Incorporating carbon footprints into seafood sustainability certification and eco-labels

The seafood industry has become increasingly interconnected at a global scale, with fish the most traded commodity worldwide. Travel to the farthest reaches of the oceans for capture is now common practice, and subsequent transport to market can require hundreds to thousands of miles of travel by sea and air. Refrigeration of seafood products is generally required at all stages of the journey from ocean to dinner plate, resulting in substantial energy expenditure. Energy input for aquaculture (including mariculture) products can also be high, namely due to the large amounts of feed required to support fish growth. As a result of these factors, the seafood industry has a substantial carbon footprint. Surprisingly, however, carbon footprints of seafood products are rarely integrated into assessments of their sustainability by eco-labels, sustainability certification, or consumer seafood sustainability guides. Suggestions are provided here for how carbon footprints could be incorporated within seafood sustainability schemes.

Sand pads : a promising technique to quantify human visitation into nature conservation areas

In many places the expansion of urban areas has brought recreationists into close proximity to nature conservation areas, sometimes leading to conflict where recreation and sensitive environmental or natural values are incompatible. An important first step in managing these conflicts is to assess the degree and nature of the problem. We describe the application, and methodological considerations, associated with the use of an innovative, low-cost, practical technique to monitor human intrusions into a wetland reserve which has been designated as ‘off-limits’ to the general public. The use of seven frequently monitored sand pads over 13 weeks enabled us to determine that intrusions occurred in every week (3–14 per sand pad), deep inside the reserve during most weeks, and also identified the key access points. Most intrusions occurred during holiday periods and were by walkers or cyclists. We also conducted a series of simple experiments to examine the utility of sand pads. Our sand pads maintained their shape well and held footprints for over 1 month, they were rarely avoided by people and provided reliable indices of the level of human activity. Sand hardness varied with rainfall, and hardened sand was frequent (53.8% of 26 days) and potentially prevented detection of people. We conclude that the sand pad technique is an effective and efficient tool to measure recreational use of off-limits areas and other conservation and recreation areas, provided human traffic is not too intense, and that checks are made reasonably frequently.

Energy-efficient management of data center resources for cloud computing : a vision, architectural elements, and open challenges

Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.

Sustainability and within use office building adaptations : a comparison of Dutch and Australian practices

Local Authorities worldwide are encouraging adaptation as a means of reducing building related urban energy consumption and greenhouse gas emissions. The City of Melbourne is promoting the retrofit of 1,200 CBD properties before 2020 with sustainability measures as part of their policy to become a carbon neutral city. Australian cities date from 1837 to the present day whereas some European cities have been inhabited for over two millennia. The concepts of adaptation and evolution of buildings and suburbs is well developed in Europe, though the scale of some of the post war developments has created different forms of building perhaps less adaptable or suited to change. The need to adapt buildings and to reduce environmental footprints becomes more pressing over time as global concentrations of carbon dioxide increase. Is it possible for Europeans to learn from Australian practices and vice averse? Through examination of office building adaptation in Melbourne and Amsterdam, it is possible to learn where similarities and differences exist and where new practices can be shared.

This paper addressed the questions; What are the key attributes influencing adaptations in Melbourne and Amsterdam office buildings, and what are the similarities and differences? Using the Melbourne CBD and Amsterdam as a case study, the research analysed 7393 commercial building adaptations in Melbourne and 98 office buildings in Amsterdam where adaptations were completed. The outcomes of this research show where similarities and differences exist and are relevant to all urban areas where adaptation of existing office buildings can mitigate the impacts of climate change and enhance the city for another generation of citizens and users.

