemporal-patterns-and-removal-by-iron-enhanced-sand-filters-IESFs.pdf Fairbairn et al.] (2018), [https://s3.amazonaws.com/academia.edu.documents/45895946/An_adaptive_comprehensive_monitoring_str20160523-5773-8srpfw.pdf?response-content-disposition=inline%3B%20filename%3DAn_Adaptive_Comprehensive_Monitoring_Str.pdf&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIATUSBJ6BAPKX5XEDF%2F20200408%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20200408T195551Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjENP%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaCXVzLWVhc3QtMSJGMEQCIGSCyrrMYy%2BuVHdyQfJPgZjqxxFH5Rs1ctKGA2tQmHKsAiAhlXJZSRibwYsi8yZ2%2FsxXMLv47nl4uVZjgEVnKwAnZCq9Awjc%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F8BEAAaDDI1MDMxODgxMTIwMCIMgFAXNG4YnXqBODmoKpEDa3c1Z56IvbZSbxrH8zcWtbG1u072FjwEYCv%2FcqJtf5dI3DCCe5NBPE0v3VHAb%2BcFs9qpmkuPsNCnYWoHsNsanczc%2FnjW5b24lEEOFzBNaeZGF5Z3bJ0SsIBpUXT1%2FDZuqw%2B5PHtfF2Q1KsvWUBaRehz%2FKGkH74W4adiUFWE3hLXxF%2FbrUaUMRdS0GgY%2F3fU0scSMyInNZwIp%2F0kGBpn83nfRp0Y2MT2HDZSzGIla8%2FCDcRGMFJYP1mElttYs9ifnoFaRggTSmEGaGiTDQIswM0W9Tg7HBn207L11%2Fro09PcCX4UXxF6ZFa6I7RuqUqMzQQTs42Hjq46AzQtSZv1DubBFyTCo4VSWJMBx93nZXgNAu%2FwBwrds1Vdwn%2FGvZQxQznVudl3iB7L02fhu97qhTWFq3IsiTacYLIp8u3MTjIdVMTsDCIeVoB2QOELo0BT0eo%2BposdUDYE3c286OlbEOtEyhi%2B2R07JM0fuFeU17fW50MDLCl5vu1tBDaaeHHEIGLWmGrCkGmeV5o8Ftq5gRNswn6%2B49AU67AFIO6wbpOn4syV%2Fhug5bJ%2Fv4tuMmGGEwXN%2FW7TL2PNzxR%2Bh%2BlB%2BPMkm06N4t%2Fs7ZbElqZxqZz3i2%2Brv2BlPkcLRXbY43saLMtXNvLVh1nzDfsXLC88wa1Bb0IZAD8bWNIg9kaP9GU4FD%2FcgpEWnP6apnVDf4NcX268aP9Cn%2FcJyrde46MVHoKdVujCDlcgmNrbCLKTa1YijzBxfUzYoqSsULblGCExoiEeCiJwEcFaQxPK9X8ZVAWq2l8R%2BlQIdfAefcdqWaUkGu79vVwQ0qrV95J3rN%2BM1orfsHKBR7cuvKeQIOOe2AtxDsm1FuA%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=904eb30b3d400616844158aba10b05631e15d16763c052c274ac43849adf0e11 Maruya] (2013), [https://pubs.acs.org/doi/10.1021/acs.est.9b02867 Masoner et al.] (2019), and [https://www.sciencedirect.com/science/article/pii/S0048969718336465 Kiesling et al.] (2019).
Because of the variability in emcs across different land uses, it is beneficial to consider different land uses when calculating pollutant loads. Compositing emcs across land uses is generally not recommended.
 
  
 
{{:Curve numbers for antecedent mositure condition 2}}
 
{{:Curve numbers for antecedent mositure condition 2}}
  
====Effects of season====
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===Effects of season===
 
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For most pollutants, there are few studies of seasonal effects on emcs. The most extensive study is that of [https://www.esf.edu/EFB/mitchell/Brezonik&Stadelmann2002.pdf Brezonik and Stadelmann] (2002). The limited information suggests the following.
==Literature review of event mean concentration (emc) values)==
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*Ranges (variability) of emcs are largest in spring
 
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*Median concentrations of many chemicals is higher in the initial spring flush
==Recommended event mean concentration (emc) values==
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*For individual pollutants, the following are observed.
As a result of our literature review we developed recommended emc values. These are summarized in the following table.
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**TSS concentrations are highest in winter and decrease throughout the year
 
