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Custom Energy Efficiency and Environmental Impact essay paper sample

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Executive Summary

Due to increased industrialization in the world, the global temperatures have been rising and experiences of adverse effects of ozone layer depletion keeps on being experienced. To be able to reduce these effects, the world made a point of reducing carbon emission under the now famous Kyoto Protocol. In this protocol, there was a decision for individual countries as well as organizations to formulate ways and means of achieving their ends by ensuring that they were in a position to effectively minimize carbon emissions. In this research paper, the researcher will conduct a critical assessment on the levels of energy efficiency that can be seen in buildings as well as make simulations on the state of buildings as they are. In this research, the researcher will start by looking at the literature that is available that is in line with energy efficiency. In this section, the researcher will look at what other researchers' term as efficient energy usage and their suggestions and whether their research is dependable or not. This will be followed by the researchers' simulations on a renewable energy which will be solar energy. With the results obtained, there will be tabulation and analysis of these results which will include graphs and other econometric analysis tools like gretl econometric tool. From the results and analysis, a conclusion will be drawn with reference to the previous research work.

Aims and Objectives

The aim of the research is to conduct a critical assessment on energy efficiency within a defined building.

The objectives of the researcher include: -

Ø  Critique the energy demands within a building

Ø  Find out the benefits of energy efficiency

Ø  Conduct review on available literature on energy efficiency as well as environmental impact of energy efficiency in the long run within a defined building.

Ø  Computer simulations in support of the researcher's argument

Ø  Analysis of the results based on econometric analysis tools for a bigger picture.

Literature Review

There is not any one building that does not require energy to some extent. What matters is the amount f energy that a building requires. The problem that is registered is that of energy requirement that has been brought about by increasing needs for energy consumptions at homes. It has been estimated that the amount of energy that is used in non-residential building accounts for up to 30-40% of the entire nation's energy that is consumed annually (von Paumgartten 2003, p. 28). It is further argued that the non-residential buildings have been found to have atmospheric emissions that account for between 30-40% that is directly linked to environmental pollution (von Paumgartten 2003, p. 28). The same non-residential buildings have been found to consume up to 60 % of the entire country's electricity consumption which is quite high resulting from increased energy efficiency. It is estimated that 25-30% of all the wood that is used and the related materials go towards the non-residential buildings creating a big surge for deforestations and logging to satisfy their needs (von Paumgartten 2003, p. 28). But then, where exactly lays the problem? Energy inefficiency is the answer to that question.

It is estimated that energy efficiency can be obtained from implementation of more aggressive measures like updating the kind of lamps (Wroblaski, Penny and Morton 2011, p. 10) by using lighting systems that are highly efficient (Life Sciences Complex Receives high Performance Building Designation 2010, p. 5). It is also proposed that the occupants of such buildings ought to be educated on ways and means of conserving energy to reduce the energy consumption within these premises (Wroblaski, Penny and Morton 2011, p. 10).

Roper and Beard (2006, p. 92) also note that, most managers and Chief Executive Officers do not know what happens to their waste as they are concerned about where their resources come from. This means that waste management is an increasing problem than anticipated. According to Roper and Beard (2006, p. 91), it is important that all people and organization know that the sustainability of an ecosystem is dependent on both the awareness and the actions that are taken to improve those conditions.

It is also argued that during a building construction undertaking, it is important that considerations be made as to the harmful effects that this construction will bring (Roper and Beard 2006, p. 93). Maybe the question to ask at this point would be; is sustainability achievable? Yes, sustainability can be achieved piece by piece.

In von Paumgartten (2003, p. 28), in a research that was done between the years 1990 to 2000, it was found out that energy saving helped decrease energy requirement by up to 166 million MWh (Mega Watt Hour) (von Paumgartten 2003, p. 28). When this is interpreted in electricity load, it translated to 2,511 Mega Watts (von Paumgartten 2003, p. 28). According to von Paumgartten (2003, p. 28), this was estimated to be an amount that a city like California, would consume in a period of two yeas in every household within that region. If this was counted in monetary terms, this would translate to a staggering $ 16.7 billion that would be saved and this would in return decrease the amount of energy imported hence decreasing amount charged per unit to the customers (von Paumgartten 2003, p. 28). This energy saving would reduce the amount of carbon dioxide emitted by up to 217 million tones, which has been found to have similar benefits  to the environment as if 650 million trees were planted (von Paumgartten 2003, p. 28).

Based on this performance, it was projected that, if the country embarked on a serious energy saving strategies, especially in buildings, by the year 2020, the amount of energy usage that will have been saved will amount to 971 million Mega Watt hour (MWh) (von Paumgartten 2003, p. 28). This is like decreasing electricity demand by a margin of up to 6,127 MW which can comfortably be equated to $ 95.2 billion saved from energy alone in United States of America (von Paumgartten 2003, p. 28).

This data is just from buildings. If similar savings were to be done in other industries, the Kyoto Protocol's mandate would be achieved much easier. However, the researcher would like to know, are the above results a true reflection of the reality or are they just theories? In the following section, the researcher will conduct some simulations that will aid in explaining this.