Computable social patterns from sparse sensor data

We present a computational framework to automatically discover high-order temporal social patterns from very noisy and sparse location data. We introduce the concept of social footprint and present a method to construct a codebook, enabling the transformation of raw sensor data into a collection of social pages. Each page captures social activities of a user over regular time period, and represented as a sequence of encoded footprints. Computable patterns are then defined as repeated structures found in these sequences. To do so, we appeal to modeling tools in document analysis and propose a Latent Social theme Dirichlet Allocation (LSDA) model - a version of the Ngram topic model in [6] with extra modeling of personal context. This model can be viewed as a Bayesian clustering method, jointly discovering temporal collocation of footprints and exploiting statistical strength across social pages, to automatically discovery high-order patterns. Alternatively, it can be viewed as a dimensionality reduction method where the reduced latent space can be interpreted as the hidden social 'theme' - a more abstract perception of user's daily activities. Applying this framework to a real-world noisy dataset collected over 1.5 years, we show that many useful and interesting patterns can be computed. Interpretable social themes can also be deduced from the discovered patterns.

Uneasily along the sand

Uneasily Along the Sand evokes the state of mind of the great Mallee poet John Shaw Neilson during a period of hospitalization for nervous exhaustion around 1900. To his bed come the voices and apparitions of all those people whom he might have met but who in life eluded him. It is a ghost community of jesters, singers and seers, who parade in harlequin costumes and recall the poet to the vanishing spirit of the Mallee forest. In particular, a Wotjobaluk man by the name of ‘Jowley’ haunts him, a man found by white people as a child abandoned in a hollow log - abandoned, lost, stolen? The sound installation ‘Mac’ (that forms part of Uneasily and which will receive its first national broadcast to coincide with Mildura Palimpsest #8) evokes their strange meeting and a kind of reconciliation of peoples and cultures with environments that remains elusive. The hospital, where Neilson heard strange voices and saw strange visions, is evoked in a video work based on a set of ‘actions’ performed in Mildura’s Old Base Hospital, and sound recordings made in Pyrenees House, Ararat (a replica of the Swan Hill Hospital where Neilson was confined). The hospital solarium is transformed into a strangely distorted Mallee paddock, of sand, barbed wire and mattresses that leak like hour glasses. Caught in the fence lines of this dream world are scraps of a woman’s dress, bed sheets inscribed with charcoaled graffiti and footprints alluding to the ‘unevennesses’ of a life. Uneasily Along the sand is inspired by Paul Carter’s recent book, ‘Ground Truthing: explorations in a creative region’. The installation of Uneasily in Mildura coincides with Opening, another work inspired by ‘Ground Truthing’ that Carter and Dirk de Bruyn have created for the big screen at Federation Square, Melbourne.

Towards a parameterless 3D mesh segmentation

This paper proposes a novel technique for 3D mesh segmentation using multiple 2D pose footprints. Such problem has been targeted many times in the literature, but still requires further development especially in the area of automation. The proposed algorithm applies cognition theory and provides a generic technique to form a 3D bounding contour from a seed vertex on the 3D mesh. Forming the cutlines is done in both 2D and 3D spaces to enrich the available information for the search processes. The main advantage of this technique is the possibility to operate without any object-dependent parameters. The parameters that can be used will only be related to the used cognition theory and the seeds suggestion, which is another advantage as the algorithm can be generic to more than one theory of segmentation or to different criterion. The results are competitive against other algorithms, which use object-dependent or tuning parameters. This plus the autonomy and generality features, provides an efficient and usable approach for segmenting 3D meshes and at the same time to reduce the computation load.

Happiness versus the environment - a case study of Australian lifestyles

Crafting environmental policies that at the same time enhance, or at least not reduce people's wellbeing, is crucial for the success of government action aimed at mitigating environmental impact. However, there does not yet exist any survey that refers to one and the same population, and that allows the identifying relationships and trade-offs between subjective wellbeing and the complete environmental impact of households. In order to circumvent the lack of comprehensive survey information, we attempt to integrate two separate survey databases, and describe the challenges associated with this integration. Our results indicate that carbon footprints are likely to increase, but wellbeing levels off with increasing income. Living together with people is likely to create a win-win situation where both climate and wellbeing benefit. Car ownership obviously creates emissions, however personal car ownership enhances subjective wellbeing, but living in an area with high car ownership decreases subjective wellbeing. Finally, gaining educational qualifications is linked with increased emissions. These results indicate that policy-making is challenged in striking a wise balance between individual convenience and the common good.

