The remediation of chromium-contaminated sites requires knowledge of the processes that control the migration and transformation of chromium. Advection, dispersion, and diffusion are physical processes affecting the rate at which contaminants can migrate in the subsurface. Heterogeneity is an important factor that affects the contribution of each of these mechanisms to the migration of chromium-laden waters. Redox reactions, chemical speciation, adsorption/desorption phenomena, and precipitation/dissolution reactions control the transformation and mobility of chromium. The reduction of CrVI to CrIII can occur in the presence of ferrous iron in solution or in mineral phases, reduced sulfur compounds, or soil organic matter. At neutral to alkaline pH, the CrIII precipitates as amorphous hydroxides or forms complexes with organic matter. CrIII is oxidized by manganese dioxide, a common mineral found in many soils. Solid-phase precipitates of hexavalent chromium such as barium chromate can serve either as sources or sinks for CrVI. Adsorption of CrVI in soils increases with decreasing chromium concentration, making it more difficult to remove the chromium as the concentration decreases during pump-and-treat remediation. Knowledge of these chemical and physical processes is important in developing and selecting effective, cost-efficient remediation designs for chromium-contaminated sites.

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Processes affecting the remediation of chromium-contaminated sites.

Relations Between Iron Oxides, Soil Color, and Soil Formation

Surface-charge properties and UO22+ adsorption of a subsurface smectite

Clays and clay minerals are common components in soils, sediments, and sedimentary rocks, and they play an important role in many environmental processes. Iron is ubiquitous in clays and clay minerals and its oxidation state, in part, controls the physical and chemical properties of these fine-grained minerals. The structural ferric iron in clay minerals can be reduced either chemically or biologically. Biological reductants include mesophilic and thermophilic microorganisms from diverse environments such as soils, sediments, sedimentary rocks, and hydrothermal hot springs. Multiple clay minerals have been used for microbial reduction studies, including dioctahedral smectiteillite series, palygorskite, chlorite, and their various mixtures in natural soils and sediments. All of these clay minerals are reducible by microorganisms under various conditions with smectite (nontronite) being the most reducible and illite the least. The rate and extent of bioreduction depends on many experimental factors, such as the type of microorganisms and clay minerals, solution chemistry, and temperature. Despite significant efforts, current understanding of the mechanisms of microbial reduction of ferric iron in clay minerals is still limited. Whereas some studies have presented evidence for a solid-state reduction mechanism, others argue that the clay mineral structure partially dissolves when the extent of reduction is high. This inconsistency may be related to several experimental conditions, and their specific effects are discussed in this paper. Whereas past experiments have been largely conducted in well-controlled laboratory systems, recent efforts have attempted to transfer knowledge to the field to improve our understanding of more complex soil systems for better agricultural practices. Biologically reduced clay minerals are also important agents in remediating inorganic and organic contaminants in soil and groundwater systems. This paper reviews the most recent developments and suggests some directions for future research.

http://www.minsocam.org/MSA/AmMin/TOC/Abstracts/2009_Abstracts/ND09_Abstracts/Dong_p1505_09.pdf

Microbe-clay mineral interactions

Smectite clay minerals are abundant in soils and sediments worldwide and are typically rich in Fe. While recent investigations have shown that the structural Fe(III) bound in clay minerals is reduced by microorganisms, previous studies have not tested growth with clay minerals as the sole electron acceptor. Here we have demonstrated that a pure culture of Shewanella oneidensis strain MR-1 as well as enrichment cultures of Fe(III)-reducing bacteria from rice paddy soil and subsurface sediments are capable of conserving energy for growth with the structural Fe(III) bound in smectite clay as the sole electron acceptor. Pure cultures of S. oneidensis were used for more detailed growth rate and yield experiments on various solid- and soluble-phase electron acceptors [smectite, Fe(III) oxyhydroxide FeOOH, Fe(III) citrate, and oxygen] in the same minimal medium. Growth was assessed as direct cell counts or as an increase in cell carbon (measured as particulate organic carbon). Cell counts showed that similar growth of S. oneidensis (10 8 cells ml 1 ) occurred with smectitic Fe(III) and on other Fe forms [amorphous Fe(III) oxyhydroxide, and Fe citrate] or oxygen as the electron acceptor. In contrast, cell yields of S. oneidensis measured as the increase in cell carbon were similar on all Fe forms tested while yields on oxygen were five times higher, in agreement with thermodynamic predictions. Over a range of particle loadings (0.5 to 4 g liter 1 ), the increase in cell number was highly correlated to the amount of structural Fe in smectite reduced. From phylogenetic analysis of the complete 16S rRNA gene sequences, a predominance of clones retrieved from the clay mineral-reducing enrichment cultures were most closely related to the low-GC gram-positive members of the Bacteria (Clostridium and Desulfitobacterium) and the -Proteobacteria (members of the Geobacteraceae). Results indicate that growth with smectitic Fe(III) is similar in magnitude to that with Fe(III) oxide minerals and is dependent upon the mineral surface area available. Iron(III) bound in clay minerals should be considered an important electron acceptor supporting the growth of bacteria in soils or sedimentary environments.

