Climate and air pollution impacts of generating biopower from forest management residues in California

California faces crisis conditions on its forested landscapes. A century of aggressive logging and fire suppression in combination with conditions exacerbated by climate change have created an ongoing ecological, economic, and public health emergency. Between commercial harvests on California’s working forestlands and the increasing number of acres the state treats each year for fire risk reduction and carbon sequestration, California forests generate millions of tons of woody residues annually—residues that are typically left or burned in the field. State policymakers have turned to biomass electricity generation as a key market for woody biomass in the hope that it can support sustainable forest management activities while also providing low-carbon renewable electricity. However, open questions surrounding the climate and air pollution performance of electricity generation from woody biomass have made it difficult to determine how best to manage the risks and opportunities posed by forest residues. The California Biomass Residue Emissions Characterization (C-BREC) model offers a spatially-explicit life cycle assessment framework to rigorously and transparently establish the climate and air pollution impacts of biopower from forest residues in California under current conditions. The C-BREC model characterizes the variable emissions from different biomass supply chains as well as the counterfactual emissions from prescribed burn, wildfire, and decay avoided by residue mobilization. We find that the life cycle ‘carbon footprint’ of biopower from woody residues generated by recent forest treatments in California ranges widely—from comparable with solar photovoltaic on the low end to comparable with natural gas on the high end. This variation stems largely from the heterogeneity in the fire and decay conditions these residues would encounter if left in the field, with utilization of residue that would otherwise have been burned in place offering the best climate and air quality performance. California’s energy and forest management policies should account for this variation to ensure desired climate benefits are achieved.


