Remediation of alachlor and atrazine contaminated water with zero-valent iron nanoparticles

Zero-valent iron nanoparticles (nZVI, diameter < 90 nm, specific surface area = 25 m² g^?1) have been used under anoxic conditions for the remediation of pesticides alachlor and atrazine in water. While alachlor (10, 20, 40 mg L^?1) was reduced by 92–96% within 72 h, no degradation of atrazine was observed. The alachlor degradation reaction was found to obey first-order kinetics very closely. The reaction rate (35.5 × 10^?3–43.0 × 10^?3 h^?1) increased with increasing alachlor concentration. The results are in conformity with other researchers who worked on these pesticides but mostly with micro ZVI and iron filings. This is for the first time that alachlor has been degraded under reductive environment using nZVI. The authors contend that nZVI may prove to be a simple method for on-site treatment of high concentration pesticide rinse water (100 mg L^?1) and for use in flooring materials in pesticide filling and storage stations.     

Isolation of mesotrione-degrading bacteria from aquatic environments in Brazil

Mesotrione is a benzoylcyclohexane-1,3-dione herbicide that inhibits 4-hydroxyphenyl pyruvate dioxygenase in target plants. Although it has been used since 2000, only a limited number of degrading microorganisms have been reported. Mesotrione-degrading bacteria were selected among strains isolated from Brazilian aquatic environments, located near corn fields treated with this herbicide. Pantoea ananatis was found to rapidly and completely degrade mesotrione. Mesotrione did not serve as a sole C, N, or S source for growth of P. ananatis, and mesotrione catabolism required glucose supplementation to minimal media. LC-MS/MS analyses indicated that mesotrione degradation produced intermediates other than 2-amino-4-methylsulfonyl benzoic acid or 4-methylsulfonyl-2-nitrobenzoic acid, two metabolites previously identified in a mesotrione-degrading Bacillus strain. Since P. ananatis rapidly degraded mesotrione, this strain might be useful for bioremediation purposes.     

Purification and Properties of Extracellular Poly(3-hydroxybutyrate) Depolymerase Produced by <Emphasis Type="Italic">Aspergillus fumigatus</Emphasis> 202

An extracellular poly(3-hydroxybutyrate) (PHB) depolymerase produced by a thermotolerant fungal soil isolate, Aspergillus fumigatus 202, was purified and characterized. Maximum PHB depolymerase production was obtained at the end of 48 h with initial medium pH 7.0 and 45 °C in Bushnell Haas Minerals medium containing PHB as sole source of carbon. The PHB depolymerase was purified using size exclusion chromatography to a fold purification of 20.62 and 61.62% yield. SDS-PAGE and isoelectric focusing revealed the molecular weight and pI of the purified enzyme as 63,744 Da and 4.2, respectively. N-terminal amino acid sequence of purified enzyme was HAXDAYLVK. This non-glycosylated enzyme was most active at pH 9.0 and 45 °C. Purified enzyme was inactivated by N-bromosuccinimide and dithiothreitol suggesting the involvement of tryptophan residues and disulfide bonds at its active site. Nonionic detergents like Tween 20, Tween 80 and Triton X-100 inhibited the enzyme activity. Ions like Ca⁺² and Mg⁺² (5 mM) increased the enzyme activity 1.5 times. Fe⁺² effectively inhibited the enzyme activity to 88% whereas Hg⁺² completely inhibited the enzyme.     

Influence of regional development policies and clean technology adoption on future air pollution exposure

Future air pollution emissions in the year 2030 were estimated for the San Joaquin Valley (SJV) in central California using a combined system of land use, mobile, off-road, stationary, area, and biogenic emissions models. Four scenarios were developed that use different assumptions about the density of development and level of investment in transportation infrastructure to accommodate the expected doubling of the SJV population in the next 20 years. Scenario 1 reflects current land-use patterns and infrastructure while scenario 2 encouraged compact urban footprints including redevelopment of existing urban centers and investments in transit. Scenario 3 allowed sprawling development in the SJV with reduced population density in existing urban centers and construction of all planned freeways. Scenario 4 followed currently adopted land use and transportation plans for the SJV. The air quality resulting from these urban development scenarios was evaluated using meteorology from a winter stagnation event that occurred on December 15th, 2000 to January 7th 2001. Predicted base-case PM2.5 mass concentrations within the region exceeded 35 μg m^?3 over the 22-day episode. Compact growth reduced the PM2.5 concentrations by ～1 μg m^?3 relative to the base-case over most of the SJV with the exception of increases (～1 μg m^?3) in urban centers driven by increased concentrations of elemental carbon (EC) and organic carbon (OC). Low-density development increased the PM2.5 concentrations by 1–4 μg m^?3 over most of the region, with decreases (0.5–2 μg m^?3) around urban areas. Population-weighted average PM2.5 concentrations were very similar for all development scenarios ranging between 16 and 17.4 μg m^?3. Exposure to primary PM components such as EC and OC increased 10–15% for high density development scenarios and decreased by 11–19% for low-density scenarios. Patterns for secondary PM components such as nitrate and ammonium ion were almost exactly reversed, with a 10% increase under low-density development and a 5% decrease under high density development. The increased human exposure to primary pollutants such as EC and OC could be predicted using a simplified analysis of population-weighted primary emissions. Regional planning agencies should develop thresholds of population-weighted primary emissions exposure to guide the development of growth plans. This metric will allow them to actively reduce the potential negative impacts of compact growth while preserving the benefits.     

