02886 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 02886 Zip Code | Rhode Island | U.S. |
Total Housing Units | 12,528, 100% | 409,569 | 116,211,092 |
Utility Gas | 7,468, 59.61%, see rank | 51.13% | 48.85% |
Bottled, Tank, or LP Gas | 125, 1.00%, see rank | 2.34% | 4.86% |
Electricity | 1,393, 11.12%, see rank | 9.15% | 36.68% |
Fuel Oil, Kerosene, etc. | 3,402, 27.16%, see rank | 34.82% | 5.86% |
Coal or Coke | 15, 0.12%, see rank | 0.11% | 0.12% |
Wood | 62, 0.49%, see rank | 1.75% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.05% |
Other Fuel | 48, 0.38%, see rank | 0.42% | 0.47% |
No Fuel Used | 15, 0.12%, see rank | 0.26% | 1.00% |
ACS 2008-2012 data
| 02886 Zip Code | Rhode Island | U.S. |
Total Housing Units | 12,900, 100% | 410,639 | 115,226,802 |
Utility Gas | 7,465, 57.87%, see rank | 49.86% | 49.42% |
Bottled, Tank, or LP Gas | 99, 0.77%, see rank | 2.00% | 5.03% |
Electricity | 1,439, 11.16%, see rank | 8.60% | 35.51% |
Fuel Oil, Kerosene, etc. | 3,787, 29.36%, see rank | 37.38% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.13% | 0.12% |
Wood | 82, 0.64%, see rank | 1.49% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 0, 0.00%, see rank | 0.30% | 0.43% |
No Fuel Used | 28, 0.22%, see rank | 0.23% | 0.90% |
US Census 2000 data
| 02886 Zip Code | Rhode Island | U.S. |
Total Housing Units | 13,032, 100% | 408,424 | 105,480,101 |
Utility Gas | 7,465, 57.28%, see rank | 46.31% | 51.22% |
Bottled, Tank, or LP Gas | 136, 1.04%, see rank | 2.51% | 6.52% |
Electricity | 1,177, 9.03%, see rank | 7.64% | 30.35% |
Fuel Oil, Kerosene, etc. | 4,127, 31.67%, see rank | 42.08% | 8.97% |
Coal or Coke | 20, 0.15%, see rank | 0.08% | 0.14% |
Wood | 22, 0.17%, see rank | 0.88% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.04% |
Other Fuel | 54, 0.41%, see rank | 0.29% | 0.39% |
No Fuel Used | 31, 0.24%, 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.