1. Introduction
The linear economy model has overlooked for decades huge opportunities to harness valuable materials. As the adage goes, the waste of one person may be the treasure of another, and those people could be a mushroom producer and a farmer.
The growth and harvesting of white button mushrooms (Agaricus bisporus) are relatively complex activities that encompass substrate preparation, spawning, growth, harvesting, and waste management. White button mushrooms grow in a manure-based compost that contains lignocellulosic materials, particularly wheat straw. Once the mushrooms have been harvested, the substrate, casing layer, and remaining mushroom debris—a mixture called spent mushroom substrate—are typically managed as a waste of the system, squandering a nutrient- and organic-carbon-rich mixture.
Recent business and regulatory shifts towards a circular economy have shed light on the opportunity of marketing spent mushroom substrate (SMS) as a soil improver, particularly useful for use in agriculture, orchards, or even the growth of other species of mushrooms.
Within the FER-PLAY project, whose objective is to contribute to the adoption of sustainable fertilization practices by identifying the impacts and tradeoffs of alternative fertilizers, SMS was selected as one of the seven most-promising circular fertilizers in the European Union after mapping over 60 fertilizers produced from waste streams. The selection was based on data availability, nutrient content, soil improvement capacity, toxicity, technical viability (Technology readiness level, TRL > 5), versatility to comply with legislation in different EU countries, and their potential for replication at industrial scale [1].
Based on that selection and the subjacent trends, it is crucial to understand the implications of using SMS as a soil improver, both in its environmental and economic dimensions. Sustainability and circular economy are not intuitive subjects that may be easily predicted, but rather require in-depth assessments to identify both the advantages and disadvantages of a given product, service or activity for the environment and the economy. Therefore, such assessment is hereby presented, aiming to bridge the knowledge gap on the environmental impacts and cost structure of the spent mushroom substrate value chain.
1.1. Spent Mushroom Substrate
When producing mushrooms, 3.3 tons of SMS are generated per ton of mushroom harvested [2]. The European Mushroom Growers Group—which represents mushroom producers accounting for 94% of total European production—produced 1.07 million tons in 2022 [3]. This means roughly 3.5 million tons of waste per year.
However, SMS is actually a high-value material that can be harnessed in agriculture as a soil improver. Its nutrient and carbon content is detailed in Table 1. Using the conventional fertilizer nomenclature (N:P as P2O5:K as K2O), SMS has a 0.9:0.9:2.1 nutrient content, but, as seen in Table 1, its biggest advantage is precisely its high carbon content, which contributes to soil health and structure when applied to agricultural land.
Mapping SMS origin requires going back to mushroom fresh substrate production. In Europe, fresh substrate is obtained by the composting of a mixture of chicken manure, gypsum, and/or wheat straw, horse manure, and lime. The exact weight of each component in the mix varies depending on local availability. After this first composting, the fresh substrate is also called “phase 1 substrate”. It then undergoes a pasteurization stage, after which it is called “phase 2 substrate”. Finally, mushroom mycelium is spawned in the substrate, and from that point on, it is referred to as “phase 3 substrate”. Mushroom growers can either purchase phase 2 substrate and make the spawning themselves, or acquire phase 3 substrate and directly grow the mushrooms after adding a casing layer of peat [7].
Mushroom cultivation takes place in temperature- and humidity-controlled chambers, ensuring that the environment is kept sterile (using disinfectant), free of pests (using pesticide), and free of fungi (using fungicide) [8]. Once the mushrooms have grown to the desired size, they are collected, and the remaining substrate is gathered and sent to an additional composting stage, after which it can be considered a product suitable to be used as a soil improver (i.e., SMS).
1.2. Sustainability Assessment Tools
The sustainability of products is being increasingly assessed following life cycle thinking, which aims to account for all the activities conducted from the very first extraction of raw materials all the way to the use and subsequent disposal of products. The main tool used to conduct such an analysis is the Life Cycle Assessment methodology.
Life Cycle Assessment (LCA) is a tool envisaged to support decision-making processes, considering the entire life cycle of a product or service by “quantifying the pollutant emissions and the use of raw materials based on the function of the product or system” [9].
By applying LCA methods, the Life Cycle Inventory (LCI, listing all the material and energy flows between the ecosphere and the technosphere) serves as input to obtain the environmental impacts of the system, distributed in so-called impact categories including climate change, eutrophication, particulate matter, acidification, and land use, among others.
It is being widely used and encouraged in the sustainability management realm. LCA has been standardized through ISO 14040/14044 [10,11]. Particularly, the European Commission has published a methodology for conducting LCAs of activities occurring in its territory, called the Product Environmental Footprint (PEF) [12]. Its application is gaining traction, working as a foundation for instruments such as the greenhouse gas (GHG) protocol, the Corporate Sustainability Reporting Directive (CSRD), the Ecodesign for Sustainable Products Regulation (ESPR), the Product Carbon Footprint (PCF), and the Environmental Product Declarations (EPD) [13,14,15,16].