Introduction
Bioenergy is currently the most widely deployed renewable energy source in the world. About 47% of all renewable energy consumed globally in 2020 was bioenergy, about four times the combined contribution of wind and solar photovoltaics (REN 21 2021). In the electric power sector, solid biomass use nearly doubled between 2011 and 2021 (REN 21 2021), and is expected to grow significantly in coming decades (Reid et al 2020). In a 2018 Special Report, the Intergovernmental Panel on Climate Change reviewed 85 pathways to achieving a maximum warming of 1.5 • C and determined that biomass electricity systems employing carbon capture and sequestration (CCS) will need to make up a median of 26% of primary energy supply by 2050, in order to meet temperature targets (Rogelj et al 2018). We highlight these findings not to advocate for the growth of the biopower sector, but in recognition of the fact that it is likely to play a significant role in a carbon-constrained energy future, and should therefore be structured to ensure that it delivers the intended climate and environmental performance.
Concerns surrounding the climate impact of biopower, as well as other ecological impacts such as those on biodiversity and water resources, have led to a shift in attention toward the use of waste and residue materials, such as forest treatment residues rather than purpose-harvested whole trees. There is now an emergent interest in biopower as a component of sustainable forest management strategies, as it represents a use pathway for material that would otherwise decay in place or be subject to prescribed fire (Cabiyo et al 2021). This is particularly relevant in California, where a century of intensive logging and aggressive fire suppression in combination with conditions exacerbated by climate change have created an ongoing ecological, economic, and public health emergency (Baker et al 2020).
Almost a half-century of literature has established life cycle assessment (LCA) as an effective tool for evaluating the total impact of a product or action, and it is the tool commonly employed in shaping bioenergy policies to deliver climate benefit. However, there is sufficient variation in analytical methods and results from LCA studies of bioenergy from forest biomass 6 that its climate impact remains contentious (Creutzig et al 2015, Ter-Mikaelian et al 2015, Sterman et al 2018.
Most early LCAs of woody biopower made the simplifying assumption that CO 2 emissions from combustion of biomass ('biogenic' emissions) do not contribute to climate change because they represent a closed loop from biomass growth to combustion. Using this assumption, these studies typically found significant net reductions in greenhouse gas (GHG) emissions when biopower displaces fossil fuel-based energy. One meta-analysis of 94 LCA studies of biomass electricity systems found only one case study which accounted for the climate impact of biogenic CO 2 emission (Cherubini and Strømman 2011). This carbon neutral treatment of biogenic emissions is a continued practice in LCA research (Xu et al 2021) and government protocols (US EPA 2018). However, recent literature has called this assumption into question, pointing out that near-term emissions lead to increased climate forcing over policy-relevant time 6 The term 'biomass' refers generally to organic material, and specifically here to woody material that can be burned or otherwise converted to create electricity. Forest biomass residue typically includes the small-diameter treetops and branches that are not part of the merchantable portion of the whole tree. frames even if it is assumed that the CO 2 emitted is eventually re-sequestered in forest regrowth or, as in the case of residues, would have been emitted later by decay or wildfire (Buchholz et al 2016, Brack 2017, Cornwall 2017, Sterman et al 2018, Agostini et al 2020. Emerging from this literature is the consensus that the comprehensive approach to LCA for biopower from woody residues is to quantify emissionsincluding biogenic emissions-from both the use of residues and their counterfactual, or 'reference,' fate. While many recent studies have done so, these typically assume that all residues not removed for biopower will decay in place (McKechnie et al 2011, Jäppinen et al 2014, Gustavsson et al 2015, Giuntoli et al 2016, Madsen and Bentsen 2018 and that this decay will occur at a single rate regardless of residue type or location (Gustavsson et al 2015, Giuntoli et al 2016, Madsen and Bentsen 2018. This ignores the potential for in-field burning, either through a prescribed burn aimed at waste management or by wildfire (Ter-Mikaelian et al 2015, Buchholz et al 2016. In the few studies that have incorporated a burn counterfactual, it is typical to assume that the biomass is completely consumed through prescribed burning, leading to instantaneous emission of all carbon present, plus additional forcing from a fixed amount of methane and nitrous oxide release (Springsteen et al 2011, Miner et al 2014, Liu and Rajagopal 2019. This simplified approach fails to account for the fact that a fraction of biomass will remain unconsumed, and that some material undergoes thermally-driven changes that result in the formation of recalcitrant char material. Further, it does not capture the spatial and material-driven variation in combustion and decay dynamics (Ter-Mikaelian et al 2015).
This paper introduces the California Biomass Residue Emissions Characterization (C-BREC) model, a LCA tool that enables transparent accounting for the GHG and criteria air pollutant emissions associated with biopower generation from forest residues in the state of California under current technological, infrastructural, and ecological conditions. It improves on existing LCA approaches by capturing the significant spatial variability in life cycle emissions owing to differences in residue characteristics and climatic conditions which significantly influence decay processes and fire behavior. This aligns with an emerging recognition that geospatial techniques should play a key role in LCA of many bioenergy systems (van der Hilst 2018, Cabiyo et al 2021). Additionally, it is becoming increasingly clear that the timing of emissions must be considered in life cycle GHG accounting (Helin et al 2013, Buchholz et al 2016, Reid et al 2020. C-BREC applies time-explicit climate metrics in alignment with guidance put forth by United Nations Environment Programme and the Society for Environmental Toxicology and Chemistry (Levasseur et al 2016) and taken up by ISO standard for LCA (ISO 14067:2018(ISO 14067: 2018.

