8. 1.2.1. Other Industrial Roundwood, Fuelwood and Charcoal Production-Consumption ..... 7.5. 5.5. 1.1. 0.3. 0.0. 0.4. 0.0. 0.0. 0.2. Cambodia. 31.4. 28.0. 8.1. 7.7. 0.2. 0.0. 0.1 .... 8.5. Madagascar. 111.1. 50.4. 14.1. 9.5. 3.9. 0.0. 0.1. 0.4. 0.0. 0.0. 0.2 ...... 0.05. 0.06. 0.08. 0.00. 0.04. 0.02. Cyprus. 0.16. 0.04. 0.18. 0.01. 0.00. 0.02.
SUPPLEMENTARY INFORMATION DOI: 10.1038/NCLIMATE1535
Timing of carbon emissions from global forest clearance
Timing of carbon emissions from global forest clearance Supplementary Information
Table of Contents 1. Estimating Initial Carbon Disposition After Forest Clearance (t = 0) ........................................ 1 1.1. Above Ground Biomass and Growing Stock ....................................................................... 2 1.2. Production, Trade and Consumption of Harvested Wood Products (HWPs) ...................... 8 1.2.1. Other Industrial Roundwood, Fuelwood and Charcoal Production-Consumption Route ..................................................................................................................................... 12 1.2.2. Sawnwood, Fiberboard and Plywood/Veneer Production-Consumption Route ........ 14 1.2.3. Paper Production-Consumption Route ....................................................................... 18 1.2.4. Mill Fuel and Fiber Production/Consumption ............................................................ 18 1.3. Estimating Carbon Disposition at t = 0 .............................................................................. 25 2. Estimating Carbon Disposition and Use Over Time................................................................. 29 2.1. HWP Stock......................................................................................................................... 29 2.2. SWDS Stock ...................................................................................................................... 31 3. Carbon Disposition of HWP and SWDS Stocks Following Forest Clearance ......................... 36 3.1. Carbon Disposition of HWP, SWDS, and Atmospheric Stocks over Time ...................... 36 3.2. Trade and Consumption of Carbon as Wood Products ...................................................... 41 3.3. Sensitivity Analysis for Select Parameters ........................................................................ 46 3.4. Regional Analysis of United States ................................................................................... 49
Supplementary Methods 1. Estimating Initial Carbon Disposition After Forest Clearance (t = 0) The first step of this study estimates the initial carbon disposition from removing timber as a result of land use change.
NATURE CLIMATE CHANGE | www.nature.com/natureclimatechange
© 2012 Macmillan Publishers Limited. All rights reserved.
1
1
1.1. Above Ground Biomass and Growing Stock Above ground biomass is defined by the Food and Agricultural Organization (FAO) as “all living biomass above the soil including stem, stump, branches, bark, seeds, and foliage.” 1 It is measured in terms of mass, typically as metric tons. The FAO’s 2010 Global Forest Resources Assessment (FRA) data 1 provides above ground biomass estimates for 169 countries. Above ground biomass is calculated by the FAO using a biomass expansion factor which “expands growing stock to account for non-merchantable biomass components such as branches, foliage, and non-commercial trees.” 2 Dividing above ground biomass values by total forest area (also from the 2010 FRA 1) provides a national average of above ground biomass per hectare. Countries lacking above ground biomass data are assigned values based on regional averages. We then convert above ground biomass to tons of carbon based on the IPCC 3 recommended value of 0.5 Mg C per Mg oven dry wood. Above ground biomass carbon values used in this study are listed in Table S1. Growing stock is the fraction of above ground biomass of merchantable size. It is defined parametrically by the FAO as the “volume over bark of all living trees more than X cm in diameter at breast height (or above buttress if these are higher)” which “includes the stem from ground level or stump height up to a top diameter of Y cm, and may also include branches to a minimum diameter of W cm”. 1 Thus, the parameters X, Y, and W are defined by and vary among countries. The US, for instance, uses values of 12.7 cm and 10 cm for X and Y, respectively, while branches are excluded. Indonesia, on the other hand, uses a value of 20 cm for X, does not specify a value for Y, and excludes branches. Similar to the calculations for above ground biomass, countries lacking growing stock data were assigned values based on regional averages. Since growing stock is specified as a volume, we estimated country-specific carbon density 2
© 2012 Macmillan Publishers Limited. All rights reserved.
factors based on forest-type (temperate vs. tropical). We calculated the proportion land coverage for temperate versus tropical forests based on UNEP World Conservation Monitoring Center geospatial data 4 and corresponding carbon factors from IPCC 3 Table 12.4 (temperate = 0.225 Mg C per m3 wood; tropical = 0.295 Mg C per m3 wood). We estimate that about 33% of Mexico’s forest area, for example, is temperate and 67% is tropical, corresponding to a foresttype weighted carbon factor of 0.272. Carbon factors and the proportion of temperate versus tropical forest area by country are given in Table S5. The resulting growing stock values used in this study are listed in Table S1. Growing stock can further be divided into the fraction commercial and non-commercial species. Commercial growing stock is the fraction of growing stock that is commercial tree species. The percent commercial species is specified by each country in the 2010 FRA survey 1. This value is multiplied by total growing stock to determine the quantity of commercially available biomass (shown in Table S1). For any country i, Equation (1) shows the relationship between above ground biomass (
), commercial growing stock (
merchantable wood (
), non-commercial growing stock (
), and non-
). (1)
In other words, above ground biomass is the sum of commercial and non-commercial growing stock, along with non-merchantable fractions of wood.
3
© 2012 Macmillan Publishers Limited. All rights reserved.
Table S1: Mg C in above ground biomass, growing stock and end product (after accounting for exports, manufacturing efficiencies, mill fuels, and fiber production) per ha at t = 0 (Mg C ha-1) Comm. Growing Stock
Fuelwood
Charcoal
Sawnwood
Fiberboard
Plyven
Mill Fuel Resid.
Country
AGB
Growing Stock
Other
PulpPaper
Afghanistan
23.5
3.6
1.9
0.1
0.1
1.0
0.0
0.5
0.1
0.0
0.1
Albania
47.7
21.8
21.8
4.7
8.7
5.6
0.0
0.7
1.7
0.2
0.3
Algeria
40.2
17.1
17.1
11.0
5.4
0.1
0.2
0.0
0.1
0.2
0.0
Angola
64.3
11.5
1.4
0.3
0.1
0.8
0.1
0.0
0.0
0.0
0.0
Argentina
85.4
24.0
16.5
1.1
0.3
0.8
7.3
2.0
2.8
0.3
2.1
Armenia
41.4
28.4
15.3
10.9
0.0
0.1
0.9
0.1
0.7
2.4
0.2
Australia
11.9
27.7
4.6
0.9
0.0
0.1
1.9
0.6
0.4
0.1
0.6
Austria
79.8
65.7
65.7
7.4
0.0
0.1
22.5
15.1
9.9
1.1
9.5
Azerbaijan
52.7
30.6
16.5
3.8
0.2
4.5
0.0
5.3
0.0
0.0
2.8
Bahamas
56.0
24.8
18.6
5.5
1.1
0.0
0.0
7.6
0.0
0.5
3.9
Bahrain
30.5
22.4
12.1
5.6
5.4
0.0
0.9
0.0
0.0
0.0
0.2
Bangladesh
49.6
14.2
8.8
7.7
0.5
0.1
0.1
0.2
0.0
0.0
0.1
Barbados
56.0
24.8
18.6
3.0
1.0
14.6
0.0
0.0
0.0
0.0
0.0
Belarus
57.7
41.2
41.2
2.5
0.0
8.0
3.7
11.4
9.2
2.2
4.1
Belgium
78.2
55.8
55.8
3.3
1.8
0.9
18.5
6.3
18.2
1.0
5.7
Belize
105.5
47.8
8.2
3.5
0.1
0.0
0.0
3.0
0.0
0.0
1.6
Benin
49.4
10.3
6.9
3.8
0.8
1.5
0.1
0.5
0.0
0.0
0.3
Bhutan Bolivia (Plurinational State of) Bosnia and Herzegovina
80.3
50.4
20.1
16.8
0.1
1.2
0.0
0.2
1.0
0.6
0.1
66.6
21.8
7.9
2.3
0.2
0.0
0.0
3.1
0.8
0.3
1.0
43.5
36.9
36.9
5.7
0.8
3.6
1.5
15.2
0.9
1.0
8.2
Brazil
105.8
71.5
25.0
6.6
2.6
0.9
7.9
2.5
1.0
0.9
2.6
Brunei Darussalam
161.6
56.1
47.1
0.9
0.1
5.7
0.0
26.4
0.0
0.0
13.9
Bulgaria
42.9
37.6
37.6
9.8
0.6
0.6
4.5
7.6
10.2
0.8
3.5
Burkina Faso
43.0
12.4
2.7
1.4
0.4
0.9
0.0
0.0
0.0
0.0
0.0
Burundi
82.6
34.5
7.5
5.5
1.1
0.3
0.0
0.4
0.0
0.0
0.2
Cambodia
31.4
28.0
8.1
7.7
0.2
0.0
0.1
0.0
0.0
0.1
0.0
Cameroon
116.1
90.9
16.4
8.6
2.1
1.1
0.0
2.3
0.0
0.9
1.2
Canada
44.0
23.9
21.8
0.1
0.0
0.2
9.5
5.0
2.8
0.8
3.4
Cape Verde
47.6
42.8
42.8
8.3
29.9
0.0
0.0
0.0
0.0
0.0
4.6
Central African Republic
108.6
49.3
13.8
4.2
2.3
4.4
0.3
1.4
0.2
0.1
0.8
Chad
45.8
5.3
2.0
1.5
0.5
0.0
0.0
0.0
0.0
0.0
0.0
Chile
69.2
41.6
26.2
2.8
0.3
0.1
12.9
4.0
1.2
1.0
3.9
China
24.0
16.3
5.1
2.2
0.1
0.2
1.1
0.2
0.4
0.6
0.3
Colombia
96.5
43.7
15.7
6.4
4.5
0.2
2.8
0.4
0.5
0.2
0.8
Congo
131.6
59.9
18.0
2.0
0.0
5.5
1.7
4.1
0.6
1.5
2.5
Costa Rica
78.3
30.7
5.2
1.6
0.0
0.6
0.2
1.6
0.2
0.3
0.7
Côte d'Ivoire
175.0
74.6
16.1
8.0
2.4
0.0
0.2
1.6
0.0
3.1
0.9
4
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Croatia
107.5
47.9
47.9
1.0
0.1
7.2
7.4
14.6
9.9
1.6
6.2
Cuba
67.4
26.0
26.0
6.8
1.6
6.7
0.6
3.6
5.3
0.1
1.3
Cyprus
13.3
11.5
10.2
1.4
4.3
0.0
2.8
0.6
0.0
0.4
0.8
Czech Republic
120.2
65.3
65.3
1.6
0.0
0.4
20.6
18.8
12.2
1.7
10.0
23.5
14.4
4.7
2.4
0.4
0.6
0.6
0.3
0.0
0.0
0.3
109.3
67.9
14.7
11.0
1.6
1.9
0.1
0.0
0.0
0.0
0.0
Denmark
58.3
44.8
44.8
10.3
0.1
0.8
16.9
5.0
6.1
0.4
5.1
Djibouti
28.3
9.4
1.6
0.9
0.7
0.0
0.0
0.0
0.0
0.0
0.0
Democratic People's Republic of Korea Democratic Republic of the Congo
Dominica
56.0
24.8
18.6
15.5
2.8
0.0
0.0
0.0
0.0
0.0
0.3
Dominican Republic
49.4
17.7
13.3
11.1
2.2
0.0
0.0
0.0
0.0
0.0
0.0
Ecuador
93.9
60.5
21.8
8.7
1.1
1.3
1.0
1.8
1.2
5.8
0.9
Egypt
84.0
35.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
El Salvador
75.7
42.0
7.2
4.6
0.1
0.0
0.7
1.1
0.0
0.0
0.7
Equatorial Guinea
107.0
48.7
10.5
0.6
0.2
0.7
3.8
0.7
1.4
2.0
1.1
Eritrea
49.3
15.0
2.5
1.8
0.7
0.0
0.0
0.0
0.0
0.0
0.0
Estonia
59.6
45.7
45.7
4.5
0.1
0.6
15.2
11.8
5.1
1.4
7.0
Ethiopia
14.9
6.2
1.5
1.1
0.2
0.1
0.0
0.0
0.0
0.0
0.0
Fiji
11.9
32.2
5.3
0.5
0.2
0.1
0.1
1.9
0.0
1.4
1.0
Finland
32.2
22.3
21.8
0.8
0.0
0.0
13.4
2.9
0.3
0.9
3.6
France
62.0
36.5
36.5
7.3
0.1
0.2
12.2
5.1
6.7
0.7
4.2
French Polynesia
116.1
32.2
5.3
5.1
0.0
0.0
0.0
0.0
0.0
0.0
0.3
Gabon
105.7
65.8
5.3
0.5
0.1
0.2
1.1
0.7
0.4
1.8
0.6
Gambia
56.4
10.9
2.4
0.8
0.4
1.0
0.0
0.1
0.0
0.0
0.1
Georgia
61.4
38.3
20.6
14.5
0.0
0.0
0.8
3.1
0.0
0.6
1.7
Germany
97.7
70.9
70.4
3.3
0.0
1.8
29.4
11.4
14.2
0.9
9.5
Ghana
66.2
17.4
3.8
2.5
0.6
0.0
0.0
0.2
0.0
0.4
0.1
Greece
16.9
10.6
10.5
2.3
0.0
0.6
1.2
0.4
5.4
0.2
0.4
Guatemala
62.1
47.9
8.1
7.6
0.1
0.0
0.0
0.2
0.0
0.1
0.1
Guinea
76.3
22.7
4.9
3.3
0.5
0.8
0.0
0.1
0.0
0.2
0.0
Guinea-Bissau
42.3
8.9
3.0
0.6
0.5
1.6
0.0
0.2
0.0
0.0
0.2
Guyana
94.3
42.8
15.4
4.2
0.7
0.8
1.5
2.7
0.3
3.4
1.7
Haiti
48.0
19.2
14.4
8.8
0.8
2.0
0.0
1.9
0.0
0.0
1.0
Honduras
54.5
31.4
5.4
4.1
0.1
0.0
0.2
0.6
0.0
0.0
0.4
Hungary
55.9
39.8
37.4
9.7
0.0
4.7
7.6
3.7
7.9
1.0
2.8
India
24.0
22.6
5.9
5.0
0.2
0.0
0.3
0.2
0.0
0.1
0.2
Indonesia
110.3
35.4
10.2
2.6
0.0
0.4
4.1
0.6
0.1
1.2
1.1
Iran (Islamic Republic of)
19.4
10.8
5.8
0.1
0.0
0.3
2.6
0.1
2.1
0.0
0.6
Iraq
30.5
22.4
12.1
3.8
8.3
0.0
0.0
0.0
0.0
0.0
0.0
Ireland
24.5
22.7
22.3
0.1
0.0
0.6
5.4
5.1
8.7
0.0
2.4
Israel
24.4
11.2
0.3
0.0
0.0
0.0
0.2
0.0
0.0
0.1
0.0
Italy
52.0
34.0
34.0
12.8
0.1
0.7
8.7
1.3
6.5
1.7
2.3
Jamaica
116.6
45.4
0.9
0.3
0.0
0.4
0.0
0.2
0.0
0.0
0.1
5
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Japan
22.9
18.9
6.1
0.0
0.0
0.0
4.1
0.5
0.2
0.3
1.0
Jordan
17.9
6.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Kazakhstan
31.9
24.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Kenya
117.8
53.4
4.8
4.0
0.0
0.1
0.4
0.1
0.0
0.1
0.1
Kuwait
30.5
22.4
12.1
6.3
5.8
0.0
0.0
0.0
0.0
0.0
0.0
Kyrgyzstan
43.7
10.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
60.4
17.4
5.0
4.1
0.1
0.2
0.1
0.2
0.0
0.1
0.1
61.3
42.5
42.5
0.6
0.0
4.4
8.6
15.4
4.6
2.4
6.5
Lebanon
10.6
8.3
2.4
1.2
1.0
0.0
0.0
0.0
0.0
0.2
0.0
Lao People's Democratic Republic Latvia
Liberia
115.9
46.6
10.1
6.9
1.4
1.2
0.0
0.4
0.0
0.0
0.2
Libyan Arab Jamahiriya
24.6
10.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Lithuania
57.4
49.1
49.1
5.2
0.0
0.7
9.2
14.6
12.2
1.0
6.2
Luxembourg
100.4
67.3
67.3
1.2
0.0
1.2
28.2
9.2
18.2
0.8
8.5
Madagascar
111.1
50.4
14.1
9.5
3.9
0.0
0.1
0.4
0.0
0.0
0.2
Malawi
38.0
32.2
5.3
3.0
1.6
0.5
0.0
0.1
0.0
0.1
0.0
Malaysia
134.7
61.1
17.6
0.5
0.0
0.5
2.4
2.1
2.3
8.7
1.2
Mali
18.7
5.9
1.8
1.1
0.2
0.5
0.0
0.0
0.0
0.0
0.0
Mauritania
25.0
5.9
4.2
2.6
1.6
0.0
0.0
0.0
0.0
0.0
0.0
Mauritius
56.3
25.1
15.5
2.4
0.6
2.3
5.2
2.7
0.2
0.0
2.1
Mexico
27.7
12.0
11.0
6.4
0.0
0.0
2.9
0.5
0.1
0.1
0.8
Mongolia
45.9
29.5
9.5
7.5
0.9
0.0
0.0
0.7
0.0
0.0
0.4
Morocco
35.4
8.1
5.8
0.4
0.6
0.0
3.4
0.3
0.0
0.2
0.8
Mozambique
34.6
10.6
1.5
1.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
Myanmar
46.1
12.7
3.6
2.0
0.0
0.3
0.2
0.4
0.1
0.2
0.3
Nepal
98.7
45.4
13.1
9.1
0.3
0.0
0.2
2.1
0.0
0.3
1.1
Netherlands
63.0
43.2
43.2
4.0
2.5
0.7
15.0
4.4
11.5
0.6
4.5
Netherlands Antilles
56.0
24.8
18.6
12.4
5.8
0.0
0.0
0.0
0.0
0.0
0.4
New Caledonia
63.2
18.9
3.1
0.8
0.2
0.5
0.0
0.8
0.0
0.0
0.7
New Zealand
125.5
97.7
13.7
0.0
0.0
2.9
4.2
2.1
1.1
1.5
1.8
Nicaragua
96.2
41.8
7.1
6.5
0.2
0.0
0.0
0.2
0.0
0.1
0.1
Niger
25.3
3.0
3.0
0.7
0.7
1.5
0.0
0.0
0.0
0.0
0.0
Nigeria
102.9
37.8
5.3
2.5
0.8
0.8
0.0
0.7
0.1
0.0
0.3
Norway
33.3
22.1
22.1
2.0
0.0
0.1
11.8
3.3
1.4
0.0
3.5
Oman
30.5
22.4
12.1
6.2
5.9
0.0
0.0
0.0
0.0
0.0
0.0
Pakistan
99.0
22.9
6.6
3.6
0.1
0.4
0.8
0.7
0.1
0.5
0.5
Panama
96.9
60.2
10.3
7.2
0.2
0.0
0.9
0.9
0.2
0.3
0.6
Papua New Guinea
71.2
28.0
4.6
1.3
0.0
0.2
1.3
0.3
0.4
0.8
0.4
Paraguay
93.9
57.8
20.8
6.5
1.6
3.6
0.4
3.8
0.0
2.8
2.0
Peru
108.0
35.4
12.7
4.4
1.8
0.5
0.6
3.1
0.0
0.6
1.7
Philippines
74.3
49.0
14.1
7.3
1.7
2.0
1.4
0.3
0.0
0.9
0.5
Poland
79.2
49.3
49.3
1.7
0.2
2.6
12.2
6.1
20.5
1.8
4.2
Portugal
22.3
12.2
10.1
0.2
0.0
0.1
6.5
0.5
1.2
0.1
1.5
6
© 2012 Macmillan Publishers Limited. All rights reserved.