While LCA results are deemed useful for the identification of barriers during the upscaling of technologies, they must be carefully interpreted, due to high data uncertainty and the need to make several assumptions during its process [17].
Life Cycle Costing (LCC) is also a tool whose objective is “to assist decision-makers in selecting the most appropriate alternative options” [18] in this case, by summing up the total costs incurred associated to a product, process or activity discounted over its lifetime. It is based upon the idea that the purchase price does not usually reflect the full costs induced by a product during its whole lifetime.
Traditionally applied in its conventional or corporate form (assessing the costs incurred by an enterprise, usually the producer, associated with a specific product), within the framework of a Life Cycle Sustainability Assessment (LCSA), a different approach is followed to account for the economic dimension of sustainability—the environmental LCC. This summarizes all the costs borne by all the relevant stakeholders involved in the life cycle, including externalities that are anticipated to be internalized in the relevant future.
Environmental LCC is an analysis that is complementary to the environmental LCA and shares its goal, scope, and system boundaries [19].
1.3. State of the Art
Mushroom cultivation and specifically SMS have been receiving increasing attention from the scientific community, though with varying approaches. Verma et al. [20], Oliveira et al. [21], and da Silva et al. [22] have studied the effects of using SMS as a biofertilizer on the growth of mung bean, tomatoes, and maize, respectively. Their target variables have mainly included the germination and growth rate, seedling quality, and physicochemical characteristics of the crops. While founding a positive effect on some of those variables, they did not consider the environmental or economic impacts of SMS usage. Likewise, Medina et al. [23] assessed the effects of applying SMS to soils, particularly the relationship between physico-chemical, chemical and biological properties.
From the LCA perspective, Leiva-Lázaro et al. [24] and Leiva et al. [25] conducted assessments for evaluating the environmental impacts of the fresh substrate production process alone. Likewise, Leiva et al. [26] assessed the mycelium production stage. Dorr et al. [27] put the focus instead on the mushroom cultivation process; even though they considered the carbon sequestered as a result of SMS usage as fertilizer and the avoidance of waste management impacts, their approach did not shed so much light specifically on SMS impacts. Leiva et al. [28], on the other hand, also conducted an LCA of mushroom cultivation, but modeled SMS as a waste that was disposed of. Following that train of thought, Robinson et al. [29] conducted an LCA on a model of mushroom production that allocated impacts to SMS via two alternatives: an economic allocation approach and a synthetic–fertilizer–displacement approach. Gunady et al. [30] also applied LCA methods to mushroom production, but focusing solely on global warming’s potential impacts.
Leiva et al. [8] elaborated scenarios for the reduction in environmental impacts in Agaricus bisporus production by conducting LCA, but none of their scenarios were related to SMS.
From a different standpoint, Mohd Hanafi et al. [31] compiled “environmentally sustainable applications” of SMS, used not only as a fertilizer but also in energy production, animal feedstock and wastewater treatment activities. Their focus was on highlighting the potential applications to avoid the environmental pollution associated with current disposal methods.
The analysis of the currently available studies on SMS allows us to identify a knowledge gap on the environmental and economic sustainability of SMS when used specifically as a soil improver for agriculture activities.
For conducting LCA, several software applications are available. They are based on cause–effect relationships, and the characterization and emission factors that allow us to calculate environmental impacts from inventory data. These software applications offer an interphase to researchers and practitioners who seek to conduct LCA calculations when coupled with datasets. Such datasets are developed by experts who gather all the inventory data and the environmental impacts associated with common processes, such as electricity generation and distribution, or chemical production, distribution and consumption.
1.4. Study Goals and Framework
The purpose of this study is to evaluate the environmental impacts of using SMS as a soil improver, comparing it with a non-renewable equivalent, and the aggregated economic (monetary) value that SMS represents for society. This is pursued by following environmental LCA and LCC methods, evaluating all the stages between mushroom fresh substrate production and SMS application on agriculture soil. Both environmental and economic aspects are paramount in the context of the expected increase in use of this waste stream as a value-added product in agriculture.
2. Materials and Methods
Following the LCA’s widely applied standards (ISO 14044) [11], the following sections detail how the study was defined and conducted.
2.1. Goal and Scope
The goal of the study is to assess the environmental and economic impacts of harnessing mushroom production waste (SMS) as a soil amendment in agriculture, considering the differences among three climate-segmented European regions.
The scope is set as cradle-to-gate-to-grave, meaning that the entire life cycle of the product from the extraction of the raw materials until the application of the soil amendment on agricultural soils is included. However, given that available data entail different levels of uncertainty between the production and use stages, the decision to split the data and results into two segments (cradle-to-gate, and gate-to-grave) was made, aiming to present both total and per-stage results, and allowing readers to make better-informed decisions.
2.2. Functional Unit
The functional unit is set as the supply of nutrients and carbon to agricultural soils, with a reference flow of 1 ton of SMS. The specific quantitative values associated with the functional unit are detailed in Table 2.
