Recently, portable monitors have been increasingly used to quantify air pollutant concentrations at high spatiotemporal resolution. A sampling campaign was conducted to measure the fine particulate matter (PM2.5) and carbon monoxide (CO) exposure concentrations in transport microenvironments (TMEs) in Hong Kong in January and June 2015 using TSI DustTrak and Q-Trak portable monitors. The objectives were to: (1) calibrate DustTrak and Q-Trak; (2) evaluate variability between seasons and microenvironments; (3) estimate indoor/outdoor relationships; and (4) determine minimum sample size. Calibration equations, obtained through side-by-side measurement against stationary reference methods in winter and summer, were applied to correct the measured PM2.5 data set. In general, PM2.5 concentrations in all TMEs were significantly higher in winter than in summer. The mean PM2.5 concentration in winter was lower for underground sections of the Mass Transit Railway (MTR) metro system (31 μg/m3) than for other TMEs, whereas in summer TMEs had mean PM2.5 concentrations in the range of 10–15 μg/m3, with above-ground MTR train as an exception, at 23 μg/m3. PM2.5 concentrations measured in TMEs were strongly correlated with nearby air quality monitoring stations (AQMSs) measurements in winter, but in summer there was little correlation. The minimum sample size estimates varied more among TMEs in summer versus winter because of the differences in PM2.5 concentration distributions related to changes in ambient PM2.5 concentrations and ventilation practices. This study provides a feasible protocol on the calibration and application of portable monitors in TME air quality measurement and develops a method for estimating minimum sample size.

Phytate is abundant in soils, which is stable and unavailable for plant uptake. However, it occurs in root exudates of As-hyperaccumulator Pteris vittata (PV). To elucidate its effect on As uptake and growth, P. vittata was examined on agar media (63 μM P) containing 50 μM As and/or 50 or 500 μM phytate with non As-hyperaccumulator Pteris ensiformis (PE) as a congeneric control. Phytate induced efficient As and P uptake, and enhanced growth in PV, but had little effects on PE. The As concentrations in PV fronds and roots were 157 and 31 mg kg−1 in As50+phytate50, 2.2- and 3.1-fold that of As50 treatment. Phosphorus uptake by PV was reduced by 27% in As treatment than the control (P vs. P + As) but increased by 73% comparing phytate500 to phytate500+As, indicating that PV effectively took up P from phytate. Neither As nor phytate affected Fe accumulation in PV, but phytate reduced root Fe concentration in PE (46–56%). As such, the increased As and P and the unsuppressed Fe uptake in PV probably promoted PV growth. Thus, supplying phytate to As-contaminated soils may promote As uptake and growth in PV and its phytoremediation ability.

Microbial methylation and demethylation are central to arsenic's (As) biogeochemical cycling. Here, the transformations of monomethylarsonic acid (MMA(V)) (50 mg L−1) for 15 days in cells of As-methylating fungi, Fusarium oxysporum CZ-8F1, Penicillium janthinellum SM-12F4, and Trichoderma asperellum SM-12F1, were evaluated, and trace concentrations of As(III) and As(V) were observed in fungal cell extracts. Trace amounts of DMA(V) were also detected in MMA(V) and P. janthinellum SM-12F4 incubations. In situ X-ray absorption near edge structure (XANES) indicated that after exposure to MMA(V) (500 mg L−1) for 15 days, 28.6–48.6% of accumulated As in fungal cells was DMA(V), followed by 18.4–30.3% from As(V), 0–28.1% from As(III), and 4.8–28.9% from MMA(V). The concurrent methylation and demethylation of As occurs in fungal cells. Furthermore, a majority of proteins involved in metabolism, transport, ATP activity, biosynthesis, signal transduction, DNA activity, translation, and oxidative stress were upregulated in T. asperellum SM-12F1 cells after MMA(V) exposure compared to As(III), As(V), and DMA(V). The detoxification process of T. asperellum SM-12F1 was As species-specific. Methylenetetrahydrofolate reductase (R7YMH0) donation of a methyl group for S-adenosylmethionine (SAM) generation significantly increased following MMA(V) exposure.

