Biomass Input Research Articles

Biomass inputs drive agronomic management impacts on soil health

Numerous conservation and regeneration practices are recognized as effective strategies in the management of soil health (SH), a critical factor for ensuring the sustainability of food production systems. Despite their acknowledged importance, the multifaceted impacts of these practices often lead to confounding effects, and reliance on generic categorization of agronomic practices often falls short in portraying the drivers of SH. We advocate for a paradigm shift from a label-centric approach to one rooted in processes. Our study underscores the pivotal role of aboveground biomass cycling as an indicator for assessing the potential of agronomic management practices to instigate shifts in carbon balances, and, consequently SH. Drawing on soil physical, biological, and chemical SH data from three Uruguayan long-term experiments on Pampas region Mollisols we (i) present quantitative evidence of the importance of evaluating SH through biomass inputs, and (ii) illustrate the applicability of the proposed framework for evaluating different scenarios of land management for the region. Management-induced variations in aboveground biomass inputs accounted for 50 % of the observed changes in a composite soil's physical and biological SH index and helped explain the inconsistent effect of management practices. Raising the SH Index by ten points required an increase in biomass inputs of over 50 Mg ha⁻¹. Based on this concept, substantial enhancements in SH can be made by narrowing yield gaps and intensifying cropping sequences over many years. The benefits of practices such as increased crop diversification, integration of perennial and cover crops, or reduced tillage in promoting SH depend in part on their ability to augment biomass production. This nuanced understanding underscores the importance of aligning agronomic strategies with the fundamental processes driving SH dynamics.

Vegetation degradation reduces aggregate associated carbon by reducing both labile and stable carbon fraction in Northeast China

Vegetation changes can affect soil organic carbon (SOC) content and storage by altering the inputs of plant biomass and the catabolism and anabolism of soil microorganisms. However, influence of vegetation degradation on aggregate associated carbon fractions and the contribution of different aggregates to total SOC in bulk soil remains poorly understood. In this study, undisturbed soil samples were collected from three types of grassland in Songnen grassland: an undegraded grassland (LEY, Leymus chinensis), a moderately degraded grassland (CHL, Chloris virgata), and a severely degraded grassland (SUA, Suaeda heteroptera). Three soil aggregates including macroaggregate (> 0.25 mm), microaggregate (0.053–0.25 mm) and silt and clay fraction (< 0.053 mm) were separated using wet sieving. Contents of total SOC, soil labile and stable carbon in bulk soil and different soil aggregates were measured. Compared with LEY, the mean weight diameter and geometric mean diameter under the degraded vegetation communities reduced by 39.42 % and 28.47 %, respectively. The reduction in SOC contents in bulk soil, macroaggregate, microaggregate and silt and clay fraction resulting from vegetation degradation was 49.81 %, 26.00 %, 76.17 % and 43.65 %, respectively. Under the degraded vegetation communities, contents of soil labile and stable carbon in bulk soil (45.73 % and 52.61 %, respectively), macroaggregate (17.38 % and 31.61 %, respectively), microaggregate (77.83 % and 74.18 %, respectively), and silt and clay fraction (21.20 % and 53.45 %, respectively) were significantly lower than those under LEY. The contribution of macroaggregate, microaggregate and silt and clay fraction to total SOC was 13.27 %, 23.61 % and 63.12 %, respectively. The contribution of soil aggregates to total SOC following vegetation degradation reduced by 53.63 % for microaggregate, but increased by 47.10 % for silt and clay fraction. These findings collectively indicate that vegetation degradation reduces the aggregate associated carbon content by reducing both labile and stable carbon fraction in Songnen grassland, and sustainable vegetation restoration strategies are need to enhance soil carbon storage in Northeast China.

