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Anthropogenic Land Use Change and Adoption of Climate Smart Agriculture in Sub-Saharan Africa
(Basel : MDPI, 2022) Tione, Sarah Ephrida; Nampanzira, Dorothy; Nalule, Gloria; Kashongwe, Olivier; Katengeza, Samson Pilanazo
Compelling evidence in Sub-Saharan Africa (SSA) shows that Climate-Smart Agriculture (CSA) has a positive impact on agricultural productivity. However, the uptake of CSA remains low, which is related to anthropogenic, or human-related, decisions about CSA and agricultural land use. This paper assesses households’ decisions to allocate agricultural land to CSA technologies across space and over time. We use the state-contingent theory, mixed methods, and mixed data sources. While agricultural land is increasing, forest land is decreasing across countries in SSA. The results show that household decisions to use CSA and the extent of agricultural land allocation to CSA remain low with a negative trend over time in SSA. Owned land and accessing land through rental markets are positively associated with allocating land to CSA technologies, particularly where land pressure is high. Regarding adaptation, experiencing rainfall shocks is significantly associated with anthropogenic land allocation to CSA technologies. The country policy assessment further supports the need to scale up CSA practices for adaptation, food security, and mitigation. Therefore, scaling up CSA in SSA will require that agriculture-related policies promote land tenure security and land markets while promoting climate-smart farming for food security, adaptation, and mitigation.
A Pixel-wise Segmentation Model to Identify Bur Chervil (Anthriscus caucalis M. Bieb.) Within Images from a Cereal Cropping Field
(Berlin ; Heidelberg : Springer, 2022) Karimi, Hadi; Navid, Hossein; Dammer, Karl-Heinz
Because of insufficient effectiveness after herbicide application in autumn, bur chervil (Anthriscus caucalis M. Bieb.) is often present in cereal fields in spring. A second reason for spreading is the warm winter in Europe due to climate change. This weed continues to germinate from autumn to spring. To prevent further spreading, a site-specific control in spring is reasonable. Color imagery would offer cheap and complete monitoring of entire fields. In this study, an end-to-end fully convolutional network approach is presented to detect bur chervil within color images. The dataset consisted of images taken at three sampling dates in spring 2018 in winter wheat and at one date in 2019 in winter rye from the same field. Pixels representing bur chervil were manually annotated in all images. After a random image augmentation was done, a Unet-based convolutional neural network model was trained using 560 (80%) of the sub-images from 2018 (training images). The power of the trained model at the three different sampling dates in 2018 was evaluated at 141 (20%) of the manually annotated sub-images from 2018 and all (100%) sub-images from 2019 (test images). Comparing the estimated and the manually annotated weed plants in the test images the Intersection over Union (Jaccard index) showed mean values in the range of 0.9628 to 0.9909 for the three sampling dates in 2018, and a value of 0.9292 for the one date in 2019. The Dice coefficients yielded mean values in the range of 0.9801 to 0.9954 for 2018 and a value of 0.9605 in 2019.