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**Total phosphorus concentrations are highest in winter and fall
For phosphorus and total suspended solids, we developed a broader discussion of emcs. We suggest you read these sections if using emcs for your stormwater applications.
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**Dissolved and soluble reactive phosphorus concentrations are highest in winter
 
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**Chemical oxygen demand is highest in winter
===Phosphorus emcs===
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**Inorganic nitrogen concentrations are highest in winter
Data from the following studies was used to generate emcs for '''total phosphorus'''.
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**Organic nitrogen concentrations are highest in spring
*National Stormwater Quality Database. This dataset provides data from several nationwide studies. We used only data from region 1, which includes Minnesota and states with similar rainfall patterns. Data were compiled for four land uses: Commercial (n=165), industrial (n=84), residential, (n=249), and open space (n=6).
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**Bacteria concentrations are highest in summer
*[https://apps.dtic.mil/dtic/tr/fulltext/u2/a430436.pdf Lin (Review of Published Export Coefficient and Event Mean Concentration (EMCs) Data]. This report includes summaries of multiple studies conducted in North America. Data existed for all land uses included in the table presenting recommended emcs.
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**Chloride concentrations are highest in winter
*[http://dcstormwaterplan.org/wp-content/uploads/AppD_EMCs_FinalCBA_12222014.pdf Washington District Department of the Environment - Selection of Event Mean Concentrations (EMCs)]. This study summarized data from studies in the Washington D.C. area. Land uses included commercial, roadway/highway, industrial, forest/open, and residential.
 
*[https://www3.epa.gov/npdes/pubs/sw_nurp_vol_1_finalreport.pdf U.S. Environmental Protection Agency, 1983, Results of the Nationwide Urban Runoff Program—Executive summary]. Land uses included commercial and residential.
 
*[https://pubs.usgs.gov/wri/wri984158/pdf/wri98-4158.pdf Urban Stormwater Quality, Event-Mean Concentrations, and Estimates of Stormwater Pollutant Loads, Dallas-Fort Worth Area, Texas, 1992–93]. Included commercial (n=42), residential (n=77), industrial (n=63) land uses.
 
*[https://ewater.org.au/uploads/files/Water%20quality%20review_Bartley%20and%20Speirs_Final.pdf A review of sediment and nutrient concentration data from Australia for use in catchment water quality models ]. A compilation of multiple studies from Australia. Included forest (n=68) and mixed (n=36) land uses.
 
*[https://www.hindawi.com/journals/tswj/2013/964737/ Characterization of Urban Runoff Pollution between Dissolved and Particulate Phases ]. Study of five sites in China. Land uses included roof and transportation (roads).
 
*[https://pubs.usgs.gov/of/1996/0458/report.pdf Quality Of Wisconsin Stormwater, 1989-94]. Samples from mixed land use in Wisconsin (n=204).
 
*[https://www.researchgate.net/publication/263627021_Analysis_of_Nonpoint_Source_Pollution_Runoff_from_Urban_Land_Uses_in_South_Korea Analysis of Nonpoint Source Pollution Runoff from Urban Land Uses in South Korea]. 23 samples in Korea from high density residential, medium desntiy residential, industrial, institutional land uses.
 
*[https://www.unh.edu/unhsc/sites/unh.edu.unhsc/files/pubs_specs_info/jee_3_09_unhsc_cold_climate.pdf Seasonal Performance Variations for Storm-Water Management Systems in Cold Climate Conditions]. 15 samples from transportation land use in New Hampshire.
 
*[http://eeer.org/journal/view.php?number=374 Determination of event mean concentrations and first flush criteria in urban runoff]. 31 samples from transportation land use in Los Angeles.
 
*[https://www.sciencedirect.com/science/article/pii/S1001074209602035 Multiple linear regression models of urban runoff pollutant load and event mean concentration considering rainfall variables]. 45 samples from commercial, industrial, and high density land uses.
 
*[https://www.nature.com/articles/s41598-018-29857-x Stormwater runoff driven phosphorus transport in an urban residential catchment: Implications for protecting water quality in urban watersheds]. 29 events from low density land use in Florida.
 
*[https://stormwater.pca.state.mn.us/images/2/2d/USGS_paper_sources_of_phosphorus.pdf Sources of phosphorus and street dirt from Two Urban Residential Basins in Madison, Wisconsin, 1994-95]. 25 samples from medium density land use in Wisconsin.
 
*[https://erams.com/co-stormwater-center/wp-content/uploads/2017/09/Nutrient_Sources_Literature_Review-2017-6-5RefUpdate.pdf Nutrient Sources in Urban Areas – A Literature Review]. Report summarizing multiple studies in Colorado. Land uses include residential, mixed, commercial, and open space.
 