Increasing plant species diversity benefits soil protein accumulation in a subtropical forest

Abstract Protein, derived from plant and microbial residues, constitutes a significant portion of soil nitrogen or organic carbon pool and plays a crucial role in determining soil nitrogen and carbon sequestration. Though diversifying plant species has been regarded as a promising strategy for promoting soil nitrogen or organic carbon accumulation during vegetation restoration or afforestation, how increasing plant species diversity (PSD) would influence soil protein pool remains unknown. We selected 45 plots covering a natural gradient of PSD, which was reflected by the Shannon index and varied from 0.15 to 3.57, in a subtropical karst forest. The major objective was to investigate the impact of increasing PSD on soil protein abundance, with soil protein depolymerization rate and multiple biotic and abiotic variables being measured to explore the underlying mechanism. The relative abundance of soil protein, that is proportion in soil organic matter varied between 24.1 and 34.0% with an average of 29.2 ± 2.3% across the 45 plots. Soil protein abundance increased on average by 1.56% with each unit of PSD increase. Nevertheless, soil protease activity, protein depolymerization rate and microbial amino acid uptake rate all significantly (p &lt; 0.05) decreased as PSD increased. The mechanism underlying the increase of soil protein abundance in response to higher PSD included three aspects, that is stimulating microbial biomass and subsequent microbial residue input to the soil, promoting mineral protection of soil protein via elevating levels of soil exchangeable calcium and magnesium, and decreasing soil protease activity and protein depolymerization due to aggravated soil microbial phosphorus limitation. Synthesis and application: Our study suggests that increasing PSD is an efficient way to promote soil protein accumulation. Given that protein is a major component of soil nitrogen or organic carbon pool, diversifying plant species during vegetation restoration or afforestation would hence benefit soil nitrogen and organic carbon sequestration.

Soil carbon stocks in temperate grasslands reach equilibrium with grazing duration

Lost soil organic carbon (SOC) in degraded grasslands can be restored via the ‘grazing exclusion’ practice, but it was unknown how long (# of years) the restoration process can take. A synthesis of four decades of studies revealed that grazing exclusion increased SOC stocks in the topsoil (0–0.30 m) by 14.8 % (±0.8 Std Err), on average, compared to moderate-to-heavy grazing (MtH); During which SOC stock increased steadily, peaked in Year 18.5, and then declined. At peak, SOC stock was 42.5 % greater under grazing exclusion than under MtH due to 100.4 ± 4.2 % increase in aboveground biomass and 80.3 ± 33.5 % increase in root biomass. Grazing exclusion also increased soil C:N ratio by 7.6 % while decreasing bulk density by 9.4 %. Grazing exclusion could be ceased 18.5 years after initiation of grazing exclusion as plant biomass input balances carbon decomposition and SOC equilibrium occurs then additional benefits start diminishing.

Impact of future scenarios of climate change on lignin dynamics in soil: A case study in a Mediterranean savannah

Lignin is an abundant and recalcitrant biopolymer of major relevance as soil organic matter (SOM) component playing a significant role in its stabilization. In this work, a factorial field experiment was established, where three climatic treatments (W, warming; D, drought; W + D, warming + drought), mimicking future climate change scenarios were installed over five years in a Mediterranean savannah “dehesa”, accounting for its landscape diversity (under the tree canopy and in open grassland). A combination of analytical pyrolysis (Py-GC/MS) and the study of biogeochemical proxies based on lignin monomers is used for the direct detection of lignin-derived phenols and to infer possible shifts in lignin dynamics in soil. A total of 27 main lignin-derived methoxyphenols were identified, exhibiting different patterns and proportions, mainly driven by the effect of habitat, hence biomass inputs to SOM. An accelerated decomposition of lignin moieties –(exhibited by higher LG/LS and Al/K + Ac ratios)– is particularly exacerbated by the effect of all climatic treatments. There is also an overall effect on increasing lignin oxidation of side chain in syringyl units, especially under the tree canopy due to the alteration in biomass degradation and potential stimulation of enzyme activities. Conversely, in open grassland these effects are slower since the microbial community is expected to be already adapted to harsher conditions. Our findings suggests that climate change-related temperature and soil moisture deviations impact soil lignin decomposition in dehesas threatening this productive Mediterranean agroecosystem and affecting the mechanism of soil carbon storage.

