A high-throughput, automated technique for microplastics detection, quantification, and characterization in surface waters using laser direct infrared spectroscopy

A high-throughput approach to detecting, quantifying, and characterizing microplastics (MPs) by shape, size, and polymer type using laser direct infrared (LDIR) spectroscopy in surface water samples is demonstrated. Three urban creeks were sampled for their MP content near Cincinnati, OH. A simple Fenton reaction was used to oxidize the surface water samples, and the water samples were filtered onto a gold-coated polyester membrane. Infrared (IR) analysis for polymer identification was conducted, with recoveries of 88.3% ± 1.2%. This method was able to quantify MPs down to a diameter of 20 µm, a size comparable to that of MPs quantified by other techniques such as Fourier transform infrared spectroscopy (FTIR) and Raman spectroscopy. A shape-classifying algorithm was designed using the aspect ratio values of particles to categorize MPs as fibers, fibrous fragments, fragments, spherical fragments, or spheres. Cut-off values were identified from measurements of known sphere, fragment, and fibrous particles. About half of all environmental samples were classified as fragments while the other shapes accounted for the other half. A cut-off hit quality index (HQI) value of 0.7 was used to classify known and unidentified particles based on spectral matches to a reference library. Center for Marine Debris Research Polymer Kit 1.0 standards were analyzed by LDIR and compared to the given FTIR spectra by HQI, showing that LDIR obtains similar identifications as FTIR analysis. The simplicity and automation of the LDIR allows for quick, reproducible particle analysis, making LDIR attractive for high-throughput analysis of MPs.

Zinc transport and partitioning of a mine-impacted watershed: An evaluation of water and sediment quality

Watershed systems influenced by mining waste products can persist for many years after operations are ceased, leading to negative impacts on the health of the surrounding environment. While geochemical behaviors of these trace metals have been studied extensively at the benchtop-scale, much fewer studies have looked at controls on their distributions at the watershed-level. In this study, trace metals (As, Cd, Cr, Cu, Ni, and Zn) were reported from water and stream bed sediments at eight sites between the years 2014-2018 along a watershed undergoing active remediation efforts. Zn was determined to be the only trace metal analyzed with concentrations above EPA and Kansas Department of Health guidelines for both water and sediment in the watershed, and thus was the primary focus for determining the health of the watershed system. Controls on trace metal pollution distribution over the watershed were investigated to determine where remediation efforts should be focused. Surface cover seemed to have the highest effectivity with pasture lands having a strong positive correlation to Zn concentrations. Initial remediation efforts were assessed by calculating the geoaccumulation index (I_geo) and the contamination factor (C_f-sediment) from sediments and contamination factor from water (C_f-water) after decades of chat pile removal efforts. Most of the sites showed significant reduction in metal concentration values compared to previous studies in the watershed for water and sediment, with four sites still reporting concentrations that reveal potential health risks. Results from this study will inform management and policy makers for areas to focus their remediation efforts on the Spring River Watershed as well as providing a framework for assessing pollution at a watershed scale.

Assessing the efficiency and mechanism of zinc adsorption onto biochars from poultry litter and softwood feedstocks

The efficiency and adsorption mechanism of zinc removal was assessed in aqueous solution using four biochars from multiple biomass residues (poultry litter and three tree species). The effect of pH, kinetic effects, and isotherm fittings were investigated, as well as zinc-laden biochar using x-ray diffraction and absorption near edge structure. Sorbent load results showed softwood biochar exhibited the greatest zinc removal from both deionized (15 mg_Zn/L) and mining influenced river water (10 mg_Zn/L). The Langmuir isotherm was the best fit for the majority of the biochars. Exchangeable cations contributed most for the adsorption mechanism from the softwood biochars, while precipitation was greatest contribution for the poultry litter biochar. Overall, our results suggest that biochars from Douglas Fir trees are more efficient at removing zinc from aqueous solutions (up to 19.80 mg_Zn/g) compared to previously studied biochars (0.61 to 11.0 mg_Zn/g) and should be used for future remediation efforts.