Dr Zahra Sobhani

The accumulation of microplastics (MP) in soil via their continuous release and degradation of large plastics has recently become a serious global problem. The major concern with MP is their potential to sorb pollutants as well as ingestion by living organisms. Hence, this study focused on the effect of PVC MP exposure on increasing the risk of perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) bioaccumulation in earthworms in addition to their reproduction. In general, the bioaccumulation factor (BAF) for PFOA and PFOS increased up to 200% in earthworms exposed to MP-contaminated soil. MP at 500 and 1000 mg kg -1 soil caused enhanced uptake of PFOS and PFOA in earthworms, and a significant reduction in their reproduction. These results have significant implications for risk assessment of MP in soil.

We recently developed the Raman mapping image to visualise and identify microplastics / nanoplastics (Fang et al. 2020, Sobhani et al. 2020). However, when the Raman signal is low and weak, the mapping uncertainty from the individual Raman peak intensity increases and may lead to images with false positive or negative features. For real samples, even the Raman signal is high, a low signal-noise ratio still occurs and leads to the mapping uncertainty due to the high spectrum background when: the target plastic is dispersed within another material with interfering Raman peaks; materials are present that exhibit broad Raman peaks; or, materials are present that fluoresce when exposed to the excitation laser. In this study, in order to increase the mapping certainty, we advance the algorithm to combine and merge multi-images that have been simultaneously mapped at the different characteristic peaks from the Raman spectra, akin imaging via different mapping channels simultaneously. These multi-images are merged into one image via algorithms, including colour off-setting to collect signal with a higher ratio of signal-noise, logic-OR to pick up more signal, logic-AND to eliminate noise, and logic-SUBTRACT to remove image background. Specifically, two or more Raman images can act as ¿parent images¿, to merge and generate a ¿daughter image¿ via a selected algorithm, to a ¿granddaughter image¿ via a further selected algorithm, and to an ¿offspring image¿ etc. More interestingly, to validate this algorithm approach, we analyse microplastics / nanoplastics that might be generated by a laser printer in our office or home. Depending on the toner and the printer, we might print and generate millions of microplastics and nanoplastics when we print a single A4 document.

Microplastics are among the ubiquitous contaminants in our environment. As emerging contaminants, microplastics are still facing with lots of challenges on the characterisation, including their capture, identification and visualisation, particularly from a complex background. For example, when we print documents using a laser printer, we are printing microplastics onto paper, because the plastics are the main ingredient of the toner powder mixture. Characterisation of these microplastic mixture meets an even more complicated challenge, because plastic's signals might be shielded by other toner powder ingredients such as the pigments, the dyes, the black carbon, and the paper fabrics as well. To solve this challenge, we employ various techniques, including SEM, TEM, XPS, FT-IR, TGA and Raman, to characterise the microplastics printed via the toner powders. Interestingly, we show that Raman can distinguish and visualise the distribution of the microplastics from the complex background of the mixture. We estimate the millions of toner powders, each of which is ~4¿6 µm in size, are printed out per A4 sheet as microplastics. The findings send a strong warning that millions of microplastics might be generated from the printing activities in our daily lives.

As an emerging contaminant, microplastic is receiving increasing attention. However, the contamination source is not fully known, and new sources are still being identified. Herewith, we report that microplastics can be found in our gardens, either due to the wrongdoing of leaving plastic bubble wraps to be mixed with mulches or due to the use of plastic landscape fabrics in the mulch bed. In the beginning, they were of large sizes, such as > 5¿mm. However, after 7 years in the garden, owing to natural degradation, weathering, or abrasion, microplastics are released. We categorize the plastic fragments into different groups, 5¿mm¿0.75¿mm, 0.75¿mm¿100¿µm, and 100¿0.8¿µm, using filters such as kitchenware, meaning we can collect microplastics in our gardens by ourselves. We then characterized the plastics using Raman image mapping and a logic-based algorithm to increase the signal-to-noise ratio and the image certainty. This is because the signal-to-noise ratio from a single Raman spectrum, or even from an individual peak, is significantly less than that from a spectrum matrix of Raman mapping (such as 1 vs. 50 × 50) that contains 2,500 spectra, from the statistical point of view. From the 10¿g soil we sampled, we could detect the microplastics, including large (5¿mm¿100¿µm) fragments and small (<100¿µm) ones, suggesting the degradation fate of plastics in the gardens. Overall, these results warn us that we must be careful when we do gardening, including selection of plastic items for gardens.

This novel study investigated the behavior and fate of chlorothalonil in terms of kinetics, sorption¿desorption and leaching potential in urban landscape soils using batch experiments. The pseudo-second-order model well described the sorption kinetics of chlorothalonil in urban soils. Consequently, chlorothalonil was partitioned into heterogeneous surfaces of soil following the Freundlich isotherm model. According to PCA, soil organic matter (OM), silt, clay, and oxides of Al and Fe exhibited a significant positive correlation (P < 0.05) with chlorothalonil K d (P < 0.05), while sand content and soil pH showed a negative correlation at P < 0.05. In soils, decreased sorption of chlorothalonil was also due to the presence of undecomposed or partly decomposed OM, whereas increased sorption could be attributed to the combined effect of OM with C = O and C¿H groups, silt, clay, Al and Fe oxides and hydrophobicity of the fungicide. Also, HI, GUS, LIX and K d of four among nine urban soils indicated that chlorothalonil has a great potential for leaching into the groundwater from the soil surface, posing an unintended threat to non-target biota and food safety. Therefore, utmost care must be taken while applying chlorothalonil in urban landscapes, particularly on impervious surfaces, to minimize the impact on the ecosystem.