China's dietary transition and its impact on cropland demand for sustainable agriculture

China's rapid economic development and urbanization have significantly shifted dietary patterns, increasing stress on cropland. This study addresses the need to quantify cropland demand under different dietary scenarios using the latest consistent, balanced, and physical Food and Agriculture Biomass Input–Output dataset for China (FABIO-CHN) dataset, which offers the highest sectorial resolution for agricultural products. Employing an environmentally extended multi-regional input-output (EE-MRIO) analysis, we estimated domestic cropland demand driven by various dietary patterns, including food consumption away from home and food waste. We found that most dietary patterns would increase China's domestic cropland demand except the EAT-Lancet diet and the Japanese diet, ranging from −7.0 Mha to 55.2 Mha. However, the cropland footprint demand for meat and grain consumption would decrease for all scenarios, with values between −44.8 Mha and − 5.8 Mha for meat consumption while −12.2 Mha and − 3.3 Mha for grain consumption. The current average diet in China aligns more closely with the Japanese or Mediterranean diet. However, changes in cropland demand would vary from province due to diverse dietary structures. For instance, the per-capita cropland footprint is highest in Tibet and Qinghai due to traditional meat-rich diets. Our findings highlight the critical need for region-specific dietary guidelines and contributions to global sustainability challenges such as agricultural land expansion, and food security. While shifting toward more plant-based diets like the EAT-Lancet or Japanese diet could mitigate cropland stress, tailored policies considering regional dietary habits and promoting sustainable agricultural practices are essential for supporting China's dietary transition and sustainable cropland use.

Comparative multi-aspect study of two scenarios and optimization of the biomass-based cogeneration system integrated with the carbon capture and utilization technology

Combined Heat and Power (CHP) system based on bio-energy is an energy-saving and environment friendly way to utilize energy, but in the background of the "carbon peaking and carbon neutrality" strategy, ensuring low-carbon operation of CHP systems becomes imperative. In this paper, we introduce two distinct CHP system scenarios based on post-combustion carbon capture technologies: a syngas-based gas turbine cycle CHP system (scenario 1) and a biogas-based steam turbine cycle CHP system (scenario 2). Then, a techno-economic evaluation has been conducted to investigate their performance under varying operational conditions of heating and power load, as well as carbon capture technology. The findings reveal that, given the same biomass input rate, the syngas-based CHP system yields superior energy and economic outcomes. To simultaneously mitigate CO2 emissions and reduce electricity costs, a process of multi-objective optimization is employed. This optimization endeavor also focuses on maximizing the overall exergy efficiency. Consequently, scenario 1 experiences substantial improvements in performance metrics. Notably, the overall energy and exergy efficiencies reach 17.32 % and 14.58 % respectively. Additionally, the power and heating load are estimated at 2.58 and 2.17 MW correspondingly. The levelized cost of electricity and heating are assessed at 30.55 USD/MWh and 36.05 USD/GJ, respectively, coinciding with a reduction in CO2 emissions to 98.27 kgCO2/MWh.

Real-world waste dispersion modelling for benthic integrated multi-trophic aquaculture.

