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What Is the Best End Use for Compost Derived from the Organic Fraction of Municipal Solid Waste?

Cite this: Environ. Sci. Technol. 2021, 55, 1, 73–81
Publication Date (Web):December 10, 2020
https://doi.org/10.1021/acs.est.0c04997

Copyright © 2020 American Chemical Society. This publication is available under these Terms of Use.

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Abstract

There is increasing interest in diverting the organic fraction of municipal solid waste from landfills to biological treatment processes that result in compost. Due to variations in compost quality and available markets, it is not always possible for compost to be beneficially used on soil. In such cases, compost may be used as alternative daily cover (ADC) in landfills. The objective of this study is to compare the environmental impacts of using compost as a soil amendment, accounting for its beneficial substitutions for fertilizer and peat, to its use as ADC. Monte Carlo simulation and parametric sensitivity analyses were performed to evaluate the effects of uncertainty in input values on the environmental performance. The ADC scenario outperforms the soil amendment scenario in terms of global warming potential, acidification, and eutrophication in ∼63, ∼77, and ∼100% of simulations, respectively, while the soil amendment scenario is better in terms of cumulative energy demand and abiotic resource depletion potential ∼94 and ∼96% of the time, respectively. Therefore, we recommend that using compost as ADC be considered, especially when site-specific factors such as feedstock contamination or a lack of markets make it difficult to find appropriate applications for compost as a soil amendment.

This publication is licensed for personal use by The American Chemical Society.

Introduction

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The organic fraction of municipal solid waste (OFMSW) (e.g., food and yard waste) is estimated to represent ∼28% of the MSW generated in the US. (1) Food waste is a leading contributor to methane (CH4) emissions from US landfills because it anaerobically biodegrades more quickly and completely than other MSW components (e.g., newsprint, cardboard, and wood), and only ∼21% of the biogenic carbon (C) in food waste is estimated to remain stored in the landfill. (2) In contrast, leaves and branches degrade more slowly and less completely than food waste, and ∼80% of their C content is estimated to remain stored after 100 years. (2) In addition, food waste decomposes more rapidly than the aforementioned lignocellulosic substrates, and gas collection is least efficient early in the life of a landfill. (2,3) Biological treatment of the OFMSW in composting facilities diverts waste from landfills and results in a nutrient-rich compost that can reduce chemical fertilizer and peat consumption. Similarly, when the OFMSW is treated by anaerobic digestion (AD), the residual solids are subsequently cured aerobically, again resulting in a nutrient rich compost. However, a substantial fraction of compost generated from the OFMSW is used as alternative daily cover (ADC) in landfills instead of being used as a soil amendment. (4) There is currently little data on how these different end uses compare to one another in terms of their overall environmental impacts.
Life cycle assessment (LCA) is frequently used to evaluate strategies for managing solid waste including OFMSW. Boldrin et al. (5) reported that the global warming potential (GWP) for composting organic waste is between −900 and 300 kg CO2e, depending on the composting technology, organic waste composition, and final compost use and offsets. Harren et al. (6) used LCA to compare using yard waste directly as ADC in landfills versus composting it in windrows. They found that the ADC scenario led to better environmental performance when the landfill was equipped with a gas collection system and that composting was better when the landfill gas was passively vented. Schott et al. (7) reported that the differences in GWP for OFMSW management alternatives were primarily controlled by the physical and chemical properties of the waste, included offsets in the background and foreground system, and system boundaries and configurations. AD is another management alternative for OFMSW that has been evaluated using LCA and can produce a compost product. Hodge et al. (8) performed an LCA on food waste management alternatives and found that diverting food waste from landfills to mass-burn combustion, henceforth referred to as waste-to-energy (WTE), composting, or AD reduces greenhouse gas (GHG) emissions and that WTE and AD have better performance than composting. Morris et al. (9) reviewed 82 studies on the end of life management methods for OFMSW and found that AD, centralized composting, and WTE lead to the lowest GHG emissions.
The environmental impacts of using compost in growth media have also been investigated using LCA. Use of compost in growth media has several benefits including increasing the nutrients (i.e., nitrogen (N), phosphorus (P), and potassium (K)), and organic C content of soil, (10) controlling plant pathogens, (11,12) and improving soil structure and water holding capacity. (13) However, compost use has the potential to increase heavy metal contamination of water and crops relative to conventional fertilizers. (14) Land application of compost and conventional fertilizers lead to different levels of nitrous oxide (N2O), ammonia (NH3), and nitrate (NO3) emissions, (15) and the relative differences in these emissions must also be considered. Boldrin et al. (16) reported that the substitution of peat with compost reduces GHG emissions by 70 to 150 kg CO2e/Mg compost (25–55%) and eutrophication by 1.7 to 6.8 kg NO3/Mg, while peat performs better in terms of human toxicity due to heavy metals in compost.
The objective of this work is to compare the environmental impacts of using compost derived from the OFMSW as a soil amendment with its use as ADC in a landfill equipped with energy recovery and leachate collection. Life-cycle process models were developed to calculate the environmental impacts associated with each alternative for GWP, eutrophication, acidification, abiotic resource depletion potential (ADP), and cumulative fossil energy demand (CED), which accounts for the use of fossil resources (i.e., oil, natural gas, coal, and peat). Monte Carlo simulation and parametric sensitivity analyses were performed to evaluate the effects of uncertainty in input values and the conditions under which each alternative outperformed the other in each impact category.