Qatar
30.5
22.4
12.1
5.7
5.2
0.0
0.9
0.0
0.0
0.0
0.2
Republic of Korea
34.1
21.8
14.4
3.5
0.1
0.2
5.3
1.4
1.5
1.0
1.6
Republic of Moldova
64.8
27.7
27.5
17.1
0.1
2.2
0.9
4.6
0.1
0.0
2.5
Romania
81.4
47.7
47.7
4.4
0.2
2.2
6.1
16.4
10.5
1.5
6.5
Russian Federation
32.1
22.7
22.7
2.2
0.0
2.4
7.7
3.5
2.4
1.7
2.8
Rwanda
78.0
53.7
51.0
39.2
6.3
3.7
0.0
1.2
0.0
0.0
0.6
56.0
24.8
18.6
12.4
3.4
0.0
0.0
0.0
0.0
0.0
2.8
11.9
32.2
5.3
5.0
0.0
0.2
0.0
0.1
0.0
0.0
0.0
120.4
49.3
49.3
26.3
12.7
0.0
0.0
6.7
0.0
0.0
3.6
Saint Vincent and the Grenadines Samoa Sao Tome and Principe Saudi Arabia
5.0
2.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Senegal
32.6
10.9
8.2
4.2
0.5
3.3
0.0
0.1
0.0
0.0
0.1
Sierra Leone
68.0
11.8
3.0
1.8
0.7
0.4
0.0
0.0
0.0
0.0
0.0
Singapore
70.2
29.2
8.4
0.0
4.2
0.2
2.0
0.4
0.2
0.6
0.7
Slovakia
90.7
59.9
59.9
0.7
1.3
0.9
22.2
14.4
10.8
0.7
8.9
Slovenia
110.9
74.7
74.7
5.3
0.0
0.9
14.9
10.6
29.5
7.3
6.2
Solomon Islands
70.5
27.7
14.1
0.3
0.0
0.1
5.8
3.7
0.6
0.6
3.0
Somalia
50.1
7.4
1.2
1.0
0.2
0.1
0.0
0.0
0.0
0.0
0.0
South Africa
73.5
18.1
6.5
0.5
0.0
0.4
3.6
0.6
0.4
0.1
0.9
Spain
18.4
11.3
10.8
0.4
0.0
0.1
6.2
0.6
1.7
0.3
1.5
Sri Lanka
29.0
6.2
1.8
0.8
0.0
0.6
0.1
0.1
0.0
0.1
0.1
Sudan
16.5
4.1
3.0
1.3
0.4
1.1
0.0
0.0
0.0
0.0
0.0
Suriname
184.0
67.9
24.4
1.2
1.2
0.7
0.9
12.8
0.2
0.7
6.8
Sweden
36.1
26.8
26.8
0.8
0.0
0.1
15.9
4.7
0.5
0.1
4.7
Switzerland
94.4
77.6
77.6
8.5
0.2
0.4
32.5
10.7
14.3
1.0
10.0
Syrian Arab Republic
30.5
17.1
9.2
0.5
0.8
1.9
0.0
0.7
1.5
3.5
0.2
Tajikistan
4.9
2.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Thailand
38.9
12.1
3.5
0.9
0.3
0.4
0.8
0.2
0.5
0.1
0.2
Timor-Leste
70.2
29.2
8.4
8.3
0.0
0.0
0.1
0.0
0.0
0.0
0.0
Togo
100.7
55.8
12.0
8.5
2.4
0.8
0.0
0.1
0.0
0.0
0.1
Tonga
101.1
46.0
19.8
2.2
1.5
1.2
6.3
1.0
2.2
3.6
1.8
Trinidad and Tobago
73.6
31.0
26.9
2.7
0.9
0.1
4.1
11.5
0.0
1.4
6.2
Tunisia
7.0
5.9
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Turkey
57.4
30.4
21.6
1.9
0.0
0.2
2.1
5.7
9.2
0.5
2.0
Turkmenistan
2.1
0.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Uganda
30.5
13.0
0.4
0.3
0.0
0.1
0.0
0.0
0.0
0.0
0.0
Ukraine
63.2
49.1
49.1
15.6
0.6
2.9
4.0
8.5
12.0
1.8
3.6
United Arab Emirates
37.2
14.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
United Kingdom
40.6
29.7
29.7
0.3
0.1
0.4
16.7
2.8
5.3
0.0
4.2
51.8
10.9
1.8
0.8
0.3
0.6
0.1
0.0
0.0
0.0
0.0
53.2
34.9
32.1
3.5
0.4
0.5
12.9
9.7
1.6
1.7
1.8
Uruguay
93.9
16.2
1.3
0.0
0.0
0.0
0.6
0.2
0.1
0.2
0.2
Uzbekistan
4.4
1.8
1.0
0.4
0.0
0.1
0.3
0.1
0.1
0.0
0.1
United Republic of Tanzania United States of America
7
© 2012 Macmillan Publishers Limited. All rights reserved.
Vanuatu
11.9
32.2
5.3
4.3
0.1
0.0
0.0
0.6
0.0
0.0
0.3
93.9
60.5
21.8
6.9
4.0
0.0
2.6
2.8
3.7
0.1
1.6
60.0
18.2
5.8
2.3
0.0
0.4
0.8
1.3
0.2
0.1
0.7
Yemen
7.0
2.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Zambia
41.9
16.5
2.0
0.9
0.4
0.5
0.0
0.1
0.0
0.0
0.0
Zimbabwe
26.3
11.2
0.2
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Venezuela (Bolivarian Republic of) Viet Nam
1.2. Production, Trade and Consumption of Harvested Wood Products (HWPs) Upon forest clearance a fraction of above ground biomass is removed from the site as harvested wood products (HWPs), while the remaining fraction is left on-site to be burned. Above ground biomass removals can be converted into three timber products (industrial roundwood, fuelwood, or charcoal) that act as inputs to primary products (e.g. pulpwood, sawlogs, etc.), intermediate products (e.g. pulp), and end-products (e.g. paper, fiberboard, etc.) either domestically or abroad. While we assume that industrial roundwood can only be produced from commercial merchantable growing stock, fuelwood and charcoal can be produced from either non-merchantable wood, commercial merchantable growing stock, or non-commercial merchantable growing stock. We assume that the amount of fuelwood/charcoal produced from non-merchantable wood is proportional to the fraction of non-merchantable wood with respect to total above ground biomass. Similarly, the amount of fuelwood/charcoal produced from merchantable commercial and non-commercial wood is set proportional to the fraction of each with respect to total above ground biomass. In Brazil, for example, we calculate that 68% of fuelwood comes from merchantable wood (71.5 Mg C ha-1 merchantable wood / 105.8 Mg C ha-1 above ground biomass; see Table S1), of which 35% is commercial species (from 2010 FRA data). Non-commercial growing stock or non-merchantable wood that is not removed as fuelwood/charcoal will be burned almost immediately to clear the land for another use. All commercial growing stock is removed and enters HWP production processes. 8
© 2012 Macmillan Publishers Limited. All rights reserved.
The production process modeled in this study is based mostly on recent historical data from the FAO ForeStat database. 5 FAO provides country-specific data regarding production and bilateral trade of wood products. The production dataset contains information on quantity and value of production, export and import. Primary products consist of four types of harvested logs/timber: other industrial roundwood, pulpwood, sawlogs and fuelwood. Intermediate products consist of various types of pulp. Many types of final products are provided in the FAO ForeStat database. Broadly, these include wood panels, lumber, paper products, and fuelwood. For a detailed list of all products included within the database see Table S2. Bilateral trade data, on the other hand, is provided by FAO5 at a much coarser resolution. Trade of primary product is only given as a general industrial roundwood category. As a result, we track a general industrial roundwood category as a primary product. Fuelwood and charcoal are given as primary products, but also serve as the end-product. With respect to intermediate products, we include an aggregate pulp category. Finally, there are seven aggregate end-product categories included: other industrial roundwood, paper, sawnwood, fiberboard, plywood/veneer, fuelwood and charcoal. The number of production steps required to convert a primary product into an endproduct varies by end-product type. Additionally, export of primary, secondary and end-products can occur across the production process. Specifically, there are four different types of production routes modeled. Figures S1 - S4 illustrate each of these routes.
9
© 2012 Macmillan Publishers Limited. All rights reserved.
harvest
Export endproduct
Export primary product
Non-export end- product Non-export end- product Export endproduct
consumption
production
Export secondary product Non-export secondary product Non-export secondary product
Exp NonExp Exp NonExp Exp NonExp
Exp
Export secondary product
harvest
Export primary product
Commercial Merchantable Growing Stock (m3 primary product)
Export end-product
Commercial Merchantable Growing Stock (m3 primary product)
Non-export end-product consumption
production
Fig. S4: Paper Route
Fig. S3: Other Industrial Roundwood Route
harvest
Non-export primary product
Merchantable Growing Stock (m3 primary product)
Export end-product consumption
Non-export primary product
harvest
Fig. S2: Sawnwood, Fiberboard, and Plywood/Veneer Route
Non-export end-product
Above-ground Biomass (m3 primary product)
Fig. S1: Fuelwood and Charcoal Route
NonExp
production
consumption
Figure S1 represents the production route for fuelwood and charcoal. In the case of fuelwood, the primary product is the same as the end-product (i.e. fuelwood). Charcoal, given in terms of weight, is converted to volume roundwood using a factor of 6 m3 roundwood per Mg
10
© 2012 Macmillan Publishers Limited. All rights reserved.
charcoal. 5 Once the primary product is extracted it can either be exported for consumption or consumed domestically. Figure S2 represents the production route for sawnwood, fiberboard and plywood/veneer panels. First, industrial roundwood is harvested and either exported or not exported to be used in the manufacturing of end-products. Once the end-product is manufactured it can either be exported for consumption or consumed domestically. Figure S3 represents the production route for other industrial roundwood. Similar to fuelwood, the primary product is the same as the end-product (i.e. fuelwood). Figure S4 represents the production route for paper. First, industrial roundwood is harvested and either exported or not exported to be used in the manufacturing of secondary products (i.e. pulp). The secondary product can either be exported or not exported to produce paper. Once the paper is manufactured it can either be exported for consumption or consumed domestically. The routes above describe the fraction of commercial merchantable growing stock contained in each end-product and map the trade of this growing stock through consumption across countries. Beginning with the GSC,i value, the first step in modeling global production, trade and consumption is to determine the amount of industrial roundwood used domestically versus that which is exported. Taking the difference between production and quantity (m3) of industrial roundwood, fuelwood, and charcoal, provides the corresponding non-export quantities. Equation (2) shows this relationship. (2) where kNE,a,i is the quantity of primary product non-export; kP,a,i is the quantity of primary product produced; kE,a,i is the quantity of primary product exported; and a = primary products = industrial roundwood, fuelwood or charcoal. Once these values are determined, the fraction of
11
© 2012 Macmillan Publishers Limited. All rights reserved.
growing stock comprised of each primary product that is export, FE,a,i, versus non-export, FNE,a,i, can be calculated. (3) (4) Theoretically, the sum of all FE,a and FNE,a should equal one, and for about 91% of countries this is the case. Due to inconsistencies within the FAO 5 data, however, the sum of these fractions does not equal one for about 13 countries. This was corrected for by normalizing by the percent error. See accompanying spreadsheet for further details. We next multiplied the fractions above by GSHWP,i which indicates the fraction of growing stock removed that ends up as exported, GSE,a,i, or non-exported, GSNE,a,i, industrial roundwood, fuelwood or charcoal. (5) (6) After finding GSE,a,i and GSNE,a,i, we had to determine the fraction growing stock that is consumed and where according to Figures S1 - S3. 1.2.1. Other Industrial Roundwood, Fuelwood and Charcoal Production-Consumption Route The other industrial roundwood, fuelwood and charcoal production route is the simplest calculation because it has the fewest trade possibilities. Since fuelwood and charcoal are not grouped into the industrial roundwood bilateral trade category, they can be calculated more simply than other industrial roundwood. These values are equal to GSE,a,i and GSNE,a,i found above where a = fuelwood or charcoal. For the exported fraction, we use bilateral trade data on industrial roundwood to approximate trade of fuelwood and charcoal among countries. 12
© 2012 Macmillan Publishers Limited. All rights reserved.
