Purpose
The aim of the study is to calculate regionalized characterization factors for the atmospheric emissions of metals transferred to soil for zinc, copper, and nickel taking into account the atmospheric fate and speciation.Methods
In order to calculate characterization factors for all possible atmospheric emission locations around the world, the link between atmospheric deposition with regionalized soil fate factors and bioavailability factors accounting for the metal’s speciation was established. The methodology to develop the regionalized fate factors and characterization factors is threefold. First, the emitted metal fraction that is deposited on soils is calculated from atmospheric source-receptor matrices providing for each emission location the fraction of an emission that is deposited on each worldwide receiving cell (2°?×?2.5° resolution). Second, the fraction of metal deposited in different soil types is determined by overlapping the deposition map with a soil map, based on the 4513 different soil types from the Harmonized World Soil Database. Third, bioavailability factors are calculated for each soil type, which allows determining the bioavailable fraction of the deposited metal depending on the soil properties. Combining these steps with the effect factors results in a series of terrestrial ecotoxicological characterization factors. These characterization factors are then applied in an illustrative example and compared to results obtained with generic characterization factors. The case study focuses on the electricity production process in Québec, whose ecosystem impacts are currently dominated by metal ecotoxicity impacts. The uncertainty due to the spatial variability of the impact is quantified.Results and discussion
Our results show that regionalized characterization factors are over three orders of magnitude lower than generic characterization factors. They are presented on maps and their spatial variability was evaluated at different regional scales (region, country, world). The use of regionalized characterization factors with their spatial variability at different geographic resolution scales in the case study gives a result more or less precise depending on the level of resolution of the characterization factor applied (country or global-default). The impact scores of the three metals in the case study are three orders of magnitude lower when compared to the scores obtained with generic characterization factors.Conclusions
The development of those regionalized characterization factors improves the terrestrial ecotoxicity assessment in life cycle impact assessment by taking into account the atmospheric fate and the speciation of the metal for new 3 metals for the different soil types in the world and by documenting their spatial variability.Purpose
Aluminum (Al) is an abundant, non-essential element with complex geochemistry and aquatic toxicity. Considering its complex environmental behavior is critical for providing a reasonable estimate of its potential freshwater aquatic ecotoxicity in the context of Life Cycle Impact Assessment (LCIA).Methods
Al characterization factors (CFs) are calculated using the following: (1) USEtox? model version 2.1 for environmental fate, (2) MINEQL+ to estimate the distribution of Al between the solid phase precipitate and total dissolved Al, (3) WHAM 7 for Al speciation within the total dissolved phase, and (4) Biotic Ligand Model (BLM) and Free Ion Activity Model (FIAM) for ecotoxicity estimation for seven freshwater archetypes and default landscape properties for the European continent. The sensitivity of the CFs to aquatic chemistry parameters is calculated. New CFs are compared with Dong et al. (Chemosphere 112:26–33, 2014) and default CF calculated by USEtox 2.1.Results and discussion
Al CFs vary over 5 orders of magnitude between the seven archetypes, with an arithmetic average CFave of 0.04 eq 1,4-DCB (recommended for use), geometric mean CFgeo of 0.0014 eq 1,4-DCB, and weighted average CFwt of 0.026 eq 1,4-DCB. These values are lower (less toxic) than those for Cu, Ni, Zn, and Pb (with one exception). The effect factor (EF) contributed most to this variability followed by the bioavailability factor (BF), varying over 8 and 4 orders of magnitude, respectively. These revised CFs are 2–6 orders of magnitude lower than those presented by Dong et al. (Chemosphere 112:26–33, 2014) mainly because of consideration of Al precipitation.Conclusions
Freshwater archetype-specific Al CFs for freshwater ecotoxicity that address the effect of Al speciation on bioavailability (BF) and ecotoxicity (EF) have been calculated, and a CF of 0.04 eq 1,4-DCB is recommended for use in generic LCA. For site-specific LCA, the choice of water chemistry and, in particular, pH, and consideration of metal precipitation could significantly influence results.Practical implications
Incorporating estimates of metal speciation and its effect on aquatic toxicity is essential when conducting LCIA. Along with metal speciation estimates, the values derived from the definition of water chemistry parameters must also be included into LCIA. For site-generic assessments, we recommend using the arithmetic average of metal CFs. We also recommend using FIAM as a suitable alternative to BLM to estimate EF if the latter is not available. Consideration of metal speciation is essential for providing more realistic estimates of Al freshwater ecotoxicity in the context of LCIA.Background
Serum albumin is the major protein component of blood plasma and is responsible for the circulatory transport of a range of small molecules that include fatty acids, hormones, metal ions and drugs. Studies examining the ligand-binding properties of albumin make up a large proportion of the literature. However, many of these studies do not address the fact that albumin carries multiple ligands (including metal ions) simultaneously in vivo. Thus the binding of a particular ligand may influence both the affinity and dynamics of albumin interactions with another.Scope of review
