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Surface melting of the Greenland Ice Sheet contributes a large amount to current and future sea level rise. Increased surface melt may lower the reflectivity of the ice sheet surface and thereby increase melt rates: the so-called melt-albedo feedback describes this self-sustaining increase in surface melting. In order to test the effect of the melt-albedo feedback in a prognostic ice sheet model, we implement dEBM-simple, a simplified version of the diurnal Energy Balance Model dEBM, in the Parallel Ice Sheet Model (PISM). The implementation includes a simple representation of the melt-albedo feedback and can thereby replace the positive-degree-day melt scheme. Using PISM-dEBM-simple, we find that this feedback increases ice loss through surface warming by 60 % until 2300 for the high-emission scenario RCP8.5 when compared to a scenario in which the albedo remains constant at its present-day values. With an increase of 90 % compared to a fixed-albedo scenario, the effect is more pronounced for lower surface warming under RCP2.6. Furthermore, assuming an immediate darkening of the ice surface over all summer months, we estimate an upper bound for this effect to be 70 % in the RCP8.5 scenario and a more than 4-fold increase under RCP2.6. With dEBM-simple implemented in PISM, we find that the melt-albedo feedback is an essential contributor to mass loss in dynamic simulations of the Greenland Ice Sheet under future warming.
Knowing the source and runout of debris flows can help in planning strategies aimed at mitigating these hazards. Our research in this paper focuses on developing a novel approach for optimizing runout models for regional susceptibility modelling, with a case study in the upper Maipo River basin in the Andes of Santiago, Chile. We propose a two-stage optimization approach for automatically selecting parameters for estimating runout path and distance. This approach optimizes the random-walk and Perla et al.'s (PCM) two-parameter friction model components of the open-source Gravitational Process Path (GPP) modelling framework. To validate model performance, we assess the spatial transferability of the optimized runout model using spatial crossvalidation, including exploring the model's sensitivity to sample size. We also present diagnostic tools for visualizing uncertainties in parameter selection and model performance. Although there was considerable variation in optimal parameters for individual events, we found our runout modelling approach performed well at regional prediction of potential runout areas. We also found that although a relatively small sample size was sufficient to achieve generally good runout modelling performance, larger samples sizes (i.e. >= 80) had higher model performance and lower uncertainties for estimating runout distances at unknown locations. We anticipate that this automated approach using the open-source R software and the System for Automated Geoscientific Analyses geographic information system (SAGA-GIS) will make process-based debris-flow models more readily accessible and thus enable researchers and spatial planners to improve regional-scale hazard assessments.
The 2020s are an essential decade for achieving the 2030 Agenda and its Sustainable Development Goals (SDGs). For this, SDG research needs to provide evidence that can be translated into concrete actions. However, studies use different SDG data, resulting in incomparable findings. Researchers primarily use SDG databases provided by the United Nations (UN), the World Bank Group (WBG), and the Bertelsmann Stiftung & Sustainable Development Solutions Network (BE-SDSN). We compile these databases into one unified SDG database and examine the effects of the data selection on our understanding of SDG interactions. Among the databases, we observed more different than similar SDG interactions. Differences in synergies and trade-offs mainly occur for SDGs that are environmentally oriented. Due to the increased data availability, the unified SDG database offers a more nuanced and reliable view of SDG interactions. Thus, the SDG data selection may lead to diverse findings, fostering actions that might neglect or exacerbate trade-offs.
