Sensitivity analysis
In this section, the parameters considered for the sensitivity analysis and the reasons for the respective SR obtained are discussed. In compost, N is organically bound and the amount of N immediately available to plants is limited. The N availability of organic fertilizers compared to mineral fertilizers can be represented by MFE, which is assumed to be 20% for organic compost [
51]. A higher MFE leads to a higher replacement quantity of mineral fertilizer and thus to a higher credit for the avoided emissions. The level of emissions avoided also influences the value of the SR; in this study, calcium ammonium nitrate has a GWP of almost 9 kg CO
2-eq. per kg N and was used as a substitute mineral fertilizer. Hence, in this case, the mineral fertiliser chosen for the replacement of N is also a determinative factor for SR. The substitution factor for N present in compost varied sharply based on the time scale chosen for the study. For the short term, the substitution factor for N content in compost was found to be 5–15% effective compared to mineral fertiliser according to Stadtmüller [
52] and Amlinger [
53], 20–30% according to Hansen et al. [
28] and 10% according to EPEA [
54].
The amount of C from the compost bound in the soil depends on the climatic and topographical conditions of the area under consideration. For fresh composting scenarios, the amount of C bound in the soil is the most influential parameter in the negative direction. The selection of a factor to represent the C bound to the soil is hence a potential source of uncertainty, a general factor of 7% was used in this study. Percentages of C bound to soil in the long-term ranged from 2 to 10% according to Fisher [
55], 9–14% according to Bruun et al. [
56] and 11% according to Diacono and Montemurro [
57].
The substitution factor for peat was estimated using the bulk density of both materials and it was found that to fill a defined volume, 2.9 times the quantity of mature compost was needed compared to peat. Peat substitution offsets the highest emissions for mature compost scenarios due to the emissions associated with peat production. According to Boldrin et al. [
30] this was estimated to be 986 kg CO
2eq. per tonne of peat produced. Since the substitution factor for peat is affected by a variation in the bulk density of the compost produced, the bulk density contributes significantly to influence the sensitivity of the modelled system.
During the composting process, more than 50% of the C present in the input material was released into the atmosphere mainly as CO2, whereas C degraded into CH4 accounted for 1–3%. Despite having a lower proportion of degraded carbon than CO2, CH4 had a considerable impact on the GWP emissions. CH4 was responsible for almost 94% of GWP emissions from the intensive composting and 50% of GWP emissions from the maturation process for OC. For PEC the share of CH4 in intensive composting emissions was 80% and the same as OC for maturation. Based on two parameters; the percentage of C degraded into CH4 and the proportion of C in the input material, CH4 emissions were calculated. An increase in either of the two parameters had an influence on the emission of CH4. Hence, from SR it can be seen that the influence of C fraction is comparatively higher than C degraded as CH4 for mature compost.
In a modelled system, the uncertainty involving the fraction of C degraded as CH
4 is difficult to estimate since several factors influence this parameter [
3]. The main parameters influencing CH
4 formation were aeration and turning frequency, for well-managed systems C degraded as CH
4 was reported to be low [
58]. However, the large particle size of the materials causes anaerobic pockets to form in the early stages of composting. Therefore, a significant portion of CH
4 emissions, ranging from 75 to 90% of the total CH
4 emissions during composting, often occur in the first few weeks [
7]. The formation of CH
4 due to the anaerobic pockets can be mitigated with a higher turning frequency and forced aeration as they contribute to the breakdown of these pockets and the degradation of C mainly takes place as CO
2. Lower CH
4 emission during PEC compared to OC can be attributed to the higher turning frequency and the presence of forced aeration systems.
The relationship between the N fraction in input material and N released as N
2O is similar to the previously mentioned relation between the C fraction and C degraded as CH
4. Looking closely at the parameter N degraded as N
2O, we can see that it predominantly influenced N
2O emission during composting but had a limited influence on N remaining in the compost. The limited influence was mainly because the share of N degraded as N
2O from the total N degraded was less than 10%. In the modelled system, the higher N proportion in the input material causes an increase in N in the compost product in addition to having an impact on the N
2O emissions. The higher N content in compost resulted in higher N
2O emissions, which were counterbalanced by the substitution of additional mineral fertilizers. Because there were fewer N
2O emissions during the intense composting stage, the effect of N fertiliser substitution on SR in FC is greater than the effect of N
2O emissions. As a result, the SR for the parameter N fraction was negative for FC. Since about 75% of the total N
2O emissions occur during the maturation stage, the impact of N
2O emissions on SR for MSC was considerably greater [
12].
