Greenhouse Gas Fluxes in Tropical and Temperae Agriculture: The Need for a Full-Cost Accounting of Global Warming Potentials

Agriculture's contribution to radiative forcing is principally through its historical release of carbon in soil and vegetation to the atmosphere and through its contemporary release of nitrous oxide (N2O) and methane (CHM4). The sequestration of soil carbon in soils now depleted in soil organic matter is a well-known strategy for mitigating the buildup of CO2 in the atmosphere. Less well-recognized are other mitigation potentials. A full-cost accounting of the effects of agriculture on greenhouse gas emissions is necessary to quantify the relative importance of all mitigation options. Such an analysis shows nitrogen fertilizer, agricultural liming, fuel use, N2O emissions, and CH4 fluxes to have additional significant potential for mitigation. By evaluating all sources in terms of their global warming potential it becomes possible to directly evaluate greenhouse policy options for agriculture. A comparison of temperate and tropical systems illustrates some of these options.

A ‘cost-per-wear’ model based on contact lens replacement frequency

Purpose: The aim was to construct and advise on the use of a cost-per-wear model based on contact lens replacement frequency, to form an equitable basis for cost comparison. ---------- Methods: The annual cost of professional fees, contact lenses and solutions when wearing daily, two-weekly and monthly replacement contact lenses is determined in the context of the Australian market for spherical, toric and multifocal prescription types. This annual cost is divided by the number of times lenses are worn per year, resulting in a ‘cost-per-wear’. The model is presented graphically as the cost-per-wear versus the number of times lenses are worn each week for daily replacement and reusable (two-weekly and monthly replacement) lenses.---------- Results: The cost-per-wear for two-weekly and monthly replacement spherical lenses is almost identical but decreases with increasing frequency of wear. The cost-per-wear of daily replacement spherical lenses is lower than for reusable spherical lenses, when worn from one to four days per week but higher when worn six or seven days per week. The point at which the cost-per-wear is virtually the same for all three spherical lens replacement frequencies (approximately AUD$3.00) is five days of lens wear per week. A similar but upwardly displaced (higher cost) pattern is observed for toric lenses, with the cross-over point occurring between three and four days of wear per week (AUD$4.80). Multifocal lenses have the highest price, with cross-over points for daily versus two-weekly replacement lenses at between four and five days of wear per week (AUD$5.00) and for daily versus monthly replacement lenses at three days per week (AUD$5.50).---------- Conclusions: This cost-per-wear model can be used to assist practitioners and patients in making an informed decision in relation to the cost of contact lens wear as one of many considerations that must be taken into account when deciding on the most suitable lens replacement modality.

Implementing value management as a decision-making tool in the design stages of design and build construction projects : a methodology for improved cost optimization

Value Management (VM) has been proven to provide a structured framework, together with other supporting tools and techniques, that facilitate effective decision-making in many types of projects, thus achieving ‘best value’ for clients. One of the major success factors of VM in achieving better project objectives for clients is through the provision of beneficial input by multi-disciplinary team members being involved in critical decision-making discussions during the early stage of construction projects. This paper describes a doctoral research proposal based on the application of VM in design and build construction projects, especially focusing on the design stage. The research aims to study the effects of implementing VM in design and build construction projects, in particular how well the methodology addresses issues related to cost overruns resulting from poor coordination and overlooking of critical constructability issues amongst team members in construction projects in Malaysia. It is proposed that through contractors’ early involvement during the design stage, combined with the use of the VM methodology, particularly as a decision-making tool, better optimization of construction cost can be achieved, thus promoting more efficient and effective constructability. The main methods used in this research involve a thorough literature study, semi-structured interviews, and a survey of major stakeholders, a detailed case study and a VM workshop and focus group discussions involving construction professionals in order to explore and possibly develop a framework and a specific methodology for the facilitating successful application of VM within design and build construction projects.

Evaluation of risk factors leading to cost overrun in delivery of highway construction projects

Accurate owner budget estimates are critical to the initial decision-to-build process for highway construction projects. However, transportation projects have historically experienced significant construction cost overruns from the time the decision to build has been taken by the owner. This paper addresses the problem of why highway projects overrun their predicted costs. It identifies the owner risk variables that contribute to significant cost overrun and then uses factor analysis, expert elicitation, and the nominal group technique to establish groups of importance ranked owner risks. Stepwise multivariate regression analysis is also used to investigate any correlation of the percentage of cost overrun with risks, together with attributes such as highway project type, indexed cost, geographics location, and project delivery method. The research results indicate a correlation between the reciprocal of project budgets size and percentage cost overrun. This can be useful for owners in determining more realistic decision-to-build highway budget estimates by taking into account the economies of scale associated with larger projects.

The importance of environmental issues and costs in Life Cycle Cost Analysis (LCCA) for highway projects

Sustainability has been increasingly recognised as an integral part of highway infrastructure development. In practice however, the fact that financial return is still a project’s top priority for many, environmental aspects tend to be overlooked or considered as a burden, as they add to project costs. Sustainability and its implications have a far-reaching effect on each project over time. Therefore, with highway infrastructure’s long-term life span and huge capital demand, the consideration of environmental cost/ benefit issues is more crucial in life-cycle cost analysis (LCCA). To date, there is little in existing literature studies on viable estimation methods for environmental costs. This situation presents the potential for focused studies on environmental costs and issues in the context of life-cycle cost analysis. This paper discusses a research project which aims to integrate the environmental cost elements and issues into a conceptual framework for life cycle costing analysis for highway projects. Cost elements and issues concerning the environment were first identified through literature. Through questionnaires, these environmental cost elements will be validated by practitioners before their consolidation into the extension of existing and worked models of life-cycle costing analysis (LCCA). A holistic decision support framework is being developed to assist highway infrastructure stakeholders to evaluate their investment decision. This will generate financial returns while maximising environmental benefits and sustainability outcome.

