48896 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | 48896 Zip Code | Michigan | U.S. |
| Total Housing Units | 56, 100% | 3,827,880 | 116,211,092 |
| Utility Gas | 47, 83.93%, see rank | 77.13% | 48.85% |
| Bottled, Tank, or LP Gas | 9, 16.07%, see rank | 8.48% | 4.86% |
| Electricity | 0, 0.00%, see rank | 8.30% | 36.68% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 1.40% | 5.86% |
| Coal or Coke | 0, 0.00%, see rank | 0.03% | 0.12% |
| Wood | 0, 0.00%, see rank | 3.39% | 2.12% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.05% |
| Other Fuel | 0, 0.00%, see rank | 0.86% | 0.47% |
| No Fuel Used | 0, 0.00%, see rank | 0.39% | 1.00% |
ACS 2008-2012 data
| | 48896 Zip Code | Michigan | U.S. |
| Total Housing Units | 58, 100% | 3,818,931 | 115,226,802 |
| Utility Gas | 46, 79.31%, see rank | 77.63% | 49.42% |
| Bottled, Tank, or LP Gas | 12, 20.69%, see rank | 8.76% | 5.03% |
| Electricity | 0, 0.00%, see rank | 7.60% | 35.51% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 1.69% | 6.46% |
| Coal or Coke | 0, 0.00%, see rank | 0.03% | 0.12% |
| Wood | 0, 0.00%, see rank | 3.20% | 2.08% |
| Solar Energy | 0, 0.00%, see rank | 0.01% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.76% | 0.43% |
| No Fuel Used | 0, 0.00%, see rank | 0.32% | 0.90% |
US Census 2000 data
| | 48896 Zip Code | Michigan | U.S. |
| Total Housing Units | 46, 100% | 3,785,661 | 105,480,101 |
| Utility Gas | 42, 91.30%, see rank | 78.22% | 51.22% |
| Bottled, Tank, or LP Gas | 2, 4.35%, see rank | 9.44% | 6.52% |
| Electricity | 2, 4.35%, see rank | 6.64% | 30.35% |
| Fuel Oil, Kerosene, etc. | 0, 0.00%, see rank | 3.46% | 8.97% |
| Coal or Coke | 0, 0.00%, see rank | 0.02% | 0.14% |
| Wood | 0, 0.00%, see rank | 1.44% | 1.68% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
| Other Fuel | 0, 0.00%, 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.
