What factors influence mitigative capacity ?

Cet article s'intéresse aux déterminants de la capacité à atténuer le changement climatique. Ceux-ci ont été élaborés initialement dans un papier de Yohe puis dans le troisième rapport d'évaluation du GIEC. Après avoir revisité la définition de la capacité à atténuer le changement climatique, nous identifions trois groupes de facteurs influençant de façon croisée cette capacité : des facteurs économiques, technologiques et institutionnels. Au niveau économique, ce sont à la fois le revenu, le coût de réduction des émissions et le coût d'opportunité lié aux réductions qui forgent la capacité d'atténuation. Du côté technologique, c'est la capacité à absorber ou à développer des technologies peu émettrices de gaz à effet de serre qui est déterminante. Enfin, au niveau institutionnel, l'efficacité de la régulation gouvernementale, la transparence des règles de marché, une main d'œuvre qualifiée et une sensibilisation de la population sont des éléments clés. Notre analyse est menée à la fois qualitativement et quantitativement. Elle permet de montrer comment les facteurs influençant la capacité d'atténuation varient d'un pays à l'autrechangement climatique ; capacité d'atténuation ; politique environnementale

Building Energy Model Development for Retrofit Homes

Based on previous research conducted by Pacific Northwest National Laboratory and Florida Solar Energy Center providing technical assistance to implement 22 deep energy retrofits across the nation, 6 homes were selected in Florida and Texas for detailed post-retrofit energy modeling to assess realized energy savings (Chandra et al, 2012). However, assessing realized savings can be difficult for some homes where pre-retrofit occupancy and energy performance are unknown. Initially, savings had been estimated using a HERS Index comparison for these homes. However, this does not account for confounding factors such as occupancy and weather. This research addresses a method to more reliably assess energy savings achieved in deep energy retrofits for which pre-retrofit utility bills or occupancy information in not available. A metered home, Riverdale, was selected as a test case for development of a modeling procedure to account occupancy and weather factors, potentially creating more accurate estimates of energy savings. This “true up” procedure was developed using Energy Gauge USA software and post-retrofit homeowner information and utility bills. The 12 step process adjusts the post-retrofit modeling results to correlate with post-retrofit utility bills and known occupancy information. The “trued” post retrofit model is then used to estimate pre-retrofit energy consumption by changing the building efficiency characteristics to reflect the pre-retrofit condition, but keeping all weather and occupancy-related factors the same. This creates a pre-retrofit model that is more comparable to the post-retrofit energy use profile and can improve energy savings estimates. For this test case, a home for which pre- and post- retrofit utility bills were available was selected for comparison and assessment of the accuracy of the “true up” procedure. Based on the current method, this procedure is quite time intensive. However, streamlined processing spreadsheets or incorporation into existing software tools would improve the efficiency of the process. Retrofit activity appears to be gaining market share, and this would be a potentially valuable capability with relevance to marketing, program management, and retrofit success metrics

Does the availability of snack foods in supermarkets vary internationally?

BackgroundCross-country differences in dietary behaviours and obesity rates have been previously reported. Consumption of energy-dense snack foods and soft drinks are implicated as contributing to weight gain, however little is known about how the availability of these items within supermarkets varies internationally. This study assessed variations in the display of snack foods and soft drinks within a sample of supermarkets across eight countries.MethodsWithin-store audits were used to evaluate and compare the availability of potato chips (crisps), chocolate, confectionery and soft drinks. Displays measured included shelf length and the proportion of checkouts and end-of-aisle displays containing these products. Audits were conducted in a convenience sample of 170 supermarkets across eight developed nations (Australia, Canada, Denmark, Netherlands, New Zealand, Sweden, United Kingdom (UK), and United States of America (US)).ResultsThe mean total aisle length of snack foods (adjusted for store size) was greatest in supermarkets from the UK (56.4 m) and lowest in New Zealand (21.7 m). When assessed by individual item, the greatest aisle length devoted to chips, chocolate and confectionery was found in UK supermarkets while the greatest aisle length dedicated to soft drinks was in Australian supermarkets. Only stores from the Netherlands (41%) had less than 70% of checkouts featuring displays of snack foods or soft drinks.ConclusionWhilst between-country variations were observed, overall results indicate high levels of snack food and soft drinks displays within supermarkets across the eight countries. Exposure to snack foods is largely unavoidable within supermarkets, increasing the likelihood of purchases and particularly those made impulsively.<br /