2.3. System Boundaries
The system under study starts upon the arrival of the secondary raw materials (i.e., waste streams such as manure and wheat straw) to the fresh substrate preparation facilities, and extends until the application of the SMS to agricultural soil. The upstream impacts of waste materials are left out of system boundaries, as seen in Figure 1. This approach follows EPD guidelines on allocating waste stream impacts, assigning its associated impacts to the system that produced them (here, for example, chicken manure impacts are assigned to the poultry industry) [32,33].
The ancillary activities included in the system boundaries are electricity, diesel, heating fuels, water, peat, lime, gypsum, woodchips, chemicals, and mushroom mycelium consumption, transportation, and landfilling, and the incineration of wastes. The main processes are the fresh substrate preparation (comprised of composting, pasteurization, and spawning), mushroom cultivation, re-composting, and the use of SMS (spreading with agricultural machinery).
Under this approach, the main co-products are the white button mushrooms (Agaricus bisporus), which in reality are the main focus of this system. All the discarded materials and the leachates generated during the composting and harvesting stages are considered to be recirculated to the system.
The only waste considered in the system is the exhausted woodchips that are used during the fresh substrate preparation stage as part of the biofilter employed to reduce GHG emissions. This material is sent for landfilling and incineration.
2.4. Data Sourcing and Limitations
For conducting such LCA, data from different sources were harnessed. With the aim of ensuring that the highest-quality available data were used, the following data hierarchy was set:
Primary data at industrial level provided by external companies or FER-PLAY project partners (i.e., research institutes and associations of farmers, waste managers, and circular fertilizer producers);
Secondary data publicly available in official reports, databases, academic literature, and technical handbooks.
It is relevant to highlight that the required datapoints for this specific assessment are scarce, diverse (i.e., not necessarily inter-operable), not always regionalized, and scattered. This endows the assessment with a non-negligible level of uncertainty. However, the strategies put in place to ensure the highest quality level possible are deemed enough to produce a reliable study that sheds light on the trends and magnitudes of the environmental and economic impacts of the use of SMS as a soil improver.
2.5. Critical Assumptions and Modelling Choices
2.5.1. Regional Distribution
The European Union member states are distributed into three regions, based on their climatic similarities. The distribution is detailed in Table 3.
The main difference among regions is the ‘recipe’ used to produce the fresh substrate. While countries with the appropriate climate and enough land area to grow cereals use wheat straw as a main component of fresh substrate, countries that do not have those characteristics (e.g., northern countries) tend to use horse manure as a substitute. This difference in ingredients, as detailed in Table 4, is the main reason for the environmental and economic profile differences.
2.5.2. Energy Supply
As the modeling comprises the study of a group of countries, it was necessary to build a representation of the electrical grid of each region. The electricity production of each region was thus obtained from the Eurostat database [34], and after calculating the total electrical output of the region, the contribution of each country was obtained (See Tables S1–S3).
Ecoinvent datasets were used, weighting the electricity market process for each country according to its weight in the regional electric output.
Regarding heat, a similar modeling approach was followed. In this case, two groups of energy vectors were defined: natural gas and non-natural gas fuels. Based on Eurostat data [34], the weight of each one was obtained and consistently applied in environmental modeling (See Tables S4–S6).
2.5.3. Waste Management
Wastes produced by the studied system (i.e., exhausted woodchips) are treated differently depending on the target regions. Table 5 details the weight of each wood waste treatment process among the target regions.
2.5.4. Transportation
Two types of transportation were modeled for the study:
Short-distance transportation—A fixed distance of 50 km was considered for the transportation of waste streams, intermediate products, and SMS. It is assumed that these trips are made by trucks > 32 tons;
Long-distance transportation—Used for the transportation of chemicals, supplies, (virgin) raw and intermediate materials that are not sourced locally. The PEF [12] guidance of assigning 130 km by truck (>32 tons, EURO 4), 240 km by train (average freight train), and 270 m by ship (barge) was followed.
2.5.5. Emissions
Several sources were used for modeling system emissions. Table 6 details the emission factors used for the composting (i.e., fresh substrate preparation and recomposting) and the application on soil stages. The model only included biofilters for abating ammonia emissions during fresh substrate preparation; recomposting takes place without a biofilter. When modeling N2O emissions to air, northern and central regions were assumed to have a wet climate, and the Mediterranean region to have a dry climate.
Emissions from heating (during pasteurization and mushroom growing) and non-road mobile machinery utilization (during fresh substrate preparation, recomposting and soil application) were sourced from the EMEP/EEA air pollutant emission inventory guidebook [36].
2.5.6. Environmental Impact Allocation
The system modeled is a multifunctional one, as it produces mushrooms and SMS. To pin point SMS’ impacts, an appropriate allocation of impacts between it and mushroom output is needed. Considering the use of mushrooms (food), a system expansion seems complicated to perform. Also, there is no relevant physical relationship between the production of mushrooms and SMS, so the path followed was to conduct an economic allocation.
