Biomass burning (BB), such as, crop field burning during the post-harvest season, emits large amounts of air pollutants (e.g., PM₂.₅) that severely impact human health. However, it is challenging to evaluate the impact of BB on PM₂.₅ due to uncertainties in the size and location of sources as well as their temporal and spatial variability. This study focused on the impacts of BB on local pollution as well as the long-range transport of PM₂.₅ in Northeast Asia resulting from a huge field BB event in Northeast China during the autumn of 2014. Air quality simulations using the Community Multiscale Air Quality (CMAQ) model were conducted in the year 2014 over the horizontal domains covering Northeast Asia, including the Japanese mainland. In the baseline simulation (Base), field BB emissions were derived from Fire INventory from NCAR (FINN) v1.5 for the year 2014. The model reasonably captured the daily mean PM₂.₅ mass concentrations, however, it underestimated concentrations in autumn around Northeast China where irregular field BB following the harvest occurred frequently. To address the underestimation of emissions from BB sources in China, another simulation with boosted BB sources from cropland area (FINN20_crop) was conducted in addition to the Base simulation. The model performance of FINN20_crop was significantly improved and showed smaller biases and higher indices of agreement between simulated and observed values in comparison to those of Base. To evaluate long-range transport of PM₂.₅ from BB sources in China towards Japan, CMAQ with brute-force method (CMAQ/BFM)-estimated BB contributions for Base and FINN20_crop cases were compared with Positive Matrix Factorization (PMF)-estimated BB contributions at Noto Peninsula in Japan. The CMAQ/BFM-estimated contributions from FINN20_crop were in greater agreement with the PMF-estimated contributions. The comparison of BB contributions estimated by the two contrasting models also indicated large underestimations in the current BB emission estimates.

The low-cost and compact size of light-scattering-based particulate matter (PM) sensors provide an opportunity for improved spatiotemporally resolved PM measurements. However, these inexpensive sensors have limitations and need to be characterized under realistic conditions. This study evaluated two Plantower PMS (particulate matter sensor) 1003s and two PMS 5003s outdoors in Salt Lake City, Utah over 320 days (1/2016–2/2016 and 12/2016–10/2017) through multiple seasons and a variety of elevated PM2.5 events including wintertime cold-air pools (CAPs), fireworks, and wildfires. The PMS 1003/5003 sensors generally tracked PM2.5 concentrations compared to co-located reference air monitors (one tapered element oscillating microbalance, TEOM, and one gravimetric federal reference method, FRM). The different PMS sensor models and sets of the same sensor model exhibited some intra-sensor variability. During winter 2017, the two PMS 1003s consistently overestimated PM2.5 by a factor of 1.89 (TEOM PM2.5<40 μg/m3). However, compared to the TEOM, one PMS 5003 overestimated PM2.5 concentrations by a factor of 1.47 while the other roughly agreed with the TEOM. The PMS sensor response also differed by season. In two consecutive winters, the PMS PM2.5 measurements correlated with the hourly TEOM measurements (R2 > 0.87) and 24-h FRM measurements (R2 > 0.88) while in spring (March–June) and wildfire season (June–October) 2017, the correlations were poorer (R2 of 0.18–0.32 and 0.48–0.72, respectively). The PMS 1003s maintained high intra-sensor agreement after one year of deployment during the winter seasons, however, one PMS 1003 sensor exhibited a significant drift beginning in March 2017 and continued to deteriorate through the end of the study. Overall, this study demonstrated good correlations between the PMS sensors and reference monitors in the winter season, seasonal differences in sensor performance, some intra-sensor variability, and drift in one sensor. These types of factors should be considered when using measurements from a network of low-cost PM sensors.

