Model-based Source Partitioning of Eddy Covariance Flux Measurements

Terrestrial ecosystems constantly exchange momentum, energy, and mass (e.g., water vapor, CO2) with the atmosphere above. This exchange is commonly measured with a micrometeorological technique, the eddy covariance (EC) method. Various components of the measured net fluxes, such as transpiration, evaporation, gross primary production, and soil respiration, cannot be depicted separately by the EC approach. Thus, so-called source partitioning approaches have to be applied to CO2 and water vapor EC data to gain a better understanding of the prevailing processes and their interrelations in terrestrial ecosystems. A large variety of partitioning procedures with diverse model approaches have been developed, including various driving variables, necessity of different input data and parameterizations. The most robust and commonly used source partitioning tools for CO2 flux components, often primarily developed to fill gaps in EC measurements, are based on the notion that during night respiration fluxes prevail. They use non-linear regressed relationships of these nighttime observations and physical drivers (e.g., temperature in the approach after Reichstein et al. 2005). Here, the challenge lies within extrapolating the nighttime relationship to daytime conditions, and analogous methods for water fluxes are lacking. In this thesis, next to the approach after Reichstein et al. (2005) various data-driven source partitioning approaches for H2O and CO2 fluxes were applied, compared, modified, and evaluated for multiple ecosystems to get a better understanding of the methods’ functionality, dependencies, uncertainties, advantages, and shortcomings. We first describe the coupling and extension of the complex terrestrial ecosystem model AgroC. Further, we conducted a comprehensive model-data fusion study to clarify the CO2 exchange in agroecosystems and estimate their annual carbon balance. For three test sites in Western Germany, AgroC was calibrated based on soil water content, soil temperature, biometric, and soil respiration measurements for each site, and validated sufficiently in terms of hourly net ecosystem exchange (NEE) measured with the EC technique. Moreover, AgroC reproduced the flux dynamics very effectively after sudden changes in the grassland canopy due to mowing. In a second step, AgroC was optimized with the EC measurements to examine the effect of various objective functions, constraints, and data-transformations on the estimated carbon balance and to compare the results to the established gap-filling approach after Reichstein et al. (2005). It was found that modeled NEE showed a distinct sensitivity to the choice of objective function and the inclusion of soil respiration data in the optimization process. Even though the model performance of the selected optimization strategies did not diverge substantially, the resulting cumulative NEE over simulation time period differed extensively. Therefore, it is concluded that data-transformations, definitions of objective functions, and data sources have to be considered cautiously when a terrestrial ecosystem model is used to determine NEE by means of EC measurements. Second, we applied the source partitioning approaches after Scanlon and Kustas (2010; SK10) and after Thomas et al. (2008; TH08) to high frequency EC measurements estimating transpiration, evaporation, net primary production, and soil respiration, of various ecosystems (croplands, grasslands, and forests). Both partitioning methods are based on higher-order statistics of the H2O and CO2 fluctuations, but proceed differently. SK10 had the tendency to overestimate and TH08 to underestimate soil flux components, where the partitioning of CO2 fluxes was more irregular than of H2O fluxes. Results derived with SK10 showed relatively large dependencies on estimated water use efficiency (WUE) on leaf-level, which is needed as an input. Measurements of outgoing longwave radiation used for the estimation of foliage temperature and WUE could slightly increase the quality of the partitioning results. A modification of the TH08 approach, by applying a cluster analysis for the conditional sampling of respiration/evaporation events, performed sufficiently, but did not result in significant advantages compared to the other method versions. The performance of each partitioning approach was dependent on meteorological conditions, plant development, canopy height, canopy density, and measurement height. Foremost, the performance of SK10 correlated negatively with the ratio between measurement and canopy height. The performance of TH08 was more dependent on canopy height and leaf area index. It was found, that all site characteristics which increase dissimilarities between scalars enhance partitioning performance for SK10 and TH08. Also, we conducted large eddy simulations (LES), simulating the turbulent transport of H2O and CO2. SK10 was applied to the synthetic high frequency data generated by LES, and the effects of canopy type, measurement height, given scalar sink-source-distributions, and estimated WUE input were tested regarding the partitioning performance. The LES-based analysis revealed that for a satisfying performance of SK10, a certain degree of decorrelation of the H2O and CO2 fluctuations was needed and a correct WUE estimation was favorable. Furthermore, another possible error source, which was so far not yet discussed in the literature, could be detected for the partitioning approach. In the special case of the LES experiments, validity of an essential assumption about the prevailing transport efficiencies of the scalars in the method’s derivation was found to be a crucial point for a correct application of SK10. The application of different source partitioning methods including their various involved assumptions, required input data and work effort showed that still uncertainties and unknowns prevail for the source partitioning of water vapor and CO2 fluxes. An assessment and evaluation of the partitioning results can only be conducted with additional measurements of flux components on differing spatial and temporal scales independent of the EC measurements. Further, the application of multiple partitioning methods (usage of an ensemble) to the same data can give a better idea about uncertainties in the results

