Intertidal bivalves are periodically exposed in air. It is tempting to speculate that the organisms would temporarily escape from contaminants when they are out of water and thus have lower risks. In this study, we tested this speculation by investigating cadmium (Cd) toxicokinetics in an intertidal mussel, Xenostrobus atratus, under the effects of tidal exposure using simulated tidal regimes. The uptake rate constant (kᵤ) of Cd ranged from 0.045 L g⁻¹ d⁻¹ to 0.109 L g⁻¹ d⁻¹, whereas the elimination rate constant (kₑ) of Cd ranged from 0.029 d⁻¹ to 0.091 d⁻¹. Cd bioaccumulation was slightly higher in the continuously immersed mussels than the alternately immersed mussels, but much lower than what would be expected if assuming bioaccumulation being proportional to immersion duration. Cd uptake was observed even when mussels were exposed in air, due to uptake of Cd dissolved in mantle cavity fluid and internalization of Cd adsorbed on mussel tissues. Overall, tidal height showed limited effects on Cd bioaccumulation, consistent with the trend of Cd concentrations found in X. atratus collected from different tidal heights. The mantle cavity uptake mechanism is expected to be applicable to other contaminants and bivalves, and should have important implications in risk assessments for intertidal environment.

Sulfate radical (SO₄⁻)-based advanced oxidation processes (SR-AOPs) are promising in-situ chemical oxidation technologies widely applied for soil/groundwater remediation. The presence of non-target water constituents may interfere the abatement of contaminants by SR-AOPs as well as result in the formation of unintended byproducts. Herein, we reported the formation of toxic chloronitrophenols during thermally activated persulfate oxidation of 2-chlorophenol (2CP) in the presence of nitrite (NO₂⁻). 2-Chloro-4-nitrophenol (2C4NP) and 2-chloro-6-nitrophenol (2C6NP) were identified as nitrated byproducts of 2CP with total yield up to 90%. The formation of nitrated byproducts is a result of coupling reaction between 2CP phenoxyl radical (ClPhO) and nitrogen dioxide radical (NO₂). As a critical step, the formation of ClPhO was supported by density functional theory (DFT) computation. Both 2C4NP and 2C6NP could convert to 2-chloro-4,6-dinitrophenol (2C46DNP) upon further treatment via a denitration-renitration process. The formation rate of 2C4NP and 2C6NP was closely dependent on the concentration of NO₂⁻, solution pH, and natural water constituents. ECOSAR calculation suggests that chloronitrophenols are generally more hydrophobic and ecotoxic than 2CP. Our result therefore reveals the potential risks in the abatement of chlorophenols by SR-AOP, particularly when high level of NO₂⁻ is present in water matrix.

In this study, we explored the influence of two metal oxide nanoparticles, nano CuO and nano ZnO (10, 50, 250 mg/kg), on accumulation of bifenthrin (100 μg/kg) in earthworms (Eisenia fetida) and its mechanism. The concentrations of bifenthrin in earthworms from binary exposure groups (bifenthrin + CuO and bifenthrin + ZnO) reached up to 23.2 and 28.9 μg/g, which were 2.65 and 3.32 times of that in bifenthrin exposure group without nanoparticles, respectively, indicating that nanoparticles facilitated the uptake of bifenthrin in earthworms. The contents of biomarkers (ROS, SOD, and MDA) in earthworms indicated that nanoparticles and bifenthrin caused damage to earthworms. Ex vivo test was utilized to investigate the toxic effects of the pollutants to cell membrane of earthworm coelomocytes and mechanism of increased bifenthrin accumulation. In ex vivo test, cell viability in binary exposure groups declined up to 30% and 21% compared to the control group after 24 h incubation, suggesting that coelomocyte membrane was injured by the pollutants. We conclude that nanoparticles damage the body cavity of earthworms, and thus lead to more accumulation of bifenthrin in earthworms. Our findings provide insights into the interactive accumulation and toxicity of nanoparticles and pesticides to soil organisms.

