30506 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 30506 Zip Code | Georgia | U.S. |
Total Housing Units | 15,365, 100% | 3,540,690 | 116,211,092 |
Utility Gas | 3,675, 23.92%, see rank | 40.63% | 48.85% |
Bottled, Tank, or LP Gas | 1,014, 6.60%, see rank | 5.27% | 4.86% |
Electricity | 10,352, 67.37%, see rank | 52.46% | 36.68% |
Fuel Oil, Kerosene, etc. | 17, 0.11%, see rank | 0.22% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 250, 1.63%, see rank | 0.99% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.05% |
Other Fuel | 15, 0.10%, see rank | 0.08% | 0.47% |
No Fuel Used | 42, 0.27%, see rank | 0.32% | 1.00% |
ACS 2008-2012 data
| 30506 Zip Code | Georgia | U.S. |
Total Housing Units | 15,311, 100% | 3,508,477 | 115,226,802 |
Utility Gas | 3,837, 25.06%, see rank | 41.92% | 49.42% |
Bottled, Tank, or LP Gas | 1,297, 8.47%, see rank | 5.83% | 5.03% |
Electricity | 9,928, 64.84%, see rank | 50.64% | 35.51% |
Fuel Oil, Kerosene, etc. | 35, 0.23%, see rank | 0.26% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.00% | 0.12% |
Wood | 148, 0.97%, see rank | 0.99% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.04% |
Other Fuel | 21, 0.14%, see rank | 0.08% | 0.43% |
No Fuel Used | 45, 0.29%, see rank | 0.26% | 0.90% |
US Census 2000 data
| 30506 Zip Code | Georgia | U.S. |
Total Housing Units | 11,376, 100% | 3,006,369 | 105,480,101 |
Utility Gas | 2,926, 25.72%, see rank | 48.92% | 51.22% |
Bottled, Tank, or LP Gas | 2,245, 19.73%, see rank | 10.78% | 6.52% |
Electricity | 5,775, 50.76%, see rank | 38.30% | 30.35% |
Fuel Oil, Kerosene, etc. | 115, 1.01%, see rank | 0.62% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.14% |
Wood | 255, 2.24%, see rank | 0.97% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 0, 0.00%, see rank | 0.08% | 0.39% |
No Fuel Used | 60, 0.53%, see rank | 0.30% | 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.