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Article

Biogas Energy Usage Through the Co-Digestion of the Organic Fraction of Urban Solid Waste with Lime Mud: An Environmental Impact Analysis

by
Ulisses Raad da Silva Coelho
,
Adriele Maria de Cássia Crispim
,
Maria Auxiliadora de Barros Martins
,
Regina Mambeli Barros
*,
Maria Luiza Grillo Reno
,
Geraldo Lucio Tiago Filho
,
Ivan Felipe Silva dos Santos
and
Aylla Joani Mendonça de Oliveira Pontes
Natural Resources Institute, Federal University of Itajubá, Itajubá 37500-903, Brazil
*
Author to whom correspondence should be addressed.
Submission received: 13 September 2024 / Revised: 11 January 2025 / Accepted: 21 January 2025 / Published: 10 March 2025

Abstract

:
This study evaluates the energy recovery from biogas generated through the anaerobic co-digestion of the Organic Fraction of Urban Solid Waste (OFUSW) with lime mud (LM). This approach aims to mitigate environmental impacts such as greenhouse gas emissions and pollution while promoting energy recovery for a diversified power matrix. Life cycle assessment (LCA) methodology, in accordance with the NBR ISO 14040 and 14044 standards, was used to compare five scenarios for the disposal of LM. The results highlight that the co-digestion scenario showed significant environmental benefits in 8 out of the 18 categories evaluated, such as reductions in eutrophication, acidification, and climate change. Additionally, the digestate produced helped avoid further environmental impacts. The integration of urban and industrial waste demonstrates the potential to enhance biogas productivity, generate savings for the pulp and paper industry, and promote sustainable practices. The innovation lies in the synergistic use of LM as a co-substrate, improving the efficiency of the anaerobic process and maximizing biogas production. This research provides a solid scientific foundation for decision-making in public policies and industrial practices, positioning itself as a viable and innovative proposal for the integrated management of solid waste and sustainable energy.

1. Introduction

Solid waste (SW) generation is inherent to human activity and influenced by phenomena such as population growth, improvements in standards of living, and urbanization, among other factors. It is estimated that global SW generation in 2020 reached 2.1 billion tons; projections foresee an increase of 56% [1], to 3.8 billion tons, by 2050. Of this amount, 32% to 50% is projected to be organic SW [2]. In Brazil, this tendency is also seen, where 77.1 million tons of urban solid waste (USW) were generated [3], and a 50% increase is expected by 2050, reaching up to 120.9 million tons per year [4].
To avoid and mitigate environmental impacts through the increase in solid waste generation, Brazil depends on a number of legal instruments, such as the National Solid Waste Policy (NSWP) Law number 12.305/2010 and the Legal Framework of Basic Sanitation, Law number 14.026/2020, which defines environmentally adequate disposal, correct solid waste management, and calls for the cessation of dumps [5]. However, while 61.1% of the collected material is disposed of in sanitary landfills, which are safe and environmentally friendly alternatives, the remaining 38.9% is destined for controlled landfills and dumps [3]. These alternatives present more elevated environmental risks, such as contaminating groundwater with leachate, transmitting diseases, and accelerating global warming through biogas emissions [6].
Biogas is the result of the anaerobic digestion (AD) of organic material (OM) [7], known as the Organic Fraction of Urban Solid Waste (OFUSW), and represents around 45.3% of total waste composition [8]. In biogas, greenhouse gases such as methane (CH4) (50% to 70%) and carbon dioxide (30% to 45%) are present [9]. Methane’s potential for global warming is 27 to 30 times greater than that of CO2 [10]. However, appropriate management of biogas can convert it into a renewable energy source instead of a pollutant gas, given its relatively elevated Lower Calorific Value (LCV), reaching up to 34 MJ/Nm3, due to the presence of CH4 [11]. Thus, biogas stands out as a source for heat and energy [12], which contributes to urban solid waste (USW) treatment and reduces waste from OFUSW, such as food waste [13]. From a greater perspective, this alternative finds incentives in the global tendency toward the circular economy [14] in the search for energy sources with diminished environmental footprints [15], as well as in the need for diversification of the Brazilian energy grid, with energy demands projected at 3.8% per year [16], and the difficulties imposed by the country’s own water crises [17].
While sanitary landfills often stand out as a necessary solution, they also generate biogas through Urban Solid Waste (USW) disposal. Anaerobic biodigesters enable better operational control for anaerobic digestion (AD) processes, elevating treatment efficiency, biogas and CH4 generation, and, in turn, energy usage [18]. Moreover, in these reactors, the solid phase resulting from AD is digestate, which is a byproduct rich in nutrients and with potential for agricultural applications [19].
It is known that when anaerobic digestion (AD) is used for monodigestion (monoAD), which is the degradation of a single, main substrate, reactor operation may become unstable [20] as the substrate availability tends to decrease to a few years’ timespan [21] due to the presence of heavy metals which damage the microorganisms responsible for decomposition [22] and decreased biogas and CH4 yields [23]. These disadvantages can be resolved through anaerobic co-digestion (AD-Co) which, by simultaneously digesting two or more substrates, improves the balance of nutrients, promotes synergetic effects for system microbiota, dilutes toxic agents, and, in turn, increases the efficiency of biogas and CH4 production [24,25].
Studies, such as that of Begum et al. [26], demonstrate these advantages. The study evaluated the performance of a self-powered continuous stir-tank reactor (CSTR) at the pilot scale for the anaerobic digestion of the solid-state waste of food waste (FW) rich in acetic acid and cardboard (CB). The aim of combining FW and CB was for the acetic acid to function as a pretreatment agent that, along with the pattern and high frequency of material addition, allowed the system to handle an organic load above 4 g of volatile solids (VSs)/(L.d) without the addition of chemical products or increasing pH.
Castro e Silva et al. [27] demonstrated that the use of iron ore tailings for AD-Co with swine manure increases the chemical oxygen demand (COD) removal from 77% to 81.4% and reduces treatment costs by up to 23.24%, with variations in the levelized cost of energy running from 80 to 90 USD/MWh. Nadaleti et al. [28] concluded that the application of viticulture waste from the AD-Co of the OFUSW improved the energy yield of biogas for vehicle usage, providing up to 37.9 Gg of biomethane per year, supplying the entire public bus fleet for the municipality of Bento Gonçalves.
While metropolitan centers are responsible for generating USW, the industrial sector must also deal with its own by-products, namely industrial solid waste (ISW). Along these lines, the paper industry is the second largest exporter of ISW in the world and produces approximately 19.7 million tons of cellulose per year [29]. Such large-scale production requires apt resource management and rational use of raw materials. Lime mud (LM) is an important byproduct of the paper industry. Naturally basic, it has a pH of around 12, and the vast majority of its composition, around 97%, is calcium carbonate [30]. In general, it is considered a byproduct by industry standards; however, when there are interruptions for cleaning and maintenance, it becomes a waste product [30,31]. Some LM applications have been studied in the literature. For example, Farage et al. [32] demonstrated its application as an intermediate covering material in sanitary landfills capable of generating an economy of up to BRL 30 million per year in cost avoidance with industrial sanitary landfills (ISLs) [33].
At the intersection between urban solid waste and ISW lies the application studied by Zhang et al. [34] and Chen et al. [35], who assessed the use of sewage sludge (SS) as a co-substrate in food waste from the OFUSW in anaerobic digestion (AD) processes. Their results demonstrated that SS contributed to increased efficiency for methane generation, since the alkalinity and inorganic micronutrients in the SS improved overall AD, generating synergies in AD and stabilizing pH through the buffering effect. In Zhang et al.’s study [34], the authors saw an increase in CH4 production of 272.8 mL/gVS, while in Chen et al.’s study [35], the authors attained methane production from 120.2 to 250.0 mL/gVS, with gains of up to 108%. Despite the promising results, studies on the application of lime mud are still scarce, especially from an economic and environmental perspective.
Aiming to address this gap in the literature, Coelho Silva et al. [36] analyzed the economic feasibility of energy usage from biogas generated using AD-Co of the OFUSW with lime mud. The study determined that, for economic viability to be guaranteed, a minimum population of 185,000 inhabitants would be necessary, resulting in a net present value of USD 23,336.94, considering an energy sales rate of USD 0.139 and a return on investment of 10 years.
The authors from the previously mentioned article used life cycle assessment (LCA) methodology, given that it enables a broad application of life cycle (LC) for products and services, allowing for the identification of a route or process that presents a greater environmental impact [37,38]. Through LCA, one may analyze several environmental impact categories, gather information on the flow of resources, raw and waste material, and emissions, and reach assertive conclusions on the sustainability of a given LC. Thus, the understanding of the use of a determined product or alternative application for a given waste material can be made more rationally and adequately from an environmental perspective [39].
Studies, such as that of Tong et al. [40], have used LCA to compare the Mono Anaerobic Digestion (Mono-AD) and AD-Co of the OFUSW with sewage sludge. According to the authors, LCA showed that AD-Co increased the collection of CH4 by 10% compared to Mono-AD. Bartocci et al. [41] developed a business model to reduce the quantity of food waste (FW) in landfills. The environmental benefit of the substitution of 9900 t of energetic cultures (such as corn silage) for 6600 t of food waste in anaerobic digestion was a 42% reduction in the carbon footprint of the electricity produced by the biogas plant.
Henriquez [39] used LCA to evaluate different routes for energy usage of USW in medium-sized cities in Brazil. Using SimaPro® along with the method for estimated cumulative demand of energy and other tools, multiple scenarios were proposed that varied everything from the disposal of the USW to the sanitary landfill without energy recovery to a scenario in which there would be energy usage within an integrated USW system. The study concluded that this last scenario offered an energy usage option with the best environmental performance, since it had negative values for environmental impacts such as abiotic depletion, global warming, and acidification, resulting from the adopted recycling stage. On the other hand, the gasification phase of the system contributed with positive values to the depletion of the ozone layer.
A study conducted by Corcelli et al. [42] evaluated the environmental and energetic sustainability of the paper industry and used an industrial complex in Finland as its basis. Even as a great consumer of resources, the pulp and paper industries can serve as references for environmental sustainability since their raw materials are renewable. The results showed that a great part of the impacts are caused by the industrial phase of production; the study also considered the foresting, distribution, and recycling phases. Thus, the production phase contributed to more than 50% of the impacts on its wastewater and up to 88% of the eutrophication of freshwater. When considering the cellulose production process, the impact on global warming receives a contribution of 46%, depletion of the ozone layer receives a contribution of 39%, and eutrophication of freshwater receives a contribution of 55%, while the remaining impact categories received at least a 42% contribution of this stage. On the other hand, the recovery of material and resources led to the reduction of global warming impacts by more than 70%.
Thus, in light of the advantages presented by the AD-Co of the OFUSW with lime mud and the scarce analysis of this topic in the literature, along with the use of LCA, this study aims to evaluate the environmental and energy feasibility of using biogas generated through the anaerobic co-digestion (AD-Co) of the Organic Fraction of Urban Solid Waste (OFUSW) with lime mud (LM). Life cycle assessment (LCA) methodology will be applied to identify the main environmental impacts, benefits, and contributions of this approach to a circular and sustainable economy.
The proposed solution offers significant advantages, such as reducing greenhouse gas emissions, providing a renewable source of electricity, promoting the diversification of Brazil’s energy matrix, and mitigating the environmental impacts associated with the improper disposal of waste. Furthermore, it delivers financial savings for the pulp and paper industries and enhances the efficiency of methane (CH4) production in anaerobic environments.
Given the promising potential of the AD-Co of the OFUSW with LM, coupled with the limited exploration of this topic in the academic literature, this study seeks to deepen the understanding of the environmental viability of this alternative, positioning it as a sustainable solution for the utilization of urban and industrial waste.

