Search Results
Coal fly ash: Linking immersion freezing behavior and physicochemical particle properties
2018, Grawe, S., Augustin-Bauditz, S., Clemen, H.-C., Ebert, M., Eriksen Hammer, S., Lubitz, J., Reicher, N., Rudich, Y., Schneider, J., Staacke, R., Stratmann, F., Welti, A., Wex, H.
To date, only a few studies have investigated the potential of coal fly ash particles to trigger heterogeneous ice nucleation in cloud droplets. The presented measurements aim at expanding the sparse dataset and improving process understanding of how physicochemical particle properties can influence the freezing behavior of coal fly ash particles immersed in water. Firstly, immersion freezing measurements were performed with two single particle techniques, i.e., the Leipzig Aerosol Cloud Interaction Simulator (LACIS) and the SPectrometer for Ice Nuclei (SPIN). The effect of suspension time on the efficiency of the coal fly ash particles when immersed in a cloud droplet is analyzed based on the different residence times of the two instruments and employing both dry and wet particle generation. Secondly, two cold-stage setups, one using microliter sized droplets (Leipzig Ice Nucleation Array) and one using nanoliter sized droplets (WeIzmann Supercooled Droplets Observation on Microarray setup) were applied. We found that coal fly ash particles are comparable to mineral dust in their immersion freezing behavior when being dry generated. However, a significant decrease in immersion freezing efficiency was observed during experiments with wet-generated particles in LACIS and SPIN. The efficiency of wet-generated particles is in agreement with the cold-stage measurements. In order to understand the reason behind the deactivation, a series of chemical composition, morphology, and crystallography analyses (single particle mass spectrometry, scanning electron microscopy coupled with energy dispersive X-ray microanalysis, X-ray diffraction analysis) were performed with dry- and wet-generated particles. From these investigations, we conclude that anhydrous CaSO4 and CaO - which, if investigated in pure form, show the same qualitative immersion freezing behavior as observed for dry-generated coal fly ash particles - contribute to triggering heterogeneous ice nucleation at the particle-water interface. The observed deactivation in contact with water is related to changes in the particle surface properties which are potentially caused by hydration of CaSO4 and CaO. The contribution of coal fly ash to the ambient population of ice-nucleating particles therefore depends on whether and for how long particles are immersed in cloud droplets.
Depolarization and lidar ratios at 355, 532, and 1064 nm and microphysical properties of aged tropospheric and stratospheric Canadian wildfire smoke
2018, Haarig, M., Ansmann, A., Baars, H., Jimenez, C., Veselovskii, I., Engelmann, R., Althausen, D.
We present spectrally resolved optical and microphysical properties of western Canadian wildfire smoke observed in a tropospheric layer from 5-6.5 km height and in a stratospheric layer from 15-16 km height during a recordbreaking smoke event on 22 August 2017. Three polarization/ Raman lidars were run at the European Aerosol Research Lidar Network (EARLINET) station of Leipzig, Germany, after sunset on 22 August. For the first time, the linear depolarization ratio and extinction-to-backscatter ratio (lidar ratio) of aged smoke particles were measured at all three important lidar wavelengths of 355, 532, and 1064 nm. Very different particle depolarization ratios were found in the troposphere and in the stratosphere. The obviously compact and spherical tropospheric smoke particles caused almost no depolarization of backscattered laser radiation at all three wavelengths ( < 3 %), whereas the dry irregularly shaped soot particles in the stratosphere lead to high depolarization ratios of 22% at 355 nm and 18% at 532 nm and a comparably low value of 4% at 1064 nm. The lidar ratios were 40- 45 sr (355 nm), 65-80 sr (532 nm), and 80-95 sr (1064 nm) in both the tropospheric and stratospheric smoke layers indicating similar scattering and absorption properties. The strong wavelength dependence of the stratospheric depolarization ratio was probably caused by the absence of a particle coarse mode (particle mode consisting of particles with radius > 500nm). The stratospheric smoke particles formed a pronounced accumulation mode (in terms of particle volume or mass) centered at a particle radius of 350-400 nm. The effective particle radius was 0.32 μm. The tropospheric smoke particles were much smaller (effective radius of 0.17 μm). Mass concentrations were of the order of 5.5 μgm-3 (tropospheric layer) and 40 μgm-3 (stratospheric layer) in the night of 22 August 2017. The single scattering albedo of the stratospheric particles was estimated to be 0.74, 0.8, and 0.83 at 355, 532, and 1064 nm, respectively.