*[https://link.springer.com/article/10.1007/s12665-014-3682-y Contribution of surface runoff from forested areas to the chemistry of a through-flow lake]. Forested land use in Poland.
 
  
The following table summarizes results from our literature review. The table includes a range of values observed in the literature. Note this range does not represent a statistically-derived range but instead is based on a combination of data analysis and best professional judgement. For example, we did analyze the data for outliers, but also omitted entire studies if we felt the data were not representative of typical conditions likely to be encountered in Minnesota. To see the full range of values compiled from the literature, open the Excel spreadsheet containing the data.
+
===Effects of rainfall characteristics===
 +
Several studies indicate rainfall characteristics are very important when assessing pollutant loads for discrete events or discrete time periods. When assessing loads on an annual basis, these factors are less important.
  
{{:Event mean concentrations for total phosphorus}}
+
Rainfall factors affecting emcs include the following.
 +
*Duration between rain events. As the duration between events increases, pollutants build up on impervious surfaces, resulting in increased pollutant concentrations when runoff occurs. The first flush effect becomes more pronounced as the interval between runoff events increases.
 +
*Short duration, higher intensity rain events result in higher concentrations of solids, pollutants associated with solids, oil, grease, and other relatively soluble organic pollutants
 +
*Longer duration, lower intensity rain events result in higher concentrations of dissolved nutrients (phosphorus and nitrogen), as these typically result from leaching from organic material
 +
*Greater runoff volumes result in lower emcs over an entire runoff event, as a result of dilution
  
====Dissolved and particulate phosphorus====
+
===Effects of connected impervious surface and watershed characteristics===
In many places in this manual and in the MIDS calculator, we assume that particulate phosphorus accounts for 55 percent of total phosphorus and dissolved phosphorus for 45 percent of total phosphorus.
+
First flush effects are greatest in small watersheds with a high degree of connected impervious surfaces.
  
==Data on event mean concentrations==
+
==Event mean concentrations for different pollutants==
Below are data we've compiled during our literature review.
+
Tabled values of recommended emcs are found at the following page - [[Stormwater event mean concentrations and pollutant loading/export rates for different land uses]]. For some pollutants, we developed individual pages with a literature review and discussion.
*[http://www.bmpdatabase.org/nsqd.html National Stormwater Quality Database]. The National Stormwater Quality Database (NSQD) is an urban stormwater runoff characterization database developed under the direction of Dr. Robert Pitt, P.E., of the University of Alabama and the Center for Watershed Protection under support from the U.S. Environmental Protection Agency.
+
*[[Event mean concentrations of total and dissolved phosphorus in stormwater runoff]]
 +
*[[Event mean concentrations of total suspended solids in stormwater runoff]]
  