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Growth of iron(III)-reducing bacteria on clay minerals as the sole electron acceptor and comparison of growth yields on a variety of oxidized iron forms.

The reduction and reoxidation of three nontronite samples, GAN (API H-33a, Garfield, Washington), SWa-1 (ferruginous Washington smectite), and NG-1 (Hohen Hagen, Federal Republic of Germany) were studied with visible absorption and Mossbauer spectroscopy. The intensity of the intervalence electron transfer (IT) band at 730 nm in these nontronites was monitored during reduction and reoxidation at 277, 294, and 348 K. The results showed that the intensity of the band followed the number of Fe(II)-O-Fe(III) groups in the clay crystal, increasing to a maximum at about Fe(II): total Fe = 0.4; upon complete reduction, the band decreased to about the intensity of the unaltered, oxidized sample. With reoxidation of the sample with O2, the intensity of the band increased sharply, followed by a gradual decay back to the original, oxidized intensity. The ultimate level of Fe reduction achieved was at least 92%. Concomitantly, the color changed from yellow through green, blue-green, dark blue, light blue, and light gray as the Fe(II) content increased. The GAN nontronite was more difficult to reduce than the SWa-1 or NG-1 samples. The rate and level of reduction increased with the amount of reducing agent added.

Reduction and reoxidation of nontronite: extent of reduction and reaction rates

The effects of chemical reduction of structural Fe 3§ in nontronite SWa-1 (ferruginous smectite) on intervalence electron transfer (IT) and magnetic exchange were investigated. Visible absorption spectra in the region 800-400 nm of a chemical reduction series of the SWa-1 nontronite revealed an IT band near 730 nm (13,700 cm-'). Both the intensity and position of this band were affected by the extent of Fe reduction. The intensity increased until the Fe 2+ content approached 40% of the total Fe, then decreased slightly with more Fe 2+. The position of the band also shifted to lower energy as the extent of reduction increased. Variable-temperature magnetic susceptibility measurements showed that the magnetic exchange in unaltered nontronite is frustrated antiferromagnetic, but ferromagnetic in reduced samples. Magnetic ordering temperatures are in the range 10-50 K, depending on the extent of reduction. The ferromagnetic component in the magnetization curve increased with increasing Fe 2§ in the crystal structure. The positive paramagnetic interaction likely is due to electron charge transfer from Fe 2§ to Fe 3§ through such structural linkages as Fe2+-O-Fe 3§ (perhaps following a double exchange mechanism), which is consistent with the visible absorption spectra.

Intervalence electron transfer and magnetic exchange in reduced nontronite

The effects of reduction and reoxidation of octahedral Fe 3+ on the exchange of structural hydrogen in nontronite were determined using tritium (all) as a label element. The uptake of H from the surrounding solution of nontronite suspensions increased as the reduction of structural Fe 3+ increased. Similarly, the loss of H from the structure increased as the reduction increased. The results are generally consistent with a reduction mechanism involving the loss of structural OH, leaving the affected Fe sites with less than six-fold coordination. The attenuation of increased negative charge on the clay layer, however, was less than predicted by such a mechanism. During the reoxidation of reduced nontronite in suspension, about one-third of the H remaining as part of the structure following reduction was lost, whereas twice that amount of H was incorporated into the structure from the surrounding solution. A reoxidation mechanism is proposed whereby H20 from the surrounding solution is incorporated into the mineral structure followed by the elimination of a hydrogen ion, returning the Fe to six-fold coordination. This mechanism implies the reversibility of Fe reduction in nontronite.

