10011 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 10011 Zip Code | New York | U.S. |
Total Housing Units | 29,921, 100% | 7,255,528 | 116,211,092 |
Utility Gas | 12,102, 40.45%, see rank | 56.12% | 48.85% |
Bottled, Tank, or LP Gas | 544, 1.82%, see rank | 3.36% | 4.86% |
Electricity | 5,729, 19.15%, see rank | 10.26% | 36.68% |
Fuel Oil, Kerosene, etc. | 9,784, 32.70%, see rank | 26.24% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.26% | 0.12% |
Wood | 0, 0.00%, see rank | 2.04% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 912, 3.05%, see rank | 0.97% | 0.47% |
No Fuel Used | 850, 2.84%, see rank | 0.72% | 1.00% |
ACS 2008-2012 data
| 10011 Zip Code | New York | U.S. |
Total Housing Units | 29,668, 100% | 7,230,896 | 115,226,802 |
Utility Gas | 10,400, 35.05%, see rank | 54.92% | 49.42% |
Bottled, Tank, or LP Gas | 682, 2.30%, see rank | 3.16% | 5.03% |
Electricity | 5,523, 18.62%, see rank | 9.44% | 35.51% |
Fuel Oil, Kerosene, etc. | 11,577, 39.02%, see rank | 28.80% | 6.46% |
Coal or Coke | 14, 0.05%, see rank | 0.26% | 0.12% |
Wood | 0, 0.00%, see rank | 1.96% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 773, 2.61%, see rank | 0.86% | 0.43% |
No Fuel Used | 699, 2.36%, see rank | 0.57% | 0.90% |
US Census 2000 data
| 10011 Zip Code | New York | U.S. |
Total Housing Units | 28,657, 100% | 7,056,860 | 105,480,101 |
Utility Gas | 10,517, 36.70%, see rank | 51.75% | 51.22% |
Bottled, Tank, or LP Gas | 546, 1.91%, see rank | 3.37% | 6.52% |
Electricity | 3,300, 11.52%, see rank | 8.72% | 30.35% |
Fuel Oil, Kerosene, etc. | 13,097, 45.70%, see rank | 33.11% | 8.97% |
Coal or Coke | 62, 0.22%, see rank | 0.14% | 0.14% |
Wood | 0, 0.00%, see rank | 1.17% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.04% | 0.04% |
Other Fuel | 913, 3.19%, see rank | 1.04% | 0.39% |
No Fuel Used | 222, 0.77%, see rank | 0.66% | 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.