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.     

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.     

Fugitive emissions opacity determination using the digital opacity compliance system (DOCS)

Maintenance of Department of Defense (DoD) weapon systems, conducting battlefield training exercises as well as meeting military construction and/or demolition schedules, invariably generate fugitive air emissions, many of which are visible. Although there is no codified federal method for quantifying fugitive emissions opacity, many state and local air regulatory agencies have instituted enforceable fugitive emission opacity standards at DoD facilities. The current study focused on comparing the performance of the digital opacity compliance system (DOCS) with U.S. Environment Protection Agency Method 9 (Method 9) certified human observers in quantifying the visible opacity associated with fugitive emissions produced using a commercial fog generator. By systematically repositioning both DOCS cameras and Method 9-certified observers during field testing, differences in method performance as a function of observational locations were documented. At both the 30- and 300-ft off-set distances, opacity levels reported by the DOCS technology and Method 9-certified smoke readers were found to be statistically different at the 99% confidence level. Alternatively, at the 90- and 150-ft off-set distances, results suggested that there was an insignificant difference at the 99% confidence level between the two methods. Comparing the magnitude of the each method's standard deviation suggested that, at the 30-ft off-set distance, the DOCS technology was consistently more precise than Method 9-certified readers regardless of the observer's downwind distance. However, at the 90, 150, and 300-ft off-set distances, method precision seemed to vary as a function of both off-set and downwind distance. The primary factor affecting the consistency in opacity measurements appeared to be the impact of ground-level air turbulence on fog plume dispersion and transport. Field observations demonstrated that localized wind shear played a critical and decisive role in how and to what extent fugitive emissions opacity could be determined, regardless of the method selected.     

Development of an extraction method for perchlorate in soils

Perchlorate originates as a contaminant in the environment from its use in solid rocket fuels and munitions. The current US EPA methods for perchlorate determination via ion chromatography using conductivity detection do not include recommendations for the extraction of perchlorate from soil. This study evaluated and identified appropriate conditions for the extraction of perchlorate from clay loam, loamy sand, and sandy soils. Based on the results of this evaluation, soils should be extracted in a dry, ground (mortar and pestle) state with Milli-Q water in a 1 ratio 1 soil ratio water ratio and diluted no more than 5-fold before analysis. When sandy soils were extracted in this manner, the calculated method detection limit was 3.5 microg kg(-1). The findings of this study have aided in the establishment of a standardized extraction method for perchlorate in soil.     

Why bees are critical for achieving sustainable development

Reductions in global bee populations are threatening the pollination benefits to both the planet and people. Whilst the contribution of bee pollination in promoting sustainable development goals through food security and biodiversity is widely acknowledged, a range of other benefits provided by bees has yet to be fully recognised. We explore the contributions of bees towards achieving the United Nation’s Sustainable Development Goals (SDGs). Our insights suggest that bees potentially contribute towards 15 of the 17 SDGs and a minimum of 30 SDG targets. We identify common themes in which bees play an essential role, and suggest that improved understanding of bee contributions to sustainable development is crucial for ensuring viable bee systems.     

Male exposure mediated adverse reproductive outcomes in carbon disulphide exposed rayon workers

The authors examined 100 carbon disulphide (CS2) exposed male workers who had been employed ten years prior to study were selected for the study. They were virtually obliged to participate in the study by the Medical Labor Inspector and all of them participated voluntary. The aim was to assess the effects of occupational exposure to carbon disulphide concentrations below the threshold limit value (31 mg/m3) on the reproductive functions with special emphasis on miscarriages. Specially, workers history records were build up on number of children, miscarriages and general weakness, mental fatigue etc. It was found that the incidences of number of miscarriages against number of living children correlated well with environmental concentration of CS2. Where the average CS2 levels were 1.695 ppm, the incidences of miscarriages was 5.71% (group 1). Where as in group 2 environmental concentrations were 12.28 ppm and the incidences of miscarriages were 18.91%. It was also found that in the spinning department the exposure exceeds many times the Threshold Limit Values (TL V).     