Biodiversity research: Data without theory-theory without data
(Lausanne : Frontiers Media, 2015) Rillig, Matthias C.; Kiessling, Wolfgang; Borsch, Thomas; Gessler, Arthur; Greenwood, Alex D.; Hofer, Heribert; Joshi, Jasmin; Schröder, Boris; Thonicke, Kirsten; Tockner, Klement; Weisshuhn, Karoline; Jeltsch, Florian
[No abstract available]
Consistency in Vulnerability Assessments of Wheat to Climate Change—A District-Level Analysis in India
(Basel : MDPI, 2020) Dhamija, Vanshika; Shukla, Roopam; Gornott, Christoph; Joshi, PK
In India, a reduction in wheat crop yield would lead to a widespread impact on food security. In particular, the most vulnerable people are severely exposed to food insecurity. This study estimates the climate change vulnerability of wheat crops with respect to heterogeneities in time, space, and weighting methods. The study uses the Intergovernmental Panel on Climate Change (IPCC) framework of vulnerability while using composite indices of 27 indicators to explain exposure, sensitivity, and adaptive capacity. We used climate projections under current (1975–2005) conditions and two future (2021–2050) Representation Concentration Pathways (RCPs), 4.5 and 8.5, to estimate exposure to climatic risks. Consistency across three weighting methods (Analytical Hierarchy Process (AHP), Principal Component Analysis (PCA), and Equal Weights (EWs)) was evaluated. Results of the vulnerability profile suggest high vulnerability of the wheat crop in northern and central India. In particular, the districts Unnao, Sirsa, Hardoi, and Bathinda show high vulnerability and high consistency across current and future climate scenarios. In total, 84% of the districts show more than 75% consistency in the current climate, and 83% and 68% of the districts show more than 75% consistency for RCP 4.5 and RCP 8.5 climate scenario for the three weighting methods, respectively. By using different weighting methods, it was possible to quantify “method uncertainty” in vulnerability assessment and enhance robustness in identifying most vulnerable regions. Finally, we emphasize the importance of communicating uncertainties, both in data and methods in vulnerability research, to effectively guide adaptation planning. The results of this study would serve as the basis for designing climate impacts adjusted adaptation measures for policy interventions.
Cylindrospermopsin is effectively degraded in water by pulsed corona-like and dielectric barrier discharges
(Amsterdam [u.a.] : Elsevier Science, 2020) Schneider, Marcel; Rataj, Raphael; Kolb, Juergen F.; Bláha, Luděk
Cylindrospermopsin (CYN) is an important cyanobacterial toxin posing a major threat to surface waters during cyanobacterial blooms. Hence, methods for cyanotoxin removal are required to confront seasonal or local incidences to sustain the safety of potable water reservoirs. Non-thermal plasmas provide the possibility for an environmentally benign treatment which can be adapted to specific concentrations and environmental conditions without the need of additional chemicals. We therefore investigated the potential of two different non-thermal plasma approaches for CYN degradation, operated either in a water mist, i.e. in air, or submerged in water. A degradation efficacy of 0.03 ± 0.00 g kWh−1 L−1 was found for a dielectric barrier discharge (DBD) operated in air, while a submerged pulsed corona-like discharge resulted in an efficacy of 0.24 ± 0.02 g kWh−1 L−1. CYN degradation followed a pseudo zeroth order or pseudo first order reaction kinetic, respectively. Treatment efficacy of the corona-like discharge submerged in water increased with pH values of the initial solution changing from 5.0 to 7.5. Notably, a pH-depending residual oxidative effect was observed for the submerged discharge, resulting in ongoing CYN degradation, even without further plasma treatment. In this case hydroxyl radicals were identified as the dominant oxidants of CYN at acidic pH values. In comparison, degradation by the DBD could be related primarily to the generation of ozone. © 2020 The AuthorsThe degradation of cylindrospermopsin by a pulsed corona-like discharge in water was more effective compared with a pulsed dielectric barrier discharge in air around a water mist. © 2020 The Authors
Declining glaciers endanger sustainable development of the oases along the Aksu-Tarim River (Central Asia)
(London : Taylor & Francis, 2021) Bolch, Tobias; Duethmann, Doris; Wortmann, Michel; Liu, Shiyin; Disse, Markus
Tarim River basin is the largest endorheic river basin in China. Due to the extremely arid climate the water supply solely depends on water originating from the glacierised mountains with about 75% stemming from the transboundary Aksu River. The water demand is linked to anthropogenic (specifically agriculture) and natural ecosystems, both competing for water. Ongoing climate change significantly impacts the cryosphere. The mass balance of the glaciers in Aksu River basin was clearly negative since 1975. The discharge of the Aksu headwaters has been increasing over the last decades mainly due to the glacier contribution. The average glacier melt contribution to total runoff is 30–37% with an estimated glacier imbalance contribution of 8–16%. Modelling using future climate scenarios indicate a glacier area loss of at least 50% until 2100. River discharge will first increase concomitant with glacier shrinkage until about 2050, but likely decline thereafter. The irrigated area doubled in the Aksu region between the early 1990s and 2020, causing at least a doubling of water demand. The current water surplus is comparable to the glacial runoff. Hence, even if the water demand will not grow further in the future a significant water shortage can be expected with declining glacial runoff. However, with the further expansion of irrigated agriculture and related industries, the water demand is expected to even further increase. Both improved discharge projections and planning of efficient and sustainable water use are necessary for further socioeconomic development in the region along with the preservation of natural ecosystems.
