ALBERT

Description: Over the last decades, treatment of domestic wastewater promoted by environmental regulations have reduced human health risks and improved water quality. However, ecological risks caused by effluents of wastewater treatment plants (WWTPs) discharged into rivers still persist. Moreover, the evolution of these ecological risks in the future is intimately related to effects of changing climate, especially regarding streamflow in receiving rivers. Here, we present an analytical and transferable framework for assessing the ecological risks posed by WWTP‐effluents at the catchment scale. The framework combines the size‐class k of WWTPs, which is a load‐proxy, with their outflows' location in river networks, represented by stream‐order ω. We identify ecological risks by using three proxy indicators: the urban discharge fraction and the local‐scale concentrations of each total phosphorous and ammonium‐nitrogen discharged from WWTPs. About 3,200 WWTPs over three large catchments (Rhine, Elbe, and Weser) in Central Europe were analyzed by incorporating simulated streamflow for the most extreme projected climate change scenario. We found that WWTPs causing ecological risks in the future prevail in lower ω, across almost all k. Distinct patterns of ecological risks are identified in the k‐ω framework for different indicators and catchments. We show, as climate changes, intensified risks are especially expected in lower ω receiving effluents of intermediate‐k WWTPs. We discuss the implications of our findings for prioritizing WWTPs upgrading and urging updates on environmental regulations. Further discussions underline the feasibility of applying the framework to any geographical regions and highlight its potentials to help in achieving global long‐term commitments on freshwater security.

Description: Key Points: An analytical, generic framework was developed to assess wastewater treatment plants causing ecological risks in rivers under climate change. Smaller streams will face higher ecological risks for almost all load classes of wastewater treatment plants in future climate. Of the legally regulated effluent parameters for treated wastewater, ammonium‐nitrogen concentration will pose the greatest ecological risk.

Description: Helmholtz Association http://dx.doi.org/10.13039/501100009318

Description: Data showing B/Ca, Mg/Ca, Li/Ca and Sr/Ca measured in the calcareous red alga Lithothamnion coralliodes lived-collected at different sites and depths across the Mediterranean Sea (Aegadian Islands, 40 m depth; Elba, 45 m depth; Pontian Islands, 66 m depth) and in the Atlantic Ocean (Morlaix Bay, 12 m depth). Element concentrations have been measured using an Agilent ICP-QQQ 8900 quadrupole ICP-MS coupled to an Excimer laser ablation system (193 nm wavelength), at 50 μm spots crossing the algal growth direction.

Description: This data set consist of a single netcdf file with a set of optimised global surface carbon fluxes (CO2), estimated by variational inverse methods using the TOMCAT chemical transport model, and the INVICAT inverse transport model. We assimilate in-situ surface flask observations from global surface observation sites and Amazonian lower-troposphere vertical profiles of CO2. The vertical profile data used here are available at PANGAEA Data Archiving, at https://doi.org/10.1594/PANGAEA.926834 and more details could be found at Gatti et al. (2021). These surface fluxes are monthly mean values for total emissions (labelled TOTAL_FLUX) on the (approximately) 5.6-degree horizontal model grid. The associated uncertainty for the flux from each grid cell is also included (labelled TOTAL_FLUX_ERROR). The fluxes and uncertainties cover the period of January 2010 to December 2018 and units are gC/m2/day, and time units are days since January 1st 2010. Further details about the data can be found in Basso et al. (2023) in the documentation section.

