Toxicological aspects of trihalomethanes: a systematic review

Environmental Science and Pollution Research - Chlorine is considered the most used chemical agent for water disinfection worldwide. However, water chlorination can lead to by-product generation...     

Study of a coupled adsorption/electro-oxidation process as a tertiary treatment for tequila industry wastewater

Environmental Science and Pollution Research - Vinasse wastewater from tequila industry that has been conventionally treated is usually characterized by a chemical oxygen demand (COD) above...     

Potential environmental benefits of ionophores in ruminant diets

A concern of the USEPA is the volatilization of NH3 from animal manure and CH4 produced from ruminal fermentation. Excess N in the environment has been associated with adverse effects on human health, and CH4 and N2O emissions are sources of greenhouse gases. The objectives of this paper are to summarize and quantify the benefits of ionophores, principally monensin, in decreasing NH3 and CH4 emissions to the environment and reducing resource utilization in cattle (Bos spp.) production. The data indicate that monensin in the diets of ruminants may decrease protein degradation in the rumen and may increase feed protein utilization by an average of 3.5 percentage units. These changes would have an effect in reducing N losses and decreasing fecal N and the amount of protein that must be fed to meet animal requirements. Additionally, CH4 is produced by enteric fermentation in ruminants, which is responsible for about 33 to 39% of CH4 emissions from agriculture. Ionophores can reduce CH4 production by 25% and decrease feed intake by 4% without affecting animal performance. The inclusion of monensin in beef and dairy cattle diets may benefit air quality by reducing CH4 and N emissions and water quality by reducing N in manure, which can potentially leave the farm through leaching into ground water and through runoff into surface water.     

Mapping non-conventional atmospheric drinking-water harvesting opportunities in Central Eurasia: The case of Kazakhstan

Drinking water scarcity is becoming an urgent problem worldwide, and it affects developing and developed countries alike. Kazakhstan is not an exception and has its primary sources of drinking water (groundwater, rivers, and lakes) continuously depleted and polluted; moreover, the country will be close to its exploitation limits within the following decades. However, modern technologies allow us to harvest drinking water from unintegrated sources, like the atmosphere. Therefore, it is crucial to research which non-conventional technologies can be used to obtain drinking water from unintegrated sources for the country, considering the cost, viability of use through the year, and local climate conditions. Thus, the present assessment was performed for the 14 demographic regions in Kazakhstan and two city-states, and a map depicting the most feasible technology for each region is presented, including their levelized cost per liter. Seven mature technologies were found to be feasible in Kazakhstani year-round climates. However, Air AW₃ technology and Artificial Glaciers (AG) were the most cost-effective for family-size and village-size solutions, respectively. The water provided via utility pipelines proved to be the most cost-effective manner, when available, to supply drinking water at a family-size scale, but found a less expensive competitor in the AG technology for village-size solutions. Moreover, the lack of utility water pipelines in some Kazakhstani regions, principally countryside rural areas, makes it vital to deploy and implement these alternative water-harvesting technologies to guarantee the future water security of these regions.     

Riparian Vegetation and Water Chemistry in a Basin Under Semiarid Mediterranean Climate, Andarax River, Spain

A study has been made of the relationships between the characteristics of the riparian vegetation (floristic composition, structure and diversity) and the spatial–temporal variation of the quality of the stream waters in a basin under a semiarid Mediterranean climate in the southeastern Iberian Peninsula. The plant communities of the high reaches present greater specific richness and diversity (S _mean= 7.0 ± 3.4 and H′_mean= 2.0 ± 0.7) than do those of the middle and low reaches (S _mean= 4.5 ± 1.6 and H′_mean= 1.8 ± 0.6). One zone reached the highest specific richness (S= 12, H′= 3.2), which, apart from being situated in the intermediate stretch of the basin, represents a transitional state (ecotone) between the Salix and Tamarix communities. The characteristics of the waters analyzed indicate very high rates of erosion and runoff due to the nature of the soils (easily eroded marls) and to agricultural expansion and mining since the 16th century. The present-day riparian vegetation is not adequate to absorb the nitrates added to the basin by crop fertilization, reaching extremely high values, particularly during the dry period (between 1.2 and 42.5 mg/liter). Sewage dumping at three sampling stations did not appear to affect the specific composition of the woody vegetation. In the zones with watercourses, water salinity was low during the period of greater water flow, but considerably higher in the dry season (the upper limit was some 1.2 mS/m), resulting in a predominance of salt cedars over willows. Three types of saltcedar areas were distinguished: subhalophilous, which barely changes its chemical composition over the season; halophilous, which develops over strongly mineralized waters and markedly alters in chemical composition during the dry season; and hyperhalophilous, where salinity is extraordinarily high and quite constant throughout the year. A direct relationship was found between the dominance of Tamarix africana and abundance of NaCl.     

