环境中的药物——LC-MS/MS分析地表水和地下水

成百上千的活性物质正被用于人药和兽药处方中.由于药物的广泛应用,它们的残留物可通过多种途径进入环境.虽然主要通过尿和粪便的排泄,但是药品生产中的排放也应被考虑.当抗生素用于水产业,就会产生更直接的影响.污水处理设备不能完全除去药物,因此药物会出现在地表和地下水样品中.近年来,人们对环境中药物的兴趣正在增加,需要建立一种快速、灵敏、有选择性的方法来分析水样.     

Priority assessment of toxic substances in life cycle assessment. Part I: calculation of toxicity potentials for 181 substances with the nested multi-media fate, exposure and effects model USES-LCA

Toxicity potentials are standard values used in life cycle assessment (LCA) to enable a comparison of toxic impacts between substances. In most cases, toxicity potentials are calculated with multi-media fate models. Until now, unrealistic system settings were used for these calculations. The present paper outlines an improved model to calculate toxicity potentials: the global nested multi-media fate, exposure and effects model USES-LCA. It is based on the Uniform System for the Evaluation of Substances 2.0 (USES 2.0). USES-LCA was used to calculate for 181 substances toxicity potentials for the six impact categories freshwater aquatic ecotoxicity, marine aquatic ecotoxicity, freshwater sediment ecotoxicity, marine sediment ecotoxicity, terrestrial ecotoxicity and human toxicity, after initial emission to the compartments air, freshwater, seawater, industrial soil and agricultural soil, respectively. Differences of several orders of magnitude were found between the new toxicity potentials and those calculated previously.     

Plant communities in relation to flooding and soil contamination in a lowland Rhine River floodplain

Using canonical correspondence analysis (CCA), relationships were investigated between plant species composition and flooding characteristics, heavy metal contamination and soil properties in a lowland floodplain of the Rhine River. Floodplain elevation and yearly average flooding duration turned out to be more important for explaining variation in plant species composition than soil heavy metal contamination. Nevertheless, plant species richness and diversity showed a significant decrease with the level of contamination. As single heavy metal concentrations seemed mostly too low for causing phytotoxic effects in plants, this trend is possibly explained by additive effects of multiple contaminants or by the concomitant influences of contamination and non-chemical stressors like flooding. These results suggest that impacts of soil contamination on plants in floodplains could be larger than expected from mere soil concentrations. In general, these findings emphasize the relevance of analyzing effects of toxic substances in concert with the effects of other relevant stressors.     

Priority assessment of toxic substances in life cycle assessment. Part II: assessing parameter uncertainty and human variability in the calculation of toxicity potentials

Toxicity potentials are standard values used in life cycle assessment (LCA) to enable a comparison of toxic impacts between substances. This paper presents the results of an uncertainty assessment of toxicity potentials that were calculated with the global nested multi-media fate, exposure and effects model USES-LCA. The variance in toxicity potentials resulting from input parameter uncertainties and human variability was quantified by means of Monte Carlo analysis with Latin Hypercube sampling (LHS). For Atrazine, 2,3,7,8-TCDD and Lead, variation, expressed by the ratio of the 97.5%-ile and the 2.5%-ile, ranges from about 1.5 to 6 orders of magnitude. The major part of this variation originates from a limited set of substance-specific input parameters, i.e. parameters that describe transport mechanisms, substance degradation, indirect exposure routes and no-effect concentrations. Considerable correlations were found between the toxicity potentials of one substance, in particular within one impact category. The uncertainties and correlations reported in the present study may have a significant impact on the outcome of LCA case studies.     

Assessing the Relative Importance of Spatial Variability in Emissions Versus Landscape Properties in Fate Models for Environmental Exposure Assessment of Chemicals

Multimedia mass balance models differ in their treatment of spatial resolution from single boxes representing an entire region to multiple interconnected boxes with varying landscape properties and emission intensities. Here, model experiments were conducted to determine the relative importance of these two main factors that cause spatial variation in environmental chemical concentrations: spatial patterns in emission intensities and spatial differences in environmental conditions. In the model, experiments emissions were always to the air compartment. It was concluded that variation in emissions is in most cases the dominant source of variation in environmental concentrations. It was found, however, that variability in environmental conditions can strongly influence predicted concentrations in some cases, if the receptor compartments of interest are soil or water—for water concentrations particularly if a chemical has a high octanol–air partition coefficient (K _oa). This information will help to determine the required level of spatial detail that suffices for a specific regulatory purpose.     

Confronting environmental pressure,environmental quality and human health impact indicators of priority air emissions

This paper evaluates the ranking of 21 priority air pollutants with three indicator schemes: environmental pressure indicator (EPI), environmental quality indicator (EQI), and human health effect indicator (HEI). The EPI and EQI compare the emissions and concentrations with the target emissions and target concentrations, respectively. The HEI comprehends the steps from cause (i.e. national emissions) to effect (i.e. human health effects), and is the total human health burden, expressed in Disability Adjusted Life Years per year of exposure (DALYs year^?1). We estimated a health burden in the Netherlands of 41 × 10³ DALYs year^?1 caused by Dutch air emissions of PM10 and its precursors in the year 2003. The burden due to 17 carcinogenic substances emitted to air, was much lower (140 DALYs year^?1). In contrast, when the same substances were evaluated regarding environmental pressure and environmental quality, carbon tetrachloride (pressure) and benzo[a]pyrene (quality) were of highest importance, whereas the importance of PM10 was substantially lower. This result is remarkable, because for the majority of substances evaluated, the target concentrations and target emissions are based on preventing human health damage. The differences in relevance are explained by the different weighting of interests in the indicators. The HEI is based on concentration–response relations, whereas the EPI and EQI also depend on other, policy-based, principles and on technical feasibility. Therefore, to effectively prioritize emission reduction measures in policy-making, substances should not only be evaluated as to whether emission targets and environmental quality targets are reached, but they should be evaluated regarding their human health impact as well. In this context, the HEI is a suitable indicator to evaluate the human health impact.     