Table 7 details price values and mass output for each of the co-products and the allocation factors derived from them.
Allocation factors are applied to fresh substrate preparation and mushroom cultivation stages. For the recomposting and use phase, impacts are allocated entirely (100%) to SMS, as mushrooms have already exited the system by that point.
2.6. Inventory
The LCI constitutes the backbone of the assessment. It summarizes all the material and energy flows between the system, the technosphere and the ecosphere, including all emissions to air, freshwater and soil. The LCIs used for the assessments are presented in the Supplementary Material (Tables S7, S15 and S22).
2.7. Baseline
The baseline was selected according to the functional unit, by selecting non-renewable suppliers of an amount of nutrients and carbon equal to that supplied by SMS. The Ecoinvent process datasets detailed in Table 8 were used to model the cradle-to-gate impacts of the nutrient mix.
Datasets for N, P and K represent an aggregation of the market datasets of an assortment of available fertilizers commercialized in Europe. Peat, for its part, was modeled with a specific process dataset. It was selected as a non-renewable supplier of carbon to be applied on soils.
2.8. Life Cycle Costing Methodology
As De Menna et al. [19] have detailed, there are three types of LCC: conventional, environmental and societal. With the aim of matching both LCA and LCC system boundaries, the environmental LCC method was followed. It summarizes all the costs borne by all the relevant stakeholders involved in the life cycle. The stakeholders are the fresh substrate producer, the mushroom producer, and the farmer.
The annual costs incurred by each stakeholder were calculated, and we sourced data in accordance with the data quality hierarchy detailed in Section 2.4. Annual data were then projected in a 15-year time span without considering inflation and applying a discount rate of 4% to obtain the net present value (NPV). The NPV was ultimately divided by the total mass production during the same time span, resulting in the LCC result (EUR per functional unit).
To conduct the calculations, a representative size of annual production had to be set for each region. This was done with the available data, following the hierarchy detailed in Section 2.4. The results of the size calculations and associated capital investment costs are detailed in Table 9.
The three fresh substrate production facilities were set to an installed capacity of 2000 tons of waste materials treated per year; this is why the required investment for this stage is the same across regions. The production differences are linked to the recipes (see Table 4), which has consequently resulted in different yields from that point on.
Other relevant costs include electricity, heating, chemicals, water and labor. For electricity, a simple average was calculated, based on the annual average price of electricity per country in the last five years [34].
For heating costing, it was necessary to identify the types of heating fuel most used in each country, sum up these values, and get the most used in each region. This resulted in: primary solid biofuels (taken as wood for pricing purposes), solid fossil fuels (hard coal), and oil and petroleum products (heating gasoil). With the corresponding prices per country, the regional average, and the weight of each fuel type in each region, the average price of heating was obtained for each of the regions under study [34].
Chemical costs were modeled using data from the International Trade Centre [41], comprising the import price for each of the countries under study, from which the average price per region was calculated. Water costs were averaged using data published by water utilities suppliers from a sample of countries within each region.
Labor costs were sourced from the International Labour Organization [42]. Manufacturing wages were assigned for activities related to waste treatment activities (fresh substrate preparation and recomposting), and agriculture, forestry and fishing wages were assigned to agriculture activities (mushroom production, and fertilizing).
Table 10 details all the costs used for different items among the three regions.
2.9. Software and Life Cycle Impact Assessment (LCIA)
The mid-point impact categories of the PEF 3.1 were calculated making use of LCA-dedicated software application LCA for Experts® v.10.7.1.28 (previously GaBi) developed by Sphera. This application was coupled with Ecoinvent 3.9.1 datasets.
All impact categories representing at least 5% of the total impact (single score, obtained after normalization and weighting, in accordance with PEF 3.1 guidelines) were then analyzed and discussed.
3. Results and Discussion
Upon obtaining the results for all the impact categories included in the Environmental Footprint 3.1 methodology (available in the Supplementary Material), the subsequent normalization and weighting calculations were conducted. This resulted in the identification of five impact categories that added up 99.99% of the total impact.
3.1. Identification of the Most Relevant Environmental Impact Categories
As can be seen in Figure 2, the five categories concentrating practically all the environmental impacts of both SMS and the non-renewable baseline are land use, fossil resource depletion, freshwater ecotoxicity, water use and climate change.
Identifying this distribution helps in narrowing the analysis to a smaller set of impact categories, which, in fact, represent virtually all the environmental impacts.
3.2. Results per Environmental Impact Category
Having narrowed the analysis to the impact categories accounting for the grand majority of the impacts, the specific analysis of the results for each one of the identified impact categories allows us to pinpoint the origins of such impacts, raising the awareness and knowledge of the environmental impacts of harnessing SMS as a soil improver.
3.2.1. Land Use
The most important impact category for both SMS and the non-renewable baseline is land use, accounting for 69 ± 4 and 54% of the impacts, respectively. However, this similarity regarding the impact weight is not retained in the actual impact of each system.