Description: To improve diagnosis of Amazonia's carbon cycle, starting in 2010, we initiated regular observation of lower troposphere CO2 concentrations at four aircraft vertical profiling sites spread over the Brazilian Amazonia. The four sites from the CARBAM project at Amazonia: SAN (2.86S 54.95W); ALF (8.80S 56.75W); RBA (9.38S 67.62W); TAB (5.96S 70.06W) was from 2010 to 2012 and TEF (3.39S 65.6W), started in 2013. The sampling period was typically twice per month (Gatti et al., 2014; Basso et al., 2016; Miller et al., 2007; d'Amelio et al., 2009; Domingues et al., 2020). Over nine-years, 590 vertical profiles were performed in a descending spiral profile from 4420 m to 300 m a.s.l. A mean of 75 vertical profiles was performed per year from 2010 to 2018 at the 4 sites, except for 2015 and 2016. In 2015 the flight collection was stopped in April at all sites, returning only in November at RBA. In 2016 only RBA and ALF were measured. The vertical profiles were usually taken between 12:0 and 13:00 local time. Air is sampled by semi-automatic filling of 0.7 L boro-silicate flasks inside purpose-built suitcases (PFP -Programmable Flask Package) (Tans et al., 1996); there are two versions, one with 17flasks at SAN, and another with 12 flasks at TAB_TEF, ALF and RBA. This suitcase is connected to a compressor package (PCP –Portable Compressor Package), containing batteries and 2 compressors, which is connected to an air inlet on the outside of the aircraft at wing or window, depending on the aircraft model. Once a PFP (i.e. one vertical profile) has been filled with air the PFP is transported (from 2010 to 2014) to the IPEN (Instituto de Pesquisas Energéticas e Nucleares) Atmospheric Chemistry Laboratory in Sao Paulo, Brazil and since 2015 to the INPE/ LaGEE(Instituto Nacional de Pesquisas Espaciais/Greenhouse Gases Laboratory), in Sao Jose dos Campos, Sao Paulo state, Brazil. This laboratory is a replica of the NOAA/ESRL/GMD trace gas analysis system at Boulder, Colorado, USA, and was constructed in 2003 and sent to IPEN where started the analysis in 2004.Air samples were analysed with a non-dispersive infrared (NDIR) analyser for CO2. To ensure the accuracy, we construct a calibration curve every 2 samples. The calibration curve constructed with 3-standards concentrations, produced by NOAA/ESRL/GMD. The “High” (10 ppm higher than medium), “medium” (similar to mean CO2 concentration founded in Amazonia), and “Low” (10 ppm lower than medium). We have an intercomparison program with NOAA at Natal site (5S, 35W, located at Brazilian northeast coast) where the comparison IPEN/INPE-NOAA was -0.05 ± 0.38ppm. The precision is analysed based on CO2mole fraction from “target tanks” (calibrated CO2in air in high pressure cylinders treated as unknowns by NOAA) and demonstrated long-term repeatability of 0.03ppm and a difference between measured and calibrated values of 0.03 ppm. Additional information can be shared from the LaGEE/INPE group as temperature, precipitation, and others parameters used by the group for the Nature paper entitled “Decrease in Amazonia carbon uptake linked to trends in deforestation and climate” (Gatti et al, 2021).

