Showing papers by "University of Bremen published in 2018"

Nanoparticles in the environment: where do we come from, where do we go to?

Abstract: Nanoparticles serve various industrial and domestic purposes which is reflected in their steadily increasing production volume. This economic success comes along with their presence in the environment and the risk of potentially adverse effects in natural systems. Over the last decade, substantial progress regarding the understanding of sources, fate, and effects of nanoparticles has been made. Predictions of environmental concentrations based on modelling approaches could recently be confirmed by measured concentrations in the field. Nonetheless, analytical techniques are, as covered elsewhere, still under development to more efficiently and reliably characterize and quantify nanoparticles, as well as to detect them in complex environmental matrixes. Simultaneously, the effects of nanoparticles on aquatic and terrestrial systems have received increasing attention. While the debate on the relevance of nanoparticle-released metal ions for their toxicity is still ongoing, it is a re-occurring phenomenon that inert nanoparticles are able to interact with biota through physical pathways such as biological surface coating. This among others interferes with the growth and behaviour of exposed organisms. Moreover, co-occurring contaminants interact with nanoparticles. There is multiple evidence suggesting nanoparticles as a sink for organic and inorganic co-contaminants. On the other hand, in the presence of nanoparticles, repeatedly an elevated effect on the test species induced by the co-contaminants has been reported. In this paper, we highlight recent achievements in the field of nano-ecotoxicology in both aquatic and terrestrial systems but also refer to substantial gaps that require further attention in the future.

Arsenic uptake, toxicity, detoxification, and speciation in plants : physiological, biochemical, and molecular aspects

Abstract: Environmental contamination with arsenic (As) is a global environmental, agricultural and health issue due to the highly toxic and carcinogenic nature of As. Exposure of plants to As, even at very low concentration, can cause many morphological, physiological, and biochemical changes. The recent research on As in the soil-plant system indicates that As toxicity to plants varies with its speciation in plants (e.g., arsenite, As(III); arsenate, As(V)), with the type of plant species, and with other soil factors controlling As accumulation in plants. Various plant species have different mechanisms of As(III) or As(V) uptake, toxicity, and detoxification. This review briefly describes the sources and global extent of As contamination and As speciation in soil. We discuss different mechanisms responsible for As(III) and As(V) uptake, toxicity, and detoxification in plants, at physiological, biochemical, and molecular levels. This review highlights the importance of the As-induced generation of reactive oxygen species (ROS), as well as their damaging impacts on plants at biochemical, genetic, and molecular levels. The role of different enzymatic (superoxide dismutase, catalase, glutathione reductase, and ascorbate peroxidase) and non-enzymatic (salicylic acid, proline, phytochelatins, glutathione, nitric oxide, and phosphorous) substances under As(III/V) stress have been delineated via conceptual models showing As translocation and toxicity pathways in plant species. Significantly, this review addresses the current, albeit partially understood, emerging aspects on (i) As-induced physiological, biochemical, and genotoxic mechanisms and responses in plants and (ii) the roles of different molecules in modulation of As-induced toxicities in plants. We also provide insight on some important research gaps that need to be filled to advance our scientific understanding in this area of research on As in soil-plant systems.

The Advancement of Learning

Abstract: 150 p. First published as "The tvvoo bookes of Francis Bacon, of the proficience and aduancement of learning, diuine and humane. To the King. At London: Printed for Henrie Tomes [...] 1605" Text based on G.W. Kitchin's 1861 edition. Paragraph sections according to J. Spedding's 1854 edition. Page numbering of J. Spedding's 1854 edition has been added in square brackets [ ] in the following manner: to avoid word separation, page numbers precede words that were separated in the original edition. Chapter and section numerals of W.A. Wright's 1869 edition have been included. Paragraph sections in Spedding's 1854 edition that were apparently omitted in Kitchin's 1861 edition and disregarded in Wright's 1869 textual analysis are marked as omissions [--]. Greek words and sentences have been enclosed within pointed brackets and will be rendered as Greek characters with appropriate True Type Fonts like Scholars Press' Ionic (SPIONIC). All quotations have been capitalized. Spedding's marginal titles and italics within the text had to be omitted as well as his tables. Please consult recent editions for translations and references for Bacon's quotations.

