Construct x-y graphs to help analyse this data set make


Atmospheric Pollutants

Acids rain is formed when sulphur dioxide from power plant and smelters, for example, and oxide of nitrogen from car exhausts react with atmospheric oxygen to for sulphuric acid. Figures 1 and 2 are 2003 and 2002 maps of North America showing measured values of rainfall acidity, expressed as pH and total sulphur deposition respectively.

1201_Figure.png

Figures 3 and 4 are from the NASA Ozone Monitoring Instrument (OMI) for 2005 and 2012 respectively, showing atmospheric concentrations of NO2 across the USA. Nitrogen dioxide is one of the six common pollutants regulated by the U.S. Environmental Protection Agency (EPA) because it is associated with adverse health effects. NO2 is produced primarily during the combustion of gasoline in automobile engines and coal in power plants.

815_Figure1.png

Complete and answer the following:

a. On Figure 1, contour the pH data in the eastern part of North America using a contour interval of 0.25 pH.

b. On Figure 2, contour the sulphur deposition data in the eastern part of North America using a contour interval of 2.5, 5.0, 7.5 and 10.

c. Are their trends in the contoured data for each map? If so what and where do they occur?

d. If you observe trends, what are the probable reasons for those trends? DO NOT GUESS!

e. What are the lowest and highest values on Figures 1 and 2? Where do those values occur?

f. What are the possible reasons for those extreme values?

g. Is there a possible causal link between pH and sulphur deposition within N. America, particularly the USA? Why?

h. Rainfall pH tends to generally range between ∼5.0 to 7.0 in the far north of North America, why?

i. Figures 3 and 4, show the change in atmospheric NO2 concentration between 2005 and 2012. What has happened?

j. How can you account for the change in NO2 concentration between 2005 and 2012, in other words WHY has the change occurred?

k. How does the pH and total sulphur values shown in Figures 1 and 2 compare to the distribution of NO2 in Figure 3? Is there a similar distribution or pattern? Explain!

l. Compare the pH and total sulphur values shown in Figures 1 and 2 to the distribution of NO2 in Figure 4? Is there a change in distribution or pattern, would you expect pH values to remain the same if measured after 2012? Explain!

Gasoline/Diesel usage

Many claim that gasoline is too cheap in North America and that we must use less. The following table shows the amount of sales tax (not carbon tax) levied on gasoline (as us$ per L) and the amount of gasoline consumed per person per country (in L).


      Fuel Cost

Fuel Fax as % of tool price


Gasoline use

Country

(in US $)

(in US $)

(% of total)

(% of total)

Urbanization

GDP
(per capita)

(capita/yd


Gasoline

Diesel

Gasoline

Diesel

% of
population

(in 1000 US$)

L per

Australia

1.23

1.28

33.11

33.13

89

60.925

2727

Belgium

1.9

1.69

54.1

46.69

98

47,352

3584

Canada

1.17

1.16

29.28

24.14

82

50.235

3852

Denmark

2.01

1.8

53.76

46.97

88

60.707

1681

Finalnd

1.89

1.78

59.68

50.78

84

49.823

2259

France

1.79

1.63

57.76

49.71

79

42.732

1644

Germany

1.8

1.58

58.08

49.21

75

47.821

1709

Ireland

1.92

1.84

55.81

50.57

63

54.374

1789

Italy

2.14

2.01

60.35

55.41

69

34.908

1454

Japan

1.38

1.1

40.03

29.66

93

36.194

2048

Mexico

1.03

1.02

13.79

13.79

79

10.325

1088

New Zealand

1.71

1.11

42.07

13.31

86

37.895

2014

Norway

2.27

2.11

58.71

52.68

80

97.307

3156

Portugal

1.89

1.64

56.84

45.53

63

22.132

1400

Spain

1.63

1.55

50.56

77.76

79

29.767

1717

Sweden

1.82

1.82

58.04

51.59

86

58.938

2017

Switzerland

1.74

1.79

19.65

48.32

74

85.594

1961

United Kingdom

1 92

1.99

61.05

58.59

82

46.332

1488

United States

0 76

0.97

14.75

13.89

81

54.629

3409


Data from World Bank (2014 data)

Data from (EA (201

a. Construct x-y graphs to help analyse this data set. Make sure each graph is properly labeled and include your name. Calculate the R2 regression value an on it assume a linear relationship!

b. Discuss possible relationships between the data! What is the causality between this data? For example, if you consider gasoline usage, are people less mobile in the United Kingdom or Portugal, or are there other reasons for the gasoline consumption patterns exhibited in the table? Research your answers, do not speculate and do not assume a single causality between data, there could be other factors at work not indicated by the data! Cite references!

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