998 resultados para Traffic emissions


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Point-to-point speed cameras are a relatively new and innovative technological approach to speed enforcement that is increasingly been used in a number of highly motorised countries. Previous research has provided evidence of the positive impact of this approach on vehicle speeds and crash rates, as well as additional traffic related outcomes such as vehicle emissions and traffic flow. This paper reports on the conclusions and recommendations of a large-scale project involving extensive consultation with international and domestic (Australian) stakeholders to explore the technological, operational, and legislative characteristics associated with the technology. More specifically, this paper provides a number of recommendations for better practice regarding the implementation of point-to-point speed enforcement in the Australian and New Zealand context. The broader implications of the research, as well as directions for future research, are also discussed.

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Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based) on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA) based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2) field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.

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To enhance the performance of the k-nearest neighbors approach in forecasting short-term traffic volume, this paper proposed and tested a two-step approach with the ability of forecasting multiple steps. In selecting k-nearest neighbors, a time constraint window is introduced, and then local minima of the distances between the state vectors are ranked to avoid overlappings among candidates. Moreover, to control extreme values’ undesirable impact, a novel algorithm with attractive analytical features is developed based on the principle component. The enhanced KNN method has been evaluated using the field data, and our comparison analysis shows that it outperformed the competing algorithms in most cases.

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Purpose The purpose of this paper is to determine whether greenhouse gas (GHG) tradeable instruments will be classified as financial products within the scope of the World Trade Organization (WTO) law and to explore the implications of this finding. Design/methodology/approach This purpose is achieved through examination of the units of the Australian Carbon Pricing Mechanism (CPM), namely eligible emissions units. These units are analysed through the lens of the definition of financial products provided in the General Agreement for Trade in Services (the GATS). Findings This paper finds that eligible emissions units will be classified as financial instruments, and therefore the provisions that govern their trade will be regulated by the GATS. Considering this, this paper explores the limitations that are introduced by the Australian legislation on the trade of eligible emissions units. Research limitations/implications This paper is limited in its analysis to the Australian CPM. In order to draw conclusions on the issues raised by this analysis it is necessary to consider the WTO requirements against an operating emissions trading scheme. The Australian CPM presents a contemporary model of an appropriate scheme. Originality/value The findings in this paper are crucial in a GHG constrained society. This is because emissions trading schemes are becoming popular measures for pricing GHG emissions, and for this reason the units that are traded and surrendered for emissions liabilities must be classified appropriately on a global scale. Failing to do this could result in differential treatment that may be contrary to the intentions of important global agreements, such as the WTO covered agreements.

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Wireless networked control systems (WNCSs) have been increasingly deployed in industrial applications. As they require timely data packet transmissions, it is difficult to make efficient use of the limited channel resources, particularly in contention based wireless networks in the layered network architecture. Aiming to maintain the WNCSs under critical real-time traffic condition at which the WNCSs marginally meet the real-time requirements, a cross-layer design (CLD) approach is presented in this paper to adaptively adjust the control period to achieve improved channel utilization while still maintaining effective and timely packet transmissions. The effectiveness of the proposed approach is demonstrated through simulation studies.

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This research identifies roadway, traffic, and environmental factors that influence the injury severity of road traffic crashes in Dhaka. Dhaka provides a rather unusual driving risk environment to study, since virtually anyone can obtain a drivers’ license and very little traffic enforcement and fines are given when drivers violate traffic rules. To examine this city with presumed heightened crash severity risk, police reported crash data from 2007 to 2011 containing about 2714 road traffic crashes were collected. The injury severity of traffic crashes—recorded as either fatal, serious injury, or property damage only—were modeled using an ordered Probit model. Significant factors increasing the probability of fatal injuries include crashes along highways (65%), absence of a road divider (80%), crashes during night time (54%), and vehicle-pedestrian collisions (367%); whereas two-way traffic configuration (21%), and traffic police controlled schemes (41%) decrease the probability of fatalities. Both similarities and differences of the findings between crash risk in Dhaka and developed countries are discussed in policy relevant terms.