Modeling Approach and Scenarios

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The functional unit for this study is 1 Mg (1000 kg) wet weight of compost produced from the OFMSW through aerobic composting or AD followed by aerobic curing. As shown in Figure 1, system boundaries for this analysis start from compost utilization and include direct emissions from compost use as well as offsets associated with each beneficial use scenario. The analysis used a 100-year time horizon for tracking environmental emissions. Process models were developed to describe the use of compost as either a soil amendment or for ADC using SwolfPy, (17) an open source python-based framework for LCA and optimization of solid waste management systems. The mathematical model for the process models is described by eqs S1–S27 of the Supporting Information (SI). In the soil amendment scenario, compost can substitute for peat and/or conventional N, P, and K fertilizers, while it substitutes for daily cover soil excavation in the ADC scenario.

Figure 1

Figure 1. System boundaries and process flows for the developed scenarios. Using compost as a soil amendment can offset fertilizer and/or peat use, while using compost as ADC can offset soil excavation and electricity produced from collected landfill gas attributable to the ADC.

Compost Composition

The chemical composition of compost varies based on the type and source of organic materials composted, the employed technology, and climate. (18) As shown in Table S1, compost derived from food waste generally has more C and nutrients than yard waste derived compost. The relatively wide ranges of the compost C (10–47% of dry compost) and moisture (18–67% of wet compost) contents in Table S1 show the inherent variability in compost composition. Default values and distributions used for compost composition in the Monte Carlo simulations are presented in Table 1.
Table 1. Input Data and Related Uncertainty Propagation Functions for Compost Physical and Chemical Properties
parameterdescriptiondefaultuncertaintya
CompDenscompost density (kg/m3)700N(700, 110) (16)
CompMoist.Contcompost moisture content (kg water/wet kg)0.45U(0.18, 0.67) (5)
Ccfraction of C in dry compost0.30U(0.10, 0.47) (5)
Ncfraction of N in dry compost0.015U(0.007, 0.028) (5,18)
Pcfraction of P in dry compost0.005U(0.0015, 0.0093) (5)
Kcfraction of K in dry compost0.01U(0.0007, 0.023) (5,18)
a

Uniform distribution: U(min, max), normal distribution: N(mean, standard deviation).