In real-world situations, marine fish farms accommodate multiple fish species and cohorts within the farm, leading to diverse farm layouts influenced by cage dimensions, configurations, and intricate arrangements. These cage management practices are essential to meet production demands, however, farm-level complexities can impact model predictions of waste deposition and benthic impact near fish cages. This is of particular importance when the cages are used for integrated multi-trophic aquaculture (IMTA) with benthic feeders, where this waste not only affects environmental conditions but also provides a potential food source. The Cage Aquaculture Particulate Output and Transport (CAPOT) model incorporated multiple species, cohorts, and cage arrangements to estimate waste distribution from a commercial fish farm in the Mediterranean between October 2018 and July 2019. This spreadsheet model estimated dispersion for individual fish cages using a grid resolution of 5 m x 5 m. The study categorized discrete production periods for each fish cage every month, aligning with intermittent changes in biomass and food inputs due to different cage management practices throughout production. This approach facilitated the use of detailed input data and enhanced model representativeness by considering variations in cage biomass, food types, settling velocities, and configurations. Model outputs, represented in contour plots, indicated higher deposition directly below fish cages that varied monthly throughout fish production cycles. Deposition footprints reflected changes in cage biomass, food inputs, and farm-level practices reflecting this real-world scenario where aquaculture does not follow a production continuum. Moreover, cohort dynamics and cage movements associated with the cage management practices of the fish farm influenced the quantity and fate of wastes distributed around fish cages, revealing variability in deposition footprints. Clearly, these findings have important implications for the design of benthic IMTA systems, with species such as sea cucumber and polychaetes. Variability in waste deposition creates challenges in identifying where the benthic organisms should be placed to allow optimal uptake of waste to meet their food requirements and increase survivability. Evidently, models have an important role to play and this study emphasizes the need for representative input data to describe actual food inputs, cage biomass changes, and management practices for more representative farm-scale modelling and essentially to improve particulate waste management. To effectively mitigate benthic impacts through IMTA, models must quantify and resolve particulate waste distribution and impact around fish farms to maintain a balanced system with net removal of wastes. Resolving farm-level complexities provides vital information about the variability of food availability and quality for extractive organisms that helps improve recycling of organic wastes in integrated systems, demanding a more representative modelling approach.

Root growth dynamics and biomass input of four over-wintering herbaceous crops in boreal conditions

Root growth of winter wheat (Triticum aestivum L.), winter rye (Secale cereale L.), red clover (Trifolium pratense L.), and timothy (Phleum pratense L.) was recorded to evaluate the environmental potential of over-wintering crops in a Nordic agroecosystem. In a field experiment on Aquic Haplocryoll soil, root intensities (number of roots/area) were measured to 50 cm depth by minirhizotron microvideo camera technology over a two -year period (21 recording sessions). At anthesis, root biomass and morphological parameters were measured by destructive soil sampling and image analysis of washed roots. Winter cereal roots reached 50 cm depth as soon as the autumn of the seeding year. For both post-seeding years, timothy roots developed the most intensively in spring, while red clover had higher root intensity than timothy in late autumn. At anthesis, the crops were ranked timothy &gt; red clover &gt; winter wheat &gt; winter rye according to root length density, surface area density, and biomass. Based on S:R ratios, red clover appears to offer the most intense carbon sink at 0–60 cm soil depth. Over-wintering crops had living roots in the subsoil both in late autumn and early spring, indicating potential to plant available nutrient uptake outside the growing season of annual crops.

Optimum Stochastic Allocation for Demand Response for Power Markets in Microgrids

This research incorporates an electricity market model based on a stochastic allocation of distributed resources and the analysis of an optimal demand response for a smart microgrid. This research develops a methodology that allows the application and comparison of various demand-response mechanisms and the analysis of the differences between them and the case of no-demand response, emphasizing economics, environmental care, demand curves, and other factors. By enabling more active participation by residential users of the smart microgrid, these demand-response methods help to flatten the demand curve and support the goals set by the electricity market model. Both conventional and non-conventional generators compete in the electricity market, with renewable energy sources preferred to encourage green generation. Conventional generators are required to supply electricity gradually, starting with the lowest pollution level. In addition, conventional generators are compensated for dispatch, system reliability, and availability. In addition, random variables are used in this study to predict initial load, solar radiation analysis, and biomass input before resources are optimized to meet demand.