(7) where FT,a,ij is the fraction of total export of a from i represented by trade between i and j. Thus, GSNE,a,i and GSE,a,ij tell us where the portion of growing stock used as fuelwood and charcoal are consumed. Other industrial roundwood, alternatively, begins with GSE,a,i and GSNE,a,i where a = industrial roundwood. As other industrial roundwood is one of five products manufactured from industrial roundwood, we had to determine the fraction of exported industrial roundwood that is consumed as other industrial roundwood (versus other secondary/end-products) by an importing country. For non-exports, this fraction is assumed to be directly proportional to the production fraction of that product (other industrial roundwood here) in the producing country. Thus, for other industrial roundwood Equation (8) was used to determine the amount of growing stock that is consumed domestically. (8) where FP,c,i is the fraction of production represented by end-product c relative to all other endproducts that also use industrial roundwood in producing country i. In the case of other industrial roundwood, c = a. For exports, this fraction is assumed to be directly proportional to the production fraction of that product (other industrial roundwood here) in the importing country. Thus, for other industrial roundwood Equation (9) was used to determine the amount of growing stock that is exported and where it is consumed as end-product c. (9) 13
© 2012 Macmillan Publishers Limited. All rights reserved.
where FP,c,j is the fraction of production represented by end-product c relative to all other endproducts that also use industrial roundwood in importing country j; and FT,c,ij is the fraction of total export of a from i that is used to produce c in j. 1.2.2. Sawnwood, Fiberboard and Plywood/Veneer Production-Consumption Route At this point, we note that all FAO 5 data for end-products is given in terms of volume or mass of the final product. Linking end-product quantities back to growing stock requires that end-products be converted into volume of industrial roundwood input per unit of end-product output. This conversion is done with manufacturing coefficients taken from Buongiorno et al.6 While Buongiorno et al.6 provide manufacturing coefficients for each country, they were estimated using FAO data and contain significant variation which is difficult to justify. So, for this study we decided to use a single set of manufacturing coefficients for all countries. We based the manufacturing coefficients on US values found by Buongiorno et al.6 The manufacturing coefficients utilized are listed in Table S2. Utilizing only a constant set of manufacturing coefficients across countries is a limitation which should be addressed if improved manufacturing data becomes available in the future. Table S2: End-products tracked by FAO 5 for production and Global Forest Products Model input-output manufacturing coefficients derived from Buongiorno et al.6 Product
Category
GFPM I/O Coefficients
Wood Charcoal
charcoal
6.00
Fibreboard, Compressed
fiberboard
1.59
Hardboard
fiberboard
1.59
Insulating Board
fiberboard
1.59
MDF
fiberboard
1.59
Particle Board
fiberboard
1.86
Other Indust Roundwd(C)
other ind. roundwood
1.00
Other Indust Roundwd(NC)
other ind. roundwood
1.00
Units m3 IRW / Mg product m3 IRW / m3 product m3 IRW / m3 product m3 IRW / m3 product m3 IRW / m3 product m3 IRW / m3 product m3 IRW / m3 product m3 IRW / m3 product
Notes
proxied from US fiberboard proxied from US fiberboard proxied from US fiberboard
14
© 2012 Macmillan Publishers Limited. All rights reserved.
Case Materials
paper
2.66
Coated Papers
paper
2.66
Folding Boxboard
paper
2.66
Household+Sanitary Paper
paper
2.66
Newsprint
paper
1.75
Other Paper+Paperboard
paper
2.66
Other Papers Packaging
paper
2.66
Paper+Paperboard NES
paper
2.66
Printing+Writing Paper
paper
2.66
Uncoated Mechanical
paper
2.66
Uncoated Woodfree
paper
2.66
Wrapping Papers
paper
2.66
Plywood
plywood/veneer panels
2.51
Veneer Sheets
plywood/veneer panels
2.51
Bleached Sulphate Pulp
pulp
3.50
Bleached Sulphite Pulp
pulp
3.50
Chemical Wood Pulp
pulp
3.50
Dissolving Wood Pulp
pulp
3.50
Mechanical Wood Pulp
pulp
2.15
Other Fibre Pulp
pulp
3.50
Recovered Paper
pulp
2.15
Semi-Chemical Wood Pulp
pulp
3.50
Recovered Fibre Pulp
pulp
2.15
Unbleached Sulphate Pulp
pulp
3.50
Unbleached Sulphite Pulp
pulp
3.50
Sawnwood (C)
sawnwood
1.52
Sawnwood (NC)
sawnwood
1.52
m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / m3 product m3 IRW / m3 product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / Mg product m3 IRW / ton product m3 IRW / Mg product m3 IRW / Mg product
representative of US printing and writing paper production representative of US printing and writing paper production representative of US printing and writing paper production representative of US printing and writing paper production representative of US production representative of US printing and writing paper production representative of US printing and writing paper production representative of US printing and writing paper production representative of US printing and writing paper production representative of US printing and writing paper production representative of US printing and writing paper production representative of US printing and writing paper production
proxied from US plywood proxied from US chempulp proxied from US chempulp
proxied from US chempulp
proxied from US chempulp proxied from US mechpulp proxied from US chempulp proxied from US mechpulp proxied from US chempulp proxied from US chempulp
Sawnwood, fiberboard and plywood/veneer can take one of four possible productionconsumption routes. These routes are described in Figure S2. Another way to understand these routes is by the location at which the harvest, production and consumption stages take place. If i represents the country of harvest and j and m represent importing countries then the four 15
© 2012 Macmillan Publishers Limited. All rights reserved.
production-consumption routes are: i-i-i, i-i-j, i-j-j, and i-j-m. The first route suggests that harvest, production and consumption take place in the country of harvest i. The second route suggests that harvest and production occur in i, but the final product is exported for consumption in j. The third route suggests that harvested industrial roundwood is exported to j where it is made into a final good and consumed. Finally, the fourth route suggests that harvested industrial roundwood is exported to j where it is made into a final good and exported to m for consumption. The first route, i-i-i, is modeled as follows. We begin with the growing stock non-export value GSNE,a,i where a = industrial roundwood. Then, similar to above we multiply this value by the fraction of production represented by end-product c (where c = sawnwood, fiberboard or plywood/veneer) relative to all other end-products that also use industrial roundwood in producing country i, or FP,c,i. (10) We multiply this growing stock value by the fraction of end-product which is consumed domestically, Fcn,i, to obtain the amount of growing stock corresponding to i-i-i, GSNE,cn,i. (11) The second route, i-i-j, shares the first production step with i-i-i. However, once the endproduct is produced it is exported. Starting with GSNE,c,i, we multiply this growing stock value by the fraction of end-product which is exported for consumption, Fce,ij, to obtain the amount of growing stock corresponding to i-i-j, GSNE,ce,ij. (12)
16
© 2012 Macmillan Publishers Limited. All rights reserved.
The third route, i-j-j, begins with the growing stock export value GSE,a,i where a = industrial roundwood. For exports, the fraction of production represented by end-product c relative to all other end-products that also use industrial roundwood in producing country i is assumed to be directly proportional to the production fraction of product c in the importing country. For instance, if 1,000 m3 of industrial roundwood is exported from Austria to Germany, and 50% of German industrial roundwood is used to produce sawnwood, then 50% of Austrian industrial roundwood export to Germany is assumed to be used for sawnwood production, or 500 m3. The remaining portion of industrial roundwood exported from Austria to Germany makes up the remainder of the fraction, or the other 500 m3. Thus, Equation (13) was used to determine the amount of industrial roundwood growing stock that is exported and where it is consumed as end-product c, GSE,c,ij. (13) where FP,c,j is the fraction of production represented by end-product c relative to all other endproducts that also use industrial roundwood in importing country j; and FT,c,ij is the fraction of total export of a from i that is used to produce c in j. Given GSE,c,ij we multiply it by the fraction of c produced in j that is consumed domestically, Fcn,i, to obtain the amount of growing stock corresponding to i-j-j, GSE,cn,ij. (14) The fourth route, i-j-m, shares the first production step with i-j-j. However, once the endproduct is produced it is exported to m. Starting with GSE,c,ij, we multiply this growing stock 17
© 2012 Macmillan Publishers Limited. All rights reserved.
value by the fraction of end-product which is exported for consumption, Fce,jm, to obtain the amount of growing stock corresponding to i-j-m, GSE,ce,im. At this point, we use matrix multiplication to determine the amount of industrial roundwood from i which ultimately is consumed in m. GSE,c,ij can be written as a matrix of i columns and j rows, or GSE,c,ij. Additionally, Fce,jm can be written as a matrix of j columns and m rows, or Fce,jm. By taking the cross-product of these two matrices, we obtain the matrix of growing stock corresponding to i-jm, GSE,ce,im. (15) 1.2.3. Paper Production-Consumption Route Paper has a unique production route because it includes pulp as an intermediary product. Consequently, paper has eight possible production routes: i-i-i-i, i-i-i-j, i-i-j-j, i-i-j-m, i-j-j-j, i-j-jm, i-j-m-m, and i-j-m-n. As one example, i-j-m-n suggests that industrial roundwood is harvested in country i and exported to j where pulp is produced. This pulp is then exported to country m where paper is produced and exported to country n for consumption. The other seven production routes follow a similar logic. The calculation of production and trade also follows a similar technique to the production route above. The primary difference is that matrix multiplication must be performed again in the case of i-j-m-n to determine the amount of industrial roundwood from i which ultimately is consumed in n as paper. 1.2.4. Mill Fuel and Fiber Production/Consumption During production, mills generate wood residues that can be combusted as fuel for heat/electricity production or sold to paper/panel producers as fiber. Aligned with Ince et al. 7, we assume that lumber, plywood/veneer, and pulp/paper manufacturers produce fuel residues,
18
© 2012 Macmillan Publishers Limited. All rights reserved.
whereas only lumber and plywood/veneer manufacturers produce fiber residues. Pulp/paper and fiberboard manufacturers, on the other hand, consume fiber to supplement industrial roundwood as a raw material. Since country-specific fuel and fiber production data by industry is unavailable, we generalize US data from Ince et al. 7 Specifically, we utilize a production-weighted US average shown in Table S3, or FFiber,c,i and FFuel,c,i. Using this value, we determine the fraction of production represented by mill fuel and fiber residues relative to all end-products that use industrial roundwood in producing country i, or FP,Fiber,c,i and FP,Fuel,c,i. Specifically, we multiply this value by the fraction of production represented by end-product c (where c = lumber, plywood/veneer, or pulp/paper for fuel residues; and c = lumber or plywood/veneer for fiber residues) relative to all other end-products that also use industrial roundwood in producing country i, or FP,c,i. Equations (16) and (17) show this calculation. (16) (17) We next estimate fiber residue consumption by pulp/paper and fiberboard producers for each country. Since a country may produce a large amount of fiber (e.g. via lumber production), yet have little to no capacity to utilize these fibers, we permit that fibers can also be used as fuel. As such, the fraction of fiber used to produce pulp/paper, Ffiber_in,pulp,i, and fiberboard, Ffiber_in,fb,i, versus fuelwood, Ffiber_in,fw,i, is made proportional to the relative quantities produced of each. Equations (18), (19) and (20) show these relationships. (18)
19
© 2012 Macmillan Publishers Limited. All rights reserved.
(19)
(20) where FGS,fw is the fraction of growing stock represented by fuelwood and charcoal, and all other variables are previously defined. Finally, we add Ffiber_in,pulp,i, and Ffiber_in,fb,i to FP,pulp,i and FP,fb,i to estimate the total amount of growing stock contained in pulp and fiberboard. Table S3: Volumetric Fraction of Industrial Roundwood Input as Fuel, Fiber, and End-Product fuel fiber product lumber
0.15
0.19
0.66
ply/ven
0.14
0.18
0.68
pulp/paper
0.18
0.00
0.82
Additionally, we adjust FP,Fuel,c,i by adding in fiber burned as fuelwood, or Ffiber_in,fw,i. Table S4 shows the results of these calculations. Table S4: Mill fuel and fiber production/consumption by country. Values are given as a fraction of total industrial roundwood input into end-product manufacturing. Mill Fuel Wood Pre-Adj.
Mill Fiber Residue Pre-Adj.
Mill Fuel Wood w/ Adjustment
Mill Fiber Residue Used for Pulp
Mill Fiber Residue Used for Fiberboard
Mill Fiber Residue Used for Fuelwood
Afghanistan
0.06
0.08
0.07
0.00
0.07
0.01
Albania
0.02
0.02
0.03
0.00
0.01
0.01
Algeria
0.06
0.01
0.08
0.00
0.00
0.01
Angola
0.02
0.00
0.02
0.00
0.00
0.00
Argentina
0.13
0.04
0.14
0.02
0.01
0.01
Armenia
0.01
0.01
0.02
0.00
0.00
0.01
Australia
0.15
0.05
0.17
0.03
0.01
0.02
Austria
0.14
0.08
0.17
0.03
0.02
0.03
Azerbaijan
0.10
0.12
0.22
0.00
0.00
0.12
Bahamas
0.15
0.19
0.34
0.00
0.00
0.19
Bahrain
0.18
0.00
0.18
0.00
0.00
0.00
Bangladesh
0.14
0.12
0.26
0.00
0.00
0.12
Barbados
0.00
0.00
0.00
0.00
0.00
0.00
20
© 2012 Macmillan Publishers Limited. All rights reserved.
Belarus
0.08
0.09
0.10
0.01
0.07
0.02
Belgium
0.10
0.04
0.11
0.01
0.02
0.01
Belize
0.15
0.19
0.34
0.00
0.00
0.19
Benin
0.05
0.06
0.10
0.00
0.00
0.06
Bhutan
0.02
0.02
0.03
0.00
0.00
0.02
0.14
0.17
0.19
0.00
0.12
0.06
0.13
0.15
0.28
0.01
0.04
0.15
Bolivia (Plurinational State of) Bosnia and Herzegovina Brazil
0.14
0.05
0.17
0.02
0.00
0.03
Brunei Darussalam
0.13
0.17
0.30
0.00
0.00
0.17
Bulgaria
0.11
0.09
0.15
0.01
0.04
0.04
Burkina Faso
0.00
0.00
0.00
0.00
0.00
0.00
Burundi
0.10
0.13
0.22
0.00
0.00
0.13
Cambodia
0.10
0.01
0.11
0.00
0.00
0.01
Cameroon
0.10
0.12
0.22
0.00
0.00
0.12
Canada
0.14
0.07
0.16
0.03
0.02
0.02
Cape Verde
0.00
0.00
0.00
0.00
0.00
0.00
0.05
0.06
0.11
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.00
Chile
0.15
0.05
0.17
0.03
0.00
0.02
China
0.10
0.02
0.11
0.00
0.00
0.01
Colombia
0.15
0.03
0.16
0.01
0.00
0.02
Congo
0.07
0.09
0.17
0.00
0.00
0.09
Costa Rica
0.11
0.13
0.20
0.01
0.03
0.09
Côte d'Ivoire
0.06
0.08
0.14
0.00
0.00
0.08
Croatia
0.10
0.10
0.14
0.01
0.05
0.03
Cuba
0.05
0.06
0.08
0.00
0.04
0.02
Cyprus
0.16
0.04
0.18
0.01
0.00
0.02
Czech Republic
0.13
0.09
0.16
0.03
0.03
0.03
0.11
0.06
0.16
0.01
0.00
0.05
0.00
0.00
0.00
0.00
0.00
0.00
Denmark
0.12
0.03
0.13
0.01
0.01
0.01
Djibouti
0.00
0.00
0.00
0.00
0.00
0.00
Central African Republic Chad
Democratic People's Republic of Korea Democratic Republic of the Congo
Dominica
0.00
0.00
0.00
0.00
0.00
0.00
Dominican Republic
0.16
0.14
0.29
0.00
0.00
0.14
Ecuador
0.05
0.04
0.08
0.00
0.01
0.03
Egypt
0.15
0.00
0.15
0.00
0.00
0.00
El Salvador Equatorial Guinea
0.16
0.13
0.28
0.02
0.00
0.12
0.02
0.03
0.05
0.00
0.00
0.03
Eritrea
0.00
0.00
1.00
0.00
0.00
1.00
21
© 2012 Macmillan Publishers Limited. All rights reserved.