Here we review the Zn2 + and fatty acid transport properties of albumin and highlight an important interplay that exists between them. Also the impact of this dynamic interaction upon the distribution of plasma Zn2 +, its effect upon cellular Zn2 + uptake and its importance in the diagnosis of myocardial ischemia are considered.Major conclusions
We previously identified the major binding site for Zn2 + on albumin. Furthermore, we revealed that Zn2 +-binding at this site and fatty acid-binding at the FA2 site are interdependent. This suggests that the binding of fatty acids to albumin may serve as an allosteric switch to modulate Zn2 +-binding to albumin in blood plasma.General significance
Fatty acid levels in the blood are dynamic and chronic elevation of plasma fatty acid levels is associated with some metabolic disorders such as cardiovascular disease and diabetes. Since the binding of Zn2 + to albumin is important for the control of circulatory/cellular Zn2 + dynamics, this relationship is likely to have important physiological and pathological implications. This article is part of a Special Issue entitled Serum Albumin. 相似文献Purpose
Graphene oxide (GO) nanomaterial has found wide potential industrial applications, but its life cycle environmental impact is not fully understood mainly because of lack of characterization factors (CFs) for the life cycle impact assessment. In this paper, we report the derivation of CF for freshwater ecotoxicity of GO based on the USEtox method.Methods
The CF is derived based on the toxic effect factor, fate factor, and exposure factor of GO in the aquatic environment. The toxic effect factor is extracted from mechanistic toxicity studies available in the literature. The fate factor is derived with the colloidal method, and the exposure factor is determined through Langmuir adsorption isotherm for interactions between GO and dissolve organic carbon. Additionally, both fate factor and exposure factor are re-calculated through the default mass-balanced model in USEtox. The apparent octanol-water partition coefficient (K ow) required in the mass balanced model is determined via experiment. Other parameters are calculated according to the apparent K ow.Results and discussion
The study derives a CF of 777.5 potentially affected species (PAF) day m3 kg?1 for GO with a fate factor of 27.2 days and an exposure factor of 0.93. Sensitivity analysis suggests that variability from the effect factor is the dominant source leading changes in CF. The uncertainty of CF value can vary between ~1 and 103 PAF day m3 kg?1. Comparison between the colloidal and the mass-balanced models indicates that heteroaggregation may be underestimated by using the apparent partition coefficient, and thus, a much higher estimate of fate factor is obtained from the mass-balanced model. Additionally, empirical formulae in the USEtox to correlate other coefficients with K ow are not proper to calculate bioaccumulation and adsorption with dissolved organic carbon since a virtually a unit exposure factor is obtained.Conclusion
The derived CFs can be readily incorporated into future toxicity assessment on GO. The fate factor is calculated in the colloidal model while adsorption of dissolved organic carbon onto GO surface should be derived from the Langmuir isotherm. Compared to the colloidal-based method, the conventional mass-balanced method may not be well applicable to GO due to the significant uncertainties in fate and exposure factors from applying the apparent partition coefficients. As three orders of magnitude variations in CF are caused by effect factor due to limited toxicity tests available for GO, more toxicological studies of GO on various species are needed in the future.Purpose
Today’s chemical society use and emit an enormous number of different, potentially ecotoxic, chemicals to the environment. The vast majority of substances do not have characterisation factors describing their ecotoxicity potential. A first stage, high throughput, screening tool is needed for prioritisation of which substances need further measures.Methods
USEtox characterisation factors were calculated in this work based on data generated by quantitative structure-activity relationship (QSAR) models to expand substance coverage where characterisation factors were missing. Existing QSAR models for physico-chemical data and ecotoxicity were used, and to further fill data gaps, an algae QSAR model was developed. The existing USEtox characterisation factors were used as reference to evaluate the impact from the use of QSARs to generate input data to USEtox, with focus on ecotoxicity data. An inventory of chemicals that make up the Swedish societal stock of plastic additives, and their associated predicted emissions, was used as a case study to rank chemicals according to their ecotoxicity potential.Results and discussion
For the 210 chemicals in the inventory, only 41 had characterisation factors in the USEtox database. With the use of QSAR generated substance data, an additional 89 characterisation factors could be calculated, substantially improving substance coverage in the ranking. The choice of QSAR model was shown to be important for the reliability of the results, but also with the best correlated model results, the discrepancies between characterisation factors based on estimated data and experimental data were very large.Conclusions
The use of QSAR estimated data as basis for calculation of characterisation factors, and the further use of those factors for ranking based on ecotoxicity potential, was assessed as a feasible way to gather substance data for large datasets. However, further research and development of the guidance on how to make use of estimated data is needed to achieve improvement of the accuracy of the results.Purpose