Beyond Blackboards: Engaging Underserved Middle School Students in Engineering

Beyond Blackboards is an inquiry-centered, after-school program designed to enhance middle school students’ engagement with engineering through design-based experiences focused on the 21st Century Engineering Challenges. Set within a predominantly lowincome, majority-minority community, our study aims to investigate the impact of Beyond Blackboards on students’ interest in and understanding of engineering, as well as their ability to align their educational and career plans. We compare participants’ and nonparticipants’ questionnaire responses before the implementation and at the end of the program’s first academic year. Statistically significant findings indicate a school-wide increase in students’ interest in engineering careers, supporting a shift in school culture. However, only program participants showed increased enjoyment of design-based strategies, understanding of what engineers do, and awareness of the steps for preparing for an engineering career. These quantitative findings are supported by qualitative evidence from participant focus groups highlighting the importance of mentors in shaping students’ awareness of opportunities within engineering

Actual and Estimated Energy Savings Comparison for Deep Energy Retrofits in the Pacific Northwest

Seven homes from the Pacific Northwest were selected to evaluate the differences between estimated and actual energy savings achieved from deep energy retrofits. The energy savings resulting from these retrofits were estimated, using energy modeling software, to save at least 30% on a whole-house basis. The modeled pre-retrofit energy use was trued against monthly utility bills. After the retrofits were completed, each of the homes was extensively monitored, with the exception of one home which was monitored pre-retrofit. This work is being conducted by Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy Building Technologies Program as part of the Building America Program. This work found many discrepancies between actual and estimated energy savings and identified the potential causes for the discrepancies. The differences between actual energy use and modeled energy use also suggest improvements to improve model accuracy. The difference between monthly whole-house actual and estimated energy savings ranged from 75% more energy saved than predicted by the model to 16% less energy saved for all the monitored homes. Similarly, the annual energy savings difference was between 36% and -14%, which was estimated based on existing monitored savings because an entire year of data is not available. Thus, on average, for all six monitored homes the actual energy use is consistently less than estimates, indicating home owners are saving more energy than estimated. The average estimated savings for the eight month monitoring period is 43%, compared to an estimated savings average of 31%. Though this average difference is only 12%, the range of inaccuracies found for specific end-uses is far greater and are the values used to directly estimate energy savings from specific retrofits. Specifically, the monthly post-retrofit energy use differences for specific end-uses (i.e., heating, cooling, hot water, appliances, etc.) ranged from 131% under-predicted to 77% over-predicted by the model with respect to monitored energy use. Many of the discrepancies were associated with occupant behavior which influences energy use, dramatically in some cases, actual versus modeled weather differences, modeling input limitations, and complex homes that are difficult to model. The discrepancy between actual and estimated energy use indicates a need for better modeling tools and assumptions. Despite the best efforts of researchers, the estimated energy savings are too inaccurate to determine reliable paybacks for retrofit projects. While the monitored data allows researchers to understand why these differences exist, it is not cost effective to monitor each home with the level of detail presented here. Therefore an appropriate balance between modeling and monitoring must be determined for more widespread application in retrofit programs and the home performance industry. Recommendations to address these deficiencies include: (1) improved tuning process for pre-retrofit energy use, which currently utilized broad-based monthly utility bills; (2) developing simple occupant-based energy models that better address the many different occupant types and their impact on energy use; (3) incorporating actual weather inputs to increase accuracy of the tuning process, which uses utility bills from specific time period; and (4) developing simple, cost-effective monitoring solutions for improved model tuning

Actual and Estimated Energy Savings Comparison for Deep Energy Retrofits in the Pacific Northwest

Seven homes from the Pacific Northwest were selected to evaluate the differences between estimated and actual energy savings achieved from deep energy retrofits. The energy savings resulting from these retrofits were estimated, using energy modeling software, to save at least 30% on a whole-house basis. The modeled pre-retrofit energy use was trued against monthly utility bills. After the retrofits were completed, each of the homes was extensively monitored, with the exception of one home which was monitored pre-retrofit. This work is being conducted by Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy Building Technologies Program as part of the Building America Program. This work found many discrepancies between actual and estimated energy savings and identified the potential causes for the discrepancies. The differences between actual energy use and modeled energy use also suggest improvements to improve model accuracy. The difference between monthly whole-house actual and estimated energy savings ranged from 75% more energy saved than predicted by the model to 16% less energy saved for all the monitored homes. Similarly, the annual energy savings difference was between 36% and -14%, which was estimated based on existing monitored savings because an entire year of data is not available. Thus, on average, for all six monitored homes the actual energy use is consistently less than estimates, indicating home owners are saving more energy than estimated. The average estimated savings for the eight month monitoring period is 43%, compared to an estimated savings average of 31%. Though this average difference is only 12%, the range of inaccuracies found for specific end-uses is far greater and are the values used to directly estimate energy savings from specific retrofits. Specifically, the monthly post-retrofit energy use differences for specific end-uses (i.e., heating, cooling, hot water, appliances, etc.) ranged from 131% under-predicted to 77% over-predicted by the model with respect to monitored energy use. Many of the discrepancies were associated with occupant behavior which influences energy use, dramatically in some cases, actual versus modeled weather differences, modeling input limitations, and complex homes that are difficult to model. The discrepancy between actual and estimated energy use indicates a need for better modeling tools and assumptions. Despite the best efforts of researchers, the estimated energy savings are too inaccurate to determine reliable paybacks for retrofit projects. While the monitored data allows researchers to understand why these differences exist, it is not cost effective to monitor each home with the level of detail presented here. Therefore an appropriate balance between modeling and monitoring must be determined for more widespread application in retrofit programs and the home performance industry. Recommendations to address these deficiencies include: (1) improved tuning process for pre-retrofit energy use, which currently utilized broad-based monthly utility bills; (2) developing simple occupant-based energy models that better address the many different occupant types and their impact on energy use; (3) incorporating actual weather inputs to increase accuracy of the tuning process, which uses utility bills from specific time period; and (4) developing simple, cost-effective monitoring solutions for improved model tuning

