Rising of temperature in conjunction with acidification due to the anthropogenic climates has tremendously affected all aquatic life. Small changes in the surrounding environment could lead to physiological constraint in the individual. Therefore, this study was designed to investigate the effects of warm water temperature (32 °C) and low pH (pH 6) on physiological responses and growth of hybrid grouper (Epinephelus fuscoguttatus ♀ × Epinephelus lanceolatus ♂) juveniles for 25 days. Growth performance was significantly affected under warm water temperature and low-pH conditions. Surprisingly, the positive effect on growth was observed under the interactive effects of warm water and low pH exposure. Hybrid grouper exposed to the interactive stressor of warm temperature and low pH exhibited higher living cost, where HSI content was greatly depleted to about 2.3-folds than in normal circumstances. Overall, challenge to warm temperature and low pH induced protein mobilization as an energy source followed by glycogen and lipid to support basal metabolic needs.

Arsenic contamination of ground water is a worldwide issue, causing a number of ailments in humans. As an engineered and integrated solution, a hybrid vertical subsurface flow constructed wetland (VSSF-CW) amended with BCXZM composite (Bacillus XZM immobilized on rice husk biochar), was found effective for the bioremediation of arsenic contaminated water. Biological filter was prepared by amending top 3 cm of VSSF-CW bed with BCXZM. This filter scavenged ∼64% of total arsenic and removal efficiency of ∼95% was achieved by amended and planted (As + P + B) VSSF-CW, while non-amended (As + P) VSSF-CW showed a removal efficiency of ∼55%. The unplanted and amended (As + B) VSSF-CW showed a removal efficiency of ∼70%. The symbiotic association of Bacillus XZM, confirmed by SEM micrographs, significantly (p ≤ 0.05) reduced reactive oxygen species (ROS) and malondialdehyde (MDA) accumulation in Typha latifolia, hence, increasing the plant growth (2 folds). An increase in the indole acetic acid (IAA) and arsenic accumulation in plant was also observed in As + P + B system. The removal efficiency of the system was compromised after 4th consecutive cycle and 48 h was observed as optimum retention time. The FTIR-spectra showed the involvement of -N-H bond, carboxylic acids, –CH₂ stretching of –CH₂ and –CH₃, carbonyl groups, -C-H, C–O–P and C–O–C, sulphur/thiol and phosphate functional groups in the bio-sorption of arsenic by BCXZM filter. Our study is a first reported on the simultaneous phytoextraction and biosorption of arsenic in a hybrid VSSF-CW. It is proposed that BCXZM can be applied effectively in CWs for the bioremediation of arsenic contaminated water on large scale.

Ambient fine particulate matter (PM₂.₅) has been ranked as the sixth leading risk factor globally for death and disability. Modelling methods based on having access to a limited number of monitor stations are required for capturing PM₂.₅ spatial and temporal continuous variations with a sufficient resolution. This study utilized a land use regression (LUR) model with machine learning to assess the spatial-temporal variability of PM₂.₅. Daily average PM₂.₅ data was collected from 73 fixed air quality monitoring stations that belonged to the Taiwan EPA on the main island of Taiwan. Nearly 280,000 observations from 2006 to 2016 were used for the analysis. Several datasets were collected to determine spatial predictor variables, including the EPA environmental resources dataset, a meteorological dataset, a land-use inventory, a landmark dataset, a digital road network map, a digital terrain model, MODIS Normalized Difference Vegetation Index (NDVI) database, and a power plant distribution dataset. First, conventional LUR and Hybrid Kriging-LUR were utilized to identify the important predictor variables. Then, deep neural network, random forest, and XGBoost algorithms were used to fit the prediction model based on the variables selected by the LUR models. Data splitting, 10-fold cross validation, external data verification, and seasonal-based and county-based validation methods were used to verify the robustness of the developed models. The results demonstrated that the proposed conventional LUR and Hybrid Kriging-LUR models captured 58% and 89% of PM₂.₅ variations, respectively. When XGBoost algorithm was incorporated, the explanatory power of the models increased to 73% and 94%, respectively. The Hybrid Kriging-LUR with XGBoost algorithm outperformed the other integrated methods. This study demonstrates the value of combining Hybrid Kriging-LUR model and an XGBoost algorithm for estimating the spatial-temporal variability of PM₂.₅ exposures.

