Methanol-based extraction protocol for insoluble and moderately water-soluble nanoparticles in plants to enable characterization by single particle ICP-MS.

The detection and characterization of soluble metal nanoparticles in plant tissues are an analytical challenge, though a scientific necessity for regulating nano-enabled agrichemicals. The efficacy of two extraction methods to prepare plant samples for analysis by single particle ICP-MS, an analytical method enabling both size determination and quantification of nanoparticles (NP), was assessed. A standard enzyme-based extraction was compared to a newly developed methanol-based approach. Au, CuO, and ZnO NPs were extracted from three different plant leaf materials (lettuce, corn, and kale) selected for their agricultural relevance and differing characteristics. The enzyme-based approach was found to be unsuitable because of changes in the recovered NP size distribution of CuO NP. The MeOH-based extraction allowed reproducible extraction of the particle size distribution (PSD) without major alteration caused by the extraction. The type of leaf tissue did not significantly affect the recovered PSD. Total metal losses during the extraction process were largely due to the filtration step prior to analysis by spICP-MS, though this did not significantly affect PSD recovery. The methanol extraction worked with the three different NPs and plants tested and is suitable for studying the fate of labile metal-based nano-enabled agrichemicals.

CuO Nanoparticles Alter the Rhizospheric Bacterial Community and Local Nitrogen Cycling for Wheat Grown in a Calcareous Soil.

The application of nanoparticles (NPs) to soils, as either fertilizers or fungicides (e.g., CuO NPs), has been proposed to improve the sustainability of agriculture. The observed effects could result directly from the NP-plant interactions or indirectly through effects on the soil microbiome. The objective of this study was to assess the effects of CuO NPs on the changes in the bacterial community structure and nitrogen-cycling-associated functions in a high pH soil and to correlate these changes with nitrate accumulation, soil parameter changes, and plant growth over 28 days. Triticum aestivum seedlings were exposed to 50 mg/kg CuO NPs, 50 mg/kg CuSO4, or 0.5 mg/kg CuSO4 in a standard soil (Lufa 2.1 soil, pH adjusted to 7.6). While Cu treatments reduced nitrate accumulation in the bulk soil, the effects were opposite in the rhizosphere (the soil influenced by root exudates). While nitrate accumulation in bulk soil negatively correlated with total Cu concentration, part of the nitrate concentration in the rhizosphere was explained by root uptake during plant growth, the rest being modulated by Cu treatments. The abundance of genes involved in the nitrogen cycle in the rhizosphere soil correlated with the ionic copper concentration. The increased nitrate concentration in the rhizosphere correlated with an increase of the gene abundance related to the nitrogen fixation and a decrease of denitrification gene abundance. Microbial diversity in bulk or rhizosphere soil under the different treatments alone could not explain these variations, while differences in the assemblages of bacteria associated with these functional gene abundances gave good insights. This study highlights the complexity of microbial N-related function in the rhizosphere and the need to characterize the rhizosphere soil, plant growth and root activity, NP (bio)transformations, along with microbial networks, to understand the impact of agrochemicals (here CuO NPs) on soil fertility.

A probabilistic model for designing and assessing the performance of eDNA sampling protocols.

Environmental DNA (eDNA) sampling, the detection of species-specific genetic material in water samples, is an emerging tool for monitoring aquatic invasive species. Optimizing eDNA sampling protocols can be challenging because there is imperfect understanding of how each step of the protocol influences its sensitivity. This paper develops a probabilistic model that characterizes each step of an eDNA sampling protocol to evaluate the protocol's overall detection sensitivity for one sample. The model is then applied to analyse how changes over time made to the eDNA sampling protocol to detect bighead (BH) and silver carp (SC) eDNA have influenced its sensitivity, and hence interpretation of the results. The model shows that changes to the protocol have caused the sensitivity of the protocol to fluctuate. A more efficient extraction method in 2013, new species-specific markers with a qPCR assay in 2014, and a more efficient capture method in 2015 have improved the sensitivity, while switching to a larger elution volume in 2013 and a smaller sample volume in 2015 have reduced the sensitivity. Overall, the sensitivity of the current protocol is higher for BH eDNA detection and SC eDNA detection compared to the original protocol used from 2009 to 2012. The paper shows how this model of eDNA sampling can be used to evaluate the effect of proposed changes in an eDNA sampling and analysis protocol on the sensitivity of that protocol to help researchers optimize their design.

