28716 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 28716 Zip Code | North Carolina | U.S. |
Total Housing Units | 7,298, 100% | 3,742,514 | 116,211,092 |
Utility Gas | 146, 2.00%, see rank | 24.68% | 48.85% |
Bottled, Tank, or LP Gas | 530, 7.26%, see rank | 8.00% | 4.86% |
Electricity | 3,237, 44.35%, see rank | 60.27% | 36.68% |
Fuel Oil, Kerosene, etc. | 2,352, 32.23%, see rank | 4.34% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 938, 12.85%, see rank | 2.17% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 0, 0.00%, see rank | 0.15% | 0.47% |
No Fuel Used | 95, 1.30%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| 28716 Zip Code | North Carolina | U.S. |
Total Housing Units | 7,316, 100% | 3,693,221 | 115,226,802 |
Utility Gas | 77, 1.05%, see rank | 24.97% | 49.42% |
Bottled, Tank, or LP Gas | 785, 10.73%, see rank | 8.90% | 5.03% |
Electricity | 3,074, 42.02%, see rank | 58.26% | 35.51% |
Fuel Oil, Kerosene, etc. | 2,519, 34.43%, see rank | 5.24% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 836, 11.43%, see rank | 2.16% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 9, 0.12%, see rank | 0.14% | 0.43% |
No Fuel Used | 16, 0.22%, see rank | 0.29% | 0.90% |
US Census 2000 data
| 28716 Zip Code | North Carolina | U.S. |
Total Housing Units | 7,063, 100% | 3,132,013 | 105,480,101 |
Utility Gas | 62, 0.88%, see rank | 24.19% | 51.22% |
Bottled, Tank, or LP Gas | 766, 10.85%, see rank | 12.59% | 6.52% |
Electricity | 1,683, 23.83%, see rank | 48.81% | 30.35% |
Fuel Oil, Kerosene, etc. | 4,003, 56.68%, see rank | 11.76% | 8.97% |
Coal or Coke | 12, 0.17%, see rank | 0.01% | 0.14% |
Wood | 514, 7.28%, see rank | 2.10% | 1.68% |
Solar Energy | 5, 0.07%, see rank | 0.04% | 0.04% |
Other Fuel | 0, 0.00%, see rank | 0.21% | 0.39% |
No Fuel Used | 18, 0.25%, see rank | 0.28% | 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.