Estonia
0.12
0.11
0.17
0.02
0.05
0.04
Ethiopia
0.00
0.00
0.01
0.00
0.00
0.00
Fiji
0.10
0.13
0.23
0.00
0.00
0.13
Finland
0.16
0.04
0.17
0.03
0.00
0.01
France
0.13
0.05
0.15
0.02
0.02
0.02
French Polynesia
0.00
0.00
0.00
0.00
0.00
0.00
Gabon
0.05
0.07
0.12
0.00
0.00
0.07
Gambia
0.03
0.04
0.06
0.00
0.00
0.04
Georgia
0.14
0.15
0.28
0.01
0.00
0.14
Germany
0.13
0.05
0.14
0.02
0.02
0.01
Ghana
0.07
0.08
0.14
0.00
0.01
0.07
Greece
0.04
0.01
0.04
0.00
0.01
0.00
Guatemala
0.12
0.14
0.26
0.00
0.00
0.14
Guinea
0.01
0.01
0.02
0.00
0.00
0.01
Guinea-Bissau
0.02
0.03
0.05
0.00
0.00
0.03
Guyana
0.07
0.09
0.17
0.00
0.00
0.09
Haiti
0.09
0.11
0.20
0.00
0.00
0.11
Honduras
0.15
0.15
0.30
0.01
0.00
0.14
Hungary
0.06
0.02
0.06
0.00
0.01
0.01
India
0.14
0.08
0.22
0.00
0.00
0.08
Indonesia
0.13
0.02
0.14
0.01
0.00
0.01
Iran (Islamic Republic of)
0.10
0.00
0.10
0.00
0.00
0.00
Iraq
0.11
0.03
0.14
0.00
0.00
0.03
Ireland
0.10
0.07
0.10
0.02
0.05
0.01
Israel
0.10
0.00
0.10
0.00
0.00
0.00
Italy
0.10
0.02
0.11
0.01
0.00
0.01
Jamaica
0.06
0.08
0.14
0.00
0.00
0.08
Japan
0.16
0.02
0.16
0.02
0.00
0.00
Jordan
0.16
0.00
0.16
0.00
0.00
0.00
Kazakhstan
0.15
0.11
0.21
0.04
0.01
0.07
Kenya
0.12
0.03
0.15
0.00
0.00
0.03
Kuwait
0.18
0.00
0.18
0.00
0.00
0.00
Kyrgyzstan
0.14
0.18
0.32
0.00
0.00
0.18
Lao People's Democratic Republic
0.08
0.10
0.17
0.00
0.00
0.10
Latvia
0.11
0.13
0.14
0.00
0.10
0.03
Lebanon
0.02
0.02
0.04
0.00
0.00
0.02
Liberia
0.05
0.06
0.12
0.00
0.00
0.06
Libyan Arab Jamahiriya
0.07
0.09
0.16
0.00
0.00
0.09
Lithuania
0.11
0.11
0.14
0.01
0.07
0.03
Luxembourg
0.04
0.00
0.04
0.00
0.00
0.00
Madagascar
0.15
0.19
0.34
0.00
0.00
0.19
22
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Malawi
0.02
0.03
0.05
0.00
0.00
0.03
Malaysia
0.04
0.04
0.06
0.00
0.02
0.01
Mali
0.01
0.01
0.02
0.00
0.00
0.01
Mauritania
0.11
0.14
0.26
0.00
0.00
0.14
Mauritius
0.13
0.06
0.17
0.02
0.00
0.04
Mexico
0.16
0.03
0.19
0.01
0.00
0.02
Mongolia
0.15
0.19
0.32
0.00
0.02
0.17
Morocco
0.17
0.02
0.17
0.01
0.00
0.00
Mozambique
0.01
0.01
0.02
0.00
0.00
0.01
Myanmar
0.09
0.10
0.19
0.00
0.00
0.10
Nepal
0.14
0.17
0.31
0.00
0.00
0.17
Netherlands
0.17
0.01
0.18
0.01
0.00
0.00
Netherlands Antilles
0.00
0.00
0.00
0.00
0.00
0.00
New Caledonia
0.11
0.14
0.25
0.00
0.00
0.14
New Zealand
0.09
0.05
0.11
0.01
0.01
0.02
Nicaragua
0.12
0.15
0.28
0.00
0.00
0.15
Niger
0.00
0.00
0.01
0.00
0.00
0.00
Nigeria
0.09
0.10
0.17
0.00
0.01
0.09
Norway
0.16
0.05
0.17
0.03
0.00
0.01
Oman
0.00
0.00
0.00
0.00
0.00
0.00
Pakistan
0.11
0.07
0.16
0.01
0.00
0.05
Panama
0.13
0.10
0.21
0.01
0.01
0.08
Papua New Guinea
0.04
0.05
0.10
0.00
0.00
0.05
Paraguay
0.08
0.09
0.16
0.00
0.00
0.08
Peru
0.13
0.14
0.26
0.01
0.00
0.13
Philippines
0.07
0.02
0.09
0.00
0.00
0.02
Poland
0.08
0.04
0.09
0.01
0.02
0.00
Portugal
0.15
0.01
0.15
0.01
0.00
0.00
Qatar Republic of Korea Republic of Moldova
0.00
0.00
0.00
0.00
0.00
0.00
0.13
0.04
0.15
0.02
0.01
0.02
0.12
0.13
0.25
0.00
0.00
0.13
Romania
0.11
0.11
0.15
0.02
0.06
0.04
Russian Federation
0.11
0.06
0.14
0.02
0.01
0.02
Rwanda Saint Vincent and the Grenadines
0.05
0.06
0.11
0.00
0.00
0.06
0.00
0.00
1.00
0.00
0.00
1.00
Samoa
0.05
0.06
0.12
0.00
0.00
0.06
Sao Tome and Principe
0.15
0.19
0.34
0.00
0.00
0.19
Saudi Arabia
0.18
0.00
0.18
0.00
0.00
0.00
Senegal
0.01
0.01
0.02
0.00
0.00
0.01
Sierra Leone
0.01
0.01
0.02
0.00
0.00
0.01
Singapore
0.07
0.00
0.08
0.00
0.00
0.00
23
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Slovakia
0.14
0.08
0.16
0.03
0.02
0.02
Slovenia
0.07
0.04
0.07
0.01
0.03
0.01
Solomon Islands
0.15
0.19
0.34
0.00
0.00
0.19
Somalia
0.03
0.04
0.07
0.00
0.00
0.04
South Africa
0.15
0.03
0.16
0.02
0.00
0.01
Spain
0.14
0.02
0.14
0.01
0.00
0.00
Sri Lanka
0.04
0.02
0.06
0.00
0.00
0.02
Sudan
0.01
0.01
0.01
0.00
0.00
0.01
Suriname
0.14
0.18
0.32
0.00
0.00
0.18
Sweden
0.17
0.05
0.18
0.04
0.00
0.01
Switzerland
0.14
0.04
0.15
0.02
0.01
0.01
Syrian Arab Republic
0.02
0.03
0.02
0.02
0.02
0.00
Tajikistan
0.00
0.00
0.00
0.00
0.00
0.00
Thailand
0.09
0.03
0.11
0.02
0.01
0.01
Timor-Leste
0.00
0.00
0.00
0.00
0.00
0.00
Togo
0.03
0.04
0.07
0.00
0.00
0.04
Tonga
0.15
0.19
0.34
0.00
0.00
0.19
Trinidad and Tobago
0.15
0.14
0.27
0.03
0.00
0.12
Tunisia
0.04
0.01
0.05
0.00
0.00
0.01
Turkey
0.09
0.09
0.10
0.07
0.06
0.01
Turkmenistan
0.00
0.00
0.00
0.00
0.00
0.00
Uganda
0.01
0.01
0.02
0.00
0.00
0.01
Ukraine United Arab Emirates
0.08
0.08
0.11
0.05
0.04
0.03
0.00
0.00
0.00
0.00
0.00
0.00
United Kingdom
0.14
0.02
0.14
0.02
0.01
0.00
0.02
0.00
0.02
0.00
0.00
0.00
0.14
0.08
0.14
0.07
0.01
0.00
Uruguay
0.13
0.05
0.15
0.02
0.00
0.03
Uzbekistan
0.13
0.03
0.14
0.01
0.00
0.02
Vanuatu Venezuela (Bolivarian Republic of)
0.15
0.19
0.34
0.00
0.00
0.19
0.11
0.07
0.15
0.03
0.02
0.04
Viet Nam
0.13
0.11
0.20
0.03
0.01
0.08
Yemen
0.00
0.00
0.00
0.00
0.00
0.00
Zambia
0.03
0.03
0.05
0.01
0.01
0.02
Zimbabwe
0.13
0.11
0.23
0.02
0.01
0.10
United Republic of Tanzania United States of America
24
© 2012 Macmillan Publishers Limited. All rights reserved.
1.3. Estimating Carbon Disposition at t = 0 As we describe all primary, secondary and end-products in terms of m3 industrial roundwood input, production-consumption volumes are converted to Mg carbon (C) using carbon factors weighted by fraction temperate versus tropical forest area as shown in Table S5. Finally, we can sum all carbon that originates from country i which is consumed in country j = k = m in the form of end-product c. These values constitute the HWP stock, or HWP0,c,ij, given in terms of Mg C ha-1, and are shown for each end-product in Table S1. Table S5: Carbon factors weighted by fraction temperate versus tropical forest area
Country
Fraction Temperate
Fraction Tropical
Carbon factor (Mg C per m3 wood)
Afghanistan
1.00
0.00
0.225
Albania
1.00
0.00
0.225
Algeria
1.00
0.00
0.225
Angola
0.00
1.00
0.295
Argentina
0.79
0.21
0.240
Armenia
1.00
0.00
0.225
Australia
0.59
0.41
0.254
Austria
1.00
0.00
0.225
Azerbaijan
1.00
0.00
0.225
Bahamas
0.00
1.00
0.295
Bahrain
0.00
1.00
0.295
Bangladesh
0.00
1.00
0.295
Barbados
0.00
1.00
0.295
Belarus
1.00
0.00
0.225
Belgium
1.00
0.00
0.225
Belize
0.00
1.00
0.295
Benin
0.00
1.00
0.295
Bhutan
0.62
0.38
0.252
Bolivia (Plurinational State of)
0.00
1.00
0.295
Bosnia and Herzegovina
1.00
0.00
0.225
Brazil
0.01
0.99
0.294
Brunei Darussalam
0.00
1.00
0.295
Bulgaria
1.00
0.00
0.225
Burkina Faso
0.00
1.00
0.295
25
© 2012 Macmillan Publishers Limited. All rights reserved.
Burundi
0.00
1.00
0.295
Cambodia
0.00
1.00
0.295
Cameroon
0.00
1.00
0.295
Canada
1.00
0.00
0.225
Cape Verde
0.00
1.00
0.295
Central African Republic
0.00
1.00
0.295
Chad
0.00
1.00
0.295
Chile
1.00
0.00
0.225
China
0.93
0.07
0.230
Colombia
0.00
1.00
0.295
Congo
0.00
1.00
0.295
Costa Rica
0.00
1.00
0.295
Côte d'Ivoire
0.00
1.00
0.295
Croatia
1.00
0.00
0.225
Cuba
0.09
0.91
0.289
Cyprus
1.00
0.00
0.225
Czech Republic
1.00
0.00
0.225
Democratic People's Republic of Korea
1.00
0.00
0.225
Democratic Republic of the Congo
0.00
1.00
0.295
Denmark
1.00
0.00
0.225
Djibouti
0.00
1.00
0.295
Dominica
0.00
1.00
0.295
Dominican Republic
0.13
0.87
0.286
Ecuador
0.00
1.00
0.295
Egypt
0.00
1.00
0.295
El Salvador
0.16
0.84
0.283
Equatorial Guinea
0.00
1.00
0.295
Eritrea
0.00
1.00
0.295
Estonia
1.00
0.00
0.225
Ethiopia
0.00
1.00
0.295
Fiji
0.00
1.00
0.295
Finland
1.00
0.00
0.225
France
1.00
0.00
0.225
French Polynesia
0.00
1.00
0.295
Gabon
0.00
1.00
0.295
Gambia
0.00
1.00
0.295
Georgia
1.00
0.00
0.225
Germany
1.00
0.00
0.225
Ghana
0.00
1.00
0.295
Greece
1.00
0.00
0.225
Guatemala
0.02
0.98
0.294
Guinea
0.00
1.00
0.295
26
© 2012 Macmillan Publishers Limited. All rights reserved.
Guinea-Bissau
0.00
1.00
0.295
Guyana
0.00
1.00
0.295
Haiti
0.00
1.00
0.295
Honduras
0.51
0.49
0.260
Hungary
1.00
0.00
0.225
India
0.18
0.82
0.283
Indonesia
0.00
1.00
0.295
Iran (Islamic Republic of)
1.00
0.00
0.225
Iraq
0.00
1.00
0.295
Ireland
1.00
0.00
0.225
Israel
0.00
1.00
0.295
Italy
1.00
0.00
0.225
Jamaica
0.00
1.00
0.295
Japan
1.00
0.00
0.225
Jordan
1.00
0.00
0.225
Kazakhstan
1.00
0.00
0.225
Kenya
0.00
1.00
0.295
Kuwait
0.00
1.00
0.295
Kyrgyzstan
1.00
0.00
0.225
Lao People's Democratic Republic
0.00
1.00
0.295
Latvia
1.00
0.00
0.225
Lebanon
1.00
0.00
0.225
Liberia
0.00
1.00
0.295
Libyan Arab Jamahiriya
0.00
1.00
0.295
Lithuania
1.00
0.00
0.225
Luxembourg
1.00
0.00
0.225
Madagascar
0.00
1.00
0.295
Malawi
0.00
1.00
0.295
Malaysia
0.00
1.00
0.295
Mali
0.00
1.00
0.295
Mauritania
0.00
1.00
0.295
Mauritius
0.00
1.00
0.295
Mexico
0.33
0.67
0.272
Mongolia
1.00
0.00
0.225
Morocco
1.00
0.00
0.225
Mozambique
0.00
1.00
0.295
Myanmar
0.17
0.83
0.283
Nepal
0.57
0.43
0.255
Netherlands
1.00
0.00
0.225
Netherlands Antilles
0.00
1.00
0.295
New Caledonia
0.00
1.00
0.295
New Zealand
1.00
0.00
0.225
27
© 2012 Macmillan Publishers Limited. All rights reserved.
Nicaragua
0.18
0.82
0.282
Niger
0.00
1.00
0.295
Nigeria
0.00
1.00
0.295
Norway
1.00
0.00
0.225
Oman
0.00
1.00
0.295
Pakistan
0.78
0.22
0.241
Panama
0.00
1.00
0.295
Papua New Guinea
0.00
1.00
0.295
Paraguay
0.18
0.82
0.282
Peru
0.00
1.00
0.295
Philippines
0.02
0.98
0.293
Poland
1.00
0.00
0.225
Portugal
1.00
0.00
0.225
Qatar
0.00
1.00
0.295
Republic of Korea
1.00
0.00
0.225
Republic of Moldova
1.00
0.00
0.225
Romania
1.00
0.00
0.225
Russian Federation
1.00
0.00
0.225
Rwanda
0.00
1.00
0.295
Saint Vincent and the Grenadines
0.00
1.00
0.295
Samoa
0.00
1.00
0.295
Sao Tome and Principe
0.00
1.00
0.295
Saudi Arabia
0.00
1.00
0.295
Senegal
0.00
1.00
0.295
Sierra Leone
0.00
1.00
0.295
Singapore
0.00
1.00
0.295
Slovakia
1.00
0.00
0.225
Slovenia
1.00
0.00
0.225
Solomon Islands
0.00
1.00
0.295
Somalia
0.00
1.00
0.295
South Africa
0.67
0.33
0.248
Spain
1.00
0.00
0.225
Sri Lanka
0.00
1.00
0.295
Sudan
0.00
1.00
0.295
Suriname
0.00
1.00
0.295
Sweden
1.00
0.00
0.225
Switzerland
1.00
0.00
0.225
Syrian Arab Republic
1.00
0.00
0.225
Tajikistan
1.00
0.00
0.225
Thailand
0.01
0.99
0.294
Timor-Leste
0.00
1.00
0.295
Togo
0.00
1.00
0.295
28
© 2012 Macmillan Publishers Limited. All rights reserved.
Tonga
0.00
1.00
0.295
Trinidad and Tobago
0.00
1.00
0.295
Tunisia
1.00
0.00
0.225
Turkey
1.00
0.00
0.225
Turkmenistan
1.00
0.00
0.225
Uganda
0.00
1.00
0.295
Ukraine
1.00
0.00
0.225
United Arab Emirates
0.00
1.00
0.295
United Kingdom
1.00
0.00
0.225
United Republic of Tanzania
0.00
1.00
0.295
United States of America
1.00
0.00
0.225
Uruguay
1.00
0.00
0.225
Uzbekistan
1.00
0.00
0.225
Vanuatu
0.00
1.00
0.295
Venezuela (Bolivarian Republic of)
0.00
1.00
0.295
Viet Nam
0.08
0.92
0.289
Yemen
0.00
1.00
0.295
Zambia
0.00
1.00
0.295
Zimbabwe
0.00
1.00
0.295
2. Estimating Carbon Disposition and Use Over Time After estimating the carbon disposition associated with the clearance of one hectare of land at t = 0, we model the effect of use, end-of-life, and decomposition on carbon storage/emissions over time. 2.1. HWP Stock To characterize the rate at which carbon exits the HWP stock, we utilize a gamma decay function approach described by Marland et al. 8 They argue that a gamma function more accurately characterizes the use and disposal of longer-lived wood products. In this study, we use a separate gamma function for all seven end product groups. Figure S5 shows the rates at which carbon exits the HWP stock for each end product.
