Neonicotinoids and the closely related insecticide classes sulfoximines and butenolides have recently attracted growing concerns regarding their potential negative effects on non-target organisms, including pollinators such as bees. Indeed, it is becoming increasingly clear that these effects may occur at much lower levels than those considered to be safe for humans. To properly assess the ecological and environmental risks posed by neonicotinoids, appropriate sampling and analytical procedures are needed. Here, we used honey as reliable environmental sampler and developed an unprecedentedly sensitive method based on QuEChERS and UHPLC-MS/MS for the simultaneous determination of the nine neonicotinoids and related molecules currently present on the market (acetamiprid, clothianidin, dinotefuran, flupyradifurone, imidacloprid, nitenpyram, sulfoxaflor, thiacloprid and thiamethoxam). The method was validated and provided excellent levels of precision and accuracy over a wide concentration range of 3–4 orders of magnitude. Lowest limits of quantification (LLOQs) as low as 2–20 pg/g of honey depending on the analytes were reached. The method was then applied to the analysis of 36 honey samples from various regions of the World which had already been analysed for the five most common neonicotinoids (acetamiprid, clothianidin, imidacloprid, thiacloprid and thiamethoxam) in a previous study. This allowed us to determine the long-term stability (i.e. up to 40 months) of these molecules in honey, both at room temperature and −20 °C. We found that the five pesticides were stable over a period of several years at −20 °C, but that acetamiprid and thiacloprid partially degraded at room temperature. Finally, we also measured the levels of dinotefuran, nitenpyram, sulfoxaflor and flupyradifurone and found that 28% of the samples were contaminated by at least one of these pesticides.

Epidemiological studies have demonstrated association between the total mass of fine particulate matter (PM2.5) exposures and inflammation. There are few studies exploring the associations between PM2.5 constituents and the biomarkers of inflammation in older adults and the underlying biological mechanisms are not exact. In this study, we examined the associations between PM2.5 and its constituents (organic carbon (OC), elemental carbon (EC), total carbon (TC), polycyclic aromatic hydrocarbons (PAHs) and complement three factor (C3), an important biomarker of inflammation in a repeated panel of 175 older adults in Beijing, China. We have constructed three different linear mixed effect models (single-pollutant model, constituent-PM2.5 joint model, and constituent-residual model) to evaluate the association of PM2.5 and its constituents and complement C3, controlling for concentration of high sensitive C-reactive protein (hs-CRP), day of week, mean temperature, relative humidity, location and potential individual confounders. We found robust positive associations of OC, EC, TC, PAHs and PM2.5 mass concentration with complement C3 at different lag patterns. The cumulative effects of pollutants increased across average of 2–5 days. Individuals aged 65 and above, or with diabetes, or BMI ≥30, or with no-cardiopathy, or with hypertension also exhibited positive associations between PM2.5 and complement C3. The results revealed that short-term exposure to PM2.5 and its constituents could result in a significant increase in serum level of complement C3. These findings suggested a possible involvement of complement C3 in the effect of PM2.5 on inflammatory reaction.

The occurrence of microplastics (MPs) in the environment has been gaining widespread attention globally. MP-colonizing microorganisms are important links for MPs contamination in various ecosystems, but have not been well understood. To partially address this issue, the present study investigated biofilm formation by microorganisms originating from lake water on low-density polyethylene (LDPE) MPs using a cultivation approach and the surface-related effects on the MP-associated microbial communities using 16S rRNA high-throughput sequencing. With the addition of nonionic surfactants and UV-irradiation pretreatment that changed the surface properties of LDPE MPs, more microorganisms were colonized on LDPE surface. Microbial community analysis indicated that LDPE MPs were primarily colonized by the phyla Proteobacteria, Bacteroidetes and Firmicutes, and the surface roughness and hydrophobicity of MP were important factors shaping the LDPE MP-associated microbial community structure. Half of the top 20 most abundant genera colonizing on LDPE were found to be potential pathogens, e.g., plant pathogens Agrobacterium, nosocomial pathogens Chryseobacterium and fish pathogens Flavobacterium. This study demonstrated rapid bacterial colonization of LDPE MPs in lake water microcosms, the role of MPs as transfer vectors for harmful microorganisms in lake water, and provided a first glimpse into the effect of surface properties on LDPE MP-associated biofilm communities.

The fate of polycyclic aromatic hydrocarbons (PAHs) determines their potential risk in soil, which may be directly affected by abiotic conditions and indirectly through the changes in decomposer communities. In comparison, the indirect effects on the fate remain largely elusive. In this study, the fate of phenanthrene and benzo[a]pyrene and the corresponding bacterial changes were investigated in three contaminated farmland soils using a ¹⁴C tracer method and Miseq sequencing. The results showed that most benzo[a]pyrene was consistently extractable with dichloromethane (DCM) after the 60-day incubation (60.4%–78.2%), while phenanthrene was mainly mineralized to CO₂ during the 30-day incubation (40.4%–58.7%). Soils from Guangzhou (GZ) showed a different distribution pattern of ¹⁴C-PAHs exemplified by low mineralization and disparate bound residue formation. The PAH fate in the Shenyang (SY) and Nanjing (NJ) soils were similar to each other than to that in the GZ soil. The fate in the GZ soil seemed to be linked to the distinct edaphic properties, such as organic matter content, however soil microbial community could have influenced the distribution pattern of PAHs. This potential role of microorganisms was reflected by the unique changes in the copy numbers of Gram positive RHDα gene, and by the distinct shifts in bacterial community composition during the incubation. A quite different shift in bacterial communities was found in the GZ microcosms which may influence PAH mineralization and non-extractable residue (NER) formation.