 
==References==
 
==References==
 +
*Acharya, A., and T. Piechota. 2010. [https://www.researchgate.net/publication/267200251_Characterization_of_First_Flush_Phenomenon_in_an_Urban_Stormwater_Runoff_A_Case_Study_of_Flamingo_Tropicana_Watershed_in_Las_Vegas_Valley Characterization of First Flush Phenomenon in an Urban Stormwater Runoff: A Case Study of Flamingo Tropicana Watershed in Las Vegas Valley]. World Environmental and Water Resources Congress 2010: Challenges of Change. American Society of Civil Engineers. p 3365-3375. 10.1061/41114(371)347.
 +
*Baldys III, S., T.H. Raines, B.L. Mansfield, and J.T. Sandlin. 1998. [https://www.semanticscholar.org/paper/Urban-stormwater-quality%2C-event-mean-and-estimates-Baldys-Raines/c8ffa3331750ead92c7ee74c2c46234fbe2572b9 Urban Stormwater Quality, Event-Mean Concentrations, and Estimates of Stormwater Pollutant Loads, Dallas-Fort Worth Area, Texas, 1992–93]. U.S. Geological Survey Water-Resources Investigations Report 98–4158.
 +
*Bannerman, Roger T., Andrew D. Legg, and Steven R. Greb. 1996. [https://pdfs.semanticscholar.org/850e/ccf19feb2157c170ebdada940d30f9426711.pdf Quality Of Wisconsin Stormwater, 1989-94]. U.S. Geological Survey. Open-File Report 96-458.
 +
*Bannerman, R.T., D. W.Owens,R. B.Dodds, and N. J. Hornewer. 1993. [https://www.fws.gov/southwest/es/Documents/R2ES/LitCited/4TX_Sal/Bannerman_1993_Pollutants_in_stormwater.pdf Sources of Pollution in Wisconsin Stormwater]. Wac Sci tech 28:3-5. pp. 241-259.
 +
*Bartley, Rebecca, and William Speirs. 2010. [https://ewater.org.au/uploads/files/Water%20quality%20review_Bartley%20and%20Speirs_Final.pdf A review of sediment and nutrient concentration data from Australia for use in catchment water quality models]. eWater Cooperative Research Centre Technical Report.
 +
*Brezonik PL, Stadelmann TH.. 2002. [https://www.esf.edu/EFB/mitchell/Brezonik&Stadelmann2002.pdf Analysis and predictive models of stormwater runoff volumes, loads, and pollutant concentrations from watersheds in the Twin Cities metropolitan area, Minnesota, USA]. Water Res. Apr;36(7):1743-57. DOI: 10.1016/s0043-1354(01)00375-x
 +
*Erickson, A.J., P.T. Weiss, J.S. Gulliver, R.M. Hozalski. [http://stormwaterbook.safl.umn.edu/pollutant-removal/analysis-individual-storm-events Analysis of individual storm events, Stormwater Treatment: Assessment and Maintenance]. Accessed December 31, 2019.
 +
*Gong, Y., X. Liang, X. Li, J. Li, X. Fang, and R. Song. 2016. [https://www.mdpi.com/2073-4441/8/7/278/htm Influence of Rainfall Characteristics on Total Suspended Solids in Urban Runoff: A Case Study in Beijing, China]. Water 2016, 8(7), 278; https://doi.org/10.3390/w8070278
 +
*Hallberg, M., G. Renman. 2008. [http://www.pjoes.com/Suspended-Solids-Concentration-in-Highway-r-nRunoff-during-Summer-Conditions,88100,0,2.html Suspended Solids Concentration in Highway Runoff during Summer Conditions]. Pol. J. Environ. Stud. 17(2):237–241.
 +
*Jung, Jae-Woon, Ha-Na Park, Kwang-Sik Yoon, Dong-Ho Choi, Byung-Jin Lim. 2013. [https://link.springer.com/article/10.1007/s13765-013-3128-3 Event mean concentrations (EMCs) and first flush characteristics of runoff from a public park in Korea]. Journal of the Korean Society for Applied Biological Chemistry. October 2013, Volume 56, Issue 5, pp 597–604.
 +
*Kim, Lee-Hyung. 2003. [http://eeer.org/upload/eer-8-4-163-1.pdf Determination of event mean concentrations and first flush criteria in urban runoff]. Environ. Eng. Res. 8:4:163-176.
 +
*Li D, Wan J, Ma Y, Wang Y, Huang M, Chen Y. 2015. [https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118776 Stormwater Runoff Pollutant Loading Distributions and Their Correlation with Rainfall and Catchment Characteristics in a Rapidly Industrialized City]. PLoS ONE 10(3): e0118776. doi:10.1371/journal.pone.0118776
 +
*Maniquiz, Marla C. , Soyoung Lee, Lee-Hyung Kim. 2010. Multiple linear regression models of urban runoff pollutant load and event mean concentration considering rainfall variables. Jour Environ. Sci. 22:6:946-852.