As Figure 3 details, the non-renewable baseline land use impact is seven times bigger than that of SMS, regardless of the region. Also, almost the entirety of the impact belongs to the production stage.
The main causes of the SMS land use impacts are woodchips production (41%), road transportation (28%), and electricity (10%). Woodchips impacts, in turn, come from intensive and extensive forestry; road transportation impacts come from the road network accounting for traffic area, and electricity impacts come from intensive and extensive forestry and dump sites. For the non-renewable baseline, the main causes are mineral extraction sites (30%), dump sites (28%), and construction sites (9%).
It is relevant to remember that land use impacts only refer to the area of land being occupied and/or transformed for the functional unit [12]. This means that during the production of the non-renewable baseline, soil is subjected to substantially greater changes and modifications, negatively affecting its ability to supply ecological services; during the production of SMS, on the other hand, these effects on soil are notably lower.
Also, the benefits or effects on other soil attributes (such as soil texture, aggregation, moisture, porosity, bulk density, soil pH, total C and N, organic matter, biodiversity, etc. [43]) as a result of the application of fertilizers are not accounted for in this impact category because of the lack of appropriate indicators and characterization and emission factors. Such variables have been reported to be among the biggest advantages of using organic soil improvers, such as SMS [43,44].
3.2.2. Resource Depletion, Fossils
Fossil resource depletion accounts for 20 ± 3% of the impacts of SMS and for 35% of the non-renewable baseline’s impacts. Figure 4 conveys the huge difference in the magnitude of the impact.
This wide difference is logical, given that non-renewable fertilizers are produced through fossil-resource-intensive processes, wherein petrochemistry plays a major role. On the other hand, the fossil resource consumption of SMS comes mostly from energy consumption. This explains why the impacts of the non-renewable scenario are almost 20 times higher than those of the SMS, regardless of the region.
3.2.3. Ecotoxicity, Freshwater
The third most relevant impact category is freshwater ecotoxicity, which accounts for 7 ± 1% of SMS’s impacts, and 10% of the non-renewable baseline’s impacts. SMS has a significantly lower impact on this category, as can be seen in Figure 5.
The sources of freshwater ecotoxicity for SMS are iron, hydrogen sulfide, nickel, and aluminum emissions into freshwater, 57% of which occur during the mushroom cultivation stage. On the other hand, the non-renewable baseline emits chloride and iron into freshwater during its production stage.
3.2.4. Water Use
In contrast to the rest of the impact categories, SMS entails higher water use impacts than the non-renewable baseline, as can be seen in Figure 6. It represents 1.9 ± 0.2% of SMS’s total impacts, and 0.09% of the non-renewable baseline’s impacts.
The impacts of both systems come logically from the water they consume, mostly during production stages. For SMS, the water consumption is distributed as follows: 41% during recomposting, 32% during fresh substrate preparation, and 27% during mushroom cultivation.
3.2.5. Climate Change
Climate change accounts for 2 ± 1% of the SMS impacts, and for 0.4% of the non-renewable baseline. As can be seen in Figure 7, the main difference is the stage at which the impact is caused—while SMS’s production stage makes the most contributions to climate change (excluding biogenic carbon emissions from the analysis, as they belong to the short carbon cycle [45]), for the non-renewable baseline, the use phase is the most highly polluting one.
The main reason for the non-renewable baseline’s use phase being more polluting is the presence of peat in its mix, and its high CO2 emission factor (0.2216 kg CO2/kg peat [46]). On the other hand, the lower carbon footprint of the non-renewable production is due to the high efficiency of the industrialized processes of fertilizer production, which do not require as much raw material to produce the same amount of nutrients as are contained in SMS.
It is worth noting that SMS, as a bio-based soil improver, has a carbon sequestration effect, which is represented via negative climate change impacts during its use phase.
When disaggregating climate change results into their three constituents (namely, biogenic, fossil, and land use and land use changes (LULUC)), additional differences can be identified. When going through Table 11, it becomes evident that most of the CO2 emitted in the SMS system (67 ± 6%) is of biogenic origin, mostly coming from composting stages. On the other hand, the greatest source of the climate change impact of the non-renewable baseline is fossil emissions, representing 68% of the total climate change results (33 ± 6% for SMS). The LULUC emissions of the non-renewable baseline are not negligible, and are mostly driven by the usage of peat, which implies its extraction from peatlands, therefore contributing to LULUC’s climate change results.
3.3. Environmental Hotspots Identification
The results of the LCA also allow the identification of the life cycle stages wherein the greatest impacts occur. After normalization and weighting, a single score was obtained, and the contributions of each stage to this score were identified. These results are presented in Figure 8.
The results across different regions are nearly identical, as reflected in the standard deviations shown in Figure 8. It becomes evident that the recomposting stage accounts for over 90% of the environmental impacts, which is primarily driven by land use (60%) and fossil resource depletion (20%).