Groundwater Vulnerability Assessment for Organic Compounds: Fuzzy Multicriteria Approach for Mexico City

This study was based on a groundwater vulnerability assessment approach implemented for the Mexico City Metropolitan Area (MCMA). The approach is based on a fuzzy multicriteria procedure integrated in a geographic information system. The approach combined the potential contaminant sources with the permeability of geological materials. Initially, contaminant sources were ranked by experts through the Analytic Hierarchy Process. An aggregated contaminant sources map layer was obtained through the simple additive weighting method, using a scalar multiplication of criteria weights and binary maps showing the location of each source. A permeability map layer was obtained through the reclassification of a geology map using the respective hydraulic conductivity values, followed by a linear normalization of these values against a compatible scale. A fuzzy logic procedure was then applied to transform and combine the two map layers, resulting in a groundwater vulnerability map layer of five classes: very low, low, moderate, high, and very high. Results provided a more coherent assessment of the policy-making priorities considered when discussing the vulnerability of groundwater to organic compounds. The very high and high vulnerability areas covered a relatively small area (71 km² or 1.5% of the total study area), allowing the identification of the more critical locations. The advantage of a fuzzy logic procedure is that it enables the best possible use to be made of the information available regarding groundwater vulnerability in the MCMA.     

Time Series Forecasting of Cyanobacteria Blooms in the Crestuma Reservoir (Douro River, Portugal) Using Artificial Neural Networks

In this work, time series neural networks were used to predict the occurrence of toxic cyanobacterial blooms in Crestuma Reservoir, which is an important potable water supply for the Porto region, located in the north of Portugal. These models can potentially be used to provide water treatment plant operators with an early warning for developing cyanobacteria blooms. Physical, chemical, and biological parameters were collected at Crestuma Reservoir from 1999 to 2002. The data set was then divided into three independent time series, each with a fortnightly periodicity. One training series was used to “teach” the neural networks to predict results. Another series was used to verify the results, and to avoid over-fitting of the data. An additional independently collected data series was then used to test the efficacy of the model for predicting the abundance of cyanobacteria. All of the models tested in this study incorporated a prediction time (look-ahead parameter) equal to the sampling interval (two weeks). Various lag periods, from 2 to 52 weeks, were also investigated. The best model produced in this study provided the following correlations between the target and forecast values in the training, verification, and validation series: 1.000 (P = 0.000), 0.802 (P = 0.000), and 0.773 (P = 0.001), respectively. By applying this model to the three-year data set, we were able to predict fluctuations in cyanobacteria abundance in the Crestuma Reservoir, with a high level of precision. By incorporating a lag-period of eight weeks, we were able to detect secondary fluctuations in cyanobacterial abundance over the annual cycle.     

The valuation of historical sites: a case study of Valdivia,Chile

The economic valuation of cultural heritage is an area of increasing interest and an important research topic in the emerging field of cultural economics. Many services and values associated with cultural heritage are not traded in markets, and their estimation requires methods developed for the valuation of non-market goods, such as those used in environmental economics. This paper applies the contingent valuation method with double dichotomous choice to estimate the value of historical sites in the city of Valdivia, Chile. The valuation exercise was implemented by designing a hypothetical guided walking tour to a cluster of historical sites in the city centre, and surveying tourists visiting the city during the summer of 2004. Parametric and non-parametric statistical methods were used to estimate the survival distribution and the mean and median estimates of the willingness-to-pay (WTP). The study emphasizes the importance of explicitly treating heterogeneous preferences and the sensitivity of the survival distribution to the estimation methods used.     

Male mating history and female fecundity in the Lepidoptera: do male virgins make better partners?

In insects, large ejaculate and associated materials, including spermatophores, appear to have evolved via sexual selection acting on males to either delay female remating or to increase the rate of egg-laying. It is also possible, however, that females use nutrients transferred during mating to increase their lifetime fecundity. If so, male ejaculate size may also have evolved under natural selection as a form of paternal investment. In Lepidoptera, males with a greater number of prior matings tend to produce smaller spermatophores. However, the reported effects of male mating history on female fecundity vary widely among species. We therefore performed a meta-analysis using data from 29 studies of 25 species. Overall, the reproductive output of females mated to virgin males was significantly higher than that of females mated to sexually experienced males (Hedges d=0.33, P<0.01). A sample size of around 145 females per male mating type is required to detect an effect of this size with 80% statistical power at =0.05 (two-tailed). There was no difference in mean effect size between butterflies/skippers and moths. After controlling for any effect of taxonomic group, however, the mean effect size for polyandrous species was significantly greater than that for monandrous species (Hedges d=0.45 vs 0.25, P=0.01). We then discuss possible reasons why male mating history, presumably acting through its effect on spermatophore size, might have a stronger effect in polyandrous than monandrous species.Communicated by A. Cockburn