942 resultados para Bus Emissions
Resumo:
The complexity of climate change and its evolution during the last few years has a positive impact on new developments and approaches to reduce the emissions of CO2. Looking for a methodology to evaluate the sustainability of a roadway, a tool has been developed. Life Cycle Assessment (LCA) is being accepted by the road industry to measure and evaluate the environmental impacts of an infrastructure, as the energy consumption and carbon footprint. This paper describes the methodology to calculate the CO2 emissions associated with the energy embodied on a roadway along its life cycle, including construction, operations and demolition. It will assist to find solutions to improve the energy footprint and reduce the amount of CO2 emissions. Details are provided of both, the methodology and the data acquisition. This paper is an application of the methodology to the Spanish highways, using a local database. Two case studies and a practical example are studied to show the model as a decision support for sustainable construction in the road industry.
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Il sistema di trasporto detto Bus Rapid Transit (BRT) è stato lanciato a Curitiba, in Brasile, nel 1974 per offrire un trasporto in bus efficiente ed efficace nella città in rapida espansione. Questa sperienza, insieme a quella di Ottawa (1983) e Quito (1994) ha dimostrato di essere una soluzione molto efficiente per il trasporto di massa. Per tutta l’Europa si sono iniziate a sviluppare esperienze simili, introducendo però un concetto diverso per quanto riguarda la qualità di servizio. Infatti sistemi come il “trunk network” nella Svezia, il Metrobus nella Germania oppure il BHNS (Bus à Aut. Niveau de Service) nella Francia trattano la qualità di servizio da una prospettiva più ampia che il BRT, dato che considerano aspetti come l’immagine ed il comfort oltre che velocità, frequenza e affidabilità. Questi nuovi sistemi BHLS (Buses with a High Quality of Service) consentono di combinare la qualità di servizio del tram con il costo basso e l’altà flessibilità dei sistema bus, fornendo soluzioni molto interessanti in termini di accessibilità e livelli di servizio, che permettono l’adattamento ai differenti contesti urbani (dimensione, popolazione, densità, ecc.). This article compares different European experiences with tramways and BHLS, especially from the economic point of view, considering their respective costs, benefits and advantages altogether.
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The city of Madrid keeps not meeting the GHG and air pollutant limits set by the European legislation. A broad range of strategies have being taken into account to reduce both types of emissions; however traffic management meas ures are usually consigned to the sidelines. In 2004, Madrid City Council launched a plan to re-design its inner ring-road supported by a socioeconomic study that evaluated the environmental and operational benefits of the project. For safety reasons the planned speed limit for the tunnel section was finally reduced from 90km/h to 70km/h. Using a Macroscopic Traffic Model and the European Air Pollutant and Emissions Inventory Guidebook (EMEP/EEA), this paper examines the environmental and traffic performance consequences of this decision. Results support the thesis that reduced speed limits leads to GHG and air pollution reductions in the area affected by the measure without substantially altering traffic performance. The implementation of the new speed limit policy brings about a 15% and 16% reduction in both CO2 and NOx emissions respectively. Emissions’ reduction during off-peak hours is larger than during peak hours.
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Grouping urban bus routes is necessary when there are evidences of significant differences among them. In Jiménez et al. (2013), a reduced sample of routes was grouped into clusters utilizing kinematic measured data. As a further step, in this paper, the remaining urban bus routes of a city, for which no kinematic measurements are available, are classified. For such purpose we use macroscopic geographical and functional variables to describe each route, while the clustering process is performed by means of a neural network. Limitations caused by reduced training samples are solved using the bootstrap method.
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Road traffic is the greatest contributor to the carbon footprint of the transport sector and reducing it has become one of the main targets of sustainable transport policies. An analysis of the main factors influencing greenhouse gas (GHG) emissions is essential for designing new energy- and environmentally efficient strategies for the road transport. This paper addresses this need by (i) identifying factors which influence the carbon footprint, including traffic activity, fuel economy and socioeconomic development; and (ii) proposing a methodological framework which uses Modified Laspeyres Index decomposition to analyze the effect of important drivers on the changes in emissions of road transport in Spain during the period from 1990 to 2010. The results demonstrate that the country׳s economic growth has been closely linked to the rise in GHG emissions. The innovative contribution of this paper is the special analysis of the changes in mobility patterns and GHG emissions during the economic crisis, when, for the first time, Spanish road traffic emissions decreased. The reduction of road transport and improved energy efficiency has been powerful contributors to this decrease, demonstrating the effectiveness of energy-saving measures. On the basis of this analysis, several tailored policy recommendations have been suggested for future implementation.
