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Carbon Emissions - Essay Example

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This paper 'Carbon Emissions' tells us that The United Kingdom plans to reduce carbon emissions by 80% by 2050. The plan is relative to 1990. From 1990 to 2008, United Kingdom had achieved a 22% reduction in greenhouse gas emissions. This is because of the climatic changes that have been experienced in the world for many years…
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Carbon Emissions by [Lecturer’s and Number] Carbon Emissions Introduction United Kingdom plans to reduce carbon emissions to 80% by 2050. The plan is relative to 1990. From 1990 to 2008, United Kingdom had achieved a 22% reduction of greenhouse gas emissions. This is because of the climatic changes that have been experienced in the world for many years. Energy security is considered in the attempt to achieve the 80% carbon emission. The development of the 2050 calculator tool is one of the strategies used to reduce the carbon emissions. The tool is used is used to generate figures that simulate the desired plan of achieving this goal. The tool has been used to generate the figures that are used to justify this report. The results of the simulation using the tool will form evidence for the justification of the intended plan. This report explores the strengths and weaknesses of the values obtained from the tool. The tool was used with an aim simulating values that can achieve the desired 80% carbon emission. The analysis of the results obtained from the 2050 calculator will form a basis for the development of plan to achieve the 80% carbon emission. The URL used to generate this report is: http://2050-calculator-tool.decc.gov.uk/pathways/31134443324444441444414113322121332311213213111411121/primary_energy_chart. Below is a screenshot of the findings obtained from the tool. Methodology The procedure used to achieve the 80% carbon emission considers factors that affect carbon emissions. The factors include lifestyle and behavioural changes that occur due to changes with time. The desired lifestyle and behavioural changes include reductions in the average room temperatures during winter and reductions in energy demand. Lifestyles such as reducing food wastage can reduce emissions. Shifting from private transportation to public transportation can reduce the amount of emissions due to high usage of petroleum products. Another factor considered in the generation the results and explanation of this report is the changes in technology. Technology is dynamic in nature and has been changing gradually. The emergence of Light Emitting Diodes (LEDs) has contributed a lot to reduction in energy usage. These are less carbon intensive technologies that reduce the emission of carbon (Carbon emissions, 2008). The availability of different fuel and technological choices makes the development of our plan for reducing carbon emissions by 80% easier. Different options of lighting and heating appliances gives power consumers varied options to minimize their energy consumption. For example, current heating appliances offer options of ground source heat pump and district heating. Another factor considered in the generation of figures using 2050 tool is the structural change in economy. For instance, the increasing and decreasing operations in manufacturing industries gives us the chance to optimize energy usage based on economy changes. These factors affecting the trajectories of carbon emissions by 2050 are used to model the plan to reduce carbon emission by 2050. The values of the factors stated above are modified to come up with the optimal figures of a model of the 80% carbon emission reduction plan. For the chosen trajectories, the 2050 tool outputs displays the figures comparing energy consumption and the target carbon emission levels (Mulligan, 2010). Interpretation and Analysis of Results The results of our 2050 manipulations produced a framework for achieving the 80% reduction in carbon emission by 2050. The target 80% reduction in carbon emissions (as displayed by the screenshot displayed in the introduction of this report) by 20250 was obtained by trying out different ways to secure low carbon emission in the future. The results were obtained after combinations of different choices of final energy demand, primary energy supply, and greenhouse gas emissions. The results of different combinations are explained in this section (Mulligan, 2010). The choice of the domestic transportation was made with the assumption that in 2050, people will be covering the same distances as they are covering in the present day. However, the successful reduction in emission from the domestic transport sector is dependent on significant shift from personal transport vehicles to public transport vehicles. The