Statistical analysis of arsenic contamination in drinking water in a city of Iran and its modeling using GIS

In this research, probable arsenic contamination in drinking water in the city of Ardabil was studied in 163 samples during four seasons. In each season, sampling was carried out randomly in the study area. Results were analyzed statistically applying SPSS 19 software, and the data was also modeled by Arc GIS 10.1 software. The maximum permissible arsenic concentration in drinking water defined by the World Health Organization and Iranian national standard is 10 μg/L. Statistical analysis showed 75, 88, 47, and 69% of samples in autumn, winter, spring, and summer, respectively, had concentrations higher than the national standard. The mean concentrations of arsenic in autumn, winter, spring, and summer were 19.89, 15.9, 10.87, and 14.6 μg/L, respectively, and the overall average in all samples through the year was 15.32 μg/L. Although GIS outputs indicated that the concentration distribution profiles changed in four consecutive seasons, variance analysis of the results showed that statistically there is no significant difference in arsenic levels in four seasons.     

Runoff loss of pesticides and soil: a comparison between vegetative mulch and plastic mulch in vegetable production systems

Current vegetable production systems use polyethylene (plastic) mulch and require multiple applications of agrochemicals. During rain events, runoff from vegetable production is enhanced because 50 to 75% of the field is covered with an impervious surface. This study was conducted to quantify off-site movement of soil and pesticides with runoff from tomato (Lycopersicon esculentum Mill.) plots containing polyethylene mulch and a vegetative mulch, hairy vetch (Vicia villosa Roth). Side-by-side field plots were instrumented with automated flow meters and samplers to measure and collect runoff, which was filtered, extracted, and analyzed to determine soil and pesticide loss. Seasonal losses of two to four times more water and at least three times as much sediment were observed from plots with polyethvlene mulch (55.4 to 146 L m(-2) and 247 to 535 g m(-2), respectively) versus plots with hairy vetch residue (13.7 to 75.7 L m(-2) and 32.8 to 118 g m(-2), respectively). Geometric means (+/-standard deviation) of total pesticide loads for chlorothalonil (tetrachloroisophthalonitrile) and alpha-and beta-endosulfan (6,7,8,9,10,10-hexachloro-1,5,5a,6,9,9a-hexahydro6,9-methano-2,4,3-benzodioxathiepin 3-oxide) for a runoff event were 19, 6, and 9 times greater from polyethylene (800+/-4.6, 17.6+/-3.9, and 39.1+/-4.9 microg m(-2), respectively) than from hairy vetch mulch plots (42+/-6.0, 2.8+/-5.0, and 4.3+/-4.6 microg m(-2), respectively) due to greater concentrations and larger runoff volumes. The increased runoff volume, soil loss, and off-site loading of pesticides measured in runoff from the polyethylene mulch suggests that this management practice is less sustainable and may have a harmful effect on the environment.     

Introducing roadside hazard severity indicator based on evidential reasoning approach

Safety experts have, in recent years, been attentive to roadside accident severity and occurrence. Hitherto, to prioritize road segment hazardousness, there have been little efforts to quantify a well defined indicator. In this regard, the existing indicators are usually very plain and the overall configuration of roadside is rated by experts with an exact number describing its condition. Hence, the uncertainties which come with the subjective judgments cannot be regarded as of any substance. This research contribution therefore presents a procedure to assess the road safety (roadside safety indicator) by means of the evidential reasoning (ER) approach. The betterment of ER as opposed to the available procedures for roadside safety assessment is that the proposed approach makes allowance for the uncertainties which may arise from individual judgments. Additionally, when there is a dearth of evidence concerning factors which affect roadside hazardousness severity to collate several roadside segments, this procedure will offer the benefits of utilizing the maximum/minimum utility function. With the aid of the drawn indicator, organizations and agencies responsible for ensuring road safety can reach more flexible decisions to set in-place uncertain planning and road segments priorities. This indicator can also be utilized as a variable to include roadside conditions in crash severity prediction models. A field case study has also been carried out in an attempt to follow and validate the proposed approach which is based on the run-off accident history for a sample road segments. The crash data confirm the suggested indicator.     

Analyzing the Variability of Remote Sensing and Hydrologic Model Evapotranspiration Products in a Watershed in Michigan

The goal of this paper was to statistically explore the spatiotemporal performance of remotely sensed actual evapotranspiration (ETa) datasets and a remotely sensed ensemble in a region that lacks observed data. The remotely sensed datasets were further compared with ETa results from a physically based hydrologic model (Soil and Water Assessment Tool) to examine the differences and determine the level of agreement between the ETa datasets and the model outputs. ETa datasets were compared on temporal (i.e., monthly and seasonal basis) and spatial (i.e., landuse) scales at both watershed and subbasin levels. The results showed a lack of consistent similarities and differences among the datasets when evaluating the monthly ETa variations; however, the seasonal aggregated data presented more consistent similarities and differences during the spring and summer compared to the fall and winter. Meanwhile, spatial analysis of the datasets showed the MOD16A2 500 m ETa product was the most versatile of the tested datasets, being able to differentiate between landuses during all seasons. Furthermore, the use of an averaging ensemble was able to improve overall ETa performance in the study area. This study showed that the remotely sensed ETa products are not similar throughout the year, but the appropriate application periods for different ETa products were identified. Finally, spatial variabilities of the ETa products are more in tune with landuse and climate characteristics.     

