last update: July 2010

ENVIRONMENTAL INDICATORS

Natural disasters:

Meteorological Disasters 

     
     
 
No. of events
Fatalities
Persons Affected
1980-89
1990-99
2000-09
1980-89
1990-99
2000-09
1980-89
1990-99
2000-09
               
Afghanistan
0
1
4
0
10
1 648
0
0
193 158
Albania
0
0
2
0
0
8
0
0
525 000
Algeria
1
0
3
0
0
27
10 107
0
0
American Samoa
1
0
2
0
0
0
0
0
20 000
Anguilla
2
1
0
0
0
0
0
150
0
Antigua and Barbuda
1
5
1
2
6
0
7 500
69 500
25 800
Argentina
2
3
8
2
21
57
2 000
14 000
6 400
Australia
22
26
26
40
51
12
0
3 935 510
35 665
Austria
2
8
6
12
3
7
0
0
300
Bahamas
0
4
8
0
5
14
0
0
20 500
Bangladesh
22
44
40
18 977
142 613
5 588
14 598 860
21 617 148
13 096 657
Barbados
2
1
2
0
0
1
0
0
0
Belarus
0
1
1
0
5
0
0
21 045
0
Belgium
3
10
3
0
24
7
0
1 700
0
Belize
0
1
7
0
9
54
0
60 000
112 000
Benin
0
0
1
0
0
0
0
0
800
Bermuda
4
0
1
0
0
4
0
0
0
Bhutan
0
1
1
0
17
12
0
65 000
0
Bolivia
0
0
2
0
0
20
0
0
18 740
Bosnia and Herzegovina
0
1
1
0
0
4
0
1 000
0
Botswana
0
0
1
0
0
0
0
0
400
Brazil
5
3
5
116
3
26
49 200
600
151 850
British Virgin Islands
0
2
0
0
0
0
0
0
0
Bulgaria
1
2
2
0
0
2
0
5 000
0
Burundi
0
1
3
0
0
0
0
30 810
0
Cambodia
0
1
2
0
25
19
0
0
178 000
Canada
5
9
11
38
38
32
2 400
7 300
500
Cape Verde
2
0
0
32
0
0
7 600
0
0
Cayman Islands
0
0
7
0
0
2
0
0
300
Central African Republic
1
0
3
0
0
6
900
0
9 137
Chad
1
0
1
11
0
14
1 200
0
0
Chile
3
4
2
143
4
47
233 854
2 250
2 112
China
37
73
85
3 231
5 636
3 180
43 969 500
89 590 928
279 159 647
China, Hong Kong SAR
12
11
6
45
34
6
1 537
1 304
3 800
China, Macao SAR
0
4
0
0
0
0
0
1 200
0
Colombia
3
1
2
31
2
5
128 000
0
3 074
Comoros
4
0
1
59
0
0
65 000
0
0
Cook Islands
2
2
2
5
20
0
2 000
700
1 344
Costa Rica
1
4
3
28
62
5
120 000
734 262
56 074
Croatia
0
0
1
0
0
2
0
0
0
Cuba
5
7
14
31
19
40
641 891
862 640
9 721 908
Cyprus
1
0
2
0
0
0
0
0
0
Czech Republic
0
0
6
0
0
10
0
0
0
Dem. Rep. of the Congo
0
0
5
0
0
49
0
0
75 000
Denmark
4
4
3
11
8
5
0
0
0
Djibouti
0
1
0
0
0
0
0
775
0
Dominica
3
3
2
2
2
5
10 710
400
7 675
Dominican Republic
4
4
12
22
382
211
2 000
880 300
185 183
Egypt
1
1
1
30
18
13
0
0
0
El Salvador
0
3
6
0
491
345
0
84 000
150 541
Eritrea
0
1
0
0
3
0
0
0
0
Estonia
0
0
1
0
0
0
0
0
100
Fiji
9
5
8
61
59
44
372 201
158 500
39 082
Finland
0
2
0
0
0
0
0
0
0
France
10
18
17
40
229
68
0
3 509 390
4 150
French Polynesia
2
0
0
7
0
0
5 000
0
0
Gabon
0
0
1
0
0
0
0
0
0
Gambia
0
0
4
0
0
5
0
0
16 675
Georgia
0
0
1
0
0
0
0
0
900
Germany
0
17
16
0
107
85
0
30 000
0
Greece
1
1
4
48
3
5
0
0
600
Grenada
1
2
2
0
0
40
0
1 210
61 650
Guadeloupe
1
4
1
5
4
0
0
400
0
Guam
1
2
4
0
1
5
0
1 400
10 544
Guatemala
0
2
5
0
384
1 540
0
105 700
486 768
Guinea
0
0
1
0
0
4
0
0
0
Guinea-Bissau
1
1
0
1
0
0
0
1 722
0
Haiti
2
5
18
274
1 378
3 663
1 200 000
1 512 000
706 756
Honduras
2
4
7
130
14 619
75
20 000
2 100 000
184 420
Hungary
1
1
3
4
40
16
0
0
0
India
32
26
29
3 909
18 091
976
17 192 700
31 578 296
5 475 905
Indonesia
3
0
2
2
0
4
10 000
0
3 715
Iran (Islamic Republic of)
1
4
5
200
31
43
0
3 700
170 500
Ireland
2
8
4
21
14
1
0
0
200
Israel
0
1
1
0
5
3
0
0
410
Italy
3
4
3
33
39
4
0
1 000
0
Jamaica
3
2
12
62
4
45
840 000
0
398 016
Japan
18
25
34
652
351
534
175 000
409 855
966 641
Jordan
0
1
2
0
2
14
0
0
0
Kazakhstan
0
1
0
0
112
0
0
0
0
Kenya
1
0
0
50
0
0
0
0
0
Korea, Dem. People's Rep.
0
2
3
0
6
49
0
2 500
487 401
Korea, Republic of
10
11
15
1 164
336
423
177 021
25 640
154 725
Kyrgyzstan
0
0
1
0
0
4
0
0
9 075
Lao People's Dem. Rep.
0
4
1
0
56
16
0
307 090
128 796
Latvia
0
1