Description: To improve diagnosis of Amazonia's carbon cycle, starting in 2010, we initiated regular observation of lower troposphere CH4 concentrations at four aircraft vertical profiling sites spread over the Brazilian Amazonia. The four sites from the CARBAM project at Amazonia: SAN (2.86S 54.95W); ALF (8.80S 56.75W); RBA (9.38S 67.62W); TAB (5.96S 70.06W) was from 2010 to 2012 and TEF (3.39S 65.6W), started in 2013. The sampling period was typically twice per month (Gatti et al., 2014; Basso et al., 2016; Miller et al., 2007; d'Amelio et al., 2009; Domingues et al., 2020). Over nine-years, 590 vertical profiles were performed in a descending spiral profile from 4420 m to 300 m a.s.l. A mean of 75 vertical profiles was performed per year from 2010 to 2018 at the 4 sites, except for 2015 and 2016. In 2015 the flight collection was stopped in April at all sites, returning only in November at RBA. In 2016 only RBA and ALF were measured. The vertical profiles were usually taken between 12:0 and 13:00 local time. Air is sampled by semi-automatic filling of 0.7 L boro-silicate flasks inside purpose-built suitcases (PFP -Programmable Flask Package) (Tans et al., 1996); there are two versions, one with 17 flasks at SAN, and another with 12 flasks at TAB_TEF, ALF and RBA. This suitcase is connected to a compressor package (PCP –Portable Compressor Package), containing batteries and 2 compressors, which is connected to an air inlet on the outside of the aircraft at wing or window, depending on the aircraft model. Once a PFP (i.e. one vertical profile) has been filled with air the PFP is transported (from 2010 to 2014) to the IPEN (Instituto de Pesquisas Energéticas e Nucleares) Atmospheric Chemistry Laboratory in Sao Paulo, Brazil and since 2015 to the INPE/ LaGEE(Instituto Nacional de Pesquisas Espaciais/Greenhouse Gases Laboratory), in Sao Jose dos Campos, Sao Paulo state, Brazil. This laboratory is a replica of the NOAA/ESRL/GMD trace gas analysis system at Boulder, Colorado, USA, and was constructed in 2003 and sent to IPEN where started the analysis in 2004. The CH 4 analysis system is an FID (Flame Ionization Detector) chromatography (HP6890 Plus+ model) with pre-column of 198 cm of length and 3/16” o.d. (Silica Gel 80/100 mesh), a column of 106 cm of length and 3/16” o.d. (Molecular Sieve 5A 80/100 mesh), and a 12 mL volume sample loop (see Basso et al. 2016 for a detailed description). In order to assess the accuracy and long-term repeatability of the CH4 measurements, a previously calibrated sample is measured as an unknown in the system regularly. These results indicate long-term repeatability (one sigma) of 1.0 ppb. An inter-comparison between INPE and NOAA of weekly measurements at NAT (Brazilian northeast coast site) had a mean difference of 0.24±2.67 ppb (r = 0.98).

Description: Statistical distributions of flood peak discharges often show heavy tail behavior, i.e., extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior. This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail behavior, and the heaviness of the tails is very difficult to predict, which may lead to unnecessarily high flood damage. Despite its high importance, the literature on the heavy tail behavior of flood distributions is rather fragmented. In this review, we provide a coherent overview of the processes causing heavy flood tails and the implications for science and practice. Specifically, we propose nine hypotheses on the mechanisms causing heavy tails in flood peak distributions related to processes in the atmosphere, the catchment and the river system. We then discuss to which extent the current knowledge supports or contradicts these hypotheses. We also discuss the statistical conditions for the emergence of heavy tail behavior based on derived distribution theory and relate them to the hypotheses and flood generation mechanisms. We review the degree to which the heaviness of the tails can be predicted from process knowledge and data. Finally, we recommend further research towards testing the hypotheses and improving the prediction of heavy tails.

Description: The robust estimation of extreme flood magnitude in poorly observed or ungauged basins is of critical importance for designing mitigation measures, particularly in the presence of anthropogenic environmental change and accelerating climatic changes. Traditional methods for estimating flood extremes are strongly limited by the availability of sufficiently long timeseries as these are typically designed to use annual maxima or a few values above a high threshold. In the present work we use a recent statistical model, the Metastatistical Extreme Values (MEV) distribution, in combination with a conceptual model of flood generation processes, the Phisically-based Extreme Values (PhEV) distribution, to explore the possible estimation of high quantiles where few or no observations exist. The main novelty of the approach is the ability of extracting extreme streamflow values from "ordinary" streamflow peaks and to provide a characterization based on a limited and physically meaningful set of hydrological parameters. The proposed methodology aims to overcome limitations in data availability by exploiting the relatively large number of daily observations available even in short time series (as opposed to the low number of yearly maxima) and a few hydrological attributes of the catchment that may be "guessed" on the basis of limited information. A large-scale application on 178 catchments in Germany allows us to formulate a reliable calibration technique and to show its controllable estimation uncertainty: the median relative error computed on predicted extreme streamflow values is globally contained between -25% and +50%:.