Using graph learning to understand adverse pregnancy outcomes and stress pathways.

To identify pathways between stress indicators and adverse pregnancy outcomes, we applied a nonparametric graph-learning algorithm, PC-KCI, to data from an observational prospective cohort study. The Measurement of Maternal Stress study (MOMS) followed 744 women with a singleton intrauterine pregnancy recruited between June 2013 and May 2015. Infant adverse pregnancy outcomes were prematurity (<37 weeks' gestation), infant days spent in hospital after birth, and being small for gestational age (percentile gestational weight at birth). Maternal adverse pregnancy outcomes were pre-eclampsia, gestational diabetes, and gestational hypertension. PC-KCI replicated well-established pathways, such as the relationship between gestational weeks and preterm premature rupture of membranes. PC-KCI also identified previously unobserved pathways to adverse pregnancy outcomes, including 1) a link between hair cortisol levels (at 12-21 weeks of pregnancy) and pre-eclampsia; 2) two pathways to preterm birth depending on race, with one linking Hispanic race, pre-gestational diabetes and gestational weeks, and a second pathway linking black race, hair cortisol, preeclampsia, and gestational weeks; and 3) a relationship between maternal childhood trauma, perceived social stress in adulthood, and low weight for gestational age. Our approach confirmed previous findings and identified previously unobserved pathways to adverse pregnancy outcomes. It presents a method for a global assessment of a clinical problem for further study of possible causal pathways.

Effect of Soil Organic Matter, Soil pH, and Moisture Content on Solubility and Dissolution Rate of CuO NPs in Soil.

The objectives of this research were to quantify the impact of organic matter content, soil pH and moisture content on the dissolution rate and solubility of copper oxide nanoparticles (CuO NPs) in soil, and to develop an empirical model to predict the dissolution kinetics of CuO NPs in soil. CuO NPs were dosed into standard LUFA soils with various moisture content, pH and organic carbon content. Chemical extractions were applied to measure the CuO NP dissolution kinetics. Doubling the reactive organic carbon content in LUFA 2.1 soil increased the solubility of CuO NP 2.7-fold but did not change the dissolution rate constant. Increasing the soil pH from 5.9 to 6.8 in LUFA 2.2 soil decreased the dissolution rate constant from 0.56 mol1/3·kg1/3·s-1 to 0.17 mol1/3·kg1/3·s-1 without changing the solubility of CuO NP in soil. For six soils, the solubility of CuO NP correlated well with soil organic matter content ( R2 = 0.89) independent of soil pH. In contrast, the dissolution rate constant correlated with pH for pH < 6.3 ( R2 = 0.89), independent of soil organic matter content. These relationships predicted the solubility and dissolution rate constants of CuO NP in two test soils (pH 5.0 and pH 7.6). Moisture content showed negligible impact on the dissolution kinetics of CuO NPs. Our study suggests that soil pH and organic matter content affect the dissolution behavior of CuO NP in soil in a predictable manner.

Biogenic Cyanide Production Promotes Dissolution of Gold Nanoparticles in Soil.

Gold nanoparticles (Au NPs) are often used to study the physiochemical behavior and distribution of nanomaterials in natural systems because they are assumed to be inert under environmental conditions, even though Au can be oxidized and dissolved by a common environmental compound: cyanide. We used the cyanogenic soil bacterium, Chromobacterium violaceum, to demonstrate that quorum-sensing-regulated cyanide production could lead to a high rate of oxidative dissolution of Au NPs in soil. After 7 days of incubation in a pH 7.0 soil inoculated with C. violaceum, labile Au concentration increased from 0 to 15%. There was no observable dissolution when Au NPs were incubated in abiotic soil. In the same soil adjusted to pH 7.5, labile Au concentration increased up to 29% over the same time frame. Furthermore, we demonstrated that Au dissolution required quorum-sensing-regulated cyanide production in soil by inoculating the soil with different cell densities and using a quorum-sensing-deficient mutant of C. violaceum, CV026. Au NP dissolution experiments in liquid media coupled with mass spectrometry analysis confirmed that biogenic cyanide oxidized Au NPs to soluble Au(CN)2-. These results demonstrate under which conditions biologically enhanced metal dissolution can contribute to the overall geochemical transformation kinetics of nanoparticle in soils, even though the materials may be inert in abiotic environments.

