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An overview of conventional and emerging aspects of compost: quality indicators for agricultural uses, emerging contaminants and technological innovations
Summary
Researchers reviewed composting technology across conventional and emerging dimensions, noting that while quality standards for heavy metals are established in most countries, emerging contaminants such as microplastics and pharmaceuticals remain largely unregulated in compost certification schemes.
Composting is a well-established technology for the treatment of a wide range of organic wastes and by-products without the production of any residue. It is a key process for the development of the circular economy. The process is well-known, conventional parameters for compost quality are established in most countries, and quality certificate schemes are in operation, based on indicators to prevent soil pollution and to promote soil health. The benefits of compost in soils have been widely recognised. This work highlights the main characteristics of compost important for different agricultural uses: growing medium, soil fertiliser or soil improver. New aspects of compost quality relevant are reviewed. These involve the presence of emerging contaminants of concern, (micro-)plastics, their degradation during composting and compost accumulation and the risk of antibiotic resistance genes (ARGs) spreading through compost use in soils. Composting is able to remove hormones and pharmaceuticals present in biosolids, including up to 96% of fragances (leaving up to 11,200 ng g −1 in compost), as well as the actibacterial tricosan and most of the UV-filters (with the exception of 4–methylbenzylidene camphor, 97% removal). Some veterinary antibiotics can still be found in manure compost (up to 1717.4 μg kg −1 ) and microplastics can generally found in compost, with a wide range of concentrations in biowastes compost. Other aspects of interest nowadays include process conditions: the use of additives, aerobic pre-treatments or certain technological advances such as electric field-assisted aerobic composting. Mathematical models for composting performance and compost quality have been developed to improve the performance and functionality, ensuring the production of homogeneous compost. Machine learning models and algorithms can help to control the process and compost quality and together with Artificial Intelligence can assist the design of decision support tools for composting installations. Finally, social acceptance of the composting process and the product, which is impacted by compost quality, is necessary to promote compost use.