Global sea-level budget 1993 - present

Abstract: Global mean sea level is an integral of changes occurring in the climate system in response to unforced climate variability as well as natural and anthropogenic forcing factors. Its temporal evolution allows detecting changes (e.g., acceleration) in one or more components. Study of the sea level budget provides constraints on missing or poorly known contributions, such as the unsurveyed deep ocean or the still uncertain land water component. In the context of the World Climate Research Programme Grand Challenge entitled “Regional Sea Level and Coastal Impacts”, an international effort involving the sea level community worldwide has been recently initiated with the objective of assessing the various data sets used to estimate components of the sea level budget during the altimetry era (1993 to present). These data sets are based on the combination of a broad range of space-based and in situ observations, model estimates and algorithms. Evaluating their quality, quantifying uncertainties and identifying sources of discrepancies between component estimates is extremely useful for various applications in climate research. This effort involves several tens of scientists from about fifty research teams/institutions worldwide (www.wcrp-climate.org/grand-challenges/gc-sea- level). The results presented in this paper are a synthesis of the first assessment performed during 2017-2018. We present estimates of the altimetry-based global mean sea level (average rate of 3.1 +/- 0.3 mm/yr and acceleration of 0.1 mm/yr2 over 1993-present), as well as of the different components of the sea level budget (http://doi.org/10.17882/54854). We further examine closure of the sea level budget, comparing the observed global mean sea level with the sum of components. Ocean thermal expansion, glaciers, Greenland and Antarctica contribute by 42%, 21%, 15% and 8% to the global mean sea level over the 1993-present. We also study the sea level budget over 2005-present, using GRACE-based ocean mass estimates instead of sum of individual mass components. Results show closure of the sea level budget within 0.3 mm/yr. Substantial uncertainty remains for the land water storage component, as shown in examining individual mass contributions to sea level.

Invertible Residual Networks

Abstract: We show that standard ResNet architectures can be made invertible, allowing the same model to be used for classification, density estimation, and generation. Typically, enforcing invertibility requires partitioning dimensions or restricting network architectures. In contrast, our approach only requires adding a simple normalization step during training, already available in standard frameworks. Invertible ResNets define a generative model which can be trained by maximum likelihood on unlabeled data. To compute likelihoods, we introduce a tractable approximation to the Jacobian log-determinant of a residual block. Our empirical evaluation shows that invertible ResNets perform competitively with both state-of-the-art image classifiers and flow-based generative models, something that has not been previously achieved with a single architecture.

Risks, Release and Concentrations of Engineered Nanomaterial in the Environment.

Abstract: For frequently used engineered nanomaterials (ENMs) CeO2-, SiO2-, and Ag, past, current, and future use and environmental release are investigated. Considering an extended period (1950 to 2050), we assess ENMs released through commercial activity as well as found in natural and technical settings. Temporal dynamics, including shifts in release due to ENM product application, stock (delayed use), and subsequent end-of-life product treatment were taken into account. We distinguish predicted concentrations originating in ENM use phase and those originating from end-of-life release. Furthermore, we compare Ag- and CeO2-ENM predictions with existing measurements. The correlations and limitations of the model, and the analytic validity of our approach are discussed in the context of massive use of assumptive model data and high uncertainty on the colloidal material captured by the measurements. Predictions for freshwater CeO2-ENMs range from 1 pg/l (2017) to a few hundred ng/l (2050). Relative to CeO2, the SiO2-ENMs estimates are approximately 1,000 times higher, and those for Ag-ENMs 10 times lower. For most environmental compartments, ENM pose relatively low risk; however, organisms residing near ENM ‘point sources’ (e.g., production plant outfalls and waste treatment plants), which are not considered in the present work, may be at increased risk.

