Illustrating sensitivity and uncertainty in environmental fate models using partitioning maps

Variations of model predictions of the environmental fate of organic contaminants are usually analyzed for only one or at most a few selected chemicals, even though parameter sensitivity and contribution to uncertainty are widely different for different chemicals. A graphical method is introduced that allows for the comprehensive investigation of model sensitivity and uncertainty for all persistent organic nonelectrolytes at the same time. This is achieved by defining a two-dimensional hypothetical "chemical space" as a function of the equilibrium partition coefficients between air, water, and octanol (KOW, KAW, KOA), and plotting sensitivity and/or uncertainty of a specific model result to each input parameter as a function of this chemical space. The approach is illustrated for the bulk phase concentrations in air, water, soil, and sediment calculated by a level III model. Colored contour maps facilitate the identification of those input parameters that cause a high output variation of hypothetical and real chemicals. They also allow for the easy categorization of chemicals in terms of common parameter sensitivities, and thus comparable environmental behavior. Sensitivity varies with the mode of emission and the degradability of the chemicals, making it necessary to develop multiple sets of contour maps. Comparison of these sets of maps in turn allows the investigation of how parameter sensitivities change as a result of changes in mode of emission and persistence. The presented method can be used for investigating the sensitivity of any prediction obtained with any linear fate model that characterizes the partitioning behavior of organic chemicals with KAW, KoW, and KOA. Once the sensitivity maps have been constructed for a given environmental scenario, it is possible to perform a sensitivity analysis for a specific chemical by simple. placement of the substances' partitioning combinations within the chemical space. The maps can further contribute to the mechanistic understanding of a model's behavior, can aid in explaining observations of divergent environmental behavior of related substances, and can provide a rationale for grouping chemicals with similar model behavior, or for selecting representative example chemicals for a model investigation. They can also help in deciding when accurate and precise knowledge of physical chemical property data is crucial and when approximate numbers suffice to conduct a model investigation.     

Modeling the effect of snow and ice on the global environmental fate and long-range transport potential of semivolatile organic compounds

Snow and ice have been implemented in a global multimedia box model to investigate the influence of these media on the environmental fate and long-range transport (LRT) of semivolatile organic compounds (SOCs). Investigated compounds include HCB, PCB28, PCB180, PBDE47, PBDE209, alpha-HCH, and dacthal. In low latitudes, snow acts as a transfer medium taking up chemicals from air and releasing them to water or soil during snowmelt. In high latitudes, snow and ice shield water, soil, and vegetation from chemical deposition. In the model version including snow and ice (scenario 2), the mass of chemicals in soil in high latitudes is between 27% (HCB) and 97% (alpha-HCH) of the mass calculated with the model version without snow and ice (scenario 1). Amounts in Arctic seawater in scenario 2 are 8% (alpha-HCH) to 21% (dacthal) of the amounts obtained in scenario 1. For all investigated chemicals except alpha-HCH, presence of snow and ice in the model increases the concentration in air by a factor of 2 (HCB)to 10 (PBDE209). Because of reduced net deposition to snow-covered surfaces in high latitudes, LRT to the Arctic is reduced for most chemicals whereas transport to the south is more pronounced than in scenario 1 ("southward shift"). The presence of snow and ice thus considerably changes the environmental fate of SOCs.     

用于过滤介质的环保型高性能粘合剂

介绍了APP公司生产的用于过滤介质的环保型高性能粘合剂(AIRFLEXEVCl粘合剂)。该粘合剂可赋予过滤介质必需的性能,还可赋予阻燃性等特殊的性能,符合环保要求和化学品的相关规定,能确保生产过程的安全性和产品的安全性。     

