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List of data         Methodology         Legal limit for radiation dose

Major accident in one of the four reactors of Cattenom NPP (4 × 3817 MWth)

Possible impact on the inhabitants of :

Fribourg (299 km) CHE

Maps of Individual committed effective doses received by inhabitants during the passage of the radioactive cloud (inhalation):
1° Each row of the table represents a different meteorological situation.
2° The hyperlink enables access to the related map.
Maps visible with free Google Earth software! Alternatively, after downloading a map file in KML format, go to google.com/earth/, launch Google Earth, click on "project" then on "open"!
Rank, NPP code, date mSv
1        CAT_2017-01-05 291.34
2        CAT_2018-10-01 65.40
3        CAT_2018-12-24 25.78
4        CAT_2018-03-26 24.97
5        CAT_2020-12-08 22.20
6        CAT_2017-04-28 19.69
7        CAT_2018-07-11 19.62
8        CAT_2018-01-26 19.48
9        CAT_2021-04-19 19.36
10        CAT_2021-09-16 18.24
11        CAT_2020-07-13 15.97
12        CAT_2021-11-29 13.33
13        CAT_2020-06-22 13.10
14        CAT_2017-12-18 12.24
15        CAT_2021-02-26 12.22
16        CAT_2018-09-05 12.21
17        CAT_2018-10-29 11.37
18        CAT_2021-11-17 11.31
19        CAT_2018-07-15 11.17
20        CAT_2017-05-31 10.71
21        CAT_2020-04-25 10.46
22        CAT_2018-08-30 10.45
23        CAT_2018-07-06 10.01
24        CAT_2021-04-12 9.01
25        CAT_2021-03-21 8.89
26        CAT_2020-09-09 8.80
27        CAT_2017-01-06 8.47
28        CAT_2021-08-28 8.34
29        CAT_2017-09-01 8.06
30        CAT_2017-07-13 7.69
31        CAT_2017-02-06 7.49
32        CAT_2020-07-22 7.46
33        CAT_2021-01-01 6.77
34        CAT_2017-01-02 6.72
35        CAT_2020-06-07 6.23
36        CAT_2017-08-10 5.97
37        CAT_2020-08-31 5.86
38        CAT_2020-12-25 5.83
39        CAT_2018-09-14 5.78
40        CAT_2017-09-02 5.40
41        CAT_2020-12-01 5.14
42        CAT_2018-08-18 4.89
43        CAT_2018-08-17 4.87
44        CAT_2017-11-13 4.80
45        CAT_2018-07-14 4.03
46        CAT_2018-04-16 3.88
47        CAT_2017-04-18 3.72
48        CAT_2018-08-19 3.51
49        CAT_2018-11-02 3.41
50        CAT_2018-09-04 3.24
51        CAT_2018-06-20 3.14
52        CAT_2018-09-27 3.14
53        CAT_2017-01-08 3.12
54        CAT_2018-07-07 3.11
55        CAT_2018-12-30 2.93
56        CAT_2018-02-16 2.69
57        CAT_2021-11-20 2.64
58        CAT_2018-07-12 2.63
59        CAT_2017-04-01 2.59
60        CAT_2017-06-13 2.43
61        CAT_2018-06-07 2.40
62        CAT_2018-08-21 2.31
63        CAT_2018-09-13 2.28
64        CAT_2018-07-22 2.21
65        CAT_2020-04-23 2.13
66        CAT_2017-03-14 2.10
67        CAT_2020-10-11 2.10
68        CAT_2018-08-16 2.08
69        CAT_2021-02-09 2.05
70        CAT_2018-05-16 2.04
71        CAT_2021-02-06 2.02
72        CAT_2017-06-19 2.01
73        CAT_2021-02-10 2.01
74        CAT_2018-08-04 1.98
75        CAT_2021-08-23 1.95
76        CAT_2018-05-14 1.88
77        CAT_2018-03-17 1.82
78        CAT_2018-08-05 1.81
79        CAT_2020-07-21 1.81
80        CAT_2021-12-14 1.77
81        CAT_2017-06-21 1.76
82        CAT_2017-01-10 1.73
83        CAT_2021-11-21 1.73
84        CAT_2020-05-11 1.72
85        CAT_2018-09-28 1.70
86        CAT_2017-01-07 1.69
87        CAT_2021-06-11 1.58
88        CAT_2020-04-18 1.53
89        CAT_2021-11-25 1.52
90        CAT_2017-11-08 1.51
91        CAT_2017-12-10 1.40
92        CAT_2018-08-20 1.35
93        CAT_2021-07-15 1.31
94        CAT_2017-11-07 1.26
95        CAT_2018-06-19 1.24
96        CAT_2018-07-19 1.16
97        CAT_2020-11-03 1.12
98        CAT_2021-04-04 1.12
99        CAT_2020-09-06 1.11
100        CAT_2021-06-23 1.08
101        CAT_2018-05-09 1.06
102        CAT_2021-03-09 1.05
103        CAT_2020-07-20 1.04
104        CAT_2018-04-09 1.02
105        CAT_2021-11-03 1.02
106        CAT_2018-07-31 1.01
107        CAT_2020-09-15 0.99
108        CAT_2017-06-20 0.98
109        CAT_2021-03-23 0.94
110        CAT_2018-04-15 0.93
111        CAT_2017-12-11 0.90
112        CAT_2020-07-11 0.90
113        CAT_2020-07-23 0.89
114        CAT_2020-04-03 0.87
115        CAT_2021-01-06 0.82
116        CAT_2018-07-13 0.78
117        CAT_2020-04-17 0.74
118        CAT_2017-11-17 0.72
119        CAT_2017-05-06 0.67
120        CAT_2018-06-14 0.67
121        CAT_2020-06-10 0.64
122        CAT_2017-05-24 0.61
123        CAT_2017-09-23 0.60
124        CAT_2021-06-22 0.56
125        CAT_2017-04-23 0.53
126        CAT_2021-11-26 0.52
127        CAT_2017-09-22 0.48
128        CAT_2021-08-29 0.48
129        CAT_2018-06-11 0.43
130        CAT_2020-07-18 0.41
131        CAT_2021-07-21 0.35
132        CAT_2017-03-15 0.33
133        CAT_2018-06-12 0.20
134        CAT_2021-07-12 0.18
135        CAT_2021-10-06 0.15
136        CAT_2020-12-31 0.14
137        CAT_2020-05-10 0.11
138        CAT_2017-01-01 0.00
139        CAT_2017-01-03 0.00
140        CAT_2017-01-04 0.00
141        CAT_2017-01-09 0.00