Carbon Balance

The C balance is calculated based on a 100-year time horizon. When the compost is used as a soil amendment, 2–16% of the initial C content remains stored (CStore.c) after 100 years, (19) and the rest is converted aerobically to biogenic CO2.
In the ADC scenario, landfill C storage after 100 years is calculated based on the fraction of biogenic C that is not anaerobically degradable (CStore.,LF). Carbon in the compost in excess of CStore.,LF biodegrades to produce landfill gas (LFG) that is equimolar CH4 and CO2. If the mass of biogenic C in the compost is less than the mass of potential C storage, then no LFG is produced (Table S4). Levis and Barlaz (2) estimated that 48–72% of generated LFG is collected by the gas collection system (CH4Col) and combusted to produce CO2 and electricity, 10–60% of the collected LFG is combusted via a flare (CH4Flr) to produce CO2 when the energy recovery system is not available, and 10–28% of the uncollected LFG is oxidized to CO2 in the landfill cover (CH4Ox), while the balance is emitted to the air (Table S6). These values are based on landfills that have energy systems installed, and the ranges are attributable to different size landfills which influences the timing of energy recovery equipment installation, as well as climate and the schedule of gas collection system installation. These values were used to develop the statistical distributions used in the Monte Carlo analysis (Table 2).
Table 2. Input Data and Related Uncertainty Propagation Functions for Soil Amendment and ADC Scenarios
parameterdescriptiondefaultuncertaintya
CStor.cfraction of C in compost that remains stored after 100 years0.10U(0.02, 0.16) (19)
CStor.pfraction of C in peat that remains stored after 100 years0.10U(0.02, 0.16) (19)
Nfrac.N2fraction of N that is lost as N2O0.018U(0.013, 0.022) (15)
Nfrac.NH3fraction of N that is NH30.25U(0.01, 0.50) (19)
NH3frac.evapfraction of NH3 that is lost to atmosphere0.15T(0.15, 0.10, 0.20) (19)
Nfrac.NO3fraction of N content that is emitted as NO30.20U(0.03, 0.87) (15)
FracGWfraction of NO3 that is emitted to groundwater0.50U(0.30, 0.90) (19)
RN2O.fratio of N2O emission from fertilizer to compost (kg/kg)0.60U(0.50, 0.85) (19)
RNH3.fratio of NH3 emission from fertilizer to compost (kg/kg)0.25U(0.20, 0.30) (19)
RNO3.fratio of NO3 emission from fertilizer to compost (kg/kg)0.50U(0.35, 0.70) (19)
MFENN mineral fertilizer equivalent (kg/kg)0.6U(0.2, 0.8) (19)
MFEPP mineral fertilizer equivalent (kg/kg)0.9U(0.8, 1) (16)
MFEKK mineral fertilizer equivalent (kg/kg)0.9U(0.8, 1) (16)
PeatMoist.Contpeat moisture content (kg water/wet kg)0.56N(0.56, 0.05) (16)
PeatDenspeat density (kg/m3)200N(200, 57) (16)
PeatC.Contfraction of C in solid content of peat0.504T(0.504, 0.48, 0.63) (16,20)
PeatSubs.facpeat volumetric substitution factor1.0T(0.9, 1, 1.1) (16)
Dslcdiesel fuel use for application compost (L/Mg)0.8 (8)L(−0.223, 0.186)
DslN.fdiesel fuel use for application N fertilizer (L/Mg N fert.)2.29 (8)L(0.829, 0.186)
DslP.fdiesel fuel use for application P fertilizer (L/Mg P fert.)1.86 (8)L(0.621, 0.186)
DslK.fdiesel fuel use for application K fertilizer (L/Mg K fert.)1.25 (8)L(0.223, 0.186)
ADC Scenario
CStoreLFfraction of C that remains stored after 100 years in ADC0.90bN(0.90, 0.03) (2)
Cfrac.C4CH4 content in the produced biogas (mol/mol)0.5bU(0.45, 0.55)
CH4Colfraction of the produced CH4 that is collected0.60bN(0.60, 0.04) (2)
CH4Oxfraction of uncollected CH4 that is oxidized0.17bN(0.17,0.03) (2)
CH4Flrfraction of collected CH4 that is flared0.31bN(0.31, 0.12) (2)
Eleceffelectricity production efficiency from biogas (MJe/MJh)0.30U(0.20, 0.37) (8)
Gridmixelectricity grid fuel mix factor1T(1, 0.7, 1.35)
LHVC4lower heating value of CH4 (MJ/kg)50 
DCsubs.facdaily cover’s soil volumetric substitution factor (vol soil/vol compost)0.9U(0,1)
AlocADCallocation of emission from material use in landfill to ADC0.5U(0, 1)
SoilDenssoil density (kg/m3)1600T(1600, 1400, 1800) (6)
DCthickthickness of daily cover form soil (cm)15 (6)L(2.708, 0.024)
ADCthickthickness of daily cover form compost (cm)22.5 (6)L(3.219, 0.115)
LCRSeffleachate collection and recovery system efficiency0.991 (21)T(0.991, 0.971, 0.999) (21)
Nfrac.NH4fraction of N that is emitted as NH+4 in ADC5.63 × 10–3 (3)L(−5.1796, 0.2093)
NH4rmv.effNH4 removal efficiency in wastewater treatment plant0.95 (22)T(0.95, 0.89, 0.98) (22)
Nfrac.NH4.S_Wtrfraction of N that is emitted to surface water as NH+4 in ADC8.7 × 10–3L(−9.355, 0.209)
a

Uniform distribution: U(min, max), normal distribution: N(mean, standard deviation), log-normal distribution: L(mean, standard deviation), triangular distribution: T(mode, min, max).

b

Calculations are described in the “Carbon Fate in ADC” section of the SI.

