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The steady rise in atmospheric long-lived greenhouse gas concentrations is the main driver of contemporary climate change. The Mauna Loa CO2time series (1,2), started by C. D. Keeling in 1958 and maintained today by the Scripps Institution of Oceanography and the Earth System Research Laboratory (ESRL) of NOAA, is iconic evidence of the effect of human-caused fossil fuel and land-use change emissions on the atmospheric increase of CO2. The continuity of such records depends critically on having stable funding, which is challenging to maintain in the context of 3- to 4-year research grant funding cycles (3), and is currently threatened by the financial crisis. The ESRL Global Monitoring Division maintains a network of about 100 surface and aircraft sites worldwide at which whole air samples are collected approximately every week for analysis of CO2, CH4, CO, halocarbons, and many other chemical species (4). This is complemented by high-frequency measurements at the Mauna Loa, Barrow, American Samoa, and South Pole observatories, and about 10 North American tall towers. The success of the NOAA program has inspired similar efforts in Europe (5), China (6), India (7), and Brazil (8), with the United Nations World Meteorological Organization providing guidance and precision requirements through the Global Atmosphere Watch program (9), but no funding. The data collected by NOAA and its worldwide partners have been used not only to demonstrate the unassailable rise of atmospheric greenhouse gas concentrations, but also to infer the magnitudes, locations, and times of surface-atmosphere exchange of those gases based on small concentration gradients between sites (10). Important findings from analysis of these records include the detection of a significant terrestrial carbon sink at northern mid-latitudes (11) and subsequent research aimed at identifying the mechanisms by which that sink must operate. Long-term, high-quality, atmospheric measurements are crucial for quanti

During each of the late Pleistocene glacial–interglacial transitions, atmospheric carbon dioxide concentrations rose by almost 100 ppm. The sources of this carbon are unclear, and efforts to identify them are hampered by uncertainties in the magnitude of carbon reservoirs and fluxes under glacial conditions. Here we use oxygen isotope measurements from air trapped in ice cores and ocean carbon-cycle modelling to estimate terrestrial and oceanic gross primary productivity during the Last Glacial Maximum. We find that the rate of gross terrestrial primary production during the Last Glacial Maximum was about 40±10 Pg C yr−1, half that of the pre-industrial Holocene. Despite the low levels of photosynthesis, we estimate that the late glacial terrestrial biosphere contained only 330 Pg less carbon than pre-industrial levels. We infer that the area covered by carbon-rich but unproductive biomes such as tundra and cold steppes was significantly larger during the Last Glacial Maximum, consistent with palaeoecological data. Our data also indicate the presence of an inert carbon pool of 2,300 Pg C, about 700 Pg larger than the inert carbon locked in permafrost today. We suggest that the disappearance of this carbon pool at the end of the Last Glacial Maximum may have contributed to the deglacial rise in atmospheric carbon dioxide concentrations.

Existing environmental risk assessment procedures are limited in their ability to evaluate the combined effects of chemical mixtures. We investigated the implications of this by analyzing the combined effects of a multicomponent mixture of five estrogenic chemicals using vitellogenin induction in male fathead minnows as an end point. The mixture consisted of estradiol, ethynylestradiol, nonylphenol, octylphenol, and bisphenol A. We determined concentration-response curves for each of the chemicals individually. The chemicals were then combined at equipotent concentrations and the mixture tested using fixed-ratio design. The effects of the mixture were compared with those predicted by the model of concentration addition using biomathematical methods, which revealed that there was no deviation between the observed and predicted effects of the mixture. These findings demonstrate that estrogenic chemicals have the capacity to act together in an additive manner and that their combined effects can be accurately predicted by concentration addition. We also explored the potential for mixture effects at low concentrations by exposing the fish to each chemical at one-fifth of its median effective concentration (EC

