Assessment of irrigation water quality. A proposal of a quality profile

Water quality indices provide a simple and understandable tool for managers on the quality and possible uses for irrigation water, however an individual quality factor alone is not enough to evaluate the irrigation water quality because it could be restrictive and sometime it could give an unfavorable qualification. The aim of this paper was propose a quality profile of irrigation water using the preexisting water quality indices to be applied to arid and semi-arid regions. As a case studied, the water of the Del Molle River (Nogolí, San Luis, Argentina) was researched. Samples were collected during the period October 2005-May 2006. Conductivity, pH, total hardness, sulphate, nitrate, nitrite, alkalinity, chloride, sodium, potassium, TDS, DO and phosphate were analyzed. The irrigation water quality, according to Riverside Norm, belongs to C(2)-S(1) class, according to Wilcox Norm as excellent to good, according to Scott quality factor it is good and according to SAR < 10 and according to RCS it is recommendable. From the obtained data, it can be concluded that the water quality profile was good, so it is useful for normal irrigation agriculture.     

Genealogical Analysis of a Closed Herd of Black Hairless Iberian Pigs

Abstract: Livestock breeds are recognized as important components of world biodiversity. The Iberian pig is a swine breed well adapted to the Mediterranean forest ecosystem and provides cured products of high quality. The ancient population of Iberian pigs (  Sus scrofa meridionalis ) was differentiated in several local types, the black hairless pigs representing the fattest genetic type. The conservation program of the Guadyerbas strain has maintained this germplasm isolated since 1945 as a closed population in an experimental herd. The complete pedigree, with 1000 breeding animals descending from 24 founders, has been used to measure along the successive cohorts of breeding animals the effective number of founders, effective number of nonfounders, founder genome equivalents, and expected number of founders' surviving alleles. For the last cohort, the values were 10.34, 1.42, 1.25, and 4.06, respectively. The evolution of inbreeding and coancestry and its components attributable to each founder were also studied. The rate of increase in inbreeding and coancestry was 2.21% per cohort, or 0.906% per year. Finally, the effect of family structure and mating tactics on the evolution of coancestry was also analyzed. The greatest rates of coancestry per cohort were attributable to unbalanced family sizes, and the use of minimum coancestry matings effectively delayed the increase in inbreeding.     

Effectiveness of three configurations of membrane bioreactors on the removal of priority and emergent organic compounds from wastewater: comparison with conventional wastewater treatments

In this work the effectiveness of membrane bioreactors as advanced treatment on the removal of emergent and priority organic compounds in wastewater treatment plants has been evaluated during a one-year monitoring study. The studied wastewater treatment plant operates with flat sheet and hollow fibre membranes in two parallel lines. Moreover, a reverse osmosis module connected in series after the hollow fibre membrane was evaluated for one month. Comparison of membrane bioreactor and conventional activated sludge treatment was also investigated, as well as the influence of the physicochemical properties of the compounds on the removal rates achieved. Sixteen pharmaceutical compounds belonging to seven therapeutic groups and eight priority organic pollutants, including linear alkylbenzene sulfonates, nonylphenol and its ethoxylates and phthalate, were monitored. The highest mean concentrations corresponded to priority organic pollutants (309 μg L(-1) of linear alkylbenzene sulfonate C(12)) followed by pharmaceutical compounds (24.5 μg L(-1) of ibuprofen). No significant difference of effectiveness was found among flat sheet and hollow fibre membranes. However, an improvement was obtained with the addition of a reverse osmosis module for most of the compounds. Biodegradation has been shown as the main route involved in the removal of organic compounds during both technologies.     

