Microplastic pollution is a global concern theme, and there is still the need for less laborious and faster analytical methods aiming at microplastics detection. This article describes a high throughput screening method based on near-infrared hyperspectral imaging (HSI-NIR) to identify microplastics in beach sand automatically with minimum sample preparation. The method operates directly in the entire sample or on its retained fraction (150 μm–5 mm) after sieving. Small colorless microplastics (<600 μm) that would probably be imperceptible as a microplastic by visual inspection, or missed during manual pick up, can be easily detected. No spectroscopic subsampling was performed due to the high-speed analysis of line-scan instrumentation, allowing multiple microplastics to be assessed simultaneously (video available). This characteristic is an advantage over conventional infrared (IR) spectrometers. A 75 cm² scan area was probed in less than 1 min at a pixel size of 156 × 156 μm. An in-house comprehensive spectral dataset, including weathered microplastics, was used to build multivariate supervised soft independent modelling of class analogy (SIMCA) classification models. The chemometric models were validated for hundreds of microplastics (primary and secondary) collected in the environment. The effect of particle size, color and weathering are discussed. Models' sensitivity and specificity for polyethylene (PE), polypropylene (PP), polyamide-6 (PA), polyethylene terephthalate (PET) and polystyrene (PS) were over 99% at the defined statistical threshold. The method was applied to a sand sample, identifying 803 particles without prior visual sorting, showing automatic identification was robust and reliable even for weathered microplastics analyzed together with other matrix constituents. The HSI-NIR-SIMCA described is also applicable for microplastics extracted from other matrices after sample preparation. The HSI-NIR principals were compared to other common techniques used to microplastic chemical characterization. The results show the potential to use HSI-NIR combined with classification models as a comprehensive microplastic-type characterization screening.

Diet, age, and growth rate influences on fish mercury concentrations were investigated for Arctic char (Salvelinus alpinus) and brook trout (Salvelinus fontinalis) in lakes of the eastern Canadian Arctic. We hypothesized that faster-growing fish have lower mercury concentrations because of growth dilution, a process whereby more efficient growth dilutes a fish’s mercury burden. Using datasets of 57 brook trout and 133 Arctic char, linear regression modelling showed fish age and diet indices were the dominant explanatory variables of muscle mercury concentrations for both species. Faster-growing fish (based on length-at-age) fed at a higher trophic position, and as a result, their mercury concentrations were not lower than slower-growing fish. Muscle RNA/DNA ratios were used as a physiological indicator of short-term growth rate (days to weeks). Slower growth of Arctic char, inferred from RNA/DNA ratios, was found in winter versus summer and in polar desert versus tundra lakes, but RNA/DNA ratio was (at best) a weak predictor of fish mercury concentration. Net effects of diet and age on mercury concentration were greater than any potential offset by biomass dilution in faster-growing fish. In these resource-poor Arctic lakes, faster growth was associated with feeding at a higher trophic position, likely due to greater caloric (and mercury) intake, rather than growth efficiency.

Soils containing a large proportion of industrial waste can pose a health risk due to high environmentally available concentrations of toxic metal(loid)s. Nano zero-valent iron (nZVI) and amorphous manganese oxide (AMO) were applied as immobilising amendments (1 wt%) to soils with different industrial origin of As and Sb, and leaching of As, Sb, Pb, and Zn was investigated using a single extraction with deionised water. The different industrial impact was reflected in the mineralogy, chemical composition and pH of these soils. Water-soluble As ratios positively correlated with pH in all experimental treatments. A significant decrease of water-soluble As ratios was observed in all nZVI-amended soils (~65–93% of the control) except for one sample with the lowest solution pH. Nano zero-valent iron was also successful in Sb immobilisation (~76–90% of the control). Highly variable results were obtained for AMO, which only led to a decrease of water-soluble As in soils with solution pH of ≥7 (~70–80% of the control), probably due to lower stability of AMO in acidic conditions. In each case, nZVI was more efficient at decreasing water-soluble As ratios than AMO. Dissolved Pb concentrations remained unchanged after the application of nZVI and AMO, and the decrease of Zn leaching using AMO was controlled mainly by soil pH increase induced by its application. According to the calculated saturation indices, tripuhyite (FeSbO₄) was predicted to be the key mineral controlling Sb solubility in mine soils. Secondary Fe (hydr)oxides either originally present or newly formed due to nZVI oxidation were instrumentally identified at different stages of their transformation and metal(loid) retention. To conclude, nZVI is suitable for application to contaminated soils at a wide pH range, while the use of AMO for decreasing As leaching is limited to soils with pH ≥ 7.

