Evaluation of olive oil mill wastewater toxicity on spinach

Background, aim, and scope

Olive oil mill wastewater (OMW), a by-product of the olive oil extraction process, is annually produced in huge amounts in olive-growing areas and represents a significant environmental problem in Mediterranean areas. We studied the impact of OMW dilutions (1:20 and 1:10) on spinach plants in order to evaluate OMW dilutions as a low-cost alternative method for the disposal of this waste.

Materials and methods

The effects of OMW dilutions were evaluated on seed germination, shoot and root elongation, biomass production, nutrient uptake and translocation, ascorbic acid content, polyphenols, photosynthetic pigments, and photosynthetic performance of spinach.

Results

Plant biomass was more affected than plant height and total chlorophyll; carotenoid and ascorbic acid content progressively decreased with decreasing OMW dilution. Exposure to both OMW dilutions resulted in overaccumulation of total polyphenols, which were negatively correlated to plant biomass and nutrients. Nutrient (Fe, Ca, and Mg) content was insufficient leading to reduced growth. Water use efficiency decreased mainly due to decreased CO₂ assimilation rate rather than to a decline of transpiration rate. Disturbances in photosystem II (PSII) photochemical efficiency could be better envisaged by the ratio between variable fluorescence and initial fluorescence (Fv/Fo), which showed much greater amplitude than the maximal photochemical efficiency of PSII photochemistry (Fv/Fm).

Conclusions

From the data obtained, it is suggested that 1:20 OMW dilutions are still phytotoxic and that higher OMW dilutions should be used in order to use this waste for the irrigation of spinach plants.     

Resolving the interactions between population density and air pollution emissions controls in the San Joaquin Valley, USA

The effectiveness of emissions control programs designed to reduce concentrations of airborne particulate matter with an aerodynamic diameter < 2.5 microm (PM2.5) in California's San Joaquin Valley was studied in the year 2030 under three growth scenarios: low, medium, and high population density. Base-case inventories for each choice of population density were created using a coupled emissions modeling system that simultaneously considered interactions between land use and transportation, area source, and point source emissions. The ambient PM2.5 response to each combination of population density and emissions control was evaluated using a regional chemical transport model over a 3-week winter stagnation episode. Comparisons between scenarios were based on regional average and population-weighted PM2.5 concentrations. In the absence of any emissions control program, population-weighted concentrations of PM2.5 in the future San Joaquin Valley are lowest undergrowth scenarios that emphasize low population density. A complete ban on wood burning and a 90% reduction in emissions from food cooking operations and diesel engines must occur before medium- to high-density growth scenarios result in lower population-weighted concentrations of PM2.5. These trends partly reflect the fact that existing downtown urban cores that naturally act as anchor points for new high-density growth in the San Joaquin Valley are located close to major transportation corridors for goods movement. Adding growth buffers around transportation corridors had little impact in the current analysis, since the 8-km resolution of the chemical transport model already provided an artificial buffer around major emissions sources. Assuming that future emissions controls will greatly reduce or eliminate emissions from residential wood burning, food cooking, and diesel engines, the 2030 growth scenario using "as-planned" (medium) population density achieves the lowest population-weighted average PM2.5 concentration in the future San Joaquin Valley during a severe winter stagnation event. Implications: The San Joaquin Valley is one of the most heavily polluted air basins in the United States that are projected to experience strong population growth in the coming decades. The best plan to improve air quality in the region combines medium- or high-density population growth with rigorous emissions controls. In the absences of controls, high-density growth leads to increased population exposure to PM2.5 compared with low-density growth scenarios (urban sprawl).     

Synthetic Media: A Promising New Treatment Technology for 1,4‐Dioxane

1,4‐Dioxane (14DX) is classified as a probable human carcinogen by the US Environmental Protection Agency (EPA), and it has toxic effects on the kidney and liver. EPA's Health Advisory Level (HAL) for 14DX is 0.35 micrograms per liter (μg/L). Accordingly, several states have lowered their drinking water advisory levels and site cleanup levels. The widespread occurrence of 14DX in contaminated groundwater has contributed to a growing demand for remediation services. Treating 14DX is a challenge due to its very low Henry's law constant, low sorption potential, and strong ether linkages. The primary solution for 14DX remediation has been various forms of advanced oxidation processes (AOP), namely pump and treat followed by ex situ treatment with catalyzed ultraviolet light oxidation or ozone‐peroxidation. Many of the available advanced oxidation systems are complex, requiring careful monitoring and maintenance to adjust for variable source water and operating conditions. Synthetic media is a relatively new 14DX treatment technology that overcomes many of the operating challenges faced by existing technologies. AMBERSORB? 560 (AMBERSORB) has recently demonstrated the effective removal of 14DX over a wide range of concentrations and operating conditions, including those created by in situ thermal remediation. Consistent and reliable treatment down to sub‐0.3 μg/L levels differentiates synthetic media technology from other 14DX treatment technologies. AMBERSORB provides a solution to the problem of “stranded capital” by offering a 14DX treatment system capable of meeting regulatory standards today and in the foreseeable future. © 2014 Wiley Periodicals, Inc.     

