Abstract:

Biofuels are an important part of reducing emission and mitigating the climate crisis. First generation biofuels are made from the edible parts of plants, while second generation biofuels (2G) are biofuels made from the non edible parts of plants. The use of both of these biofuels would leave no plant material left on the fields, which would harm the soil organic matter (SOM). In order to maintain the SOM we want to take the residues made from the 2G biofuels and put them back into the soil. We hypothesize that the processed biofuel residues will retain more soil organic carbon than the unprocessed source material. In order to determine this, residue characteristics were measured and the residues were added to soil and incubated, as respiration was monitored over time. Then a microbial biomass analysis was performed to determine the amount of carbon and nitrogen in the microbes and the soil. We found that the respiration rate is positively correlated with microbial carbon biomass. Overall, processed residues had a smaller amount of microbial carbon biomass than the unprocessed residues. This suggests that the processed material tends to store carbon more effectively than unprocessed source material.

Introduction:

Global climate change is continuing to worsen. In one of the best case scenarios, we will hit 1.5 degrees C of warming by 2025 and then drop rapidly if we take immediate action now. In order to do so, half of the future global energy supply needs to consist of energy derived from biomass. Currently it is around 10% (Riahi) This means there needs to be a significant growth in carbon dioxide removal technologies in order to reach negative emission. Biofuels can be considered a neutral or negative emission technology because they do not require fossil fuels.The impact of biofuels is influenced by the development of 2G biofuels, which is a key negative emission technology (Fields).  First generation (1G) biofuels are made up of edible plants such as corn. Second generation (2G) biofuels are made up of nonedible plant material, such as corn stover. There has been a growing interest in 2G biofuels but there has not yet been much commercial success. This is partially due to the issue with removing all of the plant material from the field, which impacts the soil organic carbon (SOC). Usually, the non edible parts of the crops are left on the field, which decompose and replenishes the SOC. It is crucial to maintain the SOC to support the crops and sequester carbon, as the SOC within the soil organic matter (SOM) is the largest terrestrial pool of carbon on earth, storing three times as much carbon as the atmosphere or terrestrial vegetation (Schmidt). But what if you could take the corn stover and process it into biofuel while producing a residue that you could add back into the ground to supplement the SOC? If that is the case, then you could use all parts of the crops for food and biofuels while maintaining the soil’s organic carbon. My hypothesis is that biologically processed residues will retain more SOC than unprocessed crop residues. Specifically, 2G biofuel residues will respire less carbon than corn stover.

Methods:

There are six treatments that are a subset of experiments by Wang (2023), and include four types of biofuel residues, corn stover (CS2, not used for biofuel production), and soil without anything added as a control. The four biofuel residues include anaerobically digested corn stover (AD2), and three kinds of high lignin fermentation byproduct (HLFB) from corn stover. The residues are added to a Palouse soil that previously grew wheat in Pullman, Washington. There are three replicates of the control and corn stover treatment and six replicates of each residue treatment. The residues were dried, milled, and incubated with soil for 135 days at 22-25 degrees C. Each substrate is measured for lignin, carbon percentage, and nitrogen percentage, and carbon respiration is measured throughout the incubation. Grams of dry soil were calculated by subtracting grams of water from the wet soil. Grams of water are determined by measuring the soil wet weight and then drying it and measuring the dry weight. 

In the lab, I determined the amount of carbon within the soil samples. In order to do so I needed to extract a solution from the soil. 10 mg of each wet soil sample was divided into a fumigated and non fumigated portion. The fumigated sample was fumigated with chloroform for 5 days in a vacuum-sealed container. Each sample was mixed with 40 ml K2SO4 and shaken for an hour. Then it was filtered through Whatman 52 filter paper into a specimen cup. 5 mL of this extract was added to a 40 ml vial with 35 mL of milliQ water. This solution was measured in a Sievers M5310 C Laboratory TOC (total organic carbon) Analyzer with a GE Autosampler along with TOC standards. These standards included carbon concentrations of 1 M, 2 M, 10 M, 20 M, 35 M, and 50M. Microbial biomass is calculated by subtracting the fumigated sample from the non fumigated. The remaining extract was collected in 50 mL tubes and given to Paul Zietz to measure nitrogen in the form of NH4+, NO3, and NO2- on a Lachat QuickChem 8500. The samples were measured in mg/L and were converted into mg/g of dry soil using Excel. 