Methods
This section describes the methods used in the C-BREC model and the study presented here. More detail on every facet of the model, including its structure, assumptions, and underlying data, can be found in the C-BREC model framework available at http:// schatzcenter.org/cbrec/. To evaluate the emissions associated with a forest residue-to-electricity system, C-BREC requires that key system characteristics be specified. These include the location of residue generation, the type of forest treatment activity being conducted, the reference fate of unremoved biomass (pile burned, broadcast burned, or left in place), and key supply chain characteristics such as biomass removal level, location of biopower generation, and end-use energy conversion technology. For a given biomass energy supply chain, the C-BREC model quantifies the emissions associated directly with a 'use' case in which biomass residues are removed from the field for use in biopower generation, and a 'reference' case representing their fate if not removed. The net emissions of the biopower system is the difference between these two fates for the same material. C-BREC reports gross and net emission profiles over a 100 year period for GHGs and criteria air pollutants 7 . Pollutant species tracked include the following: carbon dioxide (CO 2 ), carbon monoxide (CO), methane (CH 4 ), nitrous oxide (N 2 O), volatile organic compounds (VOCs), oxides of nitrogen (NO x ), sulfur dioxide (SO 2 ), particulate matter (PM 10 and PM 2.5 ), and black carbon.

Characterization of biomass residue base
To characterize the residue base generated by California forest management, C-BREC categorizes forest treatments into 13 different types, capturing the large majority of forestry activities practiced in California. The treatment activities modeled are: • Clearcut.
For each of the above forest harvest activity types, we characterized the biomass residue-divided by species and size class-at 30 m spatial resolution. This modeling drew on tree list inventory data (Ohmann 2002), the US Forest Service's Forest Vegetation Simulator (Dixon 2022), and tree component ratios from (Jenkins et al 2003) and USFS (Bechtold and Patterson 2005). Using this dataset, C-BREC characterizes the residue base for any of the above treatments on any treatment polygon on California's forested landscape.

Scope and system boundary
A central assumption underpinning the C-BREC analytical framework is that the residual material being consumed is a true waste in that it would not have been used at all were it not mobilized for bioenergy. As such, it is assumed that the residues are not a driver of the primary forestry activity. Therefore, the utilization of the residues is not allocated any of the upstream emissions or sequestration associated with those activities, including any ongoing changes to forest carbon stock or flows that results from the primary treatment activity in question. This is aligned with the LCA practice of coproduct allocation on the basis of value fraction (Ardente and Cellura 2012). Since residues typically represent none of the net revenue derived from the primary forestry activity in today's wood products market (Swezy et al 2021), they are allocated none of those upstream emissions. Additionally, C-BREC intentionally does not account for avoided emissions from displaced electricity generation, which is a function of local and regional power system economics and policies. This enables direct comparison to other sources of electricity such as natural gas, solar, and wind.

Residue mobilization and use
Mobilization and use of biomass residues for electricity generation are characterized across the following three steps: • Collection and Processing: This includes emissions from fuel use associated with transporting equipment, gathering, handling, and loading the residues to the processing stage followed by comminution, hauling to a transfer point, then loading onto hauling equipment. Variable emissions are a function of parameters such as terrain steepness, residue density (tons per acre), and residue type. Removal of 30%, 50%, and 70% of total biomass resource are modeled. • Transportation: Round-trip travel of hauling processed residues between the transfer point and the power plant. C-BREC can allocate residue to any operational biomass power facility in the state, or to a notional facility given the proposed facility's location. The vehicle type used for a given harvest is a function of residue type, amount, and  (Olson 1963). However, unlike most other studies, we vary the rate of that decay across the landscape by species, size class and disposition, and climatic factors (Blasdel 2020).
We developed a database of decay constants that vary by species and size class from empirical studies and meta-analyses of decay (see e.g. Mackensen and Bauhus 1999, Yin 1999, Laiho and Prescott 2004, Weedon et al 2009. We then varied these baseline decomposition rates by size class and between scattered and piled material (Wagener and Offord 1972, Erickson et al 1985, Edmonds et al 1986. Finally, we applied a climate modifier for decay as a function of temperature and moisture based on a variation of the Demeter equations for climate effects (adapted from Foley 1995). All else being equal, decay is more rapid in smaller diameter material, in contact with the ground, and in wetter, warmer conditions. Detail on the modeling of decay can be found in Blasdel (2020).

