Characterization and prediction of highway runoff constituent event mean concentration
- PMID: 17161904
- DOI: 10.1016/j.jenvman.2006.09.024
Characterization and prediction of highway runoff constituent event mean concentration
Abstract
Highway stormwater runoff quality data were collected from throughout California during 2000-2003. Samples were analyzed for conventional pollutants (pH, conductivity, hardness, and temperature); aggregates (TSS, TDS, TOC, DOC); total and dissolved metals (As, Cd, Cr, Cu, Ni, Pb, and Zn); and nutrients (NO(3)-N, TKN, total P, and ortho-P). Storm event and site characteristics for each sampling site were recorded. A statistical summary for chemical characteristics of highway runoff is provided based on statewide urban and non-urban highways. Constituent event mean concentrations (EMCs) were generally higher in urban highways than in non-urban highways. The chemical characteristics of highway runoff in California were compared with national highway runoff chemical characterization data. The results obtained in California were generally similar to those found in other states. The median EMC for Pb measured in studies conducted in previous decades was much higher than the current median Pb EMC in California. The lower Pb EMC in California compared to previous highway runoff monitoring is believed to be due to the elimination of leaded gasoline. An attempt was also made to identify surrogate constituents within a general family of water quality categories using Spearman correlations and selected pairs with Spearman coefficients greater than 0.8. The strongest correlations were observed among parameters associated with dissolved minerals (EC, TDS, and chloride); organic carbon (TOC and DOC); petroleum hydrocarbons (TPH and O & G); and particulate matter (TSS and turbidity). Within the metals category, total iron concentration was highly correlated with most total metal concentrations. The correlations between total and dissolved concentrations were all less than 0.8, even between total and dissolved concentrations of the same metals. Multiple linear regression (MLR) analyses were performed to evaluate the impact of various site and storm event variables on highway runoff constituent EMCs. Parameters found to have significant impacts on highway runoff constituent EMCs include: total event rainfall (TER); cumulative seasonal rainfall (CSR); antecedent dry period (ADP); contributing drainage area (DA); and annual average daily traffic (AADT). Surrounding land use and geographic regions were also determined to have a significant impact on runoff quality. The MLR model was also used to predict constituent EMCs. Model performance determined by comparing predicted and measured values showed good agreement for most constituents.
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