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Traffic safety culture is a relatively new concept which has recently gained attention in the field of traffic safety. There is currently little known regarding the nature of the concept, nor how it should be defined. Preliminary definitions have tended to focus on specific road safety problems and the anticipated effect of a strong traffic safety culture. The literature to date has tended to emphasise how traffic safety culture might be created or shaped. However, without a better understanding of the nature and structure of traffic safety culture, discussions regarding changes to traffic safety culture are restricted. An examination of different conceptualisations and definitions of organisational safety culture provides a preliminary theoretical framework for traffic safety culture. Two high risk driving behaviours within the Australian context are compared to illustrate how key factors within this framework can be used to understand and improve road safety outcomes.

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Global cereal production will need to increase by 50% to 70% to feed a world population of about 9 billion by 2050. This intensification is forecast to occur mostly in subtropical regions, where warm and humid conditions can promote high N2O losses from cropped soils. To secure high crop production without exacerbating N2O emissions, new nitrogen (N) fertiliser management strategies are necessary. This one-year study evaluated the efficacy of a nitrification inhibitor (3,4-dimethylpyrazole phosphate—DMPP) and different N fertiliser rates to reduce N2O emissions in a wheat–maize rotation in subtropical Australia. Annual N2O emissions were monitored using a fully automated greenhouse gas measuring system. Four treatments were fertilized with different rates of urea, including a control (40 kg-N ha−1 year−1), a conventional N fertiliser rate adjusted on estimated residual soil N (120 kg-N ha−1 year−1), a conventional N fertiliser rate (240 kg-N ha−1 year−1) and a conventional N fertiliser rate (240 kg-N ha−1 year−1) with nitrification inhibitor (DMPP) applied at top dressing. The maize season was by far the main contributor to annual N2O emissions due to the high soil moisture and temperature conditions, as well as the elevated N rates applied. Annual N2O emissions in the four treatments amounted to 0.49, 0.84, 2.02 and 0.74 kg N2O–N ha−1 year−1, respectively, and corresponded to emission factors of 0.29%, 0.39%, 0.69% and 0.16% of total N applied. Halving the annual conventional N fertiliser rate in the adjusted N treatment led to N2O emissions comparable to the DMPP treatment but extensively penalised maize yield. The application of DMPP produced a significant reduction in N2O emissions only in the maize season. The use of DMPP with urea at the conventional N rate reduced annual N2O emissions by more than 60% but did not affect crop yields. The results of this study indicate that: (i) future strategies aimed at securing subtropical cereal production without increasing N2O emissions should focus on the fertilisation of the summer crop; (ii) adjusting conventional N fertiliser rates on estimated residual soil N is an effective practice to reduce N2O emissions but can lead to substantial yield losses if the residual soil N is not assessed correctly; (iii) the application of DMPP is a feasible strategy to reduce annual N2O emissions from sub-tropical wheat–maize rotations. However, at the N rates tested in this study DMPP urea did not increase crop yields, making it impossible to recoup extra costs associated with this fertiliser. The findings of this study will support farmers and policy makers to define effective fertilisation strategies to reduce N2O emissions from subtropical cereal cropping systems while maintaining high crop productivity. More research is needed to assess the use of DMPP urea in terms of reducing conventional N fertiliser rates and subsequently enable a decrease of fertilisation costs and a further abatement of fertiliser-induced N2O emissions.

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Temporary Traffic Control Plans (TCP’s), which provide construction phasing to maintain traffic during construction operations, are integral component of highway construction project design. Using the initial design, designers develop estimated quantities for the required TCP devices that become the basis for bids submitted by highway contractors. However, actual as-built quantities are often significantly different from the engineer’s original estimate. The total cost of TCP phasing on highway construction projects amounts to 6–10% of the total construction cost. Variations between engineer estimated quantities and final quantities contribute to reduced cost control, increased chances of cost related litigations, and bid rankings and selection. Statistical analyses of over 2000 highway construction projects were performed to determine the sources of variation, which later were used as the basis of development for an automated-hybrid prediction model that uses multiple regressions and heuristic rules to provide accurate TCP quantities and costs. The predictive accuracy of the model developed was demonstrated through several case studies.

