98105 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 98105 Zip Code | Washington | U.S. |
Total Housing Units | 15,190, 100% | 2,645,396 | 116,211,092 |
Utility Gas | 5,876, 38.68%, see rank | 35.08% | 48.85% |
Bottled, Tank, or LP Gas | 54, 0.36%, see rank | 3.08% | 4.86% |
Electricity | 7,890, 51.94%, see rank | 53.93% | 36.68% |
Fuel Oil, Kerosene, etc. | 918, 6.04%, see rank | 2.50% | 5.86% |
Coal or Coke | 12, 0.08%, see rank | 0.01% | 0.12% |
Wood | 29, 0.19%, see rank | 4.39% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 102, 0.67%, see rank | 0.63% | 0.47% |
No Fuel Used | 309, 2.03%, see rank | 0.36% | 1.00% |
ACS 2008-2012 data
| 98105 Zip Code | Washington | U.S. |
Total Housing Units | 15,604, 100% | 2,619,995 | 115,226,802 |
Utility Gas | 5,907, 37.86%, see rank | 35.49% | 49.42% |
Bottled, Tank, or LP Gas | 81, 0.52%, see rank | 3.25% | 5.03% |
Electricity | 7,981, 51.15%, see rank | 52.97% | 35.51% |
Fuel Oil, Kerosene, etc. | 1,252, 8.02%, see rank | 2.89% | 6.46% |
Coal or Coke | 16, 0.10%, see rank | 0.02% | 0.12% |
Wood | 47, 0.30%, see rank | 4.46% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.04% |
Other Fuel | 146, 0.94%, see rank | 0.63% | 0.43% |
No Fuel Used | 174, 1.12%, see rank | 0.25% | 0.90% |
US Census 2000 data
| 98105 Zip Code | Washington | U.S. |
Total Housing Units | 14,747, 100% | 2,271,398 | 105,480,101 |
Utility Gas | 5,013, 33.99%, see rank | 32.88% | 51.22% |
Bottled, Tank, or LP Gas | 144, 0.98%, see rank | 3.06% | 6.52% |
Electricity | 7,682, 52.09%, see rank | 52.93% | 30.35% |
Fuel Oil, Kerosene, etc. | 1,684, 11.42%, see rank | 5.58% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.02% | 0.14% |
Wood | 33, 0.22%, see rank | 4.71% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 121, 0.82%, see rank | 0.61% | 0.39% |
No Fuel Used | 70, 0.47%, see rank | 0.19% | 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.