Reduction of Green House Gases Emission in the Transportation Sector - Coursework Example

Introduction The Transport sector entails the movement of persons and commodities via trains, airplanes, cars, trucks, ships and other channels (Hoffman, Schniederjans, & Sebora, 2004). In all countries, developed and developing, the transport industry has been established as one of the sectors with an escalating growth in the emission of greenhouse gases (Hoffman et al., 2004). The situation is more pronounced in developed countries due to significant escalation in the transport activities. A greater percentage of greenhouse gas emissions in transport sector are carbon IV oxide (CO2) emanating from the burning of petroleum products such as gasoline. Both commuter cars and light-duty trucks, together with sport vehicles and trucks (pickup) make up a lion share of the emission in the transport sector. These sources generate more than half of the green house gas emissions from the sector. The other emissions emanates from mercantile aircraft, pipelines, ships, freight trucks, trains, boats and lubricants (Hoffman et al., 2004). In addition, small quantities of methane and nitrous oxide are produced as a result of fuel burning. In the same vein, a little hydrofluorocarbons are also emitted. These green house gases come from embracing cooled and portable air conditioners technologies in transportation. Reduction of Green House Gases Emission in The Transportation Sector Category How Emissions are minimized Examples Fuel Substitution Embrace low carbon content fuels with less carbon (IV) oxide emission. The sources of these fuels include biofuels; H2; electricity from sources such as wind and sun which are renewable (Hoffman et al., 2004). Use of public buses with pressurized natural gas rather than diesel or petrol. Using hybrid automobiles that uses lower-carbon or non-fossil fuels. The use of low-carbon biofuels. Improving Design, Materials, and Technologies in order to boost the efficiency of fuels Embracing modern technologies, plan, and materials to come up with fuel saving automobiles. Embracing modern innovations ranging from hybrid vehicles to electric vehicles with the ability of storing energy Cutting down the substance making up automobiles Enhancing working Systems Embracing minimal fuel use Comprehensive enhancement in vehicle maintenance (Hoffman et al., 2004). Limiting the aircraft’s average taxi time. Driving sensibly for instance avoiding over speeding. Lowering engine-idling. Travel Demand Reduction Elaborate planning of urban to decrease mileage coverage by citizens driving each day. Encouraging practices for instance cycling or even walking. Developing public transport, footways, and bike paths to decrease emission (Hoffman et al., 2004). The optimal policy action to reduce green house gases, which causes climate due to the transport sector, will be arrived at using the Analytic Hierarchy Process (AHP). Analytic Hierarchy Process (AHP) was developed by Saaty (in the year 1980) and works by breaking the process of decision making in a hierarchy of decisive factor, sub- decisive factor, characteristic and alternatives through a set of weights that replicate the alternatives’ comparative significance (Vold, 2005). The AHP plays a significant part in EIA due to its capability for facilitating complex decision-making (Lee, & Chan, 2008). Evaluation of alternative transport policies In this study, a 3-level analytic hierarchy process will be applied, as shown in figure 1 below. The first level is made up of the ultimate goal one desires to achieve in executing the project: decreasing the green house gas emissions resulting from transport sector (Ragsdale, 2007) On the other hand, the 2nd level stands for the benchmark on the foundation where the projects are to be assessed: - Embracing of fuels with low carbon content (C1); - Technological improvements in the environmental efficiency of vehicles (C2); - Rise in the public and multi-modal transport market share (C3); The 3rd level presents the policy options, which are: - Voluntary arrangements amongst industries to improve the ecological efficiency of new vehicles (A1); - Incentives for turnover of car fleet renewal (A2); - Tax schemes aiming at encouraging environmental-friendly transport modes (A3); Analytic hierarchy structure Figure 1 C3 C1 C2 A1 A2 A3 C1- Rise in the public and multi-modal transport market share C2-Adoption of fuels with reduced carbon content C3-Technological improvements in the environmental efficiency of vehicles