Aspergillus sclerotiorum lipolytic activity and its application in bioremediation of high-fat dairy wastewater environments

Oils and grease (O&G) have low affinity for water and represent a class of pollutants present in the dairy industry. Enzyme-mediated bioremediation using biocatalysts, such as lipases, has shown promising potential in biotechnology, as they are versatile catalysts with high enantioselectivity and regioselectivity and easy availability, being considered a clean technology (white biotechnology). Specially in the treatment of effluents from dairy industries, these enzymes are of particular importance as they specifically hydrolyze O&G. In this context, the objective of this work is to prospect filamentous fungi with the ability to synthesize lipases for application in a high-fat dairy wastewater environment. We identified and characterized the fungal species Aspergillus sclerotiorum as a good lipase producer. Specifically, we observed highest lipolytic activity (20.72 U g⁻¹) after 96 h of fermentation using sunflower seed as substrate. The fungal solid fermented was used in the bioremediation in dairy effluent to reduce O&G. The experiment was done in kinetic from 24 to 168 h and reduced over 90% of the O&G present in the sample after 168 h. Collectively, our work demonstrated the efficiency and applicability of fungal fermented solids in bioremediation and how this process can contribute to a more sustainable wastewater pretreatment, reducing the generation of effluents produced by dairy industries.

     

Emission factors of atmospheric and climatic pollutants from crop residues burning

Biomass burning is a common agricultural practice, because it allows elimination of postharvesting residues; nevertheless, it involves an inefficient combustion process that generates atmospheric pollutants emission, which has implications on health and climate change. This work focuses on the estimation of emission factors (EFs) of PM_2.5, PM₁₀, organic carbon (OC), elemental carbon (EC), carbon monoxide (CO), carbon dioxide (CO₂), and methane (CH₄) of residues from burning alfalfa, barley, beans, cotton, maize, rice, sorghum, and wheat in Mexico. Chemical characteristics of the residues were determined to establish their relationship with EFs, as well as with the modified combustion efficiency (MCE). Essays were carried out in an open combustion chamber with isokinetic sampling, following modified EPA 201-A method. EFs did not present statistical differences among different varieties of the same crop, but were statistically different among different crops, showing that generic values of EFs for all the agricultural residues can introduce significant uncertainties when used for climatic and atmospheric pollutant inventories. EFs of PM_2.5 ranged from 1.19 to 11.30 g kg^?1, and of PM₁₀ from 1.77 to 21.56 g kg^?1. EFs of EC correlated with lignin content, whereas EFs of OC correlated inversely with carbon content. EFs of EC and OC in PM_2.5 ranged from 0.15 to 0.41 g kg^?1 and from 0.33 to 5.29 g kg^?1, respectively, and in PM₁₀, from 0.17 to 0.43 g kg^?1 and from 0.54 to 11.06 g kg^?1. CO₂ represented the largest gaseous emissions volume with 1053.35–1850.82 g kg^?1, whereas the lowest was CH₄ with 1.61–5.59 g kg^?1. CO ranged from 28.85 to 155.71 g kg^?1, correlating inversely with carbon content and MCE. EFs were used to calculate emissions from eight agricultural residues burning in the country during 2016, to know the potential mitigation of climatic and atmospheric pollutants, provided this practice was banned.

Implications: The emission factors of particles, short-lived climatic pollutants, and atmospheric pollutants from the crop residues burning of eight agricultural wastes crops, determined in this study using a standardized method, provides better knowledge of the emissions of those species in Latin America and other developing countries, and can be used as inputs in air quality models and climatic studies. The EFs will allow the development of more accurate inventories of aerosols and gaseous pollutants, which will lead to the design of effective mitigation strategies and planning processes for sustainable agriculture.