Deep Learning Object Detection for Image Analysis of Cherry Fruit Fly (Rhagoletis cerasi L.) on Yellow Sticky Traps
(Berlin ; Heidelberg : Springer, 2022) Salamut, Christian; Kohnert, Iris; Landwehr, Niels; Pflanz, Michael; Schirrmann, Michael; Zare, Mohammad
Insect populations appear with a high spatial, temporal and type-specific diversity in orchards. One of the many monitoring tools for pest management is the manual assessment of sticky traps. However, this type of assessment is laborious and time-consuming so that only a few locations can be controlled in an orchard. The aim of this study is to test state-of-the art object detection algorithms from deep learning to automatically detect cherry fruit flies (Rhagoletis cerasi), a common insect pest in cherry plantations, within images from yellow sticky traps. An image annotation database was built with images taken from yellow sticky traps with more than 1600 annotated cherry fruit flies. For better handling in the computational algorithms, the images were augmented to smaller ones by the known image preparation methods “flipping” and “cropping” before performing the deep learning. Five deep learning image recognition models were tested including Faster Region-based Convolutional Neural Network (R-CNN) with two different methods of pretraining, Single Shot Detector (SSD), RetinaNet, and You Only Look Once version 5 (YOLOv5). R‑CNN and RetinaNet models outperformed other ones with a detection average precision of 0.9. The results indicate that deep learning can act as an integral component of an automated system for high-throughput assessment of pest insects in orchards. Therefore, this can reduce the time for repetitive and laborious trap assessment but also increase the observed amount of sticky traps
Diverging importance of drought stress for maize and winter wheat in Europe
([London] : Nature Publishing Group UK, 2018) Webber, Heidi; Ewert, Frank; Olesen, Jørgen E.; Müller, Christoph; Fronzek, Stefan; Ruane, Alex C.; Bourgault, Maryse; Martre, Pierre; Ababaei, Behnam; Bindi, Marco; Ferrise, Roberto; Finger, Robert; Fodor, Nándor; Gabaldón-Leal, Clara; Gaiser, Thomas; Jabloun, Mohamed; Kersebaum, Kurt-Christian; Lizaso, Jon I.; Lorite, Ignacio J.; Manceau, Loic; Moriondo, Marco; Nendel, Claas; Rodríguez, Alfredo; Ruiz-Ramos, Margarita; Semenov, Mikhail A.; Siebert, Stefan; Stella, Tommaso; Stratonovitch, Pierre; Trombi, Giacomo; Wallach, Daniel
Understanding the drivers of yield levels under climate change is required to support adaptation planning and respond to changing production risks. This study uses an ensemble of crop models applied on a spatial grid to quantify the contributions of various climatic drivers to past yield variability in grain maize and winter wheat of European cropping systems (1984–2009) and drivers of climate change impacts to 2050. Results reveal that for the current genotypes and mix of irrigated and rainfed production, climate change would lead to yield losses for grain maize and gains for winter wheat. Across Europe, on average heat stress does not increase for either crop in rainfed systems, while drought stress intensifies for maize only. In low-yielding years, drought stress persists as the main driver of losses for both crops, with elevated CO2 offering no yield benefit in these years.