Role of structural hydrogen in the reduction and reoxidation of iron in nontronite

Tabulating soil judging contest results is often laborious and timeconsuming. These contests can be enhanced by use of a computer program, SOILPIT, to more rapidly total, rank, and display the results. Version A, best suited for on-site contest use, requires creating an input file containing the contestants' names, identification numbers, team names, and team numbers prior to data entry. This version calculates the total scores and final rankings immediately after the last scorecard has been graded and entered and all entries have been verified and edited if necessary. When used at the 25th National Soil Judging Contest in April 1985, the final totals and rankings for both individual students and teams were available 15 min after the entered scores had been verified. Version B requires that the contestants' names, identification numbers, team names, team numbers, and pit scores be assembled beforehand into an input file. Both versions are available and have been adapted to run on IBM PC and Apple He and He computers. Additional index words: IBM PC, Apple He, Apple lie, Soil contest, Collegiate judging contests. T OBJECTIVES of a soil judging contest are (i) to gain knowledge about the soil with emphasis on "in-field" training; (ii) to allow students and faculty 1 Contribution from the Illinois Agric. Exp. Stn. Univ. of Illinois, Urbana 61801, and supported by Hatch Project no. 15-357 funds. Graduate research assistant, assistant professor, Dep. of Agronomy, Univ. of Illinois, Urbana, IL 61801. 'Assistant professor, Dep. of Plant and Earth Science, Univ. of Wisconsin-River Falls, River Falls, WI 54022. to visit and exchange ideas with each other about their common interests; (iii) to have fun; (iv) to promote soil science; and (v) to have the opportunity to compete in a collegiate contest (Post et al., 1974). These objectives are often forgotten, however, when the contest is followed by a long and languid afternoon awaiting the final results. The scorecards, graded that morning, must be manually transcribed onto a master sheet. The pit scores are then totaled, checked, and rechecked using a hand calculator. The students' scores are then subdivided into teams, and then team scores must be calculated. Hours later, the final results are reported. The results may be final, but they are not always free of accounting errors. It is the computation of these results and the ranking of teams and individuals that cause tremendous stress on the contest host. Many man-hours must be used to doubleor triple-grade the scorecards and check the total points on each scorecard, but the pressure mounts when individual and team rankings are calculated. The 1979 National Contest hosted by Montana State University attempted to use a computer program to relieve some of the workload and stress (SchafFet al., 1979). The data reported by each participant were collected in the field, delivered to the computer center, and entered into the grading program LEAR: SOILPIT: A COMPUTER PROGRAM 105 by keypunch operators. The entered data were graded, then rankings for individuals and teams were calculated. This process took several hours to complete, and since it did not save time, it has not been accepted nor has it been used in any subsequent contest since. The above notwithstanding, the authors decided to develop a computer program to handle the totaling and ranking of scores for a soil judging contest. A computer can add the scores and rank the individuals and teams faster and with greater accuracy than individuals using calculators. The result was SOILPIT. Developed at the University of Illinois, the SOILPIT program was designed to handle (i) totaling of the pit scores for each individual; (ii) ranking of individual scores; (iii) calculation of team scores; and (iv) ranking of team scores. Description of the SOILPIT Versions There are two versions of SOILPIT, A (long) and B (short). Both versions can accommodate 125 individuals, 25 teams of 1 to 5 members, and 10 pits per contest. Version A of SOILPIT is the most useful in an actual contest. Before the contest a data file consisting or each contestant’s name, identification number, team name, and team number is created, the program INPUTMAK is designed to help accomplish this task. INPUTMAK allows you to enter the data for each contestant, one item at a time, and asks for verification after all the data for a contestant has been entered. If the data entered are incorrect, INPUTMAK allows you to reenter the correct data. When all the contestants’ data have been entered, INPUTMAK gives you the option of reviewing the data to check for errors. The time required is usually 30 to 40 min. With the data file made, the long version of SOILPIT is ready to run. As each scorecard is graded, the contestant number, pit number, and pit score from the scorecard are entered into the computer and also written on a master sheet. SOILPIT then asks for verification of the data entered and, if incorrect, it allows you to enter the correct data. When the final scorecard of the contest has been entered, the option to review the entered data is given to the operator to check the entries. Following review of the data using the master sheet and the correction of any errors present, the pro° gram begins totaling and ranking the scores. The output of the long version consists of four parts: (i) listing, by identification number, of each contestant’s name, pit scores, and total; (ii) a ranked listing of the contestants based on total score; (iii) a listing, by team, of the scores per pit along with the total team score; and (iv) a rank listing of the team scores. In the ranked listings, it is important o note that in the event of a tie score the program does give the contestants the same ranking. For example, if J. Smith and D. Jones both have total scores of 747, and R. Goodman total score of 745, J. Smith and D. Jones would both be ranked ninth and R. Goodman would be ranked eleventh. The team totals are calculated by dropping the team’s lowest score per pit, adding the remaining scores per pit, and summing the totals for each pit. This method is preferred by the authors to other methods for determining team totals, such as summing all the team’s scores for each pit or dropping the contestant with the lowest individual total and summing all the other team members’ cores. Version B is intended to be used after all the scores have been tabulated and requires that all the data (con° testant’s name, identification number, team name, team number, and pit scores) be prearranged in an input file. A short program, FILEMAKE, aids in creating this file. FILEMAKE allows you to enter the data for each contestant, one item at a time. After a contestant’s data have been entered, FILEMAKE will ask you to verify that the data are correct. If not, the correct data may be entered. When all the contestants’ data have been entered, you have the option to review the data to check for errors. For most contests, 60 to 75 min are required to enter the data, check the data for mistakes and make any necessary corrections. Once the data have been verified, the short version can then be run, with the same output as the long version. Preliminary Testing of the SOILPIT Program Data collected from two Region III contests, held at the University of Indiana in 1982 and the University of Illinois in 1983, and the 1982 National Contest, hosted by the University of Nebraska-Lincoln, were used to test the run time of the SOILPIT program on the IBM PC. These contests consisted of 67 individuals and 20 teams, 73 individuals and 20 teams, and 68 individuals and 17 teams, respectively. Both versions of SOILPIT took approximately 10 min for each of the above contests after the last scorecard was entered and the entries were verified. Contest Usage of SOILPIT The first contest at which SOILPIT was tested onsite was the 1984 Wisconsin state soil judging contest held in the fall of 1984. This contest consisted of 35 students and nine teams. An Apple IIe with 64 K memory was set up in the grading van with a power cord running to the host farmer’s garage. The data file was created using INPUTMAK while waiting for the scorecards from the first pit to arrive. As the scorecards were graded, the data were entered into the program. The same information was also recorded by hand on a master sheet. This process occurred much faster than the grading of the scorecards, o the operator also sorted the scorecards by pit while waiting. After all the scores had been entered, the data in the program were checked against the master sheet. Three discrepancies were found, verified using the scorecards, and corrected. This took 5 min to accomplish. The program was then run, and the output was ready in 15 min, only 20 min after the final scorecard was graded. The Region III competition held at Michigan Technological University in 1984 with 62 individuals and 17 teams was used to test the IBM version of SOILPIT 106 JOURNAL OF AGRONOMIC EDUCATION, VOL. 15, No. 2, Fall 1986 A. The IBM PC was housed in a field laboratory building nearby to the contest site. The data from each scorecard were entered after the scorecard was graded, and the results were available 16 min after the last scorecard was entered and all the entries verified. SOILPIT programs for the Apple II computers, since they are not compiled, generally take longer to run than the programs on the IBM PC. The 25th National Soil Judging Contest involved 62 contestants and 18 teams. The coaches listed their team members on the master sheet Wednesday evening at the coaches meeting, and the IBM version of INPUTMAK was used to create the data file immediately after the meeting. The data entry took 1 h, including checking and deciphering the coaches handwriting. On Friday morning, the IBM PC was set up in the host farmer's dining room. Four people were involved in the data entry process. One person read the contestant number, pit nu