MoB/g-C3N4 Interface Materials as a Schottky Catalyst to Boost Hydrogen Evolution

Abstract: Proton adsorption on metallic catalysts is a prerequisite for efficient hydrogen evolution reaction (HER). However, tuning proton adsorption without perturbing metallicity remains a challenge. A Schottky catalyst based on metal–semiconductor junction principles is presented. With metallic MoB, the introduction of n-type semiconductive g-C3N4 induces a vigorous charge transfer across the MoB/g-C3N4 Schottky junction, and increases the local electron density in MoB surface, confirmed by multiple spectroscopic techniques. This Schottky catalyst exhibits a superior HER activity with a low Tafel slope of 46 mV dec−1 and a high exchange current density of 17 μA cm−2, which is far better than that of pristine MoB. First-principle calculations reveal that the Schottky contact dramatically lowers the kinetic barriers of both proton adsorption and reduction coordinates, therefore benefiting surface hydrogen generation.

Non-Markovian quantum processes: Complete framework and efficient characterization

Abstract: Currently, there is no systematic way to describe a quantum process with memory solely in terms of experimentally accessible quantities However, recent technological advances mean we have control over systems at scales where memory effects are non-negligible The lack of such an operational description has hindered advances in understanding physical, chemical, and biological processes, where often unjustified theoretical assumptions are made to render a dynamical description tractable This has led to theories plagued with unphysical results and no consensus on what a quantum Markov (memoryless) process is Here, we develop a universal framework to characterize arbitrary non-Markovian quantum processes We show how a multitime non-Markovian process can be reconstructed experimentally, and that it has a natural representation as a many-body quantum state, where temporal correlations are mapped to spatial ones Moreover, this state is expected to have an efficient matrix-product-operator form in many cases Our framework constitutes a systematic tool for the effective description of memory-bearing open-system evolutions

Safe Reinforcement Learning via Shielding

Abstract: Reinforcement learning algorithms discover policies that maximize reward, but do not necessarily guarantee safety during learning or execution phases. We introduce a new approach to learn optimal policies while enforcing properties expressed in temporal logic. To this end, given the temporal logic specification that is to be obeyed by the learning system, we propose to synthesize a reactive system called a shield. The shield monitors the actions from the learner and corrects them only if the chosen action causes a violation of the specification. We discuss which requirements a shield must meet to preserve the convergence guarantees of the learner. Finally, we demonstrate the versatility of our approach on several challenging reinforcement learning scenarios.

Tropospheric Ozone Assessment Report: Present-day distribution and trends of tropospheric ozone relevant to climate and global atmospheric chemistry model evaluation

Abstract: The Tropospheric Ozone Assessment Report (TOAR) is an activity of the International Global Atmospheric Chemistry Project. This paper is a component of the report, focusing on the present-day distribution and trends of tropospheric ozone relevant to climate and global atmospheric chemistry model evaluation. Utilizing the TOAR surface ozone database, several figures present the global distribution and trends of daytime average ozone at 2702 non-urban monitoring sites, highlighting the regions and seasons of the world with the greatest ozone levels. Similarly, ozonesonde and commercial aircraft observations reveal ozone’s distribution throughout the depth of the free troposphere. Long-term surface observations are limited in their global spatial coverage, but data from remote locations indicate that ozone in the 21st century is greater than during the 1970s and 1980s. While some remote sites and many sites in the heavily polluted regions of East Asia show ozone increases since 2000, many others show decreases and there is no clear global pattern for surface ozone changes since 2000. Two new satellite products provide detailed views of ozone in the lower troposphere across East Asia and Europe, revealing the full spatial extent of the spring and summer ozone enhancements across eastern China that cannot be assessed from limited surface observations. Sufficient data are now available (ozonesondes, satellite, aircraft) across the tropics from South America eastwards to the western Pacific Ocean, to indicate a likely tropospheric column ozone increase since the 1990s. The 2014–2016 mean tropospheric ozone burden (TOB) between 60˚N–60˚S from five satellite products is 300 Tg ± 4%. While this agreement is excellent, the products differ in their quantification of TOB trends and further work is required to reconcile the differences. Satellites can now estimate ozone’s global long-wave radiative effect, but evaluation is difficult due to limited in situ observations where the radiative effect is greatest.

