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Valuing damages and benefits of the altered global nitrogen cycle; lessons for national to global policy support
Get PDFCost-benefit analysis (CBA) is increasingly used to inform environmental policy decisions by identifying interventions with the highest net societal benefits. Here we focus on CBAs for nitrogen (NCBA) explaining its history, presenting results of a recent first global NCBA and discussing opportunities and limitations. NCBAs have been conducted since the late 1990s for various geographic regions in Europe the US and China mostly to support air quality and also eutrophication policies. A first valuation of damages and benefits of the full nitrogen (N) cycle was conducted for the European Nitrogen Assessment in 2011, followed by NCBAs for the USA, the Netherlands and Germany. Here we present a first comprehensive global NCBA. Total global damage cost of N pollution in 2010 was estimated at US 2.2 trillion with >95% from increased crop yields. By 2050, global N-related costs rise faster than N benefits because underlying models project that economic growth (GDP) increases willingness-to-pay to prevent N pollution more than crop prices. The geographical distribution of N-related costs will also shift, with China and India surpassing Europe and North America as regions contributing most to global N-related costs. The estimated N cost range for 2010 was US$ 0.6-2.2 trillion with uncertainty largely in dose-impact and damage cost relations. Given the large uncertainties, when using valuation and NCBA to select a N mitigation option, the net benefits should be substantially higher than the costs and markedly better than for a rejected alternative option. Use of NCBA is discouraged to compare international policy options that involve regions with very different levels of GDP, cultures and political systems
Continuous improvement towards environmental protection for pharmaceuticals: advancing a strategy for Europe
Get PDFThe manufacture, use and disposal of pharmaceutical products can lead to their release into the environment, raising concerns about potential risks to biota and human health. This is recognised in the European Commission’s Pharmaceutical Strategy for Europe, which has recently overseen the development of a proposed revision of current pharmaceutical legislation. Amongst other things, this strategy and revision broadly offer strengthened protection against environmental risk. For example, it enhances the power authorities have to refuse market authorisation where an identified risk to the environment cannot be sufficiently addressed, includes a requirement for legacy pharmaceutical products to be risk assessed, includes a broadened scope to cover the entire product lifecycle, and places a greater focus on open data. In this publication, we assess the proposed legislation against the latest scientific knowledge, identifying opportunities for strengthening the protection that it offers. These opportunities include moving towards the risk assessment of mixtures, broadening the scope of effects testing to include non-conventional (e.g., behavioural) and chronic endpoints, making better use of predictive modelling such as Quantitative Structure–Activity Relationships (QSARs), and better accounting for environmental heterogeneity, such as the influence of temperature and especially pH on risk. Many of the elements discussed apply not just to pharmaceuticals but across other chemical domains and regulatory regimes, particularly when considering mixture assessment. Integrating knowledge across sectors and regulatory regimes is therefore crucial to better address the role of pharmaceuticals as one of many environmental pollutants
Where, when, and how FAIR do data from aquatic mesocosm experiments get published?