CuO Nanoparticle Dissolution and Toxicity to Wheat ( Triticum aestivum) in Rhizosphere Soil.

It has been suggested, but not previously measured, that dissolution kinetics of soluble nanoparticles such as CuO nanoparticles (NPs) in soil affect their phytotoxicity. An added complexity is that such dissolution is also affected by the presence of plant roots. Here, we measured the rate of dissolution of CuO NPs in bulk soil, and in soil in which wheat plants ( Triticum aestivum) were grown under two soil NP dosing conditions: (a) freshly added CuO NPs (500 mg Cu/kg soil) and (b) CuO NPs aged for 28 d before planting. At the end of the plant growth period (14 d), available Cu was measured in three different soil compartments: bulk (not associated with roots), loosely attached to roots, and rhizosphere (soil firmly attached to roots). The labile Cu fraction increased from 17 mg/kg to 223 mg/kg in fresh treatments and from 283 mg/kg to 305 mg/kg in aged treatments over the growth period due to dissolution. Aging CuO NPs increased the toxicity to Triticum aestivum (reduction in root maximal length). The presence of roots in the soil had opposite and somewhat compensatory effects on NP dissolution, as measured in rhizosphere soil. pH increased 0.4 pH units for fresh NP treatments and 0.6 pH units for aged NPs. This lowered CuO NP dissolution in rhizosphere soil. Exudates from T. aestivum roots also increased soluble Cu in pore water. CaCl2 extractable Cu concentrations increaed in rhizosphere soil compared to bulk soil, from 1.8 mg/kg to 6.2 mg/kg in fresh treatment and from 3.4 mg/kg to 5.4 mg/kg in aged treatments. Our study correlated CuO NP dissolution and the resulting Cu ion exposure profile to phytotoxicity, and showed that plant-induced changes in rhizosphere conditions should be considered when measuring the dissolution of CuO NPs near roots.

Making sense of the noise: The effect of hydrology on silver carp eDNA detection in the Chicago area waterway system.

Environmental DNA (eDNA) sampling is an emerging tool for monitoring the spread of aquatic invasive species. One confounding factor when interpreting eDNA sampling evidence is that eDNA can be present in the water in the absence of living target organisms, originating from excreta, dead tissue, boats, or sewage effluent, etc. In the Chicago Area Waterway System (CAWS), electric fish dispersal barriers were built to prevent non-native Asian carp species from invading Lake Michigan, and yet Asian carp eDNA has been detected above the barriers sporadically since 2009. In this paper the influence of stream flow characteristics in the CAWS on the probability of invasive Asian carp eDNA detection in the CAWS from 2009 to 2012 was examined. In the CAWS, the direction of stream flow is mostly away from Lake Michigan, though there are infrequent reversals in flow direction towards Lake Michigan during dry spells. We find that the flow reversal volume into the Lake has a statistically significant positive relationship with eDNA detection probability, while other covariates, like gage height, precipitation, season, water temperature, dissolved oxygen concentration, pH and chlorophyll concentration do not. This suggests that stream flow direction is highly influential on eDNA detection in the CAWS and should be considered when interpreting eDNA evidence. We also find that the beta-binomial regression model provides a stronger fit for eDNA detection probability compared to a binomial regression model. This paper provides a statistical modeling framework for interpreting eDNA sampling evidence and for evaluating covariates influencing eDNA detection.

Time and Nanoparticle Concentration Affect the Extractability of Cu from CuO NP-Amended Soil.