Urban growth in arid environments : developing water sustainability indicators for Abu Dhabi (UAE)

The United Arab Emirates (UAE) face a serious water problem. It has a very dry climate, high evaporation rate, combined with large water consumption from fast growing population, economic activities and uncontrolled uses of water for irrigation. Currently, UAE has one of the largest water footprints in the world. Groundwater is overexploited. Waste water is increasingly being treated to supply non-drinking water, but it still cover a small proportion of the demand. Desalination of sea water is the main source of potable water in UAE, but the high economic cost of desalination, its intensive energy demand and the adverse effects of its effluents on the marine life are a major concern. Other factors contributing to the problem are the focus of water management policies on keep supplying the growing demand for water, the increase of the per capita water consumption, and the free water charge for most of population. This research goal is to develop a water sustainability set of indicators for the challenging context of UAE. This paper presents the first stage of the research. Based on a review of the literature, the proposed framework involves 19 indicators, divided into four categories: water availability; water quality; water use efficiency; and policy and governance. Using an integrated cause-effect approach (DSR - Driving force, State, Response), the indicators were related in terms of their interdependencies, with a holistic view of the city water cycle. A preliminary test of the indicators to Abu Dhabi as a case study allowed an evaluation of the main 'Driving force' on the system, such as the scarcity of water due to natural constraints of the region, and increasing water consumption patterns of modern society; an assessment of the current 'state', which is under serious water stress. Also it indicated some potential 'responses', such as implementing policies for increasing efficient use.

Paradigm shift to enhanced water supply planning through augmented grids, scarcity pricing and adaptive factory water : a system dynamics approach

This paper details a system dynamics model developed to simulate proposed changes to water governance through the integration of supply, demand and asset management processes. To effectively accomplish this, interconnected feedback loops in tariff structures, demand levels and financing capacity are included in the model design, representing the first comprehensive life-cycle modelling of potable water systems. A number of scenarios were applied to Australia's populated South-east Queensland region, demonstrating that introducing temporary drought pricing (i.e. progressive water prices set inverse with availability), in conjunction with supply augmentation through rain-independent sources, is capable of efficiently providing water security in the future. Modelling demonstrated that this alternative tariff structure reduced demand in scarcity periods thereby preserving supply, whilst revenues are maintained to build new water supply infrastructure. In addition to exploring alternative tariffs, the potential benefits of using adaptive pressure-retarded osmosis desalination plants for both potable water and power generation was explored. This operation of these plants for power production, when they would otherwise be idle, shows promise in reducing their net energy and carbon footprints. Stakeholders in industry, government and academia were engaged in model development and validation. The constructed model displays how water resource systems can be reorganised to cope with systemic change and uncertainty.

2nd generation concrete construction: carbon footprint accounting

Purpose – Construction contractors and facility managers are being challenged to minimize the carbon footprint. Life cycle carbon‐equivalent (CO2‐e) accounting, whereby the potential emissions of greenhouse gases due to energy expenditure during construction and subsequent occupation of built infrastructure, generally ceases at the end of the service life. However, following demolition, recycling of demolition waste that becomes incorporated into 2nd generation construction is seldom considered within the management of the carbon footprint. This paper aims to focus on built concrete infrastructure, particularly the ability of recycled concrete to chemically react with airborne CO2, thereby significantly influencing CO2‐e estimates.

