Lessons Learned and Next Steps in Energy Efficiency Measurement and Attribution: Energy Savings, Net to Gross, Non-Energy Benefits, and Persistence of Energy Efficiency Behavior

This white paper examines four topics addressing evaluation, measurement, and attribution of direct and indirect effects to energy efficiency and behavioral programs: Estimates of program savings (gross); Net savings derivation through free ridership / net to gross analyses; Indirect non-energy benefits / impacts (e.g., comfort, convenience, emissions, jobs); and, Persistence of savings

Methods of Technical Prognostics Applicable to Embedded Systems

Hlavní cílem dizertace je poskytnutí uceleného pohledu na problematiku technické prognostiky, která nachází uplatnění v tzv. prediktivní údržbě založené na trvalém monitorování zařízení a odhadu úrovně degradace systému či jeho zbývající životnosti a to zejména v oblasti komplexních zařízení a strojů. V současnosti je technická diagnostika poměrně dobře zmapovaná a reálně nasazená na rozdíl od technické prognostiky, která je stále rozvíjejícím se oborem, který ovšem postrádá větší množství reálných aplikaci a navíc ne všechny metody jsou dostatečně přesné a aplikovatelné pro embedded systémy. Dizertační práce přináší přehled základních metod použitelných pro účely predikce zbývající užitné životnosti, jsou zde popsány metriky pomocí, kterých je možné jednotlivé přístupy porovnávat ať už z pohledu přesnosti, ale také i z pohledu výpočetní náročnosti. Jedno z dizertačních jader tvoří doporučení a postup pro výběr vhodné prognostické metody s ohledem na prognostická kritéria. Dalším dizertačním jádrem je představení tzv. částicového filtrovaní (particle filtering) vhodné pro model-based prognostiku s ověřením jejich implementace a porovnáním. Hlavní dizertační jádro reprezentuje případovou studii pro velmi aktuální téma prognostiky Li-Ion baterii s ohledem na trvalé monitorování. Případová studie demonstruje proces prognostiky založené na modelu a srovnává možné přístupy jednak pro odhad doby před vybitím baterie, ale také sleduje možné vlivy na degradaci baterie. Součástí práce je základní ověření modelu Li-Ion baterie a návrh prognostického procesu.The main aim of the thesis is to provide a comprehensive overview of technical prognosis, which is applied in the condition based maintenance, based on continuous device monitoring and remaining useful life estimation, especially in the field of complex equipment and machinery. Nowadays technical prognosis is still evolving discipline with limited number of real applications and is not so well developed as technical diagnostics, which is fairly well mapped and deployed in real systems. Thesis provides an overview of basic methods applicable for prediction of remaining useful life, metrics, which can help to compare the different approaches both in terms of accuracy and in terms of computational/deployment cost. One of the research cores consists of recommendations and guide for selecting the appropriate forecasting method with regard to the prognostic criteria. Second thesis research core provides description and applicability of particle filtering framework suitable for model-based forecasting. Verification of their implementation and comparison is provided. The main research topic of the thesis provides a case study for a very actual Li-Ion battery health monitoring and prognostics with respect to continuous monitoring. The case study demonstrates the prognostic process based on the model and compares the possible approaches for estimating both the runtime and capacity fade. Proposed methodology is verified on real measured data.

A Discussion on Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process and how it relates to uncertainty representation, management, and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function and the true remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for the two while considering prognostics in making critical decisions

Estimating European volatile organic compound emissions using satellite observations of formaldehyde from the Ozone Monitoring Instrument

Emission of non-methane Volatile Organic Compounds (VOCs) to the atmosphere stems from biogenic and human activities, and their estimation is difficult because of the many and not fully understood processes involved. In order to narrow down the uncertainty related to VOC emissions, which negatively reflects on our ability to simulate the atmospheric composition, we exploit satellite observations of formaldehyde (HCHO), an ubiquitous oxidation product of most VOCs, focusing on Europe. HCHO column observations from the Ozone Monitoring Instrument (OMI) reveal a marked seasonal cycle with a summer maximum and winter minimum. In summer, the oxidation of methane and other long-lived VOCs supply a slowly varying background HCHO column, while HCHO variability is dominated by most reactive VOC, primarily biogenic isoprene followed in importance by biogenic terpenes and anthropogenic VOCs. The chemistry-transport model CHIMERE qualitatively reproduces the temporal and spatial features of the observed HCHO column, but display regional biases which are attributed mainly to incorrect biogenic VOC emissions, calculated with the Model of Emissions of Gases and Aerosol from Nature (MEGAN) algorithm. These "bottom-up" or a-priori emissions are corrected through a Bayesian inversion of the OMI HCHO observations. Resulting "top-down" or a-posteriori isoprene emissions are lower than "bottom-up" by 40% over the Balkans and by 20% over Southern Germany, and higher by 20% over Iberian Peninsula, Greece and Italy. We conclude that OMI satellite observations of HCHO can provide a quantitative "top-down" constraint on the European "bottom-up" VOC inventories

Earth Observations and Integrative Models in Support of Food and Water Security

Global food production depends upon many factors that Earth observing satellites routinely measure about water, energy, weather, and ecosystems. Increasingly sophisticated, publicly-available satellite data products can improve efficiencies in resource management and provide earlier indication of environmental disruption. Satellite remote sensing provides a consistent, long-term record that can be used effectively to detect large-scale features over time, such as a developing drought. Accuracy and capabilities have increased along with the range of Earth observations and derived products that can support food security decisions with actionable information. This paper highlights major capabilities facilitated by satellite observations and physical models that have been developed and validated using remotely-sensed observations. Although we primarily focus on variables relevant to agriculture, we also include a brief description of the growing use of Earth observations in support of aquaculture and fisheries

Mapping South African farming sector vulnerability to climate change and variability: A subnational assessment

"This paper analyzes the vulnerability of South African farmers to climate change and variability by developing a vulnerability index and comparing vulnerability indicators across the nine provinces of the country. Nineteen environmental and socio-economic indicators are identified to reflect the three components of vulnerability: exposure, sensitivity, and adaptive capacity. The results of the study show that the region's most vulnerable to climate change and variability also have a higher capacity to adapt to climate change. Furthermore, vulnerability to climate change and variability is intrinsically linked with social and economic development. The Western Cape and Gauteng provinces, which have high levels of infrastructure development, high literacy rates, and low shares of agriculture in total GDP, are relatively low on the vulnerability index. In contrast, the highly vulnerable regions of Limpopo, KwaZulu Natal and the Eastern Cape are characterized by densely populated rural areas, large numbers of small-scale farmers, high dependency on rainfed agriculture and high land degradation. These large differences in the extent of vulnerability among provinces suggest that policy makers should develop region-specific policies and address climate change at the local level." from authors' abstractClimate change, Agriculture, Vulnerability, Adaptive capacity, Exposure, Sensitivity, Climate variability,