Some Effects of Atmospheric Fluoride on Plant Metabolism

Leaves of Tendergreen bean plants exposed to atmospheric fluoride concentrations in the range 1.7 to 7.6 μg/m³ showed increased levels of enolase and catalase activity and decreased levels of pyruvate and α-ketoglutarate. Phosphoenolpyruvate carboxylase activity and oxalacetate were not affected. The leaves of Milo maize plants exposed to 5.0 μg F/m³ showed increased levels of enolase and pyruvate kinase activity and a decreased level of pyruvate. Oxalacetate and α-ketoglutarate levels were not affected. Catalase activity was increased, then decreased by IIF fumigation. The changes induced by HF were greatest six to 10 days after the start of fumigation and disappeared or decreased in magnitude during the post-fumigation period.     

acid rain and environmental policy

Editor’s note: This paper by Dr. Jacobson was presented at the 74th annual meeting of the Air Pollution Control Association as part of a panel discussion entitled “Acid Rain–1981: An International Issue.” The session was held on June 22, 1981, and was arranged by APCA’s TT-6 Energy-Environmental Interactions Committee.     

Comparative performance of flat sheet and spiral wound modules in the nanofiltration of reactive dye solution

Background and purpose

Besides the opportunities for reuse, stringent regulations and growing public awareness demand an enhanced quality of effluent from dye industries. Treatment of an aqueous solution of dye (reactive red 198) was carried out in a nanofiltration unit using both flat sheet and spiral wound modules to obtain a comparative performance evaluation in terms of permeate flux and quality.

Methods

Hydrophilized polyamide membrane with molecular weight cutoff of 150 was used for the experiments. Effects of trans-membrane pressure (TMP), feed concentration and addition of salt on permeate flux were investigated. Percent reduction of color, chemical oxygen demand (COD), total dissolved solid (TDS), and conductivity were determined to assess performance of the membrane.

Results

The maximum flux decline was 16.1% of its initial value at 490 kPa TMP with 50 ppm feed concentration in spiral wound module, whereas the same in flat sheet under same conditions was 7.2%. The effect of TMP showed a quasi-linear increase in flux with increasing pressure. Increased permeate concentration led to the reduction in observed retention of dye in the membrane. The average reduction in color, COD, and TDS were 96.88%, 97.38%, and 89.24%, respectively. The decline in permeate flux was more in case of spiral wound module compared to flat sheet. However, spiral wound module performed better in terms of color removal, COD reduction, and TDS removal.

Conclusion

Substantial removal of color was achieved in the nanofiltration experiments with a marked reduction in COD and TDS. The process allowed the production of permeate stream with great reutilization possibilities.     

SOIL SALINITY PREDICTION USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: This study explores the applicability of Artificial Neural Networks (ANNs) for predicting salt build‐up in the crop root zone. ANN models were developed with salinity data from field lysimeters subirrigated with brackish water. Different ANN architectures were explored by varying the number of processing elements (PEs) (from 1 to 30) for replicate data from a 0.4 m water table, 0.8 m water table, and both 0.4 and 0.8 m water table lysimeters. Different ANN models were developed by using individual replicate treatment values as well as the mean value for each treatment. For replicate data, the models with twenty, seven, and six PEs were found to be the best for the water tables at 0.4 m, 0.8 m and both water tables combined, respectively. The correlation coefficients between observed salinity and ANN predicted salinity of the test data with these models were 0.89, 0.91, and 0.89, respectively. The performance of the ANNs developed using mean salinity values of the replicates was found to be similar to those with replicate data. Not only was there agreement between observed and ANN predicted salinity values, the results clearly indicated the potential use of ANN models for predicting salt build‐up in soil profile at a specific site.