Optimization of the proportion of multi-component rural solid wastes in mixed composting using a simplex centroid design

Systematic development of a highly efficient cell factory for 5-aminolevulinic acid production

The versatile applications of 5-aminolevulinic acid (5-ALA) across the fields of agriculture, livestock, and medicine necessitate a cost-efficient biomanufacturing process. In this study, we achieved the economic viability of biomanufacturing this compound through a systematic engineering framework. First, we obtained a 5-ALA synthase (ALAS) with superior performance by exploring its natural diversity with divergent evolution. Subsequently, using a genome-scale model, we identified and modified four key targets from distinct pathways in Escherichia coli, resulting in a final enhancement of 5-ALA titers up to 21.82 g/l in a 5-l bioreactor. Furthermore, recognizing that an imbalance of redox equivalents hindered further titer improvement, we developed a dynamic control system that effectively balances redox status and carbon flux. Ultimately, we collaboratively optimized the artificial redox homeostasis system at the transcription level with other cofactors at the feeding level, demonstrating the highest recorded performance to date with a titer of 63.39 g/l for the biomanufacturing of 5-ALA.

Assessing the suitability of municipal sewage sludge and coconut bran as breeding medium for Oryza sativa L. seedlings and developing a standardized substrate

The utilization of organic solid waste (OSW) for preparing standardized seedling substrates is a main challenge due to its temporal and spatial variability. This study aims to form models based on data from the literature and validate them through experiments to explore a standardized seedling substrate. The typical OSW in Hainan Province, including municipal sewage sludge (MSS), coconut bran (CB), seaweed mud (SM), and municipal sewage sludge biochar (MSSB), was used as raw material. A series of six mixing ratios was tested, namely: T1 (0% MSS: 90% CB), T2 (10% MSS: 80% CB), T3 (30% MSS: 60% CB), T4 (50% MSS: 40% CB), T5 (70% MSS: 20% CB), and T6 (90% MSS: 0% CB). SM and MSSB were added as amendment materials at 5% (w/w) for each treatment. The physicochemical properties of substrates, agronomic traits of rice seedlings and microbial diversity were analyzed. The results showed that the four kinds of OSW played an active role in providing rich sources of nutrients. The dry weight of the above-ground part was 2.98 times greater in T3 than that of the commercial substrate. Furthermore, the microbial analysis showed a higher abundance of Actinobacteria in T3, representing the stability of the composted products. Finally, the successful fitting of the results with the linear regression models could establish relationship equations between the physicochemical properties of the substrate and the growth characteristics of seedlings. The relevant parameters suitable for the growth of rice seedlings were as follows: pH (6.46-7.01), EC (less than 2.12 mS cm-1), DD (0.13-0.16 g cm-3), and TPS (65.68-82.73%). This study proposed relevant parameters and models for standardization of seedling substrate, which would contribute to ensuring the quality of seedlings and OSW resource utilization.

Prediction of composting maturity and identification of critical parameters for green waste compost using machine learning

Ensuring the maturity of green waste compost is crucial to composting processes and quality control of compost products. However, accurate prediction of green waste compost maturity remains a challenge, as there are limited computational methods available. This study aimed to address this issue by employing four machine learning models to predict two indicators of green waste compost maturity: seed germination index (GI) and T value. The four models were compared, and the Extra Trees algorithm exhibited the highest prediction accuracy with R2 values of 0.928 for GI and 0.957 for T value. To identify the interactions between critical parameters and compost maturity, The Pearson correlation matrix and Shapley Additive exPlanations (SHAP) analysis were conducted. Furthermore, the accuracy of the models was validated through compost validation experiments. These findings highlight the potential of applying machine learning algorithms to predict green waste compost maturity and optimise process regulation.

