Clearing up whether spilled oil is mixed or not can strengthen the accuracy of oil spill identification. In the present study, the biomarkers in spilled oil samples were detected. The weathering modes of different types of diagnostic ratio and carbon isotope values of individual n-alkanes were also analyzed. The results showed that the diagnostic ratios of steroids, terpenes and aromatics, and weathering characteristics of carbon isotope composition (δ¹³C) of individual n-alkanes supported the idea that Dalian oil spill emerged from a single oil source. Furthermore, commonly used diagnostic ratios of n-alkanes indicated that the Dalian oil spill had undergone the oil mixing process. The different identifying outcomes indicate that some kinds of n-alkane-rich substance (such as oil dispersants) were mixed in the Dalian spilled oil and interfered with the routine diagnosis ratios of n-alkanes.

The advent of modern solar energy technologies can improve the costs of energy consumption on a global, national, and regional level, ultimately spanning stakeholders from governmental entities to utility companies, corporations, and residential homeowners. For those stakeholders experiencing the four seasons, accurately accounting for snow-related energy losses is important for effectively predicting photovoltaic performance energy generation and valuation. This paper provides an examination of a new, simplified approach to decrease snow-related forecasting error, in comparison to current solar energy performance models. A new method is proposed to allow model designers, and ultimately users, the opportunity to better understand the return on investment for solar energy systems located in snowy environments. The new method is validated using two different sets of solar energy systems located near Green Bay, WI, USA: a 3.0-kW micro inverter system and a 13.2-kW central inverter system. Both systems were unobstructed, facing south, and set at a tilt of 26.56°. Data were collected beginning in May 2014 (micro inverter system) and October 2014 (central inverter system), through January 2018. In comparison to reference industry standard solar energy prediction applications (PVWatts and PVsyst), the new method results in lower mean absolute percent errors per kilowatt hour of 0.039 and 0.055%, respectively, for the micro inverter system and central inverter system. The statistical analysis provides support for incorporating this new method into freely available, online, up-to-date prediction applications, such as PVWatts and PVsyst.

Pakistan is an agricultural country and due to the shortage of clean water, most of the irrigated area (32,500 ha) of Pakistan was supplied with wastewater (0.876 × 109 m³/year). Concentrations of heavy metals in radish (Raphanus sativus) and turnip (Brassica rapa) taken from vegetable fields in Sargodha, Pakistan, were measured. Untreated wastewater was used persistently for a long time to irrigate these vegetable fields. A control site was selected that had a history of fresh groundwater irrigation. Mean metal concentrations were found for irrigation water, soil, and vegetables. In irrigation water, concentrations of Mo and Pb at three sites and Se at sites II and III were higher than the recommended limits. In vegetables, concentrations of Mo and Pb were above the maximum permissible limits. High bioconcentration factor was observed for Zn (12.61 in R. sativus and 11.72 in B. rapa) at site I and high pollution load index was found for Pb (3.89 in R. sativus and 3.87 in B. rapa) at site II. The differences in metal concentrations found in samples depended upon different soil nature and assimilation capacities of vegetables at different sites which in turn depended upon different environmental cues. The entrance of metal and metalloids to human body may happen through different pathways; however, the food chain is the chief route through which metals are transferred from vegetables to individuals. Health risk index observed for metals, (Mo, As, Ni, Cu, and Pb) higher than 1 indicated high risk through consumption of these vegetables at three sites.

To minimize the risk of negative consequences for public health from fecal pollution in lakes, the continuous surveillance of microbiological water quality parameters, alongside other environmental variables, is necessary at defined bathing sites. Such routine surveillance may prove insufficient to elucidate the main drivers of fecal pollution in a complex lake/watershed ecosystem, and it may be that more comprehensive monitoring activities are required. In this study, the aims were to identify the hotspots and main driving factors of fecal pollution in a large shallow Central European lake, the Neusiedler See, and to determine to what degree its current monitoring network can be considered representative spatially. A stochastic and geostatistical analysis of a huge data set of water quality data (~ 164,000 data points, representing a 22-year time-series) of standard fecal indicator bacteria (SFIB), water quality and meteorological variables sampled at 26 sampling sites was conducted. It revealed that the hotspots of fecal pollution are exclusively related to sites with elevated anthropogenic activity. Background pollution from wildlife or diffuse agricultural run-off at more remote sites was comparatively low. The analysis also showed that variability in the incidence of SFIB was driven mainly by meteorological phenomena, above all, temperature, number of sunny hours, and wind (direction and speed). Due to antagonistic effects and temporal undersampling, the influence of precipitation on SFIB variance could not be clearly determined. Geostatistical analysis did reveal that the current spatial sampling density is insufficient to cover SFIB variance over the whole lake, and that the sites are therefore in the most part representative of local phenomena. Suggestions for the future monitoring and managing of fecal pollution are offered. The applied statistical approach may also serve as a model for the study of other such areas, and in general indicate a method for dealing with similarly large and spatiotemporally heterogeneous datasets.

