96752 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | 96752 Zip Code | Hawaii | U.S. |
| Total Housing Units | 966, 100% | 450,299 | 116,211,092 |
| Utility Gas | 40, 4.14%, see rank | 2.05% | 48.85% |
| Bottled, Tank, or LP Gas | 17, 1.76%, see rank | 1.15% | 4.86% |
| Electricity | 84, 8.70%, see rank | 30.97% | 36.68% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 0.02% | 5.86% |
| Coal or Coke | 0, 0.00%, see rank | 0.00% | 0.12% |
| Wood | 0, 0.00%, see rank | 0.36% | 2.12% |
| Solar Energy | 15, 1.55%, see rank | 1.97% | 0.05% |
| Other Fuel | 0, 0.00%, see rank | 0.09% | 0.47% |
| No Fuel Used | 810, 83.85%, see rank | 63.39% | 1.00% |
ACS 2008-2012 data
| | 96752 Zip Code | Hawaii | U.S. |
| Total Housing Units | 1,063, 100% | 447,453 | 115,226,802 |
| Utility Gas | 37, 3.48%, see rank | 2.06% | 49.42% |
| Bottled, Tank, or LP Gas | 24, 2.26%, see rank | 1.24% | 5.03% |
| Electricity | 85, 8.00%, see rank | 33.31% | 35.51% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 0.02% | 6.46% |
| Coal or Coke | 0, 0.00%, see rank | 0.00% | 0.12% |
| Wood | 0, 0.00%, see rank | 0.46% | 2.08% |
| Solar Energy | 30, 2.82%, see rank | 1.36% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.07% | 0.43% |
| No Fuel Used | 887, 83.44%, see rank | 61.46% | 0.90% |
US Census 2000 data
| | 96752 Zip Code | Hawaii | U.S. |
| Total Housing Units | 971, 100% | 403,240 | 105,480,101 |
| Utility Gas | 95, 9.78%, see rank | 3.19% | 51.22% |
| Bottled, Tank, or LP Gas | 65, 6.69%, see rank | 2.56% | 6.52% |
| Electricity | 164, 16.89%, see rank | 47.79% | 30.35% |
| Fuel Oil, Kerosene, etc. | 7, 0.72%, see rank | 0.11% | 8.97% |
| Coal or Coke | 0, 0.00%, see rank | 0.00% | 0.14% |
| Wood | 0, 0.00%, see rank | 0.49% | 1.68% |
| Solar Energy | 51, 5.25%, see rank | 1.51% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.06% | 0.39% |
| No Fuel Used | 589, 60.66%, see rank | 44.30% | 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.