The effect of exposure to vinyl chloride monomer (VCM) on susceptibility to hepatotoxicity in children is unknown, although experimental studies have demonstrated a significantly increased risk of hepatocellular carcinoma in rodents exposed to VCM in early life. Epidemiological studies have revealed a high prevalence of liver fibrosis and abnormal liver function in workers exposed to high VCM levels. We aimed to assess the association among urinary thiodiglycolic acid (TDGA) level, abnormal liver function, and hepatic fibrosis in school-aged children living near a petrochemical complex. A total of 303 school-aged (6–13 years) children within 10 km nearly a petrochemical complex was recruited in central Taiwan. First-morning urine and blood samples were collected from each subject, and urinary TDGA level was analyzed through liquid chromatography–tandem mass spectrometry. Liver function was determined by serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels. Hepatic fibrosis was assessed using the AST to platelet ratio index (APRI) and fibrosis-4 score (FIB-4). Risk of hepatotoxicity induced by TDGA exposure was estimated using multivariate logistic regression. The median (range, subclinically abnormal %) AST and ALT levels of all subjects were 26.0 (17.0–99.0, 25.7%) and 15.0 (7.0–211.0, 5.9%) IU/L, respectively. Children in the highest urinary TDGA quartile (≥160.0 μg/g creatinine) exhibited significantly elevated median AST levels compared with those in the lowest quartiles (<35.4 μg/g creatinine, p = 0.033). After adjustment for potential confounding factors, children in the highest quartiles (Q₄) of TDGA level had significantly increased odds ratio (OR) of subclinically abnormal AST (OR = 3.86; 95% confidence interval: 1.54–9.67) compared with those in the lowest quartile. A dose-response trend (p = 0.004) was observed. Our findings support the hypothesis that elevated urinary TDGA level in children living near petrochemical complex is associated with susceptibility to hepatotoxicity.

An anaerobic incubation was launched with varying nitrate (1, 5, 10 and 20 mM exogenous NaNO₃) and molybdate (20 mM Na₂MoO₄, a sulfate-reducing inhibitor) additions to investigate the characteristics of PCP dechlorination, as well as the reduction of natural co-occurring electron acceptors, including NO₃⁻, Fe(III) and SO₄²⁻, and the responses of microbial community structures under a unique reductive mangrove soil. Regardless of exogenous addition, nitrate was rapidly eliminated in the first 12 days. The reduction process of Fe(III) was inhibited, while that of SO₄²⁻ reduction depended on addition concentration as compared to the control. PCP was mainly degraded from orth-position, forming the only intermediate 2,3,4,5-TeCP by anaerobic microbes, with the highest PCP removal rate of average 21.9% achieved in 1 and 5 mM NaNO₃ as well as 20 mM Na₂MoO₄ treatments and the lowest of 7.5% in 20 mM NaNO₃ treatment. The effects of nitrate on PCP dechlorination depended on addition concentration, while molybdate promoted PCP attenuation significantly. Analyses of the Illumina sequencing data and the relative abundance of dominant microorganisms indicated that the core functional groups regulated PCP removal at genera level likely included Bacillus, Pesudomonas, Dethiobacter, Desulfoporosinus and Desulfovbrio in the nitrate treatments; while that was likely Sedimentibacter and Geosporobacter_Thermotalea in the molybdate treatment. Nitrate supplement but not over supplement, or addition of molybdate are suggested as alternative strategies for better remediation in the nitrate-deficient and sulfur-accumulated soil ecosystem contaminated by PCP, through regulating the growth of core functional groups and thereby coordinating the interaction between dechlorination and its coupled soil redox processes due to shifts of more available electrons to dechlorination. Our results broadened the knowledge regarding microbial PCP degradation and their interactions with natural soil redox processes under anaerobic soil ecosystems.

