21401 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 21401 Zip Code | Maryland | U.S. |
Total Housing Units | 16,259, 100% | 2,155,983 | 116,211,092 |
Utility Gas | 6,342, 39.01%, see rank | 44.54% | 48.85% |
Bottled, Tank, or LP Gas | 298, 1.83%, see rank | 3.17% | 4.86% |
Electricity | 8,049, 49.50%, see rank | 39.67% | 36.68% |
Fuel Oil, Kerosene, etc. | 1,352, 8.32%, see rank | 10.31% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.11% | 0.12% |
Wood | 136, 0.84%, see rank | 1.37% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 49, 0.30%, see rank | 0.45% | 0.47% |
No Fuel Used | 33, 0.20%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| 21401 Zip Code | Maryland | U.S. |
Total Housing Units | 16,286, 100% | 2,138,806 | 115,226,802 |
Utility Gas | 6,359, 39.05%, see rank | 44.82% | 49.42% |
Bottled, Tank, or LP Gas | 174, 1.07%, see rank | 3.21% | 5.03% |
Electricity | 8,172, 50.18%, see rank | 38.74% | 35.51% |
Fuel Oil, Kerosene, etc. | 1,373, 8.43%, see rank | 11.18% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.11% | 0.12% |
Wood | 134, 0.82%, see rank | 1.27% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 44, 0.27%, see rank | 0.43% | 0.43% |
No Fuel Used | 30, 0.18%, see rank | 0.23% | 0.90% |
US Census 2000 data
| 21401 Zip Code | Maryland | U.S. |
Total Housing Units | 20,404, 100% | 1,980,859 | 105,480,101 |
Utility Gas | 6,057, 29.69%, see rank | 46.03% | 51.22% |
Bottled, Tank, or LP Gas | 308, 1.51%, see rank | 3.09% | 6.52% |
Electricity | 9,690, 47.49%, see rank | 33.09% | 30.35% |
Fuel Oil, Kerosene, etc. | 4,143, 20.30%, see rank | 15.99% | 8.97% |
Coal or Coke | 16, 0.08%, see rank | 0.13% | 0.14% |
Wood | 111, 0.54%, see rank | 1.00% | 1.68% |
Solar Energy | 6, 0.03%, see rank | 0.02% | 0.04% |
Other Fuel | 42, 0.21%, see rank | 0.37% | 0.39% |
No Fuel Used | 31, 0.15%, 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.