A review of mathematical models for composting

A novel micro-CT approach for in situ visualization of the spatial dynamics of mesovoids in aerobic composting piles

The spatial configuration of mesovoids profoundly affects the aerobic composting microenvironment, which governs vital processes such as greenhouse gas production and emission, thermal conduction, and overall composting efficiency. Nondestructive in-situ characterization of the composting spatial structure is crucial to better understand its interaction mechanism with the microenvironment. In this study, a valuable contribution to the field of composting research was made by introducing micro-computed tomography (micro-CT) tool for in situ three-dimensional (3D) visual characterizing the void structure dynamics of straw and manure compost pile units at the mesoscale. Representative samples at different composting stages derived from wheat straw and cow manure were procured by pre-embedding samplers in laboratory-based aerobic composting reactor systems. Based on an advanced Skyscan 1275 micro-CT system, scanning conditions and image processing algorithms were determined, and the void structure and their dynamic changes in the pile unit during composting were in-situ 3D visualized for the first time. The micro-CT images effectively reveal well-developed void structures exhibiting spatiotemporal dynamics during composting, and they exhibit excellent consistency with conventional macrophysical effects and wet chemical analyses. Micro-CT quantification results of the void structure parameters changes in pile unit during composting were as follows: percentage of the total voidage and the connected voidage in pile unit were in the range of 52.34%-58.56%, indicating a very suitable composting spatial structural microenvironment. This new micro-CT method provides a valuable perspective for analyzing and understanding the complex aerobic composting process.

Correlations between sewage sludge composting physicochemical parameters and emissions of greenhouse gases and ammonia: A statistical analysis

Mitigating the environmental impact of composting by the reduction of greenhouse gases (N2O, CH4) and ammonia (NH3) emissions is a major challenge. To meet this challenge, the understanding of the relationships between composted substrates initial physicochemical parameters and gas emissions is essential. From a long-term perspective, it will allow to guide the recipe formulation of the initial mixture to be composted, with a view to reducing gas emissions during composting. This study gathered literature data targeting sewage sludge composting and performed statistical correlation analyses between cumulative gas emissions and the following parameters: sewage sludge, bulking agent and composted mixture initial physicochemical parameters (pH, dry matter, total carbon, total nitrogen, C/N), the dry mass ratio of sewage sludge to bulking agent and the duration of composting. The average values of cumulative emissions show a large variability: 1.37 ± 2.71 gC.kg initial mix DM-1, 0.13 ± 0.17 gN.kg initial mix DM-1 and 2.23 ± 2.79 gN.kg initial mix DM-1 for CH4, N2O and NH3 emissions respectively. Although the correlation analysis highlighted some significant interesting correlations between initial physicochemical parameters and gas emissions (p.value < 0.05), reliable multiparametric model could not fit the data, meaning that the actual literature data are not sufficient to explain most part of gas emissions. Among the most interesting relationships, the study showed that the dry matter of the composted mixture is negatively correlated to N2O emissions, while the ratio of sewage sludge to bulking agent and the duration of composting are positively correlated to N2O emissions. It was also shown that the pH of the bulking agent is positively correlated to NH3 emissions. Considering the large part of the emission variability that is not explained and the difficulty to link the correlation with their causality, it will be interesting to improve composting gas emissions knowledge in future research by analyzing free air space, bulking agent adsorption capacity and available and biodegradable organic matter. These parameters are of particular interest in solving the main problems associated with sewage sludge composting, namely porosity and nitrogen retention. This study also highlighted the necessity to extend the duration of the composting studies over 40 days in order to measure possible N2O late release and better identify parameters influencing N2O emissions.

Optimizing stormwater runoff treatment: The role of two-stage tandem rain gardens