2
0
6
0
0
0
0
Lebanon
0
1
1
0
25
0
0
100 000
500
Lesotho
1
2
3
0
0
1
0
230
5 500
Liberia
0
1
1
0
0
0
0
0
0
Lithuania
0
2
1
0
8
0
0
780 000
0
Luxembourg
0
7
0
0
0
0
0
0
0
Madagascar
6
7
22
454
431
958
370 791
1 245 000
3 193 291
Malawi
0
0
1
0
0
11
0
0
0
Malaysia
0
2
4
0
272
3
0
3 265
41 655
Maldives
0
1
0
0
0
0
0
0
0
Marshall Islands
0
1
0
0
0
0
0
0
0
Martinique
2
5
1
0
10
1
0
1 900
0
Mauritania
0
2
0
0
5
0
0
0
0
Mauritius
6
4
2
2
5
5
36 850
6 800
0
Mexico
8
25
27
892
784
164
410 000
857 615
4 279 471
Micronesia, Federated States of
1
0
4
5
0
48
0
0
7 300
Mongolia
0
3
6
0
49
94
0
100 000
1 911 000
Montserrat
1
2
0
11
0
0
0
0
0
Morocco
0
1
1
0
14
1
0
0
0
Mozambique
3
3
9
209
251
65
354 000
2 200 000
351 650
Myanmar
1
1
3
11
17
138 636
36 000
64 970
2 460 075
Nepal
4
2
0
71
26
0
0
165
0
Netherlands
3
10
4
0
23
11
0
250 060
0
Netherlands Antilles
1
1
0
11
2
0
0
40 000
0
New Caledonia
4
1
1
6
0
2
2 000
0
0
New Zealand
1
4
4
6
4
2
0
2 140
400
Nicaragua
2
5
10
201
3 451
228
352 000
1 016 809
269 379
Niger
0
0
1
0
0
4
0
0
1 250
Nigeria
0
1
1
0
100
0
0
0
0
Niue
0
1
1
0
0
1
0
200
200
Northern Mariana Islands
0
0
1
0
0
0
0
0
0
Norway
0
4
2
0
0
0
0
0
0
Oman
1
0
3
26
0
113
0
0
20 050
Pakistan
4
8
5
121
956
369
0
315 040
1 650 000
Panama
1
2
0
30
15
0
6 732
7 500
0
Papua New Guinea
0
2
1
0
47
172
0
25 000
162 140
Paraguay
0
1
3
0
33
0
0
0
48 355
Peru
0
1
1
0
518
59
0
580 000
86 682
Philippines
58
56
81
7 203
9 717
7 258
18 634 506
25 007 817
45 118 831
Poland
1
3
8
0
4
38
900
0
1 050
Portugal
1
1
1
0
29
4
0
0
0
Puerto Rico
2
5
4
0
20
3
2 000
155 315
3 500
Republic of Moldova
0
1
1
0
3
0
0
0
2 600 000
Réunion
4
1
3
45
14
4
17 200
0
0
Romania
0
3
6
0
15
29
0
0
2 490
Russian Federation
0
7
12
0
177
34
0
1 412
18 000
Saint Helena
0
0
1
0
0
0
0
0
300
Saint Kitts and Nevis
2
4
0
1
5
0
0
12 880
0
Saint Lucia
6
2
2
72
4
1
73 000
600
0
Samoa
2
2
2
0
21
10
1 000
255 000
0
Saudi Arabia
1
0
0
0
0
0
0
0
0
Senegal
0
2
1
0
187
2
0
65 853
0
Seychelles
0
0
1
0
0
0
0
0
6 800
Sierra Leone
1
1
0
60
13
0
0
0
0
Slovakia
0
0
1
0
0
2
0
0
10 300
Slovenia
0
0
2
0
0
6
0
0
0
Solomon Islands
3
2
3
101
4
0
120 650
88 500
275
Somalia
0
1
0
0
30
0
0
0
0
South Africa
3
6
11
74
55
62
500 000
13 000
101 150
Spain
5
6
5
42
48
39
60 000
350
0
Sri Lanka
1
0
2
0
0
14
8 000
0
425 000
St. Vincent and the Grenadines
2
1
2
0
0
4
20 000
100
1 000
Sudan
0
0
1
0
0
33
0
0
0
Swaziland
1
0
2
53
0
1
632 000
0
7 425
Sweden
0
3
2
0
3
8
0
0
0
Switzerland
8
10
6
1
19
2
140
0
0
Syrian Arab Republic
0
0
2
0
0
32
0
0
0
Tajikistan
0
1
1
0
0
0
0
0
830
Thailand
3
15
11
513
337
27
197 000
2 840 379
85 869
The Former Yugoslav Rep. of Macedonia
0
0
1
0
0
1
0
0
0
Timor-Leste
0
0
1
0
0
0
0
0
8 730
Tokelau
1
1
1
0
0
0
1 700
0
0
Tonga
2
4
2
7
1
0
100 000
6 171
16 500
Trinidad and Tobago
0
2
2
0
0
1
0
1 000
560
Turkey
0
2
5
0
31
39
0
0
1 500
Turks and Caicos Islands
1
1
4
0
0
4
770
0
1 700
Tuvalu
2
2
0
0
0
0
0
300
0
Uganda
0
0
3
0
0
0
0
0
0
Ukraine
0
2
5
0
11
10
0
1 000
53 668
United Kingdom
6
15
9
72
191
55
0
465 200
23 280
United Rep. of Tanzania
0
1
3
0
4
0
0
0
1 275
United States
88
166
129
2 444
1 847
3 288
1 053 200
3 374 036
8 598 206
United States Virgin Islands
1
4
1
0
10
0
2 000
0
0
Uruguay
0
3
3
0
2
9
0
2 000
1 300
Vanuatu
6
5
3
57
38
4
168 600
8 550
54 505
Venezuela (Bolivarian Republic of)
1
1
1
11
100
5
0
0
1 645
Viet Nam
17
25
33
3 739
5 541
1 319
27 782 216
4 503 483
7 644 412
Wallis and Futuna Islands
1
0
0
1
0
0
4 500
0
0
Yemen
0
0
2
0
0
30
0
0
0
Zimbabwe
0
0
2
0
0
8
0
0
0
 
