Table 3.
Reported net cropland expansion due to modelled biofuel policies among national studies. Modelled biofuels include corn ethanol in the case of all studies, in addition to soy biodiesel and cellulosic ethanol in the case of Taheripour, Zhao and Tyner (2017), Taheripour, Baumes and Tyner (2020), Oladosu & Kline (2013), Mosnier et al. (2013), Elliot et al. (2014), Chen et al. (2021), Cai et al. (2013), and EPA (2010). We also include in this table the three empirical studies which reported nation-wide impacts of biofuel expansion on net cropland expansion (Lark et al., 2021, Li et al., 2019, and Wright et al., 2017). For these empirical studies we use the observed increase in corn ethanol volumes over the study period as the simulated increase, with the exception of Lark et al., 2021 which attributes a portion of the total observed increase in biofuel volumes to the RFS Program.
| Study | Model Name and Typea | Time period | Biofuel induced net cropland expansion in the U.S. (million acres) | Proportion of net cropland expansion from CRP land (if reported) | Simulated increase in biofuel volumes from the RFS (BGY) | Net cropland expansion per increase in biofuel volumes from the RFS (million acres/BGY) |
|---|---|---|---|---|---|---|
|
| ||||||
| Lark et al. 2021 [46] | Empirical | 2008–2016 | 2.1 | 5.5 | 0.38 | |
| Chen et al. 2021 [43] | BEPAM (PE) | 2016–2030 | 14.6 | 8.5 | 1.72 | |
| Taheripour, Baumes, and Tyner 2020 [25] | GTAP-BIO (CGE) and AEPE (PE) | 2004–2011 | 1.01 | 0.7 | 1.45 | |
| 2011–2016 | 0.16 | 1.5 | 0.05 | |||
| 2004–2016 | 1.17 | 2.2 | 0.53 | |||
| Khanna, Wang and Wang 2020 [42] | BEPAM (PE) | 2007–2017 | 1.2 | 8.5 | 0.14 | |
| 2017–2027 | 1.2 | 0 | ||||
| Li, Miao, and Khanna 2019 [33] | Empirical | 2003–2012 | 6.9 | 10.4 | 0.66 | |
| 2003–2014 | 7 | 11.5 | 0.61 | |||
| 2008–2012 | 2.1 | 4.2 | 0.50 | |||
| 2008–2014 | 2.3 | 5.3 | 0.43 | |||
| Chen & Khanna 2018 [32] | BEPAM (PE) | 2007–2012 | 3.15 | 31% | 6.7 | 0.47 |
| Taheripour, Zhao, and Tyner 2017 [26] | GTAP-BIO (CGE) | 2011–2015 | 0.01 | 1.1 | 0.01 | |
| Wright et al. 2017 [10] | Empirical | 2008–2012 | 2.7 | 4.2 | 0.64 | |
| Bento, Klotz, and Landry 2015 [31] | Multi-market equilibrium model (PE) | 2009–2012 | 0.99 | 75% | 3 | 0.33 |
| 2012–2015 | 1.48 | 84% | 3 | 0.49 | ||
| CARB 2014 [40] | GTAP-BIO (CGE) | 2004–2017 | 4.45 | 11.6 | 0.38 | |
| Elliot et al. 2014 [41] | PEEL-Co (PE) | 2010–2022 | 7.2 | 10.1 | 0.71 | |
| Mosnier et al. 2013 [37] | GLOBIOM (PE) | 2010–2020 | 7.4 | 9 | 0.82 | |
| Oladosu & Kline 2013 [38] | GTAP-DEPS (CGE) | 2001–2030 | 3.2 | 11.6 | 0.28 | |
| Cai et al. 2013 [39] | ADAGE-Biofuel (CGE) | 2010–2022 | 3.7 | 18.6 | 0.2 | |
| EPA 2010 [35] | FASOM (PE) | 2008–2022 | 8.1 | 65% | 17.1 | 0.47 |
| Hertel et al. 2010 [36] | GTAP-BIO (CGE) | 2001–2015 | 3.95 | 13.3 | 0.3 | |
| Malcolm, Aillery, and Weinberg 2009 [34] | REAP (PE) | 2015 | 4.9 | 63% | 2 | 2.45 |
| Searchinger et al 2008 [5] | FAPRI (PE) | 2005–2035 | 5.44 | 14.8 | 0.37 | |
Partial Equilibrium (PE) and Computable General Equilibrium (CGE).