Performance assessment of a zeolite treatment wall for removing Sr-90 from groundwater

Laboratory and modeling studies were conducted to assess the potential performance of a permeable reactive barrier constructed of a natural zeolite material at the West Valley Demonstration Project in western New York State. The results of laboratory column tests indicated that the barrier material would be effective at removing strontium from groundwater under natural gradient conditions. Two one-dimensional contaminant transport models were developed to interpret the data. A single-solute retardation factor model provided good agreement with the column test data, but time-consuming extraction and analysis of the zeolite material was required to parameterize the model. A preliminary six-solute model was also developed based on the assumption of competitive cation exchange as the primary removal mechanism. Both models yielded similar predictions of the long-term performance of the barrier, but the cation exchange model predicted higher effluent concentrations during the first 1000 pore volumes of operation. The cation exchange framework has several advantages, including the ability to calibrate the model using only data from column effluent samples, and the ability to account for site-specific differences in the groundwater cation composition. However, additional laboratory work is needed to develop a suitably robust model.     

Physiological and biochemical responses of several freshwater algae to a mixture of metals

A mixture of ten metals (As, Cd, Cr, Cu, Fe, Pb, Hg, Ni, Se and Zn) at the Great Lakes Water Quality Objective levels was found to reduce the primary productivity of four cultured freshwater algae ($\text{Scenedesmus}$, $\text{Chlorella}$, $\text{Anabaena}$ and $\text{Navicula}$) as well as natural phytoplankton from Lake Ontario water. The metal mixture also caused a reduction in the reproduction and transport of an amino acid analogue (α-aminoisobutyric acid) by $\text{Ankistrodesmus}$. The depuration and exchange of the amino acid analogue were not affected by the metal mixture. The nitrogenase activity of $\text{Anabaena}$ was, however, reduced in the presence of the metal mixture.     

An assessment of carbon stock for various land use system in Aravally mountains, Western India

Reducing carbon emissions from deforestation and degradation in developing countries is of the central importance in efforts to combat climate change. A study was conducted to measure carbon stocks in various land-use systems including forms and reliably estimates the impact of land use on carbon (C) stocks in the forest of Rajasthan, western India (23°3′–30°12′N longitude and 69°30′–78°17′E). 22.8% of India is forested and 0.04% is the deforestation rate of India. In Indian forest sector of western India of Aravally mountain range covered large area of deciduous forest and it’s very helpful in carbon sequestration at global level. The carbon stocks of forest, plantation (reforestation) and agricultural land in aboveground, soil organic and fine root within forest were estimated through field data collection. Results revealed that the amount of total carbon stock of forests (533.64?±?37.54 Mg·ha^?1, simplified expression of Mg (carbon) ·ha^?1) was significantly greater (P?<?0.05) than the plantation (324.37?±?15.0 Mg·ha^?1) and the agricultural land (120.50?±?2.17 Mg·ha^?1). Soil organic carbon in the forests (172.84?±?3.78 Mg·ha^?1) was also significantly greater (P?<?0.05) than the plantation (153.20?±?7.48 Mg·ha^?1) and the agricultural land (108.71?±?1.68 Mg·ha^?1). The differences in carbon stocks across land-use types are the primary consequence of variations in the vegetation biomass and the soil organic matter. Fine root carbon was a small fraction of carbon stocks in all land-use types. Most of the soil organic carbon and fine root carbon content was found in the upper 30-cm layer and decreased with soil depth. The aboveground carbon (ABGC): soil organic carbon (SOC): fine root carbon ratios (FRC), was 8:4:1, 4:5:1, and 3:37:1 for the forest, plantation and agricultural land, respectively. These results indicate that a relatively large proportion of the C loss is due to forest conversion to agricultural land.