Regarded as a superior urban stormwater management solution, rain gardens can effectively store rainfall runoff and purify water quality. However, the efficiency of traditional rain gardens (TRG) in regulating runoff and removing nitrogen and phosphorus varies under different hydrological conditions. In this study, the TRG was retrofitted to construct a two-stage tandem rain garden (TTRG). Based on the experimental monitoring of rain gardens under natural rainfall from 2011 to 2013, results indicated a significantly higher runoff reduction capacity for the TTRG compared to the traditional garden (p < 0.05), with average runoff and peak flow reduction rates increasing by 42.8% and 36.2%, respectively. Rainfall characteristics significantly impacted the runoff reduction of the TRG (p < 0.05), but not the TTRG (p > 0.05), demonstrating the enhanced control and stability of the TTRG in managing rainfall runoff. The concentration removal efficiency of nitrate nitrogen (NO3--N) was significantly improved (p < 0.05), whereas the total phosphorus (TP), ammonium nitrogen (NH3-N) and total nitrogen (TN) were not significantly changed (p > 0.05). The first-order kinetic model was used to fit the removal effect of different pollutants before and after retrofitting the rain garden, and the removal of NO3--N by the TTRG was better than that of the TRG. The TTRG showed significantly higher load removal efficiencies for TP, NO3--N, and NH3-N compared to TRG (p < 0.05), with average load removal rates increasing by 49.92%, 75.02%, and 14.81%, respectively. The TTRG can regulate urban rainfall runoff more efficiently and stably. By changing the water flow path in the rain garden, the TTRG has a better runoff reduction ability and pollutant purification effect.

Pilot-scale membrane-covered composting of food waste: Initial moisture, mature compost addition, aeration time and rate

The impact of different operational parameters on the composting efficiency and compost quality during pilot-scale membrane-covered composting (MCC) of food waste (FW) was evaluated. Four factors were assessed in an orthogonal experiment at three different levels: initial mixture moisture (IMM, 55 %, 60 %, and 65 %), aeration time (AT, 6, 9, and 12 h/d), aeration rate (AR, 0.2, 0.4, and 0.6 m3/h) and mature compost addition ratio (MC, 2 %, 4 %, and 6 %). Results indicated that 55 % IMM, 6 h/d AT, 0.4 m3/h AR, and 4 % MC addition ratio simultaneously provided the compost with the maximum cumulative temperature and the minimum moisture. It was shown that the IMM was the driving factor of this optimum composting process. On contrary, the optimal parameters for reducing carbon and nitrogen loss were 65 % IMM, 6 h/d AT, 0.4 m3/h AR, and 2 % MC addition ratio. The AR had the most influence on reducing carbon and nitrogen losses compared to all other factors. The optimal conditions for compost maturity were 55 % IMM, 9 h/d AT, 0.2 m3/h AR, and 6 % MC addition ratio. The primary element influencing the pH and electrical conductivity values was the AR, while the germination index was influenced by IMM. Protein was the main organic matter limiting the composting efficiency. The results of this study will provide guidance for the promotion and application of food waste MCC technology, and contribute to a better understanding of the mechanisms involved in MCC for organic solid waste treatment.

Enhancing C and N turnover, functional bacteria abundance, and the efficiency of biowaste conversion using Streptomyces-Bacillus inoculation

Microbial inoculation plays a significant role in promoting the efficiency of biowaste conversion. This study investigates the function of Streptomyces-Bacillus Inoculants (SBI) on carbon (C) and nitrogen (N) conversion, and microbial dynamics, during cow manure (10% and 20% addition) and corn straw co-composting. Compared to inoculant-free controls, inoculant application accelerated the compost's thermophilic stage (8 vs 15 days), and significantly increased compost total N contents (+47%) and N-reductase activities (nitrate reductase: +60%; nitrite reductase: +219%). Both bacterial and fungal community succession were significantly affected by DOC, urease, and NH4+-N, while the fungal community was also significantly affected by cellulase. The contribution rate of Cupriavidus to the physicochemical factors of compost was as high as 83.40%, but by contrast there were no significantly different contributions (∼60%) among the top 20 fungal genera. Application of SBI induced significant correlations between bacteria, compost C/N ratio, and catalase enzymes, indicative of compost maturation. We recommend SBI as a promising bio-composting additive to accelerate C and N turnover and high-quality biowaste maturation. SBI boosts organic cycling by transforming biowastes into bio-fertilizers efficiently. This highlights the potential for SBI application to improve plant growth and soil quality in multiple contexts.

