Nutrient loading is a major threat to estuaries and coastal environments worldwide, therefore, it is critical that we have good monitoring tools to detect early signs of degradation in these ecologically important and vulnerable ecosystems. Traditionally, bottom-dwelling macroinvertebrates have been used for ecological health assessment but recent advances in environmental genomics mean we can now characterize less visible forms of biodiversity, offering a more holistic view of the ecosystem and potentially providing early warning signals of disturbance. We carried out a manipulative nutrient enrichment experiment (0, 150 and 600 g N fertilizer m⁻²) in two estuaries in New Zealand to assess the effects of nutrient loading on benthic communities. After seven months of enrichment, environmental DNA (eDNA) metabarcoding was used to examine the response of eukaryotic (18S rRNA), diatom only (rbcL) and bacterial (16S rRNA) communities. Multivariate analyses demonstrated changes in eukaryotic, diatom and bacterial communities in response to nutrient enrichment at both sites, despite differing environmental conditions. These patterns aligned with changes in macrofaunal communities identified using traditional morphological techniques, confirming concordance between disturbance indicators detected by eDNA and current monitoring approaches. Clear shifts in eukaryotic and bacterial indicator taxa were seen in response to nutrient loading while changes in diatom only communities were more subtle. Community changes were discernible between 0 and 150 g N m⁻² treatments, suggesting that estuary health assessment tools could be developed to detect early signs of degradation. Increasing variation in community structure associated with nutrient loading could also be used as an indicator of stress or approaching tipping points. This work represents a first step towards the development of molecular-based estuary monitoring tools, which could provide a more holistic and standardized approach to ecosystem health assessment with faster turn-around times and lower costs.

Parabens are alkyl esters of 4-hydroxybenzoic acid, which is derived from a family of synthetic esters of p-hydroxybenzoic acid. Among all the kinds of paraben, two parabens (methyl paraben, MP; and n-propyl paraben, PP) are the most generally used as preservatives in personal care products, such as cosmetics, pharmaceuticals, and food also, and are often presented together. However, a number of studies have reported that the toxicity of parabens affects the water environment, and human as well. This study utilized M13 phage display technology to provide easy, efficient, and relatively inexpensive methods to identify peptides that bind to MP and PP, respectively, to remove in wastewater. At first, biopanning was performed, to sort MP and PP specific binding phages, and three cases of experiment, including negative control (NC), which could sort unspecific binding phage, were conducted at the same time. Phage binding affinity tests were substituted by concentration reduction using antibody conjugated magnetic beads, and paraben concentration was measured by HPLC. Analysis showed that the MP concentration reduction of 38% was the highest in M4 phage, while the PP concentration reduction of 44% was the highest in P3 phage. We successfully screened two peptides specific to MP and PP, namely, MP4 and PP3, respectively; the results showed that the MP concentration reduction in MP4 was the highest at 44%, and the PP concentration reduction in PP3 was the highest at 39%, and their specificity was measured by the capture rate between target and control. In conclusion, the phage display technique shows applicability to the removal of parabens in water; furthermore, it also shows the possibility of the detection or removal of other chemicals.

The increase of annual organic wastes generated worldwide has become a major problem for many countries since the mismanagement could bring about negative effects on the environment besides, being costly for an innocuous disposal. Recently, insect larvae have been investigated to valorize organic wastes. This entomoremediation approach is rising from the ability of the insect larvae to convert organic wastes into its biomass via assimilation process as catapulted by the natural demand to complete its lifecycle. Among the insect species, black soldier fly or Hermetia illucens is widely researched since the larvae can grow in various environments while being saprophagous in nature. Even though black soldier fly larvae (BSFL) can ingest various decay materials, some organic wastes such as sewage sludge or lignocellulosic wastes such as waste coconut endosperm are destitute of decent nutrients that could retard the BSFL growth. Hence, blending with nutrient-rich low-cost substrates such as palm kernel expeller, soybean curd residue, etc. is employed to fortify the nutritional contents of larval feeding substrates prior to administering to the BSFL. Alternatively, microbial fermentation can be adopted to breakdown the lignocellulosic wastes, exuding essential nutrients for growing BSFL. Upon reaching maturity, the BSFL can be harvested to serve as the protein and lipid feedstock. The larval protein can be made into insect meal for farmed animals, whilst the lipid source could be extracted and transesterified into larval biodiesel to cushion the global energy demands. Henceforth, this review presents the influence of various organic wastes introduced to feed BSFL, targeting to reduce wastes and producing biochemicals from mature larvae through entomoremediation. Modification of recalcitrant organic wastes via fermentation processes is also unveiled to ameliorate the BSFL growth. Lastly, the sustainable applications of harvested BSFL biomass are as well covered together with the immediate shortcomings that entail further researches.