Trace elements (TEs) in the insoluble particles of surface snow are less affected by melting processes and can be used as environmental proxies to reveal natural and anthropogenic emissions. Here the first comprehensive study of the 16 TEs (Al, As, Ba, Bi, Cr, Cu, Fe, Mn, Ni, Pb, Sn, Sr, Ti, U, V, and Zn) in insoluble particles (>0.45 μm) from surface snow samples collected at Urumqi Glacier No. 1 (UG1), Eastern Tien Shan, China, from February 2008 to January 2010 were presented. Results show that concentrations of most insoluble particulate TEs (TEs ᵢₙₛₒₗ) in the snow were higher in summer while lower in winter, due to the increasing particle inputs and melting processes. The abundances of As, Cr, Cu, Ni, Pb, and Zn in some samples were higher than those in surrounding urban soils, which might due to these TEs have further anthropogenic input beyond the already contaminated re-suspended urban soil particles and TEs were mainly enriched in particles with small grain size. Based on enrichment factor (EF) and principal component analysis (PCA), our results suggest that eight TEs (Al, Fe, Ti, Ba, Mn, Sr, U, and V) mainly came from mineral dust, while the remaining eight TEs (As, Bi, Cr, Cu, Ni, Pb, Sn, and Zn) were affected by coal combustion, mining and smelting of non-ferrous metals, traffic emissions, and the steel industry. The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model suggests that pollutants might originate from Xinjiang province, Kazakhstan, and Kyrgyzstan. Moreover, UG1 received more significant inputs of particle-bound pollutants in summer than in winter due to the stronger convection and the prevailing valley wind that transports pollutants from the city of Urumqi.

Organic contaminations and heavy metals in soils cause large harm to human and environment, which could be remedied by planting specific plants. The biochars produced by crop straws could provide substantial benefits as a soil amendment. In the present study, biochars based on wheat, corn, soybean, cotton and eggplant straws were produced. The eggplant straws based biochar (ESBC) represented higher Cd and pyrene adsorption capacity than others, which was probably owing to the higher specific surface area and total pore volume, more functional groups and excellent crystallization. And then, ESBC amendment hybrid Ryegrass (Lolium perenne L.) cultivation were investigated to remediate the Cd and pyrene co−contaminated soil. With the leaching amount of 100% (v/w, mL water/g soil) and Cd content of 16.8 mg/kg soil, dosing 3% ESBC (wt%, biochar/soil) could keep 96.2% of the Cd in the 10 cm depth soil layer where the ryegrass root could reach, and it positively help root adsorb contaminations. Compared with the single planting ryegrass, the Cd and pyrene removal efficiencies significantly increased to 22.8% and 76.9% by dosing 3% ESBC, which was mainly related with the increased plant germination of 80% and biomass of 1.29 g after 70 days culture. When the ESBC dosage increased to 5%, more free radicals were injected and the ryegrass germination and biomass decreased to 65% and 0.986 g. Furthermore, when the ESBC was added into the ryegrass culture soil, the proportion of Cd and pyrene degrading bacteria Pseudomonas and Enterobacter significantly increased to 4.46% and 3.85%, which promoted the co−contaminations removal. It is suggested that biochar amendment hybrid ryegrass cultivation would be an effective method to remediate the Cd and pyrene co−contaminated soil.

Several populations of the amphipod, Hyalella azteca, have developed resistance to pyrethroid insecticides due to non-target exposure, but the dominance of the resistance trait is unknown. The current study investigated the dominance level of point mutations in natural populations of insecticide-resistant H. azteca and determined whether H. azteca from different clades with and without resistant alleles can hybridize and produce viable offspring. A parent generation (P₀) of non-resistant homozygous wild type H. azteca was crossbred with pyrethroid-resistant homozygous mutant animals and the tolerance of the filial 1 (F₁) generation to the pyrethroid insecticide, permethrin, was measured. Then the genotypes of the F₁ generation was examined to assure heterozygosity. The resistant parents had permethrin LC₅₀ values that ranged from 52 to 82 times higher than the non-resistant animals and both crossbreeding experiments produced heterozygous hybrid offspring that had LC₅₀ values similar to the non-resistant H. azteca parent. Dominance levels calculated for each of the crosses showed values close to 0, confirming that the L925I and L925V mutations were completely recessive. The lack of reproduction by hybrids of the C x D breeding confirmed that these clades are reproductively isolated and therefore introgression of adaptive alleles across these clades is unlikely. Potential evolutionary consequences of this selection include development of population bottlenecks, which may arise leading to fitness costs and reduced genetic diversity of H. azteca.