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Loop detectors are the oldest and widely used traffic data source. On urban arterials, they are mainly installed for signal control. Recently state of the art Bluetooth MAC Scanners (BMS) has significantly captured the interest of stakeholders for exploiting it for area wide traffic monitoring. Loop detectors provide flow- a fundamental traffic parameter; whereas BMS provides individual vehicle travel time between BMS stations. Hence, these two data sources complement each other, and if integrated should increase the accuracy and reliability of the traffic state estimation. This paper proposed a model that integrates loops and BMS data for seamless travel time and density estimation for urban signalised network. The proposed model is validated using both real and simulated data and the results indicate that the accuracy of the proposed model is over 90%.

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Several significant studies have been made in recent decades toward understanding road traffic noise and its effects on residential balconies. These previous studies have used a variety of techniques such as theoretical models, scale models and measurements on real balconies. The studies have considered either road traffic noise levels within the balcony space or inside an adjacent habitable room or both. Previous theoretical models have used, for example, simplified specular reflection calculations, boundary element methods (BEM), adaptations of CoRTN or the use of Sabine Theory. This paper presents an alternative theoretical model to predict the effects of road traffic noise spatially within the balcony space. The model includes a specular reflection component by calculating up to 10 orders of source images. To account for diffusion effects, a two compartment radiosity component is utilised. The first radiosity compartment is the urban street, represented as a street with building facades on either side. The second radiosity compartment is the balcony space. The model is designed to calculate the predicted road traffic noise levels within the balcony space and is capable of establishing the effect of changing street and balcony geometries. Screening attenuation algorithms are included to determine the effects of solid balcony parapets and balcony ceiling shields.

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Although both the size and chemical composition of ambient particles are important parameters in determining their toxicities, their relative contributions are unclear (Heal et al., 2012). Children are particularly at risk to the detrimental health effects that have been linked to long term exposure to airborne particles (See e.g. Ruckerl et al., 2011). However, there is currently limited understanding of the health effects in children due to long term exposure to airborne particles. Schools are locations within an urban environment where children experience significant exposure to vehicle emissions, and to date there is limited information assessing children’s exposure at school. This study is a part of a large project aimed at gaining a holistic picture of the exposure of children to traffic related pollutants. In the current paper, results from the investigation of the elemental composition of airborne particle at urban schools are presented.

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Accurate prediction of incident duration is not only important information of Traffic Incident Management System, but also an ffective input for travel time prediction. In this paper, the hazard based prediction odels are developed for both incident clearance time and arrival time. The data are obtained from the Queensland Department of Transport and Main Roads’ STREAMS Incident Management System (SIMS) for one year ending in November 2010. The best fitting distributions are drawn for both clearance and arrival time for 3 types of incident: crash, stationary vehicle, and hazard. The results show that Gamma, Log-logistic, and Weibull are the best fit for crash, stationary vehicle, and hazard incident, respectively. The obvious impact factors are given for crash clearance time and arrival time. The quantitative influences for crash and hazard incident are presented for both clearance and arrival. The model accuracy is analyzed at the end.

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A unique high temporal frequency dataset from an irrigated cotton-wheat rotation was used to test the agroecosystem model DayCent to simulate daily N2O emissions from sub-tropical vertisols under different irrigation intensities. DayCent was able to simulate the effect of different irrigation intensities on N2O fluxes and yield, although it tended to overestimate seasonal fluxes during the cotton season. DayCent accurately predicted soil moisture dynamics and the timing and magnitude of high fluxes associated with fertilizer additions and irrigation events. At the daily scale we found a good correlation of predicted vs. measured N2O fluxes (r2 = 0.52), confirming that DayCent can be used to test agricultural practices for mitigating N2O emission from irrigated cropping systems. A 25 year scenario analysis indicated that N2O losses from irrigated cotton-wheat rotations on black vertisols in Australia can be substantially reduced by an optimized fertilizer and irrigation management system (i.e. frequent irrigation, avoidance of excessive fertiliser application), while sustaining maximum yield potentials.