What energy management practice can learn from research on energy cultures?

Purpose – This investigation aims to reframe the sizeable literature on barriers and drivers for energy efficiency measures and the phenomenon of the energy efficiency gap. We identified a gap between academic methods and industrial needs as well as a neglect of the cultural di-mension, despite its considerable impact. Based on this insight, the purpose of this paper is to integrate all of the various influences on industrial energy behavior previously identified in the literature in a refined energy cultures framework. Design/methodology/approach – This paper includes a systematic literature review of re-search in the field of energy management, energy efficiency, and cultural aspects within barri-ers and drivers of energy behavior. We selected and refined an existing energy cultures framework for the industrial context. To meet industrial needs, we applied an ontology map-ping of its core elements onto an international standard common for industrial energy man-agement practice. Findings – First, we present a refined framework for industrial energy cultures incorporating past barriers and drivers as factors. The framework enables an evaluation of attitude and be-havioral aspects, underlying technologies, organizational culture and actions related to energy as a system of interdependencies. Second, the factors are ranked based on number of appear-ances and empirical metadata. Economic aspects such as ‘Purchase, installment, and hidden costs’, ‘General investment and risk behavior’, and ‘Regulatory conditions’ are the highest ranked factors, but ‘Existing knowledge about EEM’, ‘Hierarchy approach: Top down’, and ‘Environmental concerns’ follow closely and represent cultural aspects which are still under-rated. Third, while illustrating a successful mapping onto a standardized process of continuous improvement, we also argue for heightened an academia-practice efforts. Social implications – Targeting the energy efficiency gap is an essential part of the sustainable development goals. The refined energy cultures framework allows for a better understanding of the industrial energy behaviors that are responsible for a significant share of a company’s success. The introduction of energy cultures serves as a starting point for future scholarly re-search within sustainability management accounting. Originality/value – The investigation combines existing research streams, their concepts, and their results about cultural aspects related to energy efficiency for both academics and practi-tioners. This review is the first to capture all of the various factors analyzed in academic litera-ture using the energy cultures framework as a basis. We add to the theoretical development of that framework with its application to the industrial context. This was identified as a gap. Its refinement helps to holistically understand barriers and drivers of industrial energy efficiency measures in order to support its practical implementation

Uncertainty in life cycle costing for long-range infrastructure. Part I: leveling the playing field to address uncertainties

Purpose Life cycle costing (LCC) is a state-of-the-art method to analyze investment decisions in infrastructure projects. However, uncertainties inherent in long-term planning question the credibility of LCC results. Previous research has not systematically linked sources and methods to address this uncertainty. Part I of this series develops a framework to collect and categorize different sources of uncertainty and addressing methods. This systematization is a prerequisite to further analyze the suitability of methods and levels the playing field for part II. Methods Past reviews have dealt with selected issues of uncertainty in LCC. However, none has systematically collected uncertainties and linked methods to address them. No comprehensive categorization has been published to date. Part I addresses these two research gaps by conducting a systematic literature review. In a rigorous four-step approach, we first scrutinized major databases. Second, we performed a practical and methodological screening to identify in total 115 relevant publications, mostly case studies. Third, we applied content analysis using MAXQDA. Fourth, we illustrated results and concluded upon the research gaps. Results and discussion We identified 33 sources of uncertainty and 24 addressing methods. Sources of uncertainties were categorized according to (i) its origin, i.e., parameter, model, and scenario uncertainty and (ii) the nature of uncertainty, i.e., aleatoric or epistemic uncertainty. The methods to address uncertainties were classified into deterministic, probabilistic, possibilistic, and other methods. With regard to sources of uncertainties, lack of data and data quality was analyzed most often. Most uncertainties having been discussed were located in the use stage. With regard to methods, sensitivity analyses were applied most widely, while more complex methods such as Bayesian models were used less frequently. Data availability and the individual expertise of LCC practitioner foremost influence the selection of methods. Conclusions This article complements existing research by providing a thorough systematization of uncertainties in LCC. However, an unambiguous categorization of uncertainties is difficult and overlapping occurs. Such a systemizing approach is nevertheless necessary for further analyses and levels the playing field for readers not yet familiar with the topic. Part I concludes the following: First, an investigation about which methods are best suited to address a certain type of uncertainty is still outstanding. Second, an analysis of types of uncertainty that have been insufficiently addressed in previous LCC cases is still missing. Part II will focus on these research gaps

Life cycle assessment of carbon concrete composites: a circular economy path beyond climate mitigation?