Modelling geosmin concentrations in three sources of raw water in Quebec, Canada

The presence of off-flavour compounds such as geosmin, often found in raw water, significantly reduces the organoleptic quality of distributed water and diverts the consumer from its use. To adapt water treatment processes to eliminate these compounds, it is necessary to be able to identify them quickly. Routine analysis could be considered a solution, but it is expensive and delays associated with obtaining the results of analysis are often important, thereby constituting a serious disadvantage. The development of decision-making tools such as predictive models seems to be an economic and feasible solution to counterbalance the limitations of analytical methods. Among these tools, multi-linear regression and principal component regression are easy to implement. However, due to certain disadvantages inherent in these methods (multicollinearity or non-linearity of the processes), the use of emergent models involving artificial neurons networks such as multi-layer perceptron could prove to be an interesting alternative. In a previous paper (Parinet et al., Water Res 44: 5847-5856, 2010), the possible parameters that affect the variability of taste and odour compounds were investigated using principal component analysis. In the present study, we expand the research by comparing the performance of three tools using different modelling scenarios (multi-linear regression, principal component regression and multi-layer perceptron) to model geosmin in drinking water sources using 38 microbiological and physicochemical parameters. Three very different sources of water, in terms of quality, were selected for the study. These sources supply drinking water to the Québec City area (Canada) and its vicinity, and were monitored three times per month over a 1-year period. Seven different modelling methods were tested for predicting geosmin in these sources. The comparison of the seven different models showed that simple models based on multi-linear regression provide sufficient predictive capacity with performance levels comparable to those obtained with artificial neural networks. The multi-linear regression model (R ²?=?0.657, <0.001) used only four variables (phaeophytin, sum of green algae, chlorophyll-a and potential Redox) in comparison with ten variables (potassium, heterotrophic bacteria, organic nitrogen, total nitrogen, phaeophytin, total organic carbon, sum of green algae, potential Redox, UV absorbance at 254 nm and atypical bacteria) for the best model obtained with artificial neural networks (R ²?=?0.843).     

Water quality assessment, by statistical analysis, on rural and urban areas of Chocancharava River (Río Cuarto), Córdoba, Argentina

Water quality has degraded dramatically in the Chocancharava River (Río Cuarto, Córdoba, Argentina) due to point and non-point sources. This paper aims to assess spatial and temporal variations of physical and chemical parameters of the river. Six sampling sites and six sampling campaigns were developed. During the period 2007–2008, wet and dry seasons were included. A statistical analysis was carried out with 23 physical and chemical variables. Then, a new statistical analysis was carried out including the Riparian Corridors Quality Index and the physical and chemical variables (24 variables). Considering a multivariate system, analysis of variance, principal component analysis and cluster analysis were used. From the statistical analysis, the river was divided into two zones with different degrees of contamination. The most polluted zone is due to pollution inputs of urban, industrial and agricultural sources. This area showed a remarkable deterioration in water quality, mainly due to wastewater discharges. According to Riparian Quality, better results were found in sections of poor water quality, due to the fact that the river bank forest was less degraded downstream of the sewage discharge.     

Spatial and seasonal distribution of 17 endocrine disruptor compounds in an urban estuary (Mondego River,Portugal): evaluation of the estrogenic load of the area

The Mondego River estuary demonstrates signs of pollution, but the levels of endocrine disrupting compounds (EDCs), such as the natural (17β-estradiol and estrone) and pharmaceutical (17α-ethynylestradiol) estrogens, xenoestrogenic industrial pollutants (4-octylphenol, 4-nonylphenol, and their mono- and diethoxylates and bisphenol A), phytoestrogens (formononetin, biochanin A, daidzein, and genistein), and sitosterol were either poorly or never measured in this area. Thus, to conclude about the influx of EDCs in this estuary, water samples were taken every 2 months, during 1 year (2010) in low tide, at eight sites distributed along the estuary. Water samples (1 L) were preconcentrated in the Oasis HLB cartridges and cleaned in silica cartridges before their analysis by GC-MS. In summer, potentially hazardous amounts of estrogens (≈26 ng L^?1), alkylphenols (≈11.5 μg L^?1), alkylphenolethoxylates (≈13 μg L^?1), and phytoestrogens (≈5.6 μg L^?1) were measured. These data suggest that changes in the hydrodynamics of the estuary coupled with the increase of water temperatures interfere with the amount of EDCs in the water. Complementary physicochemical parameters also point to high levels of anthropogenic pollution in this area. Globally, the estrogenic load, expressed in ethynylestradiol equivalents, attained 71.8 ng L^?1 demonstrating that, all together, the measured EDCs pose important health risks for both biota and humans.     

