Because of its persistent usage and broad-spread applicability, chlorpyrifos with high potential damage to non-target organism can be found widely in the environment. However, the relevant researches about the effects of chlorpyrifos on soil fungi, an important part of microorganisms in the planting soil, are very limited, especially when chlorpyrifos is applied in actual agricultural practices. In this study, the soils, planted with Brassica juncea (L.) Czerniak (big mustard), treated with chlorpyrifos were analyzed during vegetable growth to be harvested. The effects of chlorpyrifos on fungal abundance and community structure were determined by quantitative polymerase chain reaction (qPCR) and denaturing gradient gel electrophoresis (DGGE). The results revealed that chlorpyrifos was removed only 15.20 % on the 15th day after being sprayed. Chlorpyrifos caused inhibition on soil fungi diversity and fungal abundance significantly decreased from the early days after application. Furthermore, an obvious change in fungal community structure was found in the treatments compared with the controls, especially a significant change of Fusarium sp., which maintained stable abundance in the controls but fell sharply when chlorpyrifos started to be used and then significantly increased in the treatments, even over the controls finally. In contrast to the controls, the effects from chlorpyrifos could change soil fungal structure by affecting soil pH, while the other soil physicochemical properties without significant influence from chlorpyrifos.

A soil column leaching experiment was conducted to eliminate heavy metals from reclaimed tidal flat soil. Flue gas desulfurization (FGD) gypsum was used for leaching. The highest removal rates of Cd and Pb in the upper soil layers (0–30 cm) were 52.7 and 30.5 %, respectively. Most of the exchangeable and carbonate-bound Cd and Pb were removed. The optimum FGD gypsum application rate was 7.05 kg·m⁻², and the optimum leaching water amount for the application was 217.74 L·m⁻². The application of FGD gypsum (two times) and the extension of the leaching interval time to 20 days increased the heavy metal removal rate in the upper soil layers. The heavy metals desorbed from the upper soil layers were re-adsorbed and fixed in the 30–70 cm soil layers.

Silver nanoparticles (AgNP) are one of the most marketable nanomaterials worldwide. Their increasing production and their market insertion will deliver AgNP to the environment, exacerbating their human and environmental impacts. This review discusses the main techniques to synthesize AgNP, their properties, applications, and the cutting-edge knowledge on the effects of AgNP on human and environmental health. Through an identification of papers reporting AgNP until the beginning of 2016 in “ISI Web of Science,” and running different combinations of keywords or search strings, we identified six toxicological factors with a clear hazard potential to workers and consumers. A grading system is proposed to rank and evaluate toxicological properties of AgNP, which can be useful in supplying assistance on the classification of the priorities and concerns in the regulatory and standardization policies of the occupational health and safety issues on nanomaterials.

The objective of the study is to improve understanding of natural phosphorus removal processes to limit the need for chemical addition in an existing facultative wastewater stabilization pond in Manitoba, Canada. Surface samples were collected from lagoon cells and analyzed. The windward and leeward sides of the ponds were sampled and the results were averaged. Phosphorus appears to be removed by assimilation into biomass; and precipitation at alkaline pH. When the nitrogen to phosphorus (N/P) ratio and ideal theoretical N/P ratio for cellular growth are compared, there appears to be nitrogen-limiting conditions in the secondary cells of the stabilization system. There is evidence ammonia removal by free ammonia volatilizing to the atmosphere may be contributing to nitrogen-limiting conditions in the secondary lagoon cells. Additional nitrogen may need to be supplied to remove more phosphorus by assimilation into biomass.

This paper proposes multilayer perceptron neural network (MLPNN) to predict phycocyanin (PC) pigment using water quality variables as predictor. In the proposed model, four water quality variables that are water temperature, dissolved oxygen, pH, and specific conductance were selected as the inputs for the MLPNN model, and the PC as the output. To demonstrate the capability and the usefulness of the MLPNN model, a total of 15,849 data measured at 15-min (15 min) intervals of time are used for the development of the model. The data are collected at the lower Charles River buoy, and available from the US Environmental Protection Agency (USEPA). For comparison purposes, a multiple linear regression (MLR) model that was frequently used for predicting water quality variables in previous studies is also built. The performances of the models are evaluated using a set of widely used statistical indices. The performance of the MLPNN and MLR models is compared with the measured data. The obtained results show that (i) the all proposed MLPNN models are more accurate than the MLR models and (ii) the results obtained are very promising and encouraging for the development of phycocyanin-predictive models.

Di-n-butyl phthalate (DBP) widely used as plastic films’ plasticizer, can cause agricultural pollution which is of increasing concern because of the food safety issues. Cucumber (Cucumis sativus Linn.), commonly cultured in greenhouse, was exposed to DBP stress to gain more information about the ecological risk of DBP in this study. Changes of DBP residues and fruit quality of cucumber at different DBP concentrations (0, 5, 10, 20, 40 mg/kg of dry soil) were investigated in pot experiments using an agricultural soil under greenhouse condition, respectively. DBP residue in cucumber fruits ranged from 0.5326 to 1.8938 mg/kg, and the quality of cucumber fruits (organic acids, vitamin C, soluble protein, and soluble sugar) were influenced by DBP stress. Moreover, the health risk assessment was evaluated by estimate daily intakes (EDI) and the target hazard quotient (THQ) was analyzed. Under 40 mg/kg DBP condition, the highest value of EDI was 2.49 μg/kg bw/day and the THQ ranged from 0.000700 to 0.0249. Although the risk of DBP in cucumber fruits was lower than the threshold limit value of risk, the potential health risk was not a negligible issue.

