Monitoring growth of hard corals as performance indicators for coral reefs

Digital videophotography, computer image analysis and physical measurements have been used to monitor sedimentation rates, coral cover, genera richness, rugosity and estimated recruitment dates of massive corals at three different sites in the Wakatobi Marine National Park, Indonesia, and on the reefs around Discovery Bay, Jamaica. Semi-structured interviews with key stakeholders in the Wakatobi Marine National Park indicated that coral mining was extensively practised, and is responsible for the absence of large non-branching corals on the Sampela reef Blast fishing is also practised in the Wakatobi Marine Park, and the authors, together with students, showed that blast fishing resulted in coral bleaching and not mortality of two Porites lutea colonies. In addition, we showed that monitoring of bleaching in Porites colonies induced by blast fishing could be a useful way of monitoring blast fishing practices in susceptible areas in the Indo-Pacific. The techniques used in this study are appropriate for use by volunteers with sufficient training, and provide excellent projects for dissertation students reading undergraduate degrees.

Key performance indicators (KPIs) and priority setting in using the multi-attribute approach for assessing sustainable intelligent buildings

The main objectives of this paper are to: firstly, identify key issues related to sustainable intelligent buildings (environmental, social, economic and technological factors); develop a conceptual model for the selection of the appropriate KPIs; secondly, test critically stakeholder's perceptions and values of selected KPIs intelligent buildings; and thirdly develop a new model for measuring the level of sustainability for sustainable intelligent buildings. This paper uses a consensus-based model (Sustainable Built Environment Tool- SuBETool), which is analysed using the analytical hierarchical process (AHP) for multi-criteria decision-making. The use of the multi-attribute model for priority setting in the sustainability assessment of intelligent buildings is introduced. The paper commences by reviewing the literature on sustainable intelligent buildings research and presents a pilot-study investigating the problems of complexity and subjectivity. This study is based upon a survey perceptions held by selected stakeholders and the value they attribute to selected KPIs. It is argued that the benefit of the new proposed model (SuBETool) is a ‘tool’ for ‘comparative’ rather than an absolute measurement. It has the potential to provide useful lessons from current sustainability assessment methods for strategic future of sustainable intelligent buildings in order to improve a building's performance and to deliver objective outcomes. Findings of this survey enrich the field of intelligent buildings in two ways. Firstly, it gives a detailed insight into the selection of sustainable building indicators, as well as their degree of importance. Secondly, it tesst critically stakeholder's perceptions and values of selected KPIs intelligent buildings. It is concluded that the priority levels for selected criteria is largely dependent on the integrated design team, which includes the client, architects, engineers and facilities managers.

Building operational energy consumption of Chongqing and its exergy assessment

Building energy consumption(BEC) accounting and assessment is fundamental work for building energy efficiency(BEE) development. In existing Chinese statistical yearbook, there is no specific item for BEC accounting and relevant data are separated and mixed with other industry consumption. Approximate BEC data can be acquired from existing energy statistical yearbook. For BEC assessment, caloric values of different energy carriers are adopted in energy accounting and assessment field. This methodology obtained much useful conclusion for energy efficiency development. While the traditional methodology concerns only on the energy quantity, energy classification issue is omitted. Exergy methodology is put forward to assess BEC. With the new methodology, energy quantity and quality issues are both concerned in BEC assessment. To illustrate the BEC accounting and exergy assessment, a case of Chongqing in 2004 is shown. Based on the exergy analysis, BEC of Chongqing in 2004 accounts for 17.3% of the total energy consumption. This result is quite common to that of traditional methodology. As far as energy supply efficiency is concerned, the difference is highlighted by 0.417 of the exergy methodology to 0.645 of the traditional methodology.

Contractor key competitiveness indicators: A China study

A proper method to assess contractor competitiveness is important both for assisting clients in the selection of proper contractors and for assisting contractors in the development of more competitive bidding strategies. Previous studies have identified various indicators for assessing contractor competitiveness, and several assessment methods have been introduced. Nevertheless, these studies are limited because they are unable to tell which indicators are more important in different market environments. This paper identifies the key competitiveness indicators �KCIs� for assessing contractor competitiveness in the Chinese construction market. An index value is used to indicate the relative significance of various competitiveness indicators based on which KCIs are identified. The data applied in this study are from a survey of the construction industry in mainland China. The research findings provide valuable information for both existing businesses and the construction professionals who plan to compete for construction works in the Chinese market. The study provides useful references for further studies that compare the KCIs used in the Chinese construction industry and those used in other construction industries.

Optimal maintenance policies under different operational schedules

In the reliability literature, maintenance time is usually ignored during the optimization of maintenance policies. In some scenarios, costs due to system failures may vary with time, and the ignorance of maintenance time will lead to unrealistic results. This paper develops maintenance policies for such situations where the system under study operates iteratively at two successive states: up or down. The costs due to system failure at the up state consist of both business losses & maintenance costs, whereas those at the down state only include maintenance costs. We consider three models: Model A, B, and C: Model A makes only corrective maintenance (CM). Model B performs imperfect preventive maintenance (PM) sequentially, and CM. Model C executes PM periodically, and CM; this PM can restore the system as good as the state just after the latest CM. The CM in this paper is imperfect repair. Finally, the impact of these maintenance policies is illustrated through numerical examples.

