Biogenic volatile organic compound emissions from bioenergy plants and potential impacts on air chemistry

Bioenergy plant production is expected to rapidly expand in Europe in the near future. This might not only affect resource availability but will also influence the environment. Since many bioenergy plants do emit different amounts and different compositions of biogenic volatile organic compounds (BVOCs) compared to conventional agricultural crops, the new blend of highly reactive compounds might change the chemical composition of the atmosphere. BVOCs have a strong potential to enhance the photochemical O3 production, increase the formation of secondary organic aerosols (SOA), and prolong CH4 lifetime due to fast reactions with OH. These environmental impacts of bioenergy plants on air quality and the regional climate, however, are difficult to evaluate since accurate field observations of relevant crops are not available. Therefore, I studied a large range of BVOC fluxes from the most prominent bioenergy plants in Germany, which are maize, ryegrass, and oilseed rape, by applying field measurements and biogeochemical modeling. The plants were cultivated in Dedelow, Brandenburg, Germany and observed throughout the vegetative and reproductive development stages. Combining automatically moving large chambers and a proton transfer reaction–mass spectrometer (PTR-MS), I quantified the emission of numerous highly reactive terpenoids, together with several other BVOCs, including alcohols, aldehydes, ketones, benzenoids, and fatty acid derivatives. The characteristic seasonal BVOC flux pattern of each species, could be divided into groups and was associated to the different plant growth stages. The observations from the field campaigns were used to parameterize a biogeochemical ecosystem model coupled to a process-based BVOC emission model. The parameters for the BVOC model were fitted for each compound individually and comprise the standardized emission factor, an emission function curvature coefficient, and the fractionation into a light dependent (de novo emission) and light independent (pool emission) function. Therefore, I merged a mechanistic process-based de novo model with a pool emission approach into a joint BVOC emission model which was embedded in the biogeochemical framework LandscapeDNDC. Finally, total annual emissions were calculated in dependence on simulated plant growth and photosynthesis. Simulated BVOC emissions show that considerable differences between the investigated bioenergy plants exist with oilseed rape having 37-fold higher total annual emissions than maize (oilseed rape: 91.3 ± 8.0 mmol m-2 a-1; maize: 2.5 ± 0.1; and ryegrass: 15.7 ± 0.6). The differences in potential annual impacts on air chemistry are less pronounced between the plants, due to the large fraction of highly reactive terpenoids in the maize BVOC emissions. In particular, the difference is reduced to the 6-fold when the potential impact on OH-reactivity (a measure for O3 and SOA forming potential as well as indirect radiative forcing) is considered and to the 4.5-fold when the theoretically produced electricity yield is additionally taken as a reference. Thus, the results indicate that BVOC fluxes from large-scale bioenergy fields should be better differentiated, especially with regard to BVOC composition and reactivity. Additionally, the large impact of plant phenology on emission factors demands for elaborated models that should be based on measurements that cover the whole plant growth period.Es wird erwartet, dass der Anbau von Bioenergiepflanzen in Europa in naher Zukunft stark zunehmen wird. Dies hat nicht nur Einfluss auf die Ressourcenversorgung, sondern auch auf die Umwelt. Da viele Energiepflanzen andere Emissionsmengen und Gruppierungen