2. Results and Discussion

The results generated were life cycle inventories, impact assessments, and interpretation of the results, along with comparisons and discussions on scenarios. The life cycle inventories obtained, as well as the tables with the calculated and characterized impacts, can be found in the Supplementary Material (Tables S1–S15). For all inventories, the applied allocation factor (AF), in the relevant inputs and outputs, was 0.0379%. Table 1 summarizes the calculated and characterized impacts of the five scenarios (S0 to S4).
In the S0 inventory (Tables S1–S4, of the Supplementary Materials) the lime mud (LM) is destined for the Industrial Sanitary Landfill (ISL) and, as this is a treatment step, it is assumed to be inert lime residue. In the characterized results of this scenario, it was observed that the most relevant impact categories in descending order were WD, CC, FD, HT, and IR.
Through the graph in Figure 1, it is noted that the pulp production phase accounts for 85% or more in 12 of the 18 evaluated impact categories; these results corroborate those found in Corcelli et al.’s study [42]. In order of relevance of the cited categories, the preponderant phase contributed 99.52%, 95.98%, 92.23%, 91.52%, and 94.56%, respectively. Naturally, water consumption is elevated in the kraft process, which explains the water depletion (WD) results. As far as climate change is concerned, the gases that most contribute were CO2 and CH4, possibly from burning fossil fuels such as diesel based on the input data used in SimaPro ®, which also explains the results for FD. Regarding HT, manganese (Mn) compounds, arsenic, barium, and mercury were the main contributors, while for IR, the carbon-14 (C14), radon 222 (222Rn), and cesium 137 (137 Cs) were the most relevant.
It was also noted that MEP and NLT had avoided impacts in the pulp production (30.81%) and LM treatment phases (21.16%). The first category’s results are dependent on the avoided consumption of the marine macronutrients NO−3 and NO−2. On the other hand, the second category’s results arise from the avoided transformation of natural land through the disposal of LM in ISL. With respect to the other phases directly related to LM, transportation contributed 4.85% to ALO. The LM treatment phase influenced both the ULO (13.19%) and ALO phase (10.10%) through the occupation of disposal locations and the occupation of a traffic area in the road network, as well as through the intensive occupation of areas of forest and shrub and sclerophyll terrain, respectively.
As for S1, in which LM is co-digested for biogas generation and electricity production, the inventory (Tables S5–S7, from the Supplementary Materials) highlights include the generation of 831 m3 of biogas, with 623.08 m3 collected, of which 405 m3 was CH4, generating 112.75 kWh of electricity. The consumption of the biodigester resulted in 3.38 kWh. As for the digestate, it stood out for the generation of 5 t, intended for the replacement of NPK agricultural fertilizers, avoiding their production and their related impacts.
S1 was favorable to the LM AD-Co with the Organic Fraction of Urban Solid Waste (OFUSW) from the perspective of environmental impacts. Among the 18 impact categories, only five showed positive balances. The main results of this scenario (Table 1 and Figure 2) are related to the impact categories WD, CC, FD, ALO, HT, and TA. In WD, the results remained close to those seen in S0, indicating that the proposed changes for LM would be irrelevant in view of the impacts of the industry. As for CC, there were important changes. The digestate, due to the avoided production of NPK fertilizers, reduced the impact in this category by 4617.33 kg CO2 eq (96.51%), and therefore, it is highlighted in Figure 2. In the FD category, the digestate also stood out, since it avoided the consumption of natural gas and heat from the burning of diesel for the industrial production of fertilizer, reducing the impact by 95.52%, followed by the cellulose pulp production phase (19.09%) and the AD-Co phase with LM (−3.49%).
For ALO, the lime mud (LM) AD-Co was more relevant, contributing to −100% of the impacts, due to using 10 t of the Organic Fraction of Urban Solid Waste (OFUSW) in the AD-Co, avoiding the occupation of agriculture and forest areas. As for HT, there was a greater distribution of phases, with each one contributing as follows: industrial phases (<78%), LM AD-Co phase (−60.84%), electric energy production from biogas (−21.25%), and digestate (−17.91%). While the AD-Co phase contributed to the consumption of the OFUSW, preventing the release of manganese (Mn) and arsenic (As) compounds into aquatic environments, the phase of producing electricity from biogas avoided the release of hydrogen fluoride gas (FH) into the atmosphere. Finally, in TA, digestate reduced the impacts by 81.88% due to the avoided emission of ammonium nitrate from the production of fertilizers; electricity production reduced impacts by 12.11% due to the avoided emission of sulfur oxides (SOx) and NOx; and, by using electricity from biogas in the AD-Co phase and through the consumption of the OFUSW, the impacts were reduced by 6.01%, avoiding the emission of NOx, ammonia (NH3), and SO2.
Among the impact categories in which the biogas electricity production phase showed the highest contributions are photochemical oxidant formation POF, PMF, and HT, as already discussed. In POF, this phase contributed −45.27%, representing its highest participation among the 18 scenarios. This result is related to the substitution of fossil fuels with biogas, reducing emissions of non-methane volatile organic compounds (NMVOC), which are precursors to tropospheric ozone formation. In PMF, the biogas electricity production phase contributed −18.45%, a result of the reduction in particles released into the atmosphere from the combustion of fossil fuels, such as coal and diesel.
Finally, regarding FEP, the mitigation of over 80% of the impact observed in S1 is linked to the substitution of conventional fertilizers with digestate, which significantly reduces the release of nitrogen and phosphorus compounds into water bodies. Additionally, the use of substrates such as the OFUSW and lime mud in the biodigester promotes better nutrient management, preventing adverse impacts on aquatic systems.
It is worth highlighting that the results from AD-Co in S1 were obtained in laboratory analyses [34]; according to Tyagi et al. [43] the proportion between the mass of the Organic Fraction of Urban Solid Waste (OFUSW) and methane production does not represent the realities of large scale biodigesters with regular production and a higher methane yield rate [37]. However, precisely for that reason, it can be seen that there is a need for further investigations on the AD-Co of the OFUSW using LM, be it for scientific development, to indicate possible uses, such as Pin et al.’s study [44], or for understanding of a country’s specific technical questions, seeking its economic applicability in practical terms on a large scale.