Simultaneous spectrophotometric determination of crystal violet and malachite green in water samples using partial least squares regression and central composite design after preconcentration by dispersive solid-phase extraction

In this paper, a simple, fast, and inexpensive method is introduced for the simultaneous spectrophotometric determination of crystal violet (CV) and malachite green (MG) contents in aquatic samples using partial least squares regression (PLS) as a multivariate calibration technique after preconcentration by graphene oxide (GO). The method was based on the sorption and desorption of analytes onto GO and direct determination by ultraviolet–visible spectrophotometric techniques. GO was synthesized according to Hummers method. To characterize the shape and structure of GO, FT-IR, SEM, and XRD were used. The effective factors on the extraction efficiency such as pH, extraction time, and the amount of adsorbent were optimized using central composite design. The optimum values of these factors were 6, 15 min, and 12 mg, respectively. The maximum capacity of GO for the adsorption of CV and MG was 63.17 and 77.02 mg g^?1, respectively. Preconcentration factors and extraction recoveries were obtained and were 19.6, 98% for CV and 20, 100% for MG, respectively. LOD and linear dynamic ranges for CV and MG were 0.009, 0.03–0.3, 0.015, and 0.05–0.5 (μg mL^?1), respectively. The intra-day and inter-day relative standard deviations were 1.99 and 0.58 for CV and 1.69 and 3.13 for MG at the concentration level of 50 ng mL^?1, respectively. Finally, the proposed DSPE/PLS method was successfully applied for the simultaneous determination of the trace amount of CV and MG in the real water samples.     

A new strategy for determination of hydroxylamine and phenol in water and waste water samples using modified nanosensor

A carbon paste electrode modified with p-chloranil and carbon nanotubes was used for the sensitive and selective voltammetric determination of hydroxylamine (HX) and phenol (PL). The oxidation of HX at the modified electrode was investigated by cyclic voltammetry (CV), chronoamperommetry, and electrochemical impedance spectroscopy. The values of the catalytic rate constant (k), and diffusion coefficient (D) for HX were calculated. Square wave voltammetric peaks current of HX and PL increased linearly with their concentrations at the ranges of 0.1–172.0 and 5.0–512.0 μmol L^?1, respectively. The detection limits for HX and PL were 0.08 and 2.0 μmol L^?1, respectively. The separation of the anodic peak potentials of HX and PL reached to 0.65 V, using square wave voltammetry. The proposed sensor was successfully applied for the determination of HX and PL in water and wastewater samples.     

Developing a master plan for hospital solid waste management: a case study

Disposal of about 1750tons of solid wastes per day is the result of a rapid population growth in the province of Khuzestan in the south west of Iran. Most of these wastes, especially hospital solid wastes which have contributed to the pollution of the environment in the study area, are not properly managed considering environmental standards and regulations. In this paper, the framework of a master plan for managing hospital solid wastes is proposed considering different criteria which are usually used for evaluating the pollution of hospital solid waste loads. The effectiveness of the management schemes is also evaluated. In order to rank the hospitals and determine the share of each hospital in the total hospital solid waste pollution load, a multiple criteria decision making technique, namely analytical hierarchy process (AHP), is used. A set of projects are proposed for solid waste pollution control and reduction in the proposed framework. It is partially applied for hospital solid waste management in the province of Khuzestan, Iran. The results have shown that the hospitals located near the capital city of the province, Ahvaz, produce more than 43% of the total hospital solid waste pollution load of the province. The results have also shown the importance of improving management techniques rather than building new facilities. The proposed methodology is used to formulate a master plan for hospital solid waste management.     

Rapid Flood Damage Prediction and Forecasting Using Public Domain Cadastral and Address Point Data with Fuzzy Logic Algorithms

National Flood Interoperability Experiment (NFIE) derived technologies and workflows will offer the ability to rapidly forecast flood damages. Address Points used by emergency management personnel approximate the locations of buildings, and they are a common operating picture for emergency responders. Most United States (U.S.) county tax assessment offices throughout the contiguous U.S. (CONUS) produce georeferenced cadastral data. To varying degrees, these parcel data describe building characteristics of structures within the parcel. Address Point data with cadastral data offers the ability to rapidly develop building inventories for flood damage estimation. Flood damage forecasts can expedite recovery and improve short‐term flood resilience. In this work the authors evaluate Flood Damage Wizard, a proposed open source platform independent methodology. Flood Damage Wizard uses point shapefile building information to estimate flood damage to buildings by finding the appropriate depth‐damage function using fuzzy‐text matching. The authors apply Flood Damage Wizard using Address Point and parcel datasets to demonstrate a method of estimating flood damage to buildings nearly anywhere within the CONUS. Results indicate using Address Point and cadastral datasets can generate total flood damage estimates approximate to those estimated using existing software solutions Hazus‐MH and HEC‐FIA with minimal manual processing of input data.     

Minimum quantity lubrication in grinding: effects of abrasive and coolant–lubricant types

This research has been conducted to study the influence of the abrasive and coolant–lubricant types on the minimum quantity lubrication (MQL) grinding performance. One type of CBN and three types of conventional wheels (corundum) have been tested. The tests have been performed in presence of fluid, air jet and eleven types of coolant–lubricants, as well as, in dry condition. The results indicate that the finest surface quality and lower grinding forces could be obtained while grinding with CBN wheel. In case of conventional wheels, the coarser and high porosity wheels induce much proper grinding results. Furthermore, grinding when utilizing MQL with oil results in higher grinding performance.