Nutrient Balance and Fertilizer Offsets

While compost derived from the OFMSW can have N contents of 0.72–2.8%, (5,16) not all the N is ultimately used by plants. There are losses of N as NO3 to surface water runoff and groundwater leachate and as NH3 and N2O to the air (eqs S9–S12). In addition, the N in compost is not as readily available to plants as the N in mineral fertilizer; therefore, a mineral fertilizer equivalent (MFE) factor (kg available as fertilizer/kg nutrient added) is used to adjust the actual amount of fertilizer offset based on the availability of the applied nutrients to plants relative to conventional fertilizers. The MFE for N ranges from 0.2 to 0.8, while the MFE for P and K are typically 1.0 because they are in mineral form which is readily absorbed by plants. (19) Conventional fertilizer application also results in losses, and the ratio of emissions from fertilizer to those of compost is incorporated into the process model (RN2O.f, RNH3.f, RNO3.f).
Diesel-powered equipment is used to apply compost (Dslc) as well as conventional N, P, and K fertilizers. The use of diesel to apply the avoided conventional fertilizer use is included as a beneficial offset (DslN,f, DslP,f, DslK,f). However, due to the lower nutrient content of compost and the lower availability of compost nutrients, the diesel required for applying compost is 40 times greater than the diesel use offset from the avoided fertilizer.
In the ADC scenario, the N content of compost results in ammonium (NH+4) formation in the landfill leachate. A 99.1% leachate collection and recovery system efficiency (LCRSeff) was adopted from previous work, (21) resulting in 0.9% release to groundwater. The collected leachate is treated in a wastewater treatment plant which oxidizes 95% of NH+4 (NH4rmv.eff) to NO3, with the balance of the NH+4 released to surface water. (22) It was assumed that the wastewater treatment plant uses 0.99 kWh electricity per kg of BOD removed. (23) The model calculates NH+4 emissions to groundwater and surface water using the LCRSeff, NH4rmv.eff, and the fraction of the initial N in the applied compost that becomes NH+4 (Nfrac.NH4). (3)

Peat Offset

Peat is plant residue that has degraded anaerobically over centuries or millennia and has been reported to consist of 48–63% C (PeatC.Cont). (20) It is used as a soil additive and fertilizer in agricultural and horticultural applications due to its high water-holding capacity, porosity, permeability, and carbon content. (20) In 2015, 560,000 Mg of peat were used in the US for soil improvement and potting soil. (24,25) Although peat and compost have different nutrient, cellulose, lignin, and inorganic contents, pH’s, porosities, and densities, (26−28) compost is frequently substituted for peat in growth media in hobby gardening and horticultural applications. (29,30) Avoided peat consumption is calculated using a volumetric peat substitution factor (PeatSubs.frac), peat density (PeatDens), and compost density (CompDens). Boldrin et al. (16) assumed that compost was substituted for peat at a 1:1 volumetric ratio. Applying peat to growth media results in CO2 emissions due to the aerobic decomposition of organic C in peat. Due to the long time (>100 yr) it takes to generate peat, it is considered a fossil resource for purposes of CO2 accounting and fossil energy use calculations.

Avoided Soil Excavation

Using compost as ADC in a landfill reduces the use of soil for daily cover and associated excavation. The volume of soil excavation avoided is calculated from the thickness of the applied soil (DCthick) and compost (ADCthick) required as daily cover, as well as CompDens, soil density (SoilDens), and a volumetric substitution factor of daily cover (DCSubs.fac). The DCSubs.fac varies from 0 to 1 based on whether the compost substitutes the virgin soil use for daily cover (1) or substitutes other ADC materials (0), for which no offset is provided.

Raw Material and Electricity Use in Landfill

Landfill disposal results in diesel and raw material (e.g., geomembrane) consumption, which could be allocated to the ADC scenario (AlocADC) depending on the operating situation and model assumptions. Whether some of the burden of landfill construction should be attributed to ADC can be debated, and our analysis was formulated to allow AlocADC to vary from 0 to 1 based on whether the ADC is considered a revenue generating waste that requires additional control (1) or is a construction material that does not use additional landfill resources (0). Diesel and raw material consumption were calculated by the landfill model developed by Levis and Barlaz. (3)

Impact Categories

Five environmental impacts, GWP, CED, acidification, eutrophication, and ADP, were considered based on their relevance to compost utilization. GWP was selected due to CO2, CH4, and N2O emissions from both scenarios. Eutrophication and acidification were selected due to NO3 emissions to water and NH3 emissions to air in the soil amendment scenario as well as emissions in the background system from diesel and electricity. CED was selected due to the potential savings in fossil resource use from substituting peat use with compost. ADP was selected due to potential savings in abiotic resources use from substituting the fertilizer with compost. The 100-year GWP was calculated using characterization factors from IPCC 2013 (31) (1 kg CH4 = 36 kg CO2e, 1 kg N2O = 264.5 kg CO2e) and from IPCC 2007 (32) (1 kg CH4 = 25 kg CO2e, 1 kg N2O = 298 kg CO2e) to study the sensitivity of our findings to the CH4 and N2O characterization factors (Table S2) and to compare our results to other studies. The effect of different C accounting methods (i.e., neutral biogenic CO2 emissions and biogenic CO2 emissions equal to fossil CO2 emissions (Table S3)) was also evaluated. Acidification and eutrophication were calculated using the TRACI v2.1 methodology. (33) CED was calculated using the methodology described by Frischknecht et al., (34) and ADP was calculated using CML v4.4. (35)