Scenario projections for future market potentials of biobased bulk chemicals

Three scenario projections for future market potentials of biobased bulk chemicals produced by means of white biotechnology are developed for Europe (EU-25) until the year 2050, and potential nonrenewable energy savings, greenhouse gas emission reduction, and land use consequences are analyzed. These scenarios assume benign, moderate, and disadvantageous conditions for biobased chemicals. The scenario analysis yields a broad range of values for the possible market development of white biotechnology chemicals, that is, resulting in a share of white biotechnology chemicals relative to all organic chemicals of about 7 (or 5 million tonnes), 17.5 (or 26 million tonnes), or 38% (or 113 million tonnes) in 2050. We conclude that under favorable conditions, white biotechnology enables substantial savings of nonrenewable energy use (NREU) and greenhouse gas (GHG) emissions compared to the energy use of the future production of all organic chemicals from fossil resources. Savings of NREU reach up to 17% for starch crops and up to 31% for lignocellulosic feedstock by 2050, and saving percentages for GHG emissions are in a similar range. Parallel to these environmental benefits, economic advantages of up to 75 billion Euro production cost savings arise.     

Application of multimedia models for screening assessment of long-range transport potential and overall persistence

We propose a multimedia model-based methodology to evaluate whether a chemical substance qualifies as POP-like based on overall persistence (Pov) and potential for long-range transport (LRTP). It relies upon screening chemicals against the Pov and LRTP characteristics of selected reference chemicals with well-established environmental fates. Results indicate that chemicals of high and low concern in terms of persistence and long-range transport can be consistently identified by eight contemporary multimedia models using the proposed methodology. Model results for three hypothetical chemicals illustrate that the model-based classification of chemicals according to Pov and LRTP is not always consistent with the single-media half-life approach proposed by the UNEP Stockholm Convention and thatthe models provide additional insight into the likely long-term hazards associated with chemicals in the environment. We suggest this model-based classification method be adopted as a complement to screening against defined half-life criteria at the initial stages of tiered assessments designed to identify POP-like chemicals and to prioritize further environmental fate studies for new and existing chemicals.     

Statistical analysis of chemical transformation kinetics using Markov-Chain Monte Carlo methods

For the risk assessment of chemicals intentionally released into the environment, as, e.g., pesticides, it is indispensable to investigate their environmental fate. Main characteristics in this context are transformation rates and partitioning behavior. In most cases the relevant parameters are not directly measurable but are determined indirectly from experimentally determined concentrations in various environmental compartments. Usually this is done by fitting mathematical models, which are usually nonlinear, to the observed data and such deriving estimates of the parameter values. Statistical analysis is then used to judge the uncertainty of the estimates. Of particular interest in this context is the question whether degradation rates are significantly different from zero. Standard procedure is to use nonlinear least-squares methods to fit the models and to estimate the standard errors of the estimated parameters from Fisher's Information matrix and estimated level of measurement noise. This, however, frequently leads to counterintuitive results as the estimated probability distributions of the parameters based on local linearization of the optimized models are often too wide or at least differ significantly in shape from the real distribution. In this paper we identify the shortcoming of this procedure and propose a statistically valid approach based on Markov-Chain Monte Carlo sampling that is appropriate to determine the real probability distribution of model parameters. The effectiveness of this method is demonstrated on three data sets. Although it is generally applicable to different problems where model parameters are to be inferred, in the present case for simplicity we restrict the discussion to the evaluation of metabolic degradation of chemicals in soil. It is shown that the method is successfully applicable to problems of different complexity. We applied it to kinetic data from compounds with one and five metabolites. Additionally, using simulated data, it is shown that the MCMC method estimates the real probability distributions of parameters well and much better than the standard optimization approach.     

A Systematic Approach for Solving Large-Scale Problems by Neural Network: Open Refrigerated Display Cases and Droplet Evaporation Problems

A systematic approach for solving a large-scale design problem is proposed. The method consists of building a multidimensional test case matrix connecting an output (scalar or vector) to an input vector. Every element of the input vector spans over its possible minimum and maximum values with one or more levels in between. The experimental and validated computational methods are combined to find the output as a function of all permutations of the input variables. The results are used to train a neural network program to perform the proper interpolation for any other expected scenario. The number of required experiments is obtained asymptotically by adding more data to the neural network training set and examining the error. The applicability and feasibility of this approach is shown in two different problems: first, predicting and minimizing the infiltration rate into an open refrigerated display case; and second, predicting the evaporation rate of sessile microdroplets on a nonpermeable surface.     