Frequently detected residuals of antibiotics in crops has drawn increasing attention from research community and the general public. This study was conducted under the controlled environmental conditions to investigate the uptake, translocation and distribution of three different veterinary antibiotics (VAs) in plants of Zea mays L. (maize, the third largest crop in the world, especially in China) and the associated mechanisms. The distribution color-maps of mixed-VAs showed that the highest RCF (root concentration factors) values of chlortetracycline (CTC) and sulfamethoxazole (SMZ) were found in the 0.5–2.0 mm zone (cell division zone), while the highest RCF value of sulfathiazole (ST) was in the 6.0–8.0 mm zone (elongation zone) of root tips (0.5–10.0 mm) after 120 h of exposure to VAs. The translocation factor (TF) of CTC was greater than 1.0, but the TFs of SMZ and ST were less than 1.0 under addition of single antibiotic. However, the TFs of three VAs were all greater than 1.0 at the end of exposure under addition of mixed-VAs. The dissipation of antibiotics by maize was also demonstrated by harvesting all plant parts in an enclosed system. The possible mechanisms for uptake and translocation of VAs in maize were investigated by adding multiple respiration inhibitors into the culture solution. The RCFs of VAs were suppressed heavily by salicylhydroxamic acid (SHAM) and sodium azide (NaN3), which indicates that the uptake of VAs was an active process. The results of TFs and stem concentration factors (SCFs) of CTC and SMZ in HgCl2 treatments revealed that the translocation of VAs was associated with the aquaporin activity in maize. The findings from this study will have significant implications for the management of crop food contamination by VAs and for the development of phytoremediation technology for antibiotics in the environment.

Human activities introduce significant contamination into aquatic systems that impact biodiversity and ecosystem function. Many contaminants accumulate, and remediation options are now required worldwide. One method for bioremediation involves the application of macrofauna to stimulate microbial ecosystem processes including contaminant removal. However, if we are to confidently apply such a technique, we need clarity on the effect of bioturbators on different contaminants and how these vary under different environmental scenarios. Here we used a systematic review and meta-analysis to analyse current knowledge on the activities of bioturbating macrofauna in contaminated sediments and quantify how bioturbation-bioremediation changes depend on the taxonomic group, the aquatic ecosystem and important environmental variables. Three common contaminant classes were reviewed and analysed: metals, nutrients (i.e. ammonia and phosphorous) and polycyclic aromatic hydrocarbons (PAH). In addition, meta-regressions were calculated to estimate the effect of environmental and experimental design variables on effect sizes. Meta-analytic results revealed that deeper burrowing and more active sediment surface animals (e.g. polychaetes) increased metal release from sediments, nutrients and oxygen uptake by microbial fractions in comparison to bioturbators that inhabit shallower depths in sediments. In addition, there was a different effect of bioturbators on response variables in different aquatic systems. Finally, bioturbator effects on nutrient and metal release appeared modulated by context-specific variables such as temperature, pH, sediment grain size, animal density and experimental duration. Our findings highlight critical knowledge gaps such as field applications, less studied macrobenthic fauna and the incorporation of molecular approaches. Our results provide the first quantitative synthesis of the effects of bioturbators on contaminant fate and the variables that need to be considered for the optimization of this method as a viable approach for sediment remediation and contaminant management in aquatic systems.

The enrichment factor (EF) is a widely used metric for determining how much the presence of an element in a sampling media has increased relative to average natural abundance because of human activity. Calculation of an EF requires the selection of both a background composition and a reference element, choices that can strongly influence the result of the calculation. Here, it is shown how carefully applied, classical principal component analysis (PCA) examined via biplots can guide the selections of background compositions and reference elements. Elemental data were treated using the centered log ratio (CLR) transformation, and multiple subsets of major and trace elements were examined to gain different perspectives. The methodology was applied to a dataset of elemental soil concentrations from around breccia pipe uranium mines in Arizona, U.S.A., with most samples collected via incremental sampling methodology. Storage of ore at the surface creates the potential for wind dispersal of ore-derived material. Uranium was found to be the best individual tracer of dispersal of ore-derived material to nearby soils, with EF values up to 75. Sulfur, As, Mo, and Cu were also enriched but to lesser degrees. The results demonstrate several practical benefits of a PCA in these situations: (1) the ability to identify one or more elements best suited to distinguish a specific source of enrichment from background composition; (2) understanding how background compositions vary within and between sites; (3) identification of samples containing enriched or anthropogenic materials based upon their integrated, multi-element composition. Calculating the most representative EF values is useful for numerical assessment of enrichment, whether anthropogenic or natural. As shown here, however, the PCA and biplot method provide a visual approach that integrates information from all elements for a given subset of data in a manner that yields geochemical insights beyond the power of the EF.