The reason for lower N
2O emissions in the intensive composting stages can be attributed to the higher temperatures compared to the remaining composting stages. Usually for a temperature above 40 °C nitrifiers cease to exist, hence hindering the formation of N
2O. Furthermore, a high aeration rate and effective stripping of NH
3 during the intensive composting were also found to hinder N
2O formation [
7].
In this study, the dry matter content in the waste material was used to determine the C and N content for biowaste and garden waste with values from literature [
13]. The influence of the parameter moisture content on MSC_PEC is the greatest compared to other parameters. The reason for the strong increase in overall impacts despite a reduction in C and N in the input material can be attributed to the lower quantity of end compost produced. The amount of compost produced was reduced by nearly 16% due to a 10% increase in moisture content. Because there was less compost, less peat could be substituted, which reduced the emissions offset from peat substitution by nearly 16%. As previously stated, peat substitution is one of the most influential parameters for mature composting; thus, changes that influence peat substitution have an impact on the SR. The OC had higher emissions from the composting process than the PEC, so the impact of the emissions was greater than the savings from offset emissions. As a result, the SR for moisture content was less influential than the parameters involving the C fraction in OC. According to Clavreul et al. [
22], the influence of moisture content on SRs was found to be negative for waste management systems such as incineration and anaerobic digestion. This implied that higher water content resulted in lower GWP impacts; this would have been the case in this study as well if the emissions offset was of lower magnitude or if the offset emissions were not considered.
Lower offset emission influence is visible in the FC, where the SR for moisture content is comparatively low and even negative for PEC and OC. Biowaste and green waste are mixed together in the composting plant to achieve the ideal material consistency for composting. The composition of moisture content, C, and N in the input material mixture changes as the proportion of biowaste or green waste changes. A greater proportion of biowaste increases the moisture and nitrogen content of the input mixture while decreasing the C [
13]. Across all combinations, the direction of influence of the parameter share of biowaste was oriented with the parameter N fraction. This implies that, similar to the parameter N fraction, lower N
2O emissions during the intensive composting stage influenced SR for the share of biowaste to remain negative for FC.
It was seen the sensitivity can vary depending on the transport distance since a greater distance covered would lead to higher total emissions, which means that the proportion of transport-related emissions increases. Therefore, when interpreting the results, the influence of the transport distance on the value of SR should be taken into account. The influence of the energy consumption parameter is relatively higher for PEC since PEC is more energy-intensive than OC.
In this study, a CH
4 reduction potential in the biofilter of almost 15% was assumed according to Amlinger et al. [
7]. Other studies confirm the high uncertainty of the CH
4-formation in the biofilter; a range between 7 and 27% is mentioned [
59]. The oxidation of CH
4 to CO
2 in the biofilter takes place with the help of methanotrophic bacteria in the filter material. In some cases, it has been reported that there is a potential for further formation of CH
4 in the biofilter due to anaerobic pockets and the exact dynamics involved in the effect of NH
3 requires further investigation. Hence, the parameter CH
4 reduction involves uncertainty and this uncertainty should be considered during the interpretation of CH
4-sensitive results.
Uncertainty propagation
The boxplot obtained from the Monte-Carlo simulation reveals the range of uncertainty arising from the input values for each parameter. Although the results for SC and SR were used to interpret the Monte Carlo simulation result, they only provided information on the influence of each parameter on the uncertainty. In order to interpret the result, it was necessary to have information about the total uncertainty in the input values for each parameter. It should also be noted that the result's high minimum and maximum values could be due to a random combination of input values that may not be plausible in a real composting process. The goal of the Monte-Carlo simulation, on the other hand, was to understand the overall uncertainties in the model and to take these uncertainties into account when comparing the results for the combinations.
