01886 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 01886 Zip Code | Massachusetts | U.S. |
Total Housing Units | 7,738, 100% | 2,538,485 | 116,211,092 |
Utility Gas | 5,579, 72.10%, see rank | 49.70% | 48.85% |
Bottled, Tank, or LP Gas | 84, 1.09%, see rank | 2.86% | 4.86% |
Electricity | 333, 4.30%, see rank | 14.23% | 36.68% |
Fuel Oil, Kerosene, etc. | 1,606, 20.75%, see rank | 30.36% | 5.86% |
Coal or Coke | 7, 0.09%, see rank | 0.13% | 0.12% |
Wood | 119, 1.54%, see rank | 1.69% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 10, 0.13%, see rank | 0.65% | 0.47% |
No Fuel Used | 0, 0.00%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| 01886 Zip Code | Massachusetts | U.S. |
Total Housing Units | 7,378, 100% | 2,525,694 | 115,226,802 |
Utility Gas | 5,180, 70.21%, see rank | 48.52% | 49.42% |
Bottled, Tank, or LP Gas | 94, 1.27%, see rank | 2.58% | 5.03% |
Electricity | 252, 3.42%, see rank | 13.69% | 35.51% |
Fuel Oil, Kerosene, etc. | 1,737, 23.54%, see rank | 32.78% | 6.46% |
Coal or Coke | 7, 0.09%, see rank | 0.12% | 0.12% |
Wood | 108, 1.46%, see rank | 1.52% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.04% |
Other Fuel | 0, 0.00%, see rank | 0.53% | 0.43% |
No Fuel Used | 0, 0.00%, see rank | 0.23% | 0.90% |
US Census 2000 data
| 01886 Zip Code | Massachusetts | U.S. |
Total Housing Units | 6,808, 100% | 2,443,580 | 105,480,101 |
Utility Gas | 4,477, 65.76%, see rank | 43.89% | 51.22% |
Bottled, Tank, or LP Gas | 56, 0.82%, see rank | 2.63% | 6.52% |
Electricity | 330, 4.85%, see rank | 12.42% | 30.35% |
Fuel Oil, Kerosene, etc. | 1,893, 27.81%, see rank | 39.42% | 8.97% |
Coal or Coke | 5, 0.07%, see rank | 0.11% | 0.14% |
Wood | 42, 0.62%, see rank | 0.80% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 5, 0.07%, see rank | 0.44% | 0.39% |
No Fuel Used | 0, 0.00%, see rank | 0.27% | 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.