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In this paper, a mathematical programming model and a heuristically derived solution is described to assist with the efficient planning of services for a set of auxiliary bus lines (a bus-bridging system) during disruptions of metro and rapid transit lines. The model can be considered static and takes into account the average flows of passengers over a given period of time (i.e., the peak morning traffic hour) Auxiliary bus services must accommodate very high demand levels, and the model presented is able to take into account the operation of a bus-bridging system under congested conditions. A general analysis of the congestion in public transportation lines is presented, and the results are applied to the design of a bus-bridging system. A nonlinear integer mathematical programming model and a suitable approximation of this model are then formulated. This approximated model can be solved by a heuristic procedure that has been shown to be computationally viable. The output of the model is as follows: (a) the number of bus units to assign to each of the candidate lines of the bus-bridging system; (b) the routes to be followed by users passengers of each of the origin–destination pairs; (c) the operational conditions of the components of the bus-bridging system, including the passenger load of each of the line segments, the degree of saturation of the bus stops relative to their bus input flows, the bus service times at bus stops and the passenger waiting times at bus stops. The model is able to take into account bounds with regard to the maximum number of passengers waiting at bus stops and the space available at bus stops for the queueing of bus units. This paper demonstrates the applicability of the model with two realistic test cases: a railway corridor in Madrid and a metro line in Barcelona Planificación de los servicios de lineas auxiliares de autobuses durante las incidencias de las redes de metro y cercanías. El modelo estudia el problema bajo condiciones de alta demanda y condiciones de congestión. El modelo no lineal resultante es resuelto mediante heurísticas que demuestran su utilidad. Se demuestran los resultados en dos corredores de las ciudades de Barcelona y Madrid.
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This paper reports the results of the assessment of a range of measures implemented in bus systems in five European cities to improve the use of public transport by increasing its attractiveness and enhancing its image in urban areas. This research was conducted as part of the EBSF project (European Bus System of the Future) from 2008 to 2012. New buses (prototypes), new vehicle and infrastructure technologies, and operational best practices were introduced, all of which were combined in a system approach. The measures were assessed using multicriteria analysis to simultaneously evaluate a certain number of criteria that need to be aggregated. Each criterion is measured by one or more key performance indicators (KPI) calculated in two scenarios (reference scenario, with no measure implemented; and project scenario, with the implementation of some measures), in order to evaluate the difference in the KPI performance between the reference and project scenario. The results indicate that the measures produce a greater benefit in issues related to bus system productivity and customer satisfaction, with the greatest impact on aspects of perceptions of comfort, cleanliness and quality of service, information to passengers and environmental issues. The study also reveals that the implementation of several measures has greater social utility than very specific and isolated measures.
Resumo:
En general, la distribución de una flota de vehículos que recorre rutas fijas no se realiza completamente en base a criterios objetivos, primando otros aspectos más difícilmente cuantificables. El análisis apropiado debería tener en consideración la variabilidad existente entre las diferentes rutas dentro de una misma ciudad para así determinar qué tecnología es la que mejor se adapta a las características de cada itinerario. Este trabajo presenta una metodología para optimizar la asignación de una flota de vehículos a sus rutas, consiguiendo reducir el consumo y las emisiones contaminantes. El método propuesto está organizado según el siguiente procedimiento: - Registro de las características cinemáticas de los vehículos que recorren un conjunto representativo de rutas. - Agrupamiento de las líneas en conglomerados de líneas similares empleando un algoritmo jerárquico que optimice el índice de semejanza entre rutas obtenido mediante contraste de hipótesis de las variables representativas. - Generación de un ciclo cinemático específico para cada conglomerado. - Tipificación de variables macroscópicas que faciliten la clasificación de las restantes líneas utilizando una red neuronal entrenada con la información recopilada en las rutas medidas. - Conocimiento de las características de la flota disponible. - Disponibilidad de un modelo que estime, según la tecnología del vehículo, el consumo y las emisiones asociados a las variables cinemáticas de los ciclos. - Desarrollo de un algoritmo de reasignación de vehículos que optimice una función objetivo dependiente de las emisiones. En el proceso de optimización de la flota se plantean dos escenarios de gran trascendencia en la evaluación ambiental, consistentes en minimizar la emisión