Photosynthesis-inhibiting phenylurea derivatives, such as diuron, are widely used as herbicides. Diuron concentrations clearly exceeding the predicted-no-effect concentration have been regularly measured in European freshwater systems. The frequently observed exposure to mixtures of phenylureas additionally increases the hazard to aquatic primary producers. Fluctuating numbers and concentrations of individual toxicants make experimental testing of every potential mixture unfeasible. Thus, predictive approaches to the mixture hazard assessment are needed. For this purpose, two concepts are at hand, both of which make use of known toxicities of the individual components but are based on opposite mechanistic suppositions: Concentration addition is based on the idea of similar mechanisms of action, whereas independent action assumes dissimilarly acting mixture components. On the basis of pharmacological reasoning, it was therefore anticipated that the joint algal toxicity of phenylurea mixtures would be predictable by concentration addition. Indeed, we could demonstrate a high predictive power of concentration addition for these combinations. Surprisingly, however, the opposite concept of independent action proved to be equally valid, because both concepts predicted virtually identical mixture toxicities. This exceptional case has previously been derived from theoretical considerations. Now, the tested phenylurea mixtures serve as an example for the practical relevance of this situation for multicomponent mixtures.

The need to develop water quality objectives not only for single substances but also for mixtures of chemicals seems evident. For that purpose, the conceptual basis could be the use of the two existing biometric models: concentration addition (CA) and independent action (IA), which is also called response addition. Both may allow calculation of the toxicity of mixtures of chemicals with similar modes of action (CA) or dissimilar modes of action (IA), respectively. The joint research project Prediction and Assessment of the Aquatic Toxicity of Mixtures of Chemicals (PREDICT) within the framework of the IVth Environment and Climate Programme of the European Commission, provided the opportunity to address (a) chemometric and QSAR criteria to classify substances as supposedly similarly or dissimilarly acting; (b) the predictive values of both models for the toxicity of mixtures at low, statistically nonsignificant effect concentrations of the individual components; and (c) the predictability of mixture toxicity at higher levels of biological complexity. In this article, the general outline, methodological approach, and some preliminary findings of PREDICT are presented. A procedure for classifying chemicals in relation to their structural and toxicological similarities has been developed. The predictive capabilities of CA and IA models have been demonstrated for single species and, to some extent, for multispecies testing. The role of very low effect concentrations in multiple mixtures has been evaluated. Problems and perspectives concerning the development of water quality objectives for mixtures are discussed.

Freshwater and marine ecosystems are exposed to various multi-component mixtures of pollutants. Nevertheless, most ecotoxicological research and chemicals regulation focus on hazard and exposure assessment of individual substances only, the problem of chemical mixtures in the environment is ignored to a large extent. In contrast, the assessment of combination effects has a long tradition in pharmacology, where mixtures of chemicals are specifically designed to develop new products, e.g. human and veterinary drugs or agricultural and non-agricultural pesticides. In this area, two concepts are frequently used and are thought to describe fundamental relationships between single substance and mixture effects: Independent Action (Response Addition) and Concentration Addition. The question, to what extent these concepts may also be applied in an ecotoxicological and regulatory context may be considered a research topic of major importance, as the concepts would allow to make use of already existing single substance toxicity data for the predictive assessment of mixture toxicities. Two critical knowledge gaps are identified: (a) There is a lack of environmental realism, as a huge part of our current knowledge about the applicability of the concepts is restricted to artificial situations with respect to mixture composition or biological effect assessment. (b) The knowledge on what exactly is needed for using the concepts as tools for the predictive mixture toxicity assessment is insufficient. Both gaps seriously hamper the necessary, scientifically sound consideration of mixture toxicities in a regulatory context.In this paper, the two concepts will be briefly introduced, the necessity of considering the toxicities of chemical mixtures in the environment will be demonstrated and the applicability of Independent Action and Concentration Addition as tools for the prediction and assessment of mixture toxicities will be discussed. An overview of the specific aims and approaches