Primitive electronic waste (e-waste) recycling releases large amounts of organic pollutants and heavy metals into the environment. As crucial moderators of geochemical cycling processes and pollutant remediation, soil microbes may be affected by these contaminants. We collected soil samples heavily contaminated by e-waste recycling in China and Pakistan, and analyzed the indigenous microbial communities. The results of this work revealed that the microbial community composition and diversity, at both whole and core community levels, were affected significantly by polycyclic aromatic hydrocarbons (PAHs), polybrominated diphenyl ethers (PBDEs) and heavy metals (e.g., Cu, Zn, and Pb). The geographical distance showed limited impacts on microbial communities compared with geochemical factors. The constructed ecological network of soil microbial communities illustrated microbial co-occurrence, competition and antagonism across soils, revealing the response of microbes to soil properties and pollutants. Two of the three main modules constructed with core operational taxonomic units (OTUs) were sensitive to nutrition (total organic carbon and total nitrogen) and pollutants. Five key OTUs assigned to Acidobacteria, Proteobacteria, and Nitrospirae in ecological network were identified. This is the first study to report the effects of e-waste pollutants on soil microbial network, providing a deeper understanding of the ecological influence of crude e-waste recycling activities on soil ecological functions.

Neurotoxic methylmercury (MMHg) is formed from inorganic divalent mercury (Hg2+). However, it is poorly understood to what extent different mercury (Hg) pools contribute to existent MMHg levels. In this study, ambient concentrations of total Hg (THg) and MMHg as well as rates of methylation and demethylation were measured simultaneously in sediments with and without salt-marsh plant vegetation, which were collected in Guadiana and Tagus estuaries, Portugal. Concurrent processes of Hg methylation and MMHg demethylation were directly monitored and compared by spiking sediments cores with stable isotope tracers of 199Hg2+ and CH3201Hg+ followed by gas chromatographic separation and isotope-specific detection using inductively coupled plasma mass spectrometry. Compared to the Guadiana estuary, where concentrations were comparatively low, THg and MMHg levels varied between vegetated and non-vegetated sediments collected at the Rosário site (ROS) of the Tagus estuary. Methylation (KM) and demethylation rates (KD) were also different between estuaries being dependent on the presence of vegetation. In addition, the type of macrophyte species influenced KM and KD values. In fact, the highest KM value was found in Sarcocornia fruticosa vegetated sediments at the Castro Marim site in Guadiana (CM, 0.160 day−1) and the lowest KM was observed in non-vegetated sediments at the Alcochete site in Tagus (ALC, 0.009 day−1). KD varied by a factor of three among sites with highest rates of demethylation observed in non-vegetated sediments in Guadiana (12 ± 1.3 day−1, corresponding to a half-life of 1.4 ± 0.2 h). This study clearly shows that the presence of vegetation in sediments favors the formation of MMHg. Moreover, this effect might be site specific and further studies are needed to confirm the findings reported here.

In the current study, by combining ultra-high resolution (UHR) MS1 spectra, MS2 spectra, and derivatization, three hydroxylated isomers of 2-ethylhexyl tetrabromobenzoate (OH-TBB) were identified in Firemaster® 550 and BZ-54 technical products. Also, a new LC-UHRMS method, using atmospheric pressure chemical ionization (APCI), was developed for simultaneous analysis of OH-TBB, TBB, hydroxylated bis(2-ethylhexyl)-tetrabromophthalate (OH-TBPH) and TBPH in 23 samples of dust collected from houses in Saskatoon, SK, Canada. OH-TBBs were detected in 91% of samples, with a geometric mean concentration of 0.21 ng/g, which was slightly less than those of OH-TBPH (0.35 ng/g). TBB was detected in 100% of samples of dust with a geometric mean concentration of 992 ng/g. Significant (p < 0.001) log-linear relationships between concentrations of OH-TBBs, TBB, or OH-TBPHs and TBPH in dust support the hypothesis of a common source of these compounds. OH-TBBs were found to be strong agonists of peroxisome proliferator-activated receptor gamma (PPARγ) and weaker agonists of the estrogen receptor (ER), but no agonistic activity was observed with the androgen receptor (AR). Occurrence of OH-TBBs in technical products and house dust, together with their relatively strong PPARγ activities, indicated their potential risk to health of humans.

Concentrations of 19 PFASs in riverwater, coastal wastewater and effluents from WWTPs which were directly discharged into the Bohai Sea of China were measured and their inputs to this sea area were calculated accordingly. For riverwater samples, the total PFAS concentrations ranged from 13.1 to 69 238 ng/L. PFAS levels in riverwater collected from Liaoning Province were comparable to those from Shandong Province, while they were two orders of magnitude greater than those from Hebei Province and the city of Tianjin. The dominant PFAS patterns were spatially different. PFBS and PFOA were the predominant PFASs in riverwater samples at sites where fluorochemical industry parks are located in Liaoning Province and Shandong Province, respectively. For other sites, PFOA and PFOS were the most abundant PFASs. In contrast, the total PFAS concentrations in coastal wastewater and effluent samples ranged from 16.7 to 7 522 ng/L and from 13.1 to 319 ng/L, respectively. PFOA was dominant in these samples. Inputs of PFASs to the Bohai Sea via riverine flow, discharge of coastal wastewater and effluents were estimated to be 87.3 tons per year. As compared with coastal wastewater and effluent discharge, riverine input was a major source for the PFAS pollution in the Bohai Sea except for PFBS.