Investigating fungal community characteristics in co-composted cotton stalk and various livestock manure products

Agricultural wastes, comprising cotton straw and livestock manure, can be effectively managed through aerobic co-composting. Nevertheless, the quality and microbial characteristics of co-composting products from different sources remain unclear. Therefore, this study utilized livestock manure from various sources in Xinjiang, China, including herbivorous sheep manure (G), omnivorous pigeon manure (Y), and pigeon-sheep mixture (GY) alongside cotton stalks, for a 40-day co-composting process. We monitored physicochemical changes, assessed compost characteristics, and investigated fungal community. The results indicate that all three composts met established composting criteria, with compost G exhibiting the fastest microbial growth and achieving the highest quality. Ascomycota emerged as the predominant taxon in three compost products. Remarkably, at the genus level, the biomarker species for G, Y, and GY are Petromyces and Cordyceps, Neurospora, and Neosartorya, respectively. Microorganisms play a pivotal role in organic matter degradation, impacting nutrient composition, demonstrating significant potential for the decomposition and transformation of compost components. Redundancy analysis indicates that potassium, total organic carbon, and C:N are key factors influencing fungal communities. This study elucidates organic matter degradation in co-composting straw and livestock manure diverse sources, optimizing treatment for efficient agricultural waste utilization and sustainable practices.

Semi-quantitative study on the secondary compression characteristics of municipal solid waste in aerobic and anaerobic bioreactors

Aeration plays a crucial role in accelerating the secondary compression of municipal solid waste (MSW) for the scientific implementation of aerobic bioreactor technology. There are few comparative reports on the secondary compaction characteristics of MSW in aerobic and anaerobic bioreactors. In this study, six long-term compression tests were conducted to analyze the impact of aeration on MSW compression characteristics, considering two degradation conditions (i.e. aerobic and anaerobic conditions) and three overburden stresses (i.e. 30, 50 and 100 kPa). Model-fitting analysis was employed to examine the data from the tests and exiting literatures. The results showed that aeration effectively increased the rate of secondary compression, and slightly enhanced the steady-state secondary compression strain. In addition, these enhancements tended to decrease with increasing stresses. The increment ratio of the secondary compression rate constant (Rk) was concentrated in the range of 25 % to 100 %, and increases with the increase of aeration rate. The increment ratio of the steady-state secondary compression strain (Rε) ranged from 10 % to 90 %, for the MSW with higher content of paper and wood exhibited higher Rε. The advance ratio of the secondary compression stabilization time (Rt) fell within the range of 20-50 %, and Rt is higher when the moisture content is in the range of 50-65 %. These findings provide valuable guidance on the accelerated stabilization in aerobic bioreactors, providing practical references for the application of aerobic technology to informal landfills.

Mathematical modeling of biochar's role in elevating co-composted poultry carcass temperatures

Previous studies reported that incorporating biochar into composting systems leads to an increase in compost temperatures. Although potential reasons, such as improved microbial activity or increased insulation, were suggested, no study has quantitatively determined the contribution of either aspect. In this study, we developed a heat transfer model for a biochar-amended co-composting system based on the measurements from our two previously published studies conducted to co-compost poultry carcasses with woodchips and wood-based (WBC), distillers grain (DGBC), and cow manure (CMB) biochar. The two composting studies were conducted over three heating cycles, with two turnings separating each cycle. The simulation for the second heating cycle, during which the compost materials began to degrade and were well-mixed, showed an average R2 value of 0.86 and was selected for further analyses. Results from the model suggested that incorporating biochar into the composting mixture increases thermal conductive losses. For example, at a biochar addition rate of 13 % (v/v), the predicted longitudinal conductive resistance of the compost pile was reduced by 24.9 %. However, the total heat unit still increased by 11.2 ± 3.17 % due to the enhancement of microbial activity as supported by elevated oxygen consumption (38.1-61.1 %). When biochar was applied in layers on the surface of the composting bins, its impact on microbial activity was minimal, primarily functioning as an insulator. Under these conditions, the total heat unit was 8.7 % higher than the control. These findings suggest that biochar's primary effect on temperature development was through promoting microbial activity.