For a predictive assessment of the aquatic toxicity of chemical mixtures, two competing concepts are available: concentration addition and independent action. Concentration addition is generally regarded as a reasonable expectation for the joint toxicity of similarly acting substances. In the opposite case of dissimilarly acting toxicants the choice of the most appropriate concept is a controversial issue. In tests with freshwater algae we therefore studied the extreme situation of multiple exposure to chemicals with strictly different specific mechanisms of action. Concentration response analyses were performed for 16 different biocides, and for mixtures containing all 16 substances in two different concentration ratios. Observed mixture toxicity was compared with predictions, calculated from the concentration response functions of individual toxicants by alternatively applying both concepts. The assumption of independent action yielded accurate predictions, irrespective of the mixture ratio or the effect level under consideration. Moreover, results even demonstrate that dissimilarly acting chemicals can show significant joint effects, predictable by independent action, when combined in concentrations below individual NOEC values, statistically estimated to elicit insignificant individual effects of only 1%. The alternative hypothesis of concentration addition resulted in overestimation of mixture toxicity, but differences between observed and predicted effect concentrations did not exceed a factor of 3.2. This finding complies with previous studies, which indicated near concentration-additive action of mixtures of dissimilarly acting substances. Nevertheless, with the scientific objective to predict multi-component mixture toxicity with the highest possible accuracy, concentration addition obviously is no universal solution. Independent action proves to be superior where components are well known to interact specifically with different molecular target sites, and

The need to develop water quality objectives not only for single substances but also for mixtures of chemicals seems evident. For that purpose, the conceptual basis could be the use of the two existing biometric models: concentration addition (CA) and independent action (IA), which is also called response addition. Both may allow calculation of the toxicity of mixtures of chemicals with similar modes of action (CA) or dissimilar modes of action (IA), respectively. The joint research project Prediction and Assessment of the Aquatic Toxicity of Mixtures of Chemicals (PREDICT) within the framework of the lVth Environment and Climate Programme of the European Commission, provided the opportunity to address (a) chemometric and QSAR criteria to classify substances as supposedly similarly or dissimilarly acting; (b) the predictive values of both models for the toxicity of mixtures at low, statistically nonsignificant effect concentrations of the individual components; and (c) the predictability of mixture toxicity at higher levels of biological complexity. In this article, the general outline, methodological approach, and some preliminary findings of PREDICT are presented. A procedure for classifying chemicals in relation to their structural and toxicological similarities has been developed. The predictive capabilities of CA and IA models have been demonstrated for single species and, to some extent, for multispecies testing. The role of very low effect concentrations in multiple mixtures has been evaluated. Problems and perspectives concerning the development of water quality objectives for mixtures are discussed. (C) 2002 Elsevier Science (USA). All rights reserved.

For a predictive assessment of the aquatic toxicity of chemical mixtures, two competing concepts are available: concentration addition and independent action. Concentration addition is generally regarded as a reasonable expectation for the joint toxicity of similarly acting substances. In the opposite case of dissimilarly acting toxicants the choice of the most appropriate concept is a controversial issue. In tests with freshwater algae we therefore studied the extreme situation of multiple exposure to chemicals with strictly different specific mechanisms of action. Concentration response analyses were performed for 16 different biocides, and for mixtures containing all 16 substances in two different concentration ratios. Observed mixture toxicity was compared with predictions, calculated from the concentration response functions of individual toxicants by alternatively applying both concepts. The assumption of independent action yielded accurate predictions, irrespective of the mixture ratio or the effect level under consideration. Moreover, results even demonstrate that dissimilarly acting chemicals can show significant joint effects, predictable by independent action, when combined in concentrations below individual NOEC values, statistically estimated to elicit insignificant individual effects of only 1%. The alternative hypothesis of concentration addition resulted in overestimation of mixture toxicity, but differences between observed and predicted effect concentrations did not exceed a factor of 3.2. This finding complies with previous studies, which indicated near concentration-additive action of mixtures of dissimilarly acting substances. Nevertheless, with the scientific objective to predict multi-component mixture toxicity with the highest possible accuracy, concentration addition obviously is no universal solution. Independent action proves to be superior where components are well known to interact specifically with different molecular target sites, and