combinations for transport assumed 100% usage of electric trains and 50% usage of electric buses. The implementation of this strategy is demanding in terms of capital but effective in reduction of reduction of the transport sector carbon emissions. The choice of cars used by 2050 anticipated that 80% of vehicles would use fuel cells while the rest will use batteries. The domestic freight for transport sector assumed massive shift from road transport water and rail transport. The international aviation sector option used to generate the model used to create this report anticipated 130% increase in international flights hence a 45% increase in fuel. In the shipping sector, the model produced a two-thirds reduction in fuel usage (Elkins and Baker, 2001). In the home energy usage, the model produced a reduction of home room temperature to 16 degrees Celsius. The room temperatures reduction is predicted since the plan for carbon emissions reductions by 2050 will sensitize people on the need to reduce energy consumption through heaters. Advancements in technology will lead to the construction of better homes hence the reduction in room temperatures. The emergence of new technologies can also reduce excessive home energy consumption through heaters. Another strategy to reduce excessive consumption of energy through heaters as indicted by the model is by increasing home insulation to 20 metres. Insulation of homes reduces energy loss and hence lower energy consumptions. The insulation will result into a fifty per cent decrease in thermal leakiness of the homes hence little energy consumption. A 30% to 60% supply of energy is expected for home heating systems by 2050 as indicated by the model. This is massive reduction in energy consumption towards the realization of the target 80% carbon emission reduction by 2050 (Gilbert, 2009). The form of energy used for home chosen for this model is mostly is a mixture of biogas and other gases. The gases reduce amount of carbon emissions as planned for the target 80% reduction of carbon emissions by 2050 (2050-calculator-tool.decc.gov.uk, 2014). The model shows a 20% increase energy used for the lighting of homes. The increase in lighting energy consumption at homes is expected due to increase in populations thus increased number of homes. The form of home of energy used for home cooking energy is expected to be entirely electric. Cooking using electric energy reduces carbon emissions by 100%. Since electric energy is expensive as compared to gas energy, the model predicts increased generation of solar and wind energy (Brooks, 2011). The model shows 200% increase in the output of United Kingdom industries by 2050. The doubling of the output by industries is due to continuous improvement of technologies used in industries that in turn improve the performance of these industries. Moreover, the continuous increase in energy production is expected to improve the output of the industries. High electrification of these industries is expected to reduce industrial carbon emissions by 48% by 2050 as portrayed by the model. The 48% reduction in carbon emissions is also due to implementation of carbon capture systems in most industries. Space heating demands in the industries is expected to drop by 25 per cent (2050-calculator-tool.decc.gov.uk, 2014). Hot water demand is expected to reduce by 10% while that of cooling is expected to drop by 60%. These reductions are due to increased electrification of industries. The model indicates that biogas and other gases are expected to dominate commercial heating. The results can be interpreted in terms of safety of biogas as a source of energy. Biogas is a cheaper form of energy as compared to electricity in commercial heating. Moreover, since commercial heating uses a lot of energy, it would be economical to use biogas (Sharma and Mishra, 2013). The model predicts increased generation of nuclear energy. Nuclear energy provides large amounts of energy that is needed for the future industries. Other alternative sources of energy by 2050 include little supply of energy from CCS power stations. The reason for this is because a lot of research is needed for the CCS energy. Clean sources of energy including offshore and onshore wind energy, tidal and wave energy, biomass, and solar energy are expected to increase massively. The increased energy from these sources is because of the need to reduce carbon emissions by 2050. The improving trends in technology are expected to lead to the realization of energy generation through these sources. Hydroelectric power and geothermal energy sources are also expected to increase their output due to increased research in the sector. Emerging trends in the production of clean energy through bioenergy, marine algae, waste recycling, and biomass energy are also predicted to improve tremendously by 