Cumulative risk assessment of chemical exposures in urban environments

We performed a cumulative risk assessment for people living in a hypothetical urban environment, called Urbania. The main aims of the study were to demonstrate how a cumulative risk assessment for a middle-sized European city can be performed and to identify the bottlenecks in terms of data availability and knowledge gaps. The assessment focused on five air pollutants (i.e., PM??, benzene, toluene, nonane and naphthalene) and six food pesticides (i.e., acetamiprid, carbendazim, chlorpyrifos, diazinon, imidacloprid and permethrin). Exposure predictions showed that PM??, benzene and naphthalene exposure frequently exceeded the standards, and that the indoor environment contributed more than the outdoor environment. Effect predictions showed that mixture and interaction effects were generally limited. However, model calculations indicated potential synergistic effects between naphthalene and benzene and between chlorpyrifos, diazinon and toluene. PM?? dominated the health impact expressed in Disability Adjusted Life Years (DALYs). We conclude that measures to reduce the health impact of environmental pollution should focus on the improvement of indoor air quality and the reduction of PM?? emissions. Cumulative risk assessment can be improved by (1) the development of person-oriented exposure models that can simulate the cumulative exposure history of individuals, (2) a better mechanistic understanding of the effects of cumulative stressors, and (3) the development of instruments to prioritize stressors for inclusion in cumulative risk assessments.     

Truncated Lévy flights and agenda-based mobility are useful for the assessment of personal human exposure

Receptor-oriented approaches can assess the individual-specific exposure to air pollution. In such an individual-based model we analyse the impact of human mobility to the personal exposure that is perceived by individuals simulated in an exemplified urban area. The mobility models comprise random walk (reference point mobility, RPM), truncated Lévy flights (TLF), and agenda-based walk (RPMA). We describe and review the general concepts and provide an inter-comparison of these concepts. Stationary and ergodic behaviour are explained and applied as well as performance criteria for a comparative evaluation of the investigated algorithms. We find that none of the studied algorithm results in purely random trajectories. TLF and RPMA prove to be suitable for human mobility modelling, because they provide conditions for very individual-specific trajectories and exposure. Suggesting these models we demonstrate the plausibility of their results for exposure to air-borne benzene and the combined exposure to benzene and nonane.     

Spatial variance in multimedia mass balance models: comparison of LOTOS-EUROS and SimpleBox for PCB-153

The aim of this study was to determine whether nested generic box models can be used to predict spatial variance. An inter-comparison study was performed for the nested box model SimpleBox, and the spatially resolved model LOTOS-EUROS, using PCB-153 emissions in Europe as an example. We compared the two models concerning (1) average environmental concentrations, (2) spatial concentration variances, (3) spatial concentration patterns (maps), and (4) agreement with measured concentrations for the air and soil compartments. In SimpleBox, the spatial concentration variances and patterns were calculated subsequently for each separate grid cell surrounded by a regional and a continental shell with homogeneous, averaged circumstances. Average European PCB-153 concentrations calculated by LOTOS-EUROS and SimpleBox for the period 1981-2000 agree well for the air and soil compartments. Moreover, the predicted concentrations of both models are in line with the measured PCB-153 concentrations in Europe during that period. For PCB-153, the prediction of spatial concentration variances with the nested multimedia fate model SimpleBox performs adequately in most cases, except for the lower concentration boundary in the air compartment. It is concluded that SimpleBox can be used to predict the spatial maximum and average concentrations of PCB-153 in the air and soil compartments. The proposed method has to be tested systematically for different types of compounds, emission scenarios, environmental compartments and spatial scales in order to allow conclusions about the general applicability of the method.     

Validation of predicted exponential concentration profiles of chemicals in soils

Multimedia mass balance models assume well-mixed homogeneous compartments. Particularly for soils, this does not correspond to reality, which results in potentially large uncertainties in estimates of transport fluxes from soils. A theoretically expected exponential decrease model of chemical concentrations with depth has been proposed, but hardly tested against empirical data. In this paper, we explored the correspondence between theoretically predicted soil concentration profiles and 84 field measured profiles. In most cases, chemical concentrations in soils appear to decline exponentially with depth, and values for the chemical specific soil penetration depth (d(p)) are predicted within one order of magnitude. Over all, the reliability of multimedia models will improve when they account for depth-dependent soil concentrations, so we recommend to take into account the described theoretical exponential decrease model of chemical concentrations with depth in chemical fate studies. In this model the d(p)-values should estimated be either based on local conditions or on a fixed d(p)-value, which we recommend to be 10cm for chemicals with a log K(ow)>3.