Lancaster Micro Area Historical Type of Heating Fuel in a House Data
ACS 2008-2012 data
| Lancaster Area | South Carolina | U.S. |
Total Housing Units | 28,949, 100% | 1,768,255 | 115,226,802 |
Utility Gas | 14,433, 49.86%, see rank | 24.20% | 49.42% |
Bottled, Tank, or LP Gas | 1,215, 4.20%, see rank | 4.95% | 5.03% |
Electricity | 11,882, 41.04%, see rank | 67.56% | 35.51% |
Fuel Oil, Kerosene, etc. | 739, 2.55%, see rank | 1.75% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 582, 2.01%, see rank | 1.12% | 2.08% |
Solar Energy | 6, 0.02%, see rank | 0.01% | 0.04% |
Other Fuel | 13, 0.04%, see rank | 0.10% | 0.43% |
No Fuel Used | 79, 0.27%, see rank | 0.30% | 0.90% |
ACS 2006-2010 data
| Lancaster Area | South Carolina | U.S. |
Total Housing Units | 28,180, 100% | 1,741,994 | 114,235,996 |
Utility Gas | 13,509, 47.94%, see rank | 24.92% | 49.91% |
Bottled, Tank, or LP Gas | 1,408, 5.00%, see rank | 5.54% | 5.38% |
Electricity | 11,681, 41.45%, see rank | 65.81% | 34.20% |
Fuel Oil, Kerosene, etc. | 955, 3.39%, see rank | 2.27% | 7.07% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 552, 1.96%, see rank | 1.05% | 1.97% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.03% |
Other Fuel | 9, 0.03%, see rank | 0.08% | 0.42% |
No Fuel Used | 66, 0.23%, see rank | 0.30% | 0.90% |
ACS 2005-2009 data
| Lancaster Area | South Carolina | U.S. |
Total Housing Units | 26,006, 100% | 1,693,388 | 112,611,029 |
Utility Gas | 12,277, 47.21%, see rank | 25.46% | 50.14% |
Bottled, Tank, or LP Gas | 1,672, 6.43%, see rank | 6.05% | 5.58% |
Electricity | 10,314, 39.66%, see rank | 64.40% | 33.56% |
Fuel Oil, Kerosene, etc. | 1,097, 4.22%, see rank | 2.59% | 7.38% |
Coal or Coke | 0, 0.00%, see rank | 0.00% | 0.12% |
Wood | 558, 2.15%, see rank | 1.08% | 1.89% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.03% |
Other Fuel | 28, 0.11%, see rank | 0.09% | 0.42% |
No Fuel Used | 60, 0.23%, see rank | 0.30% | 0.88% |
* 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.