von hochreaktiven biogenen flüchtigen organischen Verbindungen (BVOCs) aufweisen als die meisten sonstigen Agrarpflanzen, könnte die chemische Zusammensetzung der Atmosphäre beeinflusst werden. BVOCs in der Atmosphäre können zu einer Zunahme der Konzentrationen von Ozon und sekundären organischen Aerosolen (SOA) führen, sowie die Lebensdauer des klimaschädlichen Gases Methan (CH4) durch Reaktionen mit dem Hydroxyl-Radikal (OH) verlängern. Diese negativen Einflüsse durch den vermehrten Anbau von Bioenergiepflanzen auf die Luftqualität und das regionale Klima sind jedoch schwer zu quantifizieren, da ausreichende Feldmessungen an diesen Pflanzen fehlen. Deshalb habe ich biogenic volatile organic compound (BVOC)-Flüsse aus den in Deutschland meistgenutzten Bioenergiepflanzen Mais, Weidelgras und Raps mittels Feldmessungen und biogeochemischer Modellierung genauer untersucht. Die Pflanzen wurden in Dedelow, Brandenburg, Deutschland angebaut und während der gesamten vegetativen und reproduktiven Entwicklungsstadien untersucht. Mit einer Kombination aus sich automatisch öffnenden und schließenden Großkammern und einem Protonentransferreaktionsmassenspektrometer (PTR-MS) konnte ich hohe Emissionsanteile von hochgradig reaktiven Terpenoiden sowie anderen BVOCs, darunter Alkohole, Aldehyde, Ketone, Benzonoide und Fettsäurederivate quantifizieren. Die Saisonalität der BVOC-Flüsse konnte in charakteristische Gruppen eingeteilt und den verschiedenen Entwicklungsstadien der Pflanze zugeordnet werden. Die Beobachtungen aus den Feldmessungen wurden unter anderem dafür verwendet, ein physiologisch-orientiertes BVOC Modell, das an ein biogeochemisches Ökosystem gekoppelt wurde, weiter zu entwickeln und zu parametrisieren. Die Parameter wurden für jeden einzelnen Stoff angepasst und beinhalten den Standardemissionsfaktor, den Krümmungskoeffizienten der Emissionsfunktion und den Anteil der lichtabhängigen und lichtunabhängigen Emissionsfunktion. Dazu wurde in dieser Arbeit ein Modell zusammengeführt, welches Emissionen von neu gebildeten Stoffen (lichtabhängige) und Emissionen aus dem Stoffspeicher (lichtunabhängig) simulieren kann. Das Modell wurde anschließend dazu verwendet, Jahresbilanzen der Emissionen zu erstellen, die nicht nur von der direkten meteorologischen Situation angetrieben werden, sondern auch vom Pflanzenwachstum und der Photosynthese abhängen. Simulierte jährliche BVOC-Gesamtemissionen weichen zwischen den Bioenergiepflanzen um den Faktor 37 zwischen der Art mit den niedrigsten und der mit den höchsten Emissionen ab (2.5 ± 0.1, 15.7 ± 0.6, and 91.3 ± 8.0 mmol m-2 a-1 aus Mais, Weidelgras und Raps). Aufgrund des hohen Anteils von hochreaktiven Terpenoiden an den emittierten BVOCs aus Mais, sind die Unterschiede von möglichen Auswirkungen auf die Luftchemie zwischen den Pflanzen weniger stark ausgeprägt. Bei Berücksichtigung der potentiellen OH-Reaktivität (ein Maß, das den Einfluss auf O3 und SOA Bildung, sowie den indirekten Klimaeinfluss wiedergibt) verringert sich dadurch der Unterschied zwischen den Arten in Bezug auf die Luftchemie auf den Faktor 6. Wenn zusätzlich auf die theoretische produzierbare Menge Strom skaliert wird, ergibt sich sogar nur ein Unterschied von dem Faktor 4.5. Die Ergebnisse zeigen, dass BVOC-Flüsse aus großflächigem Bioenergieanbau in Zukunft besser differenziert werden sollten. Dazu müssen eine Vielzahl unterschiedlicher Stoffe berücksichtigt werden. Da für den Einfluss auf die Luftchemie häufig eine zeitlich hoch aufgelöste Einschätzung der BVOC-Emission notwendig ist, muss zudem berücksichtigt werden, dass sich die Emissionsfaktoren mit dem Entwicklungsstadium ändern. Daher sollten auch Messungen verstärkt über längere Messzeiträume durchgeführt werden, die über mehrere Entwicklungsstufen hinweg gehen