29
© 2012 Macmillan Publishers Limited. All rights reserved.
fraction of growing stock remaining in use
Figure S5: Gamma function describing life span of HWPs
1 0.9 0.8 0.7
OIRW
0.6
Paper
0.5
Lumber
0.4
Fiberboard
0.3
Ply/Ven
0.2
Fuelwood
0.1
Charcoal
0 0
50
100
150
200
years
A gamma function requires two parameters: shape and scale. In this study, we identify these parameters using an estimate of the year of maximum product removal (or mode) and the time at which 95% of a product has been removed. Knowing these two parameters it is possible to solve for the appropriate shape and scale parameters. The desirable mode and mean, along with associated shape and scale parameters are shown in the Table S6 below. Based on an exponential decay function, IPCC 3 recommends that default half-lives of 2 years and 30 years be used for paper and solidwood products, respectively. For this study, we assume that the exponential decay half-life value is analogous to the year of maximum decay for our gamma function. Beyond the IPCC 3 values, we further differentiate among the lifespan of solidwood products based on values contained within Pingoud et al. 9
30
© 2012 Macmillan Publishers Limited. All rights reserved.
Table S6: Gamma function parameters fuelwood
other
paper
fiberboard
sawnwood
plywood / veneer panels
--
20
2
20
35
30
--
50
5
40
150
75
--
4.124
3.196
6.557
2.151
4.161
scale
--
6.242
0.683
3.509
29.982
9.334
Source
--
Pingoud et al. 9
IPCC 3
Pingoud et al. 9
Pingoud et al. 9
Pingoud et al. 9
year of maximum decay 95% decay period shape
Due to a lack of country-specific data, we assume that all countries have the same use patterns—generally based on US and European data. To determine the quantity of growing stock remaining in the HWP pool at any time, or HWPc,ij (t), the fraction of growing stock remaining in use for product c, or γc,j(t), shown in Figure S4, is next multiplied by the total amount of end-product consumed in country j. The latter is given as the sum of initial HWP stock, or HWP0,c,j, in end-product c for each j. Thus, HWPc,ij (t) can be written as: (21) 2.2. SWDS Stock As wood products exit the HWP stock at the end-of-life, three general options are available for waste treatment: incineration, landfilling or recycling. Recycling primarily occurs for paper. No bilateral trade data exists, however, for recycled pulp and paper from FAO5. So, we account for recycling within the gamma function described above. For paper, values of two and five years are used for the year of maximum and 95% decay parameters (see Table S6). Such values imply that virgin paper which is recycled typically remains in the HWP pool for one year 31
© 2012 Macmillan Publishers Limited. All rights reserved.
and only 5% remains after five years. These parameters can be adjusted if country-specific data becomes available. Similar to Miner 10, the percentage of carbon exiting the HWP pool which is incinerated versus landfilled is determined using IPCC 11 values on waste generation and management by country. We assume that any HWP which is not incinerated enters the SWDS pool. Therefore, beginning at t = 1 the amount of carbon from end-product c entering the SWDS pool in country j is given by:
(22)
where FSWDS,j is the fraction of HWP that enters the SWDS pool in country j. Of the carbon which enters the SWDS pool, it can enter anaerobic or aerobic conditions. Under anaerobic conditions a fraction of carbon is stored long-term (assumed to be indefinite in this study), while the rest is stored temporarily—decomposing to methane and carbon dioxide over time. Under aerobic conditions, on the other hand, carbon entirely decomposes over time; mainly to carbon dioxide. As a result, SWDSc,j can be partitioned into three sub-pools each with different decomposition rates. The proportion of carbon under anaerobic versus aerobic conditions depends on how highly managed the landfill is. In an unmanaged landfill a larger fraction of waste decomposes aerobically in the top layer, whereas a highly managed landfill can lead to completely anaerobic conditions. IPCC 12 accounts for the different degrees of landfill management and related decomposition conditions via the methane correction factor (MCF). Table S7 shows the MCF values provided by IPCC 12.
32
© 2012 Macmillan Publishers Limited. All rights reserved.
Table S7: SWDS Classification and Methane Correction Factors (MCF)
Type of Site Managed – anaerobic Managed – semi-aerobic Unmanaged – deep (>5 m waste) and/or high water table Unmanaged – shallow ( 1) Default
Range low
high
0.06
0.05
0.07
0.03
0.02
0.04
Dry (MAP < 1000 mm) Default
Range low
high
0.045
0.04
0.06
0.025
0.02
0.04
Moist and Wet (MAP >= 1000 mm) Default
Range low
high
0.07
0.06
0.085
0.035
0.03
0.05
MAT = mean annual temperature; MAP = mean annual precipitation; PET = potential for evapotranspiration
34
© 2012 Macmillan Publishers Limited. All rights reserved.
Rate constant values for aerobic decomposition are not given by IPCC 12. So, for this study we utilize values from Skog14 representative of the US. Future efforts should go toward including country-specific rate constants for aerobic decomposition. The values used in this study are given in Table S10. Table S10: Aerobic Decomposition Rate Constants for Paper and Wood Waste 12 Type of Waste Paper Wood waste
First order decay rate constant (k) 0.084 0.042
Similar to IPCC 12, we assume that both anaerobic and aerobic decomposition follow a first-order decay reaction. The quantity of carbon accumulated in the SWDS anaerobic, temporary storage pool each year is given by: (26) Similarly, the quantity of carbon accumulated in the SWDS aerobic, temporary storage pool each year is given by: (27) The total amount of carbon remaining at any time, t, following land clearing is the sum of wood left in the HWP and SWDS stocks. At this point, both HWP and SWDS stocks are given in terms of the consuming country, j. To put the stocks back in terms of the country where land clearance occurs we use matrix multiplication again. For example, suppose that SWDSc,j,A,TEMP_an is a matrix with T years for rows and j countries for columns. Also, suppose that Fc,ij is a matrix that describes the fraction of industrial roundwood originating from country i within product c consumed in country j. Then, the amount of carbon in the SWDS aerobic, temporary pool at t that originated as industrial roundwood from country i is given by: 35
© 2012 Macmillan Publishers Limited. All rights reserved.
(28) The amount of carbon in the SWDS anaerobic, temporary and long-term pools can be calculated similarly. (29) (30) The amount of carbon in the HWP pools as product c at t that originated as industrial roundwood from country i can also be calculated similarly. (31) Supplementary Results 3. Carbon Disposition of HWP and SWDS Stocks Following Forest Clearance The quantity of carbon in each type of end-product per hectare of forest cleared is shown in Table S1. 3.1. Carbon Disposition of HWP, SWDS, and Atmospheric Stocks over Time The quantity of carbon in the HWP, SWDS, and atmospheric stocks for select years following forest clearance is shown in Table S11. Table S11: Mg C ha-1 in HWP, SWDS, and atmospheric pools at t years following forest clearance 0 yrs Country of Forest Clearance
15 yrs
30 yrs
50 yrs
100 yrs
Initial HWP SWDS Atm HWP SWDS Atm HWP SWDS Atm HWP SWDS Atm HWP SWDS Atm AGB
Afghanistan
23.5
1.9
0.0
0.0
1.4
0.2
21.9
0.7
0.7
22.1
0.3
0.8
22.4
0.1
0.5
22.9
Albania
47.7
21.8
0.0
0.0
6.7
1.3
39.8
2.8
3.8
41.1
0.7
3.8
43.2
0.1
2.3
45.3
Algeria
40.2
17.1
0.0
0.0
0.4
0.1
39.7
0.2
0.2
39.8
0.1
0.3
39.9
0.0
0.2
40.0
36
© 2012 Macmillan Publishers Limited. All rights reserved.
Angola
64.3
1.4
0.0
0.0
0.7
0.2
63.4
0.3
0.5
63.6
0.0
0.5
63.8
0.0
0.3
64.1
Argentina
85.4
16.5
0.0
0.0
5.0
4.8
75.6
2.5
5.1
77.8
1.2
4.5
79.6
0.4
3.6
81.4
Armenia
41.4
15.3
0.0
0.0
3.0
0.8
37.7
1.8
1.5
38.2
0.6
1.8
39.0
0.0
1.2
40.2
Australia
11.9
4.6
0.0
0.0
1.0
1.4
9.5
0.6
1.5
9.8
0.4
1.5
10.1
0.1
1.4
10.4
Austria
79.8
65.7
0.0
0.0
23.3
16.8
39.6
14.4
19.8
45.5
8.7
20.7
50.4
2.7
20.6
56.4
Azerbaijan
52.7
16.5
0.0
0.0
8.5
1.1
43.1
5.5
3.2
44.0
3.1
3.8
45.8
1.0
3.1
48.6
Bahamas
56.0
18.6
0.0
0.0
7.5
0.5
48.0
6.2
1.4
48.4
4.3
2.3
49.5
1.4
2.5
52.1
Bahrain
30.5
12.1
0.0
0.0
0.0
0.5
29.9
0.0
0.4
30.1
0.0
0.3
30.2
0.0
0.3
30.2
Bangladesh
49.6
8.8
0.0
0.0
0.3
0.1
49.3
0.2
0.1
49.3
0.1
0.1
49.3
0.0
0.1
49.4
Barbados
56.0
18.6
0.0
0.0
11.6
2.7
41.7
4.6
7.8
43.6
0.7
8.4
46.9
0.0
5.6
50.4
Belarus
57.7
41.2
0.0
0.0
26.6
5.7
25.5
14.6
13.2
29.9
7.3
14.1
36.3
2.1
11.1
44.6
Belgium
78.2
55.8
0.0
0.0
22.3
14.7
41.2
9.5
21.1
47.7
3.9
21.2
53.1
1.1
18.7
58.4
Belize
105.5
8.2
0.0
0.0
2.8
0.2
102.5
2.3
0.5
102.7
1.7
0.8
103.0
0.5
1.0
104.0
Benin
49.4
6.9
0.0
0.0
1.6
0.3
47.4
0.8
0.9
47.7
0.3
0.9
48.1
0.1
0.6
48.7
Bhutan
80.3
20.1
0.0
0.0
2.6
0.5
77.3
1.1
1.5
77.7
0.3
1.6
78.4
0.0
0.9
79.3
Bolivia (Plurinational State of)
66.6
7.9
0.0
0.0
3.9
0.4
62.4
2.8
1.1
62.7
1.8
1.5
63.4
0.6
1.4
64.7
Bosnia and Herzegovina
43.5
36.9
0.0
0.0
18.7
2.6
22.2
13.8
5.8
23.9
8.8
7.9
26.8
2.8
8.7
32.1
Brazil
105.8
25.0
0.0
0.0
4.7
5.0
96.1
3.0
4.9
97.9
1.7
4.7
99.4
0.5
4.2
101.1
Brunei Darussalam
161.6
47.1
0.0
0.0
29.1
2.5
130.0 22.3
7.7
131.7 14.8
11.9
134.9
4.8
15.2
141.7
Bulgaria
42.9
37.6
0.0
0.0
16.6
5.1
21.2
8.6
10.4
23.9
4.5
10.9
27.5
1.4
9.2
32.4
Burkina Faso
43.0
2.7
0.0
0.0
0.7
0.2
42.1
0.3
0.5
42.3
0.0
0.5
42.5
0.0
0.3
42.8
Burundi
82.6
7.5
0.0
0.0
0.6
0.1
81.9
0.4
0.2
81.9
0.2
0.3
82.1
0.1
0.2
82.3
Cambodia
31.4
8.1
0.0
0.0
0.1
0.1
31.2
0.0
0.1
31.3
0.0
0.1
31.3
0.0
0.0
31.3
Cameroon
116.1
16.4
0.0
0.0
3.9
0.4
111.9
2.7
1.2
112.2
1.6
1.7
112.9
0.4
1.6
114.1
Canada
44.0
21.8
0.0
0.0
7.8
6.8
29.4
5.0
7.6
31.5
3.0
7.9
33.1
0.9
8.0
35.1
Cape Verde
47.6
42.8
0.0
0.0
0.0
0.0
47.6
0.0
0.0
47.6
0.0
0.0
47.6
0.0
0.0
47.6
Central African Republic
108.6
13.8
0.0
0.0
5.1
1.1
102.4
2.6
2.8
103.2
1.0
2.9
104.6
0.3
1.9
106.4
Chad
45.8
2.0
0.0
0.0
0.0
0.0
45.8
0.0
0.0
45.8
0.0
0.0
45.8
0.0
0.0
45.8
Chile
69.2
26.2
0.0
0.0
5.7
8.3
55.3
4.0
7.4
57.9
2.4
7.2
59.6
0.7
7.0
61.5
China
24.0
5.1
0.0
0.0
1.2
0.7
22.1
0.7
0.9
22.5
0.3
0.9
22.9
0.0
0.7
23.3
Colombia
96.5
15.7
0.0
0.0
1.0
1.7
93.8
0.6
1.4
94.5
0.3
1.3
95.0
0.1
1.1
95.4
Congo
131.6
17.8
0.0
0.0
9.9
2.4
119.3
5.9
4.9
120.9
2.8
5.5
123.3
0.8
4.3
126.6
Costa Rica
78.3
5.2
0.0
0.0
2.3
0.4
75.6
1.6
0.8
75.9
1.0
1.0
76.3
0.3
0.9
77.2
Côte d'Ivoire
175.0
16.1
0.0
0.0
4.4
0.4
170.2
3.2
1.3
170.5
1.6
2.0
171.3
0.3
1.7
173.0
Croatia
107.5
47.9
0.0
0.0
28.8
8.8
69.8
16.6
16.6
74.2
8.8
18.3
80.3
2.6
16.7
88.1
Cuba
67.4
26.0
0.0
0.0
13.1
2.7
51.7
6.0
7.5
53.9
2.4
7.2
57.8
0.7
4.6
62.2
Cyprus
13.3
10.2
0.0
0.0
0.9
2.1
10.3
0.7
1.9
10.7
0.4
1.9
11.0
0.1
1.9
11.3
Czech Republic
120.2
65.3
0.0
0.0
29.2
16.0
75.0
18.2
20.5
81.6
10.8
21.4
88.0
3.4
20.7
96.1
Democratic People's Republic of Korea
23.5
4.7
0.0
0.0
0.9
0.3
22.3
0.5
0.5
22.5
0.2
0.5
22.8
0.1
0.3
23.1
37
© 2012 Macmillan Publishers Limited. All rights reserved.