A Critical Review of Data Science Applications in Resource Recovery and Carbon Capture from Organic Waste

Municipal and agricultural organic waste can be treated to recover energy, nutrients, and carbon through resource recovery and carbon capture (RRCC) technologies such as anaerobic digestion, struvite precipitation, and pyrolysis. Data science could benefit such technologies by improving their efficiency through data-driven process modeling along with reducing environmental and economic burdens via life cycle assessment (LCA) and techno-economic analysis (TEA), respectively. We critically reviewed 616 peer-reviewed articles on the use of data science in RRCC published during 2002-2022. Although applications of machine learning (ML) methods have drastically increased over time for modeling RRCC technologies, the reviewed studies exhibited significant knowledge gaps at various model development stages. In terms of sustainability, an increasing number of studies included LCA with TEA to quantify both environmental and economic impacts of RRCC. Integration of ML methods with LCA and TEA has the potential to cost-effectively investigate the trade-off between efficiency and sustainability of RRCC, although the literature lacked such integration of techniques. Therefore, we propose an integrated data science framework to inform efficient and sustainable RRCC from organic waste based on the review. Overall, the findings from this review can inform practitioners about the effective utilization of various data science methods for real-world implementation of RRCC technologies.

The role of microbiota during chicken manure and pig manure co-composting

Co-composting is an excellent and effective technology for treating livestock manure in which microorganisms play a crucial function. Therefore, this study aimed at investigating the changes of microbial interactions during co-composting. Six different addition ratios of chicken and pig manure were used in composting experiment. The results showed that the co-composting system using 60% chicken manure and 40% pig manure significantly altered the microbial diversity and community structure. In addition, the complexity and tightness of its microbial community network structure reached the maximum, as did the strength of its cooperative and competitive microbial interactions. The higher microbial abundance and microbial interaction have the potential to promote the decomposition and transformation of compost components. Therefore, this study preliminarily revealed the changes of microbial community in co-composting, which provided a theoretical basis for optimizing microbial community interaction in composting systems by mixing different ratios of materials in practice.

Heat balance analysis for self-heating torrefaction of dairy manure using a mathematical model

A self-heating torrefaction system was developed to overcome the difficulties in converting high-moisture biomass to biochar. In self-heating torrefaction, the ventilation rate and ambient pressure must be set properly to initiate the process. However, the minimum temperature at which self-heating begins is unclear because the effects of these operating variables on the heat balance are not theoretically understood. The present report presents a mathematical model for the self-heating of dairy manure based on the heat balance equation. The first step was to estimate the heat source; experimental data showed that the activation energy for the chemical oxidation of dairy manure is 67.5 kJ/mol. Next, the heat balance of feedstock in the process was analyzed. Results revealed that the higher the ambient pressure and the lower the ventilation rate at any given pressure, the lower the temperature at which self-heating is induced. The lowest induction temperature was 71 °C at a ventilation rate of 0.05 L min^-1 kg-AFS^-1 (AFS: ash-free solid). The model also revealed that the ventilation rate significantly affects the heat balance of feedstock and drying rate, suggesting an optimal range for ventilation.

A first-order kinetic model for simulating the aerobic degradation of municipal solid waste

Aerobic degradation models are important tools for investigating the aerobic degradation behavior of municipal solid waste (MSW). In this paper, a first-order kinetic model for aerobic degradation of MSW was developed. The model comprehensively considers the aerobic degradation of five substrates, i.e., holocellulose, non-cellulosic sugars, proteins, lipids and lignin. The proportion ranges of the five substrates are summarized with the recommended values given. The effects of temperature, moisture content, oxygen concentration and free air space (FAS) on the reaction rates are considered, and the effect of settlement is accounted for in the FAS correction function. The reliability of the model was verified by comparing simulations of the aerobic degradation of low food waste content (LFWC-) and high food waste content (HFWC-) MSWs to the literature. Afterwards, a sensitivity analysis was carried out to establish the relative importance of aeration rate (AR), volumetric moisture content (VMC), and temperature. VMC had the greatest influence on the aerobic degradation of LFWC-MSW, followed by temperature and then AR; for HFWC-MSW, temperature was the most important factor, then VMC and last was AR. The degradation ratio of LFWC-MSW can reach 98.0% after 100 days degradation under its optimal conditions (i.e., temperature: 55 °C, VMC: 40%, AR: 0.16 L min^-1 kg^-1 DM), while it is slightly higher as 99.5% for HFWC-MSW under its optimal conditions (i.e., temperature: 55 °C, VMC: 40%, AR: 0.20 L min^-1 kg^-1 DM).