Biochar from de-oiled Chlorella vulgaris and its adsorption on antibiotics

Abstract High-performance biochar was prepared using de-oiled Chlorella vulgaris biomass as the raw material and KOH as the modifying activator. The properties of the biochar as an adsorbent for the removal of tetracycline (TC) and enrofloxacin (ENR) were investigated under different conditions by varying the amount of the Chlorella vulgaris de-oiled biomass (DB) input. The surface structure and physicochemical properties of different Chlorella vulgaris biomass charcoal (CBC) samples were studied and compared, and the best adsorption performance of the biomass charcoal was obtained when DB = 7. Through orthogonal analysis, it was determined that the optimal adsorption condition of CBC 7 on TC was 0.004 g (pH 3), which resulted in a removal rate of 96.45% and a maximum adsorption capacity of 241.1363 mg g−1, and on ENR was 0.004 g (pH 7), which resulted in a removal rate of 100% and a maximum adsorption capacity of 256.3326 mg g−1. The results of the kinetic fitting show that the adsorption of TC and ENR by CBC 7 was consistent with the pseudo-secondary kinetic equation. The maximum adsorption capacities can reach 299.8974 and 352.6736 mg g−1. Langmuir and Freundlich adsorption isotherm models were used to describe the adsorption equilibrium of TC and ENR by CBC 7. The results show that the adsorption of TC and ENR are in accordance with the Langmuir isotherm.

Mathematical Modeling Approach to the Optimization of Biomass Storage Park Management

This paper addresses the critical issue of managing biomass parks, a key component in the shift towards sustainable energy sources. The research problem centers on optimizing the management of these parks to enhance production and economic viability. Our aim was to bridge the gap in current research by developing and applying mathematical models tailored for biomass park management. The study commenced by constructing a basic model based on assumptions such as uniform biomass and steady input rates. Progressing from this initial model, we explored sophisticated control strategies, including Pontryagin’s maximum principle and dynamic programming, and employed numerical methods to tackle the nonlinearities and complexities inherent in biomass management. Our approach’s scope extended to predicting and managing biomass flow, highlighting each method’s distinct advantages. The simple model laid the groundwork for understanding, while optimal control techniques revealed the system’s intricate dynamics. The numerical methods provided practical solutions to complex equations. We found that while each method is beneficial on its own, their combined use can significantly improve decision-making in biomass park management. This research emphasizes the importance of aligning the chosen method with specific operational challenges and desired outcomes for optimal efficacy, offering both theoretical insights and practical applications in the field of renewable energy management.

Thermodynamic analysis of small-scale polygeneration systems producing natural gas, electricity, heat, and carbon dioxide from biomass

Agricultural greenhouses are still heavily dependent on fossil fuel-based products despite the abundant residual biomass at their disposal. This paper presents two novel decentralized systems that can convert biomass simultaneously into synthetic natural gas (SNG), electricity, useful heat, and a CO2-rich stream. To do so, the electricity and H2/O2 production features of reversible solid oxide cells (RSOCs) are exploited. A steam dual fluidized bed (DFB) gasifier is used in the first proposed system, while the second one adopts a simpler oxygen/steam-blown downdraft gasification approach. Thermodynamic simulations using Aspen Plus software reveal that the total polygeneration process efficiency could reach 86.6%, with a CO2 generation capacity exceeding 275g per kilogram of biomass input. If not used inside the greenhouse atmosphere to enhance crop growth, this high-purity CO2 stream could be sequestered/liquefied to render the process carbon negative. The flexibility of the polygeneration systems is investigated through parametric analysis, where maximum SNG efficiencies that are on par with large-scale plants are obtained. The possibility of storing surplus electricity from intermittent sources as chemical energy in SNG is also highlighted.