We assess the effect of CuO nanoparticle (NP) concentration and soil aging time on the extractability of Cu from a standard sandy soil (Lufa 2.1). The soil was dosed with CuO NPs or Cu(NO3)2 at 10 mg/kg or 100 mg/kg of total added Cu, and then extracted using either 0.01 M CaCl2 or 0.005 M diethylenetriaminepentaacetic acid (DTPA) (pH 7.6) extraction fluid at selected times over 31 days. For the high dose of CuO NPs, the amount of DTPA-extractable Cu in soil increased from 3 wt % immediately after mixing to 38 wt % after 31 days. In contrast, the extractability of Cu(NO3)2 was highest initially, decreasing with time. The increase in extractability was attributed to dissolution of CuO NPs in the soil. This was confirmed with synchrotron X-ray absorption near edge structure measurements. The CuO NP dissolution kinetics were modeled by a first-order dissolution model. Our findings indicate that dissolution, concentration, and aging time are important factors that influence Cu extractability in CuO NP-amended soil and suggest that a time-dependent series of extractions could be developed as a functional assay to determine the dissolution rate constant.

Lung Cancer Risk from Radon in Marcellus Shale Gas in Northeast U.S. Homes.

The amount of radon in natural gas varies with its source. Little has been published about the radon from shale gas to date, making estimates of its impact on radon-induced lung cancer speculative. We measured radon in natural gas pipelines carrying gas from the Marcellus Shale in Pennsylvania and West Virginia. Radon concentrations ranged from 1,520 to 2,750 Bq/m3 (41-74 pCi/L), and the throughput-weighted average was 1,983 Bq/m3 (54 pCi/L). Potential radon exposure due to the use of Marcellus Shale gas for cooking and space heating using vent-free heaters or gas ranges in northeastern U.S. homes and apartments was assessed. Though the measured radon concentrations are higher than what has been previously reported, it is unlikely that exposure from natural gas cooking would exceed 1.2 Bq/m3 (<1% of the U.S. Environmental Protection Agency's action level). Using worst-case assumptions, we estimate the excess lifetime (70 years) lung cancer risk associated with cooking to be 1.8×10-4 (interval spanning 95% of simulation results: 8.5×10-5 , 3.4×10-4 ). The risk profile for supplemental heating with unvented gas appliances is similar. Individuals using unvented gas appliances to provide primary heating may face lifetime risks as high as 3.9×10-3 . Under current housing stock and gas consumption assumptions, expected levels of residential radon exposure due to unvented combustion of Marcellus Shale natural gas in the Northeast United States do not result in a detectable change in the lung cancer death rates.

Risk-Based Decision Making for Reoccupation of Contaminated Areas Following a Wide-Area Anthrax Release.

This article presents an analysis of postattack response strategies to mitigate the risks of reoccupying contaminated areas following a release of Bacillus anthracis spores (the bacterium responsible for causing anthrax) in an urban setting. The analysis is based on a hypothetical attack scenario in which individuals are exposed to B. anthracis spores during an initial aerosol release and then placed on prophylactic antibiotics that successfully protect them against the initial aerosol exposure. The risk from reoccupying buildings contaminated with spores due to their reaerosolization and inhalation is then evaluated. The response options considered include: decontamination of the buildings, vaccination of individuals reoccupying the buildings, extended evacuation of individuals from the contaminated buildings, and combinations of these options. The study uses a decision tree to estimate the costs and benefits of alternative response strategies across a range of exposure risks. Results for best estimates of model inputs suggest that the most cost-effective response for high-risk scenarios (individual chance of infection exceeding 11%) consists of evacuation and building decontamination. For infection risks between 4% and 11%, the preferred option is to evacuate for a short period, vaccinate, and then reoccupy once the vaccine has taken effect. For risks between 0.003% and 4%, the preferred option is to vaccinate only. For risks below 0.003%, none of the mitigation actions have positive expected monetary benefits. A sensitivity analysis indicates that for high-infection-likelihood scenarios, vaccination is recommended in the case where decontamination efficacy is less than 99.99%.

Stream dynamics and chemical transformations control the environmental fate of silver and zinc oxide nanoparticles in a watershed-scale model.

