Effects of Wind Direction on Trace Metal Concentration in Southeast Kansas

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Information about Effects of Wind Direction on Trace Metal Concentration in Southeast Kansas

Published on February 27, 2014

Author: sergioalain

Source: slideshare.net

Effects of Wind Direction on Trace Metal Concentration in Southeast Kansas Sergio A. Guerra, Dennis D. Lane, Glen A. Marotz, Ray E. Carter, Richard W. Baldauf, Carrie M. Hohl Department of Civil, Environmental, and Architectural Engineering, University of Kansas

Introduction  Southeast Kansas supports the highest concentration of hazardous waste burners in the country  3 cement kilns  1 commercial hazardous waste incinerator  U.S. EPA sponsored the Southeast Kansas Health Study to investigate air quality and potential health effects from ambient air in the area  (report available at http://www2.kumc.edu/ceoh/skhs/)  This study was a joint effort between the Department of Civil and Environmental Engineering at KU and the KU Medical Center

Scope The environmental sampling element of the project included the determination of trace metal concentrations from PM2.5 collected in Teflon filters in Southeast Kansas. Effects of spatial and temporal factors on these concentrations were investigated Wind direction effects are of particular interest

Air Quality Monitoring March to October, 2000 Sampling Sites in the cities of Chanute, Coffeyville, Fredonia, and Independence Additional Site in Labette County Sampling Site Design, Sampling and Analysis Protocols According to EPA Guidelines

Sampling Area in Southeast Kansas

Fredonia Site Name Site Code Fredonia- Lincoln School FLS Fredonia- South Farm FSF Fredonia- South Mound FSM Independence- Eisenhower School IES Independence- Radio Tower IRT Independence- East of River IER Chanute- North Ash Grove CNA Chanute- South Ash Grove CSA Chanute- Elderly Care Center CEC Labette County- Big Hill Lake LCL

Source-specific sites  Wichita windrose (1984-1992)

Data Collection- MiniVOL

 Filters of PM2.5 samples from each sampling day were selected  Filters were digested and analyzed by ICP/MS for 20 metals

Data Analysis Descriptive statistics were calculated for all trace metal concentrations Analyses of variance (anovas) were performed on: Possible effects of sampling site Possible effects of sampling date Analogous non-parametric tests also performed to confirm anova results

Data Analysis  The effect of wind direction on PM concentrations was further investigated by performing a General Linear Model (GLM) Data was divided in four wind direction categories (from NCDC);  South  North  Calm/variable  Other  The effect of the targeted sources was also analyzed by using the paired t-test and the analogous non-parametric test

Integrated Risk Information System (IRIS) Metal Concentration (µg/m3) producing risk levels 1 in 10,000 1 in 100,000 1 in 1,000,000 Be 0.04 0.004 0.0004 Cr(VI) 0.006 0.0006 0.00006 As 0.02 0.002 0.0002 Cd 0.06 0.006 0.0006 Al, V, Fe, Co, Rb Mn, Ni, Cu, Zn, Se, Mo, Ag, Sb, Ba, Tl Pb Not listed as hazardous air pollutants Not assessed under IRIS program Carcinogen Assessment Group recommends that numerical estimate not be used  Mean Chromium conc. was found to exceed the 1 in 100,000 risk level  Mean and median arsenic conc. exceeded the 1 in 1,000,000 risk level  Mean cadmium conc. exceeded the 1 in 1,000,000

Six metals were chosen for thorough analysis Beryllium Chromium Arsenic Cadmium Barium Lead

Results  Anova and Kruskal-Wallis analysis shows: Site is not a statistically significant factor for any metals (95% confidence) Temporal factor was found to be statistically significant for chromium, arsenic, cadmium, barium and lead  Temporal factor was further investigated through temperature, wind speed and atmospheric variables

Sampling dates were divided into North, South, calm/variable and other categories GLM was run to determine the effect of site and wind direction; site and wind direction interaction Wind direction was significant for chromium, barium, and lead at 95% confidence level Wind direction was significant for arsenic at 90% confidence level

 Anova and Kruskal-Wallis tests were run on the database used for the GLM Wind direction was not statistically significant for beryllium, arsenic and cadmium Wind direction was statistically significant for chromium, barium and lead  Calm/variable winds produced highest chromium concentrations  North winds produced highest barium concentrations  South winds and calm/variable winds produced the highest lead concentrations

Upwind versus downwind samples The effect of selected sources was tested by applying the t-test and analogous nonparametric test Data included upwind and downwind samples for cities of Chanute, Independence and Fredonia Differences between upwind and downwind samples were not found statistically significant at the 95% level

Conclusions  Mean chromium concentration exceeded the 1 in 100,000 risk level Though risk level is for Cr(VI)  Mean arsenic and cadmium concentrations exceeded the 1 in 1,000,000 risk level  Sampling site was not significant for beryllium, chromium, cadmium, arsenic, barium and lead  Sampling day was significant for all metals except beryllium

Conclusions…  Calm/ variable winds produced the highest chromium concentrations  Predominantly north winds produced the highest barium concentrations  Predominantly south and calm/variable winds produced the highest lead concentrations  No statistically significant differences were found between samples upwind and downwind from targeted sources

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