Scientific assessments to facilitate deliberative policy learning
2016, Kowarsch, Martin, Garard, Jennifer, Riousset, Pauline, Lenzi, Dominic, Dorsch, Marcel J., Knopf, Brigitte, Harrs, Jan-Albrecht, Edenhofer, Ottmar
Putting the recently adopted global Sustainable Development Goals or the Paris Agreement on international climate policy into action will require careful policy choices. Appropriately informing decision-makers about longer-term, wicked policy issues remains a considerable challenge for the scientific community. Typically, these vital policy issues are highly uncertain, value-laden and disputed, and affect multiple temporal and spatial scales, governance levels, policy fields, and socioeconomic contexts simultaneously. In light of this, science-policy interfaces should help facilitate learning processes and open deliberation among all actors involved about potentially acceptable policy pathways. For this purpose, science-policy interfaces must strive to foster some enabling conditions: (1) “representation” in terms of engaging with diverse stakeholders (including experts) and acknowledging divergent viewpoints; (2) “empowerment” of underrepresented societal groups by co-developing and integrating policy scenarios that reflect their specific knowledge systems and worldviews; (3) “capacity building” regarding methods and skills for integration and synthesis, as well as through the provision of knowledge synthesis about the policy solution space; and (4) “spaces for deliberation”, facilitating direct interaction between different stakeholders, including governments and scientists. We argue that integrated, multi-stakeholder, scientific assessment processes—particularly the collaborative assessments of policy alternatives and their various implications—offer potential advantages in this regard, compared with alternatives for bridging scientific expertise and public policy. This article is part of a collection on scientific advice to governments.
Archetype analysis in sustainability research: Methodological portfolio and analytical frontiers
2019, Sietz, D., Frey, U., Roggero, M., Gong, Y., Magliocca, N., Tan, R., Janssen, P., Václavík, T.
In sustainability research, archetype analysis reveals patterns of factors and processes that repeatedly shape social-ecological systems. These patterns help improve our understanding of global concerns, including vulnerability, land management, food security, and governance. During the last decade, the portfolio of methods used to investigate archetypes has been growing rapidly. However, these methods differ widely in their epistemological and normative underpinnings, data requirements, and suitability to address particular research purposes. Therefore, guidance is needed for systematically choosing methods in archetype analysis. We synthesize strengths and weaknesses of key methods used to identify archetypes. Demonstrating that there is no “one-size-fits-all” approach, we discuss advantages and shortcomings of a range of methods for archetype analysis in sustainability research along gradients that capture the treatment of causality, normativity, spatial variations, and temporal dynamics. Based on this discussion, we highlight seven analytical frontiers that bear particular potential for tackling methodological limitations. As a milestone in archetype analysis, our synthesis supports researchers in reflecting on methodological implications, including opportunities and limitations related to causality, normativity, space, and time considerations in view of specific purposes and research questions. This enables innovative research designs in future archetype analysis, thereby contributing to the advancement of sustainability research and decision-making.
Wildfires as a source of airborne mineral dust - Revisiting a conceptual model using large-eddy simulation (LES)
2018, Wagner, R., Jähn, M., Schepanski, K.
