Review on the assessment model of nutrient recycling with agricultural residues treatment technologies

doi:10.13287/j.1001-9332.202212.022

Abstract

Abstract: The technology for nutrient resource utilization of agricultural residues is crucial to realizing a circular agricultural economy. The assessment model provides essential support to optimize nutrient recovery and treatment technologies. We specifically summarized research progress in the assessment framework of agricultural residues nutrient recycling technology, assessment models and evaluation indicators, data sources of models and their uncertainty analysis, and the application scale of models. We found that process mathematical models and industrial eco-logy models are the common nutrient flow assessment models. Process mathematical and industrial ecology models differed greatly in terms of the reliability of assessment results and the simulation scale. The former mainly focused at laboratory or pilot scale, with higher accuracy. The latter could achieve multi-scale simulation from microscopic to macroscopic and had higher uncertainty, due to the way its data were obtained. Finally, we provided an outlook on the research on the assessment model of agricultural residues nutrient resource utilisation technology. In order to achieve accurate assessment of waste resource utilisation technology in agricultural production systems at the regional scale, a reliable model framework and database should be established by combining process mathematical models with industrial ecology models. Meanwhile, we should carry out research on model expansion at the geographical scales of factory scale, farm scale, village scale, township scale, and regional scale.

Key words: agricultural waste, composting, anaerobic digestion, process modelling, industrial ecology modelling, nutrient recovery

YANG Zheng, LI Hong-qing, ZHAI Jia-ning, ZHANG Li-hua, NAN Qiong. Review on the assessment model of nutrient recycling with agricultural residues treatment technologies[J]. Chinese Journal of Applied Ecology, 2022, 33(12): 3213-3219.

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