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Chen, Luoye

Publications and source records attributed to Chen, Luoye.

Quantifying uncertainties in greenhouse gas savings and abatement costs with cellulosic biofuels

Cellulosic biofuels from non-food feedstocks, while appealing, continue to encounter uncertainty about their induced land use change (ILUC) effects, net greenhouse gas (GHG) saving potential and their economic costs. We analyze the implications of multiple uncertainties along the biofuel supply chain from feedstock yields, land availability for production to conversion to fuel in the refinery on these outcomes. Furthermore, we find that compared to corn ethanol, cellulosic biofuels have a substantially smaller and less uncertain ILUC-related GHG intensity and lead to larger GHG savings at lower welfare costs of abatement, indicating the potential to make robust and substantial contributions to cost-effective climate change mitigation.

09 BIOMASS FUELS↗

Code and Data for "Quantifying Uncertainties in Greenhouse Gas Savings and Mitigation Costs with Cellulosic Biofuels"

Use of cellulosic biofuels from non-feedstocks are modeled using the BEPAM (Biofuel and Environmental Policy Analysis Model) model to quantifying the uncertainties about induced land use change effects, net greenhouse gas saving potential, and economic costs. The code is in GAMS, general algebraic modeling language. NOTE: Column 3 is titled "BAU" in "merged_BAU.gdx", "merged_RFS.gdx", and "merged_CEM.gdx", but contains "RFS" data in "merged_RFS.gdx" and "CEM" data in "merged_CEM.gdx".

BEPAM↗

Redefining marginal land for bioenergy crop production

Abstract Marginal land has received wide attention for its potential to produce bioenergy feedstocks while minimizing diversion of productive agricultural land from food crop production. However, there has been no consensus in the literature on how to define or identify land that is marginal for food crops and beneficial for bioenergy crops. Studies have used different definitions to quantify the amount of such land available; these have largely been based on assumed biophysical thresholds for soil quality and productivity that are unchanging over space and time. We discuss the limitations of these definitions and the rationale for considering economic returns and environmental outcomes in classifying land as marginal. We then propose the concept of “socially” marginal which is defined as land that is earning close to zero returns after accounting for the monetized costs of environmental externalities generated. We discuss a broad set of criteria for classifying land as socially marginal for food crops and suitable for bioenergy crops; with these criteria, this classification depends on spatially varying and time‐varying factors, such as climate and market conditions and policy incentives. While there are challenges related to identifying this marginal land, satellite and other large‐scale datasets increasingly enable such analysis at a fine spatial resolution. We also discuss reasons why landowners might choose not to convert bioenergy‐suitable land to bioenergy crops, and thus the need for policy incentives to support conversion of land that is socially beneficial for bioenergy crop production.

09 BIOMASS FUELS↗

Assessing Marginal Land Availability Based on Land Use Change Information in the Contiguous United States

Utilization of marginal land for growing dedicated bioenergy crops for second-generation biofuels is appealing to avoid conflicts with food production. This study develops a novel framework to quantify marginal land for the Contiguous United States (CONUS) based on a history of satellite-observed land use change (LUC) over the 2008–2015 period. Frequent LUC between crop and noncrop is assumed to be an indicator of economically marginal land; this land is also likely to have a lower opportunity cost of conversion from food crop to bioenergy crop production. We first present an approach to identify cropland in transition using the time series of Cropland Data Layer (CDL) land cover product and determine the amount of land that can be considered marginal with a high degree of confidence vs with uncertainty across the CONUS. We find that the biophysical characteristics of this land and its productivity and environmental vulnerability vary across the land and lie in between that of permanent cropland and permanent natural vegetation/bare areas; this land also has relatively low intrinsic value and agricultural profit but a high financial burden and economic risk. We find that the total area of marginal land with confidence vs with uncertainty is 10.2 and 58.4 million hectares, respectively, and mainly located along the 100th meridian. Only a portion of this marginal land (1.4–2.2 million hectares with confidence and 14.8–19.4 million hectares with uncertainty) is in the rainfed region and not in crop production and, thus, suitable for producing energy crops without diverting land from food crops in 2016. These estimates are much smaller than the estimates obtained by previous studies, which consider all biophysically low-quality land to be marginal without considering economical marginality. The estimate of marginal land for bioenergy crops obtained in this study is an indicator of the availability of economically marginal land that is suitable for bioenergy crop production; whether this land is actually converted to bioenergy crops will depend on the market conditions. Here, we note the inability to conduct field-level validation of cropland in transition and leave it to future advances in technology to ground-truth land use change and its relationship to economically marginal land.