Acid rain is a serious threat to terrestrial ecosystems. To provide more accurate early warning information for acid rain prevention, urban planning, and travel planning, a novel air pollutant prediction model was proposed in this paper to predict NO₂ and SO₂. First, the data were decomposed into several sub-sequences by a complete ensemble empirical mode decomposition with adaptive noise. Second, the subsequences are reconstructed by variational mode decomposition and sample entropy. Then, the new subsequences are predicted by the extreme learning machine combined with the whale optimization algorithm. The empirical analysis was carried out through 8 data sets. According to the experimental results, three main conclusions can be drawn. First, the proposed model in this paper has excellent prediction performance and robustness. In all the comparison experiments, the R² and RMSE of the proposed model are the best among all the models. Second, data preprocessing is very necessary. After adding the decomposition algorithm, the average improvement levels of R² and RMSE were 897.57% and 50.78%, respectively. Third, the re-decomposition of IMF1 is an effective method to improve prediction accuracy. After the re-decomposition of IMF1, R² can be improved by 13.64% on average on the original basis, and RMSE can be reduced by 31.99% on average. The results of this study can provide a valuable reference for the research of air pollutant prediction. In future work, the application of the proposed model in other air pollutants or other regions can be explored.

The increased bioeconomy targets for the biomass share of renewable energy production across Europe should be met using land unsuitable for food production. Miscanthus breeding programs targeted the production of plants with a diverse range of traits allowing a wider utilization of land resources for biofuel production without competing with arable crops. These traits include increasing tolerances to drought, chilling, and to metal(loid)s excess. Two novel Miscanthus hybrids, GNT41 and GNT34, were compared against Miscanthus x giganteus (Mxg) on metal-contaminated arable land in Poland. This study aimed at evaluating their yield, biomass quality and quantifying seasonal differences in photosynthetic and transpiration parameters. A secondary objective was to identify key physiological mechanisms underlying differences in metal accumulation between the investigated plants. The new hybrids produced a similar yield to Mxg (13–15 t ha−1 yr−1), had shorter shoots, higher Leaf Area Index and stem number. Based on gas exchange measurements, GNT34 exhibited isohydric (water-conserving) behavior. The stomatal response to light of the new hybrids was at least twice as fast as that of Mxg, a trait that is often associated with increased seasonal water use efficiency. This contributed to the almost 40% reduction in shoot Pb and Cd concentrations for the new hybrids as compared to Mxg. This suggested that promoting stomatal regulation in conjunction with improved water conservation may be a target for improving plants for wider use on metals contaminated land.

Rice is one of the major pathways of arsenic (As) exposure in human food chain, threatening over half of the global population. Greenhouse pot experiments were conducted to examine the effects of Si application on iron (Fe) plaque formation, As uptake and rice grain As speciation in indica and hybrid rice genotypes with different radial oxygen loss (ROL) ability. The results demonstrated that Si significantly increased root and grain biomass. Indica genotypes with higher ROL induced greater Fe plaque formation, compared to hybrid genotypes and sequestered more As in Fe plaque. Silicon applications significantly increased Fe concentrations in iron plaque of different genotypes, but it decreased As concentrations in the roots, straws and husks by 28–35%, 15–35% and 32–57% respectively. In addition, it significantly reduced DMA accumulation in rice grains but not inorganic As accumulation. Rice of indica genotypes with higher ROL accumulated lower concentrations of inorganic As in grains than hybrid genotypes with lower ROL.

Low-methylesterified homogalacturonans have been suggested to play a role in the binding and immobilization of Pb in CW. Using root apices of hybrid aspen, a plant with a high phytoremediation potential, as a model, we demonstrated that the in situ distribution pattern of low-methylesterified homogalacturonan, pectin epitope (JIM5-P), reflects the pattern of Pb occurrence. The region which indicated high JIM5-P level corresponded with “Pb accumulation zone”. Moreover, JIM5-P was especially abundant in cell junctions, CWs lining the intercellular spaces and the corners of intercellular spaces indicating the highest accumulation of Pb. Furthermore, JIM5-P and Pb commonly co-localized.The observations indicate that low-methylesterified homogalacturonan is the CW polymer that determines the capacity of CW for Pb sequestration. Our results suggest a promising directions for CW modification for enhancing the efficiency of plant roots in Pb accumulation, an important aspect in the phytoremediation of soils contaminated with trace metals.