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a John Gilmour, Inc., P.O. Box 610, Fayetteville, AR 72702
b Puyallup Research and Extension Center, Washington State Univ., Puyallup, WA 98371
c Dep. of Crop and Soil Sciences, Michigan State Univ., East Lansing, MI 48824
d Crop and Soil Environmental Sciences, Virginia Tech, Blacksburg, VA 24061
e Dep. of Crop and Soil Science, Oregon State Univ., Corvallis, OR 97331
* Corresponding author (gilmour{at}uark.edu)
Received for publication July 18, 2002.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Abbreviations: PAN, plant-available nitrogen
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Biosolids properties and land application site characteristics vary sufficiently to make predicting total PAN for a given time period a difficult task (USEPA, 1995). Organic N concentration and decomposition kinetics vary among biosolids as does initial inorganic N content (Ajwa and Tabatabai, 1994; USEPA, 1995; Gilmour et al., 1996). Organic N from the same biosolids incubated in different soils mineralizes at different rates (Terry et al., 1979; Ajwa and Tabatabai, 1994). Soil temperature and moisture also influence the rate of decomposition and net N mineralization (Terry et al., 1979; Clark and Gilmour, 1983; Gilmour and Clark, 1988). Characterizing biosolids decomposition is important because mineralization of biosolids organic N follows the same pattern as decomposition for these low C to N ratio by-products. Decomposition rates of biosolids follow one of two patterns. In some cases, the decomposition rate is constant, while in other cases it is faster initially and then followed by a constant, slow decomposition rate (Gilmour, 1998).
Many approaches have been used to estimate total PAN in biosolids and other organic wastes. King (1984) successfully modeled PAN in a limited population of biosolids using the C and N contents of the biosolids plus cumulative decomposition at 5 d. Serna and Pomares (1992) reported that plant N uptake in a pot study was best related to N extracted by pepsin and the C to N ratio of the biosolids. Hattori and Mukai (1986) related net N mineralization to the crude protein content of biosolids. Gilmour and Skinner (1999) reported that biosolids PAN was related to biosolids C to N ratio, organic N, and total N.
The USEPA design manual (USEPA, 1995) proposed different mineralization rates for different biosolids treatment categories. These USEPA recommendations were largely based on a laboratory study that employed a small number of biosolids for groupings in categories other than the anaerobically digested group, used biosolids that were air-dried and ground before mineralization studies, and based annual mineralization rates on a 16-week incubation at 24°C and optimum soil moisture (Sommers et al., 1981).
Constant decay series have been extensively used to estimate total PAN in biosolids (USEPA, 1995). Gilmour and Clark (1988) identified variable climate and biosolids properties as factors that reduce the accuracy of the constant decay series. Computer simulation models, which consider biosolids, site, and weather as input variables, have also been proposed (USEPA, 1995), but have been criticized due to the lack of field verification of the computer models and the need for long-term incubation studies to characterize biosolids decomposability. Gilmour and Skinner (1999) recently verified the use of a computer simulation model to predict total PAN. They found that biosolids quality (organic N, inorganic N) was more important than biosolids decomposability for estimating PAN, thus eliminating the need for long-term incubation studies.
Research is required to develop more accurate estimates of N mineralization rates for a wide range of municipal biosolids types applied to different soils under varying environmental conditions. The objectives of this study were to combine laboratory and field data to characterize biosolids decomposition and N mineralization for the development of PAN estimates and to further evaluate computer simulation as a tool to calculate total PAN in biosolids.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Field-moist soil equal to 100 g dry weight was placed in a 946-mL bottle. The biosolids were mixed with the soil or placed on the soil surface as appropriate. Field application rates were duplicated for the Arkansas biosolids–soil combinations, while all other biosolids were added at a rate of 6.72 Mg ha-1 (300 mg per 100 g dry soil) in 1998. Field application rates were used for all biosolids–soil combinations in 1999. Baltimore biosolids used in the 1998 field study in Washington were omitted from the laboratory study as all material was applied in the field. Soil alone served as the control.
Soil water content was adjusted to 40% of the water holding capacity of the soil (near field capacity) with distilled water. A test tube containing 10 mL 1 M NaOH was placed in each bottle, which was sealed and then placed in a constant temperature chamber at 25°C. Treatments and controls were triplicated in 1998 and duplicated in 1999.