Nitrogen (N) plays an important role in agriculture crop production but the increasing application of nitrogen increases the possibilities of groundwater contamination through nitrate leaching. Nitrate leaching is the inevitable part of agriculture production which occurs during nitrogen fertilization. Hence, the quantification of nitrogen fertilizer is required to reduce nitrate leaching. In this study, nitrogen transformation and transport such as ammonium (NH₄⁺) and nitrate (NO3−) at different soil depths and maize crop growth stages were measured during field experiments for two sowing dates (timely and delay) and four N fertilization levels under irrigated (year 2013 and 2014) and rainfed (year 2012 and 2014) conditions for maize crop. NH₄⁺, NO3− and total nitrogen concentrations were measured using spectrophotometer at 410 nm and Kjeldahl method at varying soil depths and maize crop growth stages. Thereafter, nitrogen balance approach was used to estimate the NO3− leaching. Results indicated that NO3− leaching in irrigated condition was higher 109% in N₇₅, 179% in N₁₀₀, and 292% in N₁₂₅ level respectively in comparison to the N₀ level in timely sowing date, while in delayed sowing date, leaching was higher 54% in N₇₅, 123% in N₁₀₀, and 184% in N₁₂₅ level respectively in comparison to N₀ level. In rainfed, the NO3− leaching was higher 30% in N₆₀, 59% in N₈₀, and 99% in N₁₀₀ level respectively in comparison to N₀ level for the timely sowing date, while in delayed sowing, leaching was higher 23% in N₆₀, 44% in N₈₀, and 78% in N₁₀₀ level respectively in comparison to N₀ level. The results indicate that leaching losses were less in timely sowing dates for both rainfed and irrigated maize. The study further reveals that sowing dates combination with N levels could be an effective management strategy to reduce NO3− leaching by minimizing the N fertilization.

With the development of modern industry, the problem of cadmium (Cd) pollution cannot be ignored and its toxicity has caused great personal injury to humans. Poly (ADP-ribose) polymerase 1 (PARP-1) protein is a research hotspot in recent years, the research we have published shows that 5 μM of Cd-treated NRK-52E cells activated PARP-1, but the specific effects of PARP-1 on DNA damage and cell cycle is unclear. Therefore, the purpose of this study is to reveal the effect of Cd on DNA damage and cell cycle arrest in NRK-52E cells, in addition, to investigate the role of PARP-1 in mediating this effect. Western blotting, comet assay, QRT-PCR, immunofluorescence, and co-immunoprecipitation were used to detect DNA damage and cell cycle-associated protein expression. Flow cytometry was used to assess cell cycle distribution and the apoptosis rates. Results showed that after the increase in treatment time and Cd concentration, the degree of DNA damage was significantly increased, and a transition from G0/G1 to S phase arrest was observed. In addition, inhibition of PARP-1 expression exacerbated cell damage and cell cycle arrest when DNA damage was low, but attenuated cell damage and even cell cycle arrest when DNA damage was severe. These findings in this study indicate that Cd causes DNA damage in NRK-52E cells, leading to cell cycle arrest at different phases depending on the degree of DNA damage. Moreover, PARP-1 plays an important role in mediating this effect, when DNA damage is low, it functions in DNA repair, however, when DNA damage is severe, it aggravates cell damage and induces cell death.

Vehicular non-exhaust emissions account for a significant share of atmospheric particulate matter (PM) pollution, but few studies have successfully quantified the contribution of non-exhaust emissions via real-world measurements. Here, we conduct a comprehensive study combining tunnel measurements, laboratory dynamometer and resuspension experiments, and chemical mass balance modeling to obtain source profiles, real-world emission factors (EFs), and inventories of vehicular non-exhaust PM emissions in Chinese megacities. The average vehicular PM₂.₅ and PM₁₀ EFs measured in the four tunnels in four megacities (i.e., Beijing, Tianjin, Zhengzhou, and Qingdao) range from 8.8 to 16.0 mg km⁻¹ veh⁻¹ and from 37.4 to 63.9 mg km⁻¹ veh⁻¹, respectively. A two-step source apportionment is performed with the information of key tracers and localized profiles of each exhaust and non-exhaust source. Results show that the reconstructed PM₁₀ emissions embody 51–64% soil and cement dust, 26–40% tailpipe exhaust, 7–9% tire wear, and 1–3% brake wear, while PM₂.₅ emissions are mainly composed of 59–80% tailpipe exhaust, 11–31% soil and cement dust, 4–10% tire wear, and 1–5% brake wear. Fleet composition, road gradient, and pavement roughness are essential factors in determining on-road non-exhaust emissions. Based on the EFs and the results of source apportionment, we estimate that the road dust, tire wear, and brake wear emit 8.1, 2.5, and 0.8 Gg year⁻¹ PM₂.₅ in China, respectively. Our study highlights the importance of non-exhaust emissions in China, which is essential to assess their impacts on air quality, human health, and climate and formulating effective controlling measures.

Air quality management is underpinned by continuous measurements of concentrations of target air pollutants in monitoring stations. Although many approaches for optimizing the number and location of air quality monitoring stations are described in the literature, these are usually focused on dense networks. However, there are small and medium-size urban areas that only require one monitoring station but also suffer from severe air pollution. Given that target pollutants are usually measured at the same sampling points; it is necessary to develop a methodology to determine the optimal location of the single station. In this paper, such a methodology is proposed based on maximizing an objective function, that balances between different pollutants measured in the network. The methodology is applied to a set of data available for the city of Cartagena, in southeast Spain. A sensitivity analysis reveals that 2 small areas of the studied city account for 80% of the optimal potential locations, which makes them ideal candidates for setting up the monitoring station. The methodology is easy to implement, robust and supports the decision-making process regarding the siting of fixed sampling sites.

