11 research outputs found
Disentangling different types of El Ni\~no episodes by evolving climate network analysis
Complex network theory provides a powerful toolbox for studying the structure
of statistical interrelationships between multiple time series in various
scientific disciplines. In this work, we apply the recently proposed climate
network approach for characterizing the evolving correlation structure of the
Earth's climate system based on reanalysis data of surface air temperatures. We
provide a detailed study on the temporal variability of several global climate
network characteristics. Based on a simple conceptual view on red climate
networks (i.e., networks with a comparably low number of edges), we give a
thorough interpretation of our evolving climate network characteristics, which
allows a functional discrimination between recently recognized different types
of El Ni\~no episodes. Our analysis provides deep insights into the Earth's
climate system, particularly its global response to strong volcanic eruptions
and large-scale impacts of different phases of the El Ni\~no Southern
Oscillation (ENSO).Comment: 20 pages, 12 figure
The effect of industry delocalization on global energy use: A global sectoral perspective
Sectoral production technologies differ largely across countries, so do sectoral energy intensities. Hence, shifts in production locations within global sectors, possibly caused by environmental regulations, are likely to have an impact on aggregated energy usage and emissions. Applying a Logarithmic Mean Divisia Index decomposition we decompose changes of sectoral energy use from 2001–2011 into three effects: (sectoral) value added, energy efficiency and delocalization, which in this paper is conceived as a structural effect within sectors, between regions. Our results show that although economic activity and technological progress dominate global energy use developments, for most sectors a delocalization towards less efficient production places is ongoing. It contributes to annual increases in energy use in the range of 1–6%. Especially, manufacturing sectors, which are among the most energy consuming sectors, reveal significant increases in energy usage due to delocalization since 2004. This development is accompanied by declining energy intensity improvement rates, indicating that delocalization induces second order effects.BMBF, 01LS1610B, Klimapolitische Maßnahmen und Transformationspfade zur Begrenzung der globalen Erwärmung auf 1.5°C (PEP1p5)DFG, SFB 1026, Sustainable Manufacturing - Globale Wertschöpfung nachhaltig gestalte
Reducing global CO2 emissions with the technologies we have
The energy intensities of the various industrial sectors differ considerably across countries. This suggests a potential for emissions reductions through improved accessibility to efficient technologies. This paper estimates an upper-bound CO2 emission mitigation potential that could theoretically be achieved by improved access to efficient technologies in industrial sectors. We develop a linear optimization framework that facilitates the exchange of sectoral production technologies based on the World Input-Output Database (WIOD), assuming perfect substitutability of technologies and homogeneity within economic sectors, while ignoring barriers to technological adoption and price driven adjustments. We consider the full global supply chain network and multiple upstream production inputs in addition to energy demand. In contrast to existing literature our framework allows to consider supply chain effects of technology replacements. We use our model to calculate emission reduction potentials for varying levels of access to technology. If best practice technologies were made available globally, CO2 emissions could theoretically be reduced by more than 10 gigatons (Gt). In fact, even second-tier production technologies would create significant global reduction potentials. We decompose sectoral emission reductions to identify contributions by changes in energy intensity, supply chain effects and changes in carbon intensities. Excluding the latter, we find that considering supply chain effects increases total mitigation potentials by 14%. The largest CO2 emission reduction potentials are found for a small set of developing countries.DFG, SFB 1026, Sustainable Manufacturing - Globale Wertschöpfung nachhaltig gestalte
Assessing carbon dioxide emission reduction potentials of improved manufacturing processes using multiregional input output frameworks
Evaluating innovative process technologies has become highly important within the last decades. As standard tools different Life Cycle Assessment methods have been established, which are continuously improved. While those are designed for evaluating single processes they run into difficulties when it comes to assessing environmental impacts of process innovations at macroeconomic level. In this paper we develop a multi-step evaluation framework building on multi regional input–output data that allows estimating macroeconomic impacts of new process technologies, considering the network characteristics of the global economy.