The minimal contribution of the fresh substrate preparation and mushroom cultivation stages should be interpreted cautiously, as it largely results from the allocation method conducted. Since 99.81% of the impacts from these stages are related to the mushrooms, the SMS system inherits only a small portion of the impacts from these processes. Without allocation, however, the fresh substrate preparation and mushroom cultivation stages would accumulate 93% of the total impacts of the multifunctional system.
The concentration of impacts in mushroom production aligns with the system’s raison d’être, as the primary objective is to harvest and commercialize mushrooms. If SMSs were treated as a waste, mushrooms would bear the entirety of the system’s impacts. However, since SMS is repurposed and further processed (i.e., through recomposting), a portion of the mushroom production’s impacts is allocated to it, based on its economic value.
3.4. LCC Results
The life cycle costing of SMS revolves around the production and sale of mushrooms. SMS is a waste of the mushroom production process, which can be harnessed to produce a value-added by-product. Therefore, the calculation of the SMS’s LCC benefits from the revenue stream associated with the sale of mushrooms. Regardless of the region, the revenue obtained for the sale of mushrooms is of EUR 1151.29 (see Supplementary Material).
The regional differences that are observed in Figure 9 are caused by the different yields. The starting points for SMS production are different among regions (see Table 4), therefore fresh substrate yields differ, and with them, SMS production. This means that, for example, while capital costs for fresh substrate production are the same in absolute terms for the three regions, when dividing them by yearly production, the results show notable differences.
The aggregated LCC results are as follows: EUR 209.13/ton of SMS for the northern region, EUR 164.67/ton of SMS for the central region, and EUR −30.27/ton of SMS for the Mediterranean region. As detailed in Table 12, the origin of the wide gap between northern and central regions when compared to the Mediterranean is that, while all the calculations start with the same amount of total waste input, each region shows different levels of water consumption, which also affect the outputs of both substrate and mushrooms.
The Mediterranean region consumes the greatest amount of water, as a result of having the greatest consumption of wheat straw in its ‘recipe’, which makes it more water-demanding. The greater water consumption results in a greater production level (almost double compared to the other regions). The water costs, on the other hand, do not represent an insurmountable obstacle. Greater yields also revolve around economies of scale, which render the Mediterranean system even more efficient.
A relevant aspect to highlight is the mushroom cultivation stage, which accumulates both the highest costs and the highest revenues. Producing mushrooms is a labor-intensive activity that needs a set of specific cash-consuming supplies and facilities, which are only profitable once the mushroom is sold. SMS sales only represent 0.19% of mushroom production revenues. Thus, it is clear that its production is not based on a strict economic rationale, but rather on a solution to managing a waste produced by the production of mushrooms.
These results align with those obtained through the economic allocation of environmental impacts. The LCC analysis has confirmed that mushroom sales are the primary source of revenue for the system, and effectively reduce SMS’s LCC, providing a sort of economic burden relief.
4. Conclusions
Having analyzed SMS, its environmental profile when harnessed as a soil improver, and its life cycle costing, it can be concluded that there are important advantages to be derived from harnessing it as a value-added secondary raw material instead of disposing of it as a waste. Its biggest advantage is that, when used to substitute a non-renewable mix supplying the same amounts of nutrients and organic carbon to soil, significant environmental impacts are avoided.
In the impact categories that account for 97% of the total (i.e., land use, fossil resource depletion, and freshwater ecotoxicity), SMS causes 8- to 19-fold lower impacts than the selected non-renewable baseline.
Water use was the only impact category in which SMS performed worse than the non-renewable baseline, consuming almost double the amount of water. This may gain particular relevance when assessing mushroom production in water-stressed regions. Nevertheless, it only represents 2% of SMS total impacts.
Climate change also has a low weight in total impacts (2%), and SMS takes a smaller toll on the environment when not considering biogenic greenhouse gas emissions. In the scenario wherein biogenic emissions are accounted for as global warming vectors, SMS would have 38% higher impacts compared to the non-renewable baseline selected.
The Life Cycle Costing results shed light on how critical it is to select fresh mushroom substrate components, as this will have effects on the yield and economies of scale. Granted, these decisions are usually constrained to the local availability of supplies, but when possible, mushroom substrate may be produced with wheat straw as its main component. While this will require higher levels of water consumption, it will also produce higher mushroom outputs and higher revenues. While the sale of SMS as a soil improver currently represents only 0.19% of the system, if demand grows and the use of organic soil improvers is promoted, this previously discarded waste could become a non-negligible source of revenue for the mushroom industry.
This study highlights the environmentally competitive advantages of using SMS as a soil improver compared to an equivalent non-renewable mix. It identifies and categorizes the costs incurred by all stakeholders involved in its value chain, emphasizing the most cash-intensive processes. Furthermore, it demonstrates the potential of diverting SMS from landfills to agricultural soils, enabling the substitution of non-renewable fertilizers, reducing their associated environmental burdens and significantly contributing to the sustainable and circular transition outlined as a strategic goal by the European Union.