Space-borne Bose–Einstein condensation for precision interferometry

Abstract: Owing to the low-gravity conditions in space, space-borne laboratories enable experiments with extended free-fall times. Because Bose–Einstein condensates have an extremely low expansion energy, space-borne atom interferometers based on Bose–Einstein condensation have the potential to have much greater sensitivity to inertial forces than do similar ground-based interferometers. On 23 January 2017, as part of the sounding-rocket mission MAIUS-1, we created Bose–Einstein condensates in space and conducted 110 experiments central to matter-wave interferometry, including laser cooling and trapping of atoms in the presence of the large accelerations experienced during launch. Here we report on experiments conducted during the six minutes of in-space flight in which we studied the phase transition from a thermal ensemble to a Bose–Einstein condensate and the collective dynamics of the resulting condensate. Our results provide insights into conducting cold-atom experiments in space, such as precision interferometry, and pave the way to miniaturizing cold-atom and photon-based quantum information concepts for satellite-based implementation. In addition, space-borne Bose–Einstein condensation opens up the possibility of quantum gas experiments in low-gravity conditions1,2. A Bose–Einstein condensate is created in space that has sufficient stability to enable its characteristic dynamics to be studied.

A Review of Environmental Contamination and Health Risk Assessment of Wastewater Use for Crop Irrigation with a Focus on Low and High-Income Countries.

Abstract: Population densities and freshwater resources are not evenly distributed worldwide. This has forced farmers to use wastewater for the irrigation of food crops. This practice presents both positive and negative effects with respect to agricultural use, as well as in the context of environmental contamination and toxicology. Although wastewater is an important source of essential nutrients for plants, many environmental, sanitary, and health risks are also associated with the use of wastewater for crop irrigation due to the presence of toxic contaminants and microbes. This review highlights the harmful and beneficial impacts of wastewater irrigation on the physical, biological, and chemical properties of soil (pH, cations and anions, organic matter, microbial activity). We delineate the potentially toxic element (PTEs) build up in the soil and, as such, their transfer into plants and humans. The possible human health risks associated with the use of untreated wastewater for crop irrigation are also predicted and discussed. We compare the current condition of wastewater reuse in agriculture and the associated environmental and health issues between developing and developed countries. In addition, some integrated sustainable solutions and future perspectives are also proposed, keeping in view the regional and global context, as well as the grounded reality of wastewater use for crop production, sanitary and planning issues, remedial techniques, awareness among civil society, and the role of the government and the relevant stakeholders.

Operational Markov Condition for Quantum Processes.

Abstract: We derive a necessary and sufficient condition for a quantum process to be Markovian which coincides with the classical one in the relevant limit. Our condition unifies all previously known definitions for quantum Markov processes by accounting for all potentially detectable memory effects. We then derive a family of measures of non-Markovianity with clear operational interpretations, such as the size of the memory required to simulate a process or the experimental falsifiability of a Markovian hypothesis.

Towards Massive Connectivity Support for Scalable mMTC Communications in 5G Networks

Abstract: The fifth generation of cellular communication systems is foreseen to enable a multitude of new applications and use cases with very different requirements. A new 5G multi-service air interface needs to enhance broadband performance as well as provide new levels of reliability, latency, and supported number of users. In this paper, we focus on the massive Machine Type Communications (mMTC) service within a multi-service air interface. Specifically, we present an overview of different physical and medium access techniques to address the problem of a massive number of access attempts in mMTC and discuss the protocol performance of these solutions in a common evaluation framework.

