Bio-based fertilizer— Custom-made method for evaluation of its production; environment, climate, and overarching economic performance

1 Introduction

The European Union introduced the Farm-to-Fork strategy in 2020 with the aim of improving nutrient management and setting targets for 2030 to reduce the use of fertilizer by 20% as part of its goal to decrease nutrient losses to the environment by 50% (European Union, 2020). Achieving these targets requires complementary measures that improve nutrient use efficiency and minimize environmental impacts, including reducing over-application, preventing runoff, and increasing the recycling of valuable nutrient sources from diverse streams. The strategy explicitly promotes nutrient recycling, stating that “The Commission will also work with Member States to extend the […] recycling of organic waste into renewable fertilizers.” In addition to EU-level action, regional intergovernmental bodies are working toward the same goal. The Helsinki Commission (HELCOM) developed the Baltic Sea Regional Nutrient Recycling Strategy (HELCOM, 2021), aligning with the Farm-to-Fork strategy, to address persistent eutrophication and regional nutrient imbalances, which remain major environmental pressures in the Baltic Sea region (Thorsøe et al., 2022). This initiative outlines objectives and measures to promote increased nutrient recycling in the region and creates a clear policy imperative for scalable bio-based fertilizer (BBF) solutions.

In the Baltic Sea Region, livestock density is relatively low compared to other parts of the European Union, ranging from about 0.1 livestock units per hectare in Latvia to 1.5 in Denmark, markedly less than countries like the Netherlands and Malta (Eurostat, 2023). Lower livestock density means that agricultural nutrient surpluses, particularly manure, are less pronounced at the regional scale, yet local hotspots persist where animal farming is concentrated (Bielza et al., 2025). Reducing these surpluses requires optimized nutrient management, including precision fertilization and nutrient planning, as well as manure processing technologies that concentrate nutrients, such as anaerobic digestion, and separation. Such processing enables redistribution from surplus to deficit regions, reduces reliance on mineral fertilizers, and helps balance nutrient flows and minimize environmental risks (Akram et al., 2019). At the same time, significant nutrient resources also exist outside agriculture, meaning that effective nutrient recycling in the region requires mobilizing additional streams apart from manure.

Beyond agriculture, substantial nutrient resources are found in municipal and industrial waste streams including wastewater sludge, food industry side-streams, and other nutrient-rich organic wastes (Harder et al., 2019). These materials are often managed inefficiently, through incineration or conventional wastewater treatment, leading to significant nutrient losses (Chang et al., 2023). Recycling non-agricultural waste into BBFs recovers nutrients that would otherwise be lost, diversifies feedstock supply, and reduces eutrophication pressures in sensitive regions like the Baltic Sea. Mobilizing municipal and industrial nutrient sources is therefore essential for effective nutrient recycling in the region and increases flexibility and resilience in BBF production by reducing reliance on agricultural manure alone.

Bio-based fertilizers refer to nutrient-containing materials of biological origin that are used or processed to supply plant-available nutrients suitable for crop fertilization (Wester-Larsen et al., 2022). For the purposes of this article, the term “organic waste” refers broadly to nutrient-rich materials involved in recycling processes. However, most nutrient-rich organic waste, such as digestate, may be applied directly to soil without further processing.

One of the main purposes of converting organic wastes into BBFs is to increase nutrient concentration to enable the geographic transfer from regions with surpluses to regions with deficits, thereby reducing reliance on mineral fertilizers. Achieving a market-ready BBF typically requires a value chain that includes collection of organic waste, one or several processing steps (for example, dewatering, stabilization, and nutrient concentration) and transport to end use. Processing commonly reduces the mass of the organic waste, primarily by moisture removal, while preserving or concentrating nutrient content and often combining several technologies. A key barrier necessitating such processing is the high water content of raw organic wastes, such as slurry or digestate, which renders long-distance transport both economically and environmentally prohibitive. The overall purpose of BBF production is to obtain a product with high, well-characterized nutrient content suitable for precise application (Sindhöj and Rodhe, 2013; Luostarinen et al., 2020). Implementation of a BBF value chain also requires additional resources, such as labor, energy, and facilities, which must be weighed against environmental and economic benefits. Therefore, BBF production is justified only if it improves environmental and climate outcomes and provides overall economic benefits to society.

Despite the availability of diverse BBF production technologies that yield end-products with a broad range of nutrient compositions and fertilizer efficiencies (Hernandez-Mora et al., 2024), substantial quantities of nutrient-rich streams suitable for fertilizer production remain unexploited. Moreover, BBFs continue to occupy only a small share of the fertilizer market compared with mineral fertilizers. Correspondingly, the formal market for traded BBFs remains small: in Denmark, for example, organic fertilizers account for only about 2% of traded N and P (Ministeriet for Fødevarer, Landbrug og Fiskeri, Landbrugsstyrelsen [Danish Ministry of Food, Agriculture and Fishery], 2023). Wider nutrient recycling would conserve phosphate-rock reserves and reduce reliance on energy-intensive processes to produce mineral fertilizers, while reclassifying residual biomass as a raw material could create new value chains, additional revenue and skilled rural jobs (Egas et al., 2023).