54 ENVIRONMENTAL SCIENCES↗

Simulated Land Allocation, Nitrogen Use, and Nitrogen Loss in the Mississippi Atchafalaya River Basin for Various RFS2 (Renewable Fuel Standard) Policy Scenarios

Total nitrogen leaching rates were calculated over the Mississippi Atchafalaya River Basin (MARB) using an integrated economic-biophysical modeling approach. Land allocation for corn production and total nitrogen application rates were calculated for crop reporting districts using the Biofuel and Environmental Policy Analysis Model (BEPAM) for 5 RFS2 policy scenarios. These were used as input in the Integrated BIosphere Simulator-Agricultural Version (Agro-IBIS) and the Terrestrial Hydrologic Model with Biogeochemistry (THMB) to calculate the nitrogen loss. Land allocation and total nitrogen application simulations were simulated for the period 2016-2030 for 303 crop reporting districts (https://www.nass.usda.gov/Data_and_Statistics/County_Data_Files/Frequently_Asked_Questions/county_list.txt). The final 2030 values are reported here. Both are stored in csv files. Units for land allocation are million ha and nitrogen application are million kg. The nitrogen leaching rates were modeled with a spatial resolution of 5' x 5' using the North American Datum of 1983 projection and stored in NetCDF files. The 30-year average is calculated over the last 30 years of the 45 years being simulated. Leaching rates are calculated in kg-N/ha.

bioenergy crops↗

Water Quality Effects of Economically Viable Land Use Change in the Mississippi River Basin under the Renewable Fuel Standard

Demand for biofuel production driven by the Renewable Fuel Standard (RFS2) has coincided with increased land in corn production and increasing nitrogen (N) loss to the Gulf of Mexico. Diversifying cropland with perennial energy crops (miscanthus and switchgrass) may reduce N loss and improve water quality. However, the extent of these benefits depends on the mix of biomass feedstocks (corn stover, perennials) incentivized by the RFS2 and the extent to which energy crops displace N-intensive row crops. We developed an integrated economic-biophysical model to quantify the water quality impacts of three potential policy scenarios that provided corn ethanol at levels before the RFS2 (RFS1 baseline); 15 billion gallons of corn ethanol (corn ethanol only); or 16 billion gallons of cellulosic ethanol in addition to corn ethanol (corn + cellulosic ethanol). Our results showed that economically optimal locations for perennial energy crop production were distributed across idle cropland with lower intrinsic N loss than active cropland. We found stover removal incentivized by the RFS2 offset N loss benefits of perennial energy crops. Furthermore, this finding suggests that targeted incentives for N loss reduction are needed to supplement the RFS2 to induce displacement of N-intensive row crops with energy crops to reduce N losses.

54 ENVIRONMENTAL SCIENCES↗

Assessing the Returns to Land and Greenhouse Gas Savings from Producing Energy Crops on Conservation Reserve Program Land

Using land already enrolled in the Conservation Reserve Program (CRP) in the eastern region of the U.S. for producing energy crops for bioenergy while reducing land rental payments offers the potential for lowering the program costs, increasing returns to CRP landowners, and displacing greenhouse gas (GHG) emissions from fossil fuels. We develop an integrated modeling approach to analyze the combination of biomass prices and CRP land rental payment reductions that can incentivize energy crop production on CRP land and its potential to increase soil carbon stocks and displace fossil fuel emissions. Here, we find that conversion of 3.4 million ha in the CRP can be economically viable at a minimum biomass price of 75 Mg –1 with full CRP land rental payment or at 100 Mg –1 with 75% of this land rental payment; this conversion can result in savings of 0.52 and 1.25 billion Mg CO 2 -eq in life-cycle emissions through the displacement of energy-equivalent fossil fuels and coal-based electricity, respectively, and an additional 0.11 billion Mg CO 2 -eq soil carbon sequestration relative to the status quo, with CRP left unharvested over the 2016–2030 period. The soil carbon debt due to the transition from unharvested CRP land to energy crops is short-lived and more than offset by the reduction in fossil fuel emissions. The net discounted benefits from producing energy crops on CRP land through a reduced need for government payments to maintain existing enrollment, higher returns to CRP landowners, and the value of the reduction in GHG emissions could be as high as 16–30 billion by using them for cellulosic biofuels to displace gasoline and 35–68 billion by displacing coal-based electricity over the 2016–2030 period if biomass prices are 75–125 Mg –1 and land rental payments are reduced by 25%.

54 ENVIRONMENTAL SCIENCES↗

BEPAM Model Code and CABBI Simulation Results for "Assessing the Returns to Land and Greenhouse Gas Savings from Producing Energy Crops on Conservation Reserve Program Land"

This dataset contains BEPAM model code and input data to the replicate the results for "Assessing the Returns to Land and Greenhouse Gas Savings from Producing Energy Crops on Conservation Reserve Program Land." The dataset consists of: (1) The replication codes and data for the BEPAM model. The code file is named as output_0213-2020_Complete_daycent-agversion-[rental payment level]%_[biomass price].gms. (BEPAM-CRP model-Sep2020.zip) (2) Simulation results from the BEPAM model (BEPAM_Simulation_Results.csv) * Item (1) is in GAMS format. Item (2) is in text format.

biomass price↗

BEPAM Model Code and CABBI Simulation Results for "The Economic and Environmental Costs and Benefits of the Renewable Fuel Standard"

This dataset contains BEPAM model code and input data to replicate the outcomes for "The Economic and Environmental Costs and Benefits of the Renewable Fuel Standard". The dataset consists of: (1) The replication codes and data for the BEPAM model. The code file is named as output.gms. (BEPAM-Social cost model-ERL.zip) (2) Simulation results from the BEPAM model (BEPAM_Simulation_Results.csv) * Item (1) is in GAMS format. Item (2) is in text format.

Cost-Benefit Analysis↗