Background Life-Cycle Inventory Data

The ecoinvent (36) life-cycle inventory (LCI) database (v3.4) was used for background emission and resource use data associated with diesel, peat, fertilizers, and soil excavation. The LCI for electricity was based on the model presented in Hodge et al. (8) for the U.S. electricity grid and updated to the 2018 mix. (37) The Gridmix parameter is also defined to study the sensitivity of the results to efforts to reduce coal (currently 27% of US fuel mix). The environmental impacts associated with all background flows are shown in Table 3. The environmental burdens for conventional N fertilizer production are significantly higher than for P and K fertilizers, which suggests that the results are unlikely to be sensitive to the selected MFE for K and P.
Table 3. Environmental Impacts Associated with the Background System
flowunitGWP (kg CO2e)acidification (kg SO2e)eutrophication (kg N e)CED (MJ e)ADP (kg antimony e)
electricitykWh0.60.0040.0017.81.8 × 10–07
diesel equipmentL3.90.0330.02354.21.8 × 10–06
nitrogen fertilizerkg13.90.060.01972.67.0 × 10–05
phosphorus fertilizerkg0.60.0060.0045.31.0 × 10–05
potassium fertilizerkg2.00.0070.0025.01.5 × 10–06
peatMg28.70.1330.06510,1302.3 × 10–05
soil excavationm30.60.0050.0048.53.3 × 10–07

Input Data and Uncertainty Propagation

Probability distributions were developed for compost composition (Table 1) and each input parameter for the soil amendment and ADC scenarios (Table 2). Normal distributions were used when there was sufficient published data, uniform distributions were used when only a range was known, and triangular distributions were used when values were based on expert opinions with a reasonable value for the mode as suggested by Bisinella et al. (38) For parameters where only one value was available, log-normal distributions were developed based on the pedigree matrix and recommendations from ecoinvent data quality guidelines (39) for basic uncertainty in input data. A 20,000 iteration Monte Carlo analysis was performed to evaluate three offset options for the soil amendment scenario: (1) fertilizer only, (2) peat only, and (3) simultaneous offsets for both fertilizer and peat. Twenty-thousand iterations were determined to be sufficient based on convergence of the mean and standard deviation for all scenario results.

Results and Discussion

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Figure 2 shows how frequently each scenario outperforms the other in each impact category in each of the 20,000 iteration Monte Carlo simulations. The distributions of the impacts from the Monte Carlo simulations are shown in Figures S2–S9. Figure 3 shows the Spearman correlation between each input value and the difference in each impact category results between the ADC and soil amendment scenarios while offsetting both fertilizer and peat. This correlation analysis was used to identify the most critical inputs driving a scenario’s relative performance.

Figure 2

Figure 2. Fraction of Monte Carlo simulations in which each scenario outperformed the other in each impact category. The performance of two scenarios is considered tied when the difference between their score is less than 10% of the higher score. GWP is calculated according to IPCC 2013 and assuming that biogenic CO2 emissions are equivalent to fossil CO2.

Figure 3

Figure 3. Spearman correlation of the difference between the ADC and soil amendment (offsetting both peat and fertilizer) scenarios impacts with selected input parameters. A negative correlation indicates that increasing the parameter value improves the relative performance of the ADC scenario, while positive correlations mean that increasing the value improves the soil amendment scenario.

