16509 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 16509 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 11,682, 100% | 4,957,736 | 116,211,092 |
Utility Gas | 9,731, 83.30%, see rank | 51.01% | 48.85% |
Bottled, Tank, or LP Gas | 114, 0.98%, see rank | 3.81% | 4.86% |
Electricity | 1,413, 12.10%, see rank | 21.18% | 36.68% |
Fuel Oil, Kerosene, etc. | 232, 1.99%, see rank | 18.77% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 1.37% | 0.12% |
Wood | 141, 1.21%, see rank | 2.87% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 51, 0.44%, see rank | 0.65% | 0.47% |
No Fuel Used | 0, 0.00%, see rank | 0.30% | 1.00% |
ACS 2008-2012 data
| 16509 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 11,682, 100% | 4,959,633 | 115,226,802 |
Utility Gas | 9,462, 81.00%, see rank | 51.16% | 49.42% |
Bottled, Tank, or LP Gas | 95, 0.81%, see rank | 3.64% | 5.03% |
Electricity | 1,658, 14.19%, see rank | 20.12% | 35.51% |
Fuel Oil, Kerosene, etc. | 294, 2.52%, see rank | 20.21% | 6.46% |
Coal or Coke | 12, 0.10%, see rank | 1.35% | 0.12% |
Wood | 129, 1.10%, see rank | 2.71% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 6, 0.05%, see rank | 0.56% | 0.43% |
No Fuel Used | 26, 0.22%, see rank | 0.24% | 0.90% |
US Census 2000 data
| 16509 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 10,752, 100% | 4,777,003 | 105,480,101 |
Utility Gas | 9,173, 85.31%, see rank | 51.35% | 51.22% |
Bottled, Tank, or LP Gas | 114, 1.06%, see rank | 3.04% | 6.52% |
Electricity | 1,190, 11.07%, see rank | 16.47% | 30.35% |
Fuel Oil, Kerosene, etc. | 148, 1.38%, see rank | 25.48% | 8.97% |
Coal or Coke | 5, 0.05%, see rank | 1.42% | 0.14% |
Wood | 67, 0.62%, see rank | 1.59% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.04% |
Other Fuel | 55, 0.51%, see rank | 0.43% | 0.39% |
No Fuel Used | 0, 0.00%, see rank | 0.21% | 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.