Airborne mineral dust is a key player in the Earth system and shows manifold impacts on atmospheric properties such as the radiation budget and cloud microphysics. Investigations of smoke plumes originating from wildfires found significant fractions of mineral dust within these plumes - most likely raised by strong, turbulent fire-related winds. This study presents and revisits a conceptual model describing the emission of mineral dust particles during wildfires. This is achieved by means of high-resolution large-eddy simulation (LES), conducted with the All Scale Atmospheric Model (ASAM). The impact of (a) different fire properties representing idealized grassland and shrubland fires, (b) different ambient wind conditions modulated by the fire's energy flux, and (c) the wind's capability to mobilize mineral dust particles was investigated. Results from this study illustrate that the energy release of the fire leads to a significant increase in near-surface wind speed, which consequently enhances the dust uplift potential. This is in particular the case within the fire area where vegetation can be assumed to be widely removed and uncovered soil is prone to wind erosion. The dust uplift potential is very sensitive to fire properties, such as fire size, shape, and intensity, but also depends on the ambient wind velocity. Although measurements already showed the importance of wildfires for dust emissions, pyro-convection is so far neglected as a dust emission process in atmosphere-aerosol models. The results presented in this study can be seen as the first step towards a systematic parameterization representing the connection between typical fire properties and related dust emissions.
Broad consent under the GDPR : an optimistic perspective on a bright future
2020, Hallinan, Dara
Broad consent-the act of gaining one consent for multiple potential future research projects-sits at the core of much current genomic research practice. Since the 25th May 2018, the General Data Protection Regulation (GDPR) has applied as valid law concerning genomic research in the EU and now occupies a dominant position in the legal landscape. Yet, the position of the GDPR concerning broad consent has recently been cause for concern in the genomic research community. Whilst the text of the GDPR apparently supports the practice, recent jurisprudence contains language which is decidedly less positive. This article takes an in-depth look at the situation concerning broad consent under the GDPR and-despite the understandable concern flowing from recent jurisprudence-offers a positive outlook. This positive outlook is argued from three perspectives, each of which is significant in defining the current, and ongoing, legitimacy and utility of broad consent under the GDPR: The principled, the legal technical, and the practical. © 2020 The Author(s).
Topology of products similarity network for market forecasting
2019, Fan, Jingfang, Cohen, Keren, Shekhtman, Louis M., Liu, Sibo, Meng, Jun, Louzoun, Yoram, Havlin, Shlomo
The detection and prediction of risk in financial markets is one of the main challenges of economic forecasting, and draws much attention from the scientific community. An even more challenging task is the prediction of the future relative gain of companies. We here develop a novel combination of product text analysis, network theory and topological based machine learning to study the future performance of companies in financial markets. Our network links are based on the similarity of firms’ products and constructed using the Securities Exchange Commission (SEC) filings of US listed firms. We find that several topological features of this network can serve as good precursors of risks or future gain of companies. We then apply machine learning to network attributes vectors for each node to predict successful and failing firms. The resulting accuracies are much better than current state of the art techniques. The framework presented here not only facilitates the prediction of financial markets but also provides insight and demonstrates the power of combining network theory and topology based machine learning.
Ship-borne aerosol profiling with lidar over the Atlantic Ocean: From pure marine conditions to complex dust-smoke mixtures
2018, Bohlmann, S., Baars, H., Radenz, M., Engelmann, R., Macke, A.