Peatland restoration pathways to mitigate greenhouse gas emissions and retain peat carbon

Peatlands play a crucial role in the global carbon (C) cycle, making their restoration a key strategy for mitigating greenhouse gas (GHG) emissions and retaining C. This study analyses the most common restoration pathways employed in boreal and temperate peatlands, potentially applicable in tropical peat swamp forests. Our analysis focuses on the GHG emissions and C retention potential of the restoration measures. To assess the C stock change in restored (rewetted) peatlands and afforested peatlands with continuous drainage, we adopt a conceptual approach that considers short-term C capture (GHG exchange between the atmosphere and the peatland ecosystem) and long-term C sequestration in peat. The primary criterion of our conceptual model is the capacity of restoration measures to capture C and reduce GHG emissions. Our findings indicate that carbon dioxide (CO2) is the most influential part of long-term climate impact of restored peatlands, whereas moderate methane (CH4) emissions and low N2O fluxes are relatively unimportant. However, lateral losses of dissolved and particulate C in water can account up to a half of the total C stock change. Among the restored peatland types, Sphagnum paludiculture showed the highest CO2 capture, followed by shallow lakes and reed/grass paludiculture. Shallow lakeshore vegetation in restored peatlands can reduce CO2 emissions and sequester C but still emit CH4, particularly during the first 20 years after restoration. Our conceptual modelling approach reveals that over a 300-year period, under stable climate conditions, drained bog forests can lose up to 50% of initial C content. In managed (regularly harvested) and continuously drained peatland forests, C accumulation in biomass and litter input does not compensate C losses from peat. In contrast, rewetted unmanaged peatland forests are turning into a persistent C sink. The modelling results emphasized the importance of long-term C balance analysis which considers soil C accumulation, moving beyond the short-term C cycling between vegetation and the atmosphere.

Chemical extraction of chitin from American lobster (Homarus americanus) shells optimized through response surface methodology

Chitin extraction from the shells of American lobsters (Homarus americanus) was optimized through the use of response surface methodology (RSM). The demineralization step was optimized to minimize the ash content of shell samples and the deproteination step was optimized to minimize the protein content of the chitin product. At a laboratory scale, one set of optimized conditions for the demineralization step was 7.35 % w/w acetic acid at a 40 mL/g of powdered lobster shell ratio for 15 min; this lowered the ash content from 39.62 % to 0.41 ± 0.08 %. A set of optimized conditions for the deproteination step at a similar scale was 4 % w/w sodium hydroxide at a 43 mL/g demineralized shell ratio heated to 95 °C for 83 min. These conditions were indicated to entirely remove protein from the resultant chitin. Average yields under optimized conditions were 23.43 ± 1.75 % for demineralization and 30.33 ± 0.02 % for deproteination, though a demineralization reaction with larger biomass input had a higher yield at 40.31 %.

Snag dynamics and surface fuel loads in the Sierra Nevada: Predicting the impact of the 2012–2016 drought

Forest die-backs linked to extreme droughts are expected to increase as the climate dries and warms. An example is the 2012–2016 hotter drought in California that induced widespread tree mortality in the Sierra Nevada, California. The sudden increase in snags (i.e., standing dead trees) raised immediate concerns about their impact on wildfire hazard and longer-term questions about their effect on ecosystem structure and function. We quantified the likely progression of snag fall and fuel succession following the recent extensive mortality event in the southern Sierra Nevada mixed conifer forest. Our results used data from a long-term demography study to project trends in surface fuel loads at three study sites in Yosemite, Sequoia and Kings Canyon national parks. In the short term (2017–2021), fine woody debris and litter + duff significantly increased across all three sites (>145 % and >55 %, respectively); coarse woody debris increased significantly at one site (48.6 %); and total fuel loads increased significantly at two of the three sites (38 % and 69 %). Snag longevity increased with size, with the relationship varying by species. Yellow pine was a notable outlier: size played a small role in influencing its fall rates. Overall, species-specific snag fall rates in the southern Sierra Nevada were 20 % to 40 % slower than previously reported. By 2040, projected median cumulative inputs of biomass from future snag fall range from 49.4 Mg ha−1 to 136.1 Mg ha-1across our three sites, which exceeds the amounts currently present (47.17–89.97 Mg ha−1) and is well above estimates of historical coarse woody debris amounts in the Sierra Nevada (17.7 Mg ha -1). These results provide a robust empirical basis to refine the snag fall algorithm in vegetation simulation models. Options to manage the impact of extreme number of snags and their large surface combustible biomass include salvage operations and prescribed burning, with both methods having operational, financial, and legal limitations that need to be considered.