The use of reclaimed water (RW) for irrigation alleviates agricultural water shortages. However, N₂O emissions and N fertilizer transformations in soils irrigated with RW under different N fertilizer types and soil moisture contents are poorly understood. A 216-h laboratory incubation experiment was conducted to evaluate the effects of irrigation water types (RW and fresh water, FW), N fertilizer types (¹⁵N-labeled KNO₃ and (NH₄)₂SO₄), and soil moisture contents at 40, 60, and 90 % water-filled pore space (WFPS) on N₂O emissions and N fertilizer transformations in intact soil cores. The results showed that cumulative N₂O emissions ranged from 3.78 to 36.30 mg N m⁻², and fertilizer-derived N₂O losses accounted for 0.14–2.44 % of N fertilizers, while fertilizer-derived N residues (NO₃ ⁻-N + NH₄ ⁺-N) accounted for 10.16–26.95 % of N fertilizers. The N₂O emissions at 40 % WFPS and fertilizer-derived N residues at 60 % WFPS in soils irrigated with RW were significantly (10.98 and 20.95 %, respectively) higher than those irrigated with FW, while fertilizer-derived N₂O losses at 60 % WFPS in soils irrigated with RW were 10.26 % higher than those irrigated with FW. The N₂O emissions and fertilizer-derived N₂O losses in soils amended with (NH₄)₂SO₄ at 40 and 60 % WFPS were significantly (26.61–178.84 %) larger than those amended with KNO₃, while fertilizer-derived N residues in soils amended with KNO₃ were significantly (41.47 %) higher than those amended with (NH₄)₂SO₄. The N₂O emissions significantly increased with increasing soil moisture content. Our results indicate that N fertilizer types and soil moisture contents are the two important factors regulating N₂O emissions and N fertilizer transformations. When RW irrigation is used, controlling soil moisture contents within 41 and 60 % WFPS (the optimum is 46 % WFPS) and application of KNO₃ can reduce N₂O emissions and fertilizer-derived N₂O losses, and correspondingly increase fertilizer-derived N residues, which can contribute to climate change mitigation.

The study delineates the investigation to determine the adsorption and desorption behaviour of Pretilachlor in three soils of Punjab with varying physicochemical characteristics using batch equilibration techniques. Kinetics of adsorption followed a pseudo-second-order model (R ² > 0.99) and adsorption–desorption data fitted well to the Freundlich equation for the three soils. L-type isotherms were obtained for the adsorption process, which indicated high affinity between Pretilachlor and adsorption sites. The magnitude of logK Fₐdₛ values for the three soils ranged from 0.887–1.226 μg¹⁻¹/ⁿ g⁻¹ mL¹/ⁿ and the order of adsorption was clay loam > sandy loam > loamy sand. Desorption of Pretilachlor was concentration dependent and in three desorption cycles ranged from 5.04 to 56.03 % in loamy sand, 3.14 to 23.12 % in sandy loam and 1.63 to 18.64 % in clay loam soil indicative of difficulty in the release of strongly adsorbed Pretilachlor. The removal of organic matter by hydrogen peroxide (H₂O₂) oxidation increased the adsorption of Pretilachlor in three Punjab soils. Pretilachlor desorption was hysteretic in the original as well as H₂O₂-treated soils. It could therefore be concluded that the adsorption was controlled by clay minerals and desorption of Pretilachlor in soils was controlled by the organic matter.

Extension of hydrological or water quality records at short-gauged stations using information from another long-gauged station is termed record extension. The ordinary least squares regression (OLS) is a traditional and commonly used record-extension technique. However, OLS is more appropriate for the substitution of scattered missing values than for record-extension as the OLS provides extended records with underestimated variance. Underestimation of the variance of the extended records leads to underestimation of high percentiles and overestimation of low percentiles given that the data is normally distributed. The Maintenance of Variance Extension techniques (MOVE) have the advantage of maintaining the variance in the extended records. However, the OLS and MOVE techniques are sensitive to the presence of outliers. Two new record-extension techniques with the advantage of being robust in the presence of outliers were recently proposed by the authors: the robust line of organic correlation (RLOC) and modified version of the Kendall-Theil Robust line (KTRL2). In this study a new robust technique is proposed. The new regression technique based on L-moments (LMOM) is a modified version of the RLOC and uses the same intercept as that of RLOC and KTRL2 while the estimated slope is based on the second L-moment. An empirical examination of the preservation of the water quality variable characteristics was carried out using water quality records from the Nile Delta water quality monitoring network in Egypt. A comparison between nine record-extension techniques (OLS, MOVE1 to MOVE4, KTRL, KTRL2, RLOC and LMOM) was performed to examine the extended records for bias and standard error in their statistical moment estimates and over the full range of percentiles. Results showed that the proposed LMOM technique outperforms other techniques by producing extended records that preserve variance as well as extreme percentiles.

Acid mine drainage (AMD) is a persisting environmental problem and a grievous nuisance in the mining sector. In this study, iron (Fe(II)) removal was tested in AMD samples collected from the Enugu Okpara abandoned coal mine (Nigeria), having iron concentrations of ∼1300 mg/l. Digestion, toxicity characteristic leaching procedure (TCLP), and batch adsorption tests using coal bottom ash (BA), bentonite clay (BC), and coal fly ash (FA) were performed. Apart from elucidating the effects of adsorbent dose and initial Fe(II) concentrations on the maximum adsorption capacity (q ₑ) of the adsorbents, the experimental data were also fitted to well-known adsorption isotherms and kinetic models. The results from batch tests showed that the optimum adsorbent dosages for BA, BC, and FA were found to be 3, 4, and 4 g per 100 ml, respectively. Among the different adsorption isotherm models tested, the Temkin model fitted the experimental data well for Fe(II) removal. Results from kinetic analysis showed that the Fe(II) removal efficiency increased with an increase in the contact time and then remained almost constant after 30 min for the three tested adsorbents.