Categories in Wasselonne
Industries
Business Distribution by Industry in Wasselonne
| Industry Description | Number of Establishments | Average Age of Business |
|---|---|---|
| Health and medical | 26 | — |
| Corporate management | 22 | 18 years |
| Shopping | 19 | — |
| Restaurants | 17 | 18 years |
| Beauty salons | 16 | — |
| Shopping other | 16 | 31 years |
| Real estate | 15 | — |
| Car repair | 13 | 17 years |
| Hairdressers | 12 | — |
| Alternative medicine | 12 | — |
| Other construction | 11 | — |
| Banks | 10 | — |
| Public administration | 10 | — |
| Wholesale of machinery | 10 | 42 years |
| All food and beverage | 9 | — |
| Nurses | 9 | — |
Wasselonne Facts
| Area | 14.9 km² |
| Population | 5,297 |
| Male Population | 2,593 (49.0%) |
| Female Population | 2,704 (51.0%) |
| Population change (1975 to 2020) | -5.5% |
| Population change (2000 to 2020) | -6.1% |
| Median Age | 40 years (Male: 38.6, Female: 41.4) |
| GDP per capita (PPP) | $45,186 (2022) |
| Neighborhoods | Poincaré, Robertsau |
| Local Time | |
| Timezone | Central European Summer Time |
| Lat & Lng | 48.63723, 7.44731 |
| Postal Codes | 67318 CEDEX, 67319 CEDEX |
Map of Wasselonne
Interactive Map
Wasselonne Population
Years 1975 to 2030
| Data | 1975 | 1990 | 2000 | 2015 | 2020 | 2025* | 2030* |
|---|---|---|---|---|---|---|---|
| Population | 5,608 | 5,684 | 5,644 | 5,555 | 5,297 | 5,060 | 4,803 |
| Population Density | 377 / km² | 382.1 / km² | 379.4 / km² | 373.4 / km² | 356.1 / km² | 340.2 / km² | 322.9 / km² |
Wasselonne Population change from 2000 to 2020
Decrease of 6.1% from year 2000 to 2020
| Location | Change since 1975 | Change since 1990 | Change since 2000 |
|---|---|---|---|
| Wasselonne | -5.5% | -6.8% | -6.1% |
| France | — | — | — |
Wasselonne Median Age
Median Age: 40 years
| Location | Median Age | Median Age (Female) | Median Age (Male) |
|---|---|---|---|
| Wasselonne | 40 yrs | 41.4 yrs | 38.6 yrs |
| France | 39.6 yrs | 41 yrs | 38.1 yrs |
Wasselonne Population Density
Population Density: 356 / km²
| Location | Population | Area | Density |
|---|---|---|---|
| Wasselonne | 5,297 | 14.9 km² | 356 / km² |
| France | 65.9 million | 638,022.5 km² | 103 / km² |
Wasselonne Historical and Projected Population
Estimated Population from 0 to 2100
- JRC (European Commission's Joint Research Centre) work on the GHS built-up grid
- CIESIN (Center for International Earth Science Information Network)
- [Link] Klein Goldewijk, K., Beusen, A., Doelman, J., and Stehfest, E.: Anthropogenic land use estimates for the Holocene – HYDE 3.2, Earth Syst. Sci. Data, 9, 927–953, https://doi.org/10.5194/essd-9-927-2017, 2017.
Area Codes
Percentage Area Codes used by businesses in Wasselonne
Price Distribution
Business distribution by price for Wasselonne
Human Development Index (HDI)
Statistic composite index of life expectancy, education, and per capita income.