Robust assessment is important to justify investments in BBF value chains and guide policy. Life cycle assessment (LCA) is an established standard for evaluating environmental and climate impacts (ISO, 2006). During the last years, LCA has progressed from academic implementation to broader societal use and has become integrated in EU policies (Sala et al., 2021). This method is also widely used to evaluate BBF production (Ahlgren et al., 2012; Dahiya et al., 2020; Alengebawy et al., 2022; Egas et al., 2023). However, full LCAs are resource-intensive, with previous estimates averaging about 2,300 man-hours per case (Broberg and Christensen, 1999), which limits their practicality for supporting early-stage decision-making and assessing the market status of innovative technologies.

Additionally, LCA does not inherently capture economic performance, leaving a gap in screening the combined environmental, climate and economic outcomes of BBF value chain implementation (Gontard et al., 2018). It is essential to recognize that processing organic waste into BBFs is a highly resource-intensive undertaking, requiring significant energy, labor, and capital investment. Conducting an environmental assessment without simultaneously evaluating the associated socio-economic and business costs risks recommending technologies that may prove entirely unviable in practice. A comprehensive appraisal must therefore integrate both sustainability and financial feasibility to ensure that BBF solutions are not only environmentally beneficial but also commercially and operationally realistic. This paper presents a custom-made method designed to screen and compare BBF value chains for nutrient efficiency, climate impacts, and economic performance, providing a robust yet resource-efficient assessment. The method aims to support early decision-making on the implementation of BBF production from nutrient-rich side streams from both a socio-economic and a business perspective and to identify promising value-chain configurations for deeper LCA or pilot testing, as well as to clarify economic incentives needed to scale BBF markets. The method is applied to 11 BBF value-chain examples and uses the results to explain the current market status and policy development required to expand BBF deployment.

While the proposed assessment method developed in this study offers a more practical and resource-efficient means of evaluating BBF value chains, it does not directly resolve the underlying market failures that hinder widespread BBF adoption. Instead, it addresses the methodological gap created by the absence of tools capable of integrating nutrient efficiency, climate impacts, and economic viability into early-stage assessments.

In practical terms, the methodology supports market development by lowering the barrier to entry for innovative BBF technologies, making it feasible to evaluate multiple configurations without the prohibitive resource costs of full LCAs. This supports a more dynamic and responsive development landscape, where only the most promising and viable BBF value chains progress to further investment and scale-up. Ultimately, the custom-made method strengthens the foundation for a functioning BBF market by closing the information gap, enabling better risk assessment, and supporting the alignment of economic incentives with sustainability objectives.

The work reported here is a part of the CiNURGi project (Interreg Baltic, Circular Nutrients for a Sustainable Baltic Sea Region), initiated in 2023 to facilitate the implementation of HELCOM's Baltic Sea Regional Nutrient Recycling Strategy. CiNURGi promotes solutions for converting organic waste generated by agriculture, municipalities, and industries into BBFs, focusing on the EU Member States of the Baltic Sea Region (Denmark, Sweden, Finland, Estonia, Latvia, Lithuania, Poland, and Germany).

2 Methods

2.1 Custom-made method for BBF value chain evaluation

The methodological approach applied in this study is based on a Single Operation Unit Process (SOUP) concept, adapted from Fazio et al. (2020), which provides a structured basis for defining system boundary and operational stages (Figure 1). This framework ensures methodological consistency and comparability assessment by focusing on the core processes directly contributing to BBFs production. The three operational stages encompassed within the SOUP boundary are collection, processing and distribution. The collection stage involves gathering nutrient-rich organic wastes from diverse sources at farms, municipalities, or industrial facilities. Processing encompasses the mechanical, biological, chemical, or thermal methods to convert organic waste into BBFs. Finally, distribution refers to the delivery of BBFs to end-users, typically crop producers, where it substitutes for conventional mineral fertilizers.

This approach ensures that only processes with a primary nutrient recycling function are assessed. Larger facility operations, such as energy generation or unrelated waste treatment, are excluded. For example, in biogas plants, only the digestate treatment steps aimed at BBF production are included within the SOUP boundary, while energy generation and unrelated waste handling processes are omitted.