Frameshift mutation hotspot identified in Smith-Magenis syndrome: case report and review of literature

Smith-Magenis syndrome (SMS) is a complex syndrome involving intellectual disabilities, sleep disturbance, behavioural problems, and a variety of craniofacial, skeletal, and visceral anomalies. While the majority of SMS cases harbor an ~3.5 Mb common deletion on 17p11.2 that encompasses the retinoic acid induced-1 (RAI1) gene, some patients carry small intragenic deletions or point mutations in RAI1. We present data on two cases of Smith-Magenis syndrome with mutation of RAI1. Both cases are phenotypically consistent with SMS and RAI1 mutation but also have other anomalies not previously reported in SMS, including spontaneous pneumothoraces. These cases also illustrate variability in the SMS phenotype not previously shown for RAI1 mutation cases, including hearing loss, absence of self-abusive behaviours, and mild global delays. Sequencing of RAI1 revealed mutation of the same heptameric C-tract (CCCCCCC) in exon 3 in both cases (c.3103delC one case and and c.3103insC in the other), resulting in frameshift mutations. Of the seven reported frameshift mutations occurring in poly C-tracts in RAI1, four cases (~57%) occur at this heptameric C-tract. Collectively, these results indicate that this heptameric C-tract is a preferential hotspot for single nucleotide insertion/deletions (SNindels) and therefore, should be considered a primary target for analysis in patients suspected for mutations in RAI1. We expect that as more patients are sequenced for mutations in RAI1, the incidence of frameshift mutations in this hotspot will become more evident

Advances in the understanding, detection and management of equine strangles

Summary: Streptococcus equi subspecies equi (S. equi) is the causative organism of the upper respiratory disease of equids, strangles, characterised by pyrexia, lymphadenopathy and mucopurulent nasal discharge. Strangles was first reported over 750 years ago and continues to be of significance in equine populations across the globe. This review discusses how S. equi has adapted, the clinical manifestation of strangles, and how clinicians and caregivers can tackle the disease in the future. S. equi evolved from the commensal, and occasionally opportunistic pathogen, Streptococcus equi subspecies zooepidemicus refining its capabilities as it became host restricted. The success of S. equi can be attributed to its ability to cause both acute and persistent infection, the latter occurring in about 10% of those infected. In this carrier state, S. equi persists in the guttural pouch without causing clinical signs, intermittently shedding into the environment, and encountering naïve animals. Insight into the S. equi genome and lifestyle has led to advances in diagnostic assays and the development of a safe and efficacious recombinant‐fusion vaccine, giving clinicians and caregivers the tools to better combat this infection. Alongside rigorous biosecurity protocols and pragmatic control measures such as screening new arrivals for exposure and carrier status, these new technologies demonstrate that strangles can be an increasingly preventable infection

Aspects of designing and evaluating seasonal-to-interannual Arctic sea-ice prediction systems

Using lessons from idealised predictability experiments, we discuss some issues and perspectives on the design of operational seasonal to inter-annual Arctic sea-ice prediction systems. We first review the opportunities to use a hierarchy of different types of experiment to learn about the predictability of Arctic climate. We also examine key issues for ensemble system design, such as: measuring skill, the role of ensemble size and generation of ensemble members. When assessing the potential skill of a set of prediction experiments, using more than one metric is essential as different choices can significantly alter conclusions about the presence or lack of skill. We find that increasing both the number of hindcasts and ensemble size is important for reliably assessing the correlation and expected error in forecasts. For other metrics, such as dispersion, increasing ensemble size is most important. Probabilistic measures of skill can also provide useful information about the reliability of forecasts. In addition, various methods for generating the different ensemble members are tested. The range of techniques can produce surprisingly different ensemble spread characteristics. The lessons learnt should help inform the design of future operational prediction systems