Computer Simulation

In this section, the researcher will make use of simulations that are aimed at detailing the heat flux that is obtained and / or recorded in a building. As noted in Martens, Bass and Alcazar (2008, p. 401), computer simulations have been found to be quite effective in providing the necessary information with the least cost possible. The reason for the choice of latent heat equation is that it focuses on solar energy and the energy of the surrounding medium as it incorporates the nature of material used in its analysis. This simulation can be obtained using the equation proposed in Martens, Bass and Alcazar (2008, p. 401).

The simulation provides a good view of the different properties of different materials that are used in building and construction. This simulation is done using MATLAB & SIMULINK since the simulation program is able to provide a wide variety of analytical tools.

From the simulation, it is evident that the wall type that has the highest density does provide the highest diffusion resistance while that with the lowest (that is Air with density 0) provides almost negligible diffusion resistance. From that result, it can be concluded that diffusion is directly proportional to diffusion resistance. Similar results are obtained when considering the ordinary roof type s. However, it is interesting to note that the results are different while considering green roof materials. For example, if one compares OSB with plywood, OSB has a density of 560 while its diffusion resistance is at 12. In comparison, Plywood has a density of 600 is found to have a diffusion resistance amounting to 575. The same conflicting results can be observed in the table still meaning that there exists no direct correlation between density and diffusion resistance. This sample provides good analysis of the kind of materials that can be used to maximize on energy intake from the Sun.

As far as diffusion resistance is concerned, Air, Gravel and Fiber are the most reliable while steel and aluminum are the least reliable materials. However, when it comes to conductivity, the reverse is observed with aluminium and steel leading in the category. Air and Earth have the highest recordings in solar absorption hence the inclination to include green roofing to maximize on solar energy absorption. According to von Paumgartten (2003, p. 30) energy efficiency is achieved within a building when only a minimal amount of energy is used. For example, having green roof as also supported by Roper and Beard (2006, p. 91 +) and Martens, Bass and Alcazar (2008, p. 400 +) can help maintain conducive room temperature by ensuring that the temperature is well regulated.

Consider facts that are presented in the simulation above. Considering the column labeled Specific Heat, it can be seen that in most of the cases, for a material with higher density, there was a reported lower Specific Heat while a material with lower density recorded a higher Specific Heat. For example, Glasswool walls have a density of 250 Kg/m3 with a related Specific Heat of 821 J/ kg OC while under the same category, Brick wall's density is 2000 Kg/m3 with a Specific Heat of 652 J/ kg OC. Another example can be seen in ground floor's chipboards which have a density of 800 kg/ m3 and it has a Specific Heat of 2090 J/ kg OC. Gravel has a density of 2050 kg/m3 and a Specific Heat of 180 J/ kg OC.

Results, graphs and Discussions

The following results were obtained from collection and observation of the prevailing weather condition for a period of two weeks which would provide good data about the amount of sunshine that was being received on the earth's surface. It is good to note that at times, due to very low temperatures, some heating was done in the rooms to make it habitable. For example, at some point on both Thursday and Friday, it became necessary to increase the heat indoor since the temperatures had fallen to -6 OC. The average daily weather recordings read as follows

Quantity

Units

Total

Mon

Tue

Wed

Thur

Fri

Sat

Mon

Tue

Wed

Thur

Fri

Temp. (Average)

OC

3

-2

5

3

2

4

9

6

6

5

7

2

Temp. (High)

OC

8

5

6

5

8

10

7

10

9

9

11

6

Temp. (Lows)

OC

-2

-3

-1

-2

-6

-6

-2

1

3

0

2

-4

Ppt. (Average)

Cm

54

5

5

5

5

4

6

5

4

4

6

5

Ppt. (Morning)

%

82

86

75

79

79

83

85

81

84

85

80

81

Ppt. (Evening)

%

69

68

71

67

69

72

70

70

68

73

69

65

When the average temperature is analyzed with reference to the normalization graph, the following graphical representation is achieved with the graphs normalized at N (4.2727, 2.9695). Against the normalization curve, the data does not offer smooth representation.

When the average precipitation is plotted against the normalization curve, the following is yielded. The data is within range of the normalization curve.

From the simulation and the data provided above, it is clear that there is increased need to have better energy management. For example, as proposed, it is prudent for building architects, structural engineers and all stakeholders in the building industry should implement more practical measures to ensure better energy management. For example, having Occupancy-sensor lighting control is a more appropriate system as it ensures light is on when there is an occupant but turns off if there is no occupant even if the occupant forgot to turn the lights out (Life Sciences Complex receives High Performance Building Designation 2010, p. 5). Another area where more energy can be saved is in implementation of elevator systems that switch off lights when not in use and making ventilation systems only accessible on demand (Life Sciences Complex receives High Performance Building Designation 2010, p. 5).

The normalization graph shown above given more details as it shown that there exists great variation in the temperature received hence the analysis cannot be completely handled with these data. In addition, the data is done within a short period of time which is restrictive to the research. The second normalization graph gives better results as is lies within acceptable range.

Conclusion

In conclusion, it is clear that energy efficiency is an area that cannot be overlooked. In this research paper, it is evident that there is emphasis that is laid on energy consumption especially in non-residential buildings. In the literature review it was found that previous research has shown that it is possible to have a building that is energy-efficient. Building did save up to $ 16.7 billion out of energy savings. Future projections have been put at $ 95.2 billion in energy savings which is achievable within the next nine years. From the simulation it is evident that the density of most of the building materials is inversely proportional to the Specific Heat and directly proportional to the diffusion resistance.

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