5. Current Challenges and Future Outlook
Conducting an LCA always implies making several assumptions, primarily based on the availability of data and tools. When assessing less-studied systems, such as non-conventional soil improvers, certain aspects may be omitted. This is the case with the effects on soil caused by the application of soil improvers like SMS. Arguably, these soil-related impacts are among the primary environmental impacts of fertilizers and soil improvers.
For example, the land use impact category in LCA tools is typically limited to land occupation and transformation. However, it does not account for changes in critical soil properties such as erosion resistance, water holding capacity, biodiversity, and mechanical retention. These are some of the variables in which bio-based soil improvers can have positive impacts that are currently overlooked by LCA tools.
Additionally, the available tools for assessing use-phase emissions lack the ability to differentiate between various molecular forms. For instance, the same amount of nitrogen applied to soil is treated as having identical environmental impacts, regardless of its molecular composition. This limitation prevents capturing nuances specific to different fertilizers or soil improvers.
This highlights the need to further refine the land use impact category, or even to propose a new category that accounts for soil changes beyond mere occupation. It also underscores the importance of developing specific emission factors that reflect the unique characteristics of soil improvers.
Another aspect not addressed in this study is the actual performance of SMS as a soil improver and its comparison to non-renewable alternatives. This is a crucial consideration, as sustainability alone is insufficient. Products designed to replace fossil-based equivalents must at least match—or ideally outperform—the functionalities of their non-renewable counterparts. Addressing this would require pot or land tests to evaluate the impacts of SMS and equivalent non-renewable mixes on plant growth, soil properties, and emissions into the soil, water and atmosphere.
Conceptualization, H.I. and J.M.S.D.; data curation, H.I., A.P.O. and A.J.L.-G.; formal analysis, H.I. and A.P.O.; investigation, H.I. and A.P.O.; methodology, H.I. and A.J.L.-G.; project administration, J.M.S.D. and A.J.L.-G.; supervision, A.J.L.-G.; validation, A.J.L.-G.; visualization, H.I.; writing—original draft, H.I.; writing—review and editing, J.M.S.D. and A.J.L.-G. All authors have read and agreed to the published version of the manuscript.
The original contributions presented in this study are included in the article/
The authors wish to acknowledge that the study’s methodology and data sourcing were conducted as part of a collaborative team effort in partnership with CETAQUA–Water Technology Centre, and Draxis Environmental, to whom we extend our gratitude and recognition, as well as to all the members of the FER-PLAY project. The authors also wish to thank the Technological Research Center for Mushrooms of La Rioja (Centro Tecnológico de Investigación del Champiñón de La Rioja, CTICH), and the agriculture and horticulture research and consultancy company Inagro, for sharing relevant information and descriptions of mushroom cultivation practices and the agricultural use of spent mushroom substrate, which were of paramount importance for drafting this article.
The authors declare no conflicts of interest.
Footnotes
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Enlarge this image.Figure 2. Distribution of environmental impacts of SMS and the non-renewable baseline.
Enlarge this image.Figure 4. Fossil resource depletion’s impacts on SMS and the non-renewable baseline.
Enlarge this image.Figure 5. The freshwater ecotoxicity impacts of SMS and the non-renewable baseline.
Reference values of spent mushroom substrate (SMS) nutrient and carbon content.
| Item | Value | Reference |
|---|---|---|
| Dry matter (%) | 73.00 | [ |
| Nitrogen content (% DM) | 1.20 | [ |
| Phosphorus content (% DM) | 0.59 | [ |
| Potassium content (% DM) | 2.30 | [ |
| Carbon content (% DM) | 19.40 | [ |
Nutrient and carbon contents of the reference flow (1 ton of SMS).
| Substance | Amount (kg) |
|---|---|
| Nitrogen | 9 |
| Phosphorus (as P2O5) | 9 |
| Potassium (as K2O) | 21 |
| Carbon | 141 |
Country distribution in regions used for the modeling.
| Northern | Central | Mediterranean |
|---|---|---|
| Denmark | Austria | Cyprus |
| Estonia | Belgium | France |
| Finland | Bulgaria | Greece |
| Ireland | Croatia | Italy |
| Latvia | Czechia | Malta |
| Lithuania | Germany | Portugal |
| Sweden | Hungary | Spain |
| Luxembourg | ||
| Netherlands | ||
| Poland | ||
| Romania | ||
| Slovakia | ||
| Slovenia |
Fresh substrate ‘recipes’ depending on region.
| Ingredient | Northern | Central | Mediterranean |
|---|---|---|---|
| Wheat straw | - | 20.96% | 54.18% |
| Chicken manure | 8.38% | 75.89% | 45.82% |
| Horse manure | 91.62% | 3.14% | - |
| Gypsum | 3.43% | 16.98% | 3.79% |
| Lime | - | - | 2.32% |
Distribution of wood waste treatment per region.
| Waste Treatment | Northern | Central | Mediterranean |
|---|---|---|---|
| Landfill | 69.91% | 37.18% | 79.14% |
| Incineration | 30.09% | 62.82% | 20.86% |
Source: Eurostat [
Emission factors for fresh substrate preparation and application on soil.