SOILPIT: A computer program to rank soil judging scores

The operation of heavy equipment on the surface of saturated coal ash during the closure of impoundments containing CCR poses significant safety concerns. Saturated ash has little to no bearing strength and the depth of saturated ash in CCR impoundments can range up to hundreds of feet. In-Situ Stabilization (ISS) technology (treatment of the top 3 to 5 feet of saturated CCR material) may be used to quickly produce a stable work platform for subsequent CCR placement and compaction and capping activities within the impoundment. The plan area of the saturated ash is divided into a number of treatment cells, each sized to require a 25-ton truckload of Portland cement. Working from the edges of the treatment cells, the Portland cement is mixed into the saturated ash using long-reach excavators. Within 48 to 72 hours, the treated material develops sufficient bearing capacity to support the operation of long-reach excavators and treat the next row of treatment cells. With the stable work platform established, placement and compaction and capping activities can be conducted, operating safely on the ISS-treated CCR material.

Paul R. Lear

Papers

Reduction and reoxidation of nontronite: extent of reduction and reaction rates

Intervalence electron transfer and magnetic exchange in reduced nontronite

Role of structural hydrogen in the reduction and reoxidation of iron in nontronite

SOILPIT: A computer program to rank soil judging scores

Surface In-situ Stabilization of Saturated Ash for CCR Impoundment Closures