Large amounts of non-biodegradable plastics are currently deposited on beach-dune systems, and biodegradable plastics could enter these already declining habitats in coming years. Yet, the impacts of plastics on vegetative recruitment, a plant strategy playing a key role in dune stabilization, are unknown. Whether these pollutants interact with increased atmospheric nitrogen (N) deposition, a major global driver of plant biodiversity loss, in affecting plant communities of such nutrient-poor habitats, and how plant-plant interactions mediate their effects need to be explored. In a one-year field experiments, we examined individual and combined effects of plastic (non-biodegradable, biodegradable), N deposition (ambient, elevated) and biotic condition (no interaction, interaction with a conspecific or with a hetero-specific) on the colonization success and growth of vegetative propagules of dune plants. Thinopyrum junceum and Sporobolus pumilus were chosen as models because they co-occur along Mediterranean dunes and differ in ecological role (dune- vs. non dune-building) and photosynthetic pathway (C3 vs. C4). For both species, survival probability was reduced by non-biodegradable plastic and elevated N by up to 100%. Thinopyrum junceum survival was also reduced by S. pumilus presence. Elevated N and biodegradable plastic reduced T. junceum shoot biomass when grown alone and with a conspecific, respectively; these factors in combination mitigated their negative individual effects on root biomass. Biodegradable plastic increased S. pumilus shoot and root biomass, and in combination with elevated N caused a greater biomass investment in belowground (root plus rhizome) than aboveground organs. Non-biodegradable plastic may be a further threat to dune habitats by reducing plant colonization. Biodegradable plastic and increased N deposition could favour the generalist S. pumilus and hinder the dune-building T. junceum. These findings highlight the urgency of implementing measures for preventing plastic deposition on beaches and reducing N input.

Recently, the frequent occurrence of haze with aerosol pollution in China has attracted worldwide attention. Air pollutant emissions in conjunction with changing meteorological conditions create environment pollution in China. Aerosol pollution is spatially centralized in four regions of China, including the North China Plain, Yangtze River Delta, Pearl River Delta, and Sichuan Basin. In this observational study, a new center of aerosol pollution was identified in the Twain-Hu Basin (THB), covering the Hubei and Hunan provinces in central China. Based on the analysis of 19 years of satellite remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS), the THB experiences high aerosol optical depth (AOD) values exceeding 0.9. The fine mode fraction (FMF) values below 0.3 were also detected over the aerosol polluted THB region, where aerosol pollution was dominated by the mixed aerosol type. This reflects the role of intense human activities and the unique aerosol processes involved in the regional aerosol pollution over central China. The interannual AOD variations for THB present an increasing trend (mostly >0.02 yr⁻¹) between 2000 and 2011 and a significant descending trend (mostly < -0.06 yr⁻¹) between 2011 and 2018. This inverse trends in AOD with an overall increasing trend in FMF characterizes the past 19 years. This highlights the contribution of the increase in submicron particles and meteorological effects to the regional aerosol concentrations during recent years when considering the reduced anthropogenic aerosol emissions in the THB.

The surface organic horizons in forest soils have been affected by air and soil pollutants, including potentially toxic elements (PTEs). Monitoring of PTEs requires a large number of samples and adequate analysis. Visible–near infrared (vis–NIR: 350–2500 nm) spectroscopy provides an alternative method to conventional laboratory measurements, which are time-consuming and expensive. However, vis–NIR spectroscopy relies on an empirical calibration of the target attribute to the spectra. This study examined the capability of vis–NIR spectra coupled with machine learning (ML) techniques (partial least squares regression (PLSR), support vector machine regression (SVMR), and random forest (RF)) and a deep learning (DL) approach called fully connected neural network (FNN) to assess selected PTEs (Cr, Cu, Pb, Zn, and Al) in forest organic horizons. The dataset consists of 2160 samples from 1080 sites in the forests over all the Czech Republic. At each site, we collected two samples from the fragmented (F) and humus (H) organic layers. The content of all PTEs was higher in horizon H compared to F horizon. Our results indicate that the reflectance of samples tended to decrease with increased PTEs concentration. Cr was the most accurately predicted element, regardless of the algorithm used. SVMR provided the best results for assessing the H horizon (R² = 0.88 and RMSE = 3.01 mg/kg for Cr). FNN produced the best predictions of Cr in the combined F + H layers (R² = 0.89 and RMSE = 2.95 mg/kg) possibly due to the larger number of samples. In the F horizon, the PTEs were not predicted adequately. The study shows that PTEs in forest soils of the Czech Republic can be accurately estimated with vis–NIR spectra and ML approaches. Results hint in availability of a large sample size, FNN provides better results.