Results for S2, where LM replaces the intermediate covering soil in Municipal Sanitary Landfill (MSL), the inventory (Table S8, of the Supplementary Materials) indicates 1.0 t of this material as having its extraction avoided. In light of this, LM application contributed −284.66 kg CO2 eq (−18.81%) to the total result of 1228.99 kg CO2 eq in the CC category (Table 1 and Figure 3), since it reduced the transformation of soil and the removal of primary vegetation, in turn reducing CO2 emissions. For the same reasons, the application contributed to a 99.98% reduction in avoided impacts in the NTL category.
In the ALO category, the application phase of LM contributes −4.36 m2a, representing −52.02% of the total. For TET, the use of LM as an intermediate covering contributes −87.28%. This category measures the impact of releasing or disposing of toxic elements or products into the soil and is expressed in ‘kg 1,4DB eq’. Despite a significant contribution in this category, the total characterized value is close to zero, with the considered phase avoiding −0.02 kg 1,4DB eq, where cyanide (-CN) is the main component of the result. Finally, PMF shows a contribution of −31.83% from the LM application phase, corresponding to −0.31 kg PM10 eq. This formation arises from vegetation removal and soil alteration processes, which contribute to the formation and emission of particles smaller than 2.5 μm in diameter and between 2.5 μm and 10.0 μm into the air. The issues resulting from this impact range from reduced air quality to impairments of the respiratory and cardiovascular systems in humans.
In S3, the use of lime mud (LM), which avoided the production and application of 1 t CaO as a pH regulator and soil fertilizer (Table S9, Supplementary Materials), had a relatively small percentage impact in the categories. Its largest contribution occurred in ODP, with a value of −6.65% in the application phase, as a result of the avoided mining of crushed stone in open pits which, due to the process adopted, contributed especially to the non-release of CFC-11. The other highlighted category was IR, with the application phase participating with −3.91 kg U235-11 eq (−6.03%), out of a total of 60.92 kg U235-11 eq (Table 1 and Figure 4). This result was due to the avoidance of the open-pit mining of crushed stone, which could contribute to the release of 137Cs to water and C14.
Finally, in S4, where lime mud (LM) replaced the production and application of 1 t of CaO for ceramic pieces and blocks (Table S10, from the Supplementary Materials) significant reductions were obtained in all categories of impacts (Table 1 and Figure 5), with MEP being the smallest of them in the application phase, with −18.85%. In WD, the application phase contributed −3080.84 m3 (†70.96%) of water consumption by avoiding the use of water to generate hydroelectricity for lime production. In the CC category, the avoided lime extraction and milling processes allowed for the reduction of CO2 equivalent emissions by 429.17 kg (71.65%). In FD, up to the stage before application, fuel consumption amounted to 248.58 kg oil eq, with it being reduced to 95.98 kg oil eq. This decrease in the impact of −61.39% may be due to the avoided production of oil and natural gas, due to their reduced consumption as inputs for the production of lime.
The results of the scenarios demonstrated the most relevant impact categories in each one and their contributions; therefore, the advantages and disadvantages in each scenario were noted. The graph in Figure 6 expresses the normalized data and, along with Table 1, allows for comparison between the impact categories and the scenarios themselves.
As a general observation, it can be seen that, with S0 as a reference, most scenarios were advantageous for the reduction of impacts. In the CC category, S1 showed a significant advantage in reducing emissions, with a difference of more than 3000 kg CO2 eq avoided for S4, which was the second-best scenario. This result for S4 is in line with the fact that the CaO (lime) production process emits large amounts of CO2, approximately 1.2 tons of CO2 for each ton of CaO, as presented by Gutiérrez et al. [45]. In S1, the reduction in emissions confirms the finding made by Huttunen et al. [46], who report that when biogas replaces fossil sources, the emission of GHGs is avoided.
For the HT category, the order between S1 and S4 was maintained, and the difference was more than 60 kg 1.4-DB eq. In the IR category, S4 presented an impact reduction of 27.43 kBq U235 eq, the largest reduction of S0. In ULO, MRD, and FD, S1 and S4 were less impactful than the other scenarios. In WD, S4 presented itself as the most advantageous. About S2, only the NLT category stood out, in which it had the least impact. S3, compared to the others, was of little advantage since it did not differ much from S0 in general.
Analyzing the results in Figure 6, it is possible to observe the relevance of the impact categories in each scenario and the expressiveness of S1 about the remaining scenarios. S1 avoided impacts in 13 of the 18 categories. Among them, eight were the most relevant and were divided into water (4), air (3), and soil (1) compartments, with them being, in decreasing order of relevance, FEP, MET, TA, FD, FET, CC, PMF, and MEP. When comparing the normalized results with those characterized by S1, it was observed that the CC, FD, and TA impact categories remained relevant, which did not occur with the others. It was noted that according to the study of Tyagi et al. [43], AD-Co tends to generate smaller impacts in the categories of CC, TA, FEP, MET, and FD, impacts present and relevant in this LCA.
Thus, it can be concluded that S1 obtained the best results compared to the others. Its advantages can be explained mainly by the fact that it involves, in addition to the proper use and destination of the LM, some important factors, presented below, which add up and synergistically favor S1.
The proper disposal of the Organic Fraction of Urban Solid Waste (OFUSW) and the use of biogas for electricity avoid emissions in the environment and reduce the use of non-renewable and more polluting energy sources [43]. The emission of toxic substances that could expose aquatic fauna and flora to environmental damage is also avoided, contributing to the results in the MET and FET categories. In addition, the non-consumption of fossil fuels and the OFUSW not intended for MSL contribute to preventing PMF [47].
Regarding digestate, the non-production of NPK fertilizers proved to be a relevant factor for the results, avoiding emissions with potential for terrestrial acidification (AT) and contributing to the conservation of natural resources such as nitrogen and phosphorus, mainly responsible for impacts related to eutrophication [43]. This statement is indirectly corroborated by the authors of [48], who affirm that, on average, for each ton of the OFUSW used in AD, half results in digestate in accordance with the findings of Giuliano et al. [49], who stated that more than half of the energy in a typical AD remains in this very byproduct.