Biosolids decomposition was determined by collecting evolved carbon dioxide in 1 M NaOH base traps. The base traps were replaced regularly and analyzed by weak acid titration after the addition of barium chloride (Zibilske, 1994). Carbon dioxide evolution in one of the controls in the 1999 Washington study was much higher than other controls either year. Decomposition of incorporated Springdale biosolids in 1998 was very slow and inconsistent with the other Springdale biosolids data. These data were not used in the calculation of first-order rate constants.
In the computer simulation model described below, decomposition was treated as a sequential process. Sequential decomposition was defined as decomposition of the rapidly decomposable portion of the biosolids followed by decomposition of the slowly decomposable fraction (Gilmour et al., 1996). Rate constants and the percentage of biosolids C in the rapid fraction were determined using the Nonlinear Regression fitting platform of SAS JMP Version 3.2.1 as described by Gilmour et al. (1996).
At the end of the 1998 study, inorganic nitrogen was extracted with 1 M KCl and inorganic N determined as described for biosolids. Net N mineralization was the inorganic N in biosolids treatment minus initial biosolids inorganic N minus the inorganic N in the appropriate control. Net N mineralization is reported as a percentage of the biosolids organic N. Net N mineralization was not determined in 1999 due to the long incubation time.
Field Studies
Field studies were conducted using row crops (Arkansas, Michigan, and Virginia) and established perennial grasses (Washington and Virginia). All experiments were conducted at separate field locations each year. Before each field experiment, soil from each location was sampled and tested using methods recommended by the investigators' universities. Blanket P and K applications were applied to field plots based on soil test results. Row crop sites were fallowed or cropped without the addition of N fertilizer the year before each study. Perennial grasses were established at least one year before field studies.
Arkansas
The 1998 experiment consisted of 10 treatments: four biosolids incorporated, one biosolids surface-applied (Springdale), four inorganic fertilizer (34–0–0) rates from 56 to 224 kg N ha-1 in 56 kg N ha-1 increments, and an unfertilized control. The experimental design was a randomized, complete block with four replications. Individual plots measured 2.1 x 4.5 m. The same experimental design was used in 1999. Biosolids and inorganic fertilizers were applied and incorporated (except Springdale surface-applied) on 2 June 1998. In 1999, plots were amended with the biosolids, rototilled, and planted on 25 May. Each year, sorghum sudan grass [Sorghum bicolor (L.) Moench.] was the crop. Plots were not irrigated. In 1998, Baltimore biosolids greatly reduced sorghum sudan grass emergence and stand. In 1999, the latter effect occurred for both Baltimore and Milwaukee biosolids. No field data were obtained for these plots.
Plots were harvested on 20 Aug. 1998 and 13 July 1999 using a mechanical forage harvester. Wet weights per plot were recorded and subsamples weighed for water content determination after drying to constant weight at 50 to 60°C. Dried samples were ground for total N analysis by LECO Total CNS 2000.
Michigan
The 1998 experiment consisted of 11 treatments: three biosolids incorporated, four inorganic N fertilizer (46–0–0) rates of 56 to 224 kg N ha-1 in 56 kg N ha-1 increments, and four treatments held for the 1999 growing season. The experimental design was a randomized, complete block with four replications. Individual plots measured 4.5 x 15 m.
In 1998, liquid biosolids were injected on 13–14 May, while solid biosolids and the inorganic N fertilizer were applied to the surface of plot areas on 13 May, and then these plot areas were tilled with the injectors, so all plots would receive the same tillage before planting. Then, all plots were tilled twice and planted to field corn (Zea mays L., Pioneer #3573; Pioneer Hi-Bred International, Des Moines, IA). Diagnostic earleaf samples were collected on 18 September at the PM stalk stage of growth. Samples were dried and shipped to the University of Arkansas for total N analysis by LECO Total CNS 2000.
The 1999 experiment consisted of 10 treatments: six biosolids and four inorganic N fertilizer (46–0–0) rates of 56, 112, 168, and 224 kg N ha-1. Solid biosolids were surface-applied on 30 April or 3 May when inorganic N fertilizer treatments were surface-applied, each followed by disking to immediately incorporate these materials. Liquid biosolids were injected on 28–29 April or 3 May. Other agronomic practices were the same as in 1998. Diagnostic ear leaf samples were collected on 22 July and analyzed as in 1998.