Environmental exposure situations are often characterised by a multitude of heterogeneous chemicals with ambiguous or unknown modes of action present at low concentrations. While multiple exposure is widely acknowledged, arguments are raised that adverse combined effects might not be evoked by mixtures of substances with dissimilar modes of action and being present at only low concentrations. In this study the combined effect of a multiple mixture composed of structurally dissimilar priority pollutants with mostly unknown modes of action has been investigated using an algal biotest. The concentrations of the components in the mixture equalled statistically estimated, individual no observed effect concentrations (NOECs). The observed mixture toxicity was not only clearly higher than expected for any single substance alone, but also well predictable using the concept of independent action.

Risk assessments of toxic chemicals currently rely heavily on the use of no-observed-effect concentrations (NOECs). Due to several crucial flaws in this concept, however, discussion of replacing NOECs with statistically estimated low-effect concentrations continues. This paper describes a general best-fit method for the estimation of effects and effect concentrations by the use of a pool of 10 different sigmoidal regression functions for continuous toxicity data. Due to heterogeneous variabilities in replicated data (i.e., heteroscedasticity), the concept of generalized least squares is used for the estimation of the model parameters, whereas a nonparametric variance model based on smoothing spline functions is used to describe the heteroscedasticity. To protect the estimates against outliers, the generalized least-squares method is improved by winsorization. On the basis of statistical selection criteria, the best-fit model is chosen individually for each set of data. Furthermore, the bootstrap methodology is applied for constructing confidence intervals for the estimated effect concentrations. The best-fit method for the estimation of low-effect concentrations is validated by a simulation study, and its applicability is demonstrated with toxicity data for 64 chemicals tested in an algal and a bacterial bioassay. In comparison with common methods of concentration-response analysis, a clear improvement is achieved.

Herbicidal s-triazines are widespread contaminants of surface waters. They are highly toxic to algae and other primary producers in aquatic systems. This results from their specific interference with photosynthetic electron transport. Risk assessment for aquatic biota has to consider situations of simultaneous exposure to various of these toxicants. In tests with freshwater algae we predicted and determined the toxicity of multiple mixtures of 18 different s-triazines. The toxicity parameter was the inhibition of reproduction of Scenedesmus vacuolatus. Concentration–response analyses were performed for single toxicants and for mixtures containing all 18 s-triazines in two different concentration ratios. Experiments were designed to allow a valid statistical description of the entire concentration–response relationships, including the low concentration range down to EC1. Observed effects and effect concentrations of mixtures were compared to predictions of mixture toxicity. Predictions were calculated from the concentration–response functions of individual s-triazines by applying the concepts of concentration addition and independent action (response addition) alternatively. Predictions based on independent action tend to underestimate the overall toxicity of s-triazine mixtures. In contrast, the concept of concentration addition provides highly accurate predictions of s-triazine mixture toxicity, irrespective of the effect level under consideration and the concentration ratio of the mixture components. This also holds true when the mixture components are present in concentrations below their individual NOEC values. Concentrations statistically estimated to elicit non-significant effects of only 1% still contribute to the overall toxicity. When present in a multi-component mixture they can co-operate to give a severe joint effect. Applicability of the findings obtained with s-triazines to mixtures of other contaminants in aquatic systems and consequences for risk ass

