Development of statistical linear regression model for metals from transportation land uses.
The transportation landuses possessing impervious surfaces such as highways, parking lots, roads, and bridges were recognized as the highly polluted non-point sources (NPSs) in the urban areas. Lots of pollutants from urban transportation are accumulating on the paved surfaces during dry periods and are washed-off during a storm. In Korea, the identification and monitoring of NPSs still represent a great challenge. Since 2004, the Ministry of Environment (MOE) has been engaged in several researches and monitoring to develop stormwater management policies and treatment systems for future implementation. The data over 131 storm events during May 2004 to September 2008 at eleven sites were analyzed to identify correlation relationships between particulates and metals, and to develop simple linear regression (SLR) model to estimate event mean concentration (EMC). Results indicate that there was no significant relationship between metals and TSS EMC. However, the SLR estimation models although not providing useful results are valuable indicators of high uncertainties that NPS pollution possess. Therefore, long term monitoring employing proper methods and precise statistical analysis of the data should be undertaken to eliminate these uncertainties.
Maniquiz
Marla C
MC
Department of Civil & Environmental Engineering, Kongju National University, Seobuk-gu, Chungnam, Republic of Korea.
Lee
Soyoung
S
Lee
Eunju
E
Kim
Lee-Hyung
LH
D004784:Environmental Monitoring / Q000379:methods*; D005843:Geography; D016014:Linear Models; D008670:Metals / Q000032:analysis*; D015233:Models, Statistical; D014186:Transportation; D014872:Water Movements; D014874:Water Pollutants, Chemical / Q000032:analysis*
D008670:Metals; D014874:Water Pollutants, Chemical