The assessment framework evaluates each BBF value chain relative to the most relevant baseline scenario representing conventional waste management practices (e.g., landfilling, incineration, direct field spreading), based on three core performance indicators:

• Nutrient Recycling Impact (NRI) quantifies the efficiency of nutrient recycling (N and P) across the value chain, reflecting the core environmental purpose of BBF production.
• Direct Emission Impact (DEI) measures the net change in GHG emissions resulting from BBF production and use, including avoided emissions from mineral fertilizer substitution, transport, processing energy, and organic matter oxidation.
• Guiding Social Cost (GSC) expresses the overall socio-economic impact, in euros per functional unit, defined as 1,000 kg N + P contained in the influent organic waste. GSC serves as a decision-support tool, informing the policy relevance of BBF value chains.

In addition, the method also clarifies the value chain owner's economy, incorporating operational and fixed costs, as well as gate fees and subsidies, thus revealing the market competitiveness of BBF nutrients.

The scope of assessed value chains is therefore limited to the system where BBF production is a primary objective and where alternative waste management options exist. Processes in which nutrient recycling is a secondary or indirect outcome, such as those primarily designed for renewable energy production, were excluded, as their nutrient recycling impacts could not be meaningfully isolated from other operational functions. By applying the SOUP framework, the analysis maintains a clear and consistent system boundary across all cases, enabling robust comparisons of environmental, climate, and economic performance.

The functional unit (FU) for all assessments was defined as 1,000 kg of combined N and P (elemental form) present in the organic waste input. The FU provides a consistent basis for comparing nutrient recovery performance across diverse BBF value chains. The assessment framework was implemented in an excel based tool available for download from the Zenodo research repository (Foged et al., 2026).

2.2 Nutrient recycling impact assessment

The nutrient recycling impact (NRI) is defined as the percentage (%) of nitrogen (N) and phosphorus (P) that is recycled through processing and retained in the final product and by-product, relative to the total nutrient content in the input organic waste. It's calculated according to Equation 1.

NRI (%)=-(ΔNBBF + ΔPBBF)/1,000 × 100(1)

Where the ΔN_*BBF* and ΔP_*BBF* is the amount (kg) of N and P, respectively that are recycled as BBF per FU compared to the baseline scenario.

The NRI value of 100 % indicates that all N and P in the input organic waste are recycled and returned to the farmland, while the baseline scenario assumes no nutrient recycling. A negative NRI value indicates net nutrient losses relative to baseline, typically resulting from volatilisation, incineration, or immobilization in forms with low plant availability (e.g., P bound in ashes or biochar).

In general, the assessment does not account for nutrient availability (e.g., water-extractable phosphorus), with one exception—biochar produced from dewatered sewage sludge. In this case, phosphorus availability is known to be significantly reduced (Li et al., 2017) and it was conservatively assumed that 35% of the P became unavailable for plant uptake. The method does not include other nutrients (e.g., K, Mg) or potential environmental risks (e.g., heavy metals, PFAS), which could be addressed in complementary analyses.

2.3 Climate impact assessment

Several factors determine the climate impact associated with establishing a BBF production value chain. Based on the joint experience and accumulated knowledge of the CiNURGi project team, the following climate-related factors were identified as particularly important.

Avoided emissions from mineral fertilizer replacement (ΔGHG_*m*) refer to the GHG savings achieved when BBFs substitute conventional mineral fertilizers. These avoided emissions result from the displacing the emissions associated with production and transport of mineral fertilizers. Avoided emissions is proportional to the amount of N and P in BBFs that replace mineral fertilizers, relative to the baseline scenario (Equation 2).

ΔGHGm = ΔNBBF × FN + ΔPBBF × FP(2)

Where ΔN_*BBF* and ΔP_*BBF* are given by Equation 1; F_*N*/*P* are emission factors representing the climate impact of mineral fertilizers and assumed to be 3.40 and 2.75 kg CO₂-eq per kg of N and P, respectively. These represent median values of examples provided by Havukainen et al. (2018), including production of mineral fertilizer, and in some cases transport of input materials and fertilizer product to end use (Equation 3).

Transport emissions (ΔGHG_*t*) represent another important parameter. After conversion of organic waste into BBF, transport requirements of the end product are expected to decrease if the nutrient concentration in the BBF is higher than in the influent organic wastes. However, establishing a BBF value chain may require additional transport for the collection of organic wastes prior to processing. Transport-related emissions include the collection of organic waste, delivery to processing facilities (if these are not co-located with the organic waste storage sites), and distribution of BBFs to end-users. Transport distances were derived from information provided by value chain owner, and associated emissions were calculated as follows:

ΔGHGt = [(ΔtC + ΔtP) × minput + (tD,VC × mBBF,VC − tD,baseline × mbaseline) ] × Ft(3)

Where Δt_*C*, Δt_*P*, and Δt_*D* refer to transport distances for collection (C) of organic waste, for delivery from collection site to processing site (P), and for distribution (D) from processing to end-use (arable land), respectively (in km, when available, as given by the value chain owner); m_*input*, m_*BBF*, and m_*baseline* is the mass per FU of the organic waste input, the BBF, and the output in the baseline, respectively (ton); F_*t* is an emission factor for truck transport, set at 0.111 kg CO₂-eq for each ton-km, i.e., the emissions related to transporting 1 ton of material over a distance of 1 km (Ragon and Rodríguez, 2021; truck type RD9).