Our procedure is as follows: i) we measure differences in material usage of process alternatives, ii) we identify where the standard processes are located within economic networks and virtually replace those by innovative process technologies, iii) we account for changes within economic systems and evaluate impacts on emissions.
Within this paper we exemplarily apply the methodology to two recently developed innovative technologies: longitudinal large diameter steel pipe welding and turning of high-temperature resistant materials. While we find the macroeconomic impacts of very specific process innovations to be small, its conclusions can significantly differ from traditional process based approaches. Furthermore, information gained from the methodology provides relevant additional insights for decision makers extending the picture gained from traditional process life cycle assessment.DFG, SFB 1026, Sustainable Manufacturing - Globale Wertschöpfung nachhaltig gestalte
A climate network-based index to discriminate different types of El Niño and La Niña
Funded by German Federal Ministry for Education and Research via the BMBF Young Investigators Group CoSy-CC2. Grant Number: 01LN1306A Planetary Boundary Research Network (PB.net) Earth League's EarthDoc DFG FAPESP Acknowledgments M.W. and R.V.D. have been supported by the German Federal Ministry for Education and Research via the BMBF Young Investigators Group CoSy-CC2 (grant 01LN1306A). J.F.D. thanks the Stordalen Foundation via the Planetary Boundary Research Network (PB.net) and the Earth League's EarthDoc program for financial support. J.K. acknowledges the IRTG 1740 funded by DFG and FAPESP. NCEP Reanalysis data are provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website http://www.esrl.noaa.gov/psd/. Parts of the analysis have been performed using the Python package pyunicorn [Donges et al., 2015b] available at https://github.com/pik-copan/pyunicorn.Peer reviewedPublisher PD
Recommended from our members
Assessing human and environmental pressures of global land-use change 2000-2010
Global land is turning into an increasingly scarce resource. We here present a comprehensive assessment of co-occuring land-use change from 2000 until 2010, compiling existing spatially explicit data sources for different land uses, and building on a rich literature addressing specific land-use changes in all world regions. This review systematically categorizes patterns of land use, including regional urbanization and agricultural expansion but also globally telecoupled land-use change for all world regions. Managing land-use change patterns across the globe requires global governance. Here we present a comprehensive assessment of the extent and density of multiple drivers and impacts of land-use change. We combine and reanalyze spatially explicit data of global land-use change between 2000 and 2010 for population, livestock, cropland, terrestrial carbon and biodiversity. We find pervasive pressure on biodiversity but varying patterns of gross land-use changes across world regions. Our findings enable a classification of land-use patterns into three types. The 'consumers' type, displayed in Europe and North America, features high land footprints, reduced direct human pressures due to intensification of agriculture, and increased reliance on imports, enabling a partial recovery of terrestrial carbon and reducing pressure on biodiversity. In the 'producer' type, most clearly epitomized by Latin America, telecoupled land-use links drive biodiversity and carbon loss. In the 'mover' type, we find strong direct domestic pressures, but with a wide variety of outcomes, ranging from a concurrent expansion of population, livestock and croplands in Sub-Saharan Africa at the cost of natural habitats to strong pressure on cropland by urbanization in Eastern Asia. In addition, anthropogenic climate change has already left a distinct footprint on global land-use change. Our data- and literature-based assessment reveals region-specific opportunities for managing global land-use change. © 2019 The Author(s)
Validation practices for satellite based earth observation data across communities
Assessing the inherent uncertainties in satellite data products is a challenging task. Different technical approaches have been developed in the Earth Observation (EO) communities to address the validation problem which results in a large variety of methods as well as terminology. This paper reviews state-of-the-art methods of satellite validation and documents their similarities and differences. First the overall validation objectives and terminologies are specified, followed by a generic mathematical formulation of the validation problem. Metrics currently used as well as more advanced EO validation approaches are introduced thereafter. An outlook on the applicability and requirements of current EO validation approaches and targets is given