Baltimore Highlands, MD Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| Baltimore Highlands, MD | Maryland | U.S. |
Total Housing Units | 2,383, 100% | 2,155,983 | 116,211,092 |
Utility Gas | 1,497, 62.82%, see rank | 44.54% | 48.85% |
Bottled, Tank, or LP Gas | 6, 0.25%, see rank | 3.17% | 4.86% |
Electricity | 616, 25.85%, see rank | 39.67% | 36.68% |
Fuel Oil, Kerosene, etc. | 243, 10.20%, see rank | 10.31% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.11% | 0.12% |
Wood | 0, 0.00%, see rank | 1.37% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 8, 0.34%, see rank | 0.45% | 0.47% |
No Fuel Used | 13, 0.55%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| Baltimore Highlands, MD | Maryland | U.S. |
Total Housing Units | 2,532, 100% | 2,138,806 | 115,226,802 |
Utility Gas | 1,453, 57.39%, see rank | 44.82% | 49.42% |
Bottled, Tank, or LP Gas | 0, 0.00%, see rank | 3.21% | 5.03% |
Electricity | 809, 31.95%, see rank | 38.74% | 35.51% |
Fuel Oil, Kerosene, etc. | 250, 9.87%, see rank | 11.18% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.11% | 0.12% |
Wood | 0, 0.00%, see rank | 1.27% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 8, 0.32%, see rank | 0.43% | 0.43% |
No Fuel Used | 12, 0.47%, see rank | 0.23% | 0.90% |
ACS 2006-2010 data
| Baltimore Highlands, MD | Maryland | U.S. |
Total Housing Units | 2,555, 100% | 2,121,047 | 114,235,996 |
Utility Gas | 1,619, 63.37%, see rank | 45.09% | 49.91% |
Bottled, Tank, or LP Gas | 9, 0.35%, see rank | 3.32% | 5.38% |
Electricity | 625, 24.46%, see rank | 37.58% | 34.20% |
Fuel Oil, Kerosene, etc. | 274, 10.72%, see rank | 12.14% | 7.07% |
Coal or Coke | 0, 0.00%, see rank | 0.11% | 0.12% |
Wood | 0, 0.00%, see rank | 1.13% | 1.97% |
Solar Energy | 0, 0.00%, see rank | 0.01% | 0.03% |
Other Fuel | 17, 0.67%, see rank | 0.38% | 0.42% |
No Fuel Used | 11, 0.43%, see rank | 0.24% | 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.