Land Use Effects on Climate: Current State, Recent Progress, and Emerging Topics

As demand for food and fiber, but also for negative emissions, brings most of the Earth’s land surface under management, we aim to consolidate the scientific progress of recent years on the climatic effects of global land use change, including land management, and related land cover changes (LULCC)

Effects of crop residue incorporation and properties on combined soil gaseous N2_{2}O, NO, and NH3_{3} emissions—A laboratory-based measurement approach

Crop residues may serve as a significant source of soil emissions of N$_{2}$O and other trace gases. According to the emission factors (EFs) set by the Intergovernmental Panel on Climate Change (IPCC), N$_{2}$O emission is proportional to the amount of N added by residues to the soil. However, the effects of crop residues on the source and sink strength of agroecosystems for trace gases are regulated by their properties, such as the C and N content; C/N ratio; lignin, cellulose, and soluble fractions; and residue humidity. In the present study, an automated dynamic chamber method was used in combination with soil mesocosms to simultaneously measure the effects of nine different crop residues (oilseed rape, winter wheat, field pea, maize, potato, mustard, red clover, sugar beet, and ryegrass) on soil respiration (CO$_{2}$) and reactive N fluxes (N$_{2}$O, NO, and NH$_{3}$) at a high temporal resolution. Specifically, crop residues were incorporated in the 0–4 cm topsoil layer and incubated for 60 days at a constant temperature (15 °C) and water-filled pore space (60% WFPS). Residue incorporation immediately and sharply increased soil N$_{2}$O and CO$_{2}$ emissions, but these were short-lived and returned to background levels within respectively 10 and 30 days. The magnitude of increase in soil NO flux following residue incorporation was lower than that in CO$_{2}$ and N$_{2}$O fluxes, with peak emissions observed around day 20. Overall, the N content or C/N ratio of the applied residue could not sufficiently explain the variation in soil N2O and NO emissions. The range of the calculated N$_{2}$O EFs over a 60-day period was −0.17 to +4.5, being wider than that proposed by the IPCC (+0.01 to +1.1). Therefore, the residue maturity stage may be used as a simple proxy to estimate the N$_{2}$O + NO emissions from incorporated residue

Modeling Intra‐ and Interannual Variability of BVOC Emissions From Maize, Oil‐Seed Rape, and Ryegrass

Air chemistry is affected by the emission of biogenic volatile organic compounds (BVOCs), which originate from almost all plants in varying qualities and quantities. They also vary widely among different crops, an aspect that has been largely neglected in emission inventories. In particular, bioenergy-related species can emit mixtures of highly reactive compounds that have received little attention so far. For such species, long-term field observations of BVOC exchange from relevant crops covering different phenological phases are scarcely available. Therefore, we measured and modeled the emission of three prominent European bioenergy crops (maize, ryegrass, and oil-seed rape) for full rotations in north-eastern Germany. Using a proton transfer reaction–mass spectrometer combined with automatically moving large canopy chambers, we were able to quantify the characteristic seasonal BVOC flux dynamics of each crop species. The measured BVOC fluxes were used to parameterize and evaluate the BVOC emission module (JJv) of the physiology-oriented LandscapeDNDC model, which was enhanced to cover de novo emissions as well as those from plant storage pools. Parameters are defined for each compound individually. The model is used for simulating total compound-specific reactivity over several years and also to evaluate the importance of these emissions for air chemistry. We can demonstrate substantial differences between the investigated crops with oil-seed rape having 37-fold higher total annual emissions than maize. However, due to a higher chemical reactivity of the emitted blend in maize, potential impacts on atmospheric OH-chemistry are only 6-fold higher

Full configuration drag estimation of short-to-medium range fixed-wing UAVs and its impact on initial sizing optimization

The paper presents the derivation of a new equivalent skin friction coefficient for estimating the parasitic drag of short-to-medium range fixed-wing unmanned aircraft. The new coefficient is derived from an aerodynamic analysis of ten different unmanned aircraft used for surveillance, reconnaissance, and search and rescue missions. The aircraft is simulated using a validated unsteady Reynolds-averaged Navier Stokes approach. The UAV’s parasitic drag is significantly influenced by the presence of miscellaneous components like fixed landing gears or electro-optical sensor turrets. These components are responsible for almost half of an unmanned aircraft’s total parasitic drag. The new equivalent skin friction coefficient accounts for these effects and is significantly higher compared to other aircraft categories. It is used to initially size an unmanned aircraft for a typical reconnaissance mission. The improved parasitic drag estimation yields a much heavier unmanned aircraft when compared to the sizing results using available drag data of manned aircraft

The biogeophysical effects of idealized land cover and land management changes in Earth system models