For MSC, the most influential parameters were found to be the peat substitution factor and moisture content in the input material. However, taking the variability of input values into consideration, it was seen that the relative standard deviation (RSD) for peat and the moisture was 12% and 6% respectively, compared to this the RSD for the parameter C fraction degraded as CH
4 was almost 30%. The uncertainty of C-fraction degraded as CH
4 was estimated according to the CH
4 emission values based on UBA [
12]. For PEC, the minimum and maximum values for CH
4 emitted per tonne input material ranged from 830 to 4800 g, with a median value of 1200 g, and for OC, the values ranged from 730 to 5500 g, with a median value of 1800 g. As a result, the Monte-Carlo analysis results show a combination of moderately high SRs of 1.1 and 2.3 for PEC and OC, respectively, as well as an RSD of 30% in the input values for C degraded as CH
4.
C degraded as CH
4 was the most influential parameter for FC (Fig.
3) with an SR ranging from 0.9 to 1.2. This, together with a relatively high RSD of nearly 30%, had a significant impact on the overall uncertainty of FC. The influence of C degraded as CH
4 on FC was clear when comparing the skewness in the input values for C degraded as CH
4 and the output results used for the box-plot. For FC, the input skewness was 0.58, which was close to the output skewness of 0.53, but for MSC, the input and output skewness were 0.45 and 0.25, respectively. The smaller difference in skewness between the input and output parameters can explain why C degraded as CH
4 has a greater influence on FC. The influence of high maximum values for C degraded as CH
4, as well as its relatively higher SR, can explain the increase in the median values for the GWP balance in Monte-Carlo simulation.
The uncertainty of AP values in OC was caused by NH3 emissions ranging from 14 to 1183 g NH3 for the MSC and 9 to 1057 g NH3 for the FC. However, the range of NH3 emissions for PEC was significantly lower than for OC, so the uncertainty was lower in this case. The main source of uncertainty in the results for the impact category OFP was NOx emissions from the waste collection process. Because the value of NOx varied with transport distances, the uncertainty in the result for this impact category is highly dependent on the assumed distances. The results for the impact categories ODP were estimated using N2O emissions and the lower values for OC can be attributed to the lower N2O emissions due to the lack of a biofilter.
Comparison of LCA results with literature data
LCA studies on composting of biowastes and green cut material mainly focus on the associated GHG-emissions, seldomly measured and more frequently modelled. Therefore, the GWP is used for comparing the results of this study with results from other peer-reviewed publications. The studies compared in this section have varying input material, and composting parameters and produce different compost qualities, a reasonable comparison of the GWP results is consequently limited. When considering only GHG-emissions and excluding credits, then the GWP ranges from 50 to 100 kg CO
2eq.per t input material in this study. Considering similar LCA studies, i.e. similar input material and composting conditions, the GWP reported by Kim and Kim (2010) for producing compost from 1t food waste was found to be almost 123 kg CO
2eq. [
60]. A GWP of up to 81 kg CO
2eq. from composting of 1t household biowaste was reported by Boldrin et al., (2009) [
61]. A GWP of 218 kg CO
2eq. per tonne of organic fraction of municipal solid waste was estimated by Weligama Thuppahige et al., (2022) [
62]. Similarly, Eriksson et al., (2015) estimated a GWP of 43 kg CO
2ep.from composting 1t food waste. The results calculated in this study show a similar range to the presented studies with somehow comparable input materials and the presented results are therefore plausible. Composting of agricultural wastes was found to cause almost 200–250 kg CO
2eq. per ton of waste handled [
63], hence, different input materials and process conditions can also cause a higher GWP. Similar to the findings of this study, the other studies also identified the direct emissions due to the decomposition of organic as the main contributor to GHG-emission of composting [
35,
64]. Overall it can be seen that the range of GWP associated with composting of biowaste ranges between almost 40 and 250 kg CO
2eq.. This wide range can be attributed to multiple factors, however, the emission factor for methane formation used to estimate direct CH
4-emissions from the composting process is the most relevant for GWP. The turning frequency, type of composting process and input material influence the GHG-emissions, respectively the associated emission factors [
16].