Three novel organic vermiculites (VER) modified by amphoteric surfactants (BS, SB and PBS) with different negatively charged groups (carboxylate, sulfonate and phosphate) were demonstrated and used for removal of bisphenol A (BPA) and tetrabromobisphenol A (TBBPA). The difference in the structure and surface properties of modified vermiculites were investigated using a series of characterization methods. BS and SB surfactant mainly adsorbed on the surface and hard to intercalate into the interlayer of VER, while both adsorption and intercalation occurred in PBS modification. This difference resulted in different packing density of surfactant and hydrophobicity according to the results of contact angle, and affect the adsorption capacities ultimately. The adsorption of two pollutants onto these modified vermiculites were very fast and well fitted with pseudo-second-order kinetic model and Langmuir isotherm. PBS-VER exhibited the highest adsorption capacity (92.67 and 88.87 mg g−1 for BPA and TBBPA, respectively) than other two modified vermiculites in this order PBS-VER > BS-VER > SB-VER. The ionic strength (Na+, Ca2+) and coexisting compounds (Pb2+, humic acid) have different effects on the adsorption. PBS-VER had a good reusability and could remove ionic (methylene blue and orange G) and molecular (BPA) pollutants simultaneously and effectively due to the function of amphoteric hydrophilic groups and alkyl chains. The results might provide novel information for developing low-cost and effective adsorbents for removal of neutral and charged organic pollutants.

Nine N-nitrosamines (i.e., N-nitrosomethylamine, N-nitrosodiethylamine (NDEA), N-nitrosodimethylamine (NDMA), N-nitrosodi-n-propylamine (NDPA), N-nitrosomorpholine (NMor), N-nitrosopyrrolidine (NPyr), N-nitrosopiperidine (NPip), N-nitorosodi-n-butylamine (NDBA), and N-nitrosodiphenylamine (NDPhA) in atmospheric PM2.5 collected in the fall season from an roadside site and a residential in Seoul, Korea have been analyzed using a newly developed method consisting of simple direct liquid extraction assisted by ultrasonication and subsequent quantification using a gas chromatography-triple quadrupole mass spectrometry (GC-TQMS). Excellent recovery values (92–100%) and method detection limits for the target compounds atmospheric PM samples could be achieved even without an evaporation step for sample concentration. The concentration of total N-nitrosamines in PM2.5 was ranged from 0.3 to 9.4 ng m−3 in this study; NDMA, NDEA, NDBA, NPyr, and NMor in PM2.5 were found to be the most frequently encountered compounds at the sampling sites. Since no industrial plant is located in Seoul, vehicle exhausts were considered major cause of the formation of nitrosamines in this study. The mechanisms how these compounds are formed and detected in the atmosphere are explained from the viewpoint of secondary organic aerosol. Considering the concentrations of N-nitrosamines and their associated potential health risks, a systematic monitoring of nitrosamines present in both ambient air and PM2.5 including seasonal and diurnal variations of selected sites (including potential precursor sources) should be carried out in the future. The proposed sample pretreatment method along with the analytical method will definitely help us perform the monitoring study.

This study investigated and compared wintertime air pollution and personal exposure in the rural northern and southern Chinese homes. Daily indoor and outdoor particle samples were simultaneously collected by using stationary samplers, and personal exposure was directly measured using portable carried samplers. The daily average concentrations of indoor and outdoor PM2.5 were 521 ± 234 and 365 ± 185 μg/m³ in the northern village, that were about 2.3–2.7 times of 188 ± 104 and 150 ± 29 μg/m³ in indoor and outdoor air in the southern villages. Particle size distribution was similar between indoor and outdoor air, and had relatively smaller difference between the two sites, relative to the particle mass concentration difference. PM2.5 contributed to ∼80% of the TSP mass, and in PM2.5, near 90% were PM1.0. In homes using electricity in the southern villages, outdoor air pollution could explain 70–80% of the variation in indoor air pollution. The daily exposure to PM2.5 measured using personal carried samplers were 451 ± 301 μg/m³ in the northern villages with traditional solid fuels used for daily cooking and heating, and in the southern villages without heating, the exposure to PM2.5 were 184 ± 83 and 166 ± 45 μg/m³, respectively, for the population using wood and electricity for daily cooking. Time-weighted daily average exposure estimated from area concentration and time spent indoor and outdoor was generally correlated the directly measured exposure.