Results:

Results are illustrated graphically in Figures 1-10. Figures were created in R, and an ANOVA test and a Tukey test were performed on the boxplots to determine significant differences, which is indicated by letters in Figures 1-4. Groups that do not share the same letter are statistically different (p-value < 0.05). Figure 1 shows CS2 and HLFB2 have significantly higher microbial biomass carbon (MBC) than the other treatments. AD2 has a significantly greater microbial biomass nitrogen (MBN) than other treatments (Figure 2). For TOC, the control is statistically different from CS2 and AD2, but these treatments are not significantly different from the HLFB series (Figure 3). HLFB1 has a significantly higher total nitrogen content than the rest of the treatments (Figure 4). 

The amount of microbial biomass carbon, a metric for the biomass of the microbes, are shown in relation to various residue characteristics. Scatter plots were made for residue characteristics and a regression analysis was performed to determine significance. Lines (or curves) of best fit were added for correlated variables if statistically significant (p-value < 0.05), with the R squared value also indicated to show how related the two variables are. There is a statistically significant increase of microbial biomass carbon with the increase of the percent of carbon respired (p-value = 3.267e-06, R-squared= 0.5552) (Figure 5). The amount of MBC increases with % carbon in the substrate increases, and then begins to level off at high % carbon values. This relationship is significant (p-value = 0.0003237, R-squared = 0.4121) (Figure 6). As the % nitrogen in the substrate increases, the MBC content decreases, showing a significant negative parabolic relationship (p-value = 0.0009139, R-squared = 0.3595 ) (Figure 7). There is a statistically significant relationship between the increase in microbial biomass content and the increase in the ratio of C:N (p-value = 4.976e-05, R-squared = 0.4973) (Figure 8). There is no significant correlation between microbial biomass carbon content and the amount of lignin in the substrate (p-value = 0.3484, R-squared = -0.0035) (Figure 9). While there does not appear to be a strong correlation between MBC and lignin: N, its p-value is less than 0.05 (p-value = 0.007596, R-squared = 0.2396 (Figure 10).

Figure 1: Microbial Biomass Carbon of each Treatment

The amount of carbon within the microbial biomass. CS2 and HLFB2 are significantly greater than the rest of the treatments. One replicate of AD2 had to be removed due to lab error.

Figure 2: Microbial Biomass Nitrogen of each Treatment

The amount of nitrogen in the form of nitrate and ammonium extracted from the microbial biomass. AD2 is significantly greater than the rest of the treatments.

Figure 3: Total Organic Carbon of each Treatment

This is the amount of carbon available in the soil that was not taken up by the microbes. The control is significantly different from CS2 and AD2, but not from the HLFB series. 

Figure 4: Total Nitrogen for each Treatment

The amount of nitrogen in the soil available to organisms in the form of ammonium and nitrate. HLFB1 has a statistically significantly greater amount of total nitrogen than the other treatments. 

Figure 5: Percent carbon respired vs MBC 

This is the percent carbon respired during incubation versus the microbial biomass carbon content. There is a significant relationship between the two variables as the amount of microbial biomass carbon increases, more carbon is respired.

Figure 6: MBC vs % Carbon in Substrate

The microbial biomass carbon content compared to the percentage of carbon in the residue substrate. There is a significant relationship, although nonlinear, between them; as the amount of carbon in the substrate increases, so does the amount of carbon in the microbial biomass, until it begins to level off.