Description: Over the past decades, coralline algae have increasingly been used as archives of palaeoclimate information due to their seasonal growth bands and their vast distribution from high latitudes to the tropics. Traditionally, these reconstructions have been performed mainly on high latitude species, limiting the geographical area of their potential use. Here we assess the use of temperate crustose fossil coralline algae from shallow water habitats for palaeoenvironmental reconstruction to generate records of past climate change. We determine the potential of three different species of coralline algae, Lithothamnion minervae, Lithophyllum stictaeforme and Mesophyllum philippii, with different growth patterns, as archives for pH (δ11B) and temperature (Mg/Ca) reconstruction in the Mediterranean Sea. Mg concentration is driven by temperature but modulated by growth rate, which is controlled by species‐specific and intraspecific growth patterns. L. minervae is a good temperature recorder, showing a moderate warming trend in specimens from 11.37 cal ka BP (from 14.2 ± 0.4°C to 14.9 ± 0.15°C) to today. In contrast to Mg, all genera showed consistent values of boron isotopes (δ11B) suggesting a common control on boron incorporation. The recorded δ11B in modern and fossil coralline specimens is in agreement with literature data about early Holocene pH, opening new perspectives of coralline‐based, high‐resolution pH reconstructions in deep time.

Description: This study proposes a new process‐based framework to characterize and classify runoff events of various magnitudes occurring in a wide range of catchments. The framework uses dimensionless indicators that characterize space–time dynamics of precipitation events and their spatial interaction with antecedent catchment states, described as snow cover, distribution of frozen soils, and soil moisture content. A rigorous uncertainty analysis showed that the developed indicators are robust and regionally consistent. Relying on covariance‐ and ratio‐based indicators leads to reduced classification uncertainty compared to commonly used (event‐based) indicators based on absolute values of metrics such as duration, volume, and intensity of precipitation events. The event typology derived from the proposed framework is able to stratify events that exhibit distinct hydrograph dynamics even if streamflow is not directly used for classification. The derived typology is therefore able to capture first‐order controls of event runoff response in a wide variety of catchments. Application of this typology to about 180,000 runoff events observed in 392 German catchments revealed six distinct regions with homogeneous event type frequency that match well regions with similar behavior in terms of runoff response identified in Germany. The detected seasonal pattern of event type occurrence is regionally consistent and agrees well with the seasonality of hydroclimatic conditions. The proposed framework can be a useful tool for comparative analyses of regional differences and similarities of runoff generation processes at catchment scale and their possible spatial and temporal evolution.

Description: The climate change impact and adaptation simulations from the Agricultural Model Intercomparison and Improvement Project (AgMIP) for wheat provide a unique dataset of multi-model ensemble simulations for 60 representative global locations covering all global wheat mega environments. The multi-model ensemble reported here has been thoroughly benchmarked against a large number of experimental data, including different locations, growing season temperatures, atmospheric CO2 concentration, heat stress scenarios, and their interactions. In this paper, we describe the main characteristics of this global simulation dataset. Detailed cultivar, crop management, and soil datasets were compiled for all locations to drive 32 wheat growth models. The dataset consists of 30-year simulated data including 25 output variables for nine climate scenarios, including Baseline (1980-2010) with 360 or 550 ppm CO2, Baseline +2oC or +4oC with 360 or 550 ppm CO2, a mid-century climate change scenario (RCP8.5, 571 ppm CO2), and 1.5°C (423 ppm CO2) and 2.0oC (487 ppm CO2) warming above the pre-industrial period (HAPPI). This global simulation dataset can be used as a benchmark from a well-tested multi-model ensemble in future analyses of global wheat. Also, resource use efficiency (e.g., for radiation, water, and nitrogen use) and uncertainty analyses under different climate scenarios can be explored at different scales. The DOI for the dataset is 10.5281/zenodo.4027033 (AgMIP-Wheat, 2020), and all the data are available on the data repository of Zenodo (doi: 10.5281/zenodo.4027033). Two scientific publications have been published based on some of these data here.