Wetlands are dynamic ecosystems that require continuous monitoring and assessment of degradation status to design strategies for their sustainable management. While hydrology provides the primary functional control for the wetland ecosystem, the loss of landscape connectivity influences wetland degradation in a major way as it leads to fragmentation. This article aims to integrate hydrogeomorphic and ecological concepts for the assessment of degradation status and its causal factors for a large wetland in the western Ganga plains, India, the Haiderpur, using a wetlandscape approach. We have used a remote-sensing-based approach, which offers a powerful tool for assessing and linking cross-scale structures, functions, and controls in a wetlandscape. The Haiderpur, a Ramsar site since December 2021, is an artificial wetland located on the right bank of the Ganga River wherein the inflows are controlled by a barrage constructed on the Ganga River apart from smaller tributaries flowing in from the north. A novel aspect of this work is the integration of river dynamics and its connectivity to the wetlandscape to understand the spatiotemporal variability in the waterspread area in the wetland. In this work, we have developed an integrated wetlandscape assessment approach by evaluating wetland's geomorphic and hydrological connectivity status for the period 1993-2019 (25 years) across three different spatial scales - regional, catchment, and wetland. We have highlighted the ecological implications of connectivity and patch dynamics for developing sustainable wetland management plans.
Due to the fact that silicon (Si) increases the resistance of plants against diverse abiotic and biotic stresses, Si nowadays is categorized as beneficial substance for plants. However, humans directly influence Si cycling on a global scale. Intensified agriculture and corresponding harvest-related Si exports lead to Si losses in agricultural soils. This anthropogenic desilication might be a big challenge for modern agriculture. However, there is still only little knowledge about Si cycling in agricultural systems of the temperate zone, because most studies focus on rice and sugarcane production in (sub)tropical areas. Furthermore, many studies are performed for a short term only, and thus do not provide the opportunity to analyze slow changes in soil-plant systems (e.g., desilication) over long periods. We analyzed soil and plant samples from an ongoing long-term field experiment (established 1963) in the temperate zone (NE Germany) to evaluate the effects of different nitrogen-phosphoruspotassium (NPK) fertilization rates and crop straw recycling (i.e., straw incorporation) on anthropogenic desilication in the long term. Our results clearly show that crop straw recycling not only prevents anthropogenic desilication (about 43-60% of Si exports can be saved by crop straw recycling in the long term), but also replenishes plant available Si stocks of agricultural soil-plant systems. Furthermore, we found that a reduction of N fertilization rates of about 69% is possible without considerable biomass losses. This economy of the need for N fertilizers potentially can be combined with the benefits of crop straw recycling, i.e., enhancement of carbon sequestration via straw inputs and prevention of anthropogenic desilication of agricultural soil-plant systems. Thus crop straw recycling might have the potential to act as key management practice in sustainable, low fertilization agriculture in the temperate zone in the future.
Both ice sheets in Greenland and Antarctica are discharging ice into the ocean. In many regions along the coast of the ice sheets, the icebergs calve into a bay. If the addition of icebergs through calving is faster than their transport out of the embayment, the icebergs will be frozen into a melange with surrounding sea ice in winter. In this case, the buttressing effect of the ice melange can be considerably stronger than any buttressing by mere sea ice would be. This in turn stabilizes the glacier terminus and leads to a reduction in calving rates. Here we propose a simple parametrization of ice melange buttressing which leads to an upper bound on calving rates and can be used in numerical and analytical modelling.
The detection of auto-fluorescence in phytogenic, hydrated amorphous silica depositions (phytoliths) has been found to be a promising approach to verify if phytoliths were burnt or not, especially in archaeological contexts. However, it is unknown so far at what temperature and how auto-fluorescence is induced in phytoliths. We used fluorescence microscopy, scanning electron microscope-energy dispersive X-ray spectroscopy (SEM-EDX), and Fourier transform infrared spectroscopy to analyze auto-fluorescence in modern phytoliths extracted from plant samples or in intact leaves of winter wheat. Leaves and extracted phytoliths were heated at different temperatures up to 600 degrees C. The aims of our experiments were i) to find out what temperature is needed to induce auto-fluorescence in phytoliths, ii) to detect temperature-dependent changes in the molecular structure of phytoliths related to auto-fluorescence, and iii) to derive a mechanistic understanding of auto-fluorescence in phytoliths. We found organic compounds associated with phytoliths to cause auto-fluorescence in phytoliths treated at temperatures below approx. 400 degrees C. In phytoliths treated at higher temperatures, i.e., 450 and 600 degrees C, phytolith auto-fluorescence was mainly caused by molecular changes of phytolith silica. Based on our results we propose that auto-fluorescence in phytoliths is caused by clusterization-triggered emissions, which are caused by overlapping electron clouds forming non-conventional chromophores. In phytoliths heated at temperatures above about 400 degrees C dihydroxylation and the formation of siloxanes result in oxygen clusters that serve as non-conventional chromophores in fluorescence events. Furthermore, SEM-EDX analyses revealed that extractable phytoliths were dominated by lumen phytoliths (62%) compared to cell wall phytoliths (38%). Our findings might be not only relevant in archaeological phytolith-based examinations, but also for studies on the temperature-dependent release of silicon from phytoliths and the potential of long-term carbon sequestration in phytoliths.