  See additional explanation after the below links
The first 8 localities are placed according to 8 cardinal points at about 30 km from Cattenom, the following localities are ranked according to the severity of the health impact in decreasing order: Junglinster →N (LUX)         Fisch →NE (DEU)         Mechern →E (DEU)         Ottonville →SE (FRA)         Metz →S (FRA)         Valleroy →SW (FRA)         Ville‑au‑Montois →W (FRA)         Hivange →NW (LUX)         Esch‑sur‑Alzette (LUX)         Luxembourg (LUX)         Differdange (LUX)         Merzig (DEU)         Saarlouis (DEU)         Verdun (FRA)         Saarbrücken (DEU)         Nancy (FRA)         Koblenz (DEU)         Reims (FRA)         Liège (BEL)         Mannheim (DEU)         Maubeuge (FRA)         Namur (BEL)         Mons (BEL)         Strasbourg (FRA)         Charleroi (BEL)         Aachen (DEU)         Laon (FRA)         Troyes (FRA)         Château‑Thierry (FRA)         Maastricht (NLD)         Heidelberg (DEU)         Coulommiers (FRA)         Köln (DEU)         Valenciennes (FRA)         Épinal (FRA)         Soissons (FRA)         Romilly‑sur‑Seine (FRA)         Frankfurt am Main (DEU)         Colmar (FRA)         Provins (FRA)         Brussel (BEL)         Cambrai (FRA)         Saint‑Quentin (FRA)         Heilbronn (DEU)         Besançon (FRA)         Melun (FRA)         Pforzheim (DEU)         Compiègne (FRA)         Creil (FRA)         Stuttgart (DEU)         Lille (FRA)         Auxerre (FRA)         Gent (BEL)         Montdidier (FRA)         Sens (FRA)         Paris (FRA)         Freiburg im Breisgau (DEU)         Kortrijk (BEL)         Eindhoven (NLD)         Dijon (FRA)         Béthune (FRA)         Brugge (BEL)         Düsseldorf (DEU)         Fribourg (CHE)         Antwerpen (BEL)         Amiens (FRA)         Mulhouse (FRA)         Tilburg (NLD)         Dortmund (DEU)         Münster (DEU)         Ulm (DEU)         Beauvais (FRA)         Bielefeld (DEU)         Chartres (FRA)         Villach (AUT)         Oostende (BEL)         Hannover (DEU)         Utrecht (NLD)         Graz (AUT)         Duisburg (DEU)        

Potential impact of the cloud (inhalation) on the following areas: Europe (51 countries)         France         Germany & Austria         Luxembourg         Belgium & Netherlands         Italy         Switzerland         Spain


ADDITIONAL EXPLANATION ON THE TABLE
1° The radioactivity comes from the passage of the cloud in the hours following an accident;
2° The above individual doses do not include soil irradiation or ingestion of contaminated food after the passage of the cloud;
3° These figures are estimates;
4° SEE COMMENTARY ON LOW AND HIGH DOSES.

5° The calculations are not derived using the map in the illustration, but from another map – of the same format as the one for download on our website to study deposition – which explains some discrepancies between the figure and its illustration.
6° The analysis of the 11 situations producing the maximum fallout allows us to establish the highest risk for a given city, i.e., the consequences of weather situations occurring in 1% of the cases.
7° The above data allow for the identification of the meteorological conditions that would have the worst impact on the area in question, as well as those that would keep radioactivity away. In the event of a major accident at the nuclear power plant concerned, a quick comparison of this analysis with the then prevailing meteorological conditions could be very useful to act as decentralized as possible; local authorities could keep these analyses as ready references to better and more rapidly deploy population protection strategies.

See the details of the radioactive release taken into account for this plant (pdf)

Wikimedia map with modifications
Towns in the vicinity of Cattenom


Wikimedia map with modifications
The geographical location of Cattenom


Photo cropped from the work of Stefan Kühn, CC BY-SA 3.0, via Wikimedia Commons
Cattenom, France, pressurized water reactor (PWR), 4 × 3817 megawatts thermal (MWth)


The following maps give a brief overview of different situations and zoom function possibilities when maps are opened with Google Earth. They were generated with NOAA Hysplit software.
Cattenom (3817 MWth): 72h simulation starting on 02-01-2020
Cattenom (3817 MWth): 72h simulation starting on 17-06-2020
Cattenom (3817 MWth): 72h simulation starting on 29-11-2020