988 resultados para sustainability evaluation


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Public road authorities have a key responsibility in driving initiatives for reducing greenhouse gas (GHG) emissions in the road construction project lifecycle. A coherent and efficient chain of procurement processes and methods is needed to convert green policies into tangible actions that capture the potential for GHG reduction. Yet, many infrastructure clients lack developed methodologies regarding green procurement practices. Designing more efficient solutions for green procurement requires an evaluation of the current initiatives and stages of development. A mapping of the current GHG reduction initiatives in Australian public road procurement is presented in this paper. The study includes the five largest Australian state road authorities, which cover 94% of the total 817,089 km of Australian main roads (not local) and account for 96% of the total A$13 billion annual major road construction and maintenance expenditure. The state road authorities’ green procurement processes and tools are evaluated based on interviews and a review of documents. Altogether 12 people, comprising 1-3 people of each organisation, participated in the interviews and provided documents. An evaluation matrix was developed for mapping the findings across the lifecycle of road construction project delivery. The results show how Australian state road authorities drive decisions with an impact on GHG emissions on the strategic planning phase, project development phase, and project implementation phase. The road authorities demonstrate varying levels of advancement in their green procurement methodologies. Six major gaps in the current green procurement processes are identified and, respectively, six recommendations for future research and development are suggested. The greatest gaps remain in the project development phase, which has a critical role in fixing the project (GHG reduction) goals, identifying risks and opportunities, and selecting the contractor to deliver the project. Specifically, the role of mass-haul optimisation as a part of GHG minimisation was reviewed, and mass-haul management was found to be an underutilised element with GHG reduction potential.

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This study proposes a framework of a model-based hot spot identification method by applying full Bayes (FB) technique. In comparison with the state-of-the-art approach [i.e., empirical Bayes method (EB)], the advantage of the FB method is the capability to seamlessly integrate prior information and all available data into posterior distributions on which various ranking criteria could be based. With intersection crash data collected in Singapore, an empirical analysis was conducted to evaluate the following six approaches for hot spot identification: (a) naive ranking using raw crash data, (b) standard EB ranking, (c) FB ranking using a Poisson-gamma model, (d) FB ranking using a Poisson-lognormal model, (e) FB ranking using a hierarchical Poisson model, and (f) FB ranking using a hierarchical Poisson (AR-1) model. The results show that (a) when using the expected crash rate-related decision parameters, all model-based approaches perform significantly better in safety ranking than does the naive ranking method, and (b) the FB approach using hierarchical models significantly outperforms the standard EB approach in correctly identifying hazardous sites.

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Despite of a significant contribution of transport sector in the global economy and society, it is one of the largest sources of global energy consumption, green house gas emissions and environmental pollutions. A complete look onto the whole life cycle environmental inventory of this sector will be helpful to generate a holistic understanding of contributory factors causing emissions. Previous studies were mainly based on segmental views which mostly compare environmental impacts of different modes of transport, but very few consider impacts other than the operational phase. Ignoring the impacts of non-operational phases, e.g., manufacture, construction, maintenance, may not accurately reflect total contributions on emissions. Moreover an integrated study for all motorized modes of road transport is also needed to achieve a holistic estimation. The objective of this study is to develop a component based life cycle inventory model which considers impacts of both operational and non-operational phases of the whole life as well as different transport modes. In particular, the whole life cycle of road transport has been segmented into vehicle, infrastructure, fuel and operational components and inventories have been conducted on each component. The inventory model has been demonstrated using the road transport of Singapore. Results show that total life cycle green house gas emissions from the road transport sector of Singapore is 7.8 million tons per year, among which operational phase and non-operational phases contribute about 55% and about 45%, respectively. Total amount of criteria air pollutants are 46, 8.5, 33.6, 13.6 and 2.6 thousand tons per year for CO, SO2, NOx, VOC and PM10, respectively. From the findings, it can be deduced that stringent government policies on emission control measures have a significant impact on reducing environmental pollutions. In combating global warming and environmental pollutions the promotion of public transport over private modes is an effective sustainable policy.