A Haar Wavelet-Based Perceptual Similarity Index for Image Quality Assessment

Abstract: In most practical situations, the compression or transmission of images and videos creates distortions that will eventually be perceived by a human observer. Vice versa, image and video restoration techniques, such as inpainting or denoising, aim to enhance the quality of experience of human viewers. Correctly assessing the similarity between an image and an undistorted reference image as subjectively experienced by a human viewer can thus lead to significant improvements in any transmission, compression, or restoration system. This paper introduces the Haar wavelet-based perceptual similarity index (HaarPSI), a novel and computationally inexpensive similarity measure for full reference image quality assessment. The HaarPSI utilizes the coefficients obtained from a Haar wavelet decomposition to assess local similarities between two images, as well as the relative importance of image areas. The consistency of the HaarPSI with the human quality of experience was validated on four large benchmark databases containing thousands of differently distorted images. On these databases, the HaarPSI achieves higher correlations with human opinion scores than state-of-the-art full reference similarity measures like the structural similarity index (SSIM), the feature similarity index (FSIM), and the visual saliency-based index (VSI). Along with the simple computational structure and the short execution time, these experimental results suggest a high applicability of the HaarPSI in real world tasks.

Synchronous tropical and polar temperature evolution in the Eocene

Abstract: Palaeoclimate reconstructions of periods with warm climates and high atmospheric CO2 concentrations are crucial for developing better projections of future climate change. Deep-ocean1,2 and high-latitude3 palaeotemperature proxies demonstrate that the Eocene epoch (56 to 34 million years ago) encompasses the warmest interval of the past 66 million years, followed by cooling towards the eventual establishment of ice caps on Antarctica. Eocene polar warmth is well established, so the main obstacle in quantifying the evolution of key climate parameters, such as global average temperature change and its polar amplification, is the lack of continuous high-quality tropical temperature reconstructions. Here we present a continuous Eocene equatorial sea surface temperature record, based on biomarker palaeothermometry applied on Atlantic Ocean sediments. We combine this record with the sparse existing data4-6 to construct a 26-million-year multi-proxy, multi-site stack of Eocene tropical climate evolution. We find that tropical and deep-ocean temperatures changed in parallel, under the influence of both long-term climate trends and short-lived events. This is consistent with the hypothesis that greenhouse gas forcing7,8, rather than changes in ocean circulation9,10, was the main driver of Eocene climate. Moreover, we observe a strong linear relationship between tropical and deep-ocean temperatures, which implies a constant polar amplification factor throughout the generally ice-free Eocene. Quantitative comparison with fully coupled climate model simulations indicates that global average temperatures were about 29, 26, 23 and 19 degrees Celsius in the early, early middle, late middle and late Eocene, respectively, compared to the preindustrial temperature of 14.4 degrees Celsius. Finally, combining proxy- and model-based temperature estimates with available CO2 reconstructions8 yields estimates of an Eocene Earth system sensitivity of 0.9 to 2.3 kelvin per watt per square metre at 68 per cent probability, consistent with the high end of previous estimates11.

Improving algorithms and uncertainty estimates for satellite NO 2 retrievals: results from the quality assurance for the essential climate variables (QA4ECV) project

