20772 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 20772 Zip Code | Maryland | U.S. |
Total Housing Units | 15,779, 100% | 2,155,983 | 116,211,092 |
Utility Gas | 7,354, 46.61%, see rank | 44.54% | 48.85% |
Bottled, Tank, or LP Gas | 337, 2.14%, see rank | 3.17% | 4.86% |
Electricity | 6,836, 43.32%, see rank | 39.67% | 36.68% |
Fuel Oil, Kerosene, etc. | 952, 6.03%, see rank | 10.31% | 5.86% |
Coal or Coke | 59, 0.37%, see rank | 0.11% | 0.12% |
Wood | 171, 1.08%, see rank | 1.37% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 52, 0.33%, see rank | 0.45% | 0.47% |
No Fuel Used | 18, 0.11%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| 20772 Zip Code | Maryland | U.S. |
Total Housing Units | 15,671, 100% | 2,138,806 | 115,226,802 |
Utility Gas | 7,623, 48.64%, see rank | 44.82% | 49.42% |
Bottled, Tank, or LP Gas | 389, 2.48%, see rank | 3.21% | 5.03% |
Electricity | 6,363, 40.60%, see rank | 38.74% | 35.51% |
Fuel Oil, Kerosene, etc. | 1,030, 6.57%, see rank | 11.18% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.11% | 0.12% |
Wood | 190, 1.21%, see rank | 1.27% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 65, 0.41%, see rank | 0.43% | 0.43% |
No Fuel Used | 11, 0.07%, see rank | 0.23% | 0.90% |
US Census 2000 data
| 20772 Zip Code | Maryland | U.S. |
Total Housing Units | 12,463, 100% | 1,980,859 | 105,480,101 |
Utility Gas | 5,326, 42.73%, see rank | 46.03% | 51.22% |
Bottled, Tank, or LP Gas | 188, 1.51%, see rank | 3.09% | 6.52% |
Electricity | 5,528, 44.36%, see rank | 33.09% | 30.35% |
Fuel Oil, Kerosene, etc. | 1,291, 10.36%, see rank | 15.99% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.13% | 0.14% |
Wood | 80, 0.64%, see rank | 1.00% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 30, 0.24%, see rank | 0.37% | 0.39% |
No Fuel Used | 20, 0.16%, 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.