19540 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 19540 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 4,346, 100% | 4,957,736 | 116,211,092 |
Utility Gas | 610, 14.04%, see rank | 51.01% | 48.85% |
Bottled, Tank, or LP Gas | 351, 8.08%, see rank | 3.81% | 4.86% |
Electricity | 1,141, 26.25%, see rank | 21.18% | 36.68% |
Fuel Oil, Kerosene, etc. | 1,890, 43.49%, see rank | 18.77% | 5.86% |
Coal or Coke | 55, 1.27%, see rank | 1.37% | 0.12% |
Wood | 228, 5.25%, see rank | 2.87% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 71, 1.63%, see rank | 0.65% | 0.47% |
No Fuel Used | 0, 0.00%, see rank | 0.30% | 1.00% |
ACS 2008-2012 data
| 19540 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 4,531, 100% | 4,959,633 | 115,226,802 |
Utility Gas | 672, 14.83%, see rank | 51.16% | 49.42% |
Bottled, Tank, or LP Gas | 453, 10.00%, see rank | 3.64% | 5.03% |
Electricity | 1,130, 24.94%, see rank | 20.12% | 35.51% |
Fuel Oil, Kerosene, etc. | 1,866, 41.18%, see rank | 20.21% | 6.46% |
Coal or Coke | 51, 1.13%, see rank | 1.35% | 0.12% |
Wood | 257, 5.67%, see rank | 2.71% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 89, 1.96%, see rank | 0.56% | 0.43% |
No Fuel Used | 13, 0.29%, see rank | 0.24% | 0.90% |
US Census 2000 data
| 19540 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 4,205, 100% | 4,777,003 | 105,480,101 |
Utility Gas | 645, 15.34%, see rank | 51.35% | 51.22% |
Bottled, Tank, or LP Gas | 239, 5.68%, see rank | 3.04% | 6.52% |
Electricity | 975, 23.19%, see rank | 16.47% | 30.35% |
Fuel Oil, Kerosene, etc. | 2,023, 48.11%, see rank | 25.48% | 8.97% |
Coal or Coke | 76, 1.81%, see rank | 1.42% | 0.14% |
Wood | 203, 4.83%, see rank | 1.59% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.04% |
Other Fuel | 17, 0.40%, see rank | 0.43% | 0.39% |
No Fuel Used | 27, 0.64%, 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.