Herbicidal s-triazines are widespread contaminants of surface waters. They are highly toxic to algae and other primary producers in aquatic systems. This results from their specific interference with photosynthetic electron transport. Risk assessment for aquatic biota has to consider situations of simultaneous exposure to various of these toxicants. In tests with freshwater algae we predicted and determined the toxicity of multiple mixtures of 18 different s-triazines. The toxicity parameter was the inhibition of reproduction of Scenedesmus vacuolatus. Concentration - response analyses were performed for single toxicants and for mixtures containing all 18 s-triazines in two different concentration ratios. Experiments were designed to allow a valid statistical description of the entire concentration-response relationships, including the low concentration range down to ECL Observed effects and effect concentrations of mixtures were compared to predictions of mixture toxicity. Predictions were calculated from the concentration-response functions of individual s-triazines by applying the concepts of concentration addition and independent action (response addition) alternatively. Predictions based on independent action tend to underestimate the overall toxicity of s-triazine mixtures. In contrast, the concept of concentration addition provides highly accurate predictions of s-triazine mixture toxicity, irrespective of the effect level under consideration and the concentration ratio of the mixture components. This also holds true when the mixture components are present in concentrations below their individual NOEC values. Concentrations statistically estimated to elicit non-significant effects of only 1% still contribute to the overall toxicity. When present in a multi-component mixture they can co-operate to give a severe joint effect. Applicability of the findings obtained with s-triazines to mixtures of other contaminants in aquatic systems and consequences for risk as

Naturhaushalt und Lebensgemeinschaften sind multiplen Gemischen von Umweltchemikalien ausgesetzt. Die bisherige Abschätzung des ökologischen Gefährdungspotentials von Stoffmischungen richtet sich auf die Bewertung der Toxizität von Einzelstoffen.Mit den aus der Pharmakologie und Toxikologie verfügbaren biometrischen Modellen der Konzentrations-Additivität und der Unabhängigen Wirkung steht ein pragmatischer Ansatz für die Ermittlung und Beurteilung von Kombinationswirkungen zur Verfügung, der mit der Kenntnis von Einzelstoff-Toxizitäten Prognosen für die Toxizität von Gemischen ermöglicht.Diese als Vorhersagekonzepte nutzbaren biometrischen Modelle werden vorgestellt und das notwendige experimentelle Design erläutert. Die prinzipielle Eignung dieser Vorhersagekonzepte wurde anhand von Analysen der Toxizität binärer und multipler Gemische definierter Umweltchemikalien in zwei Biotests (Grünalgen- und Leuchtbakterien-Test) untersucht. In dieser Arbeit werden exemplarisch die Ergebnisse der Untersuchungen mit Grünalgen analysiert. Die dazu kongruenten Ergebnisse parallel durchgeführter Arbeiten mit Leuchtbakterien sind nachzulesen in Grimme (1988).Die erzielten Ergebnisse zeigen die experimentelle Zugänglichkeit der Analyse von Mischungstoxizitäten, insbesondere auch im Bereich niedriger, statistisch nicht signifikant wirkender Einzelstoff-Konzentrationen. Es wird auf die Notwendigkeit hingewiesen, Kombinationswirkungen bei der Festlegung von Umweltstandards zu berücksichtigen.AbstractEcosystems and biocoenoses are exposed to multiple mixtures of environmental pollutants, but the usual risk assessment of chemical toxicities is focussed only on the judgement of single substance toxicity.With the two biometrical models concentration-addition and independent action known from pharmacology and toxicology, a pragmatic way for the analysis of combined effects is possible using the experimental knowledge of single substance toxicity.A short introduction to the models is given

Current approaches to the assessment of chemical hazards focus on toxicity studies with single, pure chemicals. In the environment, however, organisms are exposed to numerous pollutants simultaneously. We studied the toxicities of multiple mixtures of pesticides and antibiotics in algal and bacterial bioassays. The test mixtures were composed of 14 to 18 components with either identical or completely different specific mechanisms of action. The results reveal that reliable predictions of mixture toxicities can be derived from concentration response data of single toxicants by applying two different concepts: concentration addition in cases of similarly acting mixture components and independent action for substances with dissimilar mechanisms of action.