The assessed value chains did not produce by-products, however, in cases where by-product is produced, transport related emissions associated with their disposal should be estimated and added to the overall climate impact.

Processing energy emissions (ΔGHG_*p*) arise from the energy required to convert organic waste into BBFs. This energy demand may involve electricity, fossil fuels, or other energy resources. The use of electricity (depending on the energy mix) and fossil fuels contributes to GHG emissions (Equation 4).

ΔGHGp= ΔpE × FE(4)

Where ΔpE is the electricity consumed during processing (kWh) per FU and F_*E* is the climate footprint of electricity, set at 0.255 kg CO₂-eq per kWh based on average across Europe (Jones, 2023). To reveal the regional variations the smallest and largest national emission factors were used in a sensitivity analysis, i.e., 0.015 kg CO₂-eq per kWh for Sweden and 0.692 kg CO₂-eq per kWh for Poland (Jones, 2023).

Organic matter (OM) loss translated into CO₂-eq (ΔGHG_*o*) occurs when processing methods lead to the oxidation of organic matter, releasing carbon in gaseous form (CO₂, CO, CH₄, etc.) as well as other GHG such as N₂O (Equation 5). Losses of organic matter are particularly pronounced in thermal treatments. For simplification, the C loss is estimated as a contribution to CO₂ emissions, based on the assumed molar mass of C and O, while other potential GHG are excluded from the scope of this assessment.

ΔGHGo = mDM × FOM × FC × ΔC × 4412 × 1,000(5)

Where m_*DM* is the mass of DM in organic waste (ton), F_*OM* is the assumed fraction of organic matter in organic waste dry mass, F_*C* is the share of carbon (C) in organic matter, ΔC (%) is the fraction of carbon lost during processing, 44/12 is the stoichiometric conversion factor from C to CO₂-eq. Multiplication with 1,000 is done to convert the input factors in ton to the result in kg. As a simplification F_*OM* was assumed to be 70% across all organic waste types except meat and bone meal where it was assumed to be 40%, and F_*C* was assumed to have the same value across all organic waste types, i.e., 57% (AgroTechnologyATLAS, 2025).

All the components are assessed as change in relation to the baseline in the respective value chain and expressed as CO₂-eq.

The climate impact is summarized as the Direct Emission Impact (DEI) which represents the net change in GHG emissions resulting from the production and use of BBFs compared to conventional management of the organic waste, i.e., the implementation of a BBF value chain. A positive DEI value indicates a net increase in GHG emissions relative to the baseline scenario, whereas a negative DEI value suggests that BBF production results in lower emissions than conventional waste handling. The emissions associated with the construction phase of the value chain are not included in this assessment. DEI is expressed in kilograms of CO₂-equivalents (CO₂-eq) per FU (Equation 6):

DEI = -ΔGHGm + ΔGHGt + ΔGHGp+ ΔGHGo(6)

2.4 Economic impact assessment

The overall socio-economic impact of BBF value chains is referred to as Guiding Social Costs (GSC) per FU. Defining the GSC per FU ensures consistency across all assessed cases, including value chains where nutrient recycling does not increase compared to the baseline. The GSC comprises four components: (i) the capitalized social cost of nutrient losses; (ii) the capitalized social cost of GHG emissions; (iii) value chain costs; and (iv) the societal value of domestic fertilizer production.

The cost of nutrients losses to the environment assigns a monetary value to these losses from a societal perspective. This includes the broader welfare losses associated with pollution, such as impacts on human health, ecosystem services, and the long-term degradation of environmental resources (de Bruyn et al., 2018). In this sense, the valuation reflects a societal perspective, meaning it accounts for externalities borne by communities and ecosystems.

The cost of GHG emissions, refers to the monetary value assigned to the climate damages caused by these emissions when evaluated from a societal perspective. This valuation captures the external costs that are not borne directly by the value chain owner but instead affect society at large. Such costs include the long-term impacts of climate change on human health, agriculture, infrastructure, and ecosystems, as well as the economic consequences of mitigation and adaptation measures. In this way, monetisation of GHG emissions reflects their broader social and environmental burden.