The multi-wavelength Raman lidar PollyXT has been regularly operated aboard the research vessel Polarstern on expeditions across the Atlantic Ocean from north to south and vice versa. The lidar measurements of the RV Polarstern cruises PS95 from Bremerhaven, Germany, to Cape Town, Republic of South Africa (November 2015), and PS98 from Punta Arenas, Chile, to Bremerhaven, Germany (April/May 2016), are presented and analysed in detail. The latest set-up of PollyXT allows improved coverage of the marine boundary layer (MBL) due to an additional near-range receiver. Three case studies provide an overview of the aerosol detected over the Atlantic Ocean. In the first case, marine conditions were observed near South Africa on the autumn cruise PS95. Values of optical properties (depolarisation ratios close to zero, lidar ratios of 23 sr at 355 and 532 nm) within the MBL indicate pure marine aerosol. A layer of dried marine aerosol, indicated by an increase of the particle depolarisation ratio to about 10% at 355 nm (9% at 532 nm) and thus confirming the non-sphericity of these particles, could be detected on top of the MBL. On the same cruise, an almost pure Saharan dust plume was observed near the Canary Islands, presented in the second case. The third case deals with several layers of Saharan dust partly mixed with biomass-burning smoke measured on PS98 near the Cabo Verde islands. While the MBL was partly mixed with dust in the pure Saharan dust case, an almost marine MBL was observed in the third case. A statistical analysis showed latitudinal differences in the optical properties within the MBL, caused by the downmixing of dust in the tropics and anthropogenic influences in the northern latitudes, whereas the optical properties of the MBL in the Southern Hemisphere correlate with typical marine values. The particle depolarisation ratio of dried marine layers ranged between 4 and 9% at 532 nm. Night measurements from PS95 and PS98 were used to illustrate the potential of aerosol classification using lidar ratio, particle depolarisation ratio at 355 and 532 nm, and Angström exponent. Lidar ratio and particle depolarisation ratio have been found to be the main indicator for particle type, whereas the Ångström exponent is rather variable.
Sustainable Development Goals (SDGs): Are we successful in turning trade-offs into synergies?
2019, Kroll, Christian, Warchold, Anne, Pradhan, Prajal
The Agenda 2030 with its 17 Sustainable Development Goals (SDGs) provides the framework that all United Nations (UN) member states have pledged to fulfill. The achievement of this agenda crucially depends on whether humankind will be able to maximize synergies and resolve existing trade-offs between the SDGs. We provide the first analysis of future interactions for projected SDG trends until 2030 within and between goals, and we analyze how trade-offs and synergies have evolved in the recent past globally. For certain goals, we find positive developments with notable synergies in our projections, especially for SDGs 1, 3, 7, 8, and 9: Poverty alleviation and strengthening the economy, rooted in innovation, and modern infrastructure, therefore continue to be the basis upon which many of the other SDGs can be achieved. However, especially SDGs 11, 13, 14, 16, and 17 will continue to have notable trade-offs, as well as non-associations with the other goals in the future, which emphasizes the need to foster innovations and policies that can make our cities and communities more sustainable, as well as strengthen institutions and spur climate action. We show examples of a successful transformation of trade-offs into synergies that should be emulated in other areas to create a virtuous cycle of SDG progress. The alarming inability to overcome certain persistent trade-offs we have found, and indeed the deterioration for some SDGs, can seriously threaten the achievement of the Agenda 2030.
Extending Near-Term Emissions Scenarios to Assess Warming Implications of Paris Agreement NDCs
2018, Gütschow, J., Jeffery, M.L., Schaeffer, M., Hare, B.
In the Paris Agreement countries have agreed to act together to hold global warming well below 2°C over preindustrial levels and to pursue efforts to limit warming to 1.5°C. To assess if the world is on track to meet this long-term temperature goal, countries' pledged emissions reductions (Nationally Determined Contributions, NDCs) need to be analyzed for their implied warming. Several research groups and nongovernmental organizations have estimated this warming and arrived at very different results but have invariably concluded that the current pledges are inadequate to hold warming below 2°C, let alone 1.5°C. In this paper we analyze different methods to estimate 2100 global mean temperature rise implied by countries' NDCs, which often only specify commitments until 2030. We present different methods to extend near-term emissions pathways that have been developed by the authors or used by different research groups and nongovernmental organizations to estimate 21st century warming consequences of Paris Agreement commitments. The abilities of these methods to project both low and high warming scenarios in line with the scenario literature is assessed. We find that the simpler methods are not suitable for temperature projections while more complex methods can produce results consistent with the energy and economic scenario literature. We further find that some methods can have a strong high or low temperature bias depending on parameter choices. The choice of methods to evaluate the consistency of aggregated NDC commitments is very important for reviewing progress toward the Paris Agreement's long-term temperature goal.
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