Irrigation of crop plants with microcystins (MCs) contaminated water could be a threat to human health via bioaccumulation. Despite the fact MCs bioaccumulation in crop plants is well documented, MCs depuration, as well as the mechanism involved remains unclear. The objectives of the present study were to investigate the bioaccumulation and depuration of microcystin-LR (MC-LR) in lettuce (Lactuca sativa L.) and spinach (Spinacia oleracea L.), as well as to explore the role of glutathione (GSH) biosynthesis in MC-LR depuration. The tested plants were irrigated with deionized water containing 10 μg L⁻¹ MC-LR for 12 days (bioaccumulation), and subsequently, with either deionized water only or deionized water containing 0.5 mM buthionine sulfoximine (BSO, a specific inhibitor of GSH biosynthesis) for 12 days (depuration). After bioaccumulation period, highest concentrations of MC-LR found in lettuce and spinach were 114.4 and 138.5 μg kg⁻¹ dry weight (DW) respectively. Depuration rates of MC-LR in lettuce and spinach were 9.5 and 8.1 μg kg⁻¹ DW d⁻¹, which deceased to 3.7 and 4.6 μg kg⁻¹ DW d⁻¹ in treatments with BSO application. GSH content in both lettuce and spinach were not significantly affected during depuration without BSO; whereas after treatment with BSO, GSH content significantly decreased by 36.0% and 24.7% in lettuce and spinach on 15 d, and the decrease remained on 18 d and 21 d in lettuce. Moreover, during the bioaccumulation period, activities of glutathione reductase (GR) and glutathione S-transferase (GST) were enhanced in both plants. Our results suggested that GSH biosynthesis played an important role in MC-LR depuration in the tested plants. Concerning human health risk, most of the estimated daily intake (EDI) values during the bioaccumulation period exceeded the tolerable daily intake (TDI) guideline. However, the risk could be alleviated by irrigating with MCs-free water for a certain amount of time before harvest.

An accurate estimation of PM2.5 (fine particulate matters with diameters ≤ 2.5 μm) concentration is critical for health risk assessment and generating air pollution control strategies. In this study, a hybrid remote sensing and machine learning approach, named RSRF model is proposed to estimate daily ground-level PM2.5 concentrations, which integrates Random Forest (RF), one of machine learning (ML) models, and aerosol optical depth (AOD), one of remote sensing (RS) products. The proposed RSRF model provides an opportunity for an adequate characterization of real-time spatiotemporal PM2.5 distributions at uninhabited places and complex surfaces. It also offers advantages in handling complicated non-linear relationships among a large number of meteorological, environmental and air pollutant factors, as well as ever-increasing environmental data sets. The applicability of the proposed RSRF model is tested in the Beijing-Tianjin-Hebei region (BTH region) during 2015–2017. Deep Blue (DB) AOD from Aqua-retrieved Collection 6.1 (C_61) aerosol products of Moderate Resolution Imaging Spectroradiometer (MODIS) is validated with Aerosol Robotic Network. The validation results indicate C_61 DB AOD has a high correlation with ground based AOD in the BTH region. The proposed RSRF model performed well in characterizing spatiotemporal variations of annual and seasonal PM2.5 concentrations. It not only is useful to quantify the relationships between PM2.5 and relevant factors such as DB AOD, meteorological and air pollutant variables, but also can provide decision support for air pollution control at a regional environment during haze periods.

Bacterial antibiotic resistance (BAR) is profoundly important to human health, but the environmental reservoirs of resistance determinants are poorly understood. BAR of biofilm and tap water were analyzed by using a water distribution simulator where different doses of chlorine and chloramine were used in this study. The results revealed that the disinfectants (≥2 mg/L) suppressed antibiotic resistant bacteria (ARB) in tap water and biofilms, while disinfected water and biofilms had a high relative abundance of ARB. The difference of ARB concentration and ARB percentage between the samples obtained from a disinfected pipeline and a non-disinfected pipeline became smaller over time. Because the water supply system is a unidirectional process, it is unclear how planktonic bacteria in water transfer BAR over time, although biofilm is suspected to play a role in this process. Compared with the biofilm samples without disinfectant, the disinfected biofilm had lower ICC and HPC/ICC percentage, lower AOC and AOC/TOC percentage, indicating that the disinfectant inhibited the bacteria growth in biofilm, and the disinfected biofilm had high proportion of non-culturable bacteria and low biodegradability, which affected BAR in biofilms. High throughput sequencing showed that in biofilms, the relative abundance of genera (uncultured_f_Rhodocyclaceae, Brevundimonas, and Brevibacillus in chlorinated systems, and Brevundimonas, Brevibacillus in chloraminated systems) with multiple antibiotic resistance and high abundance (up to 78.5%), were positively associated with disinfectant concentration and ARB percentage. The major prevalent genera in biofilms were also detected in tap water, suggesting that biofilm growth or biofilm detachment caused by external environmental factors will allow the movement of biofilm clusters with higher ARB concentration and percentage into bulk water, thereby increasing the antibiotic resistance of bacteria in tap water.