This work explores the use of Raman micro-spectroscopy to determine sources of airborne particulate matter collected on PM₂.₅ air filters in Imperial Valley, California. The goal is to examine if nearby soil is a potential source of particles sampled on air filters deployed in an urbanized desert area during events of unusually high PM₂.₅ excursions. Particle specific composition information can be an indicator of potential origin. This can provide insights into the source of unexpectedly high proportion of large particles sampled on PM₂.₅ filters in the vicinity of Imperial Valley. The measured spectral correspondence between the filter and soil particles, in the size range of 2.5–10 μm, is consistent with windblown dust being a likely source of the larger (>2.5 μm) particles collected on the PM₂.₅ filters. Additionally, these particles were identified as components of commonly occurring crustal minerals in the vicinity of the sampling site, such as iron oxides, hydroxides, sulfides, titanium dioxides and aluminosilicates. A substantial portion of the analyzed filter particles displayed a strong broadband fluorescence signal, which is consistent with the presence of organic matter and has been recognized as a marker for soil related origin of the filter particles. Elemental carbon (soot) was found to be prevalent among the particles as well, suggesting the existence of combustion related sources. Comparison between a heavily loaded filter sample and a filter with a more typical, lower loading did not show any obvious difference in chemical compositions. In both cases the particles appeared to be of crustal origin with the prevalence of elemental carbon. The primary difference between these two filter samples appear to be their particle size distribution - the heavily loaded filter sample contained greater proportion of large particles (>2.5 μm), and was more consistent with spectral signature of soils analyzed from the region.

Biochar has been used to remove heavy metals from aqueous solutions. In this study, a sulfurized wood biochar (SWB) by direct impregnation with elemental sulfur was produced and evaluated along with pristine wood biochar (WB) for adsorption characteristics and mechanism of mercury. Mercury adsorption by WB and SWB was well described by Langmuir model and pseudo second order model and the maximum adsorption capacities of WB and SWB were 57.8 and 107.5 mg g⁻¹, respectively. Intraparticle diffusion model showed that mercury adsorption was fast due to boundary layer and slow adsorption due to diffusion into biochar pores. Although, mercury adsorption by both WB and SWB was predominantly influenced by the pH, temperature, salt concentration, and biochar dosage, the SWB showed a relatively stable mercury adsorption compared to WB under different conditions, suggesting the strong affinity of SWB for mercury. The XPS analysis showed different adsorption mechanisms of mercury between WB and SWB. In particular, mercury adsorption in WB was due to Hg-Cπ bond formation and interaction with carboxyl and hydroxyl groups, whereas in SWB it is primarily due to mercury interaction with C-SOₓ-C and thiophenic groups in addition to Hg-Cπ bond formation and interaction with carboxyl groups. The SEM-EDS mapping also demonstrated that mercury in SWB was related to carbon, oxygen and sulfur. Overall, the sulfurized biochar was effective for removing mercury from aqueous solution, and its direct production through pyrolysis with elemental sulfur impregnation of wood chips could make it an economic option as absorbent for treating mercury-rich wastewater.

Dissimilatory nitrate reduction to ammonia (DNRA) is an important nitrate reduction pathway in lake sediments; however, little is known about the biotic factors driving the DNRA potential rates and contributions to the fate of nitrate. This study reports the first investigation of DNRA potential rates and contributions in lake sediments linked to DNRA community structures. The results of ¹⁵N isotope-tracing incubation experiments showed that 12 lakes had distinct DNRA potentials, which could be clustered into 2 groups, one with higher DNRA potentials (rates varied from 2.7 to 5.0 nmol N g⁻¹ h⁻¹ and contributions varied from 27.5% to 35.4%) and another with lower potentials (rates varied from 0.6 to 2.3 nmol N g⁻¹ h⁻¹ and contributions varied from 8.1% to 22.8%). Sediment C/N and the abundance of the nrfA gene were the key abiotic and biotic factors accounting for the distinct DNRA potential rates, respectively. A high-throughput sequencing analysis of the nrfA gene revealed that the sediment C/N could also affect the DNRA potential rates by altering the ecological patterns of the DNRA community composition. In addition, the interactions between the DNRA community and the denitrifying community were found to be obviously different in the two groups. In the higher DNRA potential group, the DNRA community mainly interacted with heterotrophic denitrifiers, while in the lower DNRA potential group, both heterotrophic and sulfur-driven autotrophic denitrifiers might cooperate with the DNRA community. The present study highlighted the role of the sulfur-driven nitrate reduction pathway in C-limited sediments, which has always been overlooked in freshwater environments, and gave new insights into the molecular mechanism influencing the fate of nitrate.