2050. The increased production of energy is due to innovations and technological advancements. Current trends in innovation and technological advancements support this prediction (Guest, 2010). The assumption that by 2050 there will be 100% reduction as indicated by the results generated by 2050 carbon emission reduction tool is not very realistic. It is based on assumption that all vehicles and trains will be electrified. Martin (2000) noted that fuels will still be used beyond 2050 though in lower amounts as demonstrated by trends in energy use. Another value that can be question as unrealistic is the use of only clean gases for home cooking by 2050. Biogas and other clean gases are not easily available for entire homes of United Kingdoms. Jackson (2009) identified that biogas and other clean gases are not easily available. Therefore, other sources of clean energy are recommended to complement biogas and other clean gases. The explorations of these sources of clean energy are still on-going (Jackson, 2009). Conclusion Most of the predictions produced by the model are effective for reduction of carbon emissions by 2050. However, the effectiveness of some results is controversial. For example, 100 per cent emission by vehicles might not be possible as demonstrated by the trends in the motor vehicle manufacturing industry. Currently, most vehicles are powered by petroleum fuels; a trend that has dominated the industry for centuries. Despite the improvement in reduction of carbon emissions from vehicles, 100 % reduction in emissions is still unrealistic. The support for 100% reduction in emission is due to 100% electrification of trains and 50% electrification of buses. The remaining 50% of buses could be emitting substantial amounts of carbon. Another controversial result from the 2050 tool is the use of a mixture of biogas and other gases for home cooking. These gases are not easily available as demonstrated by current trends. Even though there is increased research in the field, producing clean gases enough for a majority of homes cannot be achieved easily. Clean gases that do not emit significant amounts of carbon are not easily available as indicated by current trends. However, a significant number of homes can be predicted to use clean sources of energy including biogas. Work Cited 2050-calculator-tool.decc.gov.uk, (2014). 2050 Pathways Calculator. [online] Available at: http://2050-calculator-tool.decc.gov.uk/pathways/31134443324444441444414113322121332311213213111411121/primary_energy_chart [Accessed 27 Nov. 2014]. Brooks, R. (2011). Using carbon emissions data to ‘heat up’ descriptive statistics. Teaching Statistics, 34(1), pp.25-30. Building bricks from carbon emissions. (2013). ECOS. Carbon dioxide emissions rise to record levels. (2008). Nature, 455(7213), pp.581-581. Carbon emissions. (2008). ANZ Journal of Surgery, 78(12), pp.1137-1137. Elkins, P. and Baker, T. (2001). Carbon Taxes and Carbon Emissions Trading. Journal of Economic Surveys, 15(3), pp.325-376. EGU 2012: The latest dirt on reducing carbon emissions. (2013). Physics Today. Gilbert, N. (2009). Curbing population growth crucial to reducing carbon emissions. Nature. Gray, D. (2007). Increasing security and reducing carbon emissions of the U.S. transportation sector. [Pittsburgh, Pa.]: National Energy Technology Laboratory. Green, W. and Zhou, S. (2013). An International Examination of Assurance Practices on Carbon Emissions Disclosures. Australian Accounting Review, 23(1), pp.54-66. Guest, R. (2010). Global Demographic Change, Carbon Emissions, the Optimal Carbon Price and Carbon Abatement. Global Economy Journal, 10(2). Jackson, F. (2009). Conquering carbon. London: New Holland. Lysack, M. (2008). Global warming as a moral issue: ethics and economics of reducing carbon emissions.Interdisciplinary Environmental Review, 10(1/2), p.95. Martin, W. (2000). Reducing carbon dioxide emissions through joint implementation of projects. Washington, D.C.: World Bank, Development Research Group, Trade. Mulligan, J. (2010). Carbon dioxide emissions. New York: Nova Science Publishers. Nantke, H. (2011). Emissions trading in aviation. Carbon Management, 2(2), pp.127-134. Sharma, S. and Mishra, S. (2013). Intelligent Transportation Systems-Enabled Optimal Emission Pricing Models for Reducing Carbon Footprints in a Bimodal Network. Journal of Intelligent Transportation Systems, 17(1), pp.54-64. United Kingdom auctions carbon emissions permits. (2008). Nature, 456(7221), pp.435-435. Zhang, Z. (1996). Energy, carbon dioxide emissions, carbon taxes and the Chinese economy. Intereconomics, 31(4), pp.197-208. Zhanga, Y. (2011). Research on International Carbon Emissions Trading and Optimal Exports Scale of China Carbon Emissions. Procedia Environmental Sciences, 10, pp.101-107. Read More
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