21220 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 21220 Zip Code | Maryland | U.S. |
Total Housing Units | 14,937, 100% | 2,155,983 | 116,211,092 |
Utility Gas | 5,353, 35.84%, see rank | 44.54% | 48.85% |
Bottled, Tank, or LP Gas | 398, 2.66%, see rank | 3.17% | 4.86% |
Electricity | 5,636, 37.73%, see rank | 39.67% | 36.68% |
Fuel Oil, Kerosene, etc. | 3,121, 20.89%, see rank | 10.31% | 5.86% |
Coal or Coke | 4, 0.03%, see rank | 0.11% | 0.12% |
Wood | 214, 1.43%, see rank | 1.37% | 2.12% |
Solar Energy | 24, 0.16%, see rank | 0.03% | 0.05% |
Other Fuel | 62, 0.42%, see rank | 0.45% | 0.47% |
No Fuel Used | 125, 0.84%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| 21220 Zip Code | Maryland | U.S. |
Total Housing Units | 14,922, 100% | 2,138,806 | 115,226,802 |
Utility Gas | 5,187, 34.76%, see rank | 44.82% | 49.42% |
Bottled, Tank, or LP Gas | 355, 2.38%, see rank | 3.21% | 5.03% |
Electricity | 5,710, 38.27%, see rank | 38.74% | 35.51% |
Fuel Oil, Kerosene, etc. | 3,319, 22.24%, see rank | 11.18% | 6.46% |
Coal or Coke | 15, 0.10%, see rank | 0.11% | 0.12% |
Wood | 173, 1.16%, see rank | 1.27% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 110, 0.74%, see rank | 0.43% | 0.43% |
No Fuel Used | 53, 0.36%, see rank | 0.23% | 0.90% |
US Census 2000 data
| 21220 Zip Code | Maryland | U.S. |
Total Housing Units | 14,142, 100% | 1,980,859 | 105,480,101 |
Utility Gas | 6,007, 42.48%, see rank | 46.03% | 51.22% |
Bottled, Tank, or LP Gas | 450, 3.18%, see rank | 3.09% | 6.52% |
Electricity | 4,063, 28.73%, see rank | 33.09% | 30.35% |
Fuel Oil, Kerosene, etc. | 3,403, 24.06%, see rank | 15.99% | 8.97% |
Coal or Coke | 5, 0.04%, see rank | 0.13% | 0.14% |
Wood | 100, 0.71%, see rank | 1.00% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 53, 0.37%, see rank | 0.37% | 0.39% |
No Fuel Used | 61, 0.43%, 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.