Search Results
Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic
2020, Liu, Zhu, Ciais, Philippe, Deng, Zhu, Lei, Ruixue, Davis, Steven J., Feng, Sha, Zheng, Bo, Cui, Duo, Dou, Xinyu, Zhu, Biqing, Guo, Rui, Ke, Piyu, Sun, Taochun, Lu, Chenxi, He, Pan, Wang, Yuan, Yue, Xu, Wang, Yilong, Lei, Yadong, Zhou, Hao, Cai, Zhaonan, Wu, Yuhui, Guo, Runtao, Han, Tingxuan, Xue, Jinjun, Boucher, Olivier, Boucher, Eulalie, Chevallier, Frédéric, Tanaka, Katsumasa, Wei, Yiming, Zhong, Haiwang, Kang, Chongqing, Zhang, Ning, Chen, Bin, Xi, Fengming, Liu, Miaomiao, Bréon, François-Marie, Lu, Yonglong, Zhang, Qiang, Guan, Dabo, Gong, Peng, Kammen, Daniel M., He, Kebin, Schellnhuber, Hans Joachim
The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (−1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially.
Key determinants of global land-use projections
2019, Stehfest, Elke, van Zeist, Willem-Jan, Valin, Hugo, Havlik, Petr, Popp, Alexander, Kyle, Page, Tabeau, Andrzej, Mason-D’Croz, Daniel, Hasegawa, Tomoko, Bodirsky, Benjamin L., Calvin, Katherine, Doelman, Jonathan C., Fujimori, Shinichiro, Humpenöder, Florian, Lotze-Campen, Hermann, van Meijl, Hans, Wiebe, Keith
Land use is at the core of various sustainable development goals. Long-term climate foresight studies have structured their recent analyses around five socio-economic pathways (SSPs), with consistent storylines of future macroeconomic and societal developments; however, model quantification of these scenarios shows substantial heterogeneity in land-use projections. Here we build on a recently developed sensitivity approach to identify how future land use depends on six distinct socio-economic drivers (population, wealth, consumption preferences, agricultural productivity, land-use regulation, and trade) and their interactions. Spread across models arises mostly from diverging sensitivities to long-term drivers and from various representations of land-use regulation and trade, calling for reconciliation efforts and more empirical research. Most influential determinants for future cropland and pasture extent are population and agricultural efficiency. Furthermore, land-use regulation and consumption changes can play a key role in reducing both land use and food-security risks, and need to be central elements in sustainable development strategies.
A network-based microfoundation of Granovetter’s threshold model for social tipping
2020, Wiedermann, Marc, Smith, E. Keith, Heitzig, Jobst, Donges, Jonathan F.
Social tipping, where minorities trigger larger populations to engage in collective action, has been suggested as one key aspect in addressing contemporary global challenges. Here, we refine Granovetter’s widely acknowledged theoretical threshold model of collective behavior as a numerical modelling tool for understanding social tipping processes and resolve issues that so far have hindered such applications. Based on real-world observations and social movement theory, we group the population into certain or potential actors, such that – in contrast to its original formulation – the model predicts non-trivial final shares of acting individuals. Then, we use a network cascade model to explain and analytically derive that previously hypothesized broad threshold distributions emerge if individuals become active via social interaction. Thus, through intuitive parameters and low dimensionality our refined model is adaptable to explain the likelihood of engaging in collective behavior where social-tipping-like processes emerge as saddle-node bifurcations and hysteresis. © 2020, The Author(s).
State-of-the-art global models underestimate impacts from climate extremes
2019, Schewe, Jacob, Gosling, Simon N., Reyer, Christopher, Zhao, Fang, Ciais, Philippe, Elliott, Joshua, Francois, Louis, Huber, Veronika, Lotze, Heike K., Seneviratne, Sonia I., van Vliet, Michelle T. H., Vautard, Robert, Wada, Yoshihide, Breuer, Lutz, Büchner, Matthias, Carozza, David A., Chang, Jinfeng, Coll, Marta, Deryng, Delphine, de Wit, Allard, Eddy, Tyler D., Folberth, Christian, Frieler, Katja, Friend, Andrew D., Gerten, Dieter, Gudmundsson, Lukas, Hanasaki, Naota, Ito, Akihiko, Khabarov, Nikolay, Kim, Hyungjun, Lawrence, Peter, Morfopoulos, Catherine, Müller, Christoph, Müller Schmied, Hannes, Orth, René, Ostberg, Sebastian, Pokhrel, Yadu, Pugh, Thomas A. M., Sakurai, Gen, Satoh, Yusuke, Schmid, Erwin, Stacke, Tobias, Steenbeek, Jeroen, Steinkamp, Jörg, Tang, Qiuhong, Tian, Hanqin, Tittensor, Derek P., Volkholz, Jan, Wang, Xuhui, Warszawski, Lila
Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.
