Marion, NY Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | Marion, NY | New York | U.S. |
| Total Housing Units | 656, 100% | 7,255,528 | 116,211,092 |
| Utility Gas | 418, 63.72%, see rank | 56.12% | 48.85% |
| Bottled, Tank, or LP Gas | 42, 6.40%, see rank | 3.36% | 4.86% |
| Electricity | 157, 23.93%, see rank | 10.26% | 36.68% |
| Fuel Oil, Kerosene, etc. | 21, 3.20%, see rank | 26.24% | 5.86% |
| Coal or Coke | 0, 0.00%, see rank | 0.26% | 0.12% |
| Wood | 18, 2.74%, see rank | 2.04% | 2.12% |
| Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
| Other Fuel | 0, 0.00%, see rank | 0.97% | 0.47% |
| No Fuel Used | 0, 0.00%, see rank | 0.72% | 1.00% |
ACS 2008-2012 data
| | Marion, NY | New York | U.S. |
| Total Housing Units | 661, 100% | 7,230,896 | 115,226,802 |
| Utility Gas | 351, 53.10%, see rank | 54.92% | 49.42% |
| Bottled, Tank, or LP Gas | 35, 5.30%, see rank | 3.16% | 5.03% |
| Electricity | 204, 30.86%, see rank | 9.44% | 35.51% |
| Fuel Oil, Kerosene, etc. | 37, 5.60%, see rank | 28.80% | 6.46% |
| Coal or Coke | 0, 0.00%, see rank | 0.26% | 0.12% |
| Wood | 34, 5.14%, see rank | 1.96% | 2.08% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.86% | 0.43% |
| No Fuel Used | 0, 0.00%, see rank | 0.57% | 0.90% |
ACS 2006-2010 data
| | Marion, NY | New York | U.S. |
| Total Housing Units | 722, 100% | 7,205,740 | 114,235,996 |
| Utility Gas | 386, 53.46%, see rank | 53.35% | 49.91% |
| Bottled, Tank, or LP Gas | 29, 4.02%, see rank | 3.13% | 5.38% |
| Electricity | 180, 24.93%, see rank | 8.86% | 34.20% |
| Fuel Oil, Kerosene, etc. | 19, 2.63%, see rank | 31.29% | 7.07% |
| Coal or Coke | 0, 0.00%, see rank | 0.25% | 0.12% |
| Wood | 108, 14.96%, see rank | 1.76% | 1.97% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.03% |
| Other Fuel | 0, 0.00%, see rank | 0.82% | 0.42% |
| No Fuel Used | 0, 0.00%, see rank | 0.52% | 0.90% |
* 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.