2.1. Guidelines for the Implementation of Public Policies

Based on the findings of this research, several public policies are identified that could be implemented in Brazil to encourage the adoption of energy production systems from biogas generated through the Co-AD of the Organic Fraction of Urban Solid Waste (OSWU) and lime mud (LM).
Among the key policy proposals is the creation of financial incentives for renewable energy solutions, such as tax reductions and subsidies for industries and companies that adopt waste-to-energy technologies. These incentives could attract investors and stimulate the widespread adoption of these sustainable solutions. Another important aspect is the support for circular economy practices, specifically promoting the revalorization of organic waste and integrating circular economy principles into industrial policies. This approach would contribute to more sustainable industrial practices while reducing environmental impacts associated with waste and improper disposal of residues.
Moreover, it is essential to strengthen regulations on waste disposal, ensuring that industries properly manage their waste and promote environmentally friendly alternatives. The implementation of stricter waste management regulations would enhance sustainability in the sector. Public–private partnerships also hold significant potential to foster the adoption of these technologies. Collaboration between the public sector, private companies, and academic institutions could drive research and the development of pilot projects, promoting innovation and scalability of sustainable technologies, while facilitating the integration of technical and practical knowledge.
Additionally, the strengthening and regulation of the carbon market is crucial to encourage industries to reduce their greenhouse gas (GHG) emissions and promote the decarbonization of their production processes. The implementation of biogas energy systems could serve as an effective strategy to meet internal energy demands while contributing to the reduction of carbon emissions. These public policies have the potential to create an environment conducive to the adoption of biogas technologies, aligning both economic and environmental interests and helping Brazil move toward a more sustainable model of waste management and energy production.

2.2. Final Remarks

Life cycle assessment (LCA) proved to be very useful in collecting information on lime mud (LM) in the literature and especially in generating information on the most relevant environmental impacts of this material. The comparison of S1 with the others confirmed that, from an environmental perspective, LM has important advantages when used in AD-Co with the Organic Fraction of Urban Solid Waste (OFUSW). The proposal allowed for the integration of the impacts generated by the environmentally adequate disposal of the OFUSW and LM, through the energy use of biogas and the adoption of digestate as a fertilizer, synergistically achieving favorable results for the reduction of these impacts, especially in 8 of the 18 categories evaluated. The LCA demonstrated the most relevant environmental impact categories in AD-Co (FEP, MET, TA, FD, FET, CC, PMF, and MEP) and verified that the benefits are mostly concentrated in the water and air compartments of the environment. Thus, this assessment proved to be favorable to the AD-Co proposal from an environmental perspective.
The considerations, approximations, and technical/methodological choices made in this work must be observed for a proper understanding and application of the study. The characteristics of waste depend on the country, region, culture, time of year, and socioeconomic conditions. Thus, as the studies used in this work are aimed at countries other than Brazil, and there is also a difference in scale regarding CH4 generation, a need for further technical development is evident for the AD-Co of the OFUSW with LM for obtaining data that more faithfully portray the realities of the country.
Moreover, using experimental data to model large-scale biodigester applications presents relevant limitations. The behavior observed in experimental systems often does not fully account for the operational challenges and variable conditions encountered in real-world applications, such as changes in waste characteristics, climatic fluctuations, and maintenance requirements for equipment. Scaling up the process can lead to deviations, such as reduced efficiency in biogas conversion due to difficulties in controlling parameters like temperature and pH in larger volumes. Additionally, energy losses and the management of contaminants, such as hydrogen sulfide in biogas, become more critical at an industrial scale.
These factors highlight the need to validate results in medium- and large-scale facilities, enabling adjustments to predictive models. Addressing these challenges provides a more balanced and practical perspective, aiding in the planning and technical feasibility of future projects. Finally, integrating pilot studies that simulate local conditions and align with Brazilian specificities would significantly enhance the representativeness and applicability of the findings.

3. Methodology

3.1. Life Cycle Assessment

The life cycle assessment (LCA) presented herein is based on the NBR ISO 14040:2009 [50] and NBR ISO 14044:2009 [51] standards. The methodological sequence that will be presented includes the definition of the objective and scope, inventory analysis, and impact evaluation. The interpretation phase will be presented in the Results section.
The study by Corcelli et al. [42] was used to compose the data for the pulp and paper industry steps. The study captures a significant amplitude of industry-specific processes with respect to the generation of LM at a considerable level of detail which is scarce in the literature. In this case, the technological and temporal representation of the processes were relevant factors [52]. There is also the fact of presenting the reliability of the data, due to the moderately low variation of the impact indicators in the Monte Carlo analysis. Furthermore, the study by Zhang et al. [34] was used as a groundwork for the calculations of the AD-Co of the Organic Fraction of Urban Solid Waste (OFUSW) with lime mud for similar reasons to those previously cited.