Did Smoking, Alcohol Consumption, and Physical Activity Change during the COVID-19 Restrictions in Germany in Spring 2020?

Zielsetzung: Im März 2020 wurden in Deutschland flächendeckende Beschränkungen eingeführt, um die Ausbreitung des schweren akuten respiratorischen Syndroms Coronavirus Typ 2 einzudämmen. Es ist unklar, wie sich diese Beschränkungen auf das Gesundheitsverhalten der Menschen auswirkten. Ziel dieser Arbeit war es, rückblickend von den Befragten wahrgenommene Veränderungen in Bezug auf ihr Tabakrauchen, ihren Alkoholkonsum und ihre körperliche Aktivität im Vergleich zu der Zeit vor den Beschränkungen zu untersuchen und Zusammenhänge zwischen möglichen Veränderungen und sozioökonomischen und soziodemografischen Merkmalen zu erforschen. Methodik: Datenbasis war die Deutsche Befragung zum Rauchverhalten (DEBRA), eine repräsentative Querschnittserhebung bei Personen ab 14 Jahren. Analysiert wurden Daten aus 2 Wellen (Juni-August 2020) von 4.078 Teilnehmenden. Zusammenhänge zwischen sozioökonomischen und soziodemografischen Merkmalen und Veränderungen in den einzelnen Gesundheitsverhaltensweisen wurden mithilfe multinomialer logistischer Regressionsanalysen analysiert. Ergebnisse: Veränderungen im Gesundheitsverhalten: Zunahme im Rauchverhalten=24,0 % (95 % Konfidenzintervall (KI)=21,5-26,7), Abnahme=12,2 % (95 %KI=10,4-14,4); Zunahme des Alkoholkonsums=12,9 % (95 %KI=11,7-14,1), Abnahme=19,9 % (95 %KI=18,4-21,3); Zunahme des Bewegungsverhaltens=18,5 % (95 %KI=17,3-19,7), Abnahme=29,4 % (95 %KI=28,0-31,0). Personen mit einem niedrigeren Bildungsniveau und jüngerem Alter berichteten häufiger über eine schädliche Veränderung desGesundheitsverhaltens. Schlussfolgerungen: Die meisten Menschen gaben keine Veränderung ihres Gesundheitsverhalten an. Von den Personen, die ihr Verhalten verändert haben, rauchten relativ mehr Tabak, und tranken weniger Alkohol bzw. bewegten sich weniger. Von diesen Veränderungen waren vor allem Personen mit einem niedrigeren Bildungsniveau und jüngeren Alters betroffen, was bei Präventivmaßnahmen berücksichtig werden sollte.Aims: Nationwide restrictions were implemented in Germany in March 2020 to reduce the spread of the severe acute respiratory syndrome coronavirus type 2 (SARS-COV-2). It is not yet precisely known how these restrictions affected peoples’ health behaviours in Germany. Objectives were to 1) retrospectively examine changes in self-reported health behaviours (tobacco smoking, alcohol consumption, and physical activity) in response to these restrictions; and 2) to explore associations among health behaviour changes as well as links to socioeconomic and sociodemographic characteristics. Methodology: We used data from two waves (June-August 2020) of the German Study on Tobacco Use (DEBRA): a cross-sectional, representative survey with people aged ≥14 years (n=4078). Associations between socioeconomic and sociodemographic characteristics and health behaviour changes were analysed using multinomial logistic regression analyses. Results: Changes in health behaviours were as follows: smoking increase=24.0 % (95 % confidence interval (CI)=21.5-26.7), decrease=12.2 % (95 %CI=10.4-14.4); alcohol consumption increase=12.9 % (95 %CI=11.7-14.1), decrease=19.9 % (95 %CI=18.4-21.3); physical activity increase=18.5 % (95 %CI=17.3-19.7); decrease=29.4 % (95 %CI=28.0-31.0). Younger people with a lower level of education were more likely to report a harmful health behaviour change. Conclusions: The majority of people did not change their health behaviours. Among those who did, comparatively more increased their smoking and decreased their alcohol consumption and physical activity. Public health interventions in this context should particularly target younger people and those with a lower level of education