Across all three offset cases, the ADC scenario generally outperforms the soil amendment scenario in terms of GWP, eutrophication, and acidification, while the soil amendment scenarios are better in consideration of CED and ADP. Avoiding peat production slightly improves the performance of the soil amendment scenario in terms of GWP, because peat is considered a fossil resource; however, even when both fertilizer and peat are substituted, the ADC scenario outperforms the soil amendment scenario in ∼63% of simulations (Figure 2). The CED impact is primarily driven by the PeatDens and CompDens parameters (Figure 3) which are used to calculate the avoided peat production; however, the CED credits from the avoided fertilizer production are also large enough to outperform the ADC scenario in 94% of simulations (Figure 2). The relative performance in the eutrophication impact is primarily driven by NO3 leaching and runoff in the soil amendment scenarios (Figure 3). The acidification performance is highly correlated to NH3 emissions in the soil amendment scenarios, because a significant fraction of NH3 present in landfill leachate is oxidated to NO3 in a wastewater treatment plant before discharge. The relative performance in the ADP impact is dominated by the MFEN and N content of compost which are used to calculate the avoided N fertilizer production; this is due to the high ADP impact of nitrogen fertilizer production (Table 3).
The GWP results are driven by several factors: increasing the compost density improves the ADC scenario by decreasing the volumetric peat offset. Increasing the C content and landfill C storage also reduce the ADC scenario GHG emissions by increasing the total C stored in the landfill. However, increasing the peat substitution factor, peat density, and MFEN improve the soil amendment scenario by increasing the total peat and fertilizer substitution benefit. Increasing the moisture content also improves the soil amendment scenario by effectively reducing the wet C content of compost. Since some of these parameters combine in a nonlinear manner to affect the results, dual parametric sensitivity analyses were performed to investigate the collective effect of these parameters on the relative GWP (Figure 4). As shown in Figure 3, landfill C storage is a primary factor in determining relative GWP performance. This is because as landfill C storage increases, LFG emissions are reduced. Figure 4A shows that if the landfill C storage factor is less than 75%, then the soil amendment scenario outperforms the ADC scenario regardless of compost C content. If the compost has a C content of less than 14%, then the soil amendment scenario is preferable to ADC regardless of compost moisture content and landfill C storage (Figures 4A and 4B); however, 14% is a relatively low compost C content and would likely only be achieved if a large amount of soil was incorporated into the compost. Increasing the peat density and reducing the compost density combine to improve the relative performance of the soil amendment scenario by increasing the peat offsets. The peat density must be greater than 400 kg/m3, which is above previously reported ranges, for the soil amendment scenario to outperform the ADC scenario in terms of GWP using the default peat substitution factor of 1 and compost density of 700 kg/m3 (Figure 4C). Increasing the MFEN and compost moisture content combine to improve the performance of the GWP scenario by increasing the fertilizer offsets, but it is unlikely that they alone can change the scenario rankings (Figure 4D).

Figure 4

Figure 4. Dual parametric sensitivity analysis of the difference in GWP between the ADC and soil amendment (offsetting both peat and fertilizer) scenarios for selected inputs (kg CO2e). Negative values indicate that the ADC scenario has lower GWP, while positive values indicate that the soil amendment scenario has lower GWP. The white dashed lines show the results when using the default input values.

Results of dual parametric sensitivity analyses for the other impact categories are presented in Figures S10–S13. None of the driving factors alone can change the ranking of the scenarios based on eutrophication, ADP, or CED when offsetting both peat and fertilizer concurrently (Figures S10–S12), while the soil amendment scenario outperforms the ADC for the acidification impact when less than 12% of N is NH3 and regardless of the compost N content (Figure S13).
The effects of different GWP characterization values were also evaluated including the use of the IPCC 2007 GWP factors for CH4 (25 kg CO2e/kg CH4) and N2O (298 kg CO2e/kg N2O) emissions as well as using an alternative C accounting scenario (i.e., neutral biogenic C emissions) (Figure S1 and Table S8). Changing to the IPCC 2007 values from the IPCC 2013 values improves the performance of the ADC scenario relative to the soil amendment scenario, because it reduces the impacts associated with fugitive CH4 emissions from the landfill. Changing the carbon accounting method reduces the GWP of both scenarios; however, it does not change the relative rankings of the results (Figures S6–S9). Therefore, the specifics of the GWP accounting do not affect the general comparisons of the ADC and soil amendment scenarios for 100-year GWP.
Electricity is used in landfill site operation and is produced from landfill gas recovery. The contribution of electricity to the GWP of the ADC scenario is less than 5% (Figures S16 and S17), but it contributes 25-65% to the numeric results for other impact categories in the ADC scenario even though it has a relatively minor effect on the relative difference between the scenarios. As such, the effects are not significant enough to change the ranking of the scenarios, and therefore, these parameters are not shown in Figure 3.
Transport of compost from the composting facility to the landfill or farmland is excluded from the system boundary based on the assumption that the compost is transported equally in both scenarios. However, sensitivity analysis of the results to transport distance indicates that even a 50 km difference in the compost hauling distance between the scenarios only changes the relative rankings in 3% of simulations. While transport distance did not affect environmental impacts significantly, it can contribute up to 80% of the final cost of compost use as a soil amendment. Thus, if local markets are not available for the compost, then the use of compost as a soil amendment will not be cost-effective for farmers. (40)
Substitution of peat with compost is typically more applicable in gardening and small-scale applications, (29) so in larger applications it is more likely that the compost will only substitute for fertilizers. In practice, this could improve the relative performance of the ADC scenario (Figure 2).