 +
*Maniquiz, Marla C., Jiyeon Choi, Soyoung Lee, Hye Jin Cho, Lee-Hyung Kim. 2010. [https://pdfs.semanticscholar.org/e24b/670b01617980cf9458bcf868c8feaebded74.pdf Appropriate Methods in Determining the Event Mean Concentration and Pollutant Removal Efficiency of a Best Management Practice]. Environmental Engineering Research. 15:215-223.
 +
*Pan X, Jones KD. 2012. [https://watermark.silverchair.com/1076.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAAg4wggIKBgkqhkiG9w0BBwagggH7MIIB9wIBADCCAfAGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQMLHtL0TgjAGht8fqmAgEQgIIBwUMowFdEbGwUU0U6Grns7odipRlBlGWEJ_4O4e20hHld5X5e3xfmXgZbuV7eF8bIJEtdlzU8XMfOys83AaKgFXU1_UXKLthtE6PaYALaMcW49rcKwcg_24CUNu3YQgk1tnppulHOzvatpn10FUVlRrJp4vsshFsLFKyKR5N7P4RZbpz3CN03RCXEHfPlGW8mODFO0-Oq_up_C6Yjf7y-IdSVjYyJ5ms0UzUahkAsAL75DTEK5dqwmLhGc3zDqvvgCZqEoq73c8aMmGHiugcqMXNiKs0B5_BlaKOzLVGeaxCzwVI7g6tglqgOKSlImay5QcPLjEuSzqSBkqrmEdaehHCsSbmWUgf2daMFBakt49HTOHj1IIVqxeps3z8BpgEZHKV3M4XNhOxiDt2S8rvSu0SnbKul6gSCvgVsIuScYrgfEU8upepmDex21aLUu5ZgYmwuhIkH8zbF7wlSv411aBc044qCctNLwDTzmbKERqZMoehwHIUGtjnOvA8ZgnQhtNGpbYsrP19IK8b73ASfVJ5S0Rcp-MKqbjZ1wqYyPTQjp4Lj52exmnZ1dZH70hO3FhZJTDlQ6Qkgop6Kr-AP23Bs Seasonal variation of fecal indicator bacteria in storm events within the US stormwater database]. Water Sci Technol. 65(6):1076-80. doi: 10.2166/wst.2012.946.
 +
*Schiff, Kenneth C., and Liesl L. Tiefenthaler. 2011. [https://onlinelibrary.wiley.com/doi/full/10.1111/j.1752-1688.2010.00497.x Seasonal flushing of pollutant concentrations and loads in urban stormwater]. Jour. Amer. Water Works Assoc. 47:1:136-143
 +
*Schiff, Kenneth C., and Liesl L. Tiefenthaler. 2016. [https://www.mdpi.com/2073-4441/8/8/320 Effects of Rainfall Intensity and Duration on the First Flush from Parking Lots]. Water. 8(8), 320. https://doi.org/10.3390/w8080320
 +
*Stein, Eric D., Liesl L. Tiefenthaler and Kenneth C. Schiff. 2008. [http://ftp.sccwrp.org/pub/download/DOCUMENTS/AnnualReports/2008AnnualReport/AR08_015_027.pdf Comparison of stormwater pollutant loading by land use type]. Southern California Coastal Water Research Project, AR08-015-027.
 +
*Stein, Eric D., Liesl L. Tiefenthaler and Kenneth C. Schiff. 2007. [http://ftp.sccwrp.org/pub/download/DOCUMENTS/TechnicalReports/510_pollutant_loading.pdf SOURCES, PATTERNS AND MECHANISMS OF STORM WATER POLLUTANT LOADING FROM WATERSHEDS AND LAND USES OF THE GREATER LOS ANGELES AREA, CALIFORNIA, USA].  Technical Report 510.
 +
*Stenstrom, M.K., and M. Kayhanian. 2005. [https://www.researchgate.net/publication/288208061_First_flush_phenomenon_characterization First Flush Phenomenon Characterization]. Prepared for: California Department of Transportation. 81 p.
 +
*Tiefenthaler, L.L., K. C. Schiff, and M. K. Leecaster. 1997. [http://ftp.sccwrp.org/pub/download/DOCUMENTS/AnnualReports/1999AnnualReport/04_ar04.pdf Temporal variability patterns of stormwater concentrations in urban stormwater runoff].
 +
*University of Wisconsin at Milwaukee. [https://www.mmsd.com/application/files/6214/8192/3796/1103620Phosphorus20Speciation.pdf Phosphorus Speciation and Loads in Stormwater and CSOs of the MMSD Service Area (2000 – 2008) Final Report]: February, 2011
 +
*Wang, Shumin, Qiang Hea, Hainan Aia, Zhentao Wanga, and Qianqian Zhang. 2013. [https://www.sciencedirect.com/science/article/pii/S1001074211610322 Pollutant concentrations and pollution loads in stormwater runoff from different land uses in Chongqing]. Journal of Environmental Sciences. Volume 25, Issue 3, Pages 502-510. https://doi.org/10.1016/S1001-0742(11)61032-2.
 +
*Washington District Department of the Environment. 2014. [http://dcstormwaterplan.org/wp-content/uploads/AppD_EMCs_FinalCBA_12222014.pdf Selection of Event Mean Concentrations (EMCs)].
 +
*Yang, Yun-Ya, and Gurpal S. Toor. 2018. [https://www.nature.com/articles/s41598-018-29857-x  runoff driven phosphorus transport in an urban residential catchment: Implications for protecting water quality in urban watersheds]. Scientific Reports. 8:1-10
  