«Графічне оформлення схем електричних принципових» методичні вказівки до практичних занять для студентів напрямів підготовки 0501 інформатика та обчислювальна техніка; 0502 автоматика та управління; 0507 електротехніка та електромеханіка; 0509 радіотехніка, радіоелектронні апарати та зв’язок; 0510 метрологія, вимірювальна техніка та інформаційно-вимірювальні технології та 1701 інформаційна безпека.

ЗМІСТ ВСТУП ............................................................................................................................................... 1 1. ЗАГАЛЬНІ ПОНЯТТЯ ПРО СХЕМИ ТА ЇХНЮ КЛАСИФІКАЦІЮ ...................................... 1 2. ВИМОГИ І ПРАВИЛА ВИКОНАННЯ ЕЛЕКТРИЧНИХ ПРИНЦИПОВИХ СХЕМ ............. 1 2.1. ЗАГАЛЬНІ ВИМОГИ ДО ВИКОНАННЯ СХЕМ ................................................................................. 1 2.2. ВИМОГИ ДО ГРАФІЧНОГО ОФОРМЛЕННЯ СХЕМ ......................................................................... 2 2.3. УМОВНІ ГРАФІЧНІ ПОЗНАЧЕННЯ ЕЛЕМЕНТІВ НА ЕЛЕКТРИЧНИХ СХЕМАХ ................................. 4 2.4. ПОЗИЦІЙНІ ЛІТЕРНО-ЦИФРОВІ ПОЗНАЧЕННЯ В ЕЛЕКТРИЧНИХ СХЕМАХ.................................. 12 2.5. ПЕРЕЛІК ЕЛЕМЕНТІВ ................................................................................................................ 16 3. ВКАЗІВКИ ДО ВИКОНАННЯ ЗАВДАННЯ ............................................................................ 18 ЗАПИТАННЯ ДЛЯ САМОКОНТРОЛЮ ...................................................................................... 23 4. ПОРЯДОК ВИКОНАННЯ СХЕМИ ЕЛЕКТРИЧНОЇ ПРИНЦИПОВОЇ В AUTOCAD . ...... 26 ЗАПИТАННЯ ДЛЯ САМОКОНТРОЛЮ ...................................................................................... 31 ЛІТЕРАТУРА .................................................................................................................................. 31Розглянуті загальні вимоги до графічного оформлення схем електричних принципових, систематизовані основні положення державних стандартів зображення і оформлення електричних схем, наведені умовні графічні позначення електричних елементів схем

Перспективы использования термофильного режима в биогазовой технологии по переработке отходов сельского хозяйства

В данной статье рассматриваются биогазовые установки для переработки отходов сельского хозяйства и описываются базовые элементы их различных конструкций. Кроме того, рассматриваются режимы биогазовой технологии, из которых оптимальным и перспективным для Томской области является термофильный режим, который позволяет снизить капитальные затраты на производство биогазовой установки, снизить энергетические затраты на подогрев и поддержание температуры субстрата установки и получить экологически чистые биоудобрения и биогаз. This article looks at biogas plants for processing agricultural waste and outlines the basic elements of various designs. It also covers modes of biogas technology, from which the best and promising for the Tomsk region is thermophilic mode, which reduces the capital expenditure on the biogas plant, to reduce energy costs for heating and maintenance of the installation of the substrate temperature and obtain eco-friendly bio-fertilizer and biogas

Multiple sourcing in single- and multi-echelon inventory systems

This thesis deals with stochastic inventory models that focus on the following two aspects in particular: (i) the coordination of multiple supply sources and (ii) the optimization of the inventory allocation and sizing in multi-echelon systems. Initially, single-echelon inventory models with multiple sourcing and multi-echelon inventory models with single sourcing are analyzed separately. In the former case, the goal is the identification of effective inventory control policies. In the latter case, the focus lies on the development of a new multi-echelon approach, which combines the two major frameworks currently available in the literature. Subsequently, both aspects are integrated into a multi-echelon inventory model with multiple sourcing