Beyond CO2 equivalence
(2022)
In this article we review the physical and chemical properties of methane (CH4) relevant to impacts on climate, ecosystems, and air pollution, and examine the extent to which this is reflected in climate and air pollution governance. Although CH4 is governed under the UNFCCC climate regime, its treatment there is limited to the ways in which it acts as a "CO2 equivalent" climate forcer on a 100-year time frame. The UNFCCC framework neglects the impacts that CH4 has on near-term climate, as well its impacts on human health and ecosystems, which are primarily mediated by methane's role as a precursor to tropospheric ozone. Frameworks for air quality governance generally address tropospheric ozone as a pollutant, but do not regulate CH4 itself. Methane's climate and air quality impacts, together with its alarming rise in atmospheric concentrations in recent years, make it clear that mitigation of CH4 emissions needs to be accelerated globally. We examine challenges and opportunities for further progress on CH4 mitigation within the international governance landscapes for climate change and air pollution.
Prima del Novecento
(2023)
While the Intergovernmental Panel on Climate Change (IPCC) physical science reports usually assess a handful of future scenarios, the Working Group III contribution on climate mitigation to the IPCC's Sixth Assessment Report (AR6 WGIII) assesses hundreds to thousands of future emissions scenarios. A key task in WGIII is to assess the global mean temperature outcomes of these scenarios in a consistent manner, given the challenge that the emissions scenarios from different integrated assessment models (IAMs) come with different sectoral and gas-to-gas coverage and cannot all be assessed consistently by complex Earth system models. In this work, we describe the “climate-assessment” workflow and its methods, including infilling of missing emissions and emissions harmonisation as applied to 1202 mitigation scenarios in AR6 WGIII. We evaluate the global mean temperature projections and effective radiative forcing (ERF) characteristics of climate emulators FaIRv1.6.2 and MAGICCv7.5.3 and use the CICERO simple climate model (CICERO-SCM) for sensitivity analysis. We discuss the implied overshoot severity of the mitigation pathways using overshoot degree years and look at emissions and temperature characteristics of scenarios compatible with one possible interpretation of the Paris Agreement. We find that the lowest class of emissions scenarios that limit global warming to “1.5 ∘C (with a probability of greater than 50 %) with no or limited overshoot” includes 97 scenarios for MAGICCv7.5.3 and 203 for FaIRv1.6.2. For the MAGICCv7.5.3 results, “limited overshoot” typically implies exceedance of median temperature projections of up to about 0.1 ∘C for up to a few decades before returning to below 1.5 ∘C by or before the year 2100. For more than half of the scenarios in this category that comply with three criteria for being “Paris-compatible”, including net-zero or net-negative greenhouse gas (GHG) emissions, median temperatures decline by about 0.3–0.4 ∘C after peaking at 1.5–1.6 ∘C in 2035–2055. We compare the methods applied in AR6 with the methods used for SR1.5 and discuss their implications. This article also introduces a “climate-assessment” Python package which allows for fully reproducing the IPCC AR6 WGIII temperature assessment. This work provides a community tool for assessing the temperature outcomes of emissions pathways and provides a basis for further work such as extending the workflow to include downscaling of climate characteristics to a regional level and calculating impacts.