28540 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 28540 Zip Code | North Carolina | U.S. |
Total Housing Units | 17,607, 100% | 3,742,514 | 116,211,092 |
Utility Gas | 540, 3.07%, see rank | 24.68% | 48.85% |
Bottled, Tank, or LP Gas | 701, 3.98%, see rank | 8.00% | 4.86% |
Electricity | 15,791, 89.69%, see rank | 60.27% | 36.68% |
Fuel Oil, Kerosene, etc. | 300, 1.70%, see rank | 4.34% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 131, 0.74%, see rank | 2.17% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 26, 0.15%, see rank | 0.15% | 0.47% |
No Fuel Used | 118, 0.67%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| 28540 Zip Code | North Carolina | U.S. |
Total Housing Units | 17,824, 100% | 3,693,221 | 115,226,802 |
Utility Gas | 582, 3.27%, see rank | 24.97% | 49.42% |
Bottled, Tank, or LP Gas | 884, 4.96%, see rank | 8.90% | 5.03% |
Electricity | 15,786, 88.57%, see rank | 58.26% | 35.51% |
Fuel Oil, Kerosene, etc. | 360, 2.02%, see rank | 5.24% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 103, 0.58%, see rank | 2.16% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 13, 0.07%, see rank | 0.14% | 0.43% |
No Fuel Used | 96, 0.54%, see rank | 0.29% | 0.90% |
US Census 2000 data
| 28540 Zip Code | North Carolina | U.S. |
Total Housing Units | 15,695, 100% | 3,132,013 | 105,480,101 |
Utility Gas | 108, 0.69%, see rank | 24.19% | 51.22% |
Bottled, Tank, or LP Gas | 1,493, 9.51%, see rank | 12.59% | 6.52% |
Electricity | 13,067, 83.26%, see rank | 48.81% | 30.35% |
Fuel Oil, Kerosene, etc. | 827, 5.27%, see rank | 11.76% | 8.97% |
Coal or Coke | 9, 0.06%, see rank | 0.01% | 0.14% |
Wood | 96, 0.61%, see rank | 2.10% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.04% | 0.04% |
Other Fuel | 37, 0.24%, see rank | 0.21% | 0.39% |
No Fuel Used | 58, 0.37%, 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.