de dióxido de carbono y su impacto como gas de efecto invernadero (GEI), y alternativamente, la producción de nitróxidos, por su influencia en la lluvia ácida y en la formación de ozono troposférico en núcleos urbanos. Además, en ambos supuestos se introducen en el problema restricciones adicionales para evitar que las emisiones de las restantes sustancias superen los valores estipulados según la organización de la flota actualmente realizada por el operador. La metodología ha sido aplicada en 160 líneas de autobús de la EMT de Madrid, conociéndose los datos cinemáticos de 25 rutas. Los resultados indican que, en ambos supuestos, es factible obtener una redistribución de la flota que consiga reducir significativamente la mayoría de las sustancias contaminantes, evitando que, en contraprestación, aumente la emisión de cualquier otro contaminante. ABSTRACT In general, the distribution of a fleet of vehicles that travel fixed routes is not usually implemented on the basis of objective criteria, thus prioritizing on other features that are more difficult to quantify. The appropriate analysis should consider the existing variability amongst the different routes within the city in order to determine which technology adapts better to the peculiarities of each itinerary. This study proposes a methodology to optimize the allocation of a fleet of vehicles to the routes in order to reduce fuel consumption and pollutant emissions. The suggested method is structured in accordance with the following procedure: - Recording of the kinematic characteristics of the vehicles that travel a representative set of routes. - Grouping of the lines in clusters of similar routes by utilizing a hierarchical algorithm that optimizes the similarity index between routes, which has been previously obtained by means of hypothesis contrast based on a set of representative variables. - Construction of a specific kinematic cycle to represent each cluster of routes. - Designation of macroscopic variables that allow the classification of the remaining lines using a neural network trained with the information gathered from a sample of routes. - Identification and comprehension of the operational characteristics of the existing fleet. - Availability of a model that evaluates, in accordance with the technology of the vehicle, the fuel consumption and the emissions related with the kinematic variables of the cycles. - Development of an algorithm for the relocation of the vehicle fleet by optimizing an objective function which relies on the values of the pollutant emissions. Two scenarios having great relevance in environmental evaluation are assessed during the optimization process of the fleet, these consisting in minimizing carbon dioxide emissions due to its impact as greenhouse gas (GHG), and alternatively, the production of nitroxides for their influence on acid rain and in the formation of tropospheric ozone in urban areas. Furthermore, additional restrictions are introduced in both assumptions in order to prevent that emission levels for the remaining substances exceed the stipulated values for the actual fleet organization implemented by the system operator. The methodology has been applied in 160 bus lines of the EMT of Madrid, for which kinematic information is known for a sample consisting of 25 routes. The results show that, in both circumstances, it is feasible to obtain a redistribution of the fleet that significantly reduces the emissions for the majority of the pollutant substances, while preventing an alternative increase in the emission level of any other contaminant.
Resumo:
Semi-arid soils cover a significant area of Earth s land surface and typically contain large amounts of inorganic C. Determining the effects of biochar additions on CO2 emissions fromsemi-arid soils is therefore essential for evaluating the potential of biochar as a climate change mitigation strategy. Here, we measured the CO2 that evolved from semi-arid calcareous soils amended with biochar at rates of 0 and 20 t ha?1 in a full factorial combination with three different fertilizers (mineral fertilizer, municipal solid waste compost, and sewage sludge) applied at four rates (equivalent to 0, 75, 150, and 225 kg potentially available N ha?1) during 182 days of aerobic incubation. A double exponential model, which describes cumulative CO2 emissions from two active soil C compartments with different turnover rates (one relatively stable and the other more labile), was found to fit verywell all the experimental datasets. In general, the organic fertilizers increased the size and decomposition rate of the stable and labile soil C pools. In contrast, biochar addition had no effects on any of the double exponential model parameters and did not interact with the effects ascribed to the type and rate of fertilizer. After 182 days of incubation, soil organic and microbial biomass C contents tended to increase with increasing the application rates of organic fertilizer, especially of compost, whereas increasing the rate of mineral fertilizer tended to suppress microbial biomass. Biochar was found to increase both organic and inorganic C contents in soil and not to interactwith the effects of type and rate of fertilizer on C fractions. As a whole, our results suggest that the use of biochar as enhancer of semi-arid soils, either alone or combined with mineral and organic fertilizers, is unlikely to increase abiotic and biotic soil CO2 emissions.