Energy, land-use and greenhouse gas emissions trajectories under a green growth paradigm
(Amsterdam : Elsevier, 2016) van Vuuren, Detlef P.; Stehfest, Elke; Gernaat, David E.H.J.; Doelman, Jonathan C.; van den Berg, Maarten; Harmsen, Mathijs; de Boer, Harmen Sytze; Bouwman, Lex F.; Daioglou, Vassilis; Edelenbosch, Oreane Y.; Girod, Bastien; Kram, Tom; Lassaletta, Luis; Lucas, Paul L.; van Meijl, Hans; Müller, Christoph; van Ruijven, Bas J.; van der Sluis, Sietske; Tabeau, Andrzej
This paper describes the possible developments in global energy use and production, land use, emissions and climate changes following the SSP1 storyline, a development consistent with the green growth (or sustainable development) paradigm (a more inclusive development respecting environmental boundaries). The results are based on the implementation using the IMAGE 3.0 integrated assessment model and are compared with a) other IMAGE implementations of the SSPs (SSP2 and SSP3) and b) the SSP1 implementation of other integrated assessment models. The results show that a combination of resource efficiency, preferences for sustainable production methods and investment in human development could lead to a strong transition towards a more renewable energy supply, less land use and lower anthropogenic greenhouse gas emissions in 2100 than in 2010, even in the absence of explicit climate policies. At the same time, climate policy would still be needed to reduce emissions further, in order to reduce the projected increase of global mean temperature from 3 °C (SSP1 reference scenario) to 2 or 1.5 °C (in line with current policy targets). The SSP1 storyline could be a basis for further discussions on how climate policy can be combined with achieving other societal goals.
Establishment of a Laboratory Scale Set-Up with Controlled Temperature and High Humidity to Investigate Dry Matter Losses of Wood Chips from Poplar during Storage
(Basel : MDPI, 2022) Hernandez-Estrada, Albert; Pecenka, Ralf; Dumfort, Sabrina; Ascher-Jenull, Judith; Lenz, Hannes; Idler, Christine; Hoffmann, Thomas
The aim of this work was to improve the understanding of dry matter losses (DML) that occur in wood chips during the initial phase of storage in outdoor piles. For this purpose, a laboratory scale storage chamber was developed and investigated regarding its ability to recreate the conditions that chips undergo during the initial phase of outdoor storage. Three trials with poplar Max-4 (Populus maximowiczii Henry Populus nigra L.) chips were performed for 6–10 weeks in the storage chamber under controlled temperature and assisted humidity. Two different setups were investigated to maintain a high relative humidity (RH) inside the storage chamber; one using water containers, and one assisted with a humidifier. Moisture content (MC) and DML of the chips were measured at different storage times to evaluate their storage behaviour in the chamber. Additionally, microbiological analyses of the culturable fraction of saproxylic microbiota were performed, with a focus on mesophilic fungi, but discriminating also xerophilic fungi, and mesophilic bacteria, with focus on actinobacteria, in two trials, to gain a view on the poplar wood chip-inhabiting microorganisms as a function of storage conditions (moisture, temperature) and time. Results show that DML up to 8.8–13.7% occurred in the chips within 6–10 storage weeks. The maximum DML were reached in the trial using the humidifier, which seemed a suitable technique to keep a high RH in the testing chamber, and thus, to analyse the wood chips in conditions comparable to those in outdoor piles during the initial storage phase.