Democratic Republic of the 109.3 Congo
14.7
0.0
0.0
1.5
0.4
107.4
0.6
1.0
107.7
0.1
1.0
108.2
0.0
0.6
108.8
Denmark
58.3
44.8
0.0
0.0
10.7
11.2
36.4
5.6
11.8
40.8
2.9
11.7
43.6
0.9
11.2
46.2
Djibouti
28.3
1.6
0.0
0.0
0.0
0.0
28.3
0.0
0.0
28.3
0.0
0.0
28.3
0.0
0.0
28.3
Dominica
56.0
18.6
0.0
0.0
0.0
0.0
56.0
0.0
0.0
56.0
0.0
0.0
56.0
0.0
0.0
56.0
Dominican Republic
49.4
13.3
0.0
0.0
0.0
0.0
49.4
0.0
0.0
49.4
0.0
0.0
49.4
0.0
0.0
49.4
Ecuador
93.9
21.8
0.0
0.0
9.0
1.4
83.4
5.7
3.7
84.5
2.4
4.8
86.7
0.4
3.4
90.2
Egypt
84.0
0.0
0.0
0.0
0.0
0.0
84.0
0.0
0.0
84.0
0.0
0.0
84.0
0.0
0.0
84.0
El Salvador
75.7
7.2
0.0
0.0
1.1
0.4
74.2
0.9
0.4
74.4
0.6
0.5
74.6
0.2
0.5
74.9
Equatorial Guinea
107.0
10.5
0.0
0.0
4.2
2.6
100.2
2.3
3.2
101.5
0.9
3.3
102.8
0.1
2.5
104.3
Eritrea
49.3
2.5
0.0
0.0
0.0
0.0
49.3
0.0
0.0
49.3
0.0
0.0
49.3
0.0
0.0
49.3
Estonia
59.6
45.7
0.0
0.0
16.9
10.6
32.1
11.2
12.6
35.7
6.9
13.5
39.3
2.1
13.4
44.1
Ethiopia
14.9
1.5
0.0
0.0
0.1
0.0
14.8
0.1
0.1
14.8
0.0
0.1
14.8
0.0
0.0
14.9
Fiji
11.9
5.3
0.0
0.0
3.2
0.2
8.5
2.4
0.8
8.8
1.4
1.2
9.3
0.4
1.1
10.5
Finland
32.2
21.8
0.0
0.0
3.7
8.6
19.9
2.8
7.3
22.1
1.8
7.1
23.4
0.5
7.1
24.6
France
62.0
36.5
0.0
0.0
11.0
9.0
42.0
5.8
10.8
45.4
3.0
10.9
48.1
0.9
10.4
50.7
French Polynesia
116.1
5.3
0.0
0.0
0.0
0.0
116.1
0.0
0.0
116.1
0.0
0.0
116.1
0.0
0.0
116.1
Gabon
105.7
5.3
0.0
0.0
2.8
0.8
102.0
1.8
1.3
102.5
0.8
1.7
103.2
0.1
1.5
104.0
Gambia
56.4
2.4
0.0
0.0
0.9
0.2
55.3
0.4
0.5
55.4
0.1
0.6
55.7
0.0
0.3
56.0
Georgia
61.4
20.6
0.0
0.0
3.4
0.6
57.4
2.7
0.9
57.7
1.8
1.3
58.3
0.6
1.5
59.4
Germany
97.7
70.4
0.0
0.0
24.4
21.1
52.3
12.8
24.8
60.2
6.7
24.8
66.2
2.1
23.4
72.3
Ghana
66.2
3.8
0.0
0.0
0.5
0.0
65.6
0.4
0.1
65.6
0.2
0.2
65.7
0.0
0.2
65.9
Greece
16.9
10.5
0.0
0.0
5.4
1.8
9.6
1.7
4.7
10.5
0.3
4.9
11.7
0.1
3.9
12.9
Guatemala
62.1
8.1
0.0
0.0
0.3
0.0
61.7
0.2
0.1
61.8
0.1
0.1
61.8
0.0
0.1
61.9
Guinea
76.3
4.9
0.0
0.0
0.9
0.2
75.2
0.4
0.5
75.3
0.1
0.5
75.6
0.0
0.3
75.9
Guinea-Bissau
42.3
3.0
0.0
0.0
1.5
0.3
40.5
0.7
0.9
40.8
0.2
0.9
41.2
0.0
0.5
41.7
Guyana
94.3
13.5
0.0
0.0
4.8
1.4
88.0
3.4
2.2
88.7
1.9
2.7
89.7
0.5
2.5
91.3
Haiti
48.0
14.4
0.0
0.0
3.3
0.5
44.2
2.1
1.3
44.6
1.1
1.5
45.4
0.3
1.1
46.6
Honduras
54.5
5.4
0.0
0.0
0.6
0.2
53.7
0.5
0.2
53.8
0.3
0.3
53.9
0.1
0.3
54.1
Hungary
55.9
37.4
0.0
0.0
14.6
7.1
34.3
6.6
11.6
37.8
2.6
11.7
41.7
0.7
9.5
45.8
India
24.0
5.9
0.0
0.0
0.3
0.2
23.6
0.2
0.2
23.7
0.1
0.2
23.7
0.0
0.2
23.8
Indonesia
110.3
10.2
0.0
0.0
2.1
2.4
105.8
1.4
2.1
106.8
0.6
2.1
107.5
0.1
1.8
108.4
Iran (Islamic Republic of)
19.4
5.8
0.0
0.0
2.1
1.8
15.5
0.6
2.3
16.4
0.1
2.0
17.3
0.0
1.3
18.0
Iraq
30.5
12.1
0.0
0.0
0.0
0.0
30.5
0.0
0.0
30.5
0.0
0.0
30.5
0.0
0.0
30.5
Ireland
24.5
22.3
0.0
0.0
12.3
5.1
7.2
5.9
9.3
9.3
2.9
10.1
11.6
0.9
9.4
14.2
Israel
24.4
0.3
0.0
0.0
0.1
0.1
24.1
0.1
0.1
24.1
0.0
0.1
24.2
0.0
0.1
24.2
Italy
52.0
34.0
0.0
0.0
8.6
7.4
36.0
3.6
10.1
38.4
1.2
10.2
40.6
0.2
9.0
42.8
Jamaica
116.6
0.9
0.0
0.0
0.4
0.1
116.0
0.2
0.2
116.1
0.1
0.2
116.2
0.0
0.2
116.4
Japan
22.9
6.1
0.0
0.0
0.9
1.1
20.9
0.6
0.9
21.3
0.3
0.9
21.7
0.1
0.8
21.9
Jordan
17.9
0.0
0.0
0.0
0.0
0.0
17.9
0.0
0.0
17.9
0.0
0.0
17.9
0.0
0.0
17.9
38
© 2012 Macmillan Publishers Limited. All rights reserved.
Kazakhstan
31.9
0.0
0.0
0.0
0.0
0.0
31.9
0.0
0.0
31.9
0.0
0.0
31.9
0.0
0.0
31.9
Kenya
117.8
4.8
0.0
0.0
0.3
0.2
117.3
0.2
0.2
117.5
0.1
0.2
117.5
0.0
0.2
117.6
Kuwait
30.5
12.1
0.0
0.0
0.0
0.0
30.5
0.0
0.0
30.5
0.0
0.0
30.5
0.0
0.0
30.5
Kyrgyzstan
43.7
0.0
0.0
0.0
0.0
0.0
43.7
0.0
0.0
43.7
0.0
0.0
43.7
0.0
0.0
43.7
Lao People's Democratic Republic
60.4
5.0
0.0
0.0
0.5
0.1
59.8
0.3
0.2
59.9
0.2
0.2
60.0
0.0
0.2
60.2
Latvia
61.3
42.5
0.0
0.0
23.8
7.3
30.2
15.8
11.9
33.6
9.3
14.0
38.1
2.8
13.7
44.8
Lebanon
10.6
2.4
0.0
0.0
0.2
0.0
10.4
0.1
0.1
10.4
0.0
0.1
10.5
0.0
0.1
10.5
Liberia
115.9
10.1
0.0
0.0
1.3
0.2
114.3
0.7
0.7
114.5
0.3
0.7
114.9
0.1
0.5
115.4
Libyan Arab Jamahiriya
24.6
0.0
0.0
0.0
0.0
0.0
24.6
0.0
0.0
24.6
0.0
0.0
24.6
0.0
0.0
24.6
Lithuania
57.4
49.1
0.0
0.0
24.9
8.4
24.1
14.6
14.7
28.1
8.4
15.7
33.3
2.6
14.6
40.2
Luxembourg
100.4
67.3
0.0
0.0
25.0
20.8
54.5
11.6
26.2
62.6
5.4
26.1
68.9
1.7
23.9
74.9
Madagascar
111.1
14.1
0.0
0.0
0.4
0.1
110.7
0.3
0.1
110.7
0.2
0.1
110.8
0.1
0.2
110.9
Malawi
38.0
5.3
0.0
0.0
0.5
0.1
37.4
0.2
0.3
37.5
0.1
0.3
37.6
0.0
0.2
37.8
Malaysia
134.7
17.6
0.0
0.0
12.3
2.2
120.2
7.7
5.0
122.0
3.3
6.4
125.0
0.4
4.9
129.4
Mali
18.7
1.8
0.0
0.0
0.4
0.1
18.2
0.2
0.3
18.3
0.0
0.3
18.5
0.0
0.1
18.6
Mauritania
25.0
4.2
0.0
0.0
0.0
0.0
25.0
0.0
0.0
25.0
0.0
0.0
25.0
0.0
0.0
25.0
Mauritius
56.3
15.5
0.0
0.0
4.5
3.4
48.4
2.9
3.8
49.6
1.6
3.8
50.9
0.5
3.4
52.4
Mexico
27.7
11.0
0.0
0.0
0.7
1.7
25.3
0.5
1.2
26.0
0.3
1.1
26.3
0.1
1.0
26.6
Mongolia
45.9
9.5
0.0
0.0
0.7
0.0
45.1
0.6
0.1
45.2
0.4
0.2
45.3
0.1
0.2
45.5
Morocco
35.4
5.8
0.0
0.0
0.5
2.1
32.8
0.4
1.6
33.5
0.2
1.4
33.8
0.0
1.3
34.1
Mozambique
34.6
1.5
0.0
0.0
0.3
0.1
34.1
0.1
0.2
34.2
0.0
0.2
34.3
0.0
0.1
34.4
Myanmar
46.1
3.6
0.0
0.0
0.9
0.2
45.0
0.6
0.4
45.1
0.3
0.5
45.4
0.1
0.4
45.7
Nepal
98.7
13.1
0.0
0.0
2.2
0.2
96.3
1.8
0.5
96.4
1.2
0.8
96.8
0.4
0.8
97.5
Netherlands
63.0
43.2
0.0
0.0
14.5
11.4
37.1
6.3
15.0
41.7
2.7
14.9
45.4
0.8
13.3
48.9
Netherlands Antilles
56.0
18.6
0.0
0.0
0.0
0.0
56.0
0.0
0.0
56.0
0.0
0.0
56.0
0.0
0.0
56.0
New Caledonia
63.2
3.1
0.0
0.0
1.2
0.1
61.9
0.8
0.4
62.0
0.5
0.6
62.2
0.2
0.6
62.5
New Zealand
125.5
13.7
0.0
0.0
6.7
3.2
115.6
3.8
4.5
117.2
1.7
4.9
118.8
0.4
4.1
120.9
Nicaragua
96.2
7.1
0.0
0.0
0.3
0.0
95.9
0.2
0.1
95.9
0.1
0.1
96.0
0.0
0.1
96.1
Niger
25.3
3.0
0.0
0.0
1.2
0.3
23.8
0.5
0.8
24.1
0.1
0.8
24.5
0.0
0.4
24.9
Nigeria
102.9
5.3
0.0
0.0
1.3
0.2
101.4
0.8
0.6
101.5
0.4
0.6
101.9
0.1
0.5
102.3
Norway
33.3
22.1
0.0
0.0
4.3
7.7
21.3
2.9
7.2
23.3
1.8
7.0
24.5
0.6
7.0
25.7
Oman
30.5
12.1
0.0
0.0
0.0
0.0
30.5
0.0
0.0
30.5
0.0
0.0
30.5
0.0
0.0
30.5
Pakistan
99.0
6.6
0.0
0.0
1.5
0.6
96.9
1.0
0.8
97.2
0.5
0.9
97.6
0.1
0.7
98.2
Panama
96.9
10.3
0.0
0.0
1.3
0.6
95.0
0.9
0.7
95.3
0.6
0.7
95.6
0.2
0.7
96.1
Papua New Guinea
71.2
4.5
0.0
0.0
1.4
0.8
69.0
0.8
1.0
69.4
0.3
1.0
69.8
0.1
0.8
70.3
Paraguay
93.9
20.8
0.0
0.0
9.1
1.3
83.5
5.9
3.4
84.6
2.9
4.3
86.7
0.7
3.2
90.0
Peru
108.0
12.7
0.0
0.0
3.9
0.7
103.5
3.0
1.2
103.8
1.9
1.6
104.5
0.6
1.5
105.9
Philippines
74.3
14.1
0.0
0.0
2.8
1.2
70.3
1.5
1.8
71.0
0.5
1.9
71.9
0.1
1.3
72.9
Poland
79.2
49.3
0.0
0.0
26.1
12.0
41.0
10.8
21.4
46.9
4.1
21.0
54.1
1.1
16.6
61.5
39
© 2012 Macmillan Publishers Limited. All rights reserved.
Portugal
22.3
10.1
0.0
0.0
1.6
4.1
16.7
0.7
3.7
17.9
0.3
3.4
18.6
0.1
3.1
19.1
Qatar
30.5
12.1
0.0
0.0
0.0
0.7
29.8
0.0
0.6
29.9
0.0
0.5
30.0
0.0
0.4
30.0
Republic of Korea
34.1
14.4
0.0
0.0
3.5
3.6
26.9
2.0
3.8
28.2
1.0
3.8
29.3
0.3
3.3
30.5
Republic of Moldova
64.8
27.5
0.0
0.0
6.1
1.2
57.5
4.3
2.2
58.3
2.6
2.7
59.5
0.8
2.4
61.6
Romania
81.4
47.7
0.0
0.0
26.9
6.6
47.9
16.4
13.0
51.9
9.6
14.3
57.6
3.0
12.7
65.8
Russian Federation
32.1
22.7
0.0
0.0
8.7
5.1
18.3
5.0
6.3
20.8
2.5
6.5
23.2
0.6
5.6
25.9
Rwanda
78.0
51.0
0.0
0.0
4.1
0.7
73.2
2.1
2.1
73.8
0.8
2.2
75.0
0.2
1.4
76.4
Saint Vincent and the Grenadines
56.0
18.6
0.0
0.0
0.0
0.0
56.0
0.0
0.0
56.0
0.0
0.0
56.0
0.0
0.0
56.0
Samoa
11.9
5.3
0.0
0.0
0.2
0.0
11.7
0.1
0.1
11.7
0.0
0.1
11.8
0.0
0.1
11.9
Sao Tome and Principe
120.4
49.3
0.0
0.0
6.2
0.4
113.7
5.2
1.1
114.0
3.7
1.9
114.8
1.2
2.2
116.9
Saudi Arabia
5.0
0.0
0.0
0.0
0.0
0.0
5.0
0.0
0.0
5.0
0.0
0.0
5.0
0.0
0.0
5.0
Senegal
32.6
8.2
0.0
0.0
2.7
0.6
29.3
1.1
1.7
29.8
0.2
1.8
30.7
0.0
1.0
31.6
Sierra Leone
68.0
3.0
0.0
0.0
0.3
0.1
67.6
0.1
0.2
67.6
0.0
0.2
67.8
0.0
0.1
67.9
Singapore
70.2
8.4
0.0
0.0
1.2
1.2
67.7
0.8
1.2
68.2
0.4
1.2
68.6
0.1
1.1
69.0
Slovakia
90.7
59.9
0.0
0.0
23.5
17.0
50.2
14.0
20.1
56.6
8.2
20.1
62.4
2.6
18.8
69.3
Slovenia
110.9
74.7
0.0
0.0
41.4
15.7
53.8
19.0
30.2
61.7
7.9
31.2
71.9
2.0
25.5
83.4
Solomon Islands
70.5
14.1
0.0
0.0
4.6
2.3
63.5
3.4
2.6
64.5
2.2
2.9
65.4
0.7
3.1
66.8
Somalia
50.1
1.2
0.0
0.0
0.1
0.0
50.0
0.0
0.1
50.0
0.0
0.1
50.0
0.0
0.0
50.1
South Africa
73.5
6.5
0.0
0.0
1.2
2.2
70.0
0.7
1.8
70.9
0.4
1.6
71.5
0.1
1.4
72.0
Spain
18.4
10.8
0.0
0.0
2.3
4.7
11.5
1.0
4.8
12.7
0.4
4.5
13.5
0.1
4.2
14.1
Sri Lanka
29.0
5.2
0.0
0.0
3.8
0.4
24.8
3.0
0.9
25.1
2.0
1.3
25.7
0.6
1.3
27.1
Sudan
16.5
3.0
0.0
0.0
0.9
0.2
15.4
0.4
0.6
15.5
0.1
0.6
15.9
0.0
0.3
16.2
Suriname
184.0
24.4
0.0
0.0
13.2
1.5
169.2 10.6
3.2
170.2
7.2
4.6
172.1
2.3
4.9
176.8
Sweden
36.1
26.8
0.0
0.0
4.9
8.8
22.4
3.8
7.7
24.6
2.6
7.5
26.0
0.8
7.7
27.5
Switzerland
94.4
77.6
0.0
0.0
22.8
26.2
45.3
11.9
29.6
52.9
6.3
29.4
58.7
1.9
28.1
64.3
Syrian Arab Republic
30.5
9.2
0.0
0.0
6.7
0.9
22.8
3.7
3.1
23.6
1.4
3.8
25.3
0.2
2.5
27.8
Tajikistan
4.9
0.0
0.0
0.0
0.0
0.0
4.9
0.0
0.0
4.9
0.0
0.0
4.9
0.0
0.0
4.9
Thailand
38.9
3.5
0.0
0.0
1.1
0.6
37.2
0.5
0.8
37.6
0.2
0.8
37.9
0.0
0.5
38.3
Timor-Leste
70.2
8.4
0.0
0.0
0.1
0.0
70.1
0.0
0.0
70.1
0.0
0.0
70.1
0.0
0.0
70.1
Togo
100.7
12.0
0.0
0.0
0.8
0.2
99.7
0.4
0.4
99.9
0.1
0.5
100.1
0.0
0.3
100.4
Tonga
101.1
19.8
0.0
0.0
7.1
4.3
89.8
3.9
5.3
92.0
1.5
5.4
94.2
0.2
4.0
96.8
Trinidad and Tobago
73.6
26.9
0.0
0.0
12.1
3.2
58.3
9.8
4.3
59.5
6.7
5.8
61.1
2.1
6.7
64.8
Tunisia
7.0
0.1
0.0
0.0
0.0
0.0
6.9
0.0
0.0
6.9
0.0
0.0
7.0
0.0
0.0
7.0
Turkey
57.4
21.6
0.0
0.0
13.4
3.4
40.7
6.7
8.1
42.7
3.4
8.3
45.7
1.0
6.8
49.6
Turkmenistan
2.1
0.0
0.0
0.0
0.0
0.0
2.1
0.0
0.0
2.1
0.0
0.0
2.1
0.0
0.0
2.1
Uganda
30.5
0.4
0.0
0.0
0.1
0.0
30.4
0.0
0.0
30.4
0.0
0.0
30.4
0.0
0.0
30.5
Ukraine
63.2
49.1
0.0
0.0
21.7
5.4
36.1
11.1
12.0
40.1
5.4
12.2
45.6
1.5
9.5
52.1
United Arab Emirates
37.2
0.0
0.0
0.0
0.0
0.0
37.2
0.0
0.0
37.2
0.0
0.0
37.2
0.0
0.0
37.2
United Kingdom
40.6
29.7
0.0
0.0
7.2
12.2
21.2
3.3
12.9
24.4
1.6
12.4
26.6
0.5
11.6
28.5
40
© 2012 Macmillan Publishers Limited. All rights reserved.