Probability analyses of combining background concentrations with model-predicted concentrations

In order to calculate total concentrations for comparison to ambient air quality standards, monitored background concentrations are often combined with model predicted concentrations. Models have low skill in predicting the locations or time series of observed concentrations. Further, adding fixed points on the probability distributions of monitored and predicted concentrations is very conservative and not mathematically correct. Simply adding the 99th percentile predicted to the 99th percentile background will not yield the 99th percentile of the combined distributions. Instead, an appropriate distribution can be created by calculating all possible pairwise combinations of the 1-hr daily maximum observed background and daily maximum predicted concentration, from which a 99th percentile total value can be obtained. This paper reviews some techniques commonly used for determining background concentrations and combining modeled and background concentrations. The paper proposes an approach to determine the joint probabilities of occurrence of modeled and background concentrations. The pairwise combinations approach yields a more realistic prediction of total concentrations than the U.S. Environmental Protection Agency's (EPA) guidance approach and agrees with the probabilistic form of the National Ambient Air Quality Standards.

Implications: EPA's current approaches to determining background concentrations for compliance modeling purposes often lead to “double counting” of background concentrations and actual plume impacts and thus lead to overpredictions of total impacts. Further, the current Tier 1 approach of simply adding the top ends of the background and model predicted concentrations (e.g., adding the 99th percentiles of these distributions together) results in design value concentrations at probabilities in excess of the form of the National Ambient Air Quality Standards.     

The electron density distribution in pyridinium and bipyridylium compounds and its relevance to their adsorption by expanding lattice clays

Abstract

Charge distributions in 1, 1'‐ethylene‐2, 2'‐bipyridylium (diquat), 1,1'‐dimethyl‐4,4'‐bipyridylium (paraquat) and 1‐methylpyridinium organocations were calculated by a Complete Neglect of Differential Overlap semi‐empirical quantum mechanical procedure. The data show that the positive charges in the organocations are distributed around the molecules and are greatest in the positions ortho and para to the heterocyclic nitrogen atoms. Earlier interpretations of the mechanisms of adsorption of paraquat and diquat by soils and clays assumed that the charges were located in the heterocyclic nitrogen atoms. Here some consideration is given to the influence of the charge delocalizations on the processes of adsorption by montmorillonite and vermiculite clay preparations.     

Mutagenicity evaluation of chemical pesticides

Abstract

Over the last few decades, the use of chemical pesticides has increased dramatically in the U.S. This relatively sudden increase greatly concerns the U.S. Environmental Protection Agency (EPA), since it has the responsibility for ensuring the safety of all pesticides used in the U.S. In response to this concern, EPA has established a review program, the Rebuttable Presumption Against Registration (RPAR), for periodically reassessing the mutagenic and carcinogenic potential of pesticide compounds.

This paper presents a review and evaluation of the data reported in the literature on six chemical pesticides suspect for mutagenic potential. The pesticide chemicals discussed are maleic hydrazide; rotenone; monuron; diallate; triallate, and benomyl.     

Feral swine disturbance at important archaeological sites

Feral swine are well known as environmentally destructive invasive animals in many areas around the world, where they degrade native habitats, harm rare plant and animal species, damage agricultural interests, and spread disease. We provide the first quantification of their potential as agents of disturbance at archaeological sites. Our study was conducted in south-central Florida at Avon Park Air Force Range, a base comprising over 40,000 ha and containing many archaeological sites. To determine the identifiable prevalence of feral swine disturbance, we examined 36 sites registered with the Florida State Historic Preservation Office and also eligible for inclusion in the National Register of Historic Places (NRHP). Moreover, we evaluated the extent of swine disturbance at a prehistoric site of extraordinary significance to Florida’s prehistory, “Dead Cow.” Fifteen of the 36 NRHP-eligible sites (42 %) had some level of swine disturbance, including 14 of 30 (47 %) sites known to have artifacts within 20 cm of the surface (well within swine rooting depths). At the Dead Cow site, we documented disturbance at 74 % of shovel test points. Sites with shallow artifact depositions appeared highly vulnerable to disturbance by feral swine, threatening destruction of artifact stratigraphy and provenience. Our observations likely are a minimal representation of accumulated damage. These irreplaceable sites tell the area’s land use story across the millennia. That they are under threat from feral swine should serve broad notice of potential threats that feral swine may pose to archaeological sites globally, making effective swine management imperative for site protection.     

