03766 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 03766 Zip Code | New Hampshire | U.S. |
Total Housing Units | 4,232, 100% | 519,580 | 116,211,092 |
Utility Gas | 191, 4.51%, see rank | 19.69% | 48.85% |
Bottled, Tank, or LP Gas | 928, 21.93%, see rank | 14.22% | 4.86% |
Electricity | 527, 12.45%, see rank | 8.15% | 36.68% |
Fuel Oil, Kerosene, etc. | 2,182, 51.56%, see rank | 47.16% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.17% | 0.12% |
Wood | 323, 7.63%, see rank | 8.26% | 2.12% |
Solar Energy | 9, 0.21%, see rank | 0.06% | 0.05% |
Other Fuel | 60, 1.42%, see rank | 1.51% | 0.47% |
No Fuel Used | 12, 0.28%, see rank | 0.79% | 1.00% |
ACS 2008-2012 data
| 03766 Zip Code | New Hampshire | U.S. |
Total Housing Units | 4,175, 100% | 516,845 | 115,226,802 |
Utility Gas | 148, 3.54%, see rank | 19.72% | 49.42% |
Bottled, Tank, or LP Gas | 874, 20.93%, see rank | 13.45% | 5.03% |
Electricity | 357, 8.55%, see rank | 7.72% | 35.51% |
Fuel Oil, Kerosene, etc. | 2,431, 58.23%, see rank | 49.88% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.13% | 0.12% |
Wood | 281, 6.73%, see rank | 7.19% | 2.08% |
Solar Energy | 9, 0.22%, see rank | 0.05% | 0.04% |
Other Fuel | 75, 1.80%, see rank | 1.20% | 0.43% |
No Fuel Used | 0, 0.00%, see rank | 0.66% | 0.90% |
US Census 2000 data
| 03766 Zip Code | New Hampshire | U.S. |
Total Housing Units | 3,743, 100% | 474,606 | 105,480,101 |
Utility Gas | 140, 3.74%, see rank | 18.39% | 51.22% |
Bottled, Tank, or LP Gas | 728, 19.45%, see rank | 10.71% | 6.52% |
Electricity | 426, 11.38%, see rank | 7.63% | 30.35% |
Fuel Oil, Kerosene, etc. | 2,310, 61.72%, see rank | 58.12% | 8.97% |
Coal or Coke | 8, 0.21%, see rank | 0.18% | 0.14% |
Wood | 100, 2.67%, see rank | 4.26% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.04% | 0.04% |
Other Fuel | 31, 0.83%, see rank | 0.48% | 0.39% |
No Fuel Used | 0, 0.00%, 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.