The net value chain costs of a nutrient recycling value chain involve investment costs (machinery, land, and infrastructure, including financing, depreciation, etc.), operational costs (transport, handling, storage, processing, packaging, maintenance and including labor, consumables, energy, etc.), administrative costs (compliance, certification, and overhead, including labor, office, accounting, etc.) and revenue sources (government subsidies, and gate fees from input material suppliers). However, to avoid issues of business confidentiality, the assessment does not include detailed cost data from value chain owners. Instead, a generalized cost model is applied, in which value chain costs, including consumables, are estimated according to the complexity of processing. These costs assumptions are derived from prior knowledge of the CiNURGi project team, supported by assessment of data given by Hermann and Hermann (2021). The following cost categories are applied, with an assumed uncertainty of ±25% to illustrate potential effects on the output GSC:

• No-cost value chain (0 €/ton organic matter) is applied to baseline scenarios where no additional treatment is required (e.g., direct use of digestate).
• Low-cost value chain (100 €/ton organic matter) includes simpler processes such as separation, mixing, pelletising, or acidification.
• Medium-cost value chain (200 €/ton organic matter) includes moderately complex operations such as separation combined with thermal drying and pelletising.
• High-cost value chain (300 €/ton organic matter) is applied to advanced and multi-step systems such as thermal drying followed by pyrolysis, or intensive chemical treatments.

The societal value of domestic fertilizer production is estimated at 50% of the long-term market price of mineral N and P fertilizers.

Standardized pricing models are used to estimate the capitalized social costs, covering:

• Nutrient losses (N and P): valued using data from the Environmental Prices Handbook for EU28 (de Bruyn et al., 2018) assigning monetary costs to nutrient emissions linked to environmental degradation.
• GHG emissions (CO₂-eq): valued based on the prevailing prices for emission reductions under the EU Emissions Trade System, representing the cost of emission or the value of avoided emissions.

Based on these assumptions, the GSC (€ per FU) indicator is calculated as indicated in Equation 7:

GSC (€/kg N + P) = NLN+P, FU + GHGN+P, FU + PN+P, FU −(VN, BBF + VP, BBF)(7)

Where:

• NL_{*N*+*P, FU*} (€ per FU) is the social cost of nutrient losses which occur in the value chain/during processing, assumed as F_*N* × ΔN_BBF + F_*P* × ΔP_BBF, where F_*N* and F_*P* are cost factors for losses of N and P, assumed as 3.11 and 1.86 € per kg N and P, respectively (de Bruyn et al., 2018). The parameters ΔN_*BBF* and ΔP_*BBF* are according to Equation 1.
• GHG_{*N*+*P, FU*} (€ per FU) is the social cost of GHG emissions, assumed as DEI1,000×FGHG, where F_*GHG* is the price for EU Carbon Permits; assumed at 76.92 € per ton CO₂-eq, based on EMBER (2024).
• P_{*N*+*P, FU*} (€ per FU) is the processing cost calculated as m_*OM* × ΔF_*cost*, where m_*OM* is ton organic matter per FU and ΔF_*cost* is the difference in cost between the value chain (ΔF_{*cost, VC*}) and the baseline (ΔF_{*cost, baseline*}), these were each based on the cost factor as described above; assumed based on the complexity of processing: no-cost/low-cost/medium cost/high cost.
• V_{*N, BBF*} and V_{*P, BBF*} is the market value (MV) in Euro of N and P, assumed as _{V_{*N, BBF*} = ΔNBBF}×MV_{*N, BBF*} and _{V_{*P, BBF*} = ΔPBBF}×MV_*P* where MV_{*N, BBF*} is assumed to be 0.5 € per kg N and MV_{*P, BBF*} 0.75 € per kg P based on a long term perspective on mineral fertilizer market prices.

As with environmental and climate assessments, comparisons are made relative to baseline scenarios, i.e., the economic impact is calculated as the difference from the baseline.

Lastly, the business cost per recycled kg N and P was roughly estimated as the processing cost of the value chain divided by the total mass of N and P in the BBF and recycled byproduct (the latter if relevant).

2.5 Identification, surveying and short-listing of value chain cases

To uncover commercially available or nearly market ready BBF solutions across the Baltic Sea Region, an open call was launched in May 2024. The call invited practitioners with existing or advanced stage BBF value chains (encompassing waste collection, processing, and final distribution) to submit descriptions via a survey (Foged, 2025). Submissions were solicited through the CiNURGi project website, social media, newsletters and partner networks.

In total, 24 value chains were identified and surveyed. As many respondents lacked complete datasets for key variables (e.g., annual input/output flows, precise content of N, P, dry matter, or detailed information on labor, energy, transport, chemical input), participant-provided data was supplemented with standard values from literature sources. One key source was the AgroTechnologyATLAS (2025), which provides chemical composition, dry matter content, and other relevant parameter values for different organic waste streams, referenced to scientific sources of the data and information. Literature-based values were reviewed and validated by the survey participants to ensure contextual relevance and acceptability.

From an initial pool of 24 submissions, 11 value chains were retained based on criteria including data completeness, technology readiness, operational status, and the value chain owners' willingness to share information. These selected cases provided sufficient consistency and detail to support comparative analysis using the custom-made assessment method.