Limitations and Implications

The results indicate that using OFMSW-derived compost as ADC in landfills can lead to specific reduced environmental impacts compared to its use as a soil amendment. Therefore, the use of compost as ADC should be considered, especially when unmodeled factors such as feedstock or end-product contamination or a lack of markets make it difficult to find appropriate applications of compost as a soil amendment. This is important as states like California are planning to exclude the use of OFMSW as ADC from their definition of diversion. (41) The results are generally driven by the fact that most of the applied C and N will remain stored in a landfill long-term due to anaerobic conditions, but a substantially larger fraction will be released when the compost is land applied. The relative sustainability of using compost as a soil amendment was improved when the compost had less carbon and more moisture, and when it received credit for both avoided peat and fertilizer use.
Using compost as a soil amendment has other positive (e.g., improving soil structure, (13) organic content, (10) and water holding capacity, (13) enhance crop yield, (42) and control plant pathogens (11,12,42)) and negative (e.g., soil metal content) impacts, which were not quantified here but could affect the decision-making process. Producing high quality compost for soil amendment application also improves P recycling. (43) P is a nonrenewable resource, and it is estimated that known P reserves will be depleted within 50 to 400 years. (43) It would be beneficial to evaluate these potential impacts in future work.

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.0c04997.

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Author Information

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  • Corresponding Author
  • Authors
    • Mojtaba Sardarmehni - Department of Civil, Construction, and Environmental Engineering, North Carolina State University, Campus Box 7908, Raleigh, North Carolina 27695-7908, United StatesOrcidhttp://orcid.org/0000-0002-8415-2057
    • Morton A. Barlaz - Department of Civil, Construction, and Environmental Engineering, North Carolina State University, Campus Box 7908, Raleigh, North Carolina 27695-7908, United StatesOrcidhttp://orcid.org/0000-0001-8028-3917
  • Notes
    The authors declare no competing financial interest.

Acknowledgments

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The authors would like to acknowledge support from the Environmental Research and Education Foundation (EREF) and the National Science Foundation (CBET-1437498).

References

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This article references 43 other publications.

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    van Haaren, R.; Themelis, N. J.; Barlaz, M. LCA Comparison of Windrow Composting of Yard Wastes with Use as Alternative Daily Cover (ADC). Waste Manage. 2010, 30 (12), 26492656,  DOI: 10.1016/j.wasman.2010.06.007
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  • Abstract

    Figure 1

    Figure 1. System boundaries and process flows for the developed scenarios. Using compost as a soil amendment can offset fertilizer and/or peat use, while using compost as ADC can offset soil excavation and electricity produced from collected landfill gas attributable to the ADC.

    Figure 2

    Figure 2. Fraction of Monte Carlo simulations in which each scenario outperformed the other in each impact category. The performance of two scenarios is considered tied when the difference between their score is less than 10% of the higher score. GWP is calculated according to IPCC 2013 and assuming that biogenic CO2 emissions are equivalent to fossil CO2.

    Figure 3

    Figure 3. Spearman correlation of the difference between the ADC and soil amendment (offsetting both peat and fertilizer) scenarios impacts with selected input parameters. A negative correlation indicates that increasing the parameter value improves the relative performance of the ADC scenario, while positive correlations mean that increasing the value improves the soil amendment scenario.

    Figure 4

    Figure 4. Dual parametric sensitivity analysis of the difference in GWP between the ADC and soil amendment (offsetting both peat and fertilizer) scenarios for selected inputs (kg CO2e). Negative values indicate that the ADC scenario has lower GWP, while positive values indicate that the soil amendment scenario has lower GWP. The white dashed lines show the results when using the default input values.

  • References

    ARTICLE SECTIONS
    Jump To

    This article references 43 other publications.

