Deep learning based approach for automated characterization of large marine microplastic particles.

The rapidly growing concern of marine microplastic pollution has drawn attentions globally. Microplastic particles are normally subjected to visual characterization prior to more sophisticated chemical analyses. However, the misidentification rate of current visual inspection approaches remains high. This study proposed a state-of-the-art deep learning-based approach, Mask R-CNN, to locate, classify, and segment large marine microplastic particles with various shapes (fiber, fragment, pellet, and rod). A microplastic dataset including 3000 images was established to train and validate this Mask R-CNN algorithm, which was backboned by a Resnet 101 architecture and could be tuned in less than 8 h. The fully trained Mask R-CNN algorithm was compared with U-Net in characterizing microplastics against various backgrounds. The results showed that the algorithm could achieve Precision = 93.30%, Recall = 95.40%, F1 score = 94.34%, APbb (Average precision of bounding box) = 92.7%, and APm (Average precision of mask) = 82.6% in a 250 images test dataset. The algorithm could also achieve a processing speed of 12.5 FPS. The results obtained in this study implied that the Mask R-CNN algorithm is a promising microplastic characterization method that can be potentially used in the future for large-scale surveys.

Casein-assisted enhancement of the compressive strength of biocemented sand.

As a soil biomineralization process, casein-assisted enzyme-induced carbonate precipitation (EICP) yielded biocemented specimens with significantly higher compressive strength than specimens cemented by regular or skim-milk-assisted EICP treatments. The compound concentration and curing strategy of casein-assisted EICP were experimentally optimized to maximize the compressive strength of precipitates with low calcium carbonate content. Under the optimized EICP conditions (0.893 M urea, 0.581 M CaCl2, 2.6 g/L urease enzyme, and 38.87 g/L casein), the unconfined compressive strengths reached 2 MPa. The scanning electron micrographs of selected samples provided microscopic evidence that EICP treatments assisted using skim milk and casein impart distinctive strength-enhancement mechanisms. The ammonium ions released from urea hydrolysis created an alkaline environment that makes casein dissociated into the pore water. As the casein-containing pore water became more viscous, the increased contact area with particles facilitated the precipitation of co-bound CaCO3 minerals and casein in the pore water. Casein was identified as a more efficient assisting agent than skim milk for low-level CaCO3 precipitation by EICP treatment.

Proposal for an initial screening method for identifying microplastics in marine sediments.

Marine debris, which is often called microplastics, is widespread in marine environments, particularly in sediments, and is recognized as an environmental hazard because it concentrates contaminants, forms biofilms, and sinks into marine sediments. In sediments, it may be ingested by benthos and have a negative impact on higher food chain levels. In this study, a new protocol was developed to identify microplastics in various sediment fractions. This protocol combined sieving and staining based on ordinal geotechnical/geological testing methods. The sieving process was derived from the conventional particle size distribution test, and nontoxic dyes were employed in the staining process. The protocol is safe and easy to perform as it merely involves the use of conventional geological/geotechnical testing equipment. The new protocol was successfully employed to stain and categorize different types and sizes of microplastic particles from contaminated sediments. This safe, easy-to-use, and efficient protocol can serve as the basis for a new alternative approach to study microplastics present in sediments, which can be performed using basic materials familiar to geotechnical/geological engineers.

Spatiotemporal variations of surface water microplastics near Kyushu, Japan: A quali-quantitative analysis.

Microplastics in the ocean are threatening marine ecosystems. Although plastic contaminants are ubiquitous, their distribution is thought to be heterogeneous. Here, we elucidate the spatial and temporal variations in the quanti-qualitative characteristics of microplastics near Kyushu, Japan in the East China Sea. Six surveys across nine stations were conducted over a 14-month period, and a total of 6131 plastic items were identified. The average microplastic abundance and size were 0.49 ± 0.92 (items·m-3 ± S.D.), and 1.71 ± 0.93 (mm ± S.D.), respectively. Differences between the highest and lowest abundances were 50-fold among monthly means, and 550-fold across all net tows. With respect to colour, polymer type, and shape, white and transparent polyethylene fragments were the dominant composition. There were significant differences for each of the analytical microplastic parameters among the survey months. Our results provide baseline data and lead to a more comprehensive understanding of the spatiotemporal characteristics of microplastic pollution.

Characterisation of CaCO3 phases during strain-specific ureolytic precipitation.

Numerous microbial species can selectively precipitate mineral carbonates with enhanced mechanical properties, however, understanding exactly how they achieve this control represents a major challenge in the field of biomineralisation. We have studied microbial induced calcium carbonate (CaCO3) precipitation (MICP) in three ureolytic bacterial strains from the Sporosarcina family, including S. newyorkensis, a newly isolated microbe from the deep sea. We find that the interplay between structural water and strain-specific amino acid groups is fundamental to the stabilisation of vaterite and that, under the same conditions, different isolates yield distinctly different polymorphs. The latter is found to be associated with different urease activities and, consequently, precipitation kinetics, which change depending on pressure-temperature conditions. Further, CaCO3 polymorph selection also depends on the coupled effect of chemical treatment and initial bacterial concentrations. Our findings provide new insights into strain-specific CaCO3 polymorphic selection and stabilisation, and open up promising avenues for designing bio-reinforced geo-materials that capitalise on the different particle bond mechanical properties offered by different polymorphs.