Characteristics of Humification, Functional Enzymes and Bacterial Community Metabolism During Manganese Dioxide-Added Composting of Municipal Sludge DOI
Shihua Zhang,

Liujian Wang,

Bingjie Zhou

и другие.

Опубликована: Янв. 1, 2024

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Язык: Английский

Soil decreases N2O emission and increases TN content during combined composting of wheat straw and cow manure by inhibiting denitrification DOI

Ruixiao Yan,

Wu H,

Xinya Yang

и другие.

Chemical Engineering Journal, Год журнала: 2023, Номер 477, С. 147306 - 147306

Опубликована: Ноя. 12, 2023

Язык: Английский

Процитировано

22

Contribution of zeolite to nitrogen retention in chicken manure and straw compost: Reduction of NH3 and N2O emissions and increase of nitrate DOI
Bing Wang, Peng Zhang,

Xu Guo

и другие.

Bioresource Technology, Год журнала: 2023, Номер 391, С. 129981 - 129981

Опубликована: Ноя. 4, 2023

Язык: Английский

Процитировано

17

The community succession mechanisms and interactive dynamics of microorganisms under high salinity and alkalinity conditions during composting DOI
Qingyu Liu, Yuxin Wang,

Haoqun Sha

и другие.

Journal of Environmental Management, Год журнала: 2025, Номер 379, С. 124881 - 124881

Опубликована: Март 10, 2025

Язык: Английский

Процитировано

0

Biostimulants accelerate lignin degradation in semi-aerobic landfills, assisting overall lifecycle management and sustainable development of landfills DOI
Mingxing Li, Hui Jiang,

Ruiding Li

и другие.

Journal of Cleaner Production, Год журнала: 2025, Номер unknown, С. 145267 - 145267

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

Ferrous salts accelerate humification and reduced carbon emissions during the co-composting of hoggery slurry and wheat husks: New insights into their biotic and abiotic functions and mechanisms DOI
Yang Wang,

Guorong Yi,

Wanqiang Zhang

и другие.

Chemical Engineering Journal, Год журнала: 2025, Номер unknown, С. 162570 - 162570

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Mechanisms for enhanced lignin humification with reduced organic matter loss by goethite in biogas residue composting DOI
Caiqin Wang, Bing Yao, Jian Wei

и другие.

Bioresource Technology, Год журнала: 2023, Номер 389, С. 129795 - 129795

Опубликована: Окт. 1, 2023

Язык: Английский

Процитировано

11

A new strategy to increase compost carbon fixation: Shell powder reduced gaseous pollutant emissions in co-composting of cow manure and sawdust DOI

Liangcai Ma,

Qunliang Li

Journal of environmental chemical engineering, Год журнала: 2024, Номер 12(3), С. 112916 - 112916

Опубликована: Апрель 29, 2024

Язык: Английский

Процитировано

3

Characteristics of humification, functional enzymes and bacterial community metabolism during manganese dioxide-added composting of municipal sludge DOI
Shihua Zhang,

Liujian Wang,

Bingjie Zhou

и другие.

Environmental Research, Год журнала: 2024, Номер 252, С. 119151 - 119151

Опубликована: Май 14, 2024

Язык: Английский

Процитировано

3

Machine Learning Approach for Predicting Hydrothermal Liquefaction of Lignocellulosic Biomass DOI
Tossapon Katongtung,

Sanphawat Phromphithak,

Thossaporn Onsree

и другие.

BioEnergy Research, Год журнала: 2024, Номер 17(4), С. 2246 - 2258

Опубликована: Май 24, 2024

Язык: Английский

Процитировано

3

Optimizing the Composting Process Emissions – Process Kinetics and Artificial Intelligence Approach DOI Open Access
Joanna Rosik, Sylwia Stegenta-Dąbrowska

Опубликована: Апрель 28, 2024

Although composting has many advantages in the treatment of organic waste, there are still problems and challenges associated with emissions, like NH3, VOCs, H2S, as well greenhouse gases such CO2, CH4, N2O. One promising approach to enhancing conditions is used novel analytical methods bad on artificial intelligence. To predict optimize emissions (CO, NH3) during process kinetics thought mathematical models (MM) machine learning (ML) were utilized. Data about everyday from laboratory compost’s biochar different incubation (50, 60, 70 °C) doses (0, 3, 6, 9, 12, 15% d.m.) for MM ML selections training. not been very effective predicting (R2 0.1 - 0.9), while acritical neural network (ANN, Bayesian Regularized Neural Network; R2 accuracy CO:0,71, CO2:0,81, NH3:0,95, H2S:0,72)) decision tree (DT, RPART; CO:0,693, CO2:0,80, NH3:0,93, H2S:0,65) have demonstrated satisfactory results. For first time CO H2S demonstrated. Further research a semi-scale field study needed improve developments models.

Язык: Английский

Процитировано

2