3.1.1. Objective and Scope

The objective of this life cycle assessment (LCA) is to conduct an environmental performance analysis of lime mud (LM) as a co-substrate for the anaerobic digestion of the Organic Fraction of Urban Solid Waste (OFUSW). In doing so, this article seeks to further study LM as a co-substrate in anaerobic digestion (AD) and provide this information to the scientific community; to the public, this study serves as an environmentally friendly alternative for the OFUSW and a study on renewable energy; and finally, to industry, this study provides details on how financial gains can be made through suitable disposal methods for LM as an industrial solid waste (ISW).
The functional unit (FU) adopted for this study was 1.0 t of LM, generated as solid waste in the kraft production process from the pulp and paper industry. Then, the FU was converted into 1.0 t of produced paper, used in Corcelli et al.’s study [42], for the compound unit of interest for this study. The authors divide the paper and pulp production into foresting, pulp production, energy production on site, paper production, distribution, and end-of-life (paper recycling) phases. Only the phases that directly or indirectly influenced the generation of LM as a byproduct were adopted for this study, namely foresting, pulp production, and energy production on site. Furthermore, some phases were created specifically for this study.
One phase of the life cycle assessment (LCA) involved the creation of scenarios (Sx) that could put the proposed study into perspective. For all scenarios, the limits for each system were set as being cradle to grave:
  • S0: Baseline Scenario: The LM is disposed of in an Industrial Sanitary Landfill (ISL). Given that the LM is generated through interconnected processes for the extraction of cellulosic pulp, the S0 goes from the foresting phase to waste treatment in an ISL (Figure 7) [32].
The foresting phase provides the wood for the following step and involves the extraction of wood from the forests and transportation to the factories. The pulp production phase then provides the whitened pulp and involves the debarking of the tree trunks, washing of the chips, wood digestion, pulp washing, sorting, and bleaching of the washed pulp. The chemical recovery and on-site energy generation phase provides the liquor used in wood digestion, the self-consumption of energy, and the production of lime mud (LM), which is made up of the steps of recovering the dregs, capturing and leveraging the by-products, and producing heat and electricity. Transport and final disposition of the LM in an Industrial Sanitary Landfill (ISL) are the final processes.
  • S1: Main scenario, study focus. The LM is sent to a biodigestion plant where it is co-digested with the Organic Fraction of Urban Solid Waste (OFUSW) [34] for electric energy production (Figure 8).
All of the phases from S0 are included in the generation of LM. In addition, there are the LM transportation phases to the biodigestion plan, the AD-Co from the OFUSW using LM, and energy production and digestate generation, thus avoiding the production of fertilizers for the soil.
  • S2: Final disposal of lime mud is in a sanitary landfill, where it will be used as an intermediate covering, substituting soil (Figure 9).
All stages from S0 through the generation of LM as an industrial byproduct are included in this flow. There is an additional transportation phase for the LM to the sanitary landfill, thus avoiding the impacts of soil extraction, including the extraction of vegetation, and its application in a sanitary landfill [32].
  • S3: The LM is used to correct pH of the soil for fertilization, substituting lime fertilizer (CaO) [53] (Figure 10).
This scenario involves all of the S0 stages included in LM generation, with the addition of LM as a fertilizer.
  • S4: Lime mud is used for the production of bricks and ceramic pieces, substituting lime (Figure 11).
This flow involves all of the steps in S0 up to the generation of LM in industry. In addition, it includes the transportation of LM, the flows avoided by lime production, and its application in bricks and ceramic blocks [54].

3.1.2. Life Cycle Inventory Analysis

Based on the study of Corcelli et al. [42], the inventories were prepared with the aim of adapting the input and output data as closely as possible to the conditions in Brazil. Furthermore, in the aforementioned study, for every 1000 kg of paper produced (functional unit—FU—adopted), 0.379 kg of lime mud (LM) was generated. Thus, after an iterative process, it was found that, given the flow of the entire process, the contribution of LM would be relatively small, and the application of an allocation factor (AF) is pertinent. As a criterion, a mass AF was applied in the inventories of all scenarios in all inputs and outputs in which the paper and LM produced had direct or indirect participation.
In addition, for the phases of the scenarios that involved the need to calculate the transport flows for the final destination of the lime mud (LM), a standard average distance of 20 km between the production site and the destination was adopted [55,56], assuming a displacement similar to that ideal for the implantation of a sanitary landfill. This choice was made in order to bring the study closer to the realities that can be found within the country while considering the impact of this activity. As for emissions, the same means of transport, specified in S0, were assumed for all scenarios and Table 2 was used as a reference. Finally, in order to maintain the scopes and limits of systems as cradle to grave, the proposed applications of LM in scenarios S2, S3, and S4, had approximations to be explained in the following items.

S0 Inventory

In this scenario, all of the lime mud (LM) produced is disposed of in an Industrial Sanitary Landfill (ISL), serving as the baseline. It was assumed that production took place at a pulp and paper factory in Brazil. For the foresting phase, wood transportation, distances traveled, fuel consumption, and diesel Lower Calorific Value (LCV) (38.71 MJ/L) were considered [57]. The distances between the forests and the Suzano factory were used as a basis (135.5 km) [58], traversed by trucks loaded with up to 50.0 t of wood and consumption of 0.55 L/km [59]. Emission calculation for air in the foresting phase and LM transportation to an ISL was conducted using emissions factors, which were obtained from Corcelli et al.’s [42] study (Table 2). Furthermore, a distance of 20 km was adopted between the factory and the Industrial Sanitary Landfill (ISL) [55], while the LM was assumed as a byproduct of the inert lime to be treated through burial in a landfill.

S1 Inventory

In this scenario, the lime mud (LM) is disposed of during AD-Co with the Organic Fraction of Urban Solid Waste (OFUSW). In relation to S0, after generating the LM, S1 encompasses transportation, the AD-Co phase, and the production of electricity from biogas. For the LM transportation phase, a distance of 20 km from the factory and the biodigestion plant was adopted [55].
The general proposal for the biodigestion plant can be seen in Figure 12, which would have a pre-established structure. In anaerobic digestion (AD) reactors with moist material (total solid—TS—concentration of ≤15%), the OFUSW along with the LM would be co-digested. The biodigestion process was assumed as a continuous flow and complete mixture, with heating sources in a mesophilic temperature range (37 ± 1 °C) [34]. In order to obtain electrical energy from the chemical biogas energy produced in the biodigesters, a motor generator (internal combustion motor—ICM—using an Otto cycle coupled to an electrical generator) would receive the biogas and transform it into electricity. Part of the electricity obtained would be consumed by the biodigesters, and the tariff model adopted for energy use was that of compensation, included in the distributed generation system (DG) and within the Brazilian captive market [60].
For the AD-Co phase, it was assumed that the food waste (FW) studied by Zhang et al. [34] is equivalent to the Organic Fraction of Urban Solid Waste (OFUSW), the latter coming from municipalities and the lime mud (LM) coming from the pulp and paper industries. The inputs referring to the OFUSW, inoculum, and water needed, calculated for the functional unit (FU) of 1.0 t of LM, were obtained from the proportions experimented in [34]. Such proportions were based on the most expressive result for the generation of CH4 (2700 mL in 39 days), with the proportion adopted as a reference; for each 5 g of LM, there is 50 g of the OFUSW, 100 mL of inoculum, and the volume of water as the one to complete the remainder of the volume of the experimental unit, totaling 500 mL.
The average percentage of gases in biogas considered in this study is shown in Table 3. The average percentage of CH4 in biogas was assumed to be 65% since the studies of Zhang et al. [34] show the production of CH4 without indicating its participation in the generated biogas. This value was adopted because it represents above-average participation and is still in the range of values presented by Salomon and Lora [61], aside from having been adopted by Santos et al. [62]. For the other gases, the average values between the upper and lower limits of Salomon and Lora [61] were considered, with the exception of CO2, a relevant gas in biogas, for which there was a percentage increase in the remainder of the other gases.
As for the electricity used by the biodigesters, a 3% consumption rate was considered [63]. The heat consumption for the reactor was calculated when approximating the total solids of the sum of the Organic Fraction of Urban Solid Waste (OFUSW) and lime mud (LM). The equation used was from Number 1 [64,65]:
C = Q L . C E . ( T D T L )
where:
  • C: heat (energy) necessary for heating the mass, kJ·d−1;
  • QL: influent mass to the digestor, kgST·d−1;
  • CE: heat transfer coefficient by area, 4.2 kJ·kg−1·°C;
  • TD: biodigester interior temperature, °C;
  • TL: biodigester tributary mass temperature, °C.
The heat value was converted to GJ. In this case, the heat power source was assumed to be municipal or industrial natural gas. This input was obtained from databases using SimaPro ® v.8.0.3.14 (PhD). in order to evaluate the life cycle.
The product of this biogas phase is digestate, which was determined as follows: the biogas produced is calculated based on the previously presented proportion (CH4/LM) used in Zhang et al.’s study [34] (functional unit, FU = 1.0 ton of LM), while the other gases were obtained based on the CH4 volume to arrive at the total volume; the digestate generated was calculated through the proportion of 0.5 t of digestate produced per one ton of the Organic Fraction of Urban Solid Waste (OFUSW) [48]. In this case, a mass allocation was input directly into the software. The digestate was adopted as the avoided product, substituting the production of fertilizers made from nitrogen (N), potassium (K), and phosphorous (P).
Emissions were calculated based on the percentage of biogas that was not collected, considering that it would be emitted during the biodigestion and electric energy production processes and computed during the AD-Co phase. Thus, with a collection efficiency (Ec) of 75% as seen in Equation (2), there would be a 25% loss rate [66].
Finally, with the total amount of gas generation, it was possible to determine the power to be generated and the available electric energy. Equation (2), adapted from [67], enabled the calculation of the power necessary for the Internal Combustion Engine (ICE):
P = Q C H 4 . E . E C . P C H 4 .   ( 1 31   536   000   .     1 1000 )
where:
  • P: available power (kW);
  • QCH4: methane flow (m3CH4);
  • PCH4: methane calorific power (equal to 35.53·106 J/m3CH4);
  • Ec: biogas collection efficiency (%);
  • E: motor/turbine efficiency (%);
  • 31,536,000: seconds in a year (s/year);
  • 1/1000: conversion from J/s to kW.
Motor efficiency (E) was set at 33%, equivalent to a standard combustion motor [68,69]. Finally, the energy generated was the product of power, the capacity factor (CF), adopted at 0.8, and the number of hours in a year (8760 h) [70]. It was assumed that there would be sulfate treatment and water removal in order to prolong the useful life of the motor, whose impact was not considered in the life cycle assessment (LCA) [71].
Regarding the air emissions generated by the combustion of ICE, the emission factors in Table 4 were used to calculate the mass quantity of gases released in the atmosphere. These values were obtained considering the 25% loss rate, as previously adopted [66].

