06002 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 06002 Zip Code | Connecticut | U.S. |
Total Housing Units | 8,417, 100% | 1,356,206 | 116,211,092 |
Utility Gas | 3,623, 43.04%, see rank | 32.80% | 48.85% |
Bottled, Tank, or LP Gas | 217, 2.58%, see rank | 3.33% | 4.86% |
Electricity | 1,492, 17.73%, see rank | 15.36% | 36.68% |
Fuel Oil, Kerosene, etc. | 2,947, 35.01%, see rank | 45.24% | 5.86% |
Coal or Coke | 8, 0.10%, see rank | 0.12% | 0.12% |
Wood | 95, 1.13%, see rank | 2.16% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.04% | 0.05% |
Other Fuel | 35, 0.42%, see rank | 0.67% | 0.47% |
No Fuel Used | 0, 0.00%, see rank | 0.28% | 1.00% |
ACS 2008-2012 data
| 06002 Zip Code | Connecticut | U.S. |
Total Housing Units | 8,505, 100% | 1,360,184 | 115,226,802 |
Utility Gas | 3,314, 38.97%, see rank | 31.75% | 49.42% |
Bottled, Tank, or LP Gas | 284, 3.34%, see rank | 3.00% | 5.03% |
Electricity | 1,357, 15.96%, see rank | 15.12% | 35.51% |
Fuel Oil, Kerosene, etc. | 3,399, 39.96%, see rank | 47.37% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.09% | 0.12% |
Wood | 87, 1.02%, see rank | 1.90% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.04% |
Other Fuel | 64, 0.75%, see rank | 0.53% | 0.43% |
No Fuel Used | 0, 0.00%, see rank | 0.20% | 0.90% |
US Census 2000 data
| 06002 Zip Code | Connecticut | U.S. |
Total Housing Units | 7,902, 100% | 1,301,670 | 105,480,101 |
Utility Gas | 2,965, 37.52%, see rank | 29.01% | 51.22% |
Bottled, Tank, or LP Gas | 178, 2.25%, see rank | 2.39% | 6.52% |
Electricity | 1,001, 12.67%, see rank | 14.61% | 30.35% |
Fuel Oil, Kerosene, etc. | 3,667, 46.41%, see rank | 52.43% | 8.97% |
Coal or Coke | 24, 0.30%, see rank | 0.11% | 0.14% |
Wood | 8, 0.10%, see rank | 0.91% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 16, 0.20%, see rank | 0.35% | 0.39% |
No Fuel Used | 43, 0.54%, 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.