Wasselonne Gross Domestic Product (GDP)
GDP per capita, PPP (constant 2017 international $)
| Data | 1990 | 1995 | 2000 | 2005 | 2010 | 2015 | 2020 | 2022 |
|---|---|---|---|---|---|---|---|---|
| GDP per capita | $35,290 | $36,693 | $41,443 | $41,244 | $42,293 | $42,817 | $41,713 | $45,186 |
| Total GDP | $447.3M | $464.3M | $526.5M | $534.1M | $558.4M | $564.5M | $549.6M | $589.7M |
Wasselonne CO2 Emissions
Carbon Dioxide (CO2) Emissions Per Capita in Tonnes Per Year
| Location | CO2 Emissions | CO2 Emissions Per Capita | CO2 Emissions Intensity |
|---|---|---|---|
| Wasselonne | 43,431 tn | 8.2 tn | 2,919.7 tons/km² |
| France | 485,797,691 tn | 7.38 tn | 761.4 tons/km² |
| 2013 CO2 emissions (tonnes/year) | 43,431 tn |
| 2013 CO2 emissions (tonnes/year) per capita | 8.2 tn |
| 2013 CO2 emissions intensity (tonnes/km²/year) | 2,919.7 tons/km² |
Natural Hazards Risk
Relative risk out of 10
| Hazard | Risk Level |
|---|---|
| Flood | Medium (7) |
| Earthquake | Low (2) |
* Risk, particularly concerning flood or landslide, may not be for the entire area.
- Dilley, M., R.S. Chen, U. Deichmann, A.L. Lerner-Lam, M. Arnold, J. Agwe, P. Buys, O. Kjekstad, B. Lyon, and G. Yetman. 2005. Natural Disaster Hotspots: A Global Risk Analysis. Washington, D.C.: World Bank. https://doi.org/10.1596/0-8213-5930-4.
- Center for Hazards and Risk Research - CHRR - Columbia University, Center for International Earth Science Information Network - CIESIN - Columbia University. 2005. Global Flood Hazard Frequency and Distribution. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/H4668B3D.
- Center for Hazards and Risk Research - CHRR - Columbia University, Center for International Earth Science Information Network - CIESIN - Columbia University. 2005. Global Earthquake Hazard Distribution - Peak Ground Acceleration. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/H4BZ63ZS.
Recent Nearby Earthquakes
Magnitude 3.0 and greater
| Date▼ | Time↕ | Magnitude↕ | Distance↕ | Depth↕ | Location↕ | Link |
|---|---|---|---|---|---|---|
| 2/16/08 | 9:48 AM | 3.2 | 61.1 km | 10,000 m | Germany | usgs.gov |
| 7/19/06 | 6:38 PM | 3.1 | 72.8 km | 1,000 m | Germany | usgs.gov |
| 7/13/06 | 1:05 PM | 3.2 | 72.7 km | 1,000 m | Germany | usgs.gov |
| 11/13/05 | 10:42 AM | 3 | 38.6 km | 9,000 m | France | usgs.gov |
| 11/3/05 | 1:11 PM | 3.2 | 39.8 km | 10,000 m | France | usgs.gov |
| 11/3/05 | 9:37 AM | 3 | 37.5 km | 5,000 m | France | usgs.gov |
| 11/3/05 | 12:18 AM | 3.8 | 38.6 km | 5,000 m | France | usgs.gov |
| 10/11/05 | 1:18 AM | 3.1 | 66.5 km | 12,000 m | France | usgs.gov |
| 3/14/05 | 12:34 PM | 3.8 | 66.7 km | 5,000 m | France | usgs.gov |
| 12/5/04 | 2:51 AM | 3.2 | 75.5 km | 10,000 m | Germany | usgs.gov |
Wasselonne
Wasselonne (German: Wasselnheim) is a commune in the Bas-Rhin department in Alsace-Champagne-Ardenne-Lorraine in north-eastern France. It is in this city that we can see the oldest firm of unleavened bread in France: Etablissements René Neymann.
Wasselonne Wikipedia PageAbout Our Data
The data on this page is estimated using a number of publicly available tools and resources. It is provided without warranty, and could contain inaccuracies. Use at your own risk.