Land cover and land management change (LCLMC) has been highlighted for its critical role in mitigation scenarios in terms of both global mitigation and local adaptation. Yet, the climate effect of individual LCLMC options, their dependence on the background climate, and the local vs. non-local responses are still poorly understood across different Earth system models (ESMs). Here we simulate the climatic effects of LCLMC using three state-of-the-art ESMs, including the Community Earth System Model (CESM), the Max Planck Institute for Meteorology Earth System Model (MPI-ESM), and the European Consortium Earth System Model (EC-EARTH). We assess the LCLMC effects using four idealized experiments: (i) a fully afforested world, (ii) a world fully covered by cropland, (iii) a fully afforested world with extensive wood harvesting, and (iv) a full cropland world with extensive irrigation. In these idealized sensitivity experiments performed under present-day climate conditions, the effects of the different LCLMC strategies represent an upper bound for the potential of global mitigation and local adaptation. To disentangle the local and non-local effects from the LCLMC, a checkerboard-like LCLMC perturbation, i.e. alternating grid boxes with and without LCLMC, is applied. The local effects of deforestation on surface temperature are largely consistent across the ESMs and the observations, with a cooling in boreal latitudes and a warming in the tropics. However, the energy balance components driving the change in surface temperature show less consistency across the ESMs and the observations. Additionally, some biases exist in specific ESMs, such as a strong albedo response in CESM mid-latitudes and a soil-thawing-driven warming in boreal latitudes in EC-EARTH. The non-local effects on surface temperature are broadly consistent across ESMs for afforestation, though larger model uncertainty exists for cropland expansion. Irrigation clearly induces a cooling effect; however, the ESMs disagree regarding whether these are mainly local or non-local effects. Wood harvesting is found to have no discernible biogeophysical effects on climate. Our results overall underline the potential of ensemble simulations to inform decision-making regarding future climate consequences of land-based mitigation and adaptation strategies.ISSN:2190-4987ISSN:2190-497

Overcoming global inequality is critical for land-based mitigation in line with the Paris Agreement

Transformation pathways for the land sector in line with the Paris Agreement depend on the assumption of globally implemented greenhouse gas (GHG) emission pricing, and in some cases also on inclusive socio-economic development and sustainable land-use practices. In such pathways, the majority of GHG emission reductions in the land system is expected to come from low- and middle-income countries, which currently account for a large share of emissions from agriculture, forestry and other land use (AFOLU). However, in low- and middle-income countries the economic, financial and institutional barriers for such transformative changes are high. Here, we show that if sustainable development in the land sector remained highly unequal and limited to high-income countries only, global AFOLU emissions would remain substantial throughout the 21st century. Our model-based projections highlight that overcoming global inequality is critical for land-based mitigation in line with the Paris Agreement. While also a scenario purely based on either global GHG emission pricing or on inclusive socio-economic development would achieve the stringent emissions reductions required, only the latter ensures major co-benefits for other Sustainable Development Goals, especially in low- and middle-income regions

Lokale und weitreichende Klimaeffekte von Aufforstung und anderen Landnutzungsmaßnahmen zum Klimaschutz