 
==Related pages==
 
==Related pages==
 +
*[[Stormwater event mean concentrations and pollutant loading/export rates for different land uses]]
 +
*[[Total Suspended Solids (TSS) in stormwater]]
 +
*[[Event mean concentrations of total and dissolved phosphorus in stormwater runoff]]
 +
*[[Event mean concentrations of total suspended solids in stormwater runoff]]
 +
*[[Bacteria in stormwater]]
  
 
<noinclude>
 
<noinclude>
 
[[category:pollutants]]
 
[[category:pollutants]]
 
</noinclude>
 
</noinclude>

Latest revision as of 16:04, 9 April 2020

This site is currently undergoing final review. For more information, open this link.
This page is under review
image turbid runoff
Suspended sediment in stormwater runoff

Because of the expense and difficulty of monitoring stormwater runoff, we often rely on published information to estimate pollutant loading associated with runoff. Models or other tools are often used to predict pollutant loading. These models and tools require information on the pollutant concentration in runoff. For example, the Simple Method, which is commonly used to estimate pollutant loading, utilizes the following equation

\(L = 0.227 P P_j R_v C A\)

where

L = Load of a pollutant in pounds per year;
P = Rainfall depth per year (inches);
Pj = Fraction of rainfall events that produce runoff;
Rv = Runoff coefficient, which expresses the fraction of rainfall which is converted into runoff. Rv = 0.05 + 0.009(I);
I = Site imperviousness (i.e., I = 75 if site is 75% impervious);
C = Flow-weighted mean concentration of the pollutant in urban runoff (mg/l); and
A = Area of the development site (acres).

This page provides a discussion of pollutant concentrations in stormwater runoff, including a review of literature and links recommended values to use.

Factors affecting actual and measured storm concentrations

The actual concentration of a pollutant in stormwater runoff varies with several factors, including but not limited to

  • land use,
  • time between runoff events,
  • duration and intensity of runoff,
  • characteristics of the pollutant,
  • season,
  • extent of exposed soils, such as with construction sites, and
  • extent of connected impervious surfaces.

In addition, the measured concentration varies with factors related to measurement, including but not limited to

  • type of sampling equipment and sample collection,
  • location of sampling,
  • frequency of sampling,
  • laboratory analysis, and
  • data analysis.

This variability presents challenges in estimating pollutant loading, but having accurate estimates of pollutant concentrations is necessary to accurately calculate pollutant loading and reductions in loading associated with implementation of stormwater practices and to accurately select and design appropriate practices to treat runoff.

Event mean concentrations

In the absence of monitoring data for a specific study or location, we often use event mean concentrations (emc). The emc represents the average pollutant concentration for a given stormwater event, expressed in units of mass per volume (e.g., mg/L). Given the number of factors affecting pollutant concentration, determining an appropriate emc is challenging.

Despite challenges in accurately determining emcs, they are widely used in stormwater applications. Emcs are used in many stormwater water quality models and calculations of pollutant loading. They are therefore fundamental to understanding pollutant loads and how to address reducing pollutant loads in stormwater runoff.

Calculating emcs

Emcs should represent the flow proportional concentration of a given pollutant parameter during storm events. The simplest way to calculate and emc is therefore to divide the total mass of a pollutant by the total runoff volume. Emcs can also be calculated as the sum, over multiple discrete time intervals within an event, of volume times the concentration for the time interval, divided by the total volume for the event

\( emc = (∫^t_0 C_tQ_td_t) / (∫^t_0 Q_td_t) ≅ (Σ C_tQ_tΔt) / (ΣQ_tΔt) \)

where Ct and Qt are the concentration and flow volume over a discrete time interval dt (Δt).

Erickson et al. provide detailed discussion and examples for calculating pollutant loading from stormwater runoff. The emc calculated for a specific event is a function of the sampling method. Erickson et al. discuss the following methods for sampling.

image for emcs
Example of how emcs can be calculated using concentration and flow data taken at discrete time intervals. In the top example, assume all time intervals are 30. In the lower graph, intervals 1 and 2 from the top graph are combined and Q and C average, while the remaining intervals are left at 30. The emc for the top graph is 69.1 mg/L and 76.0 mg/L for the lower graph, even though the data are the same.
  • Flow-weighted discrete samples: "When samples are collected based on a user-specified constant incremental volume of discharge (e.g., every 1000, 2000, or 5000 gallons) that passes the sampler, the samples are defined as flow-weighted. Each flow-weighted sample is assumed to represent the average pollutant concentration for the entire incremental volume of water to which it corresponds. Each discrete sample is stored in an individual container, and the contents of each container are analyzed separately."
  • Flow-weighted composite samples: "Flow-weighted composite samples are collected every time a user-specified constant volume of flow passes the sampler and all samples are stored in a single container. To determine pollutant concentration, an aliquot is collected from the composite sample, and the concentration is assumed to represent that of the entire composite sample."
  • Time-weighted discrete samples: "Time-weighted discrete samples are collected at a user-specified, constant time interval (e.g., 30 minutes), and each sample is stored in a separate container and analyzed separately. Because the magnitude of the discharge during a natural storm event varies over time, each time-weighted sample does not represent a constant volume of discharge."
  • Time-weighted composite samples: "Time-weighted composite samples are collected at equal time increments, and all samples are stored in a single container. ... Time-weighted composite sampling is not recommended."
  • Discrete grab samples: "A grab sample is a single sample collected at one location over a relatively short time period, typically sampling the entire cross-section of water. Discharge must be accurately and continuously measured and the time of each grab sample must be recorded to assess pollutant removal performance. Discrete samples are stored in individual containers, and the contents of each container are analyzed separately."
  • Composite grab samples: "Composite grab samples are typically collected at variable time and volume increments and stored in a single sample storage container. Composite grab sampling is not recommended."