Composting of Organic Solid Waste of Municipal Origin: The Role of Research in Enhancing Its Sustainability

The organic solid waste of municipal origin stands as one of the residual streams of greatest concern: the great amounts continuously produced over time as well as its biochemical and physical characteristics require its proper handling via biological processes, pursuing the recovery of material and/or the generation of energy. At the European level, most of the industrial plants treating the organic fraction of municipal solid waste (OFMSW) rely on composting, which is a well-established and reliable process that is easy to operate in different socio-economic contexts. Nevertheless, when regarded in a life cycle perspective as well as in the view of the principles of circular economy underlying waste management, several issues (e.g., the presence of toxic substances in compost) can be recognized as technical challenges, requiring further studies to identify possible sustainable solutions. This work aims at discussing these challenges and figuring out the state of the art of composting in a circular perspective. Firstly, the main mentioned issues affecting compost quality and process sustainability are briefly reviewed. Next, to promote the effective use of composting in light of the circular economy principles, research experiences are critically presented to highlight the current technical challenges concerning the environmental and health impact reduction and possible scientific perspectives to overcome issues affecting the compost quality. Based on the critical analysis of reviewed studies, it emerged that further research should be aimed at unveiling the hazard potential of emerging contaminants as well as to address the understanding of the mechanisms underlying their potential removal during composting. Moreover, the adoption of a multidisciplinary perspective in the design of research studies may play a key role towards the definition of cost-effective and environmentally friendly strategies to overcome the technical issues affecting the process.

Effects of Functionalized Materials and Bacterial Metabolites on Quality Indicators in Composts

The addition of functionalized materials (biochar, zeolite, and diatomite) and lyophilized metabolic products of Pseudomonas sp. and Bacillus subtilis to composted biomass may bring many technological and environmental benefits. In this study, we verify the effects of biochar, zeolite Na-P1 (Na6Si10Al6O32·12 H2O), diatomite (SiO2_nH2O), and bacterial metabolites on the composting of biomass prepared from poultry litter, corn straw, grass, leonardite, and brown coal. The experimental design included the following treatments: C-biomass without the addition of functionalized materials and bacterial metabolites, CB-biomass with the addition of biochar, CBM-biomass with the addition of biochar and bacterial metabolites, CZ-biomass with the addition of zeolite, CZM-biomass with the addition of zeolite and bacterial metabolites, CD-biomass with the addition of diatomite, and CDM-biomass with the addition of diatomite and bacterial metabolites. Composts were analyzed for enzymatic and respiratory activities, mobility of heavy metals, and the presence of parasites. The results of this study revealed that, among the analyzed functionalized materials, the addition of diatomite to the composted biomass (CD and CDM) resulted in the most effective immobilization of Cd, Zn, Pb, and Cu. Zinc immobilization factors (IFHM) for diatomite-amended composts averaged 30%. For copper, each functionalized material was found to enhance mobilization of the element in bioavailable forms; similar observations were made for lead, except for the compost to which biochar and bacterial metabolites were added (CBM). The determined values of biochemical indicators proved the different effects of the applied functionalized materials and bacterial metabolites on the microbial communities colonizing individual composts. The dehydrogenase activity (DhA) was lower in all combinations as compared with the control, indicating an intensification of the rate of processes in the studied composts. The highest basal respiration (BR) and substrate-induced respiration (SIR) activities were determined in composts with the addition of bacterial metabolites (CBM, CZM, and CDM). The addition of functionalized materials completely inactivated Eimeria sp. in all combinations. In the case of Capillaria sp., complete inactivation was recorded for the combination with zeolite as well as biochar and diatomite without bacterial metabolites (CB, CZ, and CD).

Recent trends and advances in composting and vermicomposting technologies: A review

Composting technologies have come a long way, developing from static heaps and windrow composting to smart, artificial intelligence-assisted reactor composting. While in previous years, much attention has been paid to identifying ideal organic waste streams and suitable co-composting candidates, more recent efforts tried to determine novel process-enhancing supplements. These include various single and mixed microbial cultures, additives, bulking agents, or combinations thereof. However, there is still ample need to fine-tune the composting process in order to reduce its impact on the environment and streamline it with circular economy goals. In this review, we highlight recent advances in integrating mathematical modelling, novel supplements, and reactor designs with (vermi-) composting practices and provide an outlook for future developments. These results should serve as reference point to target adjusting screws for process improvement and provide a guideline for waste management officials and stakeholders.