3 Results

3.1 Overview of retained value chains

The 11 value chains retained for assessment (Table 1; Figure 2) represent a broad cross-section of BBF production pathways that are currently operating or nearing market readiness in the Baltic Sea Region. Together, they cover a wide range of organic waste origins, processing technologies and final product forms, reflecting the heterogeneity of nutrient recycling practices across farming, municipal, and industrial sectors.

Table 1. The 11 shortlisted BBF value chains selected for assessment with their titles, short names, Technology Readiness Level (TRL), and baseline management practices used for comparison.

Each value chain was assigned a short name that reflects its main characteristics, including waste sector (F = Farming, M = Municipal, I = Industry), dominant processing method (M = Mechanical, C = Chemical, B = Biological, T = Thermal) and product form (L = Liquids, P = Pellets, G = Granules, S = Other solids). Where several value chains shared the same waste sector, processing method, and product form, a numerical suffix was added (e.g., FMP1 and FMP2) to distinguish individual cases.

The MTS1 case was discussed during the selection process due to the ambiguous classification of biochar as a fertilizer. The case was nevertheless retained, as current EU legislation does not provide a clear distinction between fertilizers and soil amendments.

As summarized in Table 1, most of the retained value chains operate at Technology Readiness Level (TRL) of 8–9, indicating that the assessed BBF production technologies are generally mature and implemented at commercial or near-commercial scale. The baseline waste management practices vary depending on waste type and local context, ranging from direct land application of raw slurry or digestate to incineration or landfilling of municipal and industrial residues. This variation ensures that the assessment captures a representative range of BBF production strategies, from low-complexity and low-cost interventions, such as in-field acidification, to highly engineered, multistep systems, such as thermal drying followed by pyrolysis.

3.2 Comparative results relative to baseline scenarios

The comparative assessment of the 11 retained BBF value chains relative to their respective baseline scenarios is summarized in Table 2, which constitutes the main result of this study. All values are reported per functional unit (FU), defined as 1,000 kg of nitrogen (N) and phosphorus (P) in the influent organic waste.

Table 2. Overview of nutrient recycling (NRI), climate (DEI) and overall economic assessments of BBF value chains, ranked by Guiding Social Cost (GSC, € per FU), including mass reduction ratio, organic matter (OM) losses (kg per FU) and nutrient loss (kg per FU); FU, functional unit, defined as 1,000 kg N and P in the influent organic wastes.

Table 2 presents the results of the environmental, climate, and socio-economic assessments, including indicators related to material transformation, nutrient recycling, GHG emissions, and overall economic performance. The mass reduction ratios (the mass of the BBF compared to mass of input organic waste) range from 1 to 422, reflecting large differences in the degree of concentration achieved in the final BBF products. Net organic matter losses span from −15,917 to +270 kg per FU, while nitrogen and phosphorus losses range from −950 to +90 kg N and from −436 to 0 kg P per FU, respectively.

Across all value chains, the Nutrient Recycling Impact (NRI) ranges from −9 to 100%, the Direct Emission Impact (DEI) from −13.2 to +28.4 t CO₂-eq per FU, and the Guiding Social Cost (GSC) from –€3,550 to €1,487 per FU. Average values across the dataset are 47% for NRI, 0.5 t CO₂-eq per FU for DEI, and –€416 per FU for GSC.

These results demonstrate a wide variation in performance across BBF value chains and provide the quantitative basis for the more detailed visual analyses presented below.

The cost-tier structure applied in this study (0/100/200/300 €/ton organic matter) provides a practical and standardized way to compare heterogeneous BBF value chains; however, it also introduces uncertainty. The tiered approach simplifies complex financial realities and may not fully capture cost variability arising from scale, technology-specific energy demand, regional labor prices, capital depreciation schedules, or gate-fee arrangements. Because these generalized cost categories are based on expert judgement rather than transparent, case-specific financial data, the resulting economic indicators (net value chain cost and GSC) should be interpreted with caution.

3.3 Indicator-specific results supported by graphical analysis

The relationships between nutrient recycling performance, climate impact, and socio-economic outcome are illustrated in Figure 3, which visualizes the NRI, DEI, and GSC value reported in Table 2, with value chains arranged in the same order.

Figure 4 provides a more detailed breakdown of GHG emissions by category for each value chain, highlighting the relative contribution of energy use, transport, organic matter losses, and other sources to the overall DEI.

The composition of the Guiding Social Cost is further detailed in Figure 5, which shows the contribution of nutrient losses, greenhouse gas emissions, value chain costs, and the societal value of domestic fertilizer production to the total GSC for each value chain.

3.4 BBF market competitiveness

The market competitiveness of BBF production can be assessed by comparing the estimated value chain costs with the amount of N and P delivered in the final BBF products, without respect to the baseline (Table 2).

