06488 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 06488 Zip Code | Connecticut | U.S. |
Total Housing Units | 7,841, 100% | 1,356,206 | 116,211,092 |
Utility Gas | 462, 5.89%, see rank | 32.80% | 48.85% |
Bottled, Tank, or LP Gas | 327, 4.17%, see rank | 3.33% | 4.86% |
Electricity | 2,985, 38.07%, see rank | 15.36% | 36.68% |
Fuel Oil, Kerosene, etc. | 3,696, 47.14%, see rank | 45.24% | 5.86% |
Coal or Coke | 13, 0.17%, see rank | 0.12% | 0.12% |
Wood | 253, 3.23%, see rank | 2.16% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.04% | 0.05% |
Other Fuel | 91, 1.16%, see rank | 0.67% | 0.47% |
No Fuel Used | 14, 0.18%, see rank | 0.28% | 1.00% |
ACS 2008-2012 data
| 06488 Zip Code | Connecticut | U.S. |
Total Housing Units | 8,022, 100% | 1,360,184 | 115,226,802 |
Utility Gas | 445, 5.55%, see rank | 31.75% | 49.42% |
Bottled, Tank, or LP Gas | 249, 3.10%, see rank | 3.00% | 5.03% |
Electricity | 2,947, 36.74%, see rank | 15.12% | 35.51% |
Fuel Oil, Kerosene, etc. | 4,129, 51.47%, see rank | 47.37% | 6.46% |
Coal or Coke | 6, 0.07%, see rank | 0.09% | 0.12% |
Wood | 178, 2.22%, see rank | 1.90% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.04% |
Other Fuel | 68, 0.85%, see rank | 0.53% | 0.43% |
No Fuel Used | 0, 0.00%, see rank | 0.20% | 0.90% |
US Census 2000 data
| 06488 Zip Code | Connecticut | U.S. |
Total Housing Units | 7,225, 100% | 1,301,670 | 105,480,101 |
Utility Gas | 110, 1.52%, see rank | 29.01% | 51.22% |
Bottled, Tank, or LP Gas | 212, 2.93%, see rank | 2.39% | 6.52% |
Electricity | 2,941, 40.71%, see rank | 14.61% | 30.35% |
Fuel Oil, Kerosene, etc. | 3,816, 52.82%, see rank | 52.43% | 8.97% |
Coal or Coke | 16, 0.22%, see rank | 0.11% | 0.14% |
Wood | 113, 1.56%, see rank | 0.91% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 17, 0.24%, 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.