| Ethanol Imports have ticked up some.. but Ethanol Exports are FAR Greater
Imports https://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=W_EPOOXE_IM0_NUS-Z00_MBBLD&f=W
| Weekly U.S. Imports of Fuel Ethanol (Thousand Barrels per Day) | | |
| Year-Month | Week 1 | Week 2 | Week 3 | Week 4 | Week 5 |
|---|
| End Date | Value | End Date | Value | End Date | Value | End Date | Value | End Date | Value |
|---|
| 2020-Jan | 01/03 | 0 | 01/10 | 25 | 01/17 | 0 | 01/24 | 0 | 01/31 | 0 | | 2020-Feb | 02/07 | 0 | 02/14 | 0 | 02/21 | 35 | 02/28 | 0 | | | | 2020-Mar | 03/06 | 9 | 03/13 | 0 | 03/20 | 0
|
We don't have the updated numbers but Exports are.. https://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=M_EPOOXE_EEX_NUS-Z00_MBBL&f=M
| U.S. Exports of Fuel Ethanol (Thousand Barrels) | | |
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec |
|---|
| 2010 | 324 | 519 | 1,153 | 973 | 414 | 387 | 603 | 707 | 929 | 834 | 930 | 1,717 | | 2011 | 1,364 | 1,425 | 2,003 | 2,865 | 1,743 | 1,604 | 3,036 | 1,246 | 2,525 | 2,895 | 3,634 | 4,117 | | 2012 | 1,819 | 1,785 | 1,992 | 1,775 | 1,397 | 1,410 | 1,519 | 1,206 | 1,191 | 1,284 | 965 | 1,313 | | 2013 | 1,518 | 1,017 | 1,312 | 967 | 952 | 796 | 830 | 1,182 | 1,299 | 1,206 | 2,134 | 1,525 | | 2014 | 2,091 | 1,517 | 2,059 | 1,659 | 1,265 | 1,378 | 1,599 | 1,292 | 1,353 | 1,949 | 2,114 | 1,872 | | | | 2015 | 1,640 | 1,662 | 2,057 | 1,761 | 1,497 | 1,499 | 1,716 | 1,272 | 1,492 | 1,792 | 1,427 | 1,995 | | 2016 | 2,297 | 2,027 | 2,614 | 2,922 | 1,628 | 1,295 | 1,955 | 2,179 | 2,346 | 2,946 | 3,074 | 2,583 | | 2017 | 2,844 | 3,605 | 3,023 | 2,115 | 2,862 | 2,297 | 2,822 | 2,285 | 2,011 | 2,488 | 2,565 | 4,175 | | 2018 | 2,522 | 4,838 | 5,516 | 3,675 | 2,262 | 3,585 | 2,439 | 2,798 | 2,348 | 4,078 | 3,465 | 3,179 | | 2019 | 3,048 | 2,715 | 3,335 | 3,578 | 2,375 | 3,059 | 2,863 | 2,921 | 2,540 | 2,689 | 2,558 | 3,490 | | |
need to divide bbls by the month to get bbls per day Thus 3490 / 31 days/ Dec = 112.58 k bbls/day
Far Greater than Imports. |
Ethanol imported time series converted to lost corn bushels(Demand destruction)