Fossil-fueled development (SSP5): An energy and resource intensive scenario for the 21st century
(Amsterdam : Elsevier, 2016) Kriegler, Elmar; Bauer, Nico; Popp, Alexander; Humpenöder, Florian; Leimbach, Marian; Strefler, Jessica; Baumstark, Lavinia; Bodirsky, Benjamin Leon; Hilaire, Jérôme; Klein, David; Mouratiadou, Ioanna; Weindl, Isabelle; Bertram, Christoph; Dietrich, Jan-Philipp; Luderer, Gunnar; Pehl, Michaja; Pietzcker, Robert; Piontek, Franziska; Lotze-Campen, Hermann; Biewald, Anne; Bonsch, Markus; Giannousakis, Anastasis; Kreidenweis, Ulrich; Müller, Christoph; Rolinski, Susanne; Schultes, Anselm; Schwanitz, Jana; Stevanovic, Miodrag; Calvin, Katherine; Emmerling, Johannes; Fujimori, Shinichiro; Edenhofer, Ottmar
This paper presents a set of energy and resource intensive scenarios based on the concept of Shared Socio-Economic Pathways (SSPs). The scenario family is characterized by rapid and fossil-fueled development with high socio-economic challenges to mitigation and low socio-economic challenges to adaptation (SSP5). A special focus is placed on the SSP5 marker scenario developed by the REMIND-MAgPIE integrated assessment modeling framework. The SSP5 baseline scenarios exhibit very high levels of fossil fuel use, up to a doubling of global food demand, and up to a tripling of energy demand and greenhouse gas emissions over the course of the century, marking the upper end of the scenario literature in several dimensions. These scenarios are currently the only SSP scenarios that result in a radiative forcing pathway as high as the highest Representative Concentration Pathway (RCP8.5). This paper further investigates the direct impact of mitigation policies on the SSP5 energy, land and emissions dynamics confirming high socio-economic challenges to mitigation in SSP5. Nonetheless, mitigation policies reaching climate forcing levels as low as in the lowest Representative Concentration Pathway (RCP2.6) are accessible in SSP5. The SSP5 scenarios presented in this paper aim to provide useful reference points for future climate change, climate impact, adaption and mitigation analysis, and broader questions of sustainable development.
Future air pollution in the Shared Socio-economic Pathways
(Amsterdam : Elsevier, 2016) Rao, Shilpa; Klimont, Zbigniew; Smith, Steven J.; Van Dingenen, Rita; Dentener, Frank; Bouwman, Lex; Riahi, Keywan; Amann, Markus; Bodirsky, Benjamin Leon; van Vuuren, Detlef P.; Aleluia Reis, Lara; Calvin, Katherine; Drouet, Laurent; Fricko, Oliver; Fujimori, Shinichiro; Gernaat, David; Havlik, Petr; Harmsen, Mathijs; Hasegawa, Tomoko; Heyes, Chris; Hilaire, Jérôme; Luderer, Gunnar; Masui, Toshihiko; Stehfest, Elke; Strefler, Jessica; van der Sluis, Sietske; Tavoni, Massimo
Emissions of air pollutants such as sulfur and nitrogen oxides and particulates have significant health impacts as well as effects on natural and anthropogenic ecosystems. These same emissions also can change atmospheric chemistry and the planetary energy balance, thereby impacting global and regional climate. Long-term scenarios for air pollutant emissions are needed as inputs to global climate and chemistry models, and for analysis linking air pollutant impacts across sectors. In this paper we present methodology and results for air pollutant emissions in Shared Socioeconomic Pathways (SSP) scenarios. We first present a set of three air pollution narratives that describe high, central, and low pollution control ambitions over the 21st century. These narratives are then translated into quantitative guidance for use in integrated assessment models. The resulting pollutant emission trajectories under the SSP scenarios cover a wider range than the scenarios used in previous international climate model comparisons. In the SSP3 and SSP4 scenarios, where economic, institutional and technological limitations slow air quality improvements, global pollutant emissions over the 21st century can be comparable to current levels. Pollutant emissions in the SSP1 scenarios fall to low levels due to the assumption of technological advances and successful global action to control emissions.
Future growth patterns of world regions – A GDP scenario approach
(Amsterdam : Elsevier, 2015) Leimbach, Marian; Kriegler, Elmar; Roming, Niklas; Schwanitz, Jana
Global GDP projections for the 21st century are needed for the exploration of long-term global environmental problems, in particular climate change. Greenhouse gas emissions as well as climate change mitigation and adaption capacities strongly depend on growth of per capita income. However, long-term economic projections are highly uncertain. This paper provides five new long-term economic scenarios as part of the newly developed shared socio-economic pathways (SSPs) which represent a set of widely diverging narratives. A method of GDP scenario building is presented that is based on assumptions about technological progress, and human and physical capital formation as major drivers of long-term GDP per capita growth. The impact of these drivers differs significantly between different shared socio-economic pathways and is traced back to the underlying narratives and the associated population and education scenarios. In a highly fragmented world, technological and knowledge spillovers are low. Hence, the growth impact of technological progress and human capital is comparatively low, and per capita income diverges between world regions. These factors play a much larger role in globalization scenarios, leading to higher economic growth and stronger convergence between world regions. At the global average, per capita GDP is projected to grow annually in a range between 1.0% (SSP3) and 2.8% (SSP5) from 2010 to 2100. While this covers a large portion of variety in future global economic growth projections, plausible lower and higher growth projections may still be conceivable. The GDP projections are put into the context of historic patterns of economic growth (stylized facts), and their sensitivity to key assumptions is explored.