Black carbon (BC), by the combustion of fossil fuels and biomass, has profound effects on climate change and glacier retreat in industrial eras. In the present study, we report refractory BC (rBC) in an ice core spanning 1850–2014, retrieved from the Hariqin Glacier of the Tanggula Mountains in the central Tibetan Plateau, measured using a single particle soot photometer (SP2). The rBC concentration shows a three-fold increase since the 1950s. The mean rBC concentration was 0.71 ± 0.52 ng mL⁻¹ during 1850s–1940s and 2.11 ± 1.60 ng mL⁻¹ during 1950s–2010s. The substantial increase in rBC since the 1950s is consistent with rBC ice core records from the Tibetan Plateau and Eastern Europe. According to the predominant atmospheric circulation patterns over the glacier and timing of changes in regional emissions, the post-1950 amplification of rBC concentration in the central Tibetan Plateau most likely reflects increases in emissions in Eastern Europe, former USSR, the Middle East, and South Asia. Despite the low-level background rBC concentrations in the ice cores from the Tibetan Plateau, the present study highlights a remarkable increase in anthropogenic BC emissions in recent decades and the consequent influence on glaciers in the Tibetan Plateau.

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal).This article has been retracted at the request of the Editors and Corresponding Author.The authors have plagiarized part of a paper that had already appeared in Environmental and Experimental Botany, 179 (2020) 104227, https://doi.org/10.1016/j.envexpbot.2020.104227. One of the conditions of submission of a paper for publication is that authors declare explicitly that their work is original and has not appeared in a publication elsewhere. Re-use of any data should be appropriately cited. As such this article represents a severe abuse of the scientific publishing system. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process.

Nanoscale zero-valent iron (nZVI) is the main nanomaterial used in environmental remediation processes. The present study aims to evaluate the life cycle sustainability of nZVI production methods applied in environmental remediation. Three production methods of nZVI were selected for analysis: milling, liquid reduction with sodium borohydride, and chemical reduction with hydrogen gas (in two approaches: considering the goethite and hematite synthesis and after using in nZVI production and, using goethite and hematite particles already synthesized for nZVI production). The life cycle sustainability assessment was carried out based on a multi-criteria and multi-attribute analysis. The multi-criteria analysis was used to determine impact category preferences of different specialists in sustainability and remediation, and calculate the sustainability score through a linear additive model. Finally, a Monte Carlo simulation was used to quantify the results uncertainty. The functional unit considered was 1.00 kg of nZVI produced. The milling method and the hydrogen gas method in approach considering the use goethite and hematite particles already synthesized were the most sustainable. Moreover, the sustainability index was found to be influenced by the considered location scenarios as well as the perspectives of the different specialists, which was essential in producing a more accurate and comprehensive evaluation of the aforementioned sustainability methods. Overall, this study significantly contributed to applications of the state-of-the-art life cycle sustainability assessment in studies regarding nanomaterials, employing a simple methodology that included an analysis of different specialists. In addition, this is the first article that uses life cycle sustainability assessment in nanomaterials.

The release of reactive nitrogen (Nᵣ) from food production and consumption constitute the primary source of nitrogen pollution. However, nitrogen flows and the driving factors of food chain of Shanghai, China have not been previously studied. Here, we used a substance flow analysis model to analyze the changes in Nᵣ inputs and outputs in agricultural production, livestock and poultry farming, and food consumption related to the Shanghai food chain between 2000 and 2018. The driving forces of Nᵣ inputs, Nᵣ use efficiency, and Nᵣ surpluses/deficits in the food production and consumption system were also investigated. The results indicated that the main sources of Nᵣ input in the food production and consumption system were nitrogen fertilizers, livestock and poultry feed from external sources, and plant-based foods, which accounted for 36.28–59.45% of Nᵣ input in agricultural production, 37.32–76.57% of Nᵣ input in livestock and poultry farming, and 35.38–59.37% of Nᵣ input in food consumption, respectively. The main forms of Nᵣ outputs were surplus nitrogen in the soil, excretal nitrogen from livestock and poultry animals, and excretal nitrogen from humans, which accounted for 38.2–48.89% of Nᵣ output in agricultural production, 36.78–55.18% of Nᵣ output in livestock and poultry farming, and 85.36% of Nᵣ output in food consumption, respectively. From 2000 to 2018, the Nᵣ inputs per unit area from agricultural production decreased at a rate of 20.42% before 2012, and then increased at a rate of 5.72%. Moreover, the Nᵣ use efficiency of agricultural production component of Shanghai was at a low level, only 18.43–27.6%. Cultivation area of crops was the main driving forces of the Nᵣ input to food production and consumption system. These results provide essential data for controlling nitrogen pollution caused by Shanghai food production and consumption, which can serve as a reference for administrative agencies in formulating policies.