Table 3 presents the estimated value chain costs, the N:P ratio in the produced BBFs, and the resulting business cost per kilogram of recycled N and P for each value chain. Business costs range from €0.7 to €4.9 per kg N + P, with an average value of €2.6 per kg N + P across all assessed value chains.

Table 3. Ratio of N:P in BBF and estimated business cost per recycled kg N and P.

For comparison, the long-term market price of nutrients in mineral fertilizers was estimated at €1.08 per kg N + P, based on assumed prices of €1.00 per kg N and €1.50 per kg P and a crop demand ratio of N:P = 85:15. When applying this reference price, two value chains (FCL and MML) exhibit business costs below €1.08 per kg N + P.

If policy mechanisms were introduced to internalize the societal economic benefits of BBFs production, such as subsidies reflecting the capitalized value of reduced GHG emission and avoided nutrient losses, four additional value chains (MCG, MCS, MTS1, and MCL) would become competitive with mineral fertilizers. This would broaden the range of viable BBF technologies to include P recovery (struvite), ammonium sulfate production from reject waste, and other wastewater-based processes that currently struggle to compete on the market terms alone.

4 Discussion

The results demonstrate that the environmental, climate, and economic performance of bio-based fertilizer (BBF) value chains is highly heterogeneous and strongly dependent on the baseline waste management practice, the origin of the organic waste, and the intensity of the applied processing technologies. The wide ranges observed across all indicators, including nutrient recycling impact (NRI), direct emission impact (DEI), and guiding social cost (GSC), confirm that BBF production cannot be evaluated as a single solution, but rather as a set of context-specific strategies whose performance must be assessed relative to realistic alternatives. This finding confirms theoretical conclusions made by Gontard et al. (2018).

A key finding is that BBF value chains based on municipal and industrial waste streams consistently achieve higher nutrient recycling impacts than farming-based systems. This pattern is primarily driven by differences in baseline scenarios. Municipal and industrial residues are often managed through incineration, landfilling, or conventional wastewater treatment, where nutrient losses are substantial. In these contexts, BBF production enables recovery of nutrients that would otherwise be dissipated, leading to high or even complete nutrient recycling relative to the baseline. In contrast, farming-based value chains typically replace direct land application of slurry or digestate, a baseline that already recycles most nutrients efficiently. As a result, any nutrient losses introduced during additional processing steps, such as ammonia volatilisation during thermal processing directly reduce the NRI and can lead to zero or negative outcomes.

Processing technology is central to variations in nutrient recycling performance. Low-temperature stabilization processes are effective at preserving nutrients, while thermal and oxidative treatments reduce mass and volume but often result in significant nitrogen losses. Table 2 highlights this trade-off, showing that mass reduction through thermal methods is frequently accompanied by diminished nutrient recycling impact, especially due to ammonia volatilisation. Although phosphorus can often be recovered in mineralised forms, its plant availability may be decreased, leading to intermediate NRI values in some thermally treated sludge pathways. Technologies focused solely on one nutrient are limited in overall recycling efficiency when nitrogen losses are high.

To thoroughly evaluate each value chain, it's important to quantify mass and nutrient flows at each processing stage, identify specific loss pathways like ammonia volatilisation, benchmark against baseline waste management practices, and consider both socio-economic and environmental factors. This includes assessing GSC, DEI, value chain costs, energy demands, and market competitiveness. A BBF evaluation tool in the form of a spreadsheet model has been developed for anyone to apply the described methodology for assessing the impacts of BBF value chains. For instance, if a value chain owner wish to assess a given value chain before investing in it, or to assess the overall incremental economic impact of another processing configuration, such as the adding of ammonia recovery technology before a thermal processing like pyrolysis, the model can be used for such.

The value chain should be evaluated using a holistic framework that combines mass reduction and nutrient retention data (as in Table 2), process-level nutrient and emission balances, and the integration of ammonia recovery technologies. These strategies offer real potential to mitigate N losses following thermal treatment, enhancing both nutrient recycling impact and overall sustainability performance for BBF systems. Their adoption helps resolve the trade-off between efficient mass reduction and the need to retain key nutrients, improving the viability of thermal treatment within circular nutrient management strategies. From a socio-economic perspective, the GSC results reveal a structural divergence between societal benefits and private economic incentives. Reduced nutrient losses represent the dominant driver of socio-economic benefits and explain why several municipal and industrial waste-based value chains achieve negative GSC values. However, these benefits are frequently offset by increased value chain costs associated with processing, energy use, and operational complexity. Farming-based value chains, where baseline nutrient recycling is already high, show limited or no socio-economic benefit once additional processing costs are included. This explains why fewer than half of the assessed value chains are justified from a societal perspective when full value chain costs are considered.