Pyrethroids are an important class of insecticides, and thousands of tons of these compounds are used in the United States every year. This study characterized exposures to pyrethroids and assessed demographic, socioeconomic, and lifestyle factors that modulate pyrethroid exposure using data from the National Health and Nutrition Examination Survey (NHANES) 2007–2012, a nationally representative survey of the non-institutionalized population of the United States. Urinary levels of commonly used biomarkers of pyrethroid exposure, including 3-phenoxybenzoic acid (3-PBA), 4-fluoro-3-phenoxybenzoic acid (F-PBA), and cis-dibromovinyl-dimethylcyclopropane carboxylic acid (DBCA), were determined by liquid chromatography-tandem mass spectrometry. The detection rate of 3-PBA, a nonspecific metabolite of several pyrethroids, was 78.1% in adults (N = 5233) and 79.3% in children (N = 2295). The detection rates of all other pyrethroid metabolites were <10%. The median urinary level of 3-PBA in adults was 0.47 μg/L (interquartile range, 0.14–1.22 μg/L). For children, the median urinary level was 0.49 μg/L (interquartile range, 0.17–1.29 μg/L). Age, gender, family income-to-poverty ratio (PIR), levels of physical activity, alcohol intake, and body mass index were associated with 3-PBA levels in adults. In children, age, gender, race/ethnicity, and PIR were associated with 3-PBA levels. 3-PBA levels also differed significantly across NHANES cycles, with higher levels observed in NHANES 2011–2012. Geometric mean 3-PBA levels in U.S. adults were 0.41 μg/L in NHANES 2007–2008, 0.41 μg/L in NHANES 2009–2010, and 0.66 μg/L in NHANES 2011–2012. In U.S. children, geometric mean 3-PBA levels were 0.40 μg/L in NHANES 2007–2008, 0.46 μg/L in NHANES 2009–2010, and 0.70 μg/L in NHANES 2011–2012. These results demonstrate that pyrethroid exposures remain a current environmental health concern and lay the foundation for further preclinical and epidemiological studies assessing human health risks associated with pyrethroids.

Volatile Petroleum Hydrocarbon (VPH) class effects on soil microbial composition were investigated using two next-generation sequencing (NGS) techniques – 454 pyrosequencing and ion torrent sequencing. Microbial activity was stimulated by adding different VPH compound classes to the sandy soil in comparison with live controls without VPH addition. Microbial community structure was significantly affected by the various VPH classes. At the genus level, Rhodococcus, Desulfosporosinus, Polaromonas, Mesorhizobium and Methylibium had the highest relative abundances in the straight-chain alkane (str-alk) treated soil as compared to the control (p < 0.05, 2 sample t-tests) while Pseudomonas was more dominant in the cyclic alkane (cyc-alk) contaminated soil. Pseudonocardia was significantly higher in relative abundance in the aromatic hydrocarbon (aro-H) treated batches as compared to the control (p < 0.05, 2 sample t-tests). A non-metric multidimensional scaling (NMDS) of the Bray Curtis similarity between microbial communities in the batches revealed at least 60% similarity for each treatment and also showed that VPH class was a statistically significant factor in shaping the bacterial communities in the soil treatments (Global R = 0.861, p < 0.01). The NGS platforms (454 GS Junior and Ion torrent) compared in this study did not appear to affect the outcomes of the microbial community structure and composition analysis.

Kitchen emissions are mixed indoor air pollutants with adverse health effects, but the large-scale assessment is limited by costly equipment and survey methods. This study aimed to discuss the application of backpropagation (BP) neural network models in the assessment of kitchen emissions based on the exposure marker. A total of 3686 participants were recruited for the kitchen survey, and their sleep quality was measured by the Pittsburgh sleep quality index (PSQI). After excluding the confounders, 365 participants were selected to assess their urinary hydroxy polycyclic aromatic hydrocarbons (OH-PAHs) concentrations by ultra-high-performance liquid chromatography/tandem mass spectrometry. Two BP neural network models were then set up using the survey and detection data from the 365 participants and used to predict the total urinary OH-PAHs concentrations of all participants. The total urinary OH-PAHs and 1-hydroxy-naphthalene (1-OHNap) concentrations were significantly higher among the 365 participants with poor sleep quality (global PSQI score > 5; P < 0.05). Results from internal and external validation showed that our model has high credibility (model 2). Further, the participants with higher predicted total urinary OH-PAHs concentrations were associated with the global PSQI score of >5 (odds ratio (OR) = 1.284, 95% confidence interval (CI) = 1.082–1.525 for participants with predicted total urinary OH-PAHs concentrations of over 1.897 μg/mmol creatinine in model 1, and OR = 1.467, 95% CI = 1.240–1.735 for participants with predicted total urinary OH-PAHs concentrations of over 2.253 μg/mmol creatinine in model 2) after adjusting for the confounders. Findings suggest that the BP neural network model is suitable for assessing kitchen emissions, and the urinary OH-PAHs concentrations can be taken as the model outlay.