Die große Mehrzahl der Emissionspfade, die die globale Erwärmung entsprechend des Paris-Abkommens beschränken, geht von einem großskaligen Einsatz von Maßnahmen zur CO2-Entnahme mit anschließender langfristiger Speicherung aus (»Carbon Dioxide Removal«, CDR). Hierbei werden vor allem Maßnahmen unter Einsatz terrestrischer Vegetation, wie Aufforstung oder Biokohle, diskutiert. Zusammen mit Emissionsreduktionen aus dem Landnutzungsbereich könnten sie vermutlich etwa 30% des benötigten Potentials für das 1,5°C-Ziel liefern. Allerdings werden in Abschätzungen der Gesamtklimawirkung politisch derzeit die biogeophysikalischen Nebeneffekte (z. B. veränderte Albedo und Energieflüsse) vernachlässigt, obwohl Landnutzungspraktiken lokale Temperaturen um mehrere Grad verändern können. Beispielsweise führt die Aufforstung in nördlichen Breiten typisch zu einer Erhöhung der Oberflächenrauigkeit, die die lokalen Temperaturen erhöht, wohingegen die erhöhte Transpiration und Rauigkeit auf aufgeforsteten Flächen besonders in den Tropen die lokalen Temperaturen senkt und somit zur lokalen Anpassung an den Klimawandel beitragen kann. Landnutzungspraktiken verändern die Wasser- und Energiebilanz aber auch substanziell über die Region hinaus. Diese nicht-lokalen Effekte können zwar nicht direkt von Beobachtungsdaten erfasst werden, sind aber von Klimamodellen darstellbar. Achtsamkeit ist nötig, um lokale und nicht-lokale biogeophysikalische Effekte gegeneinander und gegen das CDR-Potential einer Maßnahme abzuwägen und idealerweise Win-win-Situationen zu schaffen. Local and far-reaching effects on climate of reforestation/afforestation and other land use-based climate protection measures: The vast majority of emission pathways limiting global warming according to the Paris Agreement assumes large-scale deployment of methods for CO2 removal with long-term storage (»Carbon Dioxide Removal«, CDR). Especially methods using terrestrial vegetation, such as reforestation or biochar, are discussed as viable CDR options. Together with emission reductions from land use, they could likely provide about 30% of the required potential for the 1.5°C target. However, estimates of overall climate impacts used in policy currently neglect biogeophysical side effects (e.g., altered albedo and energy fluxes), even though land-use practices can alter local temperatures by several degrees. For example, afforestation in northern latitudes typically increases surface roughness, which increases local temperatures, whereas increased transpiration and roughness on afforested land in particular in the tropics lowers local temperatures and thus can contribute to local adaptation to climate change. However, land-use practices also substantially alter water and energy balances beyond the region. While these non-local effects cannot be directly captured by observational data, they can be represented by climate models. Attention is needed to balance local and non-local biogeophysical effects against each other and against the CDR potential of a method, to ideally create win-win situations. Efectos climáticos locales y de largo alcance de la forestación/reforestación y otras medidas de uso de la tierra para la protección del clima: La gran mayoría de las rutas de emisión que limitan el calentamiento global de acuerdo con el Acuerdo de París asumen un uso a gran escala de medidas para la remoción de CO2 con el subsiguiente largo almacenamiento a largo plazo (»Eliminación de dióxido de carbono«, CDR). Sobre todo, se discuten las medidas que utilizan vegetación terrestre, como la forestación o el biocarbón. Junto con las reducciones de emisiones derivadas del uso de la tierra, presumiblemente podrían generar alrededor del 30% del potencial requerido para el objetivo de 1.5° C. Sin embargo, en las evaluaciones del impacto climático general, los efectos colaterales biogeofísicos (por ejemplo, cambios en el albedo y los flujos de energía) actualmente se descuidan políticamente, aunque las prácticas de uso de la tierra pueden cambiar las temperaturas locales en varios grados. Por ejemplo, la forestación en latitudes septentrionales generalmente conduce a un aumento de la rugosidad de la superficie, lo que aumenta las temperaturas locales, mientras que el aumento de la transpiración y la rugosidad en las áreas forestadas, especialmente en los trópicos, reduce las temperaturas locales y, por lo tanto, puede contribuir a la adaptación local al cambio climático. Las prácticas de uso de la tierra también cambian sustancialmente el equilibrio hídrico y energético más allá de la región. Estos efectos no locales no pueden registrarse directamente a partir de los datos de observación, pero pueden representarse mediante modelos climáticos. La atención plena es necesaria para sopesar los efectos biogeofísicos locales y no locales entre sí y contra el potencial de CDR de una medida e idealmente para crear situaciones de beneficio mutuo

Empirical Correlations for Geometry Build-Up of Fixed Wing Unmanned Air Vehicles

The results of a statistical investigation of 42 fixed-wing, small to medium sized (20 kg−1000 kg) reconnaissance unmanned air vehicles (UAVs) are presented. Regression analyses are used to identify correlations of the most relevant geometry dimensions with the UAV’s maximum take-off mass. The findings allow an empirical based geometry-build up for a complete unmanned aircraft by referring to its take-off mass only. This provides a bridge between very early design stages (initial sizing) and the later determination of shapes and dimensions. The correlations might be integrated into a UAV sizing environment and allow designers to implement more sophisticated drag and weight estimation methods in this process. Additional information on correlation factors for a rough drag estimation methodology indicate how this technique can significantly enhance the accuracy of early design iterations