11

LEVELS AND TRENDS OF LEVELS AND TRENDS OF CARBON DIOXIDE CARBON DIOXIDE

EMISSIONSEMISSIONS

Arun K SinhaArun K Sinha

Markandey Rai &Markandey Rai &

Ashbindu SinghAshbindu Singh

IAOS Conference 2010, Santiago, Chile, Oct. 20-22, 2010IAOS Conference 2010, Santiago, Chile, Oct. 20-22, 2010

2222

LEVELS AND TRENDS OF CARBON DIOXIDE…LEVELS AND TRENDS OF CARBON DIOXIDE…

There are eight United Nations Millennium There are eight United Nations Millennium Development Goals (MDGs).Development Goals (MDGs).

Its seventh goal aims to ensure Its seventh goal aims to ensure environmental sustainability, which is of environmental sustainability, which is of interest for the present investigation. interest for the present investigation.

It consists of four targets that include It consists of four targets that include target 7.A, 7.B, 7.C, and 7.D .target 7.A, 7.B, 7.C, and 7.D .

3333

LEVELS AND TRENDS OF CARBON DIOXIDE…LEVELS AND TRENDS OF CARBON DIOXIDE…

Target 7.ATarget 7.A consists of ten indicators that consists of ten indicators that include proportion of land area covered by include proportion of land area covered by forest and carbon dioxide (COforest and carbon dioxide (CO22) )

emissions. emissions.

The address for the MDGs Indicators is The address for the MDGs Indicators is http://mdgs.un.org or http://mdgs.un.org/unsd/mdg/Data.aspx .

4444

LEVELS AND TRENDS OF CARBON …LEVELS AND TRENDS OF CARBON …

The site presents the official data, The site presents the official data, definitions, methodologies and sources for definitions, methodologies and sources for the 48 indicators for measuring progress the 48 indicators for measuring progress made towards the Millennium made towards the Millennium Development Goals. Development Goals.

Analyses point out to the excessive carbon Analyses point out to the excessive carbon dioxide emissions as one of the main dioxide emissions as one of the main factors of climate change across the world. factors of climate change across the world.

5555

LEVELS AND TRENDS OF CARBON LEVELS AND TRENDS OF CARBON ……

With this view a trend analysis of the With this view a trend analysis of the emission is conducted. emission is conducted.

There are two main sources for the data of There are two main sources for the data of the carbon dioxide emission.the carbon dioxide emission.

6666

LEVELS AND TRENDS OF CARBON …LEVELS AND TRENDS OF CARBON …

The Carbon Dioxide Information Analysis The Carbon Dioxide Information Analysis Center (Center (CDIACCDIAC) and the United Nations ) and the United Nations Framework Convention on Climate Framework Convention on Climate Change (Change (UNFCCCUNFCCC). ).

For the present investigation the data set For the present investigation the data set provided by the CDIAC is used because it provided by the CDIAC is used because it gives data sets for a larger number of gives data sets for a larger number of countries / areas as compared with the countries / areas as compared with the UNFCCC. UNFCCC.

7777

LEVELS AND TRENDS OF CARBON LEVELS AND TRENDS OF CARBON ……

The used data set was last updated on 23 The used data set was last updated on 23 June 2010. June 2010.

The unit of emission value is in thousand The unit of emission value is in thousand metric tons of COmetric tons of CO22. .

Only 210 out of 216 countries / areas have Only 210 out of 216 countries / areas have values of emissions for 1998-2007. values of emissions for 1998-2007.

8888

LEVELS AND TRENDS OF CARBON LEVELS AND TRENDS OF CARBON ……

But 209 places are considered after But 209 places are considered after excluding “Niue” because its value is “4” excluding “Niue” because its value is “4” for each of the ten years under for each of the ten years under investigation. investigation.

99

TREND ANALYSIS OF CARBON DIOXIDE EMISSION …

For understanding the trends of the carbon dioxide emissions a linear trend equation based on the last ten years data is obtained for each country / area.

The investigation is based on the data of 1998 to 2007.

1010

TREND ANALYSIS OF CARBON DIOXIDE EMISSION …

The assumption of linear trend is justified because of smaller number of observations.

This assumption appears to be more reasonable for understanding the annual growth rate.

1111

TREND ANALYSIS OF CARBON DIOXIDE EMISSION …

Out of the two hundred nine thirty four countries / areas (16.3%) reveal negative annual growth rates (showing decreasing emission).

The linear trend equations disclose that China has the highest annual growth rate (394016) while Germany has its lowest value (-7488).

