Publications by authors named "He Pinjing"

Deep dewatering is crucial for effectively reducing the volume of organic waste and facilitating its downstream transportation and disposal. An in-depth understanding of the occurrence states, composition, and morphological characteristics of moisture in organic waste is the basis for optimizing the dewatering process, improving dewatering efficiency, and reducing energy consumption. Given the common problems of time-consuming, low sensitivity, and poor parallelism of traditional methods, this work reviews the advanced in-situ analysis methods for moisture distribution of organic waste.

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The complex composition of solid waste leads to the variability of flue gas emissions during its incineration, which poses a challenge to the stable operation of incineration and pollution control systems. To address this problem, the study explored a new method to predict the concentrations of flue gas pollutants during incineration based on the composition of mixed solid waste using machine learning. Through comprehensive model interpretation and analysis, the important influence of waste composition characteristics on the generation of flue gas pollutants during incineration was deeply explored.

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Article Synopsis
  • This study analyzed 1.5 years of data from four full-scale dry anaerobic digesters treating kitchen food waste to identify the best machine learning model for predicting biogas production.
  • The CatBoost algorithm outperformed others, achieving high prediction accuracy for biogas and VFA/ALK ratios, with accuracies ranging from 0.604 to 0.915 and 0.618 to 0.768, respectively.
  • Key factors influencing biogas production were found to be the amount of biomass entering the digester, while Chemical Oxygen Demand (COD) and Free Ammonia Nitrogen (FAN) were significant for the VFA/ALK ratio, together affecting nearly 50% of the results.
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Article Synopsis
  • Researchers are exploring the use of near-infrared hyperspectral imaging (HSI) combined with machine learning to analyze solid waste more efficiently than traditional methods, addressing challenges like contamination from leachates.* -
  • The study introduces hyperspectral unmixing (HU) techniques to identify and quantify different components of solid waste, focusing on how substances like water and oil affect spectral readings.* -
  • The methods developed show promising results in accurately estimating the compositions of solid waste, with validation metrics indicating close alignment with actual components, while also demonstrating the capacity to analyze complex mixed spectroscopic images.*
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This study presents a comprehensive analysis of greenhouse gas (GHG) emissions associated with waste transfer and transport, incorporating derived leachate treatment-a factor often overlooked in existing research. Employing an integration model of life cycle assessment and a vehicle routing problem (VRP) methods, we evaluated the GHG reduction potential of waste transfer and transport system. Two Chinese counties with different topographies and demographics were selected, yielding 80 scenarios that factored in waste source separation as well as vehicle capacity, energy sources, and routes.

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Methods used to monitor anaerobic digestion (AD) indicators are commonly based on wet chemical analyses, which consume time and materials. In addition, physical disturbances, such as floating granules (FGs), must be monitored manually. In this study, we present an eco-friendly, high-throughput methodology that uses near-infrared hyperspectral imaging (NIR-HSI) to build a machine-learning model for characterizing the chemical composition of the digestate and a target detection algorithm for identifying FGs.

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For the resource recovery of biomass waste, it is a challenge to simultaneously remove micro-/nano-plastics pollution but preserve organic resources. Wet oxidation is a promising technology for valorization of organic wastes through thermal hydrolysis and oxidation. This might in turn result in the degradation of microplastics in the presence of oxygen and high temperatures.

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Article Synopsis
  • The study focuses on improving methods for identifying and characterizing both colored and colorless plastic fragments in the environment, addressing the gap in existing research that often neglects colorless fragments.
  • The research utilized near-infrared spectroscopy and various analytical models, finding that partial least squares-discriminant analysis (PLS-DA) was the most effective in classifying plastic types with fewer misclassifications.
  • A new two-stage modeling approach was introduced, allowing for over 99% accuracy in identifying colorless fragments, even in complex backgrounds.
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A regular tetrahedron model was established to pierce the fractionation of dissolved organic matter (DOM) among quaternary components by using high-resolution mass spectrometry. The model can stereoscopically visualize molecular formulas of DOM to show the preference to each component according to the position in a regular tetrahedron. A classification method was subsequently developed to divide molecular formulas into 15 categories related to fractionation ratios, the relative change of which was demonstrated to be convergent with the uncertainty of mass peak area.

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Poly(butylene adipate-co-terephthalate) (PBAT) is a biodegradable plastic that is difficult to degrade under both mesophilic and thermophilic anaerobic conditions. In this study, the impact of the thermo-alkaline pretreatment (48 h, 70 °C, 1 % w/v NaOH) on the anaerobic degradation (AD) of PBAT, poly(lactic acid) (PLA) and PBAT/PLA blended plastics was investigated. Under mesophilic conditions, pretreatment only improved the methane yield of PBAT/PLA/starch plastic (100 days, 51 and 34 NmL/g VS for the treated and original plastics, respectively).

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Plastic pollution pervades natural environments and wildlife. Consequently, high-throughput detection methods for plastic debris are urgently needed. A novel method was developed to detect plastic debris larger than 0.

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Revealing the role of functional redundancy is of great importance considering its key role in maintaining the stability of microbial ecosystems in response to various disturbances. However, experimental evidence on this point is still lacking due to the difficulty in "manipulating" and depicting the degree of redundancy. In this study, manipulative experiments of functional redundancy were conducted by adopting the mixed inoculation strategy to evaluate its role in engineered anaerobic digestion systems under ammonium inhibition conditions.