Sustainable construction and materials play an ever-important role to stay within our planetary boundaries. In support, innovative carbon concrete composites (CCC) promise significant raw material savings by integral design. We aim to illustrate current environmental hotspots and a feasible recycling scenario of CCC that meets circularity requirements. We modelled a cradle-to-grave life cycle assessment for two potential building structural applications (sandwich wall, ceiling reinforcement) made of CCC. We based our recycling scenario on previously conducted large-scale experiments. Results show a relative larger energy intensity and abiotic depletion of fossil fuels for variants of CCC but lower global warming. Yet, recycling is, second to embodied emissions of basic materials, the driving force of total environmental impacts. The presented recycling path (demolition, pyrolysis for carbon fabric, reuse in fiber fleece) offers less "green credentials" than steel

Ökonomisch-ökologischer Nettoeffekt der Elektromobilität im öffentlichen Personennahverkehr

Im Rahmen einer Elektromobilitäts-Fallstudie kombinieren wir zwei lebenszyklusbasierte Methoden und veranschaulichen die Ergebnisse zur Kommunikations- und Entscheidungsunterstützung mittels der Methode des ökonomisch-ökologischen Nettoeffekts. Die Ergebnisse zeigen, dass Elektrofahrzeuge im Vergleich zur EURO6-Dieselfahrzeugen erst in langer Frist ökonomisch und ökologisch wettbewerbsfähig sind.Building on a case study on electric mobility, we integrate two life cycle methods and visualize the results for communication and decision-support using the economic environmental trade-off. Results suggest that in comparison to EURO6 diesel vehicles electric vehicles are only in the long run economically and environmentally competitive

Greener, cheaper, or more sustainable: reviewing sustainability assessments of maintenance strategies of concrete structures

Concrete is the most widely used material in construction and infrastructure, and is often reinforced by steel to improve tensile strength. Despite its enduring popularity, the material’s inherent weaknesses – namely corrosion damage and material fatigue – combined with ageing infrastructure, poses a challenge to both decision-makers and civil engineers to optimise sustainable infrastructure services. This article explores and synthesises the sustainable potential of maintenance and repair methods using concrete and cement-based composite materials. We draw on published case studies where sustainability assessments have been applied within this field. We also included cases that describe themselves as a type of sustainability assessment, but lack the assessment of all dimensions. Our research aims, firstly, to identify what maintenance interventions were assessed by means of sustainability criteria. Second, it explores the basic conceptual understanding which underlies each sustainability assessment. Third, it analyses the many methodological choices made for system boundaries, selection of indicators, or forms of aggregation. We have applied a systematic literature review to develop evidence-based management knowledge; this shows that current sustainability assessments are diverse regarding system boundaries, their scope, levels of detail, and overall quality. Although there is a trend towards more holistic types of assessment, environmental and economic sustainability dominated our sample, with global warming and energy consumed being most often reported. External costs, if included in the assessment, drive the overall economic score, while life cycle sustainability assessment is applied to only three cases. The most critical and challenging issues were shown to be the long-term orientation of maintenance measures and the complexity of undertaking a truly holistic sustainability assessment. To that end, we have stimulated scholarly discussion on further methodological progress to align with the good practices identified in our review, and call for greater application of these methods in the construction industry

Uncertainty in life cycle costing for long-range infrastructure. Part II: guidance and suitability of applied methods to address uncertainty

Life cycle costing (LCC) is the state-of-the-art method to economically evaluate long-term projects over their life spans. However, uncertainty in long-range planning raises concerns about LCC results. In Part I of this series, we developed a holistic framework of the different types of uncertainty in infrastructure LCCs. We also collected methods to address these uncertainties. The aim of Part II is to evaluate the suitability of methods to cope with uncertainty in LCC. Part I addressed two research gaps. It presented a systematic collection of uncertainties and methods in LCC and, furthermore, provided a holistic categorization of both. However, Part I also raised new issues. First, a combined analysis of sources and methods is still outstanding. Such an investigation would reveal the suitability of different methods to address a certain type of uncertainty. Second, what has not been assessed so far is what types of uncertainty are insufficiently addressed in LCC. This would be a feature to improve accuracy of LCC results within LCC, by suggesting options to better cope with uncertainty. To address these research gaps, we conducted a systematic literature review. Part II analyzed the suitability of methods to address uncertainties. The suitability depends on data availability, type of data (tangible, intangible, random, non-random), screened hotspots, and tested modeling specifications. We identified types of uncertainties and methods that have been insufficiently addressed. The methods include probabilistic modeling such as design of experiment or subset simulation and evolutionary algorithm and Bayesian modeling such as the Bayesian latent Markov decision process. Subsequently, we evaluated learning potential from other life cycle assessment (LCA) and life cycle sustainability assessment (LCSA). This analysis revealed 28 possible applications that have not yet been used in LCC. Lastly, we developed best practices for LCC practitioners. This systematic review complements prior research on uncertainty in LCC for infrastructure, as laid out in Part I. Part II concludes that all relevant methods to address uncertainty are currently applied in LCC. Yet, the level of application is different. Moreover, not all methods are equally suited to address different categories of uncertainty. This review offers guidance on what to do for each source and type of uncertainty. It illustrates how methods can address both based on current practice in LCC, LCA, and LCSA. The findings of Part II encourage a dialog between practitioners of LCC, LCA, and LCSA to advance research and practice in uncertainty analysis

