04095 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | 04095 Zip Code | Maine | U.S. |
| Total Housing Units | 585, 100% | 553,086 | 116,211,092 |
| Utility Gas | 0, 0.00%, see rank | 5.45% | 48.85% |
| Bottled, Tank, or LP Gas | 111, 18.97%, see rank | 7.75% | 4.86% |
| Electricity | 18, 3.08%, see rank | 4.79% | 36.68% |
| Fuel Oil, Kerosene, etc. | 285, 48.72%, see rank | 66.66% | 5.86% |
| Coal or Coke | 0, 0.00%, see rank | 0.35% | 0.12% |
| Wood | 162, 27.69%, see rank | 13.20% | 2.12% |
| Solar Energy | 0, 0.00%, see rank | 0.08% | 0.05% |
| Other Fuel | 9, 1.54%, see rank | 1.48% | 0.47% |
| No Fuel Used | 0, 0.00%, see rank | 0.24% | 1.00% |
ACS 2008-2012 data
| | 04095 Zip Code | Maine | U.S. |
| Total Housing Units | 503, 100% | 553,208 | 115,226,802 |
| Utility Gas | 0, 0.00%, see rank | 4.60% | 49.42% |
| Bottled, Tank, or LP Gas | 95, 18.89%, see rank | 6.93% | 5.03% |
| Electricity | 12, 2.39%, see rank | 4.62% | 35.51% |
| Fuel Oil, Kerosene, etc. | 276, 54.87%, see rank | 70.45% | 6.46% |
| Coal or Coke | 0, 0.00%, see rank | 0.29% | 0.12% |
| Wood | 114, 22.66%, see rank | 11.78% | 2.08% |
| Solar Energy | 0, 0.00%, see rank | 0.07% | 0.04% |
| Other Fuel | 6, 1.19%, see rank | 1.02% | 0.43% |
| No Fuel Used | 0, 0.00%, see rank | 0.23% | 0.90% |
US Census 2000 data
| | 04095 Zip Code | Maine | U.S. |
| Total Housing Units | 496, 100% | 518,200 | 105,480,101 |
| Utility Gas | 2, 0.40%, see rank | 3.46% | 51.22% |
| Bottled, Tank, or LP Gas | 55, 11.09%, see rank | 4.88% | 6.52% |
| Electricity | 6, 1.21%, see rank | 4.44% | 30.35% |
| Fuel Oil, Kerosene, etc. | 348, 70.16%, see rank | 80.17% | 8.97% |
| Coal or Coke | 0, 0.00%, see rank | 0.15% | 0.14% |
| Wood | 80, 16.13%, see rank | 6.44% | 1.68% |
| Solar Energy | 5, 1.01%, see rank | 0.03% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.31% | 0.39% |
| No Fuel Used | 0, 0.00%, see rank | 0.12% | 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.