1212

TREND ANALYSIS OF CARBON DIOXIDE EMISSION …

This shows that the emission over the years has decreased in Germany.

The descriptive statistics of the two countries are obtained.

1313

Figure 1. A pie chart depicting the sign of the annual growth rates of the carbon dioxide emissions

NP

Category

P175, 83.7%

N34, 16.3%

Countries / Areas with Negative (N) and Positive (P) Growth Rates

1414

Table . Descriptive Statistics of China and Germany

Variable China Germany

Total Count 10 10

Mean 4493614 831121

SE Mean 394807 9055

StDev 1248490 28635

CV 27.78 3,45

Minimum 3318045 787936

Q1 3384908 811310

Median 4020418 829716

Q3 5738873 840683

Maximum 6538367 894381

Range 3220322 106445

1515

Figure2. Boxplots of carbon dioxide in China and Germany during 1998-2007

7000000

6000000

5000000

4000000

3000000

Carb

on D

ioxid

e Em

issions

900000

875000

850000

825000

800000

Carb

on D

ioxid

e Em

issions

Boxplot of Carbon Dioxide Emissions in China, 1998-2007

Median 4020418

Boxplot of Carbon Dioxide Emissions in Germany, 1998-2007

Median 829716

894381 in 1998

1616

Figure3. Trend analysis plots for China and Germany, 1998-2007

10987654321

7000000

6000000

5000000

4000000

3000000

YearsCarb

on D

ioxid

e Em

issions

ActualFits

Variable

10987654321

900000

875000

850000

825000

800000

YearsCarb

on D

ioxid

e Em

issions

ActualFits

Variable

Trend Analysis Plot for China, 1998-2007Linear Trend Model

Yt = 2326528 + 394016*t

Trend Analysis Plot for Germany, 1998-2007Linear Trend Model

Yt = 872307 - 7488.34*t

1717

References

Levin, Richard I. and Rubin, David S. (2004). Statistics for Management. Seventh Edition. Pearson Education, (Singapore) Pte. Ltd. Indian Branch, Delhi 110092, India.

Levine, D. M., Stephan, D., Krehbiel T. C. and Berenson, M. L (2006).

Statistics for Mangers, Fourth Edition. Prentice- Hall of India Private Limited, New Delhi-110 001,India

1818

Table1. Countries / areas with linear trend equations and annual growth rates during 1998-2007

Serial No. Countries / Areas LinearTrend Equations

Annual Growth Rate

12345678910

AfghanistanAlbaniaAlgeriaAndorraAngolaAnguillaAnt. BarbudaArgentinaArmeniaAruba

841.1-24.3t 2224.6 + 266.4t105018+ 3314.45t496.7 + 6.7t3700.9 + 1877.6t22.5 + 3.1t313.7 + 12.1t126161 + 4489.7t2758.5 + 177.2t1819.1 + 65.9t

-24.3266.43314.46.71877.63.112.14489.7177.265.9

1919

111213141516171819202122232425

AustraliaAustriaAzerbaijanBahamasBahrainBangladeshBarbadosBelarusBelgiumBelizeBeninBermudaBhutanBoliviaBosnia Her.

320386 + 4587.3t60142.5 +1211.9t29174.7 + 479.0t1701.7 + 5.9t16424.8 + 416.7t21833.5 +2236.5t1128.2 + 21.2t56210.7+ 1118.7t120384 - 1535.5t581.4 - 20.0t767.5 + 279.1t483 + 5.4t345 + 23.1t8716.3 + 362.4t16548 + 1178.8t

4587.31211.9479.045.9416.72236.521.21118.7-1535.5-20.0279.15.423.1362.41178.8

2020

2627282930313233343536373839404142434445

BotswanaBrazilBrit.V. IslandsBrunei Daru.BulgariaBurkina FasoBurundiCambodiaCameroonCanadaCape VerdeCayman Isl.Cent. Af. RepChadChileChinaChina,HKS AChina, MSRColombiaComoros

3662.2 + 122.8t311315 + 4816.0t45.9 + 5.3t5460.6 + 96.9t44090.1 + 428.9t784.9 + 67.4t309.4 - 16.4t1666 + 261.7t2603.1 + 234.6t484375 + 8588.6t137.8 + 18.6t301.7 + 27.2t257.3 - 1.7t57.3 + 38.7t54635.1 +1284.4t2326528 +394016t40122.5 - 112.4t1565.5 + 10.5t58337.7 + 79.0t67.4 + 5.4t

122.84816.05.396.9428.967.4-16.4261.7234.68588.618.627.2-1.738.71284.4394016.0-112.410.579.05.4