Improving Deep Learning-based Plant Disease Classification with Attention Mechanism
(Berlin ; Heidelberg : Springer, 2022) Alirezazadeh, Pendar; Schirrmann, Michael; Stolzenburg, Frieder
In recent years, deep learning-based plant disease classification has been widely developed. However, it is challenging to collect sufficient annotated image data to effectively train deep learning models for plant disease recognition. The attention mechanism in deep learning assists the model to focus on the informative data segments and extract the discriminative features of inputs to enhance training performance. This paper investigates the Convolutional Block Attention Module (CBAM) to improve classification with CNNs, which is a lightweight attention module that can be plugged into any CNN architecture with negligible overhead. Specifically, CBAM is applied to the output feature map of CNNs to highlight important local regions and extract more discriminative features. Well-known CNN models (i.e. EfficientNetB0, MobileNetV2, ResNet50, InceptionV3, and VGG19) were applied to do transfer learning for plant disease classification and then fine-tuned by a publicly available plant disease dataset of foliar diseases in pear trees called DiaMOS Plant. Amongst others, this dataset contains 3006 images of leaves affected by different stress symptoms. Among the tested CNNs, EfficientNetB0 has shown the best performance. EfficientNetB0+CBAM has outperformed EfficientNetB0 and obtained 86.89% classification accuracy. Experimental results show the effectiveness of the attention mechanism to improve the recognition accuracy of pre-trained CNNs when there are few training data.
L-(+)-Lactic Acid from Reed: Comparing Various Resources for the Nutrient Provision of B. coagulans
(Basel : MDPI, 2020) Schroedter, Linda; Schneider, Roland; Remus, Lisa; Venus, Joachim
Biotechnological production of lactic acid (LA) is based on the so-called first generation feedstocks, meaning sugars derived from food and feed crops such as corn, sugarcane and cassava. The aim of this study was to exploit the potential of a second generation resource: Common reed (Phragmites australis) is a powerfully reproducing sweet grass which grows in wetlands and creates vast monocultural populations. This lignocellulose biomass bears the possibility to be refined to value-added products, without competing with agro industrial land. Besides utilizing reed as a renewable and inexpensive substrate, low-cost nutritional supplementation was analyzed for the fermentation of thermophilic Bacillus coagulans. Various nutritional sources such as baker’s and brewer’s yeast, lucerne green juice and tryptone were investigated for the replacement of yeast extract. The structure of the lignocellulosic material was tackled by chemical treatment (1% NaOH) and enzymatic hydrolysis (Cellic® CTec2). B. coagulans DSM ID 14-300 was employed for the homofermentative conversion of the released hexose and pentose sugars to polymerizable L-(+)-LA of over 99.5% optical purity. The addition of autolyzed baker’s yeast led to the best results of fermentation, enabling an LA titer of 28.3 g L−1 and a yield of 91.6%.