Small drinking water systems under spatiotemporal water quality variability: a risk-based performance benchmarking framework

Traditional approaches for benchmarking drinking water systems are binary, based solely on the compliance and/or non-compliance of one or more water quality performance indicators against defined regulatory guidelines/standards. The consequence of water quality failure is dependent on location within a water supply system as well as time of the year (i.e., season) with varying levels of water consumption. Conventional approaches used for water quality comparison purposes fail to incorporate spatiotemporal variability and degrees of compliance and/or non-compliance. This can lead to misleading or inaccurate performance assessment data used in the performance benchmarking process. In this research, a hierarchical risk-based water quality performance benchmarking framework is proposed to evaluate small drinking water systems (SDWSs) through cross-comparison amongst similar systems. The proposed framework (R _WQI framework) is designed to quantify consequence associated with seasonal and location-specific water quality issues in a given drinking water supply system to facilitate more efficient decision-making for SDWSs striving for continuous performance improvement. Fuzzy rule-based modelling is used to address imprecision associated with measuring performance based on singular water quality guidelines/standards and the uncertainties present in SDWS operations and monitoring. This proposed R _WQI framework has been demonstrated using data collected from 16 SDWSs in Newfoundland and Labrador and Quebec, Canada, and compared to the Canadian Council of Ministers of the Environment WQI, a traditional, guidelines/standard-based approach. The study found that the R _WQI framework provides an in-depth state of water quality and benchmarks SDWSs more rationally based on the frequency of occurrence and consequence of failure events.     

Psychosocial and ergonomic survey of office and field jobs in a utility company

Introduction. The effect of different kinds of work on the psychosocial assessment of workers under the same management and organizational environment is investigated. Methods. A voluntary assessment in a utility company was carried out using the short version of the Copenhagen psychosocial questionnaire (CoPsoQ) on two occasions, 1.5 years apart. Initially, 25 office workers (11 men and 14 women) participated, while 14 of those workers (8 women and 6 men) participated in the second assessment together with 32 field workers. The sewage, water treatment and maintenance workers, totaling 32 men, also participated in a field ergonomics assessment using the Washington State Department of Labor and Industries field work ergonomic checklist. Results. The longitudinal outlook was fairly stable, with sustained severe scores in many CoPsoQ subscales and intensification of severity of workers’ control over work and esteem for men. A significantly higher esteem score resulted for field rather than office workers. Workers subjected to foul odors showed similar severity of psychosocial factors. Discussion. For most psychosocial dimensions, the organizational design and management system in place, as well as the overall cultural environment in which it operates, create a much stronger and more decisive impact than job-specific factors.     

Evaluation of extracted organic carbon and microbial biomass as stability parameters in ligno-cellulosic waste composts

Extracted organic C and microbial biomass were evaluated as stability parameters in 3 different ligno-cellulosic waste composts. Organic C was extracted by both water and alkali and further separated in humic-like carbon (HLC) and nonhumic carbon (NHC). Conventional humification parameters, such as humification index and degree of humification were calculated from NHC and HLC. Microbial biomass carbon (B(C)) was determined as an indicator of the degree of biochemical transformation, whereas ninhydrin reactive N (B(NIN)) was measured to obtain the stability parameter B(NIN)/N(TOT) (N(TOT), total N). The water-extracted organic C did not provide reliable information on the transformations underwent by the ligno-cellulosic wastes during composting, since its content remained almost unaltered during the whole process. In contrast, parameters based on the alkali-extracted organic C and microbial biomass clearly reflected organic matter (OM) changes during the process. There was an increase in the net amount of HLC in the alkali extracts throughout composting, especially in the first 7 to 12 wk of the process, as well as a relative enrichment of HLC with respect to NHC. Values of humification index and degree of humification in end products were consistent with an adequate level of compost stability. The stability parameter B(NIN)/N(TOT) showed to be a reliable indicator of stability in ligno-cellulosic wastes. Parameters based on the alkali-extracted C and microbial biomass clearly reflected the transformation of the OM during composting and can be used as stability parameters in ligno-cellulosic waste composts.