Sources:
EM-DAT: The OFDA/CRED International Disaster Database – www.emdat.be– Université catholique de Louvain – Brussels – Belgium.
 
Definitions & Technical notes:
 
Meteorological disasters are defined as events caused by short-lived/small to meso scale atmospheric processes (lasting minutes to days). Such events are classified as: Tropical Storms and Extra-tropical Cyclones (winter storms).
Only disasters that fulfil at least one of the below criteria are included in EM-DAT:
- 10 or more people reported killed
- 100 or more people reported affected
- Declaration of a state of emergency
- Call for international assistance
Fatalities are the number of Killed according to the EM-DAT definitions. Killed is defined as persons confirmed as dead and persons missing and presumed dead (official figures when available).
Persons affected are the number of Total affected according to the EM-DAT definitions. Total affected is the sum of injured, homeless, and affected. Injured is defined as people suffering from physical injuries, trauma or an illness requiring medical treatment as a direct result of a disaster. Homeless is defined as people needing immediate assistance for shelter. Affected is defined as people requiring immediate assistance during a period of emergency; it can also include displaced or evacuated people.
A “0” in EM-DAT does not represent a value and can mean either there were no reported events or no information is available.
 
Data Quality:
 
The EM-DAT database is compiled from various sources, including UN agencies, non-governmental organizations, insurance companies, research institutes and press agencies. Priority is given to data from UN agencies, governments and the International Federation of Red Cross and Red Crescent Societies. The entries are constantly reviewed for redundancy, inconsistencies and incompleteness. CRED consolidates and updates data on a daily basis. A further check is made at monthly intervals. Revisions are made annually at the end of each calendar year.
For more information see: http://www.emdat.be.
 
United Nations Statistics Division - Environment Statistics