49095 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | 49095 Zip Code | Michigan | U.S. |
| Total Housing Units | 759, 100% | 3,827,880 | 116,211,092 |
| Utility Gas | 44, 5.80%, see rank | 77.13% | 48.85% |
| Bottled, Tank, or LP Gas | 406, 53.49%, see rank | 8.48% | 4.86% |
| Electricity | 130, 17.13%, see rank | 8.30% | 36.68% |
| Fuel Oil, Kerosene, etc. | 37, 4.87%, see rank | 1.40% | 5.86% |
| Coal or Coke | 0, 0.00%, see rank | 0.03% | 0.12% |
| Wood | 92, 12.12%, see rank | 3.39% | 2.12% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.05% |
| Other Fuel | 40, 5.27%, see rank | 0.86% | 0.47% |
| No Fuel Used | 10, 1.32%, see rank | 0.39% | 1.00% |
ACS 2008-2012 data
| | 49095 Zip Code | Michigan | U.S. |
| Total Housing Units | 784, 100% | 3,818,931 | 115,226,802 |
| Utility Gas | 32, 4.08%, see rank | 77.63% | 49.42% |
| Bottled, Tank, or LP Gas | 425, 54.21%, see rank | 8.76% | 5.03% |
| Electricity | 120, 15.31%, see rank | 7.60% | 35.51% |
| Fuel Oil, Kerosene, etc. | 70, 8.93%, see rank | 1.69% | 6.46% |
| Coal or Coke | 0, 0.00%, see rank | 0.03% | 0.12% |
| Wood | 92, 11.73%, see rank | 3.20% | 2.08% |
| Solar Energy | 0, 0.00%, see rank | 0.01% | 0.04% |
| Other Fuel | 14, 1.79%, see rank | 0.76% | 0.43% |
| No Fuel Used | 31, 3.95%, see rank | 0.32% | 0.90% |
US Census 2000 data
| | 49095 Zip Code | Michigan | U.S. |
| Total Housing Units | 756, 100% | 3,785,661 | 105,480,101 |
| Utility Gas | 15, 1.98%, see rank | 78.22% | 51.22% |
| Bottled, Tank, or LP Gas | 363, 48.02%, see rank | 9.44% | 6.52% |
| Electricity | 132, 17.46%, see rank | 6.64% | 30.35% |
| Fuel Oil, Kerosene, etc. | 177, 23.41%, see rank | 3.46% | 8.97% |
| Coal or Coke | 0, 0.00%, see rank | 0.02% | 0.14% |
| Wood | 67, 8.86%, see rank | 1.44% | 1.68% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
| Other Fuel | 2, 0.26%, see rank | 0.49% | 0.39% |
| No Fuel Used | 0, 0.00%, see rank | 0.28% | 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.