Abstract: . Global observations of tropospheric nitrogen dioxide (NO2) columns have been shown to be feasible from space, but consistent multi-sensor records do not yet exist, nor are they covered by planned activities at the international level. Harmonised, multi-decadal records of NO2 columns and their associated uncertainties can provide crucial information on how the emissions and concentrations of nitrogen oxides evolve over time. Here we describe the development of a new, community best-practice NO2 retrieval algorithm based on a synthesis of existing approaches. Detailed comparisons of these approaches led us to implement an enhanced spectral fitting method for NO2, a 1° × 1° TM5-MP data assimilation scheme to estimate the stratospheric background and improve air mass factor calculations. Guided by the needs expressed by data users, producers, and WMO GCOS guidelines, we incorporated detailed per-pixel uncertainty information in the data product, along with easily traceable information on the relevant quality aspects of the retrieval. We applied the improved QA4ECV NO2 algorithm to the most current level-1 data sets to produce a complete 22-year data record that includes GOME (1995–2003), SCIAMACHY (2002–2012), GOME-2(A) (2007 onwards) and OMI (2004 onwards). The QA4ECV NO2 spectral fitting recommendations and TM5-MP stratospheric column and air mass factor approach are currently also applied to S5P-TROPOMI. The uncertainties in the QA4ECV tropospheric NO2 columns amount to typically 40 % over polluted scenes. The first validation results of the QA4ECV OMI NO2 columns and their uncertainties over Tai'an, China, in June 2006 suggest a small bias (−2 %) and better precision than suggested by uncertainty propagation. We conclude that our improved QA4ECV NO2 long-term data record is providing valuable information to quantitatively constrain emissions, deposition, and trends in nitrogen oxides on a global scale.

Automatic liver tumor segmentation in CT with fully convolutional neural networks and object-based postprocessing

Abstract: Automatic liver tumor segmentation would have a big impact on liver therapy planning procedures and follow-up assessment, thanks to standardization and incorporation of full volumetric information. In this work, we develop a fully automatic method for liver tumor segmentation in CT images based on a 2D fully convolutional neural network with an object-based postprocessing step. We describe our experiments on the LiTS challenge training data set and evaluate segmentation and detection performance. Our proposed design cascading two models working on voxel- and object-level allowed for a significant reduction of false positive findings by 85% when compared with the raw neural network output. In comparison with the human performance, our approach achieves a similar segmentation quality for detected tumors (mean Dice 0.69 vs. 0.72), but is inferior in the detection performance (recall 63% vs. 92%). Finally, we describe how we participated in the LiTS challenge and achieved state-of-the-art performance.

Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm

Abstract: . Since September 2014, NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite has been taking measurements of reflected solar spectra and using them to infer atmospheric carbon dioxide levels. This work provides details of the OCO-2 retrieval algorithm, versions 7 and 8, used to derive the column-averaged dry air mole fraction of atmospheric CO2 ( X CO 2 ) for the roughly 100 000 cloud-free measurements recorded by OCO-2 each day. The algorithm is based on the Atmospheric Carbon Observations from Space (ACOS) algorithm which has been applied to observations from the Greenhouse Gases Observing SATellite (GOSAT) since 2009, with modifications necessary for OCO-2. Because high accuracy, better than 0.25 %, is required in order to accurately infer carbon sources and sinks from X CO 2 , significant errors and regional-scale biases in the measurements must be minimized. We discuss efforts to filter out poor-quality measurements, and correct the remaining good-quality measurements to minimize regional-scale biases. Updates to the radiance calibration and retrieval forward model in version 8 have improved many aspects of the retrieved data products. The version 8 data appear to have reduced regional-scale biases overall, and demonstrate a clear improvement over the version 7 data. In particular, error variance with respect to TCCON was reduced by 20 % over land and 40 % over ocean between versions 7 and 8, and nadir and glint observations over land are now more consistent. While this paper documents the significant improvements in the ACOS algorithm, it will continue to evolve and improve as the CO2 data record continues to expand.