Inventories of S2, S3, and S4

Scenarios 2, 3, and 4 all underwent substitution of some input for lime mud (LM), using input available in the SimaPro® database, which is why their descriptions are more simplified.
For S2, transportation assumed the considerations at the beginning of Section 3.1.1. The substituted input in this case was the natural resource of soil. In this case, the LM transportation to the Municipal Sanitary Landfill (MSL) was added; however, due to limitations in the database, the application of LM in the Municipal Sanitary Landfill was not included. Thus, to maintain the scenario boundaries, it was assumed that these flows would be approximated to the application flows for MSL in general.
Regarding S3, the avoided product was lime fertilizer, which included the flows from fertilizer production to availability on the market in its inventory. Transportation from this point to the soil application location was added and the avoided product flow was also approximated to the flows of LM on the soil.
Finally, S4 avoided the production of ground and loose lime, considering the flows up to production in its inventory. In this case, the transportation to the ceramic block production locale was added, and it was assumed that it would have approximate LM application values.

3.1.3. Impact Assessment

For the stage of impact assessment, the life cycle assessment (LCA) software SimaPro® v.8.0.3.14 (PhD) was used. The databases and libraries available on the software were considered, namely Industry data 2.0, Ecoinvent 3, ELCD, USLCI, the USA Database, Agri-footprint, the EU&DK Database, LCA Food DK, and the Swiss Database.
Since the purpose of this step is to associate the inventory data with the effects caused by the life cycle, it is necessary to choose an evaluation method that expresses the inventory flows in indicators and categories suitable for the study. Thus, it is possible to obtain scores for these indicators, which express the relative severity of the environmental impact categories aligned with the study [73].
The chosen method was ReCiPe (H) V1.10/World (2010), with all impact categories being adopted as the midpoint (18), seeing that the approach is oriented to the problem or effect, while in the endpoint category, “the middle point”, the approach is oriented to the damages caused [74]. The environmental impact categories, with their respective abbreviations, are as follows [75]:
  • Climate change (CC), ozone depletion (ODP), terrestrial acidification (TA), freshwater eutrophication (FEP), marine eutrophication (MEP), human toxicity (HT), photochemical oxidant formation (POF), particulate material formation (PMF), terrestrial ecotoxicity (TET), freshwater ecotoxicity (FET), marine ecotoxicity (MET), ionizing radiation (IR), agricultural land occupation (ALO), urban land occupation (ULO), natural land transformation (NLT), water depletion (WD), mineral resource depletion (MRD), and fossil fuel depletion (FD).
In this study, the selected impact categories are relevant for understanding the environmental effects, particularly those associated with the co-digestion of the OFUSW with lime mud (LM), assessing the benefits and impacts of this process compared to other scenarios.
The CC (climate change) category is crucial as it measures greenhouse gas emissions associated with life cycle stages, a central factor given the potential of biogas to replace fossil fuels. ODP (ozone depletion), although less critical in this context, is relevant for assessing specific chemical emissions that may occur in the industrial processes involved. TA (terrestrial acidification) and FEP (freshwater eutrophication) are significant due to the management of waste and nutrients, which can impact soils and water bodies if not properly handled. MEP (marine eutrophication) complements this analysis by considering potential nutrient discharges into coastal environments, while HT (human toxicity) and TET (terrestrial ecotoxicity), FET (freshwater ecotoxicity), and MET (marine ecotoxicity) allow for the assessment of toxicity risks from substances released into the environment during processing and product use in the life cycle. POF (photochemical ozone formation) and PMF (particulate matter formation) are relevant to evaluate the atmospheric emissions that affect public health and air quality.
Regarding natural resources, WD (water depletion) is particularly important due to the water consumption in lime mud production and its direct impact on water sustainability. MRD (mineral resource depletion) and FD (fossil fuel depletion) emphasize the importance of rationalizing the use of non-renewable resources and promoting energy diversification, particularly through biogas. Land-use-related categories, such as Agricultural ALO (land occupation), ULO (urban land occupation), and NLT (natural land transformation), enable the analysis of territorial expansion impacts for waste management, raw material production, and infrastructure development. Finally, IR (ionizing radiation), though less directly applicable, helps identify potential impacts associated with specific energy sources in the system’s life cycle.
These metrics are essential for the integrated assessment of environmental impacts and for proposing solutions that maximize the environmental and economic benefits of the studied process.
Regarding the choice of method ReCiPe, the alignment of midpoint indicators with the target audience of the study was the central criterion. The option to keep all impact categories is related to one of the purposes of this study, which is to explore the extent of the impacts associated with LM in the proposed scenarios and make this information available to the target audience. Through ReCiPe, impacts were identified, characterized, evaluated, and normalized. It has been observed that normalization is an important procedure for comparing different impact categories since it allows for the use of a common unit between them [76].
The justifications for using this method include the fact that it is widely used and can enable a more robust comparison of studies in general with the current study. Moreover, it is one of the most recent and up-to-date life cycle assessment (LCA) methods [75,77], and it allows for the use of a hierarchical consensus model (H), which is frequently adopted in scientific models and many times held as the standard model. As well as the normalization of this study’s data in relation to studies around the world, it possesses the widest range of midpoint categories; it uses, when possible, mechanisms of global impact and, in relation to other approaches, it does not potentialize impacts from future flows [42,73,75].