A novel method to measure air-immobile regions of the composting pile by inverse calculation combined with gas tracer test

Air-immobile regions in composting piles obstruct O₂ mass transport and exacerbate the formation and emission of harmful off-gases. However, effective methods for measuring the parameters of these air-immobile regions are lacking. With quartz sand piles, this study first adjusted the circumstances of a gas tracer test (gas tracer, its injection volume, and chamber type) using the two-region model (TRM). The effects of β (proportional coefficient of gas in the air-mobile region) and ω (mass exchange coefficient) on the breakthrough curves (BTCs) of the gases were then explored. Finally, an inverse calculation method was used to measure the feature parameters of air-immobile regions in two composting piles (temperature-increasing and thermophilic phases) and estimate the O₂ concentrations in different composting piles (50, 100, 200 cm whole height; layers of 50, 100, 200 cm height in a 200-cm high pile). The results showed that the optimal conditions were achieved when 100 mL helium (He) as the gas tracer and a cylinder with a height/diameter ratio of 3 as the chamber were used. With the simulating composting piles, increasing β or ω slowed breakthrough and decreased peak concentration in BTCs of a gas tracer. Tracer-inverse calculation protocol can be used to efficiently estimate the volume ratios of air-immobile regions (φ) and first-order mass transfer coefficient (α), with the values of 39%/46% and 0.001/0.006 min^-1 in the composting piles during temperature-increasing /thermophilic phase. The TRM also predicted the O₂ concentration in the off-gas or air-mobile/immobile regions of the temperature-increasing-phase composting piles.

Application of machine learning algorithms in municipal solid waste management: A mini review

Population growth and the acceleration of urbanization have led to a sharp increase in municipal solid waste production, and researchers have sought to use advanced technology to solve this problem. Machine learning (ML) algorithms are good at modeling complex nonlinear processes and have been gradually adopted to promote municipal solid waste management (MSWM) and help the sustainable development of the environment in the past few years. In this study, more than 200 publications published over the last two decades (2000-2020) were reviewed and analyzed. This paper summarizes the application of ML algorithms in the whole process of MSWM, from waste generation to collection and transportation, to final disposal. Through this comprehensive review, the gaps and future directions of ML application in MSWM are discussed, providing theoretical and practical guidance for follow-up related research.

Biochemical-thermal-hydro-mechanical coupling model for aerobic degradation of landfilled municipal solid waste

Ventilating solid waste landfills with an oxygen supply can effectively accelerate the degradation of waste, achieve rapid stabilization, and realize the sustainable utilization of landfills. Aiming to understand and verify the aerobic degradation process in landfills, this paper proposed a biochemical-thermal-hydro-mechanical coupling model. The model considers aerobic biochemical reactions, dissolved solute migration, heat transport, two-phase flow, and skeleton deformation. The model was verified by comparison with an in-situ experiment at Jinkou landfill. The results showed the model could accurately represent the observed degradation phenomena during the experiment. The modelling results indicated that the rate of temperature increase and peak temperature of the upper layer, which were lower than those of the middle layer, were affected by heat exchange at the landfill surface. The lowest temperatures occurred near the bottom because of high water content and low oxygen concentrations. The high temperature zone migrated out from the injection well during degradation, reflecting the degradation of degradable organic matter associated with oxygen diffusion rates and aerobic degradation reactions. The initial accumulated settlement value was fast, but slowed and finally stabilized. The surface subsidence also developed from the center around the injection well to the surrounding area, and 70% of the total subsidence occurred within 150 days. This newly developed model provides a theoretical framework for analyzing the multi-field coupling of aerobic degradation of landfilled municipal solid waste (MSW).

Application of Optimization and Modeling for the Enhancement of Composting Processes

Composting is a more environmentally friendly and cost-effective alternative to digesting organic waste and turning it into organic fertilizer. It is a biological process in which polymeric waste materials contained in organic waste are biodegraded by fungi and bacteria. Temperature, pH, moisture content, C/N ratio, particle size, nutrient content and oxygen supply all have an impact on the efficiency of the composting process. To achieve optimal composting efficiency, all of these variables and their interactions must be considered. To this end, statistical optimization techniques and mathematical modeling approaches have been developed over the years. In this paper, an overview of optimization and mathematical modeling approaches in the field of composting processes is presented. The advantages and limitations of optimization and mathematical modeling for improving composting processes are also addressed.