Land-use futures in the shared socio-economic pathways
(Amsterdam [u.a.] : Elsevier, 2017) Popp, Alexander; Calvin, Katherine; Fujimori, Shinichiro; Havlik, Petr; Humpenöder, Florian; Stehfest, Elke; Bodirsky, Benjamin Leon; Dietrich, Jan Philipp; Doelmann, Jonathan C.; Gusti, Mykola; Hasegawa, Tomoko; Kyle, Page; Obersteiner, Michael; Tabeau, Andrzej; Takahashi, Kiyoshi; Valin, Hugo; Waldhoff, Stephanie; Weindl, Isabelle; Wise, Marshall; Kriegler, Elmar; Lotze-Campen, Hermann; Fricko, Oliver; Riahi, Keywan; Vuuren, Detlef P. van
In the future, the land system will be facing new intersecting challenges. While food demand, especially for resource-intensive livestock based commodities, is expected to increase, the terrestrial system has large potentials for climate change mitigation through improved agricultural management, providing biomass for bioenergy, and conserving or even enhancing carbon stocks of ecosystems. However, uncertainties in future socio-economic land use drivers may result in very different land-use dynamics and consequences for land-based ecosystem services. This is the first study with a systematic interpretation of the Shared Socio-Economic Pathways (SSPs) in terms of possible land-use changes and their consequences for the agricultural system, food provision and prices as well as greenhouse gas emissions. Therefore, five alternative Integrated Assessment Models with distinctive land-use modules have been used for the translation of the SSP narratives into quantitative projections. The model results reflect the general storylines of the SSPs and indicate a broad range of potential land-use futures with global agricultural land of 4900 mio ha in 2005 decreasing by 743 mio ha until 2100 at the lower (SSP1) and increasing by 1080 mio ha (SSP3) at the upper end. Greenhouse gas emissions from land use and land use change, as a direct outcome of these diverse land-use dynamics, and agricultural production systems differ strongly across SSPs (e.g. cumulative land use change emissions between 2005 and 2100 range from −54 to 402 Gt CO2). The inclusion of land-based mitigation efforts, particularly those in the most ambitious mitigation scenarios, further broadens the range of potential land futures and can strongly affect greenhouse gas dynamics and food prices. In general, it can be concluded that low demand for agricultural commodities, rapid growth in agricultural productivity and globalized trade, all most pronounced in a SSP1 world, have the potential to enhance the extent of natural ecosystems, lead to lowest greenhouse gas emissions from the land system and decrease food prices over time. The SSP-based land use pathways presented in this paper aim at supporting future climate research and provide the basis for further regional integrated assessments, biodiversity research and climate impact analysis. © 2016 The Authors
Mechanically Stable, Binder‐Free, and Free‐Standing Vanadium Trioxide/Carbon Hybrid Fiber Electrodes for Lithium‐Ion Batteries
(Weinheim : Wiley-VCH, 2023) Bornamehr, Behnoosh; Gallei, Markus; Husmann, Samantha; Presser, Volker
Binder is a crucial component in present-day battery electrodes but commonly contains fluorine and requires coating processing using organic (often toxic) solvents. Preparing binder-free electrodes is an attractive strategy to make battery electrode production and its end-of-use waste greener and safer. Herein, electrospinning is employed to prepare binder-free and self-standing electrodes. Such electrodes often suffer from low flexibility, and the correlation between performance and flexibility is usually overlooked. Processing parameters affect the mechanical properties of the electrodes, and for the first time it is reported that mechanical flexibility directly influences the electrochemical performance of the electrode. The importance is highlighted when processing parameters advantageous to powder materials, such as a higher heat treatment temperature, harm self-standing electrodes due to deterioration of fiber flexibility. Other strategies, such as conductive carbon addition, can be employed to improve the cell performance, but their effect on the mechanical properties of the electrodes must be considered. Rapid heat treatment achieves self-standing V2O3 with a capacity of 250 mAh g−1 at 250 mA g−1 and 390 mAh g−1 at 10 mA g−1
Methods for Recognition of Colorado Beetle (Leptinotarsa decemlineata (Say)) with Multispectral and Color Camera-sensors
(Berlin ; Heidelberg : Springer, 2022) Dammer, Karl-Heinz
At the beginning of an epidemic, the Colorado beetle occur sparsely on few potato plants in the field. A target-orientated crop protection applies insecticides only on infested plants. For this, a complete monitoring of the whole field is required, which can be done by camera-sensors attached to tractors or unmanned aerial vehicles (UAVs). The gathered images have to be analyzed using appropriate classification methods preferably in real-time to recognize the different stages of the beetle in high precision. In the paper, the methodology of the application of one multispectral and three commercially available color cameras (RGB) and the results from field tests for recognizing the development stages of the beetle along the vegetation period of the potato crop are presented. Compared to multispectral cameras color cameras are low-cost. The use of artificial neural network for classification of the larvae within the RGB-images are discussed. At the bottom side of the potato leaves the eggs are deposited. Sensor based monitoring from above the crop canopy cannot detect the eggs and the hatching first instar. The ATB developed a camera equipped vertical sensor for scanning the bottom of the leaves. This provide a time advantage for the spray decision of the farmer (e.g. planning of the machine employment, purchase of insecticides). In this paper, example images and a possible future use of the presented monitoring methods above and below the crop surface are presented and discussed.
