Public health assessment : Railroad Avenue groundwater contamination, West Des Moines, Polk County, Iowa EPA facility ID: IA0001610963 (2004)

The Railroad Avenue groundwater contamination site (the site) is in West Des Moines, Polk County, Iowa. Located on approximately 120 acres. The site comprises mixed residential, industrial and commercial properties. Underneath the site, chlorinated volatile organic compounds (VOCs) have contaminatcd the shallow (i.e., 30-50 feet deep) groundwater. These compounds have compromised several shallow wells within the West Des Moines water works system. A contamination source, however, has not yet been identified. In 1993, routine water analysis by the City of West Des Moines identified 1, 2 cis-dichlorocthylcne (1, 2 cis-DCE) at a concentration of 1.2 μg/L (micrograms) per liter of water) in the water supply. Subsequently. several shallow municipal wells were found to be contaminated by VOCs, including 1. 2 cis-DCE, trichloroethylene (TCE), tetrachloroethylene (PCE) and benzene. Five of these wells have been taken out of service. Because of the impact on the West Des Moines water supply, the U.S. Environmental Protection Agency (USEPA) has assigned the site to the National Priorities List. Surface water und sediment at the site have not been impacted by the VOCs. Testing for VOCs in surface soils has not revealed any significant VOC contamination. Subsurface soils -- generally 8 feet or greater in depth -- are contaminated with VOCs, but at levels which should not present a health hazard. The past, present, and future health hazard category chosen for this site is no apparent public health hazard. This category is used when exposure to toxins might be occurring or might have occurrcd in the past, but at levels below any known health hazard. Analysis of available environmental data has not revealed that residental or commercial water customers are or have been exposed to VOCs at concentrations that might cause any adverse health effects.

VISSIM Calibration for Urban Freeways, 2015

In urban areas, interchange spacing and the adequacy of design for weaving, merge, and diverge areas can significantly influence available capacity. Traffic microsimulation tools allow detailed analyses of these critical areas in complex locations that often yield results that differ from the generalized approach of the Highway Capacity Manual. In order to obtain valid results, various inputs should be calibrated to local conditions. This project investigated basic calibration factors for the simulation of traffic conditions within an urban freeway merge/diverge environment. By collecting and analyzing urban freeway traffic data from multiple sources, specific Iowa-based calibration factors for use in VISSIM were developed. In particular, a repeatable methodology for collecting standstill distance and headway/time gap data on urban freeways was applied to locations throughout the state of Iowa. This collection process relies on the manual processing of video for standstill distances and individual vehicle data from radar detectors to measure the headways/time gaps. By comparing the data collected from different locations, it was found that standstill distances vary by location and lead-follow vehicle types. Headways and time gaps were found to be consistent within the same driver population and across different driver populations when the conditions were similar. Both standstill distance and headway/time gap were found to follow fairly dispersed and skewed distributions. Therefore, it is recommended that microsimulation models be modified to include the option for standstill distance and headway/time gap to follow distributions as well as be set separately for different vehicle classes. In addition, for the driving behavior parameters that cannot be easily collected, a sensitivity analysis was conducted to examine the impact of these parameters on the capacity of the facility. The sensitivity analysis results can be used as a reference to manually adjust parameters to match the simulation results to the observed traffic conditions. A well-calibrated microsimulation model can enable a higher level of fidelity in modeling traffic behavior and serve to improve decision making in balancing need with investment.