Computationally efficient numerical methods for time- and space-fractional Fokker–Planck equations

Fractional Fokker–Planck equations have been used to model several physical situations that present anomalous diffusion. In this paper, a class of time- and space-fractional Fokker–Planck equations (TSFFPE), which involve the Riemann–Liouville time-fractional derivative of order 1-α (α(0, 1)) and the Riesz space-fractional derivative (RSFD) of order μ(1, 2), are considered. The solution of TSFFPE is important for describing the competition between subdiffusion and Lévy flights. However, effective numerical methods for solving TSFFPE are still in their infancy. We present three computationally efficient numerical methods to deal with the RSFD, and approximate the Riemann–Liouville time-fractional derivative using the Grünwald method. The TSFFPE is then transformed into a system of ordinary differential equations (ODE), which is solved by the fractional implicit trapezoidal method (FITM). Finally, numerical results are given to demonstrate the effectiveness of these methods. These techniques can also be applied to solve other types of fractional partial differential equations.

Important omitted spatial variables in safety models: Understanding contributing crash causes at intersections

Advances in safety research—trying to improve the collective understanding of motor vehicle crash causation—rests upon the pursuit of numerous lines of inquiry. The research community has focused on analytical methods development (negative binomial specifications, simultaneous equations, etc.), on better experimental designs (before-after studies, comparison sites, etc.), on improving exposure measures, and on model specification improvements (additive terms, non-linear relations, etc.). One might think of different lines of inquiry in terms of ‘low lying fruit’—areas of inquiry that might provide significant improvements in understanding crash causation. It is the contention of this research that omitted variable bias caused by the exclusion of important variables is an important line of inquiry in safety research. In particular, spatially related variables are often difficult to collect and omitted from crash models—but offer significant ability to better understand contributing factors to crashes. This study—believed to represent a unique contribution to the safety literature—develops and examines the role of a sizeable set of spatial variables in intersection crash occurrence. In addition to commonly considered traffic and geometric variables, examined spatial factors include local influences of weather, sun glare, proximity to drinking establishments, and proximity to schools. The results indicate that inclusion of these factors results in significant improvement in model explanatory power, and the results also generally agree with expectation. The research illuminates the importance of spatial variables in safety research and also the negative consequences of their omissions.

A simultaneous equations model of crash frequency by collision type for rural intersections

Safety at roadway intersections is of significant interest to transportation professionals due to the large number of intersections in transportation networks, the complexity of traffic movements at these locations that leads to large numbers of conflicts, and the wide variety of geometric and operational features that define them. A variety of collision types including head-on, sideswipe, rear-end, and angle crashes occur at intersections. While intersection crash totals may not reveal a site deficiency, over exposure of a specific crash type may reveal otherwise undetected deficiencies. Thus, there is a need to be able to model the expected frequency of crashes by collision type at intersections to enable the detection of problems and the implementation of effective design strategies and countermeasures. Statistically, it is important to consider modeling collision type frequencies simultaneously to account for the possibility of common unobserved factors affecting crash frequencies across crash types. In this paper, a simultaneous equations model of crash frequencies by collision type is developed and presented using crash data for rural intersections in Georgia. The model estimation results support the notion of the presence of significant common unobserved factors across crash types, although the impact of these factors on parameter estimates is found to be rather modest.

Low-cost hardware speech enhancement for improved speech recognition in automotive environments

Voice recognition is one of the key enablers to reduce driver distraction as in-vehicle systems become more and more complex. With the integration of voice recognition in vehicles, safety and usability are improved as the driver’s eyes and hands are not required to operate system controls. Whilst speaker independent voice recognition is well developed, performance in high noise environments (e.g. vehicles) is still limited. La Trobe University and Queensland University of Technology have developed a low-cost hardware-based speech enhancement system for automotive environments based on spectral subtraction and delay–sum beamforming techniques. The enhancement algorithms have been optimised using authentic Australian English collected under typical driving conditions. Performance tests conducted using speech data collected under variety of vehicle noise conditions demonstrate a word recognition rate improvement in the order of 10% or more under the noisiest conditions. Currently developed to a proof of concept stage there is potential for even greater performance improvement.

A parallel computation of power system equations

Streaming SIMD Extensions (SSE) is a unique feature embedded in the Pentium III and P4 classes of microprocessors. By fully exploiting SSE, parallel algorithms can be implemented on a standard personal computer and a theoretical speedup of four can be achieved. In this paper, we demonstrate the implementation of a parallel LU matrix decomposition algorithm for solving power systems network equations with SSE and discuss advantages and disadvantages of this approach.

SSE based parallel solution for power systems network equations

Streaming SIMD Extensions (SSE) is a unique feature embedded in the Pentium III class of microprocessors. By fully exploiting SSE, parallel algorithms can be implemented on a standard personal computer and a theoretical speedup of four can be achieved. In this paper, we demonstrate the implementation of a parallel LU matrix decomposition algorithm for solving power systems network equations with SSE and discuss advantages and disadvantages of this approach.