ColiCoords: A Python package for the analysis of bacterial fluorescence microscopy data
2019, Smit, Jochem H., Li, Yichen, Warszawik, Eliza M., Herrmann, Andreas, Cordes, Thorben, Gilestro, Giorgio F
Single-molecule fluorescence microscopy studies of bacteria provide unique insights into the mechanisms of cellular processes and protein machineries in ways that are unrivalled by any other technique. With the cost of microscopes dropping and the availability of fully automated microscopes, the volume of microscopy data produced has increased tremendously. These developments have moved the bottleneck of throughput from image acquisition and sample preparation to data analysis. Furthermore, requirements for analysis procedures have become more stringent given the demand of various journals to make data and analysis procedures available. To address these issues we have developed a new data analysis package for analysis of fluorescence microscopy data from rod-like cells. Our software ColiCoords structures microscopy data at the single-cell level and implements a coordinate system describing each cell. This allows for the transformation of Cartesian coordinates from transmission light and fluorescence images and single-molecule localization microscopy (SMLM) data to cellular coordinates. Using this transformation, many cells can be combined to increase the statistical power of fluorescence microscopy datasets of any kind. ColiCoords is open source, implemented in the programming language Python, and is extensively documented. This allows for modifications for specific needs or to inspect and publish data analysis procedures. By providing a format that allows for easy sharing of code and associated data, we intend to promote open and reproducible research. The source code and documentation can be found via the project’s GitHub page.
The ongoing nutrition transition thwarts long-term targets for food security, public health and environmental protection
2020, Bodirsky, Benjamin Leon, Dietrich, Jan Philipp, Martinelli, Eleonora, Stenstad, Antonia, Pradhan, Prajal, Gabrysch, Sabine, Mishra, Abhijeet, Weindl, Isabelle, Le Mouël, Chantal, Rolinski, Susanne, Baumstark, Lavinia, Wang, Xiaoxi, Waid, Jillian L., Lotze-Campen, Hermann, Popp, Alexander
The nutrition transition transforms food systems globally and shapes public health and environmental change. Here we provide a global forward-looking assessment of a continued nutrition transition and its interlinked symptoms in respect to food consumption. These symptoms range from underweight and unbalanced diets to obesity, food waste and environmental pressure. We find that by 2050, 45% (39–52%) of the world population will be overweight and 16% (13–20%) obese, compared to 29% and 9% in 2010 respectively. The prevalence of underweight approximately halves but absolute numbers stagnate at 0.4–0.7 billion. Aligned, dietary composition shifts towards animal-source foods and empty calories, while the consumption of vegetables, fruits and nuts increases insufficiently. Population growth, ageing, increasing body mass and more wasteful consumption patterns are jointly pushing global food demand from 30 to 45 (43–47) Exajoules. Our comprehensive open dataset and model provides the interfaces necessary for integrated studies of global health, food systems, and environmental change. Achieving zero hunger, healthy diets, and a food demand compatible with environmental boundaries necessitates a coordinated redirection of the nutrition transition. Reducing household waste, animal-source foods, and overweight could synergistically address multiple symptoms at once, while eliminating underweight would not substantially increase food demand.
Environmental co-benefits and adverse side-effects of alternative power sector decarbonization strategies
2019, Luderer, Gunnar, Pehl, Michaja, Arvesen, Anders, Gibon, Thomas, Bodirsky, Benjamin L., de Boer, Harmen Sytze, Fricko, Oliver, Hejazi, Mohamad, Humpenöder, Florian, Iyer, Gokul, Mima, Silvana, Mouratiadou, Ioanna, Pietzcker, Robert C., Popp, Alexander, van den Berg, Maarten, van Vuuren, Detlef, Hertwich, Edgar G.
A rapid and deep decarbonization of power supply worldwide is required to limit global warming to well below 2 °C. Beyond greenhouse gas emissions, the power sector is also responsible for numerous other environmental impacts. Here we combine scenarios from integrated assessment models with a forward-looking life-cycle assessment to explore how alternative technology choices in power sector decarbonization pathways compare in terms of non-climate environmental impacts at the system level. While all decarbonization pathways yield major environmental co-benefits, we find that the scale of co-benefits as well as profiles of adverse side-effects depend strongly on technology choice. Mitigation scenarios focusing on wind and solar power are more effective in reducing human health impacts compared to those with low renewable energy, while inducing a more pronounced shift away from fossil and toward mineral resource depletion. Conversely, non-climate ecosystem damages are highly uncertain but tend to increase, chiefly due to land requirements for bioenergy.
Farmer typology to understand differentiated climate change adaptation in Himalaya
2019, Shukla, Roopam, Agarwal, Ankit, Gornott, Christoph, Sachdeva, Kamna, Joshi, P.K.
Smallholder farmers’ responses to the climate-induced agricultural changes are not uniform but rather diverse, as response adaptation strategies are embedded in the heterogonous agronomic, social, economic, and institutional conditions. There is an urgent need to understand the diversity within the farming households, identify the main drivers and understand its relationship with household adaptation strategies. Typology construction provides an efficient method to understand farmer diversity by delineating groups with common characteristics. In the present study, based in the Uttarakhand state of Indian Western Himalayas, five farmer types were identified on the basis of resource endowment and agriculture orientation characteristics. Factor analysis followed by sequential agglomerative hierarchial and K-means clustering was use to delineate farmer types. Examination of adaptation strategies across the identified farmer types revealed that mostly contrasting and type-specific bundle of strategies are adopted by farmers to ensure livelihood security. Our findings show that strategies that incurred high investment, such as infrastructural development, are limited to high resource-endowed farmers. In contrast, the low resourced farmers reported being progressively disengaging with farming as a livelihood option. Our results suggest that the proponents of effective adaptation policies in the Himalayan region need to be cognizant of the nuances within the farming communities to capture the diverse and multiple adaptation needs and constraints of the farming households. © 2019, The Author(s).