This experiment was conducted in order to determine the effects of different concentrations of manganese (Mn) on the levels and correlations of multiple primary and secondary metabolites in Mentha aquatica. With this aim, four levels of Mn concentrations were used as follows: basic Hoagland’s solution (control), 40, 80, and 160 μM of Mn supplied as MnSO₄.H₂O. The results indicated that the biomass and the contents of photosynthetic pigments and soluble carbohydrates were higher in the plants that were treated with the moderate concentrations of Mn (40 and 80 μM) than the control and 160 μM-treated plants. On the other hand, the contents of flavonoids, anthocyanins, malonaldehyde (MDA), hydrogen peroxide (H₂O₂), and the activities of antioxidant enzymes (total superoxide dismutase (SOD), catalase (CAT), and peroxidase (POX)) were progressively increased with the enhancement of Mn concentration in the nutrient solution. In addition, there were clear differences in the content and chemical composition of essential oils among the control and treatment groups. In this study, 1,8-cineole, menthofuran, and β-caryophyllene were the most abundant constituents of essential oils in both the control and Mn-treated plants. The correlation analysis between pairs of the primary and secondary metabolites showed that there were positive and negative correlations among the variables when the Mn concentration was increased in the nutrient solution. These findings clearly display a positive effect of Mn up to 80 μM in the nutrient solution on the growth of M. aquatica.

In this paper, numerous studies on groundwater in Malaysia were reviewed with the aim of evaluating past trends and the current status for discerning the sustainability of the water resources in the country. It was found that most of the previous groundwater studies (44 %) focused on the islands and mostly concentrated on qualitative assessment with more emphasis being placed on seawater intrusion studies. This was then followed by inland-based studies, with Selangor state leading the studies which reflected the current water challenges facing the state. From a methodological perspective, geophysics, graphical methods, and statistical analysis are the dominant techniques (38, 25, and 25 %) respectively. The geophysical methods especially the 2D resistivity method cut across many subjects such as seawater intrusion studies, quantitative assessment, and hydraulic parameters estimation. The statistical techniques used include multivariate statistical analysis techniques and ANOVA among others, most of which are quality related studies using major ions, in situ parameters, and heavy metals. Conversely, numerical techniques like MODFLOW were somewhat less admired which is likely due to their complexity in nature and high data demand. This work will facilitate researchers in identifying the specific areas which need improvement and focus, while, at the same time, provide policymakers and managers with an executive summary and knowledge of the current situation in groundwater studies and where more work needs to be done for sustainable development.

Cadmium (Cd) pollution in rice and its transfer to food chain are cause of global concern. Application of zinc (Zn) can reduce Cd uptake by plants, as both these metals are generally antagonistic in soil–plant systems. In a field experiment on Cd-contaminated acid soil, we investigated the effectiveness of foliar application of Zn in minimizing Cd accumulation and its effect on the content of mineral nutrient elements in rice. The treatment was done at an early grain filling stag using 0.3 and 0.5% w/v ZnSO₄·7H₂O solution. The spray did not affect the grain yield of rice but decreased the Cd concentration in the root, straw, husk, and brown rice to some extent and increased the Zn concentration. Foliar application of 0.5% ZnSO₄ resulted in maximum Zn concentration and minimum Cd concentration in brown rice. However, the concentrations of P, K, Ca, Mg, Cu, and Mn in brown rice were not affected. The correlation between Cd and Zn concentrations in brown rice, husk, and root was significantly negative, and that between Cd and Mn concentrations in brown rice was significantly positive. The inhibition of Cd uptake resulted in a decrease in its concentration in brown rice after the treatments. Thus, the foliar application of a suitable concentration of Zn at the early grain filling stage could effectively minimize the Cd concentration while enhancing the Zn concentration in brown rice on Cd-contaminated acid soil.