2121

4647484950515253545556575859606162636465

CongoCook IslandsCosta RicaCote d'IvoireCroatiaCubaCyprusCzech RepublDemR CongoDenmarkDjiboutiDominicaDom RepuEcuadorEgyptEl SalvadorEquatGuineaEritreaEstoniaEthiopia

583.6 + 109.6t12.7 + 5.4t4787 + 301.6t6806.5 + 26.8t20022.6 + 466.7t24863.3 + 130.3t6378.2 + 161.9t122430 + 193.5t1896 + 30.0t51784.7 - 121.7t383.1 + 9.6t82 + 4.2t19284.4 + 165t19618.9 + 985.3t107571 + 6691.3t5555.4 + 103.7t123.9 + 598.0t626.1 + 3.4t15647.3 + 344.2t4577.8 + 136.4t

109.65.4301.626.8466.7130.3161.9193.530.0-121.79.64.2165.0985.36691.3103.7598.03.4344.2136.4

2222

66

67

68

69

70

71

72

73

74

75

76

77

78

79

80

81

82

83

84

85

Faeroe Islands

Falkland Is (M)

Fiji

Finland

France

French Guiana

French Poly

Gabon

Gambia

Georgia

Germany

Ghana

Gibraltar

Greece

Greenland

Grenada

Guadeloupe

Guatemala

Guinea

Guinea-Bissau

653.4 + 3.7t

31.8 + 2.7t

638.9 + 113.1t

53909.6 +1157.7t

387334 - 699.2t

909.9 - 6.1t

567.9 + 30.8t

1312.2 + 60.8t

226.7 + 14.4t

3841.3 + 119.9t

872307 - 7488.3t

5633.2 + 327.2t

301.4 + 9.9t

86893.4 +1301.1t

548.067 - 5.5t

190.5 + 5.2t

1657.3+ 59.5t

8412.3 + 447.6t

1238.1 + 15.1t

193.8 + 8.4t

3.7

2.7

113.1

1157.7

-699.2

-6.1

30.8

60.8

14.4

119.9

-7488.3

327.2

9.9

1301.1

-5.5

5.2

59.5

447.6

15.1

8.4

2323

86

87

88

89

90

91

92

93

94

95

96

97

98

99

100

101

102

103

104

105

Guyana

Haiti

Honduras

Hungary

Iceland

India

Indonesia

Iran

Iraq

Ireland

Israel

Italy

Jamaica

Japan

Jordan

Kazakhstan

Kenya

Kiribati

Korea, Dem. P

Korea, Rep of

1641 - 18.4t

1073.5 + 125.6t

3965.5 + 441.2t

59810.5 - 261.0t

2047.7 + 23.8t

999346+ 54481.5t

202922+ 18003.5t

278656+ 20834.2t

67252.5+ 3570.6t

39432.9 + 522.8t

62392.9 + 229.9t

437707 + 3086.5t

9023.9 + 328.6t

1213100+ 4374.4t

12951.1 + 877.1t

100113+ 10741.6t

9072.3+ 205.5t

29.9 - 0.2t

70651.7+ 1101.5t

389238+ 11733.6t

-18.4

125.6

441.2

-261.0

23.8

54481.5

18003.5

20834.2

3570.6

522.8

229.9

3086.5

328.6

4374.4

877.1

10741.6

205.5

-0.2

1101.5

11733.6

2424

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

Kuwait

Kyrgyzstan

Lao P D Repu

Latvia

Lebanon

Liberia

Libyan A Jama

Lithunia

Luxembourg

Madagascar

Malawi

Malaysia

Maldives

Mali

Malta

Marshall Island

Martinique

Mauritania

Mauritius

Mexico

58505.8+ 2979.7t

4652.8 + 108.0t

843.5 + 76.0t

6655.1 + 69.5t

16824.8 - 115.4t

325.5 + 41.9t

46130.9+ 1162.9t

13483.7 + 65.1t

6902.5 + 485.9t

1905 + 21.0t

944.5 + 14.7t

95611.3+10110.9t

328.3+ 55.9t

520.9 + 5.6t

2098.7 + 63.8t

65.9 + 3.0t

1915.5 - 16.5t

981.7 + 85.8t

2132.1 + 172.3t

367873 + 8851.3t

2979.7

108.0

76.0

69.5

-115.4

41.9

1162.9

65.1

485.9

21.0

14.7

10110.9

55.9

5.6

63.8

3.0

-16.5

85.8

172.3

8851.3

2525

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

Mongolia

Montserrat

Morocco

Mozambique

Myanmar

Namibia

Nauru

Nepal

Netherlands

Netherl Ant.