Aqueous photolysis of the organic ultraviolet filter chemical octyl methoxycinnamate

Organic UV filter chemicals are the active ingredients in personal care products designed to protect the skin from UV radiation, and hundreds of tons are estimated to be produced annually. Despite their entrance into the aquatic environment by both direct and indirect routes and their detection in surface waters and fish, little is known about their environmental fate. UV filter chemicals are designed to be photostable, but some undergo transformation upon exposure to UV light. Octyl methoxycinnamate (OMC), a commonly used UV filter chemical, degrades rapidly by direct photolysis; previous studies have focused on its photoisomerization, and a few investigators have reported the formation of cyclodimers. Here, we present the kinetics and quantum efficiency of the direct photolysis of OMC and confirm that dimerization occurs as a result of direct photolysis in aqueous solution. Likely identities of the dimers are offered based on comparison to reported results for other cinnamate derivatives. We have identified additional products of direct photolysis that have not been previously reported and investigated their photostability, as well as the mechanism of product formation. There is also some evidence of indirect photolysis in the presence of dissolved natural organic matter.     

The impact of endocrine disruptors on oocyte competence

To date, approximately 60 chemicals have been identified as endocrine disruptors: exogenous agents that interfere with various aspects of natural hormone physiology. The potential reproductive and health hazards of these environmental chemicals have recently generated concern among the scientific community, policy makers and general public. The present review presents and discusses the available evidence that environmental chemicals are causing ovarian toxicity in various species, with particular attention to farm animals. The impact of chronic exposure to endocrine disruptors via food and drinking water cannot be neglected when studying fertility problems in these species. This review focuses attention on the superfamily of organochlorine chemicals, persistent organic pollutants (POPs), because of their persistence in the environment, ability to concentrate up the food chain, continued detection in environmental matrices and ability to be stored in the adipose tissue of animals and humans. Published data clearly indicate that POPs disrupt mammalian oocyte maturation and follicle physiology in every species studied so far, including farm animals. However, as most of the data available still derive from experiments performed on laboratory species or in vitro models, great care should be taken when extrapolations to other species or environmental situations are attempted.     

Genomic selection using indicator traits to reduce the environmental impact of milk production

The aim of this simulation study was to test the hypothesis that phenotype information of specific indicator traits of environmental importance recorded on a small-scale can be implemented in breeding schemes with genomic selection to reduce the environmental impact of milk production. A stochastic simulation was undertaken to test alternative breeding strategies. The breeding goal consisted of milk production, a functional trait, and environmental impact (EI). The indicator traits (IT) for EI were categorized as large-, medium-, or small-scale, depending on how the traits were recorded. The large-scale traits were stayability and stature; the medium-scale traits were live weight and methane in the breath of the cow measured during milking; and the small-scale traits were residual feed intake and methane recorded in a respiration chamber. Simulated scenarios considered information for just one IT in addition to information for milk production and functional traits. The annual monetary genetic gain was highest in the large-scale scenario that included stayability as IT. The annual monetary gain in the scenarios with medium- or small-scale IT varied from €50.5 to 47.5. The genetic gain improvement in EI was, however, best in the scenarios where the genetic correlation between IT and EI was ≥0.30 and the accuracy of direct genomic value was ≥0.40. The genetic gain in EI was 26 to 34% higher when indicator traits such as greenhouse gases in the breath of the cow and methane recorded in respiration chamber were used compared with a scenario where no indicator trait was included. It is possible to achieve increased genetic gain in EI by using a highly correlated indicator trait, but it requires that the established reference population for the indicator trait is large enough so that the accuracy of direct genomic values will be reasonably high.     