Temporal variability is a major source of uncertainty in current life cycle assessment (LCA) practice. In this paper, the recently developed dynamic LCA approach is adapted to assess freshwater ecotoxicity impacts of metals. The objective is to provide relevant information regarding the distribution and magnitude of metal impacts over time and to show whether the dynamic approach significantly influences the conclusions of an LCA. An LCA of zinc fertilization in agriculture was therefore carried out.Methods
Dynamic LCA is based on the temporal disaggregation of the inventory, which is then assessed using time-horizon-dependent characterization factors. The USEtox multimedia fate model is used to develop time-horizon-dependent characterization factors for the freshwater ecotoxicity impact of 18 metals. Mass balance equations are solved dynamically to obtain fate factors as a function of time, providing both instantaneous (impact at time t following a pulse emission) and cumulative (total time-integrated impact following a pulse emission) characterization factors (CFs).Results and discussion
Time-horizon-dependent CFs for freshwater ecotoxicity depend on the emission compartment and the metal itself. The two variables clearly influence metal fate aspects such as the maximum mass loading reaching freshwater and the persistence time of metals into this compartment. The time needed to reach the total impact for each metal may exceed thousands of years, so the time horizon used in the analysis constitutes a determining factor. The case study reveals that the results of a classical LCA are always higher than those obtained from a dynamic LCA, especially for short time horizons. For instance, at the end of a 100-year fertilization treatment, only 25 % of the impacts obtained through traditional LCA occurred.Conclusions
Results show that dynamic LCA enables assessing freshwater ecotoxicity impacts of metals over time, allowing decision makers to test the sensitivity of their results to the choice of a time horizon. For the particular case study of zinc fertilization over a period of 20 years, the use of time-horizon-dependent CFs is more important in determining the dynamics of impacts than the timing of emission. 相似文献2. Diversity indices did not group samples by site whereas the divisive polythetic classification analysis TWINSPAN showed that the two sites possessed clearly different communities. In the classification, site was of primary importance, with time of year, and trap position within site of secondary and tertiary importance respectively.
3. Samples were compared at different taxonomic levels and using different subsets of the database. Determination of the main families, morphotyped to species or species complex, was found to be sufficient to classify most samples to the appropriate community group.
4. The divisive classification procedure applied to four consecutive weekly Coleoptera samples over early summer, is suggested as a means of describing and identifying terrestrial arthropod communities characteristic of site and year of collection. This approach provides a potentially sensitive tool for monitoring terrestrial ecosystems. 相似文献
In Life Cycle Impact Assessment, atmospheric fate factors, soil exposure factors, and effect factors are combined to characterize potential impacts of acidifying substances in terrestrial environments. Due to the low availability of global data sets, effect factors (EFs) have been reported as the major contributors to statistical uncertainties of characterization factors and they are the focus of this study. We aim to develop spatially differentiated EFs taking Brazil as case and explore new methodological ways to derive them.
MethodsEFs are calculated based on a comprehensive database reporting observations of approximately 30,000 plant species at biome and ecoregion levels. Species richness distributions as function of soil pH are developed and translated into potentially not occurring fraction (PNOF) of species, which can be equated to the more commonly used potentially disappeared fraction of species, to assess effects of changes in soil hydrogen ion concentration on terrestrial plant species. Potentially extinct fraction (PXF) of species is proposed as a complementary metric for LCIA models based on distributions of range-restricted species (species only occurring in one ecoregion of Brazil). Different approaches for determining EFs from the species richness distributions are evaluated. Area-weighted EFs are explored to determine potential effects when considering both acid and alkaline sides of species richness curves, thus integrating potentially positive effects of acidification on biodiversity.
Results and discussionSpatially differentiated EFs are provided for 6 biomes and 45 ecoregions composing Brazil. Comparisons with previous EFs demonstrate that data availability might significantly influence regression analyses, and the use of more representative data can lead to more consistent EFs. Moreover, consideration of the entire species richness curves yields positive and negative EFs. Adding acidifying substances onto specific soils in Brazilian ecoregions may therefore be associated with increased species richness if the pH approaches the optimum pH from the alkaline side of the curve. The meaningfulness of species richness as indicator of acidification stress is discussed based on this finding, as is the inclusion of the metric PXF, highlighting species whose loss could cause irreversible damages to the environment.
ConclusionsWe recommend the calculation of area-weighted EFs to be integrated into characterization models for terrestrial acidification, and we therefore advocate that similar work be done for other regions in the world than Brazil to enhance the consistency of the EFs and reduce their uncertainties. We additionally recommend that LCIA method developers further explore the application of PXF for other impact categories than acidification.
相似文献