16648 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 16648 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 6,135, 100% | 4,957,736 | 116,211,092 |
Utility Gas | 3,598, 58.65%, see rank | 51.01% | 48.85% |
Bottled, Tank, or LP Gas | 93, 1.52%, see rank | 3.81% | 4.86% |
Electricity | 1,018, 16.59%, see rank | 21.18% | 36.68% |
Fuel Oil, Kerosene, etc. | 1,158, 18.88%, see rank | 18.77% | 5.86% |
Coal or Coke | 63, 1.03%, see rank | 1.37% | 0.12% |
Wood | 114, 1.86%, see rank | 2.87% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 37, 0.60%, see rank | 0.65% | 0.47% |
No Fuel Used | 54, 0.88%, see rank | 0.30% | 1.00% |
ACS 2008-2012 data
| 16648 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 6,150, 100% | 4,959,633 | 115,226,802 |
Utility Gas | 3,444, 56.00%, see rank | 51.16% | 49.42% |
Bottled, Tank, or LP Gas | 84, 1.37%, see rank | 3.64% | 5.03% |
Electricity | 975, 15.85%, see rank | 20.12% | 35.51% |
Fuel Oil, Kerosene, etc. | 1,434, 23.32%, see rank | 20.21% | 6.46% |
Coal or Coke | 122, 1.98%, see rank | 1.35% | 0.12% |
Wood | 45, 0.73%, see rank | 2.71% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 0, 0.00%, see rank | 0.56% | 0.43% |
No Fuel Used | 46, 0.75%, see rank | 0.24% | 0.90% |
US Census 2000 data
| 16648 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 6,045, 100% | 4,777,003 | 105,480,101 |
Utility Gas | 3,667, 60.66%, see rank | 51.35% | 51.22% |
Bottled, Tank, or LP Gas | 48, 0.79%, see rank | 3.04% | 6.52% |
Electricity | 615, 10.17%, see rank | 16.47% | 30.35% |
Fuel Oil, Kerosene, etc. | 1,479, 24.47%, see rank | 25.48% | 8.97% |
Coal or Coke | 107, 1.77%, see rank | 1.42% | 0.14% |
Wood | 113, 1.87%, see rank | 1.59% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.04% |
Other Fuel | 16, 0.26%, 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.