Resumo:
It has been suggested that different pathways through the brain are followed depending on the type of information that is being processed. Although it is now known that there is a continuous exchange of information through both hemispheres, language is considered to be processed by the left hemisphere, where Broca?s and Wernicke?s areas are located. On the other hand, music is thought to be processed mainly by the right hemisphere. According to Sininger Y.S. & Cone- Wesson, B. (2004), there is a similar but contralateral specialization of the human ears; due to the fact that auditory pathways cross-over at the brainstem. A previous study showed an effect of musical imagery on spontaneous otoacoustic emissions (SOAEs) (Perez-Acosta and Ramos-Amezquita, 2006), providing evidence of an efferent influence from the auditory cortex on the basilar membrane. Based on these results, the present work is a comparative study between left and right ears of a population of eight musicians that presented SOAEs. A familiar musical tune was chosen, and the subjects were trained in the task of evoking it after having heard it. Samples of ear-canal signals were obtained and processed in order to extract frequency and amplitude data on the SOAEs. This procedure was carried out before, during and after the musical image creation task. Results were then analyzed to compare the difference between SOAE responses of left and right ears. A clear asymmetrical SOAEs response to musical imagery tasks between left and right ears was obtained. Significant changes of SOAE amplitude related to musical imagery tasks were only observed on the right ear of the subjects. These results may suggest a predominant left hemisphere activity related to a melodic image creation task.
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Agriculture significantly contributes to global greenhouse gas (GHG) missions and there is a need to develop effective mitigation strategies. The efficacy of methods to reduce GHG fluxes from agricultural soils can be affected by a range of interacting management and environmental factors. Uniquely, we used the Taguchi experimental design methodology to rank the relative importance of six factors known to affect the emission of GHG from soil: nitrate (NO3?) addition, carbon quality (labile and non-labile C), soil temperature, water-filled pore space (WFPS) and extent of soil compaction. Grassland soil was incubated in jars where selected factors, considered at two or three amounts within the experimental range, were combined in an orthogonal array to determine the importance and interactions between factors with a L16 design, comprising 16 experimental units. Within this L16 design, 216 combinations of the full factorial experimental design were represented. Headspace nitrous oxide (N2O), methane (CH4) and carbon dioxide (CO2) concentrations were measured and used to calculate fluxes. Results found for the relative influence of factors (WFPS and NO3? addition were the main factors affecting N2O fluxes, whilst glucose, NO3? and soil temperature were the main factors affecting CO2 and CH4 fluxes) were consistent with those already well documented. Interactions between factors were also studied and results showed that factors with Little individual influence became more influential in combination. The proposed methodology offers new possibilities for GHG researchers to study interactions between influential factors and address the optimized sets of conditions to reduce GHG emissions in agro-ecosystems, while reducing the number of experimental units required compared with conventional experimental procedures that adjust one variable at a time.
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Abstract In this paper we examine the trends of nitrous oxide (N2O) emissions of the Spanish agricultural sector related to national production and consumption in the 1961?2009 period.The comparison between production- and consumption-based emissions at the national level provides a complete overview of the actual impact resulting from the dietary choices of a given country and allows the evaluation of potential emission leakages. On average, 1.5 % of the new reactive nitrogen that enters Spain every year is emitted as N2O. Production- and consumption-based emissions have both significantly increased in the period studied and nowadays consumption-based emissions are 45 % higher than production-based emissions. A large proportion of the net N2O emissions associated with imported agricultural godos comes from countries that are not committers for the United Nations Framework Convention on Climate Change Kyoto Protocol Annex I. An increase in feed consumption is the main driver of the changes observed, leading to a arkable emission leakage in the Spanish agricultural sector. The complementary approach used here is essential to achieve an effective mitigation of Spanish greenhouse gas emissions.