A method of weighting indicators in building energy efficiency assessment

This paper identifies the indicators of energy efficiency assessment in residential building in China through a wide literature review. Indicators are derived from three main sources: 1) The existing building assessment methods; 2)The existing Chinese standards and technology codes in building energy efficiency; 3)Academia research. As a result, we proposed an indicator list by refining the indicators in the above sources. Identified indicators are weighted by the group analytic hierarchy process (AHP) method. Group AHP method is implemented following key steps: Step 1: Experienced experts are selected to form a group; Step 2: A survey is implemented to collect the individual judgments on the importance of indicators in the group; Step 3: Members’ judgments are synthesized to the group judgments; Step 4: Indicators are weighted by AHP on the group judgments; Step 5: Investigation of consistency estimation shows that the consistency of the judgment matrix is accepted. We believe that the weighted indicators in this paper will provide important references to building energy efficiency assessment.

Test performance indicators from a single soccer specific fitness test differentiate between highly trained and recreationally active soccer players

Aim. The aim of this study was to investigate whether a single soccer specific fitness test (SSFT) could differentiate between highly trained and recreationally active soccer players in selected test performance indicators. Methods. Subjects: 13 Academy Scholars (AS) from a professional soccer club and 10 Recreational Players (RP) agreed to participate in this study. Test 1-(V)over dotO(2) max was estimated from a progressive shuttle run test to exhaustion. Test 2-The SSFT was controlled by an automated procedure and alternated between walking, sprinting, jogging and cruise running speeds. Three activity blocks (1A, 2A and 3A) were separated by 3 min rest periods in which blood lactate samples were drawn. The 3 blocks of activity (Part A) were followed by 10 min of exercise at speeds alternating between jogging and cruise running (Part B). Results. Estimated (V)over dotO(2) max did not significantly differ between groups, although a trend for a higher aerobic capacity was evident in AS (p<0.09). Exercising heart rates did not differ between AS and RP, however, recovery heart rates taken from the 3 min rest periods were significantly lower in AS compared with RP following blocks 1A (124.65 b(.)min(-1) +/-7.73 and 133.98 b(.)min(-1) +/-6.63), (p<0.05) and 3A (129.91 b.min(-1) +/-10.21 and 138.85 b.min(-1) +/-8.70), (p<0.01). Blood lactate concentrations were significantly elevated in AS in comparison to RP following blocks 2A (6.91 mmol(.)l(-1) +/-2.67 and 4.74 mmol(.)l(-1) +/-1.28) and 3A (7.18 mmol(.)l(-1) +/-2.97 and 4.88 mmol(.)l(-1) +/-1.50), (p<0.05). AS sustained significantly faster average sprint times in block 3A compared with RP (3.18 sec +/-0.12 and 3.31 sec +/-0.12), (p<0.05). Conclusion. The results of this study show that highly trained soccer players are able to sustain, and more quickly recover from, high intensity intermittent exercise.

Using continuous ground-based radar and lidar measurements for evaluating the representation of clouds in four operational models

The ability of four operational weather forecast models [ECMWF, Action de Recherche Petite Echelle Grande Echelle model (ARPEGE), Regional Atmospheric Climate Model (RACMO), and Met Office] to generate a cloud at the right location and time (the cloud frequency of occurrence) is assessed in the present paper using a two-year time series of observations collected by profiling ground-based active remote sensors (cloud radar and lidar) located at three different sites in western Europe (Cabauw. Netherlands; Chilbolton, United Kingdom; and Palaiseau, France). Particular attention is given to potential biases that may arise from instrumentation differences (especially sensitivity) from one site to another and intermittent sampling. In a second step the statistical properties of the cloud variables involved in most advanced cloud schemes of numerical weather forecast models (ice water content and cloud fraction) are characterized and compared with their counterparts in the models. The two years of observations are first considered as a whole in order to evaluate the accuracy of the statistical representation of the cloud variables in each model. It is shown that all models tend to produce too many high-level clouds, with too-high cloud fraction and ice water content. The midlevel and low-level cloud occurrence is also generally overestimated, with too-low cloud fraction but a correct ice water content. The dataset is then divided into seasons to evaluate the potential of the models to generate different cloud situations in response to different large-scale forcings. Strong variations in cloud occurrence are found in the observations from one season to the same season the following year as well as in the seasonal cycle. Overall, the model biases observed using the whole dataset are still found at seasonal scale, but the models generally manage to well reproduce the observed seasonal variations in cloud occurrence. Overall, models do not generate the same cloud fraction distributions and these distributions do not agree with the observations. Another general conclusion is that the use of continuous ground-based radar and lidar observations is definitely a powerful tool for evaluating model cloud schemes and for a responsive assessment of the benefit achieved by changing or tuning a model cloud