06489 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 06489 Zip Code | Connecticut | U.S. |
Total Housing Units | 12,746, 100% | 1,356,206 | 116,211,092 |
Utility Gas | 5,737, 45.01%, see rank | 32.80% | 48.85% |
Bottled, Tank, or LP Gas | 785, 6.16%, see rank | 3.33% | 4.86% |
Electricity | 1,162, 9.12%, see rank | 15.36% | 36.68% |
Fuel Oil, Kerosene, etc. | 4,759, 37.34%, see rank | 45.24% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.12% | 0.12% |
Wood | 195, 1.53%, see rank | 2.16% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.04% | 0.05% |
Other Fuel | 108, 0.85%, see rank | 0.67% | 0.47% |
No Fuel Used | 0, 0.00%, see rank | 0.28% | 1.00% |
ACS 2008-2012 data
| 06489 Zip Code | Connecticut | U.S. |
Total Housing Units | 12,680, 100% | 1,360,184 | 115,226,802 |
Utility Gas | 5,805, 45.78%, see rank | 31.75% | 49.42% |
Bottled, Tank, or LP Gas | 840, 6.62%, see rank | 3.00% | 5.03% |
Electricity | 1,143, 9.01%, see rank | 15.12% | 35.51% |
Fuel Oil, Kerosene, etc. | 4,682, 36.92%, see rank | 47.37% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.09% | 0.12% |
Wood | 162, 1.28%, see rank | 1.90% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.04% |
Other Fuel | 48, 0.38%, see rank | 0.53% | 0.43% |
No Fuel Used | 0, 0.00%, see rank | 0.20% | 0.90% |
US Census 2000 data
| 06489 Zip Code | Connecticut | U.S. |
Total Housing Units | 11,302, 100% | 1,301,670 | 105,480,101 |
Utility Gas | 4,814, 42.59%, see rank | 29.01% | 51.22% |
Bottled, Tank, or LP Gas | 417, 3.69%, see rank | 2.39% | 6.52% |
Electricity | 989, 8.75%, see rank | 14.61% | 30.35% |
Fuel Oil, Kerosene, etc. | 4,937, 43.68%, see rank | 52.43% | 8.97% |
Coal or Coke | 41, 0.36%, see rank | 0.11% | 0.14% |
Wood | 65, 0.58%, see rank | 0.91% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 39, 0.35%, see rank | 0.35% | 0.39% |
No Fuel Used | 0, 0.00%, see rank | 0.18% | 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.