Accuracy of dermatoscopy for the diagnosis of nonpigmented cancers of the skin

BACKGROUND: Nonpigmented skin cancer is common, and diagnosis with the unaided eye is error prone. OBJECTIVE: To investigate whether dermatoscopy improves the diagnostic accuracy for nonpigmented (amelanotic) cutaneous neoplasms. METHODS: We collected a sample of 2072 benign and malignant neoplastic lesions and inflammatory conditions and presented close-up images taken with and without dermatoscopy to 95 examiners with different levels of experience. RESULTS: The area under the curve was significantly higher with than without dermatoscopy (0.68 vs 0.64, P < .001). Among 51 possible diagnoses, the correct diagnosis was selected in 33.1% of cases with and 26.4% of cases without dermatoscopy (P < .001). For experts, the frequencies of correct specific diagnoses of a malignant lesion improved from 40.2% without to 51.3% with dermatoscopy. For all malignant neoplasms combined, the frequencies of appropriate management strategies increased from 78.1% without to 82.5% with dermatoscopy. LIMITATIONS: The study deviated from a real-life clinical setting and was potentially affected by verification and selection bias. CONCLUSIONS: Dermatoscopy improves the diagnosis and management of nonpigmented skin cancer and should be used as an adjunct to examination with the unaided eye

Expert-Level diagnosis of nonpigmented skin cancer by combined convolutional neural networks

IMPORTANCE Convolutional neural networks (CNNs) achieve expert-level accuracy in the diagnosis of pigmented melanocytic lesions. However, the most common types of skin cancer are nonpigmented and nonmelanocytic, and are more difficult to diagnose.OBJECTIVE To compare the accuracy of a CNN-based classifier with that of physicians with different levels of experience.DESIGN, SETTING, AND PARTICIPANTS A CNN-based classification model was trained on 7895 dermoscopic and 5829 close-up images of lesions excised at a primary skin cancer clinic between January 1, 2008, and July 13, 2017, for a combined evaluation of both imaging methods. The combined CNN (cCNN) was tested on a set of 2072 unknown cases and compared with results from 95 human raters who were medical personnel, including 62 board-certified dermatologists, with different experience in dermoscopy.MAIN OUTCOMES AND MEASURES The proportions of correct specific diagnoses and the accuracy to differentiate between benign and malignant lesions measured as an area under the receiver operating characteristic curve served as main outcome measures.RESULTS Among 95 human raters (51.6% female; mean age, 43.4 years; 95% CI, 41.0-45.7 years), the participants were divided into 3 groups (according to years of experience with dermoscopy): beginner raters (10 years). The area under the receiver operating characteristic curve of the trained cCNN was higher than human ratings (0.742; 95% CI, 0.729-0.755 vs 0.695; 95% CI, 0.676-0.713; P < .001). The specificity was fixed at the mean level of human raters (51.3%), and therefore the sensitivity of the cCNN (80.5%; 95% CI, 79.0%-82.1%) was higher than that of human raters (77.6%; 95% CI, 74.7%-80.5%). The cCNN achieved a higher percentage of correct specific diagnoses compared with human raters (37.6%; 95% CI, 36.6%-38.4% vs 33.5%; 95% CI, 31.5%-35.6%; P = .001) but not compared with experts (37.3%; 95% CI, 35.7%-38.8% vs 40.0%; 95% CI, 37.0%-43.0%; P = .18).CONCLUSIONS AND RELEVANCE Neural networks are able to classify dermoscopic and close-up images of nonpigmented lesions as accurately as human experts in an experimental setting

Local or systemic treatment for New World cutaneous leishmaniasis? Re-evaluating the evidence for the risk of mucosal leishmaniasis

This review addresses the question of whether the risk of developing mucosal leishmaniasis (ML) warrants systemic treatment in all patients with New World cutaneous leishmaniasis (CL) or whether local treatment might be an acceptable alternative. The risk of patients with New World CL developing ML after the initial infection has been the main argument for systemic treatment. However, this statement needs re-evaluation and consideration of all the available data. The putative benefit of preventing ML should outweigh the toxicity of systemic antileishmanial therapy. To assess the need for and risk of systemic treatment the following factors were reviewed: the incidence and prevalence of ML in endemic populations and in travellers; the severity of mucosal lesions; the efficacy of current options to treat ML; the toxicity and, to a lesser extent, the costs of systemic treatment; the risk of developing ML after local treatment; and the strengths and limitations of current estimates of the risk of developing ML in different situations. Local treatment might be considered as a valuable treatment option for travellers suffering from New World CL, provided that there are no risk factors for developing ML such as multiple lesions, big lesions (>4 cm(2)), localisation of the lesion on the head or neck, immunosuppression or acquisition of infection in the high Andean countries, notably Bolivi