Individuals with metabolic disorders exhibit enhanced susceptibility to the cardiovascular health effects of particulate air pollution, but the underlying mechanisms are not yet understood. We aim to assess whether changes in proinflammatory lipid signals are associated with fine particulate matter (PM₂.₅) exposure in individuals with and without prediabetes. A longitudinal panel study was conducted in Beijing, China, and included 120 participants followed up over 589 clinical visits from August 2013 to February 2015. We measured 12 lipids derived from arachidonic acid pathways in blood samples of the participants via targeted lipidomic analyses. Ambient PM₂.₅ concentrations were continuously monitored at a station for associations with the lipids. Among the 120 participants, 110 (mean [SD] age at recruitment, 56.5 [4.2] years; 31 prediabetics) who visited the clinic at least twice over the follow-up period were assigned exposure values of the outdoor residential PM₂.₅ concentrations during the 1–14 days preceding each clinical visit. With an interquartile range increase in the 1-day-lag PM₂.₅ exposure (64.0 μg/m³), the prediabetic group had consistently greater increases in the concentration of arachidonate metabolites derived from the cytochrome P450 (CYP450) pathway (5,6-DHET, 15.8% [95% CI, 3.5–29.7%]; 8,9-DHET, 9.7% [95% CI, 0.6–19.6%]; 11,12-DHET, 8.3% [95% CI, 1.9–15.1%]; 14,15-DHET, 7.4% [95% CI, 0.9–14.4%]; and 20-HETE, 8.9% [95% CI, 1.0–17.5%]), compared with the healthy group. Among CYP450-derived lipids, 14,15-DHET and 20-HETE significantly mediated 8% and 8% of the PM₂.₅-associated increase in white blood cells, 10% and 13% of that in neutrophils, and 20% and 23% of that in monocytes, respectively, in the prediabetic group. In conclusion, proinflammatory lipid signals from CYP450 pathways triggered the health effects of particulate air pollution in individuals with prediabetes, suggesting that targeting lipid metabolism has therapeutic potential to attenuate or prevent the cardiovascular effects of air pollution in susceptible populations.

Elevated levels of particulate matter (PM) in urban atmospheres are one of the major environmental challenges of the Anthropocene. To effectively lower those levels, identification and quantification of sources of PM is required. Biomonitoring methods are helpful tools to tackle this problem but have not been fully established yet. An example is the sampling and subsequent analysis of spider webs to whose adhesive surface dust particles can attach. For a methodical inspection, webs of orb-weaving spiders were sampled repeatedly from 2016 to 2018 at 22 locations in the city of Jena, Germany. Contents of Ag, Al, As, B, Ba, Ca, Cd, Co, Cr, Cs, Cu, Fe, K, La, Li, Mg, Mn, Mo, Na, Ni, P, Pb, Rb, S, Sb, Si, Sn, Sr, Th, Ti, V, Y, Zn and Zr were determined in the samples using inductively coupled plasma-mass spectrometry (ICP-MS) and inductively coupled plasma-optical emission spectroscopy (ICP-OES) after aqua regia digestion.Multivariate statistical methods were applied for a detailed evaluation. A combination of cluster analysis and principal component analysis allows for the clear identification of three main sources in the study area: brake wear from car traffic, abrasion of tram/train tracks and particles of geogenic origin. Quantitative source contributions reveal that high amounts of most of the metals are derived from a combination of brake wear and geogenic particles, the latter of which are likely resuspended by moving vehicles. This emphasizes the importance of non-exhaust particles connected to road traffic.Once a source identification has been performed for an area of interest, classification models can be applied to assess air quality for further samples from within the whole study area, offering a tool for air quality assessment. The general validity of this approach is demonstrated using samples from other locations.