4. Conclusions

The objective of this study was to evaluate the environmental impacts associated with biogas production from the AD-Co of organic residues with LM. Based on the results from the LCA, avoided impacts were identified in the pulp production phase (30.81%) and the LM treatment phase (21.16%). Transportation related to LM contributed 4.85% to the impacts in the ALO category. In scenario S1, in which LM was co-digested with the OFUSW for biogas generation and electricity production, 831 m3 of biogas was produced, with 623.08 m3 collected. This scenario was favorable from an environmental perspective, showing positive results in five impact categories (WD, CC, FD, ALO, HT, and TA). However, when normalized data were considered, avoided impacts were observed in 8 out of the 18 categories analyzed.
In scenarios S2, S3, and S4, significant reductions were observed in several categories. In S2 LM contributed −284.66 kg CO2 eq (−18.81%) in the CC category and a 99.98% reduction in NTL. S3 obtained a relatively smaller impact, with a highlight in ODP (−6.65%) and IR (−6.03%). S4 obtained a significant reduction in all categories, such as WD (−70.96%) and CC (−71.65%), due to the avoided processes of lime extraction and milling. With S0 as a reference, most scenarios demonstrated environmental advantages. S1 stood out as the most favorable, especially due to the proper use and disposal of LM, along with factors like the energy recovery from biogas and the replacement of conventional fertilizers, which synergistically contributed to the best results.
It is understood that the present study precisely contributes to the understanding of how energy alternatives can help reduce environmental impacts. The AD-Co of the OFUSW with LM stands as an alternative for the environmentally appropriate disposal of these residues, adds value to USW through the energy use of biogas and the agricultural use of digestate, and provides energy from a renewable source, which contributes to the diversification of the energy matrix of the country. In addition, it avoids several environmental impacts and can generate savings in financial resources for industries and public entities. Such results stem from the study’s adherence to the global trend of circular economics, which guided the approach of reintroducing materials, previously disposed of without added value, in the productive and economic value chain.
Although challenges still exist, the implementation of public policies and incentives such as tax reductions for businesses that decide to adopt this energy-producing system could attract investors. The adoption of this energy system could also provide the pulp and paper industry with an opportunity to decarbonize the sector, as well as mitigate the associated environmental impacts. As future work, a technical and economic evaluation is suggested, considering the AD-Co of the OFUSW and LM, along with the implementation of a pilot-scale plant, to evaluate potential improvements to be implemented.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/methane4010007/s1. Table S1: S0 Inventory—Foresting Phase. Values from production of 1t of LS. Table S2: S0 Inventory—Pulp Production Phase. Values from production of 1t of LS. Table S3: Inventory of S0—chemical recovery phase and on-site energy production. Values from production of 1t of LS. Table S4: S0 Inventory—Lime Mud Transportation Phase to the ISL and Treatment at the ISL. Values from production of 1t of LS. Table S5: S1 Inventory—foresting phase through LS transportation to the biodigestion plant. Values from production of 1t of LS. Table S6: S1 Inventory—Lime Mud co-digestion. Values from production of 1t of LS. Table S7: S1 Inventory—Electrical Energy Production via Biogas. Values from production of 1t of LS. Table S8: S2 Inventory—foresting phase to substitution of soil with LS in an MSL. Values from production of 1t of LS. Table S9: Inventory of S3—foresting phase for substituting lime fertilizer with LS on soil. Values from production of 1t of LS. Table S10: Foresting phase through the substitution of lime with Lime Mud in ceramic pieces. Values from production of 1t of LS. Table S11: Calculated and characterized impacts of CV of LC for S0 (UF = 1t of LC). Table S12: Calculated and characterized results for CV of LS for S1 (UF = 1t of LS). Table S13: Calculated and characterized impacts of CV from LS for S2 (UF = 1t of LS). Table S14: Calculated and characterized impacts of CV of LS for S3 (UF = 1t of LS). Table S15: Calculated and characterized impacts of CV of LS for S4 (UF = 1t of LS).

Author Contributions

Conceptualization, R.M.B., U.R.d.S.C., M.L.G.R., G.L.T.F. and I.F.S.d.S.; methodology, R.M.B., U.R.d.S.C. and M.L.G.R.; software, R.M.B., U.R.d.S.C. and M.L.G.R.; validation, U.R.d.S.C., A.M.d.C.C. and M.A.d.B.M.; formal analysis, R.M.B., U.R.d.S.C. and M.L.G.R.; investigation, U.R.d.S.C., A.M.d.C.C. and M.A.d.B.M.; resources, R.M.B. and U.R.d.S.C.; data curation, U.R.d.S.C. and M.L.G.R.; writing—original draft preparation, U.R.d.S.C., R.M.B., A.M.d.C.C. and M.A.d.B.M.; writing—review and editing, R.M.B., U.R.d.S.C., A.M.d.C.C., M.A.d.B.M. and A.J.M.d.O.P.; visualization, U.R.d.S.C., A.M.d.C.C., M.A.d.B.M. and A.J.M.d.O.P.; supervision, R.M.B.; project administration, R.M.B.; funding acquisition, R.M.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Federal University of Itajubá by granting the Master of Science scholarship to Ulisses Raad Coelho.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are openly available at https://repositorio.unifei.edu.br/xmlui/handle/123456789/3244. Access on 11 January 2025.

Acknowledgments

The authors would like to thank the Federal University of Itajubá (Universidade Federal de Itajubá, UNIFEI; in Portuguese) for granting the Master of Science scholarship to Ulisses Raad Coelho through its Institutional Scholarship Program. The authors would like to thank the Brazilian National Council for Scientific and Technological Development (Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq; in Portuguese) for granting the Productivity in Research scholarship to Regina Mambeli Barros (P1D Process Number 303036/2021-4) and Geraldo Lúcio Tiago Filho. We would like to thank the Minas Gerais State Agency for Research and Development (Fundação de Amparo à Pesquisa do Estado de Minas Gerais, FAPEMIG, in Portuguese) for granting financial support through “Improvement of biogas energy potential from anaerobic (co)digestion of solid organic waste as an incentive to renewable energy sources: substrate pre-treatment and co(digestion) aiming at Hydrogen use” (Process N.: APQ-00568-21) and the project RED-00090-21, “Theoretical-experimental evaluation of the production and use of green hydrogen in Minas Gerais”. We are thankful to FAPEMIG for granting the Doctorate scholarship (finance code I) to Adriele Maria de Cássia Crispim and the Master of Science scholarship to Aylla Joani Mendonça de Oliveira Pontes.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

AD-CoAnaerobic Co-digestion
ADAnaerobic Digestion
ALOAgricultural Land Occupation
AFAllocation Factor
CFCapacity Factor
CBCardboard
CCClimate Change
CODChemical Oxygen Demand
CSTRContinuous Stir-Tank Reactor
EMotor Efficiency
FDFossil Fuel Depletion
FEPFreshwater Eutrophication
FETFreshwater Ecotoxicity
FWFood Waste
FUFunctional Unit
GHGGreenhouse Gas
HTHuman Toxicity
ICEInternal Combustion Engine
IRIonizing Radiation
ISLIndustrial Sanitary Landfill
ISWIndustrial Solid Waste
LCLife Cycle
LCALife Cycle Assessment
LCVLower Calorific Value
LMLime Mud
MEP Marine Eutrophication
METMarine Ecotoxicity
Mono-ADMono Anaerobic Digestion
MRDMineral Resource Depletion
MSLMunicipal Sanitary Landfill
NLTNatural Land Transformation
NMVOCNon-Methane Volatile Organic Compounds
NSWPNatural Solid Waste Policy
ODPOzone Depletion
OFUSWOrganic Fraction of Urban Solid Waste
OMOrganic Material
PMFParticulate Matter Formation
POF Photochemical Ozone Formation
SSSewage Sludge
TATerrestrial Acidification
TETTerrestrial Ecotoxicity
USWUrban Solid Waste
ULOUrban Land Occupation
VSsVolatile Solids
WDWater Depletion