Trends in the management of organic swine farm waste by composting: A systematic review

Pig farming contributes to the economic development of nations and supplies human food demand; however, it generates a large amount of organic waste which, if not managed properly, becomes a risk to the environment and human and animal health. Considering the relevance of composting and its usefulness for the use of waste, this study aimed to determine the global trends in the management of composting manure, mortality and other organic waste produced on pig farms over the last five years (2017-2022). Systematic search involved four databases: ISI Web of Science, Scopus, Ebsco and Scielo. Of the total findings, 56 articles were included in the review, further classified into 14 categories for their respective analysis: co-substrates/additives, microbial communities, antibiotic resistance, heavy metals, polycyclic aromatic hydrocarbons, microbiological/parasitological quality, phytopathogens, nitrogen transformation, bioinoculants, comparison/combination with other waste management techniques, factors affecting composting, swine mortality and plant growth promotion/phytotoxicity. The review exemplified the importance of swine mortality composting as an alternative for organic matter management in pig farms, considering that the process also includes manure, vegetable waste and wood chips, among others. Controlled factors throughout the process are a requirement to obtain a stable product with physicochemical and microbiological quality that complies with national and international regulations and that will be useful and safe for application on crops, ensuring environmental, animal, and human health.

Physicochemical properties and risk assessment of perishable waste primary products

Fertilization has become one of the most important ways to recycle perishable waste. In order to reveal the effect of the nutrient of the perishable waste primary products on the market and the possible impact of their application, 136 perishable waste primary products were sampled in nine cities in Zhejiang province, China. The result shows that these products have high nutrient content (average nutrient content was 5.00%). However, the conductivity (7.19 mS/cm) total soluble salt content (12.07%), and grease content (5.99%) were too high. The excessive salt and grease may cause harm to soil and crops, and become the main limiting factors for the fertilizer utilization of perishable waste. Heavy metal content of most of the samples met current commercial organic fertilizer standards, except that lead and chromium content of some samples exceeded the limit standard. Toluene, ethylbenzene, m & p-xylene were generally detected in the samples. These toxic and harmful substances have brought risks to the safe use of perishable waste into fertilizers.

Employing salt-tolerant bacteria Serratia marcescens subsp. SLS for biodegradation of oily kitchen waste

The high oil and salt content of kitchen waste (KW) inhibit bioconversion and humus production. To efficiently degrade oily kitchen waste (OKW), a halotolerant bacterial strain, Serratia marcescens subsp. SLS which could transform various animal fats and vegetable oils, was isolated from KW compost. Its identification, phylogenetic analysis, lipase activity assays, and oil degradation in liquid medium were assessed, and then it was employed to carry out a simulated OKW composting experiment. In liquid medium, the 24 h degradation rate of mixed oils (soybean oil: peanut oil: olive oil: lard = 1:1:1:1, v/v/v/v) was up to 87.37% at 30 °C, pH 7.0, 280 rpm, 2% oil concentration and 3% NaCl concentration. The ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS) method demonstrated that the mechanism of SLS strain metabolizing long-chain triglycerides (TAGs) (C53-C60), especially the biodegradation of TAG (C18:3/C18:3/C18:3) by the strain can reach more than 90%. Degradation of 5, 10, 15% concentrations of total mixed oil were also calculated to be 64.57, 71.25, 67.99% respectively after a simulated composting duration of 15 days. The results suggest that the isolated strain of S. marcescens subsp. SLS is suitable for OKW bioremediation in high NaCl concentration within a reasonably short period of time. The findings introduced a salt-tolerant and oil-degrading bacteria, providing insights into the mechanism of oil biodegradation and offering new avenues of study for OKW compost and oily wastewater treatment.

Total petroleum hydrocarbons and influencing factors in co-composting of rural sewage sludge and organic solid wastes