A further source of uncertainty arises from the use of simplified cost tiers intended to approximate value chain expenditures. While these categories enable cross-case comparison, they inevitably generalize diverse cost structures and may not reflect true capital, operational, or administrative expenditures. This simplification can influence the assessment of market competitiveness and contribute to misalignment between private business costs and societal value demonstrated through the GSC. To minimize this misalignment, future BBF assessments should incorporate transparent, disaggregated financial data provided by value chain operators, including detailed energy use, labor requirements, chemical inputs, maintenance, and capital financing structures. Such validation would enable more accurate estimation of value chain costs and support policies that better align business incentives with societal benefits. Without this refinement, economic indicators risk under- or overestimating the true cost-effectiveness of BBF systems, particularly in contexts where operational costs are highly sensitive to technology design or regional factors.

The market analysis reveals a major economic challenge: most BBF pathways are not cost-competitive with mineral fertilizers, except for one value chain. This success is attributed to simple, low-energy processing or operating at a large scale, which lowers costs. Cost-effectiveness tends to be highest with straightforward stabilization processes or high throughput, keeping energy and complexity minimal. Thus, while BBF can provide societal value, market signals rarely reflect these benefits, and profit-driven decisions may not align with broader social good.

For investors, the guidance is straightforward: focus on BBF systems that minimize processing costs per recycled N + P nutrient, targeting waste streams with poor nutrient recycling and low energy demand. Low-tech BBF operations are most likely to be cost-effective, while energy-intensive processes will struggle unless supported by policy or sustainability premiums. Stakeholders should carefully assess processing methods, scale, and baseline management to ensure both economic and societal returns. The combined results indicate that BBF production is most viable where it replaces nutrient-inefficient baseline practices and where processing can be achieved with limited additional energy demand. Municipal waste-based systems therefore show higher overall potential than farming-based systems, where nutrient recycling is already embedded in existing practices and regulatory frameworks. This also suggests that future BBF deployment strategies should prioritize nutrient rich waste streams and contexts where baseline management options are environmentally and economically suboptimal.

Overall, the findings highlight that BBF production should be regarded as a targeted complement to existing nutrient management systems rather than a universal solution. Its contribution to sustainability depends on careful alignment between waste stream characteristics, processing technology, baseline practices, and economic context. Addressing the current gap between societal value and market competitiveness will be essential if BBF production is to scale beyond niche applications.

5 Conclusions

This study shows that the sustainability performance of bio-based fertilizer (BBF) production, both environmental and socio-economic, cannot be understood independently of the baseline waste management practices it replaces. BBF production is not inherently beneficial, its value is fundamentally shaped by the magnitude of nutrient losses, emissions, and costs embedded in existing systems. Where baseline practices such as incineration, landfilling, or conventional wastewater treatment lead to substantial nutrient dissipation, BBF production can markedly increase nutrient retention and generate significant societal benefits. Conversely, in farming systems where direct land application already recycles nutrients efficiently, additional processing often adds energy use and costs without improving overall system performance.

A central insight of this work is that nutrient recycling efficiency is the dominant driver of societal value in BBF systems. Reduced nutrient losses consistently explain the largest share of positive socio-economic outcomes, whereas climate benefits, though relevant, play a secondary and context-specific role. This finding challenges assumptions that greenhouse gas mitigation alone can justify investment in BBF technologies and underscores the need to evaluate nutrient retention as the primary performance metric.

The study also highlights a persistent misalignment between societal benefits and market incentives. Several of the assessed value chains deliver clear socio-economic gains but remain commercially uncompetitive under current fertilizer markets. This misalignment helps explain the limited uptake of BBF solutions despite strong policy ambitions for nutrient circularity. The results indicate that technological optimisation alone is insufficient to drive widespread adoption, rather, market development will require mechanisms capable of aligning private costs with societal value.

Importantly, the analysis shows that conventional life cycle assessment (LCA) approaches are insufficient for evaluating nutrient recycling systems. LCAs generally overlook the economic consequences of nutrient losses and the distribution of costs and benefits among actors, which can lead to incomplete or misleading conclusions regarding the desirability of BBF pathways. By integrating nutrient retention, avoided losses, greenhouse gas emissions, and socio-economic impacts into a single framework, this study provides a more comprehensive basis for identifying when and where BBF production can meaningfully contribute to circular nutrient management.

Overall, BBF production should be pursued selectively, targeting waste streams with nutrient-inefficient baselines and processing systems capable of achieving high nutrient retention without excessive energy demand. Strategic deployment, combined with improved alignment between policy objectives and economic conditions, will be essential for enabling BBF systems to move beyond niche applications and deliver their potential contributions to sustainable nutrient management.

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Footnotes

Edited by: Jaime Moll de Alba, United Nations Industrial Development Organization, Austria

Reviewed by: Eugenia Grecu, Politehnica University of Timisoara, Romania

Erry Ika Rhofita, Sunan Ampel State Islamic University (UINSA), Indonesia