5 resultados para CBD

em Digital Commons at Florida International University


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The Convention on Biodiversity (CBD) was created in 1992 to coordinate global governments to protect biological resources. The CBD has three goals: protection of biodiversity, achievement of sustainable use of biodiversity and facilitation of equitable sharing of the benefits of biological resources. The goal of protecting biological resources has remained both controversial and difficult to implement. This study focused more on the goal of biodiversity protection. The research was designed to examine how globally constructed environmental policies get adapted by national governments and then passed down to local levels where actual implementation takes place. Effectiveness of such policies depends on the extent of actual implementation at local levels. Therefore, compliance was divided and examined at three levels: global, national and local. The study then developed various criteria to measure compliance at these levels. Both qualitative and quantitative methods were used to analyze compliance and implementation. The study was guided by three questions broadly examining critical factors that most influence the implementation of biodiversity protection policies at the global, national and local levels. Findings show that despite an overall biodiversity deficit of 0.9 hectares per person, global compliance with the CBD goals is currently at 35%. Compliance is lowest at local levels at 14%, it is slightly better at national level at 50%, and much better at the international level 64%. Compliance appears higher at both national and international levels because compliance here is paper work based and policy formulation. If implementation at local levels continues to produce this low compliance, overall conservation outcomes can only get worse than what it is at present. There are numerous weaknesses and capacity challenges countries are yet to address in their plans. In order to increase local level compliance, the study recommends a set of robust policies that build local capacity, incentivize local resource owners, and implement biodiversity protection programs that are akin to local needs and aspirations.^

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The Convention on Biodiversity (CBD) was created in 1992 to coordinate global governments to protect biological resources. The CBD has three goals: protection of biodiversity, achievement of sustainable use of biodiversity and facilitation of equitable sharing of the benefits of biological resources. The goal of protecting biological resources has remained both controversial and difficult to implement. This study focused more on the goal of biodiversity protection. The research was designed to examine how globally constructed environmental policies get adapted by national governments and then passed down to local levels where actual implementation takes place. Effectiveness of such policies depends on the extent of actual implementation at local levels. Therefore, compliance was divided and examined at three levels: global, national and local. The study then developed various criteria to measure compliance at these levels. Both qualitative and quantitative methods were used to analyze compliance and implementation. The study was guided by three questions broadly examining critical factors that most influence the implementation of biodiversity protection policies at the global, national and local levels. Findings show that despite an overall biodiversity deficit of 0.9 hectares per person, global compliance with the CBD goals is currently at 35%. Compliance is lowest at local levels at 14%, it is slightly better at national level at 50%, and much better at the international level 64%. Compliance appears higher at both national and international levels because compliance here is paper work based and policy formulation. If implementation at local levels continues to produce this low compliance, overall conservation outcomes can only get worse than what it is at present. There are numerous weaknesses and capacity challenges countries are yet to address in their plans. In order to increase local level compliance, the study recommends a set of robust policies that build local capacity, incentivize local resource owners, and implement biodiversity protection programs that are akin to local needs and aspirations.

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Choosing between Light Rail Transit (LRT) and Bus Rapid Transit (BRT) systems is often controversial and not an easy task for transportation planners who are contemplating the upgrade of their public transportation services. These two transit systems provide comparable services for medium-sized cities from the suburban neighborhood to the Central Business District (CBD) and utilize similar right-of-way (ROW) categories. The research is aimed at developing a method to assist transportation planners and decision makers in determining the most feasible system between LRT and BRT. ^ Cost estimation is a major factor when evaluating a transit system. Typically, LRT is more expensive to build and implement than BRT, but has significantly lower Operating and Maintenance (OM) costs than BRT. This dissertation examines the factors impacting capacity and costs, and develops cost models, which are a capacity-based cost estimate for the LRT and BRT systems. Various ROW categories and alignment configurations of the systems are also considered in the developed cost models. Kikuchi's fleet size model (1985) and cost allocation method are used to develop the cost models to estimate the capacity and costs. ^ The comparison between LRT and BRT are complicated due to many possible transportation planning and operation scenarios. In the end, a user-friendly computer interface integrated with the established capacity-based cost models, the LRT and BRT Cost Estimator (LBCostor), was developed by using Microsoft Visual Basic language to facilitate the process and will guide the users throughout the comparison operations. The cost models and the LBCostor can be used to analyze transit volumes, alignments, ROW configurations, number of stops and stations, headway, size of vehicle, and traffic signal timing at the intersections. The planners can make the necessary changes and adjustments depending on their operating practices. ^

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In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.

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In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.