    1. 1
      US EPA. Advancing Sustainable Materials Management: 2015 Fact Sheet; Washington, DC, 2018.
    2. 2
      Levis, J.; Barlaz, M. A. Landfill Gas Monte Carlo Model Documentation and Results; Washington, DC, 2014. https://go.ncsu.edu/lf_warm (accessed 2020-12-07).
    3. 3
      Levis, J. W.; Barlaz, M. A. Is Biodegradability a Desirable Attribute for Discarded Solid Waste? Perspectives from a National Landfill Greenhouse Gas Inventory Model. Environ. Sci. Technol. 2011, 45 (13), 54705476,  DOI: 10.1021/es200721s
    4. 4
      Integrated Waste Management Consulting. SB 1383 Infrastructure and Market Analysis; Nevada, CA, 2019.
    5. 5
      Boldrin, A.; Andersen, J. K.; Møller, J.; Christensen, T. H.; Favoino, E. Composting and Compost Utilization: Accounting of Greenhouse Gases and Global Warming Contributions. Waste Manage. Res. 2009, 27 (8), 800812,  DOI: 10.1177/0734242X09345275
    6. 6
      van Haaren, R.; Themelis, N. J.; Barlaz, M. LCA Comparison of Windrow Composting of Yard Wastes with Use as Alternative Daily Cover (ADC). Waste Manage. 2010, 30 (12), 26492656,  DOI: 10.1016/j.wasman.2010.06.007
    7. 7
      Bernstad Saraiva Schott, A.; Wenzel, H.; La Cour Jansen, J.; Schott, A. B. S.; Wenzel, H.; Jansen, J. la C. Identification of Decisive Factors for Greenhouse Gas Emissions in Comparative Life Cycle Assessments of Food Waste Management - An Analytical Review. J. Cleaner Prod. 2016, 119, 1324,  DOI: 10.1016/j.jclepro.2016.01.079
    8. 8
      Hodge, K. L.; Levis, J. W.; DeCarolis, J. F.; Barlaz, M. A. Systematic Evaluation of Industrial, Commercial, and Institutional Food Waste Management Strategies in the United States. Environ. Sci. Technol. 2016, 50 (16), 84448452,  DOI: 10.1021/acs.est.6b00893
    9. 9
      Morris, J.; Scott Matthews, H.; Morawski, C. Review and Meta-Analysis of 82 Studies on End-of-Life Management Methods for Source Separated Organics. Waste Manage. 2013, 33 (3), 545551,  DOI: 10.1016/j.wasman.2012.08.004
    10. 10
      Hemmat, A.; Aghilinategh, N.; Rezainejad, Y.; Sadeghi, M. Long-Term Impacts of Municipal Solid Waste Compost, Sewage Sludge and Farmyard Manure Application on Organic Carbon, Bulk Density and Consistency Limits of a Calcareous Soil in Central Iran. Soil Tillage Res. 2010, 108 (1–2), 4350,  DOI: 10.1016/j.still.2010.03.007
    11. 11
      Litterick, A. M.; Harrier, L.; Wallace, P.; Watson, C. A.; Wood, M. The Role of Uncomposted Materials, Composts, Manures, and Compost Extracts in Reducing Pest and Disease Incidence and Severity in Sustainable Temperate Agricultural and Horticultural Crop Production - A Review. Crit. Rev. Plant Sci. 2004, 23 (6), 453479,  DOI: 10.1080/07352680490886815
    12. 12
      Chen, T.; Zhang, S.; Yuan, Z. Adoption of Solid Organic Waste Composting Products: A Critical Review. J. Cleaner Prod. 2020, 272, 122712,  DOI: 10.1016/j.jclepro.2020.122712
    13. 13
      Khaleel, R.; Reddy, K. R.; Overcash, M. R. Changes in Soil Physical Properties Due to Organic Waste Applications: A Review. J. Environ. Qual. 1981, 10 (2), 133141,  DOI: 10.2134/jeq1981.00472425001000020002x
    14. 14
      Hargreaves, J.; Adl, M.; Warman, P. A Review of the Use of Composted Municipal Solid Waste in Agriculture. Agric., Ecosyst. Environ. 2008, 123 (1–3), 114,  DOI: 10.1016/j.agee.2007.07.004
    15. 15
      Bruun, S.; Hansen, T. L.; Christensen, T. H.; Magid, J.; Jensen, L. S. Application of Processed Organic Municipal Solid Waste on Agricultural Land - A Scenario Analysis. Environ. Model. Assess. 2006, 11 (3), 251265,  DOI: 10.1007/s10666-005-9028-0
    16. 16
      Boldrin, A.; Hartling, K. R.; Laugen, M.; Christensen, T. H. Environmental Inventory Modelling of the Use of Compost and Peat in Growth Media Preparation. Resour. Conserv. Recycl. 2010, 54 (12), 12501260,  DOI: 10.1016/j.resconrec.2010.04.003
    17. 17
      Sardarmehni, M.; Anchieta, P. H. C.; Levis, J. W. Solid Waste Optimization Life-cycle Framework in Python (SwolfPy). https://go.ncsu.edu/swolfpy (accessed 2020-12-07).
    18. 18
      He, X. T.; Traina, S. J.; Logan, T. J. Chemical Properties of Municipal Solid Waste Composts. J. Environ. Qual. 1992, 21 (3), 318329,  DOI: 10.2134/jeq1992.00472425002100030003x
    19. 19
      Hansen, T. L.; Bhander, G. S.; Christensen, T. H.; Bruun, S.; Jensen, L. S. Life Cycle Modelling of Environmental Impacts of Application of Processed Organic Municipal Solid Waste on Agricultural Land (Easewaste). Waste Manage. Res. 2006, 24 (2), 153166,  DOI: 10.1177/0734242X06063053
    20. 20
      Boron, D. J.; Evans, E. W.; Peterson, J. M. An Overview of Peat Research, Utilization, and Environmental Considerations. Int. J. Coal Geol. 1987, 8 (1–2), 131,  DOI: 10.1016/0166-5162(87)90020-6
    21. 21
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