New Caledonia

New Zealand

Nicaragua

Niger

Nigeria

Norway

Occ Pale Terri

Oman

Pakistan

Palau

6857.3 + 287t

46 + 3.3t

29845.7+ 1637.5t

948.9+ 139.9t

6401.6 + 711.6t

1564.1+ 138.1t

135.9 + 0.8t

2740.5 + 57.8t

169071 + 383.6t

2245 + 469.7t

1817.3 + 113.5t

31656.8 + 226.5t

3427.7 + 100.8t

940.5 - 11.7t

48613.7 +6433.1t

35693.3+ 1153.8t

238.1 + 230.7t

14074.4+ 2525.7t

85871.9+ 6500.8t

107.9 + 11.5t

287.0

3.3

1637.5

139.9

711.6

138.1

0.8

57.8

383.6

469.7

113.5

226.5

100.8

-11.7

6433.1

1153.8

230.7

2525.7

6500.8

11.5

2626

146

147

148

149

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

165

Panama

Papua N Gui

Paraguay

Peru

Philippines

Poland

Portugal

Qatar

Rep of Moldova

Reunion

Romania

Russian Feder

Rwanda

Saint Helena

S Kit and Nevis

Saint Lucia

S P and Miqu

SVince and G

Samoa

Sao T Principe

5637.1 + 109.4t

2455.7 + 204.1t

4227.7 - 31.9t

24091.9+ 1355.7t

77616.7 - 406.1t

311190 - 293.6t

63232 - 187.6t

21059.9+ 3349.4t

4569.1 - 3.1t

2421.6 + 42.7t

92371.7 + 140.7t

1389868 + 15759t

657.7 + 4.8t

17.5 - 0.8t

83.9 + 18.5t

309.9 + 6.6t

51.9 + 1.6t

157.8 + 4.9t

130.1 + 3.2t

5.9t

109.4

204.1

-31.9

1355.7

-406.1

-293.6

-187.6

3349.4

-3.1

42.7

140.7

15759.0

4.8

-0.8

18.5

6.6

1.6

4.9

3.2

5.9

2727

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

Saudi Arabia

Senegal

Serbia and Mont

Seychelles

Sierra Leone

Singapore

Slovakia

Slovenia

Solomon Islands

Somalia

South Africa

Spain

Sri Lanka

Sudan

Suriname

Swaziland

Sweden

Switzerland

Syrian A Repub

Tajikistan

205722+ 20327.3t

3412.4 + 209.3t

41863.9 + 1251t

465.3 + 26.3t

500.5 + 90.1t

54465.3 - 78.8t

40859 - 310.5t

14735.5 + 26t

157.1 + 3.3t

486.6 + 11.6t

347408 + 7068.7t

263241+ 10100.1t

8083.5+ 458.3t

3529 + 858.8t

2081.7 + 35.1t

1247.7 - 25.4t

54020.8 - 290.6t

41559.3 - 144.2t

62514.1 + 836.3t

4423.53 + 191.3t

20327.3

209.3

1251.0

26.3

90.1

-78.8

-310.5

26.0

3.3

11.6

7068.7

10100.1

458.3

858.8

35.1

-25.4

-290.6

-144.2

836.3

191.3

2828

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

Thailand

The fo Yug R M

Togo

Tonga

Trin and Toba

Tunisia

Turkey

Turkmenistan

Turks and C Isl

Uganda

Ukraine

Unit A Emirates

United King

Uni R of Tanzan

United States

Uruguay

Uzbekistan

Vanuatu

Venezuela

Viet Nam

173794 + 11477t

12331.9 - 146.3t

1319.27 - 0.1t

107.9 + 7.8t

18238.1 + 1780t

17638.1 + 642.7t

177859 + 8572.7t

30093.3+ 1656.5t

-20.7 + 18.1t

918.9 + 185.8t

309954 + 1323.6t

93027.9+ 3158.6t

544899 - 92.2t

1668.5 + 408.1t

5516667+34014.9t

5314.1 + 68.9t

121009 - 445.9t

78.3 + 1.7t

172740 - 242.3t

33091 + 8194.2t

11477.0

-146.3

-0.1

7.8

1780.0

642.7

8572.7

1656.5

18.1

185.8

1323.6

3158.6

-92.2

408.1

34014.9

68.9

-445.9

1.7

-242.3

8194.2

2929

206

207

208

209

Western Sahara

Yemen

Zambia

Zimbabwe

231.4 + t

11418.4+ 1046.7t

1761.3 + 76.3t

15476.7 - 634.7t

1.0

1046.7

76.3

-634.7