Virginia Experiment 1
The plot area was a pasture of well-established (>15 yr old) tall fescue (Festuca arundinacea Schreb. ‘KY31’). The experiment consisted of nine treatments: an unfertilized control; four inorganic fertilizer N (34–0–0) rates designed to supply 112, 224, 336, and 448 kg N ha-1; and four biosolids surface-applied. The experimental design was a randomized, complete block with four replications. Individual plots measured 3 x 3 m. Biosolids were collected on 24–25 March. Biosolids and inorganic fertilizers were surface-applied on 25 March. Fertilizer N treatments were split as follows: 112–0–0, 224–0–0, 224–112–0, or 224–112–114 kg N ha-1 on 25 March, 17 May, and 23 August, respectively. Plots were not irrigated. Tall fescue was harvested by mowing with a mechanical forage plot combine to a height of 5 cm on 17 May, 22 June, 23 August, and 25 October. Tall fescue fresh weights for each plot were recorded, and subsamples were dried at 65°C until constant weight was achieved. Dried samples were ground and total Kjeldahl N determined by digesting ground plant tissue in sulfuric acid and analyzing the digests for ammonium using a QuikChem automated ion analyzer (Lachat Instruments, Milwaukee, WI).
Virginia Experiment 2
Treatments were an unfertilized control, four rates of inorganic fertilizer N (67, 134, 202, and 267 kg N ha-1 as 34–0–0), and two rates of biosolids. Each treatment was replicated four times and arranged in a randomized, complete block design.
Treatment plots were 12 x 15 m. Biosolids was applied with a commercial spreader on 7 April and incorporated into the soil by chisel-plowing within four hours. Commercial fertilizer was applied by hand on 7 April and Pioneer #3394 corn was planted on 13 April. Eight whole corn plants were sampled at crop physiological maturity (black layer, 5 August) from 2.1 m of the center row of each treatment plot for biomass production and N uptake. Samples were analyzed as in Experiment 1.
Washington
The experiment consisted of 14 treatments: eight biosolids (all dried or dewatered), five inorganic fertilizer (34–0–0) rates from 50 to 250 kg N ha-1, and a zero N control treatment in 1998. The experimental design was a randomized, complete block with four replications. Individual plots measured 1.5 x 6 m. The fescue grass was mowed to a 5-cm height and a single surface application of biosolids or one-third of the N fertilizer was made on 6 May. The remainder of the 34–0–0 was applied following the June and July harvests. A 0.9- x 5.5-m swath was harvested at a 5-cm height on 3 June, 6 July, 5 August, and 14 September. The harvested grass from each plot was weighed wet, and a subsample was collected and oven-dried for determination of dry matter and N content (LECO Total CNS 2000).
In 1999, the experiment included nine biosolids treatments, four inorganic N rates (50–200 kg N ha-1) split over three dates in May, June, and July, and a zero-N control. Biosolids were applied on 25–28 May 1999. All other procedures were the same as in 1998.
Description of the Computer Simulation Model
The computer simulation model, Decomposition, is a mechanistic model that was first described by Gilmour and Clark (1988). The version of the model used in the simulations outlined below was described in detail by Gilmour (1998). A brief summary of that description follows.
The model employs first-order kinetics to estimate rates of C and N transfer among biosolids (rapid and slow fractions), microbial biomass (indigenous, new), and soil organic matter (decomposable, recalcitrant) pools. Rapid and slow fraction rate constants describe the decomposition of the rapidly and slowly decomposable biosolids fractions, respectively, using the sequential model where the rapidly decomposable portion of biosolids precedes slow biosolids fraction decomposition. Nitrogen mineralized from biosolids is equal to the C decomposed divided by the biosolids C to N ratio.
New microbial biomass forms as biosolids decompose using a microbial efficiency of 0.4. New biomass is distributed among biomass pools and the newer soil organic matter (OM) pool. The soil OM pool is assigned a C to N ratio of 10, while biomass has a C to N ratio of 8. Organic C in the two biomass pools and the newer soil OM pool subsequently decomposes and N is mineralized (decomposition divided by appropriate C to N ratio). Initial soil organic matter is equally divided between the two soil OM pools. The recalcitrant soil OM is considered stable for the simulation periods used here.
Model inputs included average monthly air temperature, precipitation, and potential evapotranspiration. Weather data (temperature, rainfall) were obtained daily for each location. Soil temperature was assumed to equal air temperature and soil water potential was obtained by a water balance using the water release curve for application site soil texture as described by Gilmour and Clark (1988). The model time step was 1 d.
Estimation of PAN used analytical data and decomposition kinetics obtained in the laboratory portion of this study. Actual weather data during each field study was used in simulations for the growing season. Actual growing-season weather supplemented with average weather for other months (from Springdale, AR; Detroit, MI; Blacksburg, VA; and Seattle, WA) was used in computer simulations of the year after application.