Get PDFWe analyzed 192 publications from two EU projects focused on aquatic mesocosm facilities for a) the number of data publications in a repository on its own and the number of data publications associated with a scientific paper, b) the time lag between mesocosm experiments and data or paper publication, and c) adherence of scientific papers to FAIR principles of data publication. More data sets were published alongside scientific papers (103) than in a data repository alone (17). The time lag between experimental end to paper publication (34.9 months) was not significantly different from the time lag between experimental end to data publication (36.7 months). Regarding FAIR principles, 32.6% of papers achieved the highest scores (7 or 8), emphasizing a high data transparency relative to other disciplines. To improve data publications, we recommend increased support (especially for interoperability) for and recognition of researchers, as well as increased efforts by journals, repositories, and funders
Zooming in the plastisphere: the ecological interface for phytoplankton–plastic interactions in aquatic ecosystems
Get PDFPhytoplankton is an essential resource in aquatic ecosystems, situated at the base of aquatic food webs. Plastic pollution can impact these organisms, potentially affecting the functioning of aquatic ecosystems. The interaction between plastics and phytoplankton is multifaceted: while microplastics can exert toxic effects on phytoplankton, plastics can also act as a substrate for colonisation. By reviewing the existing literature, this study aims to address pivotal questions concerning the intricate interplay among plastics and phytoplankton/phytobenthos and analyse impacts on fundamental ecosystem processes (e.g. primary production, nutrient cycling). This investigation spans both marine and freshwater ecosystems, examining diverse organisational levels from subcellular processes to entire ecosystems. The diverse chemical composition of plastics, along with their variable properties and role in forming the “plastisphere”, underscores the complexity of their influences on aquatic environments. Morphological changes, alterations in metabolic processes, defence and stress responses, including homoaggregation and extracellular polysaccharide biosynthesis, represent adaptive strategies employed by phytoplankton to cope with plastic-induced stress. Plastics also serve as potential habitats for harmful algae and invasive species, thereby influencing biodiversity and environmental conditions. Processes affected by phytoplankton–plastic interaction can have cascading effects throughout the aquatic food web via altered bottom-up and top-down processes. This review emphasises that our understanding of how these multiple interactions compare in impact on natural processes is far from complete, and uncertainty persists regarding whether they drive significant alterations in ecological variables. A lack of comprehensive investigation poses a risk of overlooking fundamental aspects in addressing the environmental challenges associated with widespread plastic pollution
Mélange dehydration and melting beneath South Sandwich Islands arc
Get PDFMechanisms regulating material transfer from subducted slabs to arc magmas remain debated, centered on metasomatized mantle wedge interactions versus mélange mobilization at the slab-mantle interface. The South Sandiwch Islands arc offers a unique setting to distinguish between these models due to the significant barium isotope contrast between altered oceanic crust and sediments, the latter displaying unusually light barium isotope compositions compared to the global sediment range. Here we show substantial barium isotope variations coupled with invariant strontium isotope ratios in arc lavas, consistent with mélange mobilization beneath the arc. Northern arc lavas display a broader range of barium isotope values than expected from slab inputs, suggesting barium isotope fractionation during slab material transport, potentially driven by phengite-related barium retention within the mélange. Notably, sediments, rather than altered oceanic crust, emerge as the dominant source of barium in arc lavas. While a comparison of barium isotope data from four additional arcs indicates mantle wedge metasomatism remains visible in several cases, mélange mobilization is consistent with available data across all of these subduction zones
Remote mapping of bedrock for future cosmogenic nuclide exposure dating studies in unvisited areas of Antarctica
Get PDFCosmogenic nuclide exposure dating is an important technique for reconstructing glacial histories. Many of the most commonly applied cosmogenic nuclides are extracted from the mineral quartz, meaning sampling of felsic (silica-rich) rock is often preferred to sampling of mafic (silica-poor) rock for exposure dating studies. Fieldwork in remote regions such as Antarctica is subject to time constraints and considerable logistical challenges, making efficient sample recovery critical to successful research efforts. Remote sensing offers an effective way to map the geology of large areas prior to fieldwork and expedite the sampling process. In this study, we assess the viability of multispectral remote sensing to distinguish felsic from mafic rock outcrops at visible-near infrared (VNIR) and shortwave infrared (SWIR) wavelengths using both the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and very high-resolution Worldview-3 (WV-3) imagery. We applied a combination of spectral mapping and ground truth from spectral measurements of 17 rock samples from Mount Murphy in the Amundsen Sea sector of West Antarctica. Using this approach, we identified four dominant rock types which we used as a basis for felsic–mafic differentiation: felsic granites and gneisses, and mafic basalts and fragmental hydrovolcanic rocks. Supervised classification results indicate WV-3 performs well at differentiating felsic and mafic rock types and that ASTER, while coarser, could also achieve satisfactory results and be used in concert with more targeted WV-3 image acquisitions. Finally, we present a revised felsic–mafic geological map for Mt Murphy. Overall, our results highlight the potential of spectral mapping for preliminary reconnaissance when planning future cosmogenic nuclide sampling campaigns in remote, unvisited areas of the polar regions