Figure 7: MBC vs % Nitrogen in Substrate

The microbial biomass carbon content compared to the percentage of nitrogen in the residue substrate. There is a significant relationship between them; as the amount of carbon in the substrate increases, the amount of nitrogen in the microbial biomass decreases, and then begins to level off.

Figure 8: MBC vs C:N ratio in Substrate

The microbial biomass carbon content compared to the C:N ratio of the substrate. There is a significant relationship between them, as microbial biomass increases, so does the C:N ratio.

Figure 9: MBC vs Lignin of Substate

The microbial biomass carbon content versus the percentage of lignin in each of the substrates. There is no significant correlation between microbial biomass carbon content and the amount of lignin in the substrate.

Figure 10: MBC vs Lignin:N ratio of Substrate

The microbial biomass carbon content compared to the ratio of lignin to N in the substrate. There is a weak but significant relationship between them; as the Lignin:N ratio increases so does MBC.

Discussion:

The biologically processed residues had a statistically significant smaller microbial biomass than the unprocessed residues, with the exception of HLFB2. HLFB2 had a significantly greater MBC than the other processed residues and was statistically similar to the corn stover (Figure 1). Since MBC is a predictor of microbial biomass, this means that adding corn stover to the soil resulted in a similar amount of microbes as HLFB2. As shown in Figure 3, the corn stover has a greater amount of total organic carbon than HLFB2. The total organic carbon is the amount available in the soil for microbes to take up. This is the carbon that has been freed up by microbial enzymes but has not yet been taken up by the microbes. Since HLFB2 has less carbon available, over time fewer microbes will be able to grow than the corn stover. Therefore the microbial biomass of HLFB2 will plateau before the corn stover.

 AD2, the anaerobic digestate, has a significantly greater amount of nitrogen in its microbial biomass than the rest of the treatments (Figure 2). This may be related to its low C:N ratio, indicating that it is more processed and has a greater necromass (mass of dead microbes) (Figure 8). It also has a greater amount of % nitrogen in the substrate than the other treatments (Figure 7). However, in Figure 4 we see that HLFB1 has a significantly larger amount of available nitrogen than all other treatments. While HLFB1 does have a high amount of % nitrogen in the substrate and a low C:N value, it is not as dramatic as AD2 (Figure 7,8). Microbes concentrate nitrogen in their cells from the surrounding soil in a process called immobilization. This could be explained by AD2 having a greater amount of nitrogen immobilized in necromass, due to the differences in the biofuel production processes that made the residue. Anaerobic digestion is made from biogas, while the HLFB’s are made from biofuels.

As microbial biomass carbon increases, so does the percent of carbon respired. As MBC is a metric for microbial biomass, this can be interpreted as the greater the amount of microbes, the more carbon can be respired. The percent carbon in the substrate increases with increasing MBC until a point where it begins to level off (Figure 6). This makes sense because the amount of carbon in the substrate will lead to more carbon being able to be taken up by microbes, up until a point where other factors have a greater influence on how much carbon can be taken up, such as nitrogen. The percent of nitrogen in the substrate decreases as microbial biomass increases. This occurs because nitrogen is easy to break down, and more nitrogen is used up with greater microbial biomass. This will begin to level off because eventually the amount of microbial biomass content is more influenced by other factors. A lower C:N ratio means that the substrate is easier to decompose. While we would expect the easier decomposed substrates to have greater microbial biomass, we actually see an opposite trend to this. This is because the substrate has already been decomposed by the process of turning it into a biofuel, so this ratio represents how much processing occurred during biofuel production. The lower C:N ratio of around 10 is associated with necromass. The biofuel residues with a lower C:N ratio have undergone a greater amount of processing, have less decomposed material left in the residue, and therefore have a smaller living microbial biomass and a greater necromass.