Emissions from fire
Emissions from residue consumption by prescribed fire (pile burn or broadcast burning of scattered residue) and wildfires are modeled using the 'activity' fuels equations from the Consume software, version 4.2, created by the U.S. Forest Service (Prichard et al 2006). These equations provide estimates of fuel consumption for each size class, weighted by combustion phase: flaming, smoldering, and residual. The consumption estimates are then multiplied by emission factors specific to each pollutant species (e.g. CO, CO 2, CH 4 ) taken from the Bluesky modeling framework (Larkin et al 2010).
We model the emissions from a wildfire if one were to occur on the landscape in each of the next 100 years-both with and without woody residues left on the forest floor. Because it is not possible to predict when a fire will occur at a given site, the C-BREC model characterizes expected emissions from wildfire at each location in each year by taking the product of the emissions from a wildfire in that year and the probability of it occurring-each of which changes over time. This quantifies the expected annual emissions from wildfire on average, which is accurate at a landscape scale, but will necessarily differ from actual emissions at any specific site. Current and projected future wildfire probability across California is derived from the Cal-Adapt dataset (Westerling 2018).

Accounting for time
Biopower emissions occur in one pulse at roughly the time of primary treatment, whereas the emissions associated with the reference fate of the biomass may occur slowly over decades of biomass decay or in some future year via wildfire. Just as financial accounting must consider the time value of money in comparing expenses or revenues at different points in time, LCA can account for the 'time value' of emissions or sequestration over time in terms of their differing climate forcing effects over policy-relevant timescales.
The C-BREC model uses an 'emissions scenario' approach as described by the Intergovernmental Panel on Climate Change (Myhre et al 2013), elaborated on by (Aamaas et al 2012), and implemented in several publications related to the emissions profile of biomass energy (e.g. Giuntoli et al 2015). The result is a time-explicit 100 year absolute global warming potential (AGWP) profile that approximates the global aggregate radiative forcing associated with the emissions profile generated by the C-BREC model. The model uses these to calculate the mass of CO 2 equivalent (CO 2 e) emissions for reporting all emissions on a uniform basis-that is the equivalent mass of CO 2 emitted in year one that would yield the same AGWP as of year 100. This mirrors the approach taken by the Intergovernmental Panel on Climate Change in its calculation of CO 2 equivalent GWP values for different GHGs, except applied across time as well as across emission species. It also mirrors the approach taken in calculating GWPbio values for biogenic emissions (Liu et al 2017), but applied in a case-specific manner.

Results
This study applies the C-BREC model to the forest treatment activities conducted in California in the years 2016-2019 (figure 1) to investigate the net GHG and air pollution emissions that would have resulted had the residues of those treatments been mobilized for biomass electricity generation. Figure 2 demonstrates the relative contribution of the different emission sources to reference and use-case emissions and how these vary by collection and burn scenario as well as across different climate zones in California. Use-case emissions from residue mobilization and power generation are arrayed above the x-axis, where reference-case emissions from the counterfactual fate of the same biomass are arrayed below the x-axis as these represent 'negative' emissions, avoided by residue mobilization. The difference between the two cases is net emission from biopower generation and is indicated by the black point in each column.