Statistical Analyses
Linear regression equations and standard error of means were determined using the Fit Y by X platform of SAS JMP Version 3.2.1. Means and standard deviations were determined using the Distribution of Y platform of SAS JMP Version 3.2.1 (SAS Institute, 1997).
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RESULTS AND DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Laboratory Studies
Figure 1
presents an example of laboratory decomposition data for the various biosolids–soil combinations used in the Washington study. In general, decomposition followed typical patterns and did not appear to cease in most samples during the extended incubation time in 1999.
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Percent decomposition of the Baltimore biosolids was similar among years and states except for a higher value in Michigan in 1998: Arkansas (14 and 17%), Michigan (28 and 20%), and Washington (16%). The mean values for the three states were 16, 24, and 16%, respectively, with an overall mean of 19%. In 1999, Milwaukee biosolids decomposition in soils from the three states was 20, 36, and 34%, respectively.
Table 4 presents the sequential decomposition kinetics obtained for each biosolids–soil combination incubated at 25°C and soil moisture at 40% water holding capacity. Biosolids in 27 of the 37 biosolids–soil combinations that had not been in a lagoon had two decomposition phases. For this biosolids group, the mean rapid and slow fraction rate constants were 0.021 (0.003) and 0.0015 (0.0003) d-1, while the percentage of total C in the rapid fraction averaged 23 (2)%, where the values in parentheses are the standard errors of the means. Parallel mean values were 0.025 d-1, 0.0029 d-1, and 28% for the 24 biosolids–soil combinations reported by Gilmour et al. (1996). For the six biosolids exhibiting only one decomposition phase that had not been in a lagoon, the mean first-order rate constant was 0.0046 (0.001) d-1. Everett, Iona, and San Jose biosolids were stored in lagoons for varying time periods. These biosolids had a mean rate constant of 0.00097 (0.0002) d-1. Thus, biosolids stored in a lagoon decomposed much more slowly than those that had not.
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Observed PAN ranged from 9 to 74% of the total N in the biosolids with a mean value of 37% (Table 6). Sommers et al. (1981) reported that 16 to 24% of biosolids total N was recovered in grain sorghum aboveground tissue and soil inorganic N for incorporated biosolids. King (1984) found from 6 to 42% of the total N (mean 24%) in biosolids was PAN after 107 d incubation in the laboratory. In that study, from 4 to 39% of the organic N was mineralized with a mean value of 20%.
Linear regressions were run for observed PAN versus biosolids organic N, biosolids total N, and biosolids C to N ratio in an attempt to estimate observed PAN from analytical data. The relationships where organic N (y = 0.84 + 0.43x; r2 = 0.36, P < 0.0001) or C to N ratio (y = 40 - 2.8x; r2 = 0.31, P = 0.0003) was the independent variable were statistically significant, but did not estimate observed PAN as well as equations reported by Gilmour and Skinner (1999). The best relationship was between observed PAN and biosolids total N (Fig. 2) . A similar relationship was reported by Gilmour and Skinner (1999). Use of this relationship should be limited to biosolids and weather scenarios similar to those in this study.
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Computer Simulations
Temperature, precipitation (plus irrigation), and, in some cases, potential evapotranspiration, were measured at each land application site (Table 7)
. These data were used to estimate growing-season PAN under actual conditions. For the Arkansas study, the 1998 growing season was drier and the 1999 growing season was wetter than normal. For Experiment 2 in Virginia, the growing season was much drier than normal. The Washington study was irrigated both years and, so, was wetter than normal. Temperatures at all locations were near mean values.
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Since biosolids total N provided a statistically significant estimate of growing-season PAN, mean predicted PAN was estimated using the mean two-phase decomposition rate constants for biosolids not in a lagoon or biosolids in a lagoon. Figure 4 presents this relationship. The intercept was small, but significantly greater than zero and the slope (0.86) was significantly different from unity. Prediction of PAN with Decomposition using mean decomposition kinetics offers an alternative where rate constants for the biosolids are not available. Output can be adjusted using the relationship shown in Fig. 4.
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CONCLUSIONS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Since weather affects biosolids decomposition and organic N mineralization, use of the computer simulation model Decomposition provides the best estimates of PAN for field situations. Plant-available N predictions using Decomposition can be made using mean decomposition rate constants for the two biosolids groups when individual biosolids decomposition data are not available.
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ACKNOWLEDGMENTS |
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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