United Republic of Tanzania
51.8
1.8
0.0
0.0
0.5
0.1
51.2
0.2
0.3
51.3
0.0
0.3
51.4
0.0
0.2
51.6
United States of America
53.2
32.1
0.0
0.0
12.3
9.4
31.5
9.1
10.1
34.1
5.8
11.1
36.4
1.8
11.9
39.6
Uruguay
93.9
1.3
0.0
0.0
0.4
0.4
93.1
0.3
0.4
93.2
0.1
0.4
93.4
0.0
0.4
93.5
Uzbekistan
4.4
1.0
0.0
0.0
0.2
0.2
3.9
0.1
0.2
4.0
0.0
0.2
4.1
0.0
0.2
4.2
Vanuatu
11.9
5.3
0.0
0.0
0.6
0.0
11.4
0.5
0.1
11.4
0.3
0.1
11.5
0.1
0.2
11.7
Venezuela (Bolivarian Republic of)
93.9
21.8
0.0
0.0
5.7
2.5
85.7
2.9
4.1
86.9
1.6
4.1
88.2
0.5
3.5
89.9
Viet Nam
60.0
5.8
0.0
0.0
1.8
0.6
57.6
1.2
0.8
57.9
0.8
0.9
58.3
0.2
0.8
59.0
Yemen
7.0
0.0
0.0
0.0
0.0
0.0
7.0
0.0
0.0
7.0
0.0
0.0
7.0
0.0
0.0
7.0
Zambia
41.9
2.0
0.0
0.0
0.5
0.1
41.3
0.2
0.3
41.4
0.1
0.3
41.5
0.0
0.2
41.7
Zimbabwe
26.3
0.2
0.0
0.0
0.0
0.0
26.3
0.0
0.0
26.3
0.0
0.0
26.3
0.0
0.0
26.3
3.2. Trade and Consumption of Carbon as Wood Products Table S12 provides a detailed breakdown of the how the proportion of forest carbon consumed as wood products domestically versus abroad varies by country. Figure S6 graphically displays this information for four selected countries. Further detail is provided in the supplementary spreadsheets with respect to trade between individual countries. Figure S6: Fraction above ground biomass that is consumed domestically or abroad as end-product following forest clearance at t = 0 (negative values indicate export of good). Supporting Information Section 3.2 provides a table of values for all 169 countries examined.
41
© 2012 Macmillan Publishers Limited. All rights reserved.
Table S12: Fraction above ground carbon that is consumed domestically or consumed abroad as end product following forest clearance at t = 0 (negative values indicate consumption abroad) Domestic SawnFiberwood board
Ply/ Ven
Fuelwood
Other
Consumed Abroad Sawn- FiberPaper wood board
Ply/ Ven
Fuelwood
Nonmerch
0.00
0.00
0.92
0.00
-0.21
0.55
0.00
0.00
0.00
0.58
0.00
0.00
0.00
0.00
0.98
-0.03
0.00
-0.01
0.00
0.00
0.83
-0.02
0.00
-0.02
0.00
0.00
0.64
0.00
-0.06
-0.01
-0.01
0.00
0.00
0.67
0.09
0.00
-0.25
-0.13
-0.11
-0.01
0.00
0.29
0.00
0.07
0.00
0.00
-0.08
0.00
0.00
0.00
0.74
0.00
0.12
0.00
0.00
-0.14
0.00
-0.01
0.00
0.74
0.00
0.00
0.35
0.00
-0.03
0.00
0.00
0.00
-0.01
0.61
0.00
0.00
0.00
0.17
0.00
0.00
0.00
0.00
0.00
0.00
0.83
0.00
0.00
0.00
0.00
0.07
0.00
0.00
0.00
0.00
0.00
0.00
0.67
0.02
0.09
0.08
0.01
0.04
-0.01
-0.04
-0.11
-0.08
-0.03
0.00
0.36
0.01
0.00
0.00
0.01
0.00
0.04
0.00
-0.24
-0.08
-0.22
-0.01
-0.02
0.36
Belize
0.00
0.00
0.03
0.00
0.00
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.94
Benin
0.03
0.00
0.01
0.00
0.00
0.09
0.00
0.00
0.00
0.00
0.00
0.00
0.87
Bhutan
0.02
0.00
0.00
0.01
0.01
0.21
0.00
0.00
0.00
0.00
0.00
0.00
0.75
0.00
0.00
0.04
0.00
0.00
0.04
0.00
0.00
-0.01
-0.01
0.00
0.00
0.90
0.08
0.01
0.00
0.01
0.00
0.09
0.00
-0.03
-0.35
-0.01
-0.02
-0.06
0.34
Brazil Brunei Darussalam
0.01
0.03
0.02
0.01
0.00
0.09
0.00
-0.05
0.00
0.00
-0.01
0.00
0.79
0.04
0.00
0.16
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.79
Bulgaria
0.01
0.04
0.13
0.01
0.00
0.22
-0.01
-0.07
-0.05
-0.23
-0.02
-0.02
0.21
Burkina Faso
0.02
0.00
0.00
0.00
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.94
Other
Paper
Afghanistan
0.04
0.00
0.02
0.01
0.00
0.01
0.00
0.00
0.00
0.00
Albania
0.12
0.00
0.00
0.04
0.00
0.07
0.00
0.00
-0.01
0.00
Algeria
0.00
0.00
0.00
0.00
0.00
0.41
0.00
0.00
0.00
Angola
0.01
0.00
0.00
0.00
0.00
0.01
0.00
0.00
Argentina
0.01
0.06
0.02
0.02
0.00
0.01
0.00
Armenia
0.00
0.00
0.00
0.00
0.06
0.26
0.00
Australia
0.01
0.11
0.05
0.03
0.00
0.04
Austria
0.00
0.03
0.06
0.02
0.00
Azerbaijan
0.08
0.00
0.02
0.00
Bahamas
0.00
0.00
0.00
0.00
Bahrain
0.00
0.00
0.00
Bangladesh
0.00
0.00
Barbados
0.26
Belarus
0.13
Belgium
Bolivia (Plurinational State of) Bosnia and Herzegovina
Burundi
0.00
0.00
0.00
0.00
0.00
0.08
0.00
0.00
0.00
0.00
0.00
0.00
0.91
Cambodia
0.00
0.00
0.00
0.00
0.00
0.25
0.00
0.00
0.00
0.00
0.00
0.00
0.74
Cameroon
0.01
0.00
0.00
0.00
0.00
0.09
0.00
0.00
-0.02
0.00
0.00
0.00
0.87
Canada
0.00
0.03
0.04
0.02
0.01
0.00
0.00
-0.19
-0.07
-0.05
-0.01
0.00
0.58
Cape Verde
0.00
0.00
0.00
0.00
0.00
0.80
0.00
0.00
0.00
0.00
0.00
0.00
0.20
Central African Republic
0.04
0.00
0.01
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.00
0.88
Chad
0.00
0.00
0.00
0.00
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.96
Chile
0.00
0.02
0.03
0.00
0.00
0.04
0.00
-0.17
-0.02
-0.02
-0.01
0.00
0.68
China
0.01
0.04
0.01
0.01
0.02
0.10
0.00
0.00
0.00
0.00
-0.01
0.00
0.80
Colombia
0.00
0.02
0.00
0.00
0.00
0.11
0.00
-0.01
0.00
0.00
0.00
0.00
0.85
Congo
0.04
0.00
0.00
0.00
0.00
0.02
0.00
-0.01
-0.03
0.00
-0.01
0.00
0.88
Costa Rica
0.01
0.00
0.02
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.94
Côte d'Ivoire
0.00
0.00
0.00
0.00
0.01
0.06
0.00
0.00
-0.01
0.00
-0.01
0.00
0.91
42
© 2012 Macmillan Publishers Limited. All rights reserved.
Croatia
0.06
0.01
0.00
0.02
0.00
0.00
0.00
-0.06
-0.14
-0.07
-0.01
-0.01
0.61
Cuba
0.10
0.01
0.05
0.08
0.00
0.12
0.00
0.00
0.00
0.00
0.00
0.00
0.63
Cyprus
0.00
0.00
0.04
0.00
0.03
0.42
0.00
-0.21
0.00
0.00
0.00
0.00
0.30
Czech Republic
0.00
0.01
0.08
0.02
0.00
0.01
0.00
-0.16
-0.08
-0.08
-0.01
0.00
0.54
0.02
0.02
0.01
0.00
0.00
0.12
0.00
0.00
0.00
0.00
0.00
0.00
0.81
0.02
0.00
0.00
0.00
0.00
0.12
0.00
0.00
0.00
0.00
0.00
0.00
0.87
Denmark
0.01
0.00
0.00
0.05
0.00
0.17
-0.01
-0.29
-0.09
-0.06
-0.01
-0.01
0.32
Djibouti
0.00
0.00
0.00
0.00
0.00
0.05
0.00
0.00
0.00
0.00
0.00
0.00
0.95
Democratic People's Republic of Korea Democratic Republic of the Congo
Dominica
0.00
0.00
0.00
0.00
0.00
0.33
0.00
0.00
0.00
0.00
0.00
0.00
0.67
Dominican Republic
0.00
0.00
0.00
0.00
0.00
0.27
0.00
0.00
0.00
0.00
0.00
0.00
0.73
Ecuador
0.01
0.00
0.02
0.00
0.05
0.10
0.00
-0.01
0.00
-0.01
-0.01
0.00
0.78
Egypt
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
El Salvador
0.00
0.00
0.01
0.00
0.00
0.06
0.00
-0.01
0.00
0.00
0.00
0.00
0.91
Equatorial Guinea
0.00
0.00
0.00
0.00
0.00
0.01
-0.01
-0.04
-0.01
-0.01
-0.02
0.00
0.91
Eritrea
0.00
0.00
0.00
0.00
0.00
0.05
0.00
0.00
0.00
0.00
0.00
0.00
0.95
Estonia
0.01
0.00
0.08
0.02
0.00
0.07
0.00
-0.25
-0.11
-0.07
-0.02
-0.01
0.35
Ethiopia
0.01
0.00
0.00
0.00
0.00
0.09
0.00
0.00
0.00
0.00
0.00
0.00
0.90
Fiji
0.01
0.00
0.15
0.00
0.11
0.03
0.00
0.00
-0.03
0.00
-0.01
0.00
0.65
Finland
0.00
0.03
0.04
0.00
0.00
0.02
0.00
-0.39
-0.05
0.00
-0.02
0.00
0.44
France
0.00
0.05
0.07
0.05
0.00
0.12
0.00
-0.14
-0.02
-0.06
-0.01
0.00
0.48
French Polynesia
0.00
0.00
0.00
0.00
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.96
Gabon
0.00
0.00
0.00
0.00
0.00
0.01
0.00
-0.01
-0.01
0.00
-0.02
0.00
0.96
Gambia
0.02
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.96
Georgia
0.00
0.01
0.01
0.00
0.00
0.24
0.00
0.00
-0.04
0.00
-0.01
0.00
0.69
Germany
0.02
0.09
0.06
0.07
0.00
0.03
0.00
-0.22
-0.06
-0.08
-0.01
0.00
0.38
Ghana
0.00
0.00
0.00
0.00
0.00
0.05
0.00
0.00
0.00
0.00
0.00
0.00
0.94
Greece
0.04
0.00
0.02
0.30
0.01
0.14
0.00
-0.07
0.00
-0.03
0.00
0.00
0.40
Guatemala
0.00
0.00
0.00
0.00
0.00
0.12
0.00
0.00
0.00
0.00
0.00
0.00
0.87
Guinea
0.01
0.00
0.00
0.00
0.00
0.05
0.00
0.00
0.00
0.00
0.00
0.00
0.94
Guinea-Bissau
0.04
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.93
Guyana
0.01
0.00
0.01
0.00
0.01
0.05
0.00
-0.02
-0.02
0.00
-0.02
0.00
0.86
Haiti
0.04
0.00
0.04
0.00
0.00
0.20
0.00
0.00
0.00
0.00
0.00
0.00
0.72
Honduras
0.00
0.00
0.01
0.00
0.00
0.08
0.00
0.00
0.00
0.00
0.00
0.00
0.91
Hungary
0.08
0.01
0.01
0.05
0.00
0.16
0.00
-0.13
-0.06
-0.09
-0.01
-0.02
0.38
Iceland
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
India
0.00
0.01
0.01
0.00
0.00
0.21
0.00
0.00
0.00
0.00
0.00
0.00
0.76
Indonesia
0.00
0.01
0.00
0.00
0.00
0.02
0.00
-0.03
0.00
0.00
-0.01
0.00
0.92
Iran (Islamic Republic of)
0.02
0.13
0.00
0.11
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.73
Iraq
0.00
0.00
0.00
0.00
0.00
0.40
0.00
0.00
0.00
0.00
0.00
0.00
0.60
Ireland
0.02
0.00
0.13
0.08
0.00
0.01
0.00
-0.22
-0.08
-0.28
0.00
0.00
0.19
43
© 2012 Macmillan Publishers Limited. All rights reserved.