Mathematical models are needed to estimate environmental concentrations of engineered nanoparticles (NPs), which enter the environment upon the use and disposal of consumer goods and other products. We present a spatially resolved environmental fate model for the James River Basin, Virginia, that explores the influence of daily variation in streamflow, sediment transport, and stream loads from point and nonpoint sources on water column and sediment concentrations of zinc oxide (ZnO) and silver (Ag) NPs and their reaction byproducts over 20 simulation years. Spatial and temporal variability in sediment transport rates led to high NP transport such that less than 6% of NP-derived metals were retained in the river and sediments. Chemical transformations entirely eliminated ZnO NPs and doubled Zn mobility in the stream relative to Ag. Agricultural runoff accounted for 23% of total metal stream loads from NPs. Average NP-derived metal concentrations in the sediment varied spatially up to 9 orders of magnitude, highlighting the need for high-resolution models. Overall, our results suggest that "first generation" NP risk models have probably misrepresented NP fate in freshwater rivers due to low model resolutions and the simplification of NP chemistry and sediment transport.

Modeling nanomaterial environmental fate in aquatic systems.

Mathematical models improve our fundamental understanding of the environmental behavior, fate, and transport of engineered nanomaterials (NMs, chemical substances or materials roughly 1-100 nm in size) and facilitate risk assessment and management activities. Although today's large-scale environmental fate models for NMs are a considerable improvement over early efforts, a gap still remains between the experimental research performed to date on the environmental fate of NMs and its incorporation into models. This article provides an introduction to the current state of the science in modeling the fate and behavior of NMs in aquatic environments. We address the strengths and weaknesses of existing fate models, identify the challenges facing researchers in developing and validating these models, and offer a perspective on how these challenges can be addressed through the combined efforts of modelers and experimentalists.

A meta-analysis of carbon nanotube pulmonary toxicity studies--how physical dimensions and impurities affect the toxicity of carbon nanotubes.

This article presents a regression-tree-based meta-analysis of rodent pulmonary toxicity studies of uncoated, nonfunctionalized carbon nanotube (CNT) exposure. The resulting analysis provides quantitative estimates of the contribution of CNT attributes (impurities, physical dimensions, and aggregation) to pulmonary toxicity indicators in bronchoalveolar lavage fluid: neutrophil and macrophage count, and lactate dehydrogenase and total protein concentrations. The method employs classification and regression tree (CART) models, techniques that are relatively insensitive to data defects that impair other types of regression analysis: high dimensionality, nonlinearity, correlated variables, and significant quantities of missing values. Three types of analysis are presented: the RT, the random forest (RF), and a random-forest-based dose-response model. The RT shows the best single model supported by all the data and typically contains a small number of variables. The RF shows how much variance reduction is associated with every variable in the data set. The dose-response model is used to isolate the effects of CNT attributes from the CNT dose, showing the shift in the dose-response caused by the attribute across the measured range of CNT doses. It was found that the CNT attributes that contribute the most to pulmonary toxicity were metallic impurities (cobalt significantly increased observed toxicity, while other impurities had mixed effects), CNT length (negatively correlated with most toxicity indicators), CNT diameter (significantly positively associated with toxicity), and aggregate size (negatively correlated with cell damage indicators and positively correlated with immune response indicators). Increasing CNT N2 -BET-specific surface area decreased toxicity indicators.

Surface water withdrawals for Marcellus Shale gas development: performance of alternative regulatory approaches in the Upper Ohio River Basin.

Almost all of the water used for developing Marcellus Shale gas is withdrawn from surface water sources. State environmental and interstate water authorities take different approaches to managing these withdrawals. In the Upper Ohio River Basin, which covers the western third of Pennsylvania, the Pennsylvania Department of Environmental Protection requires that all water sources used for development have an approved water management plan. For surface water sources the plans stipulate the amount and timing of withdrawals from each source as a function of annual streamflow statistics. Neighboring regulatory authorities and some environmental groups now favor the use of monthly streamflow statistics to establish the conditions for water withdrawals. Our analysis indicates that, given the state of flow measurement data in the Upper Ohio River Basin, the annual streamflow statistics are more likely to prevent water withdrawals during the driest times of the year when aquatic ecosystems are most stressed, and to result in fewer and smaller occurrences of computed low-flow ecodeficits.

Modeling nanosilver transformations in freshwater sediments.