Peanut and hazelnut traces in cookies and chocolates: Relationship between analytical results and declaration of food allergens on product labels

Accidental exposure to hazelnut or peanut constitutes a real threat to the health of allergic consumers. Correct information regarding food product ingredients is of paramount importance for the consumer, thereby reducing exposure to food allergens. In this study, 569 cookies and chocolates on the European market were purchased. All products were analysed to determine peanut and hazelnut content, allowing a comparison of the analytical results with information provided on the product label. Compared to cookies, chocolates are more likely to contain undeclared allergens, while, in both food categories, hazelnut traces were detected at higher frequencies than peanut. The presence of a precautionary label was found to be related to a higher frequency of positive test results. The majority of chocolates carrying a precautionary label tested positive for hazelnut, whereas peanut traces were not be detected in 75% of the cookies carrying a precautionary label.     

Screening level risk assessment model for chemical fate and effects in the environment

A screening level risk assessment model is developed and described to assess and prioritize chemicals by estimating environmental fate and transport, bioaccumulation, and exposure to humans and wildlife for a unit emission rate. The most sensitive risk endpoint is identified and a critical emission rate is then calculated as a result of that endpoint being reached. Finally, this estimated critical emission rate is compared with the estimated actual emission rate as a risk assessment factor. This "back-tracking" process avoids the use of highly uncertain emission rate data as model input. The application of the model is demonstrated in detail for three diverse chemicals and in less detail for a group of 70 chemicals drawn from the Canadian Domestic Substances List. The simple Level II and the more complex Level III fate calculations are used to "bin" substances into categories of similar probable risk. The essential role of the model is to synthesize information on chemical and environmental properties within a consistent mass balance framework to yield an overall estimate of screening level risk with respect to the defined endpoint. The approach may be useful to identify and prioritize those chemicals of commerce that are of greatest potential concern and require more comprehensive modeling and monitoring evaluations in actual regional environments and food webs.     

Geo-referenced multimedia environmental fate model (G-CIEMS): model formulation and comparison to the generic model and monitoring approaches

A spatially resolved and geo-referenced dynamic multimedia environmental fate model, G-CIEMS (Grid-Catchment Integrated Environmental Modeling System) was developed on a geographical information system (GIS). The case study for Japan based on the air grid cells of 5 x 5 km resolution and catchments with an average area of 9.3 km2, which corresponds to about 40,000 air grid cells and 38,000 river segments/catchment polygons, were performed for dioxins, benzene, 1,3-butadiene, and di-(2-ethyhexyl)phthalate. The averaged concentration of the model and monitoring output were within a factor of 2-3 for all the media. Outputs from G-CIEMS and the generic model were essentially comparable when identical parameters were employed, whereas the G-CIEMS model gave explicit information of distribution of chemicals in the environment. Exposure-weighted averaged concentrations (EWAC) in air were calculated to estimate the exposure ofthe population, based on the results of generic, G-CIEMS, and monitoring approaches. The G-CIEMS approach showed significantly better agreement with the monitoring-derived EWAC than the generic model approach. Implication for the use of a geo-referenced modeling approach in the risk assessment scheme is discussed as a generic-spatial approach, which can be used to provide more accurate exposure estimation with distribution information, using generally available data sources for a wide range of chemicals.     

Empirical and modeling evidence of the long-range atmospheric transport of decabromodiphenyl ether