Misuse of null hypothesis significance testing: would estimation of positive and negative predictive values improve certainty of chemical risk assessment?

Although generally misunderstood, the p value is the probability of the test results or more extreme results given H₀ is true: it is not the probability of H₀ being true given the results. To obtain directly useful insight about H₀, the positive predictive value (PPV) and the negative predictive value (NPV) may be useful extensions of null hypothesis significance testing (NHST). They provide information about the probability of statistically significant and non-significant test outcomes being true based on an a priori defined biologically meaningful effect size. The present study explores the utility of PPV and NPV in an ecotoxicological context by using the frequently applied Daphnia magna reproduction test (OECD guideline 211) and the chemical stressor lindane as a model system. The results indicate that especially the NPV deviates meaningfully between a test design strictly following the guideline and an experimental procedure controlling for α and β at the level of 0.05. Consequently, PPV and NPV may be useful supplements to NHST that inform the researcher about the level of confidence warranted by both statistically significant and non-significant test results. This approach also reinforces the value of considering α, β, and a biologically meaningful effect size a priori.     

Relationships Between Nitrogen Transformation Rates and Gene Abundance in a Riparian Buffer Soil

Denitrification is a critical biogeochemical process that results in the conversion of nitrate to volatile products, and thus is a major route of nitrogen loss from terrestrial environments. Riparian buffers are an important management tool that is widely utilized to protect water from non-point source pollution. However, riparian buffers vary in their nitrate removal effectiveness, and thus there is a need for mechanistic studies to explore nitrate dynamics in buffer soils. The objectives of this study were to examine the influence of specific types of soluble organic matter on nitrate loss and nitrous oxide production rates, and to elucidate the relationships between these rates and the abundances of functional genes in a riparian buffer soil. Continuous-flow soil column experiments were performed to investigate the effect of three types of soluble organic matter (citric acid, alginic acid, and Suwannee River dissolved organic carbon) on rates of nitrate loss and nitrous oxide production. We found that nitrate loss rates increased as citric acid concentrations increased; however, rates of nitrate loss were weakly affected or not affected by the addition of the other types of organic matter. In all experiments, rates of nitrous oxide production mirrored nitrate loss rates. In addition, quantitative polymerase chain reaction (qPCR) was utilized to quantify the number of genes known to encode enzymes that catalyze nitrite reduction (i.e., nirS and nirK) in soil that was collected at the conclusion of column experiments. Nitrate loss and nitrous oxide production rates trended with copy numbers of both nir and 16s rDNA genes. The results suggest that low-molecular mass organic species are more effective at promoting nitrogen transformations than large biopolymers or humic substances, and also help to link genetic potential to chemical reactivity.     

Addressing climate change: Determinants of consumers' willingness to act and to support policy measures

Consumers influence climate change through their consumption patterns and their support or dismissal of climate mitigation policy measures. Both climate-friendly actions and policy support comprise a broad range of options, which vary in manifold ways and, therefore, might be influenced by different factors. The aims of the study were, therefore, two-fold: first, we intended to find a meaningful way to classify different ways of addressing climate change. Second, we aimed to examine which determinants influence people's willingness to engage in these behaviors. We conducted a large-scale mail survey in Switzerland in which respondents rated, among other items, their willingness to act or support a range of possible actions and mitigations measures. A principal component analysis indicated that a distinction in terms of a behavior's directness as well as a differentiation according to perceived costs seem to be appropriate to classify climate-friendly actions. Multiple regression analyses showed that perceived costs and perceived climate benefit turned out to be the strongest predictors for willingness to act or to support climate policy measures. The strong influence of perceived climate benefit might reflect a strategy of reducing cognitive dissonance. As high-cost behaviors are more difficult to adopt, consumers may reduce dissonance by dismissing high-cost behaviors as not effective in terms of climate mitigation. Political affiliation proved to be another strong determinant of willingness to act or support. Participants on the right wing were less willing to show indirect climate-friendly behaviors, change their mobility behaviors, and to support any type of climate mitigation policy measures. Climate-friendly low-cost behaviors, however, were not influenced by political affiliation.