21532 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 21532 Zip Code | Maryland | U.S. |
Total Housing Units | 5,918, 100% | 2,155,983 | 116,211,092 |
Utility Gas | 2,094, 35.38%, see rank | 44.54% | 48.85% |
Bottled, Tank, or LP Gas | 233, 3.94%, see rank | 3.17% | 4.86% |
Electricity | 2,007, 33.91%, see rank | 39.67% | 36.68% |
Fuel Oil, Kerosene, etc. | 865, 14.62%, see rank | 10.31% | 5.86% |
Coal or Coke | 298, 5.04%, see rank | 0.11% | 0.12% |
Wood | 354, 5.98%, see rank | 1.37% | 2.12% |
Solar Energy | 9, 0.15%, see rank | 0.03% | 0.05% |
Other Fuel | 9, 0.15%, see rank | 0.45% | 0.47% |
No Fuel Used | 49, 0.83%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| 21532 Zip Code | Maryland | U.S. |
Total Housing Units | 6,223, 100% | 2,138,806 | 115,226,802 |
Utility Gas | 2,367, 38.04%, see rank | 44.82% | 49.42% |
Bottled, Tank, or LP Gas | 154, 2.47%, see rank | 3.21% | 5.03% |
Electricity | 1,974, 31.72%, see rank | 38.74% | 35.51% |
Fuel Oil, Kerosene, etc. | 1,064, 17.10%, see rank | 11.18% | 6.46% |
Coal or Coke | 309, 4.97%, see rank | 0.11% | 0.12% |
Wood | 287, 4.61%, see rank | 1.27% | 2.08% |
Solar Energy | 9, 0.14%, see rank | 0.02% | 0.04% |
Other Fuel | 32, 0.51%, see rank | 0.43% | 0.43% |
No Fuel Used | 27, 0.43%, see rank | 0.23% | 0.90% |
US Census 2000 data
| 21532 Zip Code | Maryland | U.S. |
Total Housing Units | 5,452, 100% | 1,980,859 | 105,480,101 |
Utility Gas | 2,288, 41.97%, see rank | 46.03% | 51.22% |
Bottled, Tank, or LP Gas | 117, 2.15%, see rank | 3.09% | 6.52% |
Electricity | 1,319, 24.19%, see rank | 33.09% | 30.35% |
Fuel Oil, Kerosene, etc. | 1,053, 19.31%, see rank | 15.99% | 8.97% |
Coal or Coke | 432, 7.92%, see rank | 0.13% | 0.14% |
Wood | 222, 4.07%, see rank | 1.00% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 21, 0.39%, 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.