In this study, ambient fine particles (PM₂.₅) were collected in two urban cities in China and Korea (Beijing and Gwangju, respectively) simultaneously in January 2018. Analysis of the nonpolar and semipolar organic matter (OM) using atmospheric pressure photoionization (APPI) Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) revealed that compounds containing only C, H, and O (CHO) and those containing C, H, O, and N (CHON) accounted for more than 90% of the total intensity of the OM peaks. Higher proportions of CHON compounds were observed during days with abnormally high PM₂.₅ concentrations at both sites than on regular or non-event days. The proportion of CHON species at the Beijing site was not correlated with secondary ionic species (i.e., NO₃⁻, SO₄²⁻, and NH₄⁺) or gaseous components (i.e., O₃, NO₂, and SO₂). In contrast, the proportion of CHON species at the Gwangju site was positively correlated with the concentrations of particulate nitrate and ammonium ions, assuming that ambient ammonium nitrate plays a role in the atmospheric formation of nitrogen-containing organic compounds (NOCs) at the Gwangju site and that Gwangju is more strongly influenced by secondary aerosols than Beijing is. In particular, a significant proportion of the compounds observed at the Beijing site contained only C, H and N (CHN), while negligible amounts of CHN were detected at the Gwangju site. The CHN species in Beijing were identified as quinoline compounds and the corresponding –CH₂ homologous series using complementary GC × GC-TOF MS analysis. These results suggest that NOCs and their –CH₂ homologous series from primary emissions may be significant contributors to nonpolar and semipolar OM during winter in Beijing, while NOCs with high oxidation states, likely formed via ambient-phase nitrate-mediated reactions, may be the dominant OM constituents in Gwangju.

Silver nanoparticles (AgNPs) are known to exert adverse effects on both humans and aquatic organisms; however, the toxic mechanisms underlying these effects remain unclear. In this study, we investigated the toxic mechanisms of various AgNPs with different surface electrical properties in the freshwater algae Chlorella vulgaris using an advanced proteomics approach with Data-Independent Acquisition. Citrate-coated AgNPs (Cit-AgNPs) and polyethyleneimine-coated AgNPs (PEI-AgNPs) were selected as representatives of negatively and positively charged nanoparticles, respectively. Our results demonstrated that the AgNPs exhibited surface electrical property-dependent effects on the proteomic profile of C. vulgaris. In particular, the negatively charged Cit-AgNPs specifically regulated mitochondrial function-related proteins, resulting in the disruption of several associated metabolic pathways, such as those related to energy metabolism, oxidative phosphorylation, and amino acid synthesis. In contrast, the positively charged PEI-AgNPs primarily targeted ribosome function-related proteins and interrupted pathways of protein synthesis and DNA genetic information transmission. In addition, Ag⁺ ions released from the AgNPs had a significant influence on protein regulation and the induction of cellular stress. Collectively, our findings provide new insight into the surface electrical property-dependent proteomic effects of AgNPs on C. vulgaris and should improve our understanding of the toxic mechanisms of AgNPs in freshwater algae.

Humic-like substances (HULIS) are complex mixtures that are highly associated with brown carbon (BrC) and are important components of biomass burning (BB) emissions. In this study, we investigated the light absorption, emission factors (EFs), and amounts of HULIS emitted from the simulated burning of 27 types of regionally important rainforest biomass in Southeast Asia. We observed that HULIS had a high mass absorption efficiency at 365 nm (MAE₃₆₅), with an average value of 2.6 ± 0.83 m² g⁻¹ C. HULIS emitted from BB accounted for 65% ± 13% of the amount of water-soluble organic carbon (WSOC) and 85% ± 10% of the light absorption of WSOC at 365 nm. The EFs of HULIS from BB averaged 2.3 ± 2.1 g kg⁻¹ fuel, and the burning of the four vegetation subtypes (herbaceous plants, shrubs, evergreen trees, and deciduous trees) exhibited different characteristics. The differences in EFs among the subtypes were likely due to differences in lignin content in the vegetation, the burning conditions, or other factors. The light absorption characteristics of HULIS were strongly associated with the EFs. The annual emissions (minimum–maximum) of HULIS from BB in this region in 2016 were 200–371 Gg. Furthermore, the emissions from January to April accounted for 99% of the total annual emissions of HULIS, which is likely the result of the burning activities during this season. The most significant emission regions were Cambodia, Burma, Thailand, and Laos. This study, which evaluated emissions of HULIS by simulating open BB, contributes to a better understanding of the light-absorbing properties and regional budgets of BrC in this region.