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Carbon (C) and nitrogen (N) process-based models are important tools for estimating and reporting greenhouse gas emissions and changes in soil C stocks. There is a need for continuous evaluation, development and adaptation of these models to improve scientific understanding, national inventories and assessment of mitigation options across the world. To date, much of the information needed to describe different processes like transpiration, photosynthesis, plant growth and maintenance, above and below ground carbon dynamics, decomposition and nitrogen mineralization. In ecosystem models remains inaccessible to the wider community, being stored within model computer source code, or held internally by modelling teams. Here we describe the Global Research Alliance Modelling Platform (GRAMP), a web-based modelling platform to link researchers with appropriate datasets, models and training material. It will provide access to model source code and an interactive platform for researchers to form a consensus on existing methods, and to synthesize new ideas, which will help to advance progress in this area. The platform will eventually support a variety of models, but to trial the platform and test the architecture and functionality, it was piloted with variants of the DNDC model. The intention is to form a worldwide collaborative network (a virtual laboratory) via an interactive website with access to models and best practice guidelines; appropriate datasets for testing, calibrating and evaluating models; on-line tutorials and links to modelling and data provider research groups, and their associated publications. A graphical user interface has been designed to view the model development tree and access all of the above functions.
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Among the mitigation strategies to prevent nitrogen (N) losses from ureic fertilizers, urease inhibitors (UIs) have been demonstrated to promote high N use efficiency by reducing ammonia (NH3) volatilization. In the last few years, some field experiments have also shown its effectiveness in reducing nitrous oxide (N2O) losses from fertilized soils under conditions of low soil moisture. An incubation experiment was carried out with the aim of assessing the main biotic mechanisms behind N2O emissions once that the UIs N-(n-butyl) thiophosphoric triamid (NBPT) and phenil phosphorodiamidate (PPDA) were applied with Urea (U) under different soil moisture conditions (40, 60 and 80 % water-filled pore space, WFPS). In the same study we tried to analyze to what extent soil WFPS regulates the effect of these inhibitors on N2O emissions. The use of PPDA in our study allowed us to compare the effect of NBPT with that of another commercially available urease inhibitor, aiming to see if the results were inhibitor-specific or not. Based on the results from this experiment, a WFPS (i.e. 60 %) was chosen for a second study (i.e. mesocosm experiment) aiming to assess the efficiency of the UIs to indirectly affect N2O emissions through influencing the pool of soil mineral N. The N2O emissions at 40 % WFPS were almost negligible, being significantly lower from all fertilized treatments than that produced at 60 and 80 % WFPS. When compared to U alone, NBPT+U reduced the N2O emissions at 60 % WFPS but had no effect at 80 % WFPS. The application of PPDA significantly increased the emissions with respect to U at 80 % WFPS whereas no significant effect was found at 60 %. At 80 % WFPS, denitrification was the main source of N2O emissions for all treatments. In the mesocosm study, the application of NBPT+U was an effective strategy to reduce N2O emissions (75 % reduction compared to U alone), due to a lower soil ammonium (NH4 +) content induced by the inhibitor. These results suggest that adequate management of the UI NBPT could provide, under certain soil conditions, an opportunity for mitigation of N2O emissions from fertilized soils.
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This study evaluates the effect of planting three cover crops (CCs) (barley, Hordeum vulgare L.; vetch, Vicia villosa L.; rape, Brassica napus L.) on the direct emission of N2O, CO2 and CH4 in the intercrop period and the impact of incorporating these CCs on the emission of greenhouse gas (GHG) from the forthcoming irrigated maize (Zea mays L.) crop. Vetch and barley were the CCs with the highest N2O and CO2 losses (75 and 47% increase compared with the control, respectively) in the fallow period. In all cases, fluxes of N2O were increased through N fertilization and the incorporation of barley and rape residues (40 and 17% increase, respectively). The combination of a high C:N ratio with the addition of an external source of mineral N increased the fluxes of N2O compared with − Ba and − Rp. The direct emissions of N2O were lower than expected for a fertilized crop (0.10% emission factor, EF) compared with other studies and the IPCC EF. These results are believed to be associated with a decreased NO3− pool due to highly denitrifying conditions and increased drainage. The fluxes of CO2 were in the range of other fertilized crops (i.e., 1118.71–1736.52 kg CO2–C ha− 1). The incorporation of CC residues enhanced soil respiration in the range of 21–28% for barley and rape although no significant differences between treatments were detected. Negative CH4 fluxes were measured and displayed an overall sink effect for all incorporated CC (mean values of − 0.12 and − 0.10 kg CH4–C ha− 1 for plots with and without incorporated CCs, respectively).