Israel
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.99
Italy
0.01
0.09
0.02
0.10
0.02
0.25
0.00
-0.08
-0.01
-0.03
-0.01
0.00
0.39
Jamaica
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.99
Japan
0.00
0.16
0.02
0.01
0.01
0.00
0.00
-0.02
0.00
0.00
0.00
0.00
0.78
Jordan
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
Kazakhstan
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
Kenya
0.00
0.00
0.00
0.00
0.00
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.96
Kuwait
0.00
0.00
0.00
0.00
0.00
0.40
0.00
0.00
0.00
0.00
0.00
0.00
0.60
Kyrgyzstan
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
Lao People's Democratic Republic
0.00
0.00
0.00
0.00
0.00
0.07
0.00
0.00
0.00
0.00
0.00
0.00
0.92
Latvia
0.07
0.00
0.08
0.00
0.00
0.00
0.00
-0.14
-0.17
-0.07
-0.04
-0.01
0.41
Lebanon
0.00
0.00
0.00
0.00
0.01
0.20
0.00
0.00
0.00
0.00
0.00
0.00
0.77
Liberia
0.01
0.00
0.00
0.00
0.00
0.07
0.00
0.00
0.00
0.00
0.00
0.00
0.91
Libyan Arab Jamahiriya
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
Lithuania
0.00
0.00
0.10
0.12
0.00
0.09
-0.01
-0.16
-0.15
-0.09
-0.02
0.00
0.25
Luxembourg
0.00
0.00
0.00
0.00
0.00
0.01
-0.01
-0.28
-0.09
-0.18
-0.01
0.00
0.41
Madagascar
0.00
0.00
0.00
0.00
0.00
0.12
0.00
0.00
0.00
0.00
0.00
0.00
0.87
Malawi
0.01
0.00
0.00
0.00
0.00
0.12
0.00
0.00
0.00
0.00
0.00
0.00
0.86
Malaysia
0.00
0.01
0.01
0.00
0.03
0.00
0.00
-0.01
-0.01
-0.01
-0.04
0.00
0.88
Mali
0.03
0.00
0.00
0.00
0.00
0.07
0.00
0.00
0.00
0.00
0.00
0.00
0.91
Malta
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
Mauritania
0.00
0.00
0.00
0.00
0.00
0.17
0.00
0.00
0.00
0.00
0.00
0.00
0.83
Mauritius
0.04
0.00
0.03
0.00
0.00
0.05
0.00
-0.09
-0.02
0.00
0.00
0.00
0.76
Mexico
0.00
0.09
0.02
0.00
0.00
0.23
0.00
-0.01
0.00
0.00
0.00
0.00
0.63
Mongolia
0.00
0.00
0.02
0.00
0.00
0.18
0.00
0.00
0.00
0.00
0.00
0.00
0.80
Morocco
0.00
0.03
0.01
0.00
0.00
0.03
0.00
-0.06
0.00
0.00
0.00
0.00
0.86
Mozambique
0.01
0.00
0.00
0.00
0.00
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.96
Myanmar
0.01
0.00
0.01
0.00
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.93
Nepal
0.00
0.00
0.02
0.00
0.00
0.10
0.00
0.00
0.00
0.00
0.00
0.00
0.88
Netherlands
0.00
0.00
0.00
0.00
0.00
0.05
-0.01
-0.24
-0.07
-0.18
-0.01
-0.05
0.39
Netherlands Antilles
0.00
0.00
0.00
0.00
0.00
0.32
0.00
0.00
0.00
0.00
0.00
0.00
0.68
New Caledonia
0.01
0.00
0.01
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.96
New Zealand
0.02
0.00
0.01
0.00
0.01
0.00
0.00
-0.03
-0.01
-0.01
-0.01
0.00
0.91
Nicaragua
0.00
0.00
0.00
0.00
0.00
0.07
0.00
0.00
0.00
0.00
0.00
0.00
0.93
Niger
0.06
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.00
0.88
Nigeria
0.01
0.00
0.01
0.00
0.00
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.95
Norway
0.00
0.04
0.07
0.02
0.00
0.06
0.00
-0.31
-0.03
-0.02
0.00
0.00
0.44
Oman
0.00
0.00
0.00
0.00
0.00
0.39
0.00
0.00
0.00
0.00
0.00
-0.01
0.60
Pakistan
0.00
0.01
0.01
0.00
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.94
Panama Papua New Guinea
0.00
0.00
0.00
0.00
0.00
0.08
0.00
-0.01
-0.01
0.00
0.00
0.00
0.90
0.00
0.00
0.00
0.00
0.00
0.02
0.00
-0.02
0.00
-0.01
-0.01
0.00
0.94
44
© 2012 Macmillan Publishers Limited. All rights reserved.
Paraguay
0.04
0.00
0.03
0.00
0.02
0.07
0.00
0.00
-0.01
0.00
0.00
-0.01
0.80
Peru
0.00
0.01
0.02
0.00
0.00
0.06
0.00
0.00
-0.01
0.00
0.00
0.00
0.90
Philippines
0.03
0.02
0.00
0.00
0.01
0.12
0.00
0.00
0.00
0.00
0.00
0.00
0.82
Poland
0.03
0.07
0.07
0.19
0.02
0.02
0.00
-0.09
-0.01
-0.07
-0.01
0.00
0.43
Portugal
0.00
0.13
0.01
0.02
0.00
0.01
0.00
-0.16
-0.02
-0.03
0.00
0.00
0.62
Qatar
0.00
0.00
0.00
0.00
0.00
0.36
0.00
-0.03
0.00
0.00
0.00
0.00
0.61
Republic of Korea
0.01
0.15
0.04
0.04
0.03
0.10
0.00
-0.01
0.00
0.00
0.00
0.00
0.62
Republic of Moldova
0.03
0.01
0.06
0.00
0.00
0.26
0.00
0.00
-0.01
0.00
0.00
0.00
0.61
Romania
0.03
0.07
0.08
0.05
0.00
0.05
0.00
-0.01
-0.12
-0.08
-0.02
0.00
0.49
Russian Federation
0.07
0.11
0.02
0.05
0.01
0.07
-0.01
-0.13
-0.08
-0.03
-0.04
0.00
0.38
Rwanda Saint Vincent and the Grenadines
0.05
0.00
0.02
0.00
0.00
0.58
0.00
0.00
0.00
0.00
0.00
0.00
0.35
0.00
0.00
0.00
0.00
0.00
0.28
0.00
0.00
0.00
0.00
0.00
0.00
0.72
Samoa
0.04
0.00
0.01
0.00
0.00
0.39
0.00
0.00
0.00
0.00
0.00
0.00
0.56
Sao Tome and Principe
0.00
0.00
0.06
0.00
0.00
0.32
0.00
0.00
0.00
0.00
0.00
0.00
0.62
Saudi Arabia
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
Senegal
0.10
0.00
0.00
0.00
0.00
0.14
0.00
0.00
0.00
0.00
0.00
0.00
0.75
Sierra Leone
0.01
0.00
0.00
0.00
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.96
Singapore
0.00
0.00
0.00
0.00
0.00
0.00
0.00
-0.03
-0.01
0.00
-0.01
-0.06
0.89
Slovakia
0.00
0.17
0.08
0.04
0.00
0.02
-0.01
-0.07
-0.08
-0.08
-0.01
0.00
0.44
Slovenia
0.00
0.06
0.00
0.18
0.03
0.03
0.00
-0.08
-0.10
-0.09
-0.04
-0.02
0.38
Solomon Islands
0.00
0.00
0.00
0.00
0.00
0.00
0.00
-0.08
-0.05
-0.01
-0.01
0.00
0.84
Somalia
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.98
South Africa
0.00
0.04
0.01
0.00
0.00
0.01
0.00
-0.01
0.00
0.00
0.00
0.00
0.92
Spain
0.00
0.25
0.03
0.06
0.01
0.02
0.00
-0.09
0.00
-0.03
-0.01
-0.01
0.49
Sri Lanka
0.02
0.00
0.00
0.00
0.00
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.94
Sudan
0.07
0.00
0.00
0.00
0.00
0.11
0.00
0.00
0.00
0.00
0.00
0.00
0.82
Suriname
0.00
0.00
0.07
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.90
Sweden
0.00
0.29
0.05
0.00
0.00
0.02
0.00
-0.15
-0.08
-0.01
0.00
0.00
0.39
Switzerland
0.00
0.19
0.06
0.04
0.00
0.09
0.00
-0.16
-0.05
-0.12
-0.01
0.00
0.28
Syrian Arab Republic
0.06
0.00
0.02
0.05
0.12
0.00
0.00
0.00
0.00
0.00
0.00
-0.04
0.70
Tajikistan
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
Thailand
0.01
0.02
0.00
0.00
0.00
0.03
0.00
0.00
0.00
-0.01
0.00
0.00
0.92
Timor-Leste
0.00
0.00
0.00
0.00
0.00
0.12
0.00
0.00
0.00
0.00
0.00
0.00
0.88
Togo
0.01
0.00
0.00
0.00
0.00
0.11
0.00
0.00
0.00
0.00
0.00
0.00
0.88
Tonga Trinidad and Tobago
0.00
0.00
0.00
0.00
0.00
0.04
-0.01
-0.06
-0.01
-0.02
-0.04
0.00
0.82
0.00
0.00
0.16
0.00
0.02
0.05
0.00
-0.06
0.00
0.00
0.00
0.00
0.72
Tunisia
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.98
Turkey
0.00
0.04
0.10
0.14
0.01
0.03
0.00
0.00
0.00
-0.02
0.00
0.00
0.66
Turkmenistan
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
Uganda
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.99
Ukraine
0.03
0.02
0.04
0.11
0.01
0.22
-0.01
-0.04
-0.10
-0.08
-0.02
-0.03
0.28
45
© 2012 Macmillan Publishers Limited. All rights reserved.
United Arab Emirates
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
United Kingdom
0.01
0.24
0.05
0.10
0.00
0.00
0.00
-0.18
-0.02
-0.03
0.00
-0.01
0.37
0.01
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.97
0.01
0.19
0.17
0.03
0.03
0.07
0.00
-0.05
-0.01
0.00
0.00
0.00
0.43
Uruguay
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.99
Uzbekistan
0.01
0.04
0.01
0.00
0.00
0.08
0.00
-0.03
-0.01
-0.03
0.00
0.00
0.80
United Republic of Tanzania United States of America
Vanuatu
0.00
0.00
0.10
0.00
0.00
0.29
0.00
0.00
0.00
0.00
0.00
0.00
0.61
Venezuela (Bolivarian Republic of)
0.00
0.03
0.03
0.03
0.00
0.12
0.00
0.00
0.00
-0.01
0.00
0.00
0.79
Viet Nam
0.01
0.01
0.02
0.00
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.91
Yemen
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
Zambia
0.01
0.00
0.00
0.00
0.00
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.95
Zimbabwe
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.99
3.3. Sensitivity Analysis for Select Parameters We tested the sensitivity of the results for various model parameters. Table S13 shows the parameters tested, the default value used, alternative values tested, and the corresponding scenario number for Figures S7 and S8. The first scenario is set to the default values used for this study. As previously mentioned, we assume that fuelwood and charcoal can be produced from either non-merchantable wood, commercial merchantable growing stock, or non-commercial merchantable growing stock. The second scenario tests this assumption by restricting fuelwood only to non-merchantable wood. Scenarios 3 - 16 examine various aspects of the solid waste disposal process. Scenarios 17 and 18 test the sensitivity of varying the fraction above ground biomass relative to growing stock by ±50% from FRA 2010-derived values. The results for each of these scenarios are shown in Figures S7 and S8. We observe a large sensitivity to occur with respect to the assumption that fuelwood and charcoal can be produced from either non-merchantable wood, commercial merchantable growing stock, or non-commercial merchantable growing stock (see manuscript for further
46
© 2012 Macmillan Publishers Limited. All rights reserved.
discussion). The fraction above ground biomass relative to growing stock also has a substantial effect on the fraction carbon remaining after 30 years--particularly in countries with predominantly temperate forests. Additionally, assuming that all countries have highly aerobic landfills (scenario 3) reduces the overall carbon storage time as wood products decay more quickly once in the landfill. Conversely, assuming that all countries have highly anaerobic landfills (scenario 4) substantially increases the overall carbon storage time as wood products decay more slowly once in the landfill. Scenarios 5 - 16 appear to have a relatively small effect on carbon storage. Table S13: Sensitivity analysis -- parameters tested, the default value used, alternative values tested, and the corresponding scenario number for Figures S7 and S8
Alternative Values No highly aerobic (all countries = 0.4); highly anaerobic (all countries = 0.9)
Alternative Scenario (see Figures S7 & S8) 2
Parameter Fuelwood from Growing Stock?
Default Value Yes
IPCC SWDS Methane Correction Factor (fraction anaerobic)
GDP Based (see Table S8)
IPCC methane generation rate constant, wood products and paper
default (varies by climate, see Table S9)
low; high (varies by climate, see Table S9)
5,6
IPCC DOCf default value
0.5
0.4 (low); 0.6 (high)
7,8
IPCC DOC, default value, wood
0.43
0.35 (low); 0.5 (high)
9,10
IPCC DOC, default value, paper Skog (2008) rate constant for aerobic decomposition of wood; in terms of half-life (years) Skog (2008) rate constant for aerobic decomposition of paper; in terms of half-life (years) Fraction above ground biomass relative to merchantable wood
0.4
0.35 (low); 0.5 (high)
11,12
16.25
24.375 (slow); 8.125 (fast)
13,14
8.25
16.5 (slow); 4.125 (fast)
15,16
FRA 2010
FRA 2010 * 150% FRA 2010 * 50% (min =1)
17 18
3,4
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Figure S7: Countries with predominantly temperate forests, sensitivity to select parameters
1.00 Fraction C remaining at t = 30 years
0.90 0.80 0.70
min
0.60
lower 5th
0.50
lower 25th
0.40
median
0.30
upper 75th upper 95th
0.20
max
0.10 0.00 0
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18
Scenario # (see corresponding table)
Figure S8: Countries with predominantly tropical forests, sensitivity to select parameters
1.00
Fraction C remaining at t = 30 years
0.90 0.80 0.70
min
0.60
lower 5th
0.50
lower 25th
0.40
median
0.30
upper 75th
0.20
upper 95th max
0.10 0.00 0
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18
Scenario # (see corresponding table)
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3.4. Regional Analysis of United States In this section, we address the question: how representative is the US average value of HWP and SWDS carbon disposition for US regions? Specifically, the US North, South, Rocky Mountain, and Pacific Coast regions are examined. US FIA 15 data, and corresponding regional definitions, are used to conduct this sensitivity analysis. Figure S8 shows the fraction of forest products manufactured in the US by region. Figure S8: Production by region as a percent of the US total
100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%
US Pacific Coast US Rocky Mountain US South US North
For four US regions, the method described previously is used to estimate (1) the volume of growing stock (m3 ha-1) that is stored in each type of end-product at t = 0 and (2) the tons (Mg) of carbon remaining over time in the HWP and SWDS pools after a hectare of land is cleared. Figure S8 shows the fate of carbon following forest clearance in four US regions. Whereas the US North and South are fairly well represented by the US average, the US Rocky Mountain region is less so. Even more, the US Pacific Coast varies substantially from the US average. Variation exists in growing stock, end-product composition, and percent commercial versus non-commercial species.
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Figure S9: Fate of carbon following forest clearance in four US regions
Supplementary Spreadsheets Spreadsheets used for model are hosted at: www.steps.ucdavis.edu/research/Thread_6/lcfs/forestry Supplementary References 1. Food and Agricultural Organization (FAO), FAO Forestry Paper Report No. 163, 2010. 2. Intergovernmental Panel on Climate Change (IPCC), Good Practice Guidance for Land-Use, Land-Use Change and Forestry, 2003. 3. Intergovernmental Panel on Climate Change, IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4, Ch. 12, 2006a. 4. United Nations Environmental Programme, World Conservation Monitoring Center (UNEP50
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WCMC), Original and Current Forest, Global Generalized Current Forest, Available at http://www.unep-wcmc.org/generalised-original-and-current-forests-1998_718.html (1998). 5. Forest and Agricultural Organization, FAO, ForeStat Dataset, Available at http://faostat.fao.org/site/630/default.aspx (2011). 6. Buongiorno, J., Shushuai, Z., Zhang, D., Turner, J. & Tomberlin, D., The Global Forest Products Model (Academic Press, 2003). 7. Ince, P. J., Kramp, A. D., Skog, K. E., Spelter, H. N. & Wear, D. N., A Technical Document Supporting the Forest Service 2010 RPA Assessment Report No. Research Paper FPL-RP662, 2011. 8. Marland, E. S., Stellar, K. & Marland, G. H., A Distributed Approach to Accounting for Carbon in Wood Products. Mitigation and Adaptation Strategies for Global Change 15, 7191 (2010). 9. Pingoud, K., Perala, A.-L., Soimakallio, S. & Pussinen, A., Greenhouse gas impacts of harvested wood products: Evaluation and development of methods, 2003. 10. Miner, R., Impact of the global forest industry on atmospheric greenhouse gases, 2010. 11. Intergovernmental Panel on Climate Change, IPCC Guidelines on National Greenhouse Gas Inventories, Vol. 5, Ch. 2, 2006. 12. Intergovernmental Panel on Climate Change, IPCC Guidelines for National Greenhouse Gas Inventories, Vol. 5, Ch. 3, 2006. 13. Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A., Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25, 1965 - 1978 (2005). 14. Skog, K., Sequestration of carbon in harvested wood products for the United States. Forest Products Journal 58 (6), 56 - 72 (2008). 15. Smith, B., Miles, P., Perry, C. & Pugh, S., Gen. Tech. Rep. WO-78, 2009.
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