Net climate impact varies greatly by reference fate and location
The carbon intensity of biopower generation from forest residues varies across system characteristics such as forest treatment type, residue disposition, transport distance, and power plant technology as well as geographic characteristics such as residue species, decay rate, and wildfire probability. To explore key variables, the following figures are based on C-BREC model runs assuming a uniform base case of biopower system configuration. Unless otherwise noted, these runs assume biopower to be generated 50 km from the feedstock source and using a combustion plant of statewide average efficiency without combined heat and power (CHP) capability. Emission time series are normalized to CO 2 e using 100 year GWP equivalencies as this is the common analytical framework in California policy structures.
While the actual fate of woody residues from recent forest treatments is not known, figure 3 displays the carbon intensity of the resultant electricity if they had been mobilized for power generation. It is clear that a major driver of the net carbon footprint of biopower from woody residues is the counterfactual (or 'reference') fate of the biomass-that is, whether it would have been burned or left to decay on site. This is because these figures are reported on a 100 year GWP basis, meaning that the delay in CO 2 emissions from residues left in the field to decay results in a lower CO 2 e in the reference case than if those same materials had been burned in place. The shapes of the distributions displayed in figure 3 are instructive. Scenarios in which only piled material would be collected, and a pile burn is therefore the reference fate, exhibit the least variability because pile burns are relatively uniform in their combustion dynamics. Broadcast burning and decay, on the other hand, are more sensitive to the spatial variability of climate and material-type.
In addition, long 'tails' are evident, especially for residues with no prescribed burn reference fate. These outlier treatments are predominantly those with very low total residue base and/or very low residue density. In such cases, the fixed emissions associated with mobilizing collection equipment to field locations can become a dominant source of emissions since they are distributed across a very small number of total kWh. These outlier cases are likely not logistically or economically viable for residue mobilization.
The variation within each of the curves displayed in figure 3 is driven by factors that vary geographically, such as the species and size class characteristics of the residue base as well as the climatic drivers of decay and wildfire emissions. Mapping the net emissions from biomass use (figure 4) allows these geographic variations to be assessed. Figure 4(a) displays the range in carbon intensity of biopower generation from forest treatment residue if that residue would otherwise have been subject to a prescribed burn. The spread in carbon intensity stems primarily from variation in emissions from prescribed burning owing to residue species, size class distribution, and climate (i.e. fuel moisture). Figure 4(b) displays the range in carbon intensity of biopower from residues of the same treatments if those residues would otherwise have been left in place, subject to decay and a subsequent wildfire. The spread in carbon intensity stems primarily from climatic and residue-type variables driving differing decay rates and wildfire probability.

Air quality impacts of mobilizing woody biomass
Beyond GHGs, we also investigated the net emissions of VOCs, carbon monoxide (CO), oxides of nitrogen  (NO x ), sulfur dioxide (SO 2 ), and particulate matter (both PM 2.5 and PM 10 ). We find that mobilizing forestry residues for biopower generation typically leads to a reduction in cumulative mass of emissions per ton of residue for most criteria air pollutants. Figure 5 shows this effect across four key criteria pollutants. The reduction in emissions is unsurprisingly strongest for biomass that would otherwise have been burned in the field. By removing this material to an engineered combustion chamber, and one where emissions are tightly controlled, the criteria pollutant emissions from a ton of biomass are significantly reduced compared to burning that same ton in the field. Where residues would otherwise have been left in the field to decay rather than subjected to a prescribed burn, mobilization for biopower generation generally yields slightly lower PM and VOC emissions over 10 years (because of probabilistic exposure to wildfire), but higher emissions of SO 2 and NO x , owing to fossil fuel consumption in the bioenergy supply chain.

