21050 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 21050 Zip Code | Maryland | U.S. |
Total Housing Units | 6,390, 100% | 2,155,983 | 116,211,092 |
Utility Gas | 2,981, 46.65%, see rank | 44.54% | 48.85% |
Bottled, Tank, or LP Gas | 329, 5.15%, see rank | 3.17% | 4.86% |
Electricity | 1,723, 26.96%, see rank | 39.67% | 36.68% |
Fuel Oil, Kerosene, etc. | 1,049, 16.42%, see rank | 10.31% | 5.86% |
Coal or Coke | 18, 0.28%, see rank | 0.11% | 0.12% |
Wood | 153, 2.39%, see rank | 1.37% | 2.12% |
Solar Energy | 14, 0.22%, see rank | 0.03% | 0.05% |
Other Fuel | 108, 1.69%, see rank | 0.45% | 0.47% |
No Fuel Used | 15, 0.23%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| 21050 Zip Code | Maryland | U.S. |
Total Housing Units | 6,311, 100% | 2,138,806 | 115,226,802 |
Utility Gas | 2,949, 46.73%, see rank | 44.82% | 49.42% |
Bottled, Tank, or LP Gas | 355, 5.63%, see rank | 3.21% | 5.03% |
Electricity | 1,701, 26.95%, see rank | 38.74% | 35.51% |
Fuel Oil, Kerosene, etc. | 1,070, 16.95%, see rank | 11.18% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.11% | 0.12% |
Wood | 151, 2.39%, see rank | 1.27% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 74, 1.17%, see rank | 0.43% | 0.43% |
No Fuel Used | 11, 0.17%, see rank | 0.23% | 0.90% |
US Census 2000 data
| 21050 Zip Code | Maryland | U.S. |
Total Housing Units | 5,306, 100% | 1,980,859 | 105,480,101 |
Utility Gas | 2,175, 40.99%, see rank | 46.03% | 51.22% |
Bottled, Tank, or LP Gas | 266, 5.01%, see rank | 3.09% | 6.52% |
Electricity | 1,426, 26.88%, see rank | 33.09% | 30.35% |
Fuel Oil, Kerosene, etc. | 1,291, 24.33%, see rank | 15.99% | 8.97% |
Coal or Coke | 16, 0.30%, see rank | 0.13% | 0.14% |
Wood | 118, 2.22%, see rank | 1.00% | 1.68% |
Solar Energy | 7, 0.13%, see rank | 0.02% | 0.04% |
Other Fuel | 7, 0.13%, 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.