Applications for Reuse of Lime Sludge from Water Softening, TR-535, 2005

Lime sludge, an inert material mostly composed of calcium carbonate, is the result of softening hard water for distribution as drinking water. A large city such as Des Moines, Iowa, produces about 30,700 tons of lime sludge (dry weight basis) annually (Jones et al., 2005). Eight Iowa cities representing, according to the United States (U.S.) Census Bureau, 23% of the state’s population of 3 million, were surveyed. They estimated that they collectively produce 64,470 tons of lime sludge (dry weight basis) per year, and they currently have 371,800 tons (dry weight basis) stockpiled. Recently, the Iowa Department of Natural Resources directed those cities using lime softening in drinking water treatment to stop digging new lagoons to dispose of lime sludge. Five Iowa cities with stockpiles of lime sludge funded this research. The research goal was to find useful and economical alternatives for the use of lime sludge. Feasibility studies tested the efficacy of using lime sludge in cement production, power plant SOx treatment, dust control on gravel roads, wastewater neutralization, and in-fill materials for road construction. Applications using lime sludge in cement production, power plant SOx treatment, and wastewater neutralization, and as a fill material for road construction showed positive results, but the dust control application did not. Since the fill material application showed the most promise in accomplishing the project’s goal within the time limits of this research project, it was chosen for further investigation. Lime sludge is classified as inorganic silt with low plasticity. Since it only has an unconfined compressive strength of approximately 110 kPa, mixtures with fly ash and cement were developed to obtain higher strengths. When fly ash was added at a rate of 50% of the dry weight of the lime sludge, the unconfined strength increased to 1600 kPa. Further, friction angles and California Bearing Ratios were higher than those published for soils of the same classification. However, the mixtures do not perform well in durability tests. The mixtures tested did not survive 12 cycles of freezing and thawing and wetting and drying without excessive mass and volume loss. Thus, these mixtures must be placed at depths below the freezing line in the soil profile. The results demonstrated that chemically stabilized lime sludge is able to contribute bulk volume to embankments in road construction projects.

Methods for Estimating Annual Exceedance-Probability Discharges for Streams in Iowa, Based on Data through Water Year 2010, TR-519, 2013

A statewide study was performed to develop regional regression equations for estimating selected annual exceedance- probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedanceprobability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized leastsquares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized leastsquares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97.9 percent for flood region 2, and 92.4 to 96.0 percent for flood region 3. The regression equations are applicable only to stream sites in Iowa with flows not significantly affected by regulation, diversion, channelization, backwater, or urbanization and with basin characteristics within the range of those used to develop the equations. These regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the eight selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided by the Web-based tool. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these eight selected statistics are provided for the streamgage.

Carbonate Rock Pore Size Distribution Determination through Iowa Pore Index Testing, MLR-15-01, 2015

The Iowa Pore Index (IPI) measures the pore system of carbonate (limestone and dolomite) rocks using pressurized water to infiltrate the pore system. This technique provides quantitative results for the primary and capillary (secondary) pores in carbonate rocks. These results are used in conjunction with chemical and mineralogical test results to calculate a quality number, which is used as a predictor of aggregate performance in Portland cement concrete (PCC) leading to the durability classification of the aggregate. This study had two main objectives: to determine the effect different aggregate size has on IPI test results and to establish the precision of IPI test and test apparatus. It was found that smaller aggregate size fractions could be correlated to the standard 1/2”-3/4” size sample. Generally, a particle size decrease was accompanied by a slight decrease in IPI values. The IPI testing also showed fairly good agreement of the secondary pore index number between the 1/2”-3/4”and the 3/8”-1/2” fraction. The #4-3/8” showed a greater difference of the secondary number from the 1/2”-3/4” fraction. The precision of the IPI test was established as a standard deviation (Sr) of 2.85 (Primary) and 0.87 (Secondary) with a repeatability limit (%r) of 8.5% and 14.9% for the primary and secondary values, respectively.