Discussion and conclusions
We find that the primary drivers of climate and air quality performance of biopower from forest residuals are the counterfactual fate of the biomass in question and the climatic conditions of the landscape from which it was harvested. Biopower generated from residues that would otherwise have been burned on site consistently has a lower climate impact over 100 years than if those residues would otherwise have remained in place. In addition, mobilizing residues from regions-such as northwestern California and the western Sierra Nevada range-where a moist climate facilitates relatively rapid decay of residues left in place leads to lower-carbon biopower than residues from other regions. Finally, more efficient supply chains, where residues can be used nearby their source, by efficient generators, and without long-term open-air storage offer improved climate performance.
We find there to be almost no circumstances under business-as-usual conditions in which biopower from woody residues has a zero or net negative carbon intensity, with the possible exception of a facility employing efficient CHP or CCS, though these pathways are outside the scope of this analysis. The avoided emissions of CH 4 and N 2 O that can emerge from prescribed burns are typically more than offset by the fossil carbon emerging from a biopower supply chain, and the fact that prescribed burns do not combust the residue as completely as a biopower system can. However, biopower does not need to have a negative carbon footprint to offer a benefit in some circumstances; there are very few products or processes in existence that can claim a negative carbon intensity.
The air quality benefits offered by mobilizing residues that would otherwise have been burned in the field may be substantial and should be considered alongside climate, wildfire, and ecosystem impact.
While mobilization of residues typically reduces the total mass of particulates emitted per metric ton of residue, it also aggregates this emission to a point source, and one that may be closer to human populations. This paper does not evaluate the human exposure to these pollutants, nor the equity of distribution of that health burden across populations. This is an important area for future research that will be enabled by the modeling tools and datasets developed under this project.
This analysis does not account for carbon emissions or sequestration implications of the primary treatment activity that yields the woody residues in question. This is because under current market conditions, payment for residues is not driving those activities. If biomass removal is a necessary part of forest management activities that reduce fire risk or improve the carbon storage on the landscape or both, biopower that facilitates these activities by offering an outlet for residues could provide further climate benefit not quantified here. However, these benefits do not accrue uniquely to biomass electricity, future research and policy should consider alternate uses such as biochar, liquid fuels, or durable wood products that may provide stronger climate performance alongside or as an alternative to biopower generation.
Most policies that support biopower are predicated on the assertion that the pathways being promoted offer a climate benefit compared to a scenario in which this biopower was not produced. The C-BREC model has shown that the climate performance of biopower from forest residues is highly variable across supply chains, feedstock types, and geographies in California. It is therefore incumbent upon policymakers in California and elsewhere to design biopower and woody residue utilization policies that prioritize pathways offering the intended climate and/or other environmental and human benefits. For example, biopower supports under California's Bio-MAT and BioRAM programs, aimed at creating a market for residues from forest treatment activities, could be structured to ensure or to preferentially support supply chains that offer the most climate and/or air quality benefit. In addition, California's low-carbon fuel standard (LCFS) is structured to deliver a financial incentive to fuel producers based on the life-cycle climate impact of fuel pathways. LCFS evaluation of any pathways delivering transportation fuels derived from woody biomass should take into account the spatial and supply-chain variability in both reference and use-case emissions revealed by this analysis.
The C-BREC model can be useful in shaping the biomass energy system and other uses for woody residues, enabling activities to be targeted where they offer the greatest benefit. In particular, it can: • Identify the geographic locations and forest treatment types in which utilization of residues offers the greatest climate and air pollution benefit in order to structure incentives accordingly. • Aid in shaping residue mobilization and conversion supply chains to minimize emissions by identifying what improvements will offer the greatest life cycle emissions reduction potential. • Provide project-level analysis for policies aiming to reduce GHG emissions from California's forestlands and energy systems.
Future work can expand the findings and utility of this analysis by extending the C-BREC analytical framework. For example, using C-BREC's criteria pollutant emission profiles to evaluate human exposures would enable us to evaluate the human health burden associated with these emissions or the equity of the distribution of this burden. Expanding C-BREC to other end uses of woody biomass such as liquid fuels, biochar, bioenergy with CCS (BECCS), or durable wood products is ongoing, and will enable it to support integrated analysis and policy in the broader forest practice and wood products space.

Code implementation
The open-source C-BREC model is built using the R programming language and is available on GitHub. A limited version of the model is available for exploration via an interactive web tool. The web tool allows a user to identify a specific project area in California and specify the key project characteristics for the use and reference fates, producing a report of biomass residue harvested, electricity generation, and net emissions. Links to the webtool and the GitHub repository for the model code and can be found at schatzcenter.org/cbrec/.

Data availability statement
The data that support the findings of this study are openly available at the following URL/DOI: https://schatzcenter.org/cbrec. ongoing support of Melissa Hardy, Nico Harman, and Micah Harman.