Design/methodology/approach – CO2‐e estimates were made in accordance with the methodology outlined in the Australian National Greenhouse Accounts (NGA) Factors and were based on the energy expended for each life cycle activity from audited records. Offsets to the CO2‐e estimates were based on the documented ability of concrete to chemically react with airborne carbon dioxide (“carbonation”) and predictions of CO2 uptake by concrete and recycled concrete was made using existing predictive diffusion models. The author's study focused on a built concrete bridge which was demolished and recycled at the end of the service life, and the recycled concrete was utilized towards 2nd generation construction. The sensitivity of CO2‐e and carbonation estimates were tested on several different types of source demolition waste as well as subsequent construction applications using recycled concrete (RCA). Whole‐of‐life CO2‐e estimates, including carbonation of RCA over the 1st and 2nd generations, were estimated and contrasted with conventional carbon footprints that end at the conclusion of the 1st generation.

Findings – Following demolition, CO2 capture by RCA is significant due to the more permeable nature of the crushed RCA compared with the original built infrastructure. RCA also has considerably greater exposed surface area, relative to volume, than a built concrete structure, and therefore more highly exposed surface to react with CO2: it therefore carbonates more comprehensively. CO2‐e estimates can be offset by as much as 55‐65 per cent when including the contribution of carbonation of RCA built within 2nd generation infrastructure. Further offsets are achievable using blended fly ash or slag cement binders; however, this study has focused on concrete composed of 100 per cent OPC binders and the effects of RCA.

Originality/value – Construction project estimates of life cycle CO2‐e emissions should include 2nd generation applications that follow the demolition of the 1st generation infrastructure. Life cycle estimates generally end at the time of demolition. However, by incorporating the recycled concrete demolition waste into the construction of 2nd generation infrastructure, the estimated CO2‐e is significantly offset during the 2nd generation life cycle by chemical uptake of CO2 (carbonation). This paper provides an approach towards inclusion of 2nd generation construction applications into whole‐of‐life estimates of CO2‐e.

Automated analysis of performance and energy consumption for cloud applications

In cloud environments, IT solutions are delivered to users via shared infrastructure. One consequence of this model is that large cloud data centres consume large amounts of energy and produce significant carbon footprints. A key objective of cloud providers is thus to develop resource provisioning and management solutions at minimum energy consumption while still guaranteeing Service Level Agreements (SLAs). However, a thorough understanding of both system performance and energy consumption patterns in complex cloud systems is imperative to achieve a balance of energy efficiency and acceptable performance. In this paper, we present StressCloud, a performance and energy consumption analysis tool for cloud systems. StressCloud can automatically generate load tests and profile system performance and energy consumption data. Using StressCloud, we have conducted extensive experiments to profile and analyse system performance and energy consumption with different types and mixes of runtime tasks. We collected finegrained energy consumption and performance data with different resource allocation strategies, system configurations and workloads. The experimental results show the correlation coefficients of energy consumption, system resource allocation strategies and workload, as well as the performance of the cloud applications. Our results can be used to guide the design and deployment of cloud applications to balance energy and performance requirements.

Automating performance and energy consumption analysis for cloud applications

In cloud environments, IT solutions are delivered to users via shared infrastructure, enabling cloud service providers to deploy applications as services according to user QoS (Quality of Service) requirements. One consequence of this cloud model is the huge amount of energy consumption and significant carbon footprints caused by large cloud infrastructures. A key and common objective of cloud service providers is thus to develop cloud application deployment and management solutions with minimum energy consumption while guaranteeing performance and other QoS specified in Service Level Agreements (SLAs). However, finding the best deployment configuration that maximises energy efficiency while guaranteeing system performance is an extremely challenging task, which requires the evaluation of system performance and energy consumption under various workloads and deployment configurations. In order to simplify this process we have developed Stress Cloud, an automatic performance and energy consumption analysis tool for cloud applications in real-world cloud environments. Stress Cloud supports the modelling of realistic cloud application workloads, the automatic generation of load tests, and the profiling of system performance and energy consumption. We demonstrate the utility of Stress Cloud by analysing the performance and energy consumption of a cloud application under a broad range of different deployment configurations.