Mitigation of carbon and nitrogen losses during pig manure composting: A meta-analysis

Composting is a reliable way to recycle manure for use on croplands in sustainable agriculture. Poor management of the composting process can result in a decrease in the final compost quality and negative environmental impacts. Optimization technologies during composting have varied effects on the mitigation of carbon (C) and nitrogen (N) losses. To determine the feasibility and effectiveness of mitigation options, a meta-analysis was performed based on 68 studies in which C and/or N losses were investigated during pig manure composting. The results indicated that 48.7% of the total C (TC) was lost with 34.8% as CO₂-C and 0.9% as CH₄-C, and 27.5% of the total N (TN) was lost with 17.1% as NH₃-N and 1.5% as N₂O-N. The composting method and bulking agent type obviously influenced the C and N losses. CO₂-C and CH₄-C emission was significantly influenced by the initial C/N ratio and moisture, respectively. At the same time, NH₃-N and N₂O-N emissions were remarkably affected by the initial pH and composting duration, respectively. The results of the meta-analysis showed that TC and TN losses were reduced by 12.4% and 27.5%, respectively. Controlling feedstock, including the C/N ratio and moisture, could be regarded as N conservation technology. Controlling aeration, including turning frequency and ventilation rate, would be reliable in reducing greenhouse gas emissions. Applying additives, especially biochar and superphosphate, was found to be an effective method for synergistically mitigating C and N losses. Therefore, the production of high-quality compost products and minimization of environmental pollution will be achieved by a combination of adjusting the initial substrate properties, controlling the composting process conditions and applying additives.

A Review of Composting Process Models of Organic Solid Waste with a Focus on the Fates of C, N, P, and K

To foster a circular economy in line with compost quality assessment, a deep understanding of the fates of nutrients and carbon in the composting process is essential to achieve the co-benefits of value-added and environmentally friendly objectives. This paper is a review aiming to fill in the knowledge gap about the composting process. Firstly, a systematic screening search and a descriptive analysis were conducted on composting models involving the fates of Carbon (C), Nitrogen (N), Phosphorus (P) and Potassium (K) over the past decade, followed by the development of a checklist to define the gap between the existing models and target models. A review of 22 models in total led to the results that the mainstream models involved the fates of C and N, while only a few models involved P and K as target variables. Most of the models described the laboratory-scale composting process. Mechanism-derived models were relatively complex; however, the application of the fractionation of substrates could contribute to reducing the complexity. Alternatively, data-driven models can help us obtain more accurate predictions and involve the fates of more nutrients, depending on the data volume. Finally, the perspective of developing composting models for the fates of C, N, P, and K was proposed.

Greenhouse gas emissions from inorganic and organic fertilizer production and use: A review of emission factors and their variability

Fertilizers have become an essential part of our global food supply chain and are necessary to sustain our growing population. However, fertilizers can also contribute to greenhouse gas (GHG) emissions, along with other potential nutrient losses in the environment, e.g. through leaching. To reduce this environmental impact, tools such as life cycle assessments and decision support systems are being used to aid in selecting sustainable fertilization scenarios. These scenarios often include organic waste-derived amendments, such as manures, composts and digestates. To produce an accurate assessment and comparison of potential fertilization scenarios, these tools require emission factors (EFs) that are used to estimate GHG emissions and that are an integral part of these analyses. However, such EFs seem to be very variable in nature, thereby often resulting in high uncertainty on the outcomes of the analyses. This review aims to identify ranges and sources of variability in EFs to provide a better understanding of the potential uncertainty on the outcomes, as well as to provide recommendations for selecting EFs for future studies. As such, an extensive review of the literature on GHG emissions from production, storage, transportation and application of synthetic fertilizers (N, P, K), composts, digestates and manures was performed. This paper highlights the high variability that is present in emissions data and confirms the great impact of this uncertainty on the quality and validity of GHG predictions related to fertilizers. Variability in EFs stem from the energy source used for production, operating conditions, storage systems, crop and soil type, soil nutrient content, amount and method of fertilizer application, soil bacterial community, irrigation method, among others. Furthermore, a knowledge gap exists related to EFs for potassium fertilizers and waste valorization (anaerobic digestion/composting) processes. Overall, based on this review, it is recommended to determine EFs on a case by case basis when possible and to use uncertainty analyses as a tool to better understand the impact of EF variability.