Lignin is difficult for plants to decompose, which means where there is a higher lignin percentage, less processing is able to occur, and there would be a smaller microbial biomass. However, we do not see any significant correlation between the two (Figure 9). This is because the relationship is complicated by the processing that occurs in the formation of the biofuel. We have found that the more processing (represented by the C:N ratio) that occurs during biofuel formation, the lesser the microbial biomass (Figure 8). Therefore processing is a significant factor in microbial biomass, while lignin may not be. Since lignin is difficult to decompose and nitrogen is easier to decompose, as nitrogen increases and lignin decreases, the smaller the Lignin:N ratio and the easier it is to decompose, meaning it is a higher quality. This is suggested by the weak but significant (p<0.05) correlation between the two (Figure 10).  Since the nitrogen is an outcome of processing, the low lignin:N ratio indicates more processing, despite lignin not having any statistical significance. 

Conclusion:

We studied several residuals from biofuel production for their potential to respire carbon when returned to soil. The processed residues used in this experiment showed a significantly smaller microbial biomass and low respiration rate than the unprocessed residues, with the exception of HLFB2, which showed a similar level of MBC to an unprocessed residue. Because HLFB2 has a smaller amount of carbon available in the soil compared to unprocessed corn stover (CS2), HLFB2 will not be able to accumulate a greater microbial biomass over time. 

This study suggests that a high degree of processing during the production of biofuels generates residuals that tend to have low microbial biomass and respiration rate. The degree of processing is indicated by a greater amount of % nitrogen and a low C:N value in substrate;  with low C:N ratio corresponding to a greater necromass. We found that the greater the processing, the smaller the microbial biomass. With low respiration rate in the low C:N ratio substrate, more carbon is stored in the soil.

In summary, residues that undergo a greater amount of processing have a smaller microbial biomass, which means that less carbon is respired and there is a greater amount of necromass. Therefore more processing results in more carbon being kept in the soil. These results support with Michelles thesis, where she found that the unprocessed treatments respired more carbon quicker than the processed treatments. This effect was still found to be significant in the event of mass loss during biofuel production (Wang). 

Since this residue consists of high lignin byproduct and a large necromass, we may expect this residue to decompose slowly, being less available to plants and sequestering more carbon in the process. This would mean that biofuel residues would be most beneficial to be used for sequestering carbon in the field, but not quite as beneficial for nutrient availability for crops. However, there is a growing understanding of soil’s role in the ecosystem, and it is much a more complex system than researchers once thought. While we once thought that molecular structure alone controls SOM stability, it turns out that environmental and biological controls predominate. This means that components such as lignin were assumed to decompose slower and therefore would result in a more stable organic matter, when in fact, new research shows that lignin turns over more rapidly than the bulk of organic matter, while potentially labile compounds, the dominant constituents of microbial products, can exist for decades (Schmidt). These microbial products of decomposition thus promote a more stable SOM, and do so by promoting aggregation to minerals (Cotrufo). This means that our HLFB’s may not be quite so difficult to decompose as we once thought, and it is the microbial biomass which promotes a greater carbon sequestration. However, soil is a very complicated system, and it is difficult to draw conclusions by isolating a small system. It is important to be able to understand as many ecosystem connections as possible. This is why it is necessary to do in situ experiments in the field, where we not only measure the amount of microbial biomass and carbon respired from the soil, but we also look at decomposition rates of the various components of the residue.

Works cited

Cotrufo, M Francesca et al. “The Microbial Efficiency-Matrix Stabilization (MEMS) Framework Integrates Plant Litter Decomposition with Soil Organic Matter Stabilization: Do Labile Plant Inputs Form Stable Soil Organic Matter?” Global change biology 19.4 (2013): 988–995.

Michelle Wang, 2023, Returning Byproducts from 2nd Generation Biofuel Production to Soil Replenishes Lost Soil Organic Carbon, Dartmouth 

Riahi, K. et al. Mitigation pathways compatible with long-term goals. in (Cambridge University Press (CUP), 2022). doi:10.1017/9781009157926.005.

Schmidt, M. W. I. et al. Persistence of soil organic matter as an ecosystem property. Nature 478, 49–56 (2011).