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Biological treatment is one of the most promising efficient, low-carbon and affordable approaches for the treatment of recalcitrantly degradable wastewater, such as landfill leachate. However, even the macroscopic molecular level analysis of dissolved organic matter (DOM) is limiting to the enhancement of biological treatment efficacy, and there is an urgent need for deeper exploration of DOM to gain insights into the key constraining substances. In the present study targeting at piercing leachate organic at molecular level, nitrogen-containing dissolved organic matter (DOM) was identified to be the bottleneck that govern the biotreatment potential.

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Two novel biogas upgrading strategies that recover high-value chemicals or CO liquid fertilizer from biogas besides biomethane were evaluated from the view of global warming potential (GWP) through life cycle assessment in comparison with conventional approaches. Results show that the scenarios producing biomethane with nano calcium carbonate or CO liquid fertilizer from biogas present significantly lower GWP (-3.4 kgCO-eq/Nm-biogas and -4.

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With the implementation of municipal solid waste source segregation, the enormous sorted biogenic waste has become an issue that needs to be seriously considered. Anaerobic digestion, which can produce biogas and extract floating oil for biodiesel production, is the most prevalent treatment in China for waste management and greenhouse gas (GHG) emissions reduction, in accordance with Sustainable Development Goal 13 of the United Nations. Herein, a large-scale biogas plant with a capacity of 1000 tonnes of biogenic waste (400 tonnes of restaurant biogenic waste and 600 tonnes of kitchen biogenic waste) per day was investigated onsite using material flow analysis, and the parts of the biogas plant were thoroughly analyzed, especially the pretreatment system for biogenic waste impurity removal and homogenization.

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The significant increase in the demand for biomass waste treatment after garbage classification has led to housefly larvae treatment becoming an attractive treatment option. It can provide a source of protein while treating biomass waste, which means that nutrients can be returned to the natural food chain. However, the performance of this technology in terms of its environmental impacts is still unclear, particularly with regards to global warming potential (GWP).

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Poly (lactic acid) (PLA) and Poly(butylene adipate-co-terephthalate) (PBAT) are two of biodegradable plastics with the highest production capacities in 2021. Bioplastic waste management can be easily integrated with organic waste management, especially when bioplastics are used as food packaging material, since they are potentially biodegradable. The aim of this study was to assess the biodegradability of biodegradable polymer-coated paper (BPCP) and bioplastic bags made from PBAT/PLA blend during mesophilic and thermophilic anaerobic digestion (AD) and to reveal the changes in the physicochemical properties of the bioplastics.

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Diverse factors influence biogas production, such as material properties, testing conditions, reporting methods and other additional processing techniques. This complexity makes it difficult to compare biochemical methane potential (BMP) data, replicate experiments' results, and improve efficiencies associated with engineering applications. This study has taken preliminary attempts to build a sliced and structured BMP database, but optimizing the organization of data information and collecting more comprehensive and manually checked data information to cope with the increasing richness of the BMP test content.

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Bioaugmentation shows promise in mitigating ammonia-induced microbial inhibition in anaerobic digestion processes. However, the advanced technical requirements and high costs associated with pure strain cultivation, as well as the time-consuming and labor-intensive process of domesticating consortia, present challenges for industrial applications. Herein, the efficacy of bioaugmentation with nondomesticated mixed microbial consortia was evaluated, which resulted in a significant methane production improvement of 5.

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Halogenated organic compounds in wastewater are persistent and bioaccumulative contaminants of great concern, but few are known at the molecular level. Herein, we focus on nontarget screening of halogenated dissolved organic matter (DOM) in highly concentrated organic matrices of waste leachates and their concentrates. Solid-phase extraction (SPE) was optimized before capturing halogenated signatures via HaloSeeker 2.

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Fenton is one of the most promising processes for the removal of dissolved organic matter (DOM). It has always been highly suspected that derived-DOM would be generated during Fenton reaction, but there is lack of direct evidence at the molecular level. The present study explored the molecular properties of the derived-DOM of five common Fenton technologies for degradation of nine landfill organics including leachates and concentrates based on UPLC Orbitrap MS/MS analysis.

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Food waste management is an important global issue, and anaerobic digestion (AD) is a sustainable technology for treating food waste and developing a circular economy. Odor and health problems in AD plants have drawn increasing public attention. Therefore, this study investigated the odor characteristics and health risks in different workshops of food waste AD plants.

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Background: The interaction among microorganisms in the anaerobic digestion of food waste (ADFW) reactors lead to the degradation of organics and the recycling of energy. Viruses are an important component of the microorganisms involved in ADFW, but are rarely investigated. Furthermore, little is known about how viruses affect methanogenesis.

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The importance and urgency of domestic solid waste (DSW) source segregation in universities is self-evident. Although many universities have carried out waste management, however, a comprehensive summary for successful implementation work of DSW segregation is lacking. This study summarizes the mechanism of DSW segregation in Chinese university based on questionnaire survey, on-site inquiry and sampling analysis in a comprehensive university in Shanghai.

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The wide application of anaerobic digestion (AD) technology is limited by process fluctuations. Thus, process monitoring based on screening state parameters as early warning indicators (EWI) is a top priority for AD facilities. However, predicting anaerobic digester stability based on such indicators is difficult, and their threshold values are uncertain, case-specific, and sometimes produce conflicting results.

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