The sampling method affects the resulting calculation of emc. For example, in the adjacent image, emcs were calculated for the same runoff event. In the top portion of the image, sampling occurred every 30 minutes and the overall emc is 69.1 mg/L. In the lower portion of the image, the first two time intervals were combined and Q and C averaged over the 60 minute time interval, while the remaining time intervals were 30 minutes each. The overall emc is 76.0 mg/L. The difference is a result of a bias toward higher concentrations in the early portion of the runoff event for the lower graph. This tendency toward higher pollutant concentrations in the early part of a runoff event is called the first flush.

Washington State developed standard operating procedures for measuring pollutant loads, including emcs. They include procedures for addressing seasonality.

Factors affecting emcs

Many factors affect the emc. The most important factors and how to address them are dicussed below.

What is the first flush?
First flush is a phenomenon in which pollutant concentrations in stormwater runoff are greater in the early portion of a runoff event. First flush is common for relatively uniform land use settings, for winter and early spring runoff events, and for runoff events during fall leaf-drop. During dry periods between runoff events, pollutants build-up on impermeable surfaces. For Type 2 rain distribution, initial rain intensity is low and increases through a storm before decreasing near the end of the storm. The initial runoff is therefore highly concentrated with pollutants that have accumulated on impermeable surfaces. As runoff volume increases during an event and pollutants become more resistant to being washed off, concentrations decrease and typically reach steady state. First flush is not universally applicable to stormwater runoff, however. For example, if higher pollutant buildup on impermeable surfaces occurs in upper portions of a watershed, as might occur in an area with variable land uses, the peak concentration may be delayed as those higher pollutant loads take time to reach a receiving point. Similarly, some pollutants may be resistant to transport in early stages of an event. In other situations, concentrations in runoff may be uniform throughout an event, particularly if rainfall intensities are uniform and pollutants are soluble (e.g. chloride).
schematic of different concentrations in runoff
Schematic illustrating different runoff concentration profiles. Events 1 and 3 show delayed peak concentrations, Event 2 shows a strong first flush effect, and Event 4 a steady concentration profile. See text for discussion.

Land use

Caution: Using an emc for the specific land use being considered is highly recommended. See Stormwater event mean concentrations and pollutant loading/export rates for different land uses for emcs for different pollutants and land uses.
image of land uses
Photos of different land uses

Because of the variability in emcs across different land uses, it is beneficial to consider different land uses when calculating pollutant loads. Compositing emcs across land uses is generally not recommended.

Some generalizations about pollutant loading as a function of land use include the following.

