02144 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 02144 Zip Code | Massachusetts | U.S. |
Total Housing Units | 10,735, 100% | 2,538,485 | 116,211,092 |
Utility Gas | 7,910, 73.68%, see rank | 49.70% | 48.85% |
Bottled, Tank, or LP Gas | 283, 2.64%, see rank | 2.86% | 4.86% |
Electricity | 950, 8.85%, see rank | 14.23% | 36.68% |
Fuel Oil, Kerosene, etc. | 1,431, 13.33%, see rank | 30.36% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.13% | 0.12% |
Wood | 0, 0.00%, see rank | 1.69% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 24, 0.22%, see rank | 0.65% | 0.47% |
No Fuel Used | 137, 1.28%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| 02144 Zip Code | Massachusetts | U.S. |
Total Housing Units | 10,646, 100% | 2,525,694 | 115,226,802 |
Utility Gas | 7,774, 73.02%, see rank | 48.52% | 49.42% |
Bottled, Tank, or LP Gas | 292, 2.74%, see rank | 2.58% | 5.03% |
Electricity | 845, 7.94%, see rank | 13.69% | 35.51% |
Fuel Oil, Kerosene, etc. | 1,653, 15.53%, see rank | 32.78% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.12% | 0.12% |
Wood | 0, 0.00%, see rank | 1.52% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.04% |
Other Fuel | 13, 0.12%, see rank | 0.53% | 0.43% |
No Fuel Used | 69, 0.65%, see rank | 0.23% | 0.90% |
US Census 2000 data
| 02144 Zip Code | Massachusetts | U.S. |
Total Housing Units | 10,413, 100% | 2,443,580 | 105,480,101 |
Utility Gas | 6,841, 65.70%, see rank | 43.89% | 51.22% |
Bottled, Tank, or LP Gas | 342, 3.28%, see rank | 2.63% | 6.52% |
Electricity | 734, 7.05%, see rank | 12.42% | 30.35% |
Fuel Oil, Kerosene, etc. | 2,433, 23.37%, see rank | 39.42% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.11% | 0.14% |
Wood | 0, 0.00%, see rank | 0.80% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 40, 0.38%, see rank | 0.44% | 0.39% |
No Fuel Used | 23, 0.22%, 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.