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OBJECTIVE: To evaluate a universal obesity prevention intervention, which commenced at infant age 4-6 months, using outcome data assessed 6-months after completion of the first of two intervention modules and 9 months from baseline. DESIGN: Randomised controlled trial of a community-based early feeding intervention. SUBJECTS AND METHODS: 698 first-time mothers (mean age 30±5 years) with healthy term infants (51% male) aged 4.3±1.0 months at baseline. Mothers and infants were randomly allocated to self-directed access to usual care or to attend two group education modules, each delivered over three months, that provided anticipatory guidance on early feeding practices. Outcome data reported here were assessed at infant age 13.7±1.3 months. Anthropometrics were expressed as z-scores (WHO reference). Rapid weight gain was defined as change in weight-for-age z-score (WAZ) > +0.67. Maternal feeding practices were assessed via self-administered questionnaire. RESULTS: There were no differences according to group allocation on key maternal and infant characteristics. At follow up (n=598 [86%]) the intervention group infants had lower BMIZ (0.42±0.85 vs 0.23±0.93, p=0.009) and infants in the control group were more likely to show rapid weight gain from baseline to follow up (OR=1.5 CI95%1.1-2.1, p=0.014). Mothers in the control group were more likely to report using non- responsive feeding practices that fail to respond to infant satiety cues such as encouraging eating by using food as a reward (15% vs 4%, p=0.001) or using games ( 67% vs 29%, p<0.001). CONCLUSIONS: These results provide early evidence that anticipatory guidance targeting the ‘when, what and how’ of solid feeding can be effective in changing maternal feeding practices and, at least in the short term, reducing anthropometric indicators of childhood obesity risk. Analyses of outcomes at later ages are required to determine if these promising effects can be sustained.

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This series of paper examines industrial issues from a nonprofit management perspective.

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IEEE 802.11p is the new standard for inter-vehicular communications (IVC) using the 5.9 GHz frequency band; it is planned to be widely deployed to enable cooperative systems. 802.11p uses and performance have been studied theoretically and in simulations over the past years. Unfortunately, many of these results have not been confirmed by on-tracks experimentation. In this paper, we describe field trials of 802.11p technology with our test vehicles. Metrics such as maximum range, latency and frame loss are examined.

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Objective The aim of this study was to demonstrate the potential of near-infrared (NIR) spectroscopy for categorizing cartilage degeneration induced in animal models. Method Three models of osteoarthritic degeneration were induced in laboratory rats via one of the following methods: (i) menisectomy (MSX); (ii) anterior cruciate ligament transaction (ACLT); and (iii) intra-articular injection of mono-ido-acetete (1 mg) (MIA), in the right knee joint, with 12 rats per model group. After 8 weeks, the animals were sacrificed and tibial knee joints were collected. A custom-made nearinfrared (NIR) probe of diameter 5 mm was placed on the cartilage surface and spectral data were acquired from each specimen in the wavenumber range 4 000 – 12 500 cm−1. Following spectral data acquisition, the specimens were fixed and Safranin–O staining was performed to assess disease severity based on the Mankin scoring system. Using multivariate statistical analysis based on principal component analysis and partial least squares regression, the spectral data were then related to the Mankinscores of the samples tested. Results Mild to severe degenerative cartilage changes were observed in the subject animals. The ACLT models showed mild cartilage degeneration, MSX models moderate, and MIA severe cartilage degenerative changes both morphologically and histologically. Our result demonstrate that NIR spectroscopic information is capable of separating the cartilage samples into different groups relative to the severity of degeneration, with NIR correlating significantly with their Mankinscore (R2 = 88.85%). Conclusion We conclude that NIR is a viable tool for evaluating articularcartilage health and physical properties such as change in thickness with degeneration.