Trends and challenges in the valorization of kitchen waste to polyhydroxyalkanoates

Amino acids as bio-organocatalysts in ring-opening copolymerization for eco-friendly synthesis of biobased oligomers from vegetable oils

Herein, we present an innovative synthetic approach for producing a diverse set of biobased oligomers. This method begins with olive oil and employs a wide variety of commercially available amino acids (AAs) as bio-organocatalysts, in addition to tetrabutylammonium iodide (TBAI) as a cocatalyst, to synthesize various biobased oligomers. These biobased oligomers were strategically prepared starting from epoxidized olive oil (EOO) and a variety of cyclic anhydrides (phthalic, PA; maleic, MA; succinic, SA; and glutaric, GA). Among the amino acids tested as bio-organocatalysts, L-glutamic acid (L-Glu) showed the best performance for the synthesis of both poly(EOO-co-PA) and poly(EOO-co-MA), exhibiting 100% conversion at 80 °C in 2 hours, whereas the formation of poly(EOO-co-SA) and poly(EOO-co-GA) required more extreme reaction conditions (72 hours under toluene reflux conditions). Likewise, we have succeeded in obtaining the trans isomer exclusively for the MA based-oligomer within the same synthetic framework. The obtained oligomers were extensively characterized using techniques including NMR, FT-IR, GPC and TGA. A series of computational simulations based on density functional theory (DFT) and post-Hartree Fock (post-HF) methods were performed to corroborate our experimental findings and to obtain an understanding of the reaction mechanisms.

Microbiome data analysis via machine learning models: Exploring vital players to optimize kitchen waste composting system

Composting, reliant on microorganisms, effectively treats kitchen waste. However, it is difficult to precisely understand the specific role of key microorganisms in the composting process by relying solely on experimental research. This study aims to employ machine learning models to explore key microbial genera and to optimize composting systems. After introducing a novel microbiome preprocessing approach, Stacking models were constructed (R2 is about 0.8). The SHAP method (SHapley Additive exPlanations) identified Bacillus, Acinetobacter, Thermobacillus, Pseudomonas, Psychrobacter, and Thermobifida as prominent microbial genera (Shapley values ranging from 3.84 to 1.24). Additionally, microbial agents were prepared to target the identified key genera, and experiments demonstrated that the composting quality score was 76.06 for the treatment and 70.96 for the control. The exogenous agents enhanced decomposition and improved compost quality in later stages. In summary, this study opens up a new avenue to identifying key microorganisms and optimizing the biological treatment process.

Environmental Evaluation of Polyhydroxyalkanoates from Animal Slaughtering Waste Using Material Input Per Service Unit

The massive production and extensive use of fossil-based non-biodegradable plastics are leading to their environmental accumulation and ultimately cause health threats to animals, humans, and the biosphere in general. The problem can be overcome by developing eco-friendly ways for producing plastics-like biopolymers from waste residues such as of agricultural origin. This will solve two currently prevailing social issues: waste management and the efficient production of a biopolymer that is environmentally benign, polyhydroxyalkanoates (PHA). The current study assesses the environmental impact of biopolymer (PHA) manufacturing, starting from slaughterhouse waste as raw material. The Material Input Per Service Unit methodology (MIPS) is used to examine the sustainability of the PHA production process. In addition, the impact of shifting from business-as-usual energy provision (i.e., electricity from distribution grid network and heat provision from natural gas) to alternative renewable energy sources is also evaluated. As a major outcome, it is shown that the abiotic material contribution for PHA production process is almost double for using hard coal as an energy source than the petro-plastic low-density-poly(ethene) (LPDE), which PHA shall ultimately replace. Likewise, abiotic material contribution is 43% and 7% higher when using the electricity from the European electricity mix (EU-27 mix) and biogas, respectively, than in the case of LDPE production. However, PHA production based on wind power for energy provision has 12% lower abiotic material input than LDPE. Furthermore, the water input decreases when moving from the EU-27 mix to wind power. The reduction in water consumption for various electricity provision resources amounts to 20% for the EU-27 mix, 25% for hard coal, 71% for wind, and 70% for biogas. As the main conclusion, it is demonstrated that using wind farm electricity to generate PHA is the most environmentally friendly choice. Biogas is the second-best choice, although it requires additional abiotic material input.