A1-Incentives for turnover of car fleet renewal A2-Tax schemes aiming at promoting environmental friendly transport modes A3-Voluntary arrangements amongst industries to improve new vehicles’ ecological efficiency The criteria C2 and C3 entail the alternatives A1, A2 and A3. Fundamentally, A2 and A3 consider the aspects straightforwardly reliant on the vehicle emissions by predetermined values on automobiles and fuels. The policy option A2 indirectly generates ecological paybacks through the hindrance on the use of private-owned cars and encouraging the public transportation as well as other modes such as cycling and walking (Sayers, Jessop, & Hills, 2003). Besides, the criteria C1 entail the policy preference A1, because their ecological paybacks are interrelated to the traffic cutback (Ragsdale, 2007) Findings The results show the highest importance to the “technological improvements in the ecological efficiency of vehicles” (criteria C3, at 55.7%); the other two criteria, C2 and C1 have priorities of 32 % and 12.3 %) respectively as results from the eigenvector of the criteria assessment template, whose features offer an inference on the criteria’s weights. See table 1 below. Table 1 Normalized Comparisons Criterion Consistency   C1 C2 C3 Weight Measure C1 0.125 0.100 0.143 0.123 3.006 C2 0.375 0.300 0.286 0.320 3.019 C3 0.500 0.600 0.571 0.557 3.030 Consistency Ratio 0.016 Table 2, offers the priorities of the policy preferences for each decisive factor. “Tax schemes aiming at promoting environmental-friendly transport modes” (A2) turns out to have the premier priority with a Weighted Average Score of 39.7 %. This is closely followed by “voluntary arrangements amongst industries to improve new vehicles’ ecological efficiency” at 35 % (A3). Table 2. Alternative Criterion Criterion A1 A2 A3   Weights C1 0.724 0.193 0.083 0.123 C2 0.230 0.648 0.122 0.320 C3 0.164 0.297 0.539   0.557 Weighted Average Score 0.254 0.397 0.350 1.000 Weighted Average Score Discussion and Conclusions Amongst the proxy policies, the tax schemes aiming at promoting environmental-friendly transport modes has been assessed as the best transportation guiding principle to reduce the adverse effects of climate change resulting from green house gases. This outcome is due to the fact that the strategy helps regulate the action of consumers through valuable price tools, raising the cost of private transport and enhancing public and transport modes which are friendly to the environment, such as car sharing and car pooling. In this perspective, a critical function is carried out by the public transportation network, which is viewed as having the ability to attract major volumes of the transport needs by information propagation to boost the perceived service quality. This strategy generates instantaneous impact in reducing traffic and eventually the environmental pressure in the area. The 2nd best strategy is the voluntary arrangements amongst industries to improve new vehicles’ ecological efficiency. This generates gradual effect because its effectiveness relies on normal turnover of car fleet or by incentives; however, it generates environmental benefits in the long run. Although the escalation in car possession pace is not controlled and mobility requirements are not regulated, in the next future the ecological reimbursement offered by new vehicles will be totally remunerated by the increase in the quantity of vehicles running on the road system. For this reason, the planning strategies ought to be tackled to modify the actions of users, rationalizing their journey (plummeting the distance covered curbing useless trips), and rebalancing their modal alternatives to reduce climate change impacts (Vold, 2005). References Hoffman, J., Schniederjans, M. and Sebora, T. (2004). A multi-objective approach to CEO selection, 42(4), 237-255 Lee, G. and Chan, E. (2008). The Analytic Hierarchy Process (AHP) Approach for Assessment of Urban Renewal Proposals, Social Indicators Research, 89(1); p. 155 (14 pages); Ragsdale, C. (2007). Spreadsheet Modeling & Decision Analysis: A Practical Introduction to Management Science (5th ed.) Saaty, T. (1990). How to make a decision: The Analytic Hierarchy Process. European Journal of Operational Research, 48, 9-25. Sayers T.M., Jessop A.T., Hills P. (2003). Multi-criteria evaluation of transport options – flexible, transparent and user-friendly? Transport Policy, 10, 95-105. Vold A. (2005). Optimal land use and transport planning for the Greater Oslo area. Transportation Research, 548-565. Read More