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The (partial) replacement of synthetic polymers with bioplastics is due to increased production of conventional packaging plastics causing for severe environmental pollution with plastics waste. The bioplastics, however, represent complex mixtures of known and unknown (bio)polymers, fillers, plasticizers, stabilizers, flame retardant, pigments, antioxidants, hydrophobic polymers such as poly(lactic acid), polyethylene, polyesters, glycol, or poly(butylene succinate), and little is known of their chemical safety for both the environment and the human health. Polymerization reactions of bioplastics can produce no intentionally added chemicals to the bulk material, which could be toxic, as well. When polymers are used to food packing, then the latter chemicals could also migrate from the polymer to food. This fact compromises the safety for consumers, as well. The scarce data on chemical safety of bioplastics makes a gap in knowledge of their toxicity to humans and environment. Thus, development of exact analytical protocols for determining chemicals of bioplastics in environmental and food samples as well as packing polymers can only provide warrant for reliable conclusive evidence of their safety for both the human health and the environment. The task is compulsory according to legislation Directives valid to environmental protection, food control, and assessment of the risk to human health. The quantitative and structural determination of analytes is primary research task of analysis of polymers. The methods of mass spectrometry are fruitfully used for these purposes. Methodological development of exact analytical mass spectrometric tools for reliable structural analysis of bioplastics only guarantees their safety, efficacy, and quality to both humans and environment. This study, first, highlights innovative stochastic dynamics equations processing exactly mass spectrometric measurands and, thus, producing exact analyte quantification and 3D molecular and electronic structural analyses. There are determined synthetic polymers such as poly(ethylenglycol), poly(propylene glycol), and polyisoprene as well as biopolymers in bags for foodstuffs made from renewable cellulose and starch, and containing, in total within the 20,416–17,495 chemicals per sample of the composite biopolymers. Advantages of complementary employment in mass spectrometric methods and Fourier transform infrared spectroscopy is highlighted. The study utilizes ultra-high resolution electrospray ionization mass spectrometric and Fourier transform infrared spectroscopic data on biodegradable plastics bags for foodstuffs; high accuracy quantum chemical static methods, molecular dynamics; and chemometrics. There is achieved method performance |r| = 0.99981 determining poly(propylene glycol) in bag for foodstuff containing 20,416 species and using stochastic dynamics mass spectrometric formulas. The results highlight their great capability and applicability to the analytical science as well as relevance to both the fundamental research and to the industry.
Quantifying ecological toxicity from real heavy metal co-contamination in site soil
Vol 4, Issue 1, 2023
VIEWS - 5932 (Abstract)
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Abstract
This summary outlines a significant challenge in ecological risk assessment of contaminated sites: quantitatively evaluating the ecological effects of combined heavy metal pollution in real-world soil. The study proposes a novel quantitative ecological assessment approach that integrates both broad ("top-down") and detailed ("bottom-up") knowledge. This approach involves three key steps: identifying effective biomarkers, pinpointing dominant pollutants, and assessing the combined effects of various exposure types and contaminants. To validate this approach, researchers examined an abandoned electronic waste site in Jiangsu Province using soil microcosms with earthworms. By analyzing biomarkers such as malondialdehyde (MDA), metallothionein (MT), catalase (CAT), superoxide dismutase (SOD), and reduced glutathione (GSH), they found that earthworms accumulated heavy metals in the order of Cd > Cu > Zn > Ni > Pb > Cr. Principal component analysis (PCA) identified GSH, CAT, and MDA as effective biomarkers, with Cd and Zn as the primary contaminants. The study revealed significant linear relationships between biomarker changes and specific heavy metal concentrations in soil (e.g., GSH with total Cd and DTPA-extractable Zn, MDA with DTPA-extractable Cd, and CAT with total Zn and bioaccumulated Zn). The sensitivity of the biomarkers to heavy metal contamination was ranked as GSH > CAT > MDA. Furthermore, the study highlighted complex interactions among different heavy metals, exposure types (e.g., soil vs. bioaccumulated), and biomarkers, emphasizing the need for comprehensive assessments in contaminated site evaluations.
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References
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Prof. Hongxing Dai
Beijing University of Technology, China
