21790 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | 21790 Zip Code | Maryland | U.S. |
| Total Housing Units | 36, 100% | 2,155,983 | 116,211,092 |
| Utility Gas | 0, 0.00%, see rank | 44.54% | 48.85% |
| Bottled, Tank, or LP Gas | 6, 16.67%, see rank | 3.17% | 4.86% |
| Electricity | 30, 83.33%, see rank | 39.67% | 36.68% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 10.31% | 5.86% |
| Coal or Coke | 0, 0.00%, see rank | 0.11% | 0.12% |
| Wood | 0, 0.00%, see rank | 1.37% | 2.12% |
| Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
| Other Fuel | 0, 0.00%, see rank | 0.45% | 0.47% |
| No Fuel Used | 0, 0.00%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| | 21790 Zip Code | Maryland | U.S. |
| Total Housing Units | 25, 100% | 2,138,806 | 115,226,802 |
| Utility Gas | 0, 0.00%, see rank | 44.82% | 49.42% |
| Bottled, Tank, or LP Gas | 7, 28.00%, see rank | 3.21% | 5.03% |
| Electricity | 18, 72.00%, see rank | 38.74% | 35.51% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 11.18% | 6.46% |
| Coal or Coke | 0, 0.00%, see rank | 0.11% | 0.12% |
| Wood | 0, 0.00%, see rank | 1.27% | 2.08% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.43% | 0.43% |
| No Fuel Used | 0, 0.00%, see rank | 0.23% | 0.90% |
US Census 2000 data
| | 21790 Zip Code | Maryland | U.S. |
| Total Housing Units | 32, 100% | 1,980,859 | 105,480,101 |
| Utility Gas | 0, 0.00%, see rank | 46.03% | 51.22% |
| Bottled, Tank, or LP Gas | 0, 0.00%, see rank | 3.09% | 6.52% |
| Electricity | 17, 53.13%, see rank | 33.09% | 30.35% |
| Fuel Oil, Kerosene, etc. | 15, 46.88%, see rank | 15.99% | 8.97% |
| Coal or Coke | 0, 0.00%, see rank | 0.13% | 0.14% |
| Wood | 0, 0.00%, see rank | 1.00% | 1.68% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.37% | 0.39% |
| No Fuel Used | 0, 0.00%, see rank | 0.28% | 0.69% |
* ACS stands for U.S. Census American Community Survey. According to the U.S. Census, if the date is a range, you can interpret the data as an average of the period of time.