  • Commercial, industrial, and transportation land use typically have higher percentages of impervious and directly connected impervious surface, as shown in the accompanying table summarizing curve numbers for different land uses. This results in more efficient delivery of pollutants and runoff compared to other land uses. Consequently, we expect higher emcs from these land uses for smaller runoff events and when pollutant buildup on impermeable surfaces is greater, and lower emcs for larger runoff events with greater rainfall intensities as a result of dilution.
  • Nutrient (phosphorus, nitrogen) concentrations are greater in residential areas and other land uses that contribute significant amounts of organic material to impermeable surfaces. Dissolved fractions also comprise a greater percent of the total load for these pollutants when the source of the nutrient is organic material.
  • Concentrations of metals increase as road density and traffic volume increase.
  • Concentrations of petroleum-related compounds and polycyclic aromatic hydrocarbons (PAHs) increase as road density and traffic volume increase.
  • Concentrations of total suspended solids (TSS) may be similar across different land uses, but the characteristics of the TSS varies. Organic fractions make up a larger percent of TSS in residential areas and other land uses where there are sources of organic material to impermeable surfaces, while inorganic fractions (e.g. sand, silt) comprise the majority of TSS in settings with low inputs of organic material.
  • Bacteria concentrations are typically greater in residential areas due to greater inputs from domestic animals (e.g. dogs), birds, and other animals. Studies also suggest irrigated lawns and leaves/organic material on impermeable surfaces contribute to bacteria loads.
  • In cold climates where deicers are applied, chloride concentrations are a function of deicer application rates. Chloride concentrations are therefore highly variable in areas where deicers are applied. Also note that within a land use receiving high inputs of chloride-deicers, chloride emcs vary with season.
  • Oxygen demand is typically related to the amount of organic carbon in runoff. Thus, land uses with greater inputs of organic material (e.g. residential) will have greater oxygen demand.
  • Concentrations of several organic chemicals, such as pesticides and chlorinated compounds, varies. Factors affecting concentrations include industrial sources, presence of contaminated sites, historic use of these materials, and atmospheric deposition.
  • Although the potential for nutrient and bacteria loads is greater in lower density residential areas, the lower amount of directly connected impervious surface typically results in lower emcs for lower density residential land use.
  • Pollutant concentrations in open, forested, and park areas are lower, primarily due to reduced impervious surface.
  • There is limited information on many of the newer chemicals, such as commercial-consumer compounds, veterinary and human pharmaceuticals, lifestyle and personal care compounds, and others. These chemicals, generically labeled as contaminants of emerging concern (CEC), have variable sources, including industry, sediment, and atmospheric deposition. For more information, see Fairbairn et al. (2018), Maruya (2013), Masoner et al. (2019), and Kiesling et al. (2019).

Curve numbers for antecedent moisture condition II (Source USDA-NRCS).
Link to this table

Land use description
Hydrologic soil group
A B C D
Meadow - good condition 30 58 72 78
Forest
Poor 45 66 77 83
Fair 36 60 73 79
Good 30 55 70 77
Open space
Poor 68 79 86 89
Fair 49 69 79 84
Good 39 61 74 80
Commercial 85% impervious 89 92 94 95
Industrial 72% impervious 81 88 91 93
Residential
1/8 acre lots (65% impervious) 77 85 90 92
1/4 acre lots (38% impervious) 61 75 83 87
1/2 acre lots (25% impervious) 54 70 80 85
1 acre lots (20% impervious) 51 68 79 84
Impervious areas 98 98 98 98
Roads (including right of way)
Paved 83 89 92 93
Gravel 76 85 89 91
Dirt 72 82 87 89
Row crops
Straight row - good 67 78 85 89
Contoured row - good 65 75 82 86
Pasture - good 39 61 74 80
Open water 99 99 99 99

Effects of season

For most pollutants, there are few studies of seasonal effects on emcs. The most extensive study is that of Brezonik and Stadelmann (2002). The limited information suggests the following.

  • Ranges (variability) of emcs are largest in spring
  • Median concentrations of many chemicals is higher in the initial spring flush
  • For individual pollutants, the following are observed.
    • TSS concentrations are highest in winter and decrease throughout the year
    • Total phosphorus concentrations are highest in winter and fall
    • Dissolved and soluble reactive phosphorus concentrations are highest in winter
    • Chemical oxygen demand is highest in winter
    • Inorganic nitrogen concentrations are highest in winter
    • Organic nitrogen concentrations are highest in spring
    • Bacteria concentrations are highest in summer
    • Chloride concentrations are highest in winter

Effects of rainfall characteristics

Several studies indicate rainfall characteristics are very important when assessing pollutant loads for discrete events or discrete time periods. When assessing loads on an annual basis, these factors are less important.

Rainfall factors affecting emcs include the following.

  • Duration between rain events. As the duration between events increases, pollutants build up on impervious surfaces, resulting in increased pollutant concentrations when runoff occurs. The first flush effect becomes more pronounced as the interval between runoff events increases.
  • Short duration, higher intensity rain events result in higher concentrations of solids, pollutants associated with solids, oil, grease, and other relatively soluble organic pollutants
  • Longer duration, lower intensity rain events result in higher concentrations of dissolved nutrients (phosphorus and nitrogen), as these typically result from leaching from organic material
  • Greater runoff volumes result in lower emcs over an entire runoff event, as a result of dilution

Effects of connected impervious surface and watershed characteristics

First flush effects are greatest in small watersheds with a high degree of connected impervious surfaces.

Event mean concentrations for different pollutants

Tabled values of recommended emcs are found at the following page - Stormwater event mean concentrations and pollutant loading/export rates for different land uses. For some pollutants, we developed individual pages with a literature review and discussion.

References

Related pages


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