Co-composting is an efficient strategy for collaborative disposal of multiple organic wastes in rural areas. In this study, we explored the co-composting of rural sewage sludge and other organic solid wastes (corn stalks and kitchen waste), with a focus on the variation of total petroleum hydrocarbons (TPH) during this process. 12% corn-derived biochar was applied in the composting (BC), with no additives applied as the control treatment (CK). The TPH contents of piles after composting ranged from 0.70 to 0.74 mg/g, with overall removal efficiencies of 35.6% and 61.1% for CK and BC, respectively. The results indicate that the addition of 12% biochar increased the rate of TPH degradation and accelerated the degradation process. 16s rDNA high-throughput sequencing was applied to investigate the biodiversity and bacterial community succession during the composting process. Diverse bacterial communities with TPH degradation functions were observed in the composting process, including Acinetobacter, Flavobacterium, Paenibacillus, Pseudomonas, and Bacillus spp. These functional bacteria synergistically degraded TPH, with cooperative behavior dominating during composting. Biochar amendment enhanced the microbial activity and effectively promoted the biodegradation of TPH. The physicochemical properties of the compost piles, including environmental factors (pH and temperature), nutrients (nitrogen, phosphorus, potassium), and humic substances produced in composting (humic acids and fulvic acids), directly and indirectly affected the variation in TPH contents. In conclusion, this work illustrates the variation in TPH content and associated influencing factors during co-composting of rural organic solid wastes, providing valuable guidance toward the further optimization of rural organic waste management.

Design and operation of a fixed-bed pyrolysis-gasification-combustion pilot plant for rural solid waste disposal

This paper is to explore the use of rural solid waste (RSW) for pyrolysis-gasification-combustion in pilot plant scale aiming at sustainable management of rural waste in remote areas. Based on the experimental data obtained during pilot scale operation, the temperature in the furnace needs to be kept at least at 600 °C through analyzing the pyrolysis weight loss of the main combustibles in the RSW. Besides, the effects of the air supply method and ventilation rate on the pilot plant performance were explored. Results indicate that the active air supply method positively contributes to the performance of the pilot plant. The plant processed 10 t RSW/d, producing 12.82 g/Nm³ of tar with 1.75 % of ash. This study confirms the feasibility of the pilot plant for RSW disposal and provides theoretical support for the optimization of pilot plant operation.

Impact of composting factors on the biodegradation of lignin in Eichhornia crassipes (water hyacinth): A response surface methodological (RSM) investigation

Water hyacinth (Eichhornia crassipes) is a hydrophyte weed that causes havoc in the aquatic ecosystem as an invasive plant that can obstruct waterways and bring about nutrient imbalance. This study aims to address how this invasive hydrophyte can be physically harvested and biochemically transformed into a bioproduct that can enhance the restoration of damaged soil. Biocomposting, a low-cost biotechnological technique, was designed to degrade the lignocellulosic Eichhornia crassipes biomass and transform it into a valuable bioproduct. The process used response surface methodology (RSM) to investigate the aggregate effect of moisture content, turning frequency, and microbial isolate (Chitinophaga terrae) inoculum size on the breakdown of lignin over 21 days. The moisture content (A), (45, 55, 65) % v/w, inoculum size (B), (5, 7.5, 10)% v/v, and turning frequency (C), (1, 3, 5) days were considered independent variables, while percentage lignin degradation was considered a response variable. The optimal conditions for lignin breakdown were 65.7 percent (v/w) moisture, 7.5 percent (v/v) inoculum concentration, and 5-day interval turning. The R2 score of 0.9733 demonstrates the model's integrity and reliability. Thus, the RSM approach resulted in a fine grain dark brown Nutri-compost that proved effective in enhancing soil fertility. This procedure is recommended for a scale-up process where large quantities of the hydrophyte could be treated for conversion into Nutri compost.

Accumulation Characteristics and Pollution Evaluation of Soil Heavy Metals in Different Land Use Types: Study on the Whole Region of Tianjin