Acrylonitrile (ACN) spills in marine environment have the potential to cause ecological hazards and consequences, but currently little is known about the disruptive effects of ACN on marine organisms. In the present study, we investigated the lethal and sublethal effects of ACN on juvenile flounder Paralichthys olivaceus. The results showed that the 96-h LC50 of ACN to P. olivaceus juveniles was 6.07 mg/L. The fish were then exposed to different sublethal concentrations (0.1, 0.2, and 0.4 mg/L) of ACN for 28 days and then transferred to clean seawater and keep in clean seawater for 14 days to simulate the conditions of a spill incident. Biomarkers (EROD, GST, SOD, AChE activity, and levels of LPO and DNA alkaline unwinding) were tested in liver and brain. The weight gain rates and specific growth rate of juvenile marine flounder exposed to ACN (≥ 0.1 mg/L) for 28 days decreased significantly, indicating that ACN had an inhibitory effect on juvenile growth. Deformity of fish tails was observed on individuals exposed to the highest concentration (0.4 mg/L ACN) for 14 days, and the malformation rate was 38% after 28-day exposure. The present study provides the first evidence that ACN causes inhibition of AChE activity in fish brain. Furthermore, the results showed that ACN can significantly inhibit SOD activity and cause lipid peroxidation and DNA damage in fish brain. The results indicated that brain is more sensitive to ACN toxicity compared to liver and provides a suitable tissue for biomonitoring. The biomarkers measured during the depuration period showed that the effects caused by ACN were reversible when the exposure concentration was lower than 0.4 mg/L. These results highlight the adverse effects of ACN in brain of fish, which should be considered in environmental risk assessment. Biomarkers including AChE activity, LPO, and DNA damage of brain tissue should be included in fish bioassays for toxic effect assessment of ACN spills.

Fine particulate matter (PM₂.₅) is a current environmental issue that has an impact on the global ecology. Vegetation is a known sink for PM₂.₅ deposition but the effects of these particles on plant growth, and specifically on plant photosynthesis by changing their leaf water potential, are still not well understood. This study aimed to determine and characterize possible relationships between PM₂.₅ and plant photosynthesis under different PM₂.₅ concentrations. Both indoor and outdoor measurements were carried out to evaluate the variation dynamics of net photosynthetic rate and stomatal conductance of four plant species with different leaf characteristics under different PM₂.₅ levels. A calibrated coupled model of photosynthesis and stomatal conductance was developed to estimate the relationship between plant photosynthesis and PM₂.₅ reliably. Net photosynthetic rate and stomatal conductance declined over time at elevated PM₂.₅, with large variations with PM₂.₅ concentrations. Using a calibrated model of photosynthesis coupled to stomatal conductance, we show that PM₂.₅ can influence plant photosynthesis that primarily occurs through the stomata on leaves. Although the effect of particles on plant photosynthesis was not as high as that of photosynthetically active radiation, temperature, and CO₂ concentration around the leaf, the effect from PM₂.₅ can be significant, in particular, in highly polluted atmospheres.

Soil erosion is a universal phenomenon on the Loess Plateau but it exhibits complex and typical mechanism which makes it difficult to understand soil loss laws on slopes. We design artificial simulated rainfall experiments including six rainfall intensities (45, 60, 75, 90, 105, 120 mm/h) and five slopes (5°, 10°, 15°, 20°, 25°) to reveal the fundamental changing trends of runoff and sediment yield on bare loess soil. Here, we show that the runoff yield within the initial 15 min increased rapidly and its trend gradually became stable. Trends of sediment yield under different rainfall intensities are various. The linear correlation between runoff and rainfall intensity is obvious for different slopes, but the correlations between sediment yield and rainfall intensity are weak. Runoff and sediment yield on the slope surface both presents an increasing trend when the rainfall intensity increases from 45 mm/h to 120 mm/h, but the increasing trend of runoff yield is higher than that of sediment yield. The sediment yield also has an overall increasing trend when the slope changes from 5° to 25°, but the trend of runoff yield is not obvious. Our results may provide data support and underlying insights needed to guide the management of soil conservation planning on the Loess Plateau.