| Process | Substance | Emission Factor | Reference |
|---|---|---|---|
| Fresh substrate | Biogenic CO2 to air | 247 g/kg wet waste | [ |
| Methane (CH4) to air | 5.11 g/kg wet waste | ||
| Nitrous oxide (N2O) to air | 0.22 g/kg wet waste | ||
| Ammonia (NH3) to air | 0.24 g/kg wet waste | [ | |
| Ammonia abatement with biofilter | 90% | ||
| NMVOC to air | 1.21 g/kg wet waste | [ | |
| CO2 to air | 0.16 kg/kg C | [ | |
| Application on soil | Soil C sequestration | 0.11 kg/kg C | [ |
| N2O to air (wet climate) | 0.018 kg/kg N | [ | |
| N2O to air (dry climate) | 0.010 kg/kg N | ||
| Nitrogen dioxide to air (NO2) | 0.04 kg/kg N | [ | |
| NH3 to air | 0.24 kg/kg wet waste | [ | |
| Phosphorus (P) to freshwater | 0.05 kg/kg P | [ | |
| Nitrates (NO3) to freshwater | 1.06 kg/kg N | [ |
Economic allocation factors applicable to SMS.
| Item | Value |
|---|---|
| Mushrooms market price | EUR 2357.79/ton |
| SMS market price | EUR 3.00/ton |
| Mushroom output | 658.76 kg |
| SMS output | 1000.00 kg |
| Mushrooms allocation factor | 99.81% |
| SMS allocation factor | 0.19% |
Ecoinvent process datasets selected to model the baseline.
| Nutrient/Substance | Ecoinvent Dataset |
|---|---|
| Nitrogen | RER|market group for inorganic nitrogen fertilizer, as N |
| Phosphorus | RER|market group for inorganic phosphorus fertilizer, as P2O5 |
| Potassium | RER|market group for inorganic potassium fertilizer, as K2O |
| Carbon | RER|market for peat |
Production facilities’ sizes and their corresponding required capital investments.
| Stage | Northern | Central | Mediterranean | |||
|---|---|---|---|---|---|---|
| Size | Investment | Size | Investment | Size | Investment | |
| Fresh substrate production | 1530 | 1.21 | 1848 | 1.21 | 3346 | 1.21 |
| Mushroom production | 363 | 0.72 | 439 | 0.86 | 794 | 1.56 |
| SMS production | 551 | 1.04 | 666 | 1.21 | 1205 | 1.70 |
Costs set for utilities, chemicals and labor in each region.
| Item | Northern | Central | Mediterranean |
|---|---|---|---|
| Electricity (EUR/kWh) | 0.18 | 0.19 | 0.20 |
| Heating (EUR/kWh) | 0.037 | 0.038 | 0.040 |
| Disinfectant (Formalin 10%) (EUR/ton) | 8044 | 6822 | 6917 |
| Fungicide (Benomyl) (EUR/ton) | 8044 | 6822 | 6917 |
| Pesticide (Pyrethrin) (EUR/ton) | 8044 | 6822 | 6917 |
| Peat (EUR/ton) | 159 | 119 | 135 |
| Lime (CaO) (EUR/ton) | 166 | 128 | 204 |
| Gypsum (EUR/ton) | 81 | 72 | 43 |
| Water (EUR/m3) | 1.77 | 1.60 | 1.68 |
| Labor (Manufacturing) (EUR/h) | 21.03 | 19.41 | 17.65 |
| Labor (Agriculture, forestry and fishing) (EUR/h) | 14.22 | 14.28 | 12.28 |
The disaggregation of the climate change impacts of SMS across the three target regions and of the non-renewable baseline.
| Impact Categories | Non-Renewable | Northern | Central | Mediterranean |
|---|---|---|---|---|
| Climate change, total | 328.53 | 436.10 | 499.74 | 420.26 |
| Climate change, biogenic | 0.12 | 300.71 | 300.64 | 300.34 |
| Climate change, fossil | 222.26 | 135.33 | 199.08 | 119.90 |
| Climate change, land use and land use change | 105.74 | 0.06 | 0.02 | 0.02 |
Regional yield differences causing LCC differences in SMS.
| Waste Input (ton/y) | Water Consumption (m3/y) | Fresh Substrate Output (ton/y) | Mushroom Output (ton/y) | |
|---|---|---|---|---|
| Northern | 1475 | 2058 | 1530 | 363 |
| Central | 1475 | 2790 | 1875 | 438 |
| Mediterranean | 1475 | 6249 | 3346 | 794 |
Supplementary Materials
The following supporting information can be downloaded at:
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; Ana Paredes Ortiz 2 ; Soriano Disla, José M 2
; Lara-Guillén, Andrés J 2 1 Technology Centre for Energy and the Environment (CETENMA), 30353 Región de Murcia, Spain;
2 Technology Centre for Energy and the Environment (CETENMA), 30353 Región de Murcia, Spain;