Understanding of the long-range atmospheric transport (LRT) behavior of decabromodiphenyl ether (BDE-209) is still limited. Most existing model-based approaches to assessing an organic chemical's potential for LRT have assumed invariant environmental conditions, even though many factors impacting on the atmospheric residence time are known to vary considerably over a variety of time scales. Model estimates of LRT also suffer from limited evaluation against observational evidence. Such evidence was sought from dated sediment cores taken from lakes along a latitudinal transect in North America. BDE-209 was generally detected only in recent sediment horizons, and sedimentation fluxes were found to decline exponentially with latitude. The empirical half-distance (EHD) for BDE-209 derived from surface flux data is approximately half that of the sigmaPCBs. A dynamic multimedia fate and transport model provides further insight into the temporal variability of processes that control LRT for BDE-209 and PCBs. The variability of precipitation, and in particular, the occurrence of time periods without precipitation coinciding with strong winds, influences the LRT potential of chemicals that combine a sufficiently long atmospheric half-life with very low volatility. Likewise, the forest filter effect may be important for a wider range of chemicals than believed previously, because models assuming constant precipitation fail to account for the impact of differences in dry deposition on days without rain. Chemicals that are both sorbed to particles and potentially persistent in the atmosphere, such as BDE-209, may have a larger potential for LRT than anticipated on the basis of earlier model evaluations. Still, the EHDs illustrate that the model seems to underestimate atmospheric loss processes of potential significance to BDE-209, illustrating the need to critically compare predictions of LRT against observations. Processes that need to be understood better in order to improve predictions of LRT for BDE-209 include particle dry deposition, precipitation scavenging, and photolysis in the sorbed state.     

造纸使用荧光增白剂的危害

荧光增白剂广泛用于纸张增白。由于它的化学结构和高负电性,使用荧光增白剂不仅会造成生活污染,而且会显著增加纸浆的负电性,干扰其它阳离子助剂,尤其是助留剂的正常使用。     

Estimating phospholipid membrane-water partition coefficients using comprehensive two-dimensional gas chromatography

Recent studies have shown that membrane-water partition coefficients of organic chemicals can be used to predict bioaccumulation and type I narcosis toxicity more accurately than the traditional K(OW)-based approach. In this paper, we demonstrate how comprehensive two-dimensional gas chromatography (GC × GC) can be used to estimate such membrane-water partition coefficients (K(PLW)s), focusing in particular on phosphatidyl choline based lipids. This method performed well for a set of 38 compounds, including polycyclic aromatic hydrocarbons, polychlorinated benzenes and biphenyls, and substituted benzenes including some phenols and anilines. The average difference between the estimated and the measured log K(PLW) values of 0.47 log units is smaller than in the case of a log K(OW) correlation approach but larger than seen using a polyparameter linear free energy relationship based approach. However, the GC × GC based method presents the advantage that it can be applied to mixtures of chemicals that are not completely identified, such as petroleum hydrocarbon mixtures. At the same time, our application of the GC × GC method suffered larger errors when applied to certain hydrogen bonding compounds due to the inability of the GC × GC capillary columns phases that we used to interact with analytes via hydrogen bond donation/electron acceptance.     

中温磷化工艺的关键和控制

对中温磷化进行了深入探讨，详述了中温磷化的优点和影响中温磷化工艺的６大因素，并指出关键因素和控制方法。分析了中温磷化可能产生的缺陷，提出了出现缺陷的处理方法和应采取的预防措施。     

Perinatal exposure to environmental estrogens and the development of obesity

Dietary substances and xenobiotic compounds with hormone-like activity can disrupt the programming of endocrine signaling pathways that are established during perinatal differentiation. The consequences of this disruption may not be apparent until later in life but increasing evidence implicates developmental exposure to environmental hormone-mimics with a growing list of adverse health effects including reproductive problems and increased cancer risks. Obesity has recently been proposed to be yet another adverse health consequence of exposure to endocrine disrupting substances during development. There is a renewed focus on identifying contributions of environmental factors to the development of obesity since it is reaching worldwide epidemic proportions, and this disease has the potential to overwhelm healthcare systems with associated illnesses such as diabetes and cardiovascular disease. Here, we review the literature that proposes an association of perinatal exposure to endocrine disrupting chemicals, in particular those with estrogenic activity, with the development of obesity later in life. We further describe an animal model of developmental exposure to diethylstilbestrol (DES) to study mechanisms involved in programming for obesity. Our experimental data support the idea that adipocytes and the mechanisms involved in weight homeostasis are novel targets of abnormal programming of environmental estrogens, some of which are found in our foods as naturally occurring substances or inadvertently as contaminants.