Conductive silver fabric as a shorting calibration standard for dielectric coaxial probes
No full textDielectric measurements are of significant relevance in many areas of research and industry. The accuracy of dielectric sensors depends highly on their calibration. Traditional short-circuit standards for calibrating coaxial probes face challenges in practical application and interchangeability between probe geometries. We evaluated the use of a polyvalent electrically conductive silver fabric as a shorting standard for empirical calibration of open-ended and coaxial cell probes by comparing it with other materials. Results showed that the type of shorting material used was less critical with increasing probe size as observed in the case of open-ended coaxial probes and that silver fabric was more consistent than other materials across probe geometries. Silver fabric demonstrated high accuracy at frequencies below 100 MHz for the coaxial cell. We also demonstrated the need for including a shorting standard in the empirical calibration of coaxial probes to account for dielectric relaxation phenomena in the radio frequency bandwidth
The impact of variable DOC concentrations on acidification assessments
No full textDissolved organic carbon (DOC) affects the acidity in soil and lake waters and buffers both against acidification and against recovery from acidification. Current acidification assessments, based on the widely used MAGIC (Model of Acidification of Groundwater In Catchments) model, often assume constant DOC concentrations through time, but observations suggest this assumption may not be warranted. Here we used MAGIC to investigate the effect of four different scenarios of variable DOC concentrations on acidification assessments of 75 Swedish lakes during peak acidification (1980), in the recent past (2012) and the near future (2030). In all scenarios, DOC concentrations varied to the same extent in soil and lake waters, so the effects of DOC on soil cation exchange and water acid–base chemistry were accounted for. To capture the possible span of the variable DOC effects, modelled variations covered a large range of concentration levels suggested by earlier studies. A higher proportion of the modelled lakes in the scenarios with variable DOC concentrations were assessed as acidified at the time of peak acidification compared to in the scenario with constant DOC concentration. In 2012 and 2030, the proportion of acidified lakes was in the same range regardless of historical and future DOC scenarios. This means that for management purposes, the MAGIC model with constant DOC concentration assessed the extent of acidification for the recent past and near future without bias
DNA metabarcoding reveal hidden diversity of periphytic eukaryotes on marine Antarctic macroalgae
Get PDFPolar marine macroalgae thrive in extreme conditions, often displaying geographic isolation and high degree of endemism. The “phycosphere” refers to the zone around the algae inhabited by microrganisms. Our study used DNA metabarcoding to survey the eukaryotic communities associated with seven seaweed species obtained at King George Island (South Shetland Islands, maritime Antarctic), including two Rhodophyta, two Chlorophyta and three Phaeophyceae. The ITS2 region was used as a barcode and our analysis yielded 77 eukaryotic ASVs spanning five Kingdoms (Fungi, Metazoa, Chromista, Protozoa, and Viridiplantae) and ten phyla (Ascomycota, Basidiomycota, Cercozoa, Ciliophora, Ochrophyta, Amebozoa, Chlorophyta, Rhodophyta, Bryophyta and Cnidaria). Additionally, we identified 14 potential new occurrence records for Antarctica. Ciliates and green algae were the most species-rich groups. The most abundant assigned associated species was Monostroma angicava (Chrorophyta). Within the macroalgal, the Chlorophyceans Ulothrix sp. hosted the greatest number of taxa, followed by Monostroma hariotii. Our data suggested that Antarctic macroalgae host a rich diversity of associated organisms and the biodiversity associated with the phycosphere remains underestimated
Machine learning for stochastic parametrization
Get PDFAtmospheric models used for weather and climate prediction are traditionally formulated in a deterministic manner. In other words, given a particular state of the resolved scale variables, the most likely forcing from the subgrid scale processes is estimated and used to predict the evolution of the large-scale flow. However, the lack of scale separation in the atmosphere means that this approach is a large source of error in forecasts. Over recent years, an alternative paradigm has developed: the use of stochastic techniques to characterize uncertainty in small-scale processes. These techniques are now widely used across weather, subseasonal, seasonal, and climate timescales. In parallel, recent years have also seen significant progress in replacing parametrization schemes using machine learning (ML). This has the potential to both speed up and improve our numerical models. However, the focus to date has largely been on deterministic approaches. In this position paper, we bring together these two key developments and discuss the potential for data-driven approaches for stochastic parametrization. We highlight early studies in this area and draw attention to the novel challenges that remain
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