TY - JOUR
T1 - Machine learning and computational chemistry to improve biochar fertilizers
T2 - a review
AU - Osman, Ahmed I.
AU - Zhang, Yubing
AU - Lai, Zhi Ying
AU - Rashwan, Ahmed K.
AU - Farghali, Mohamed
AU - Ahmed, Ashour A.
AU - Liu, Yunfei
AU - Fang, Bingbing
AU - Chen, Zhonghao
AU - Al-Fatesh, Ahmed
AU - Rooney, David W.
AU - Yiin, Chung Loong
AU - Yap, Pow Seng
N1 - Funding Information:
Dr. Ahmed I. Osman and Prof. David W. Rooney wish to acknowledge the support of The Bryden Centre project (Project ID VA5048), which was awarded by The European Union’s INTERREG VA Programme, managed by the Special EU Programmes Body (SEUPB), with match funding provided by the Department for the Economy in Northern Ireland and the Department of Business, Enterprise and Innovation in the Republic of Ireland. Dr. Chung Loong Yiin would also like to acknowledge the technical and financial support from Universiti Malaysia Sarawak (UNIMAS). Dr. Ashour A. Ahmed gratefully acknowledges the financial support provided by the InnoSoilPhos project, funded by the German Federal Ministry of Education and Research (BMBF) in the frame of the BonaRes program.
Publisher Copyright:
© 2023, The Author(s).
PY - 2023
Y1 - 2023
N2 - Traditional fertilizers are highly inefficient, with a major loss of nutrients and associated pollution. Alternatively, biochar loaded with phosphorous is a sustainable fertilizer that improves soil structure, stores carbon in soils, and provides plant nutrients in the long run, yet most biochars are not optimal because mechanisms ruling biochar properties are poorly known. This issue can be solved by recent developments in machine learning and computational chemistry. Here we review phosphorus-loaded biochar with emphasis on computational chemistry, machine learning, organic acids, drawbacks of classical fertilizers, biochar production, phosphorus loading, and mechanisms of phosphorous release. Modeling techniques allow for deciphering the influence of individual variables on biochar, employing various supervised learning models tailored to different biochar types. Computational chemistry provides knowledge on factors that control phosphorus binding, e.g., the type of phosphorus compound, soil constituents, mineral surfaces, binding motifs, water, solution pH, and redox potential. Phosphorus release from biochar is controlled by coexisting anions, pH, adsorbent dosage, initial phosphorus concentration, and temperature. Pyrolysis temperatures below 600 °C enhance functional group retention, while temperatures below 450 °C increase plant-available phosphorus. Lower pH values promote phosphorus release, while higher pH values hinder it. Physical modifications, such as increasing surface area and pore volume, can maximize the adsorption capacity of phosphorus-loaded biochar. Furthermore, the type of organic acid affects phosphorus release, with low molecular weight organic acids being advantageous for soil utilization. Lastly, biochar-based fertilizers release nutrients 2–4 times slower than conventional fertilizers.
AB - Traditional fertilizers are highly inefficient, with a major loss of nutrients and associated pollution. Alternatively, biochar loaded with phosphorous is a sustainable fertilizer that improves soil structure, stores carbon in soils, and provides plant nutrients in the long run, yet most biochars are not optimal because mechanisms ruling biochar properties are poorly known. This issue can be solved by recent developments in machine learning and computational chemistry. Here we review phosphorus-loaded biochar with emphasis on computational chemistry, machine learning, organic acids, drawbacks of classical fertilizers, biochar production, phosphorus loading, and mechanisms of phosphorous release. Modeling techniques allow for deciphering the influence of individual variables on biochar, employing various supervised learning models tailored to different biochar types. Computational chemistry provides knowledge on factors that control phosphorus binding, e.g., the type of phosphorus compound, soil constituents, mineral surfaces, binding motifs, water, solution pH, and redox potential. Phosphorus release from biochar is controlled by coexisting anions, pH, adsorbent dosage, initial phosphorus concentration, and temperature. Pyrolysis temperatures below 600 °C enhance functional group retention, while temperatures below 450 °C increase plant-available phosphorus. Lower pH values promote phosphorus release, while higher pH values hinder it. Physical modifications, such as increasing surface area and pore volume, can maximize the adsorption capacity of phosphorus-loaded biochar. Furthermore, the type of organic acid affects phosphorus release, with low molecular weight organic acids being advantageous for soil utilization. Lastly, biochar-based fertilizers release nutrients 2–4 times slower than conventional fertilizers.
KW - Biochar-based fertilizer
KW - Climate change
KW - Machine learning and computational chemistry
KW - Organic acids
KW - Phosphorus bioavailability
KW - Phosphorus-loaded biochar
UR - http://www.scopus.com/inward/record.url?scp=85168118834&partnerID=8YFLogxK
U2 - 10.1007/s10311-023-01631-0
DO - 10.1007/s10311-023-01631-0
M3 - Review article
AN - SCOPUS:85168118834
SN - 1610-3653
VL - 21
SP - 3159
EP - 3244
JO - Environmental Chemistry Letters
JF - Environmental Chemistry Letters
IS - 6
ER -