Silver nanoparticles (AgNPs), an effective antibacterial agent, are a significant and fast-growing application of nanotechnology in consumer goods. The toxicity of AgNPs released to surface waters during the use or disposal of AgNP-containing products will depend on the chemical transformations the nanoparticles undergo in the environment. We present a simple one-dimensional diagenetic model for predicting AgNP distribution and silver speciation in freshwater sediments. The model is calibrated to data collected from AgNP-dosed large-scale freshwater wetland mesocosms. The model predicts that AgNP sulfidation will retard nanoparticle oxidation and ion release. The resultant Ag2S-coated AgNPs are expected to persist and accumulate in sediment downstream from sources of AgNPs. Silver speciation and persistence in the sediment depend on the seasonally variable availability of organic carbon and dissolved oxygen. The half-life of typical sulfidized (85% Ag2S) AgNPs may vary from less than 10 years to over a century depending on redox conditions. No significant difference in silver speciation and distribution is observed between ≥50% Ag2S and 100% Ag2S AgNPs. Formation and efflux of toxic silver ion is reduced in eutrophic systems and maximized in oligotrophic systems.

Modeling nanomaterial fate in wastewater treatment: Monte Carlo simulation of silver nanoparticles (nano-Ag).

Wastewater effluent and sewage sludge are predicted to be important release pathways for nanomaterials used in many consumer products. The uncertainty and variability of potential nanomaterial inputs, nanomaterial properties, and the operation of the wastewater treatment plant contribute to the difficulty of predicting sludge and effluent nanomaterial concentration. With a model parsimony approach, we developed a mass-balance representation of engineered nanomaterial (ENM) behavior based on a minimal number of input variables to describe release quantities to the environment. Our simulations show that significant differences in the removal of silver nanoparticles (nano-Ag) can be expected based on the type of engineered coatings used to stabilize these materials in suspension. At current production estimates, 95% of the estimated effluent concentrations of the nano-Ag considered to be least well-removed by the average wastewater treatment plant are calculated to fall below 0.12 µg/L, while 95% of the estimated sludge concentrations of nano-Ag with coatings that increase their likelihood of being present in biosolids, fall below 0.35 µg/L.

Development of failure scenarios for biosolids land application risk assessment.

Although deviations from standard guidance for land application of biosolids occur in practice, their importance is largely unknown. A list of such deviations (plausible failure scenarios) were identified at a workshop of industry, regulators, and academic professionals. Next, a survey of similar professionals was conducted to rank the plausible failure scenarios according to their severity, frequency, incentive to ignore control measures, gaps in existing control processes, public concern, and overall concern. Survey participants rated intentional dumping (unpermitted disposal) as the most severe of the failure scenarios, lack of worker protection as the most frequent scenario, and application of Class A biosolids that have failed to meet treatment standards as the scenario for which incentives to ignore control measures are highest. Failure of public access restrictions to application sites was the scenario for which existing controls were judged the weakest; application of biosolids too close to wells was ranked highest for public concern and for overall concern. Two scenarios for which existing controls were considered weaker, site restriction violations and animal contact leading to human exposure, were also rated as frequently occurring. Both scenarios are related in that they (1) involve inappropriate access to a site before the required time has elapsed, and (2) could be addressed through similar biosolids management measures.

Should cities invest in sheltering-in-place measures against chlorine truck attacks by terrorists?

After an intentional release of chlorine in an office district, public responses such as sheltering-in-place could save many lives if rapid enough. However, previous work does not estimate how fast and effective such responses would be for several possible investments in attack detection, public alert, and building ventilation, nor whether such measures would be cost effective. We estimate public response times with investment options in place, and resulting changes in fatalities as well as system costs, including false alarm costs, and cost effectiveness in terms of cost per net death avoided. The measures do have life-saving potential, especially if all response times are at or near the lower limits of the ranges assumed in this article. However, due to uncertainties, it is not clear that responses would be rapid enough to save many people. In some cases total fatalities would increase, since sheltering after chlorine vapor has already entered buildings can increase occupants' chlorine exposure. None of the options considered have median cost per statistical life saved meeting a cost-effectiveness threshold of $6.5 million across all of the chlorine exposure dose-response and ingress-delay models considered here, even if there were one attack per year in the area covered by the system. Given these and other issues discussed in this article, at this point investments to improve sheltering-in-place capability appear not to be robust strategies for reducing fatalities from chlorine attack in an office district.