The land ice contribution to sea level during the satellite era

Abstract: Since 1992, there has been a revolution in our ability to quantify the land ice contribution to SLR using a variety of satellite missions and technologies. Each mission has provided unique, but sometimes conflicting, insights into the mass trends of land ice. Over the last decade, over fifty estimates of land ice trends have been published, providing a confusing and often inconsistent picture. The IPCC Fifth Assessment Report (AR5) attempted to synthesise estimates published up to early 2013. Since then, considerable advances have been made in understanding the origin of the inconsistencies, reducing uncertainties in estimates and extending time series. We assess and synthesise results published, primarily, since the AR5, to produce a consistent estimate of land ice mass trends during the satellite era (1992 to 2016). We combine observations from multiple missions and approaches including sea level budget analyses. Our resulting synthesis is both consistent and rigorous, drawing on i) the published literature, ii) expert assessment of that literature, and iii) a new analysis of Arctic glacier and ice cap trends combined with statistical modelling. We present annual and pentad (five-year mean) time series for the East, West Antarctic and Greenland Ice Sheets and glaciers separately and combined. When averaged over pentads, covering the entire period considered, we obtain a monotonic trend in mass contribution to the oceans, increasing from 0.31±0.35 mm of sea level equivalent for 1992-1996 to 1.85±0.13 for 2012-2016. Our integrated land ice trend is lower than many estimates of GRACE-derived ocean mass change for the same periods. This is due, in part, to a smaller estimate for glacier and ice cap mass trends compared to previous assessments. We discuss this, and other likely reasons, for the difference between GRACE ocean mass and land ice trends.

Emergent Properties of Microbial Activity in Heterogeneous Soil Microenvironments: Different Research Approaches Are Slowly Converging, Yet Major Challenges Remain.

Abstract: Over the last 60 years, soil microbiologists have accumulated a wealth of experimental data showing that the usual bulk, macroscopic parameters used to characterize soils (e.g., granulometry, pH, soil organic matter and biomass contents) provide insufficient information to describe quantitatively the activity of soil microorganisms and some of its outcomes, like the emission of greenhouse gases. Clearly, new, more appropriate macroscopic parameters are needed, which reflect better the spatial heterogeneity of soils at the microscale (i.e., the pore scale). For a long time, spectroscopic and microscopic tools were lacking to quantify processes at that scale, but major technological advances over the last 15 years have made suitable equipment available to researchers. In this context, the objective of the present article is to review progress achieved to date in the significant research program that has ensued. This program can be rationalized as a sequence of steps, namely the quantification and modeling of the physical-, (bio)chemical-, and microbiological properties of soils, the integration of these different perspectives into a unified theory, its upscaling to the macroscopic scale, and, eventually, the development of new approaches to measure macroscopic soil characteristics. At this stage, significant progress has been achieved on the physical front, and to a lesser extent on the (bio)chemical one as well, both in terms of experiments and modeling. In terms of microbial aspects, whereas a lot of work has been devoted to the modeling of bacterial and fungal activity in soils at the pore scale, the appropriateness of model assumptions cannot be readily assessed because relevant experimental data are extremely scarce. For the overall research to move forward, it will be crucial to make sure that research on the microbial components of soil systems does not keep lagging behind the work on the physical and (bio)chemical characteristics. Concerning the subsequent steps in the program, very little integration of the various disciplinary perspectives has occurred so far, and, as a result, researchers have not yet been able to tackle the scaling up to the macroscopic level. Many challenges, some of them daunting, remain on the path ahead.

Palaeoclimate constraints on the impact of 2 °C anthropogenic warming and beyond

Abstract: Over the past 3.5 million years, there have been several intervals when climate conditions were warmer than during the pre-industrial Holocene. Although past intervals of warming were forced differently than future anthropogenic change, such periods can provide insights into potential future climate impacts and ecosystem feedbacks, especially over centennial-to-millennial timescales that are often not covered by climate model simulations. Our observation-based synthesis of the understanding of past intervals with temperatures within the range of projected future warming suggests that there is a low risk of runaway greenhouse gas feedbacks for global warming of no more than 2 °C. However, substantial regional environmental impacts can occur. A global average warming of 1–2 °C with strong polar amplification has, in the past, been accompanied by significant shifts in climate zones and the spatial distribution of land and ocean ecosystems. Sustained warming at this level has also led to substantial reductions of the Greenland and Antarctic ice sheets, with sea-level increases of at least several metres on millennial timescales. Comparison of palaeo observations with climate model results suggests that, due to the lack of certain feedback processes, model-based climate projections may underestimate long-term warming in response to future radiative forcing by as much as a factor of two, and thus may also underestimate centennial-to-millennial-scale sea-level rise.