Jumping on the bed is a favorite behavior of children; however, no study has investigated the increased air pollutants resulting from jumping on the bed. Therefore, we aimed to investigate the elevated concentrations of particulate matter (PM) and bioaerosols from jumping on the bed and making the bed. Simulation of jumping on the bed and making the bed was performed at sixty schoolchildren's houses in Taiwan. PM10, PM2.5, PM1 (PM with aerodynamic diameter less than 10, 2.5, and 1 μm, respectively) and airborne bacteria, fungi and endotoxin concentrations were simultaneously measured over simulation and background periods. Our results show the increase of PM10, PM2.5, PM1, airborne bacteria and fungi through the behavior of jumping on the bed (by 414 μg m-3, 353 μg m-3, 349 μg m-3, 6569 CFU m-3 and 978 CFU m-3, respectively). When making the bed, the PM10, PM2.5, PM1, airborne bacteria and fungi also significantly increased by 4.69 μg m-3, 4.09 μg m-3, 4.15 μg m-3, 8569 CFU m-3, and 779 CFU m-3, respectively. Airborne endotoxin concentrations significantly increased by 21.76 EU m-3 following jumping on the bed and making the bed. Moreover, when jumping on the bed, higher PM2.5 and PM1 concentrations in houses with furry pets rather than no furry pets, and less airborne fungi in apartments than in townhouses were found. For making the bed, lower airborne fungi was found in houses using essential oils rather than no essential oils using. The airborne endotoxin concentrations were positively associated with furry pets and smokers in the homes and negatively correlated to the home with window opening with a statistical significance during the periods of jumping on the bed and making the bed. In conclusion, significant increases of PM and bioaerosols during jumping on the bed and making the bed may need to be concerned.

Dyeing wastewaters are toxic and carcinogenic to both aquatic life and human beings. Adsorption technology, as a facile and effective method, has been extensively used for removing dyes from aqueous solutions for decades. Numerous researchers have attempted to seek or design alternative materials for dye adsorption. However, using various novel adsorbents to remove dyes has not been extensively reviewed before. In this review, the key advancement on the preparation and modification of novel adsorbents and their adsorption capacities for dyes removal under various conditions have been highlighted and discussed. Specific adsorption mechanisms and functionalization methods, particularly for increasing adsorption capacities are discussed for each adsorbent. This review article mainly includes (1) the categorization, side effects and removal technologies of dyes; (2) the characteristics, advantages and limitations of each sort of adsorbents; (3) the functionalization and modification methods and controlling mechanisms; and (4) discussion on the problems and future perspectives about adsorption technology from adsorbents aspects and practical application aspects.

Microplastics in water environment and its ability to load various environmental pollutants have attracted wide attention in recent years. However, effect of microplastic size on the adsorption behavior of environmental pollutants and interaction mechanism has not been thoroughly explored. In this study, triclosan (TCS) was selected as model pollutant, and polyvinyl chloride (PVC) with different particle sizes (small size (<1 μm) is recorded as PVC-S and PVC-L means large particle size of about 74 μm) were used as the typical microplastics, the adsorption behavior of TCS on PVC was investigated by studying kinetics, isotherms, and other influencing factors, such as pH and salinity. The results indicate PVC-S has greater distribution coefficient kd values of TCS (1.35 L/g > 1.05 L/g) and stronger adsorption capacity (12.7 mg/g > 8.98 mg/g) compared with PVC-L, which may be due to higher specific surface area, stronger hydrophobicity and relatively small electronegative property of PVC-S. Moreover, the initial pH value and salinity of the solution played crucial role in the adsorption process. The distribution diffusion mechanisms (including liquid-film diffusion and intra-particle diffusion), hydrophobic interaction, electrostatic interaction, halogen bonding, and hydrogen bonding may be the important reasons for adsorption. These findings show that MPs with different particle sizes have vary adsorption behaviors and load capacities for environmental pollutants, which deserve our further concerned.