03833 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 03833 Zip Code | New Hampshire | U.S. |
Total Housing Units | 8,408, 100% | 519,580 | 116,211,092 |
Utility Gas | 2,146, 25.52%, see rank | 19.69% | 48.85% |
Bottled, Tank, or LP Gas | 875, 10.41%, see rank | 14.22% | 4.86% |
Electricity | 783, 9.31%, see rank | 8.15% | 36.68% |
Fuel Oil, Kerosene, etc. | 4,230, 50.31%, see rank | 47.16% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.17% | 0.12% |
Wood | 286, 3.40%, see rank | 8.26% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.06% | 0.05% |
Other Fuel | 77, 0.92%, see rank | 1.51% | 0.47% |
No Fuel Used | 11, 0.13%, see rank | 0.79% | 1.00% |
ACS 2008-2012 data
| 03833 Zip Code | New Hampshire | U.S. |
Total Housing Units | 8,159, 100% | 516,845 | 115,226,802 |
Utility Gas | 2,177, 26.68%, see rank | 19.72% | 49.42% |
Bottled, Tank, or LP Gas | 876, 10.74%, see rank | 13.45% | 5.03% |
Electricity | 620, 7.60%, see rank | 7.72% | 35.51% |
Fuel Oil, Kerosene, etc. | 4,046, 49.59%, see rank | 49.88% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.13% | 0.12% |
Wood | 296, 3.63%, see rank | 7.19% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.05% | 0.04% |
Other Fuel | 135, 1.65%, see rank | 1.20% | 0.43% |
No Fuel Used | 9, 0.11%, see rank | 0.66% | 0.90% |
US Census 2000 data
| 03833 Zip Code | New Hampshire | U.S. |
Total Housing Units | 7,462, 100% | 474,606 | 105,480,101 |
Utility Gas | 1,741, 23.33%, see rank | 18.39% | 51.22% |
Bottled, Tank, or LP Gas | 538, 7.21%, see rank | 10.71% | 6.52% |
Electricity | 582, 7.80%, see rank | 7.63% | 30.35% |
Fuel Oil, Kerosene, etc. | 4,407, 59.06%, see rank | 58.12% | 8.97% |
Coal or Coke | 13, 0.17%, see rank | 0.18% | 0.14% |
Wood | 126, 1.69%, see rank | 4.26% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.04% | 0.04% |
Other Fuel | 34, 0.46%, see rank | 0.48% | 0.39% |
No Fuel Used | 21, 0.28%, 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.