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Figure 1. Graph of the calculated and characterized impacts of LM for S0, expressed in percentages (%) (FU = 1 t of LM).
Figure 1. Graph of the calculated and characterized impacts of LM for S0, expressed in percentages (%) (FU = 1 t of LM).
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Figure 2. Graph of the calculated and characterized impacts of LM for S1, expressed in percentages (%) (FU = 1 t of LM).
Figure 2. Graph of the calculated and characterized impacts of LM for S1, expressed in percentages (%) (FU = 1 t of LM).
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Figure 3. Graph of the calculated and characterized impacts of LM for S2, expressed in percentages (%) (FU = 1 t of LM).
Figure 3. Graph of the calculated and characterized impacts of LM for S2, expressed in percentages (%) (FU = 1 t of LM).
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Figure 4. Graph of the calculated and characterized impacts of LM for S3, expressed in percentages (%) (FU = 1 t of LM).
Figure 4. Graph of the calculated and characterized impacts of LM for S3, expressed in percentages (%) (FU = 1 t of LM).
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Figure 5. Graph of the calculated and characterized impacts of LM for S4, expressed in percentages (%) (FU = 1 t of LM).
Figure 5. Graph of the calculated and characterized impacts of LM for S4, expressed in percentages (%) (FU = 1 t of LM).
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Figure 6. Graph of the normalized impacts for each scenario.
Figure 6. Graph of the normalized impacts for each scenario.
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Figure 7. System boundaries for the product in S0.
Figure 7. System boundaries for the product in S0.
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Figure 8. System boundaries for the product in S1.
Figure 8. System boundaries for the product in S1.
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Figure 9. System boundaries for the product in S2.
Figure 9. System boundaries for the product in S2.
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Figure 10. System boundaries for the product in S3.
Figure 10. System boundaries for the product in S3.
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Figure 11. System boundaries for the product in S4.
Figure 11. System boundaries for the product in S4.
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Figure 12. General proposal for a biodigestion plant for electrical energy production.
Figure 12. General proposal for a biodigestion plant for electrical energy production.
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Table 1. Impacts calculated and characterized by scenario (FU = 1 t of LM).
Table 1. Impacts calculated and characterized by scenario (FU = 1 t of LM).
Impact CategoryUnitS0
(LM—ASI)
S1
(LM—Biogas)
S2
(LM—MSL)
S3
(LM—Soil)
S4
(LM—Ceramic)
CCkg CO2 eq1519.35−3270.451228.991482.06429.17
ODPkg CFC-11 eq0.000050.0000060.000050.000050.00002
TAkg SO2 eq3.40−28.913.253.201.66
FEPkg P eq0.09−0.520.080.080.05
MEPkg N eq0.21−2.060.210.210.15
HTkg 1,4-DB eq78.65−17.7676.1077.4244.00
POFkg NMVOC3.69−9.293.353.461.69
PMFkg PM10 eq1.36−6.180.911.280.61
TETkg 1,4-DB eq0.02−0.280.0030.020.01
FETkg 1,4-DB eq2.31−2.742.282.281.29
METkg 1,4-DB eq2.49−2.282.422.461.29
IRkBq U235 eq65.4528.4464.7260.9227.43
ALOm2a9.33−43.134.028.396.24
ULOm2a7.811.246.606.782.29
NLTm20.150.13−3.980.190.07
WDm34345.524408.284341.044340.511260.71
MRDkg Fe eq13.89−6.9913.5813.625.86
FDkg oil eq252.19−970.06247.96236.2995.98
Impact category legend: Climate change (CC), ozone depletion (ODP), terrestrial acidification (TA), freshwater eutrophication (FEP), marine eutrophication (MEP), human toxicity (HT), photochemical oxidant formation (POF), particulate material formation (PMF), terrestrial ecotoxicity (TET), freshwater ecotoxicity (FET), marine ecotoxicity (MET), ionizing radiation (IR), agricultural land occupation (ALO), urban land occupation (ULO), natural land transformation (NLT), water depletion (WD), mineral resource depletion (MRD), and fossil fuel depletion (FD). Color highlight legend: Green—avoided negative impact; Yellow—lower relevant negative impact; Red—higher relevant negative impact.
Table 2. Gas emission factors for transport via truck on the highway.
Table 2. Gas emission factors for transport via truck on the highway.
Gas Emission Factors (kg/t-km) on the Highway
CO20.083008
N2O0.000002
CO0.000671
CH40.000006
NOx0.001014
Non-methane volatile organic compound0.000145
Source: [42].
Table 3. Participation of gases in the biogas.
Table 3. Participation of gases in the biogas.
GasBiogas Participation (%)
CH465.00%
CO230.35%
N21.50%
H2S0.30%
O20.55%
NH30.30%
H22.00%
Total100.00%
Table 4. Biogas emission factors through the use of an ICE.
Table 4. Biogas emission factors through the use of an ICE.
GasEmission Factor Through the Use of an ICE (g/m3 Biogas)
NOx6.96
CO5.076
Particulate Material0.139
SOx0.953
HCl0.085
HF0.095
Source: Adapted from [72] apud [39].
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Coelho, U.R.d.S.; Crispim, A.M.d.C.; Martins, M.A.d.B.; Barros, R.M.; Reno, M.L.G.; Filho, G.L.T.; dos Santos, I.F.S.; Pontes, A.J.M.d.O. Biogas Energy Usage Through the Co-Digestion of the Organic Fraction of Urban Solid Waste with Lime Mud: An Environmental Impact Analysis. Methane 2025, 4, 7. https://doi.org/10.3390/methane4010007

AMA Style

Coelho URdS, Crispim AMdC, Martins MAdB, Barros RM, Reno MLG, Filho GLT, dos Santos IFS, Pontes AJMdO. Biogas Energy Usage Through the Co-Digestion of the Organic Fraction of Urban Solid Waste with Lime Mud: An Environmental Impact Analysis. Methane. 2025; 4(1):7. https://doi.org/10.3390/methane4010007

Chicago/Turabian Style

Coelho, Ulisses Raad da Silva, Adriele Maria de Cássia Crispim, Maria Auxiliadora de Barros Martins, Regina Mambeli Barros, Maria Luiza Grillo Reno, Geraldo Lucio Tiago Filho, Ivan Felipe Silva dos Santos, and Aylla Joani Mendonça de Oliveira Pontes. 2025. "Biogas Energy Usage Through the Co-Digestion of the Organic Fraction of Urban Solid Waste with Lime Mud: An Environmental Impact Analysis" Methane 4, no. 1: 7. https://doi.org/10.3390/methane4010007

APA Style

Coelho, U. R. d. S., Crispim, A. M. d. C., Martins, M. A. d. B., Barros, R. M., Reno, M. L. G., Filho, G. L. T., dos Santos, I. F. S., & Pontes, A. J. M. d. O. (2025). Biogas Energy Usage Through the Co-Digestion of the Organic Fraction of Urban Solid Waste with Lime Mud: An Environmental Impact Analysis. Methane, 4(1), 7. https://doi.org/10.3390/methane4010007

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