A new method to measure real-world respiratory tract deposition of inhaled ambient black carbon
(Amsterdam [u.a.] : Elsevier Science, 2019) Madueño, Leizel; Kecorius, Simonas; Löndahl, Jakob; Müller, Thomas; Pfeifer, Sascha; Haudek, Andrea; Mardoñez, Valeria; Wiedensohler, Alfred
In this study, we present the development of a mobile system to measure real-world total respiratory tract deposition of inhaled ambient black carbon (BC). Such information can be used to supplement the existing knowledge on air pollution-related health effects, especially in the regions where the use of standard methods and intricate instrumentation is limited. The study is divided in two parts. Firstly, we present the design of portable system and methodology to evaluate the exhaled air BC content. We demonstrate that under real-world conditions, the proposed system exhibit negligible particle losses, and can additionally be used to determine the minute ventilation. Secondly, exemplary experimental data from the system is presented. A feasibility study was conducted in the city of La Paz, Bolivia. In a pilot experiment, we found that the cumulative total respiratory tract deposition dose over 1-h commuting trip would result in approximately 2.6 μg of BC. This is up to 5 times lower than the values obtained from conjectural approach (e.g. using physical parameters from previously reported worksheets). Measured total respiratory tract deposited BC fraction varied from 39% to 48% during walking and commuting inside a micro-bus, respectively. To the best of our knowledge, no studies focusing on experimental determination of real-world deposition dose of BC have been performed in developing regions. This can be especially important because the BC mass concentration is significant and determines a large fraction of particle mass concentration. In this work, we propose a potential method, recommendations, as well as the limitations in establishing an easy and relatively cheap way to estimate the respiratory tract deposition of BC. In this study we present a novel method to measure real-world respiratory tract deposition dose of Black Carbon. Results from a pilot study in La Paz, Bolivia, are presented. © 2019 The Authors
Projected changes in persistent extreme summer weather events: The role of quasi-resonant amplification
(Washington, DC [u.a.] : Assoc., 2018) Mann, Michael E.; Rahmstorf, Stefan; Kornhuber, Kai; Steinman, Byron A.; Miller, Sonya K.; Petri, Stefan; Coumou, Dim
Persistent episodes of extreme weather in the Northern Hemisphere summer have been associated with highamplitude quasi-stationary atmospheric Rossby waves, with zonal wave numbers 6 to 8 resulting from the phenomenon of quasi-resonant amplification (QRA). A fingerprint for the occurrence of QRA can be defined in terms of the zonally averaged surface temperature field. Examining state-of-the-art [Coupled Model Intercomparison Project Phase 5 (CMIP5)] climate model projections, we find that QRA events are likely to increase by ∼50% this century under business-as-usual carbon emissions, but there is considerable variation among climate models. Some predict a near tripling of QRA events by the end of the century, while others predict a potential decrease. Models with amplified Arctic warming yield the most pronounced increase in QRA events. The projections are strongly dependent on assumptions regarding the nature of changes in radiative forcing associated with anthropogenic aerosols over the next century. One implication of our findings is that a reduction in midlatitude aerosol loading could actually lead to Arctic de-amplification this century, ameliorating potential increases in persistent extreme weather events.

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