Heavy metal pollution in soil has received much attention in recent decades. Many studies have analyzed the interaction between specific soil quality and soil heavy metal pollution. However, there is little information about the pollution status, spatial distribution and pollution sources of heavy metals in the province of Tianjin. In this paper, the distribution characteristics and pollution sources of heavy metals in soil were studied by means of the surface soil of Tianjin, as the study area and object, conducted in combination with land use types, using multiple data analysis and multivariate statistics, while the pollution levels were evaluated by various indices. The results showed the mean contents of the seven heavy metals of the studied elements followed an increasing order of Cd (0.15 mg/kg) < As (11.9 mg/kg) < Cu (24.3 mg/kg) = Pb (24.3 mg/kg) < Ni (27.9 mg/kg) < Cr (70.7 mg/kg) < Zn (79.1 mg/kg). The median values of Cr and Ni were lower than the background values and did not exceed the screening values at the points, and the median values of Cu, Zn and Pb were close to the background values, while the median contents of As and Cd were higher than the background values. The highest accumulation of heavy metals was found in grassland, and the coefficient of variation of heavy metal contents were higher in garden land, industrial and mining storage land, residential land and transportation land, indicating that the soil heavy metal contents under these land use types were more significantly disturbed by human factors. The evaluation results of the ground accumulation index method showed that the soil in Tianjin was free of pollution, except for Cd, which was at the non-polluted to moderately polluted level. The Nemero integrated pollution index evaluation method and the pollution load index evaluation method together showed that the integrated pollution levels of heavy metals in Tianjin soils were both at no pollution level/safety level. Apart from Cd and As, which were not correlated, the other heavy metals were correlated with each other two by two. Cd, Pb and Zn were the main pollution contributors from traffic, industry and other anthropogenic factors, while Cr and Ni were the main pollution contributors from soil parent material, and Cu was the main pollution contributor from mining and metal smelting. In addition, As was presumed to be the main source of pollution contribution from agriculture and surface runoff.

Full-Scale of a Compost Process Using Swine Manure, Human Feces, and Rice Straw as Feedstock

Regarding the composting of rural waste, numerous studies either addressed the composting of a single waste component or were conducted at a laboratory/pilot scale. However, far less is known about the mixed composting effect of multi-component rural waste on a large scale. Here, we examined nutrient transformation, maturity degree of decomposition, and succession of microbial communities in large-scale (1,000 kg mixed waste) compost of multi-component wastes previously optimized by response models. The results showed that multi-component compost can achieve the requirement of maturity and exhibit a higher nutritional value in actual compost. It is worth noting that the mixed compost effectively removed pathogenic fungi, in which almost no pathogenic fungi were detected, and only two pathogenic bacteria regrown in the cooling and maturation stages. Structural equation models revealed that the maturity (germination index and the ratio of ammonium to nitrate) of the product was directly influenced by compost properties (electrical conductivity, pH, total organic carbon, moisture, temperature, and total nitrogen) compared with enzymes (cellulase, urease, and polyphenol oxidase) and microbial communities. Moreover, higher contents of total phosphorus, nitrate-nitrogen, and total potassium were conducive to improving compost maturity, whereas relatively lower values of moisture and pH were more advantageous. In addition, compost properties manifested a remarkable indirect effect on maturity by affecting the fungal community (Penicillium and Mycothermus). Collectively, this evidence implies that mixed compost of multi-component rural waste is feasible, and its efficacy can be applied in practical applications. This study provides a solution for the comprehensive treatment and utilization of rural waste.

Variation and factors on heavy metal speciation during co-composting of rural sewage sludge and typical rural organic solid waste

In this study, a co-composting of rural organic solid waste (rural sewage sludge, kitchen waste and corn stalks) was conducted to analyze the variation of heavy metals (As, Cu, Cr, Ni, Pb, Hg, and Zn) and their major influencing factors. During composting, significant changes were observed in the total contents of heavy metals (p < 0.01): the total concentrations of As, Cu, Hg, Pb and Zn increased by 7.5%, 54.1%, 26.3%, 15.8%, and 34.2%, whereas that of Cr and Ni decreased by 71.3% and 33.4%, respectively. Heavy metals were mainly bound to the oxidizable and residual fractions. Spearman and Redundancy analysis (RDA) indicated that substances were significantly correlated with the changes in speciation of heavy metals, among all the factors, while pH and temperature were the dominating environmental influencing parameters. Several metal-resistant bacterial genera (Pseudomonas, Paenibacillus, Bacillus, Acinetobacter, Desulfovibrio, and Ochrobactrum, etc) were observed, with significant explanatory capacity for the changes in heavy metals. Composting showed a poor effect on heavy metal passivation, except for that of As. After composting, the heavy metal contents were consistent with the application standards. The evaluation of potential ecological risk showed a high cumulative ecological risk (336.9) of heavy metals. This study provides technical support and practical information for the disposal and safe recycling for rural organic solid waste.

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.