The positive effect of plant diversity on soil carbon depends on climate

Little is currently known about how climate modulates the relationship between plant diversity and soil organic carbon and the mechanisms involved. Yet, this knowledge is of crucial importance in times of climate change and biodiversity loss. Here, we show that plant diversity is positively correlated with soil carbon content and soil carbon-to-nitrogen ratio across 84 grasslands on six continents that span wide climate gradients. The relationships between plant diversity and soil carbon as well as plant diversity and soil organic matter quality (carbon-to-nitrogen ratio) are particularly strong in warm and arid climates. While plant biomass is positively correlated with soil carbon, plant biomass is not significantly correlated with plant diversity. Our results indicate that plant diversity influences soil carbon storage not via the quantity of organic matter (plant biomass) inputs to soil, but through the quality of organic matter. The study implies that ecosystem management that restores plant diversity likely enhances soil carbon sequestration, particularly in warm and arid climates.

Biomass price as a key factor for the further development of biogas and biomethane use – Methodology and policy implications

Intentionally planted biomass is one of the important possible sources for biomethane production. The production cost of biomass plays a key role in both a farmer's decision to grow it and the efficiency of biomethane production. Unlike conventional agricultural crops, biomass grown for biogas or biomethane plants does not have a direct market price. The paper presents a methodology for determining the limit of biomass production price based on modelling lost revenue from planting conventional crops over the lifetime of the biogas or biomethane plant, considering local agrotechnical practices and soil and climatic conditions. The application of the methodology is demonstrated by providing maize biomass for a reference biogas plant and conditions of the Czech Republic. The production price of maize silage is in the range of 25.6–29.4 EUR/tFM for base line scenario of conventional crop prices. The increase in commodity prices in 2021 and 2022 leads to an increase in the biomass production price up to 34–43 EUR/tFM. The paper also discusses the influence of the biomass input price on the cost of biomethane production.

Soil carbon storage capacity of drylands under altered fire regimes

The determinants of fire-driven changes in soil organic carbon (SOC) across broad environmental gradients remains unclear, especially in global drylands. Here we combined datasets and field sampling of fire-manipulation experiments to evaluate where and why fire changes SOC and compared our statistical model to simulations from ecosystem models. Drier ecosystems experienced larger relative changes in SOC than humid ecosystems—in some cases exceeding losses from plant biomass pools—primarily explained by high fire-driven declines in tree biomass inputs in dry ecosystems. Many ecosystem models underestimated the SOC changes in drier ecosystems. Upscaling our statistical model predicted that soils in savannah–grassland regions may have gained 0.64 PgC due to net-declines in burned area over the past approximately two decades. Consequently, ongoing declines in fire frequencies have probably created an extensive carbon sink in the soils of global drylands that may have been underestimated by ecosystem models.

Fast pyrolysis simulation via kinetic approach and multivariate analysis to assess the effect of biomass properties on product yields, properties, and pyrolyzer performance

Fast pyrolysis (FP) is the thermochemical conversion of biomasses and other carbonaceous materials into bio-oil (liquid), char (solid), and gas products to be used to generate heat, power, chemicals, and fuels of lower greenhouse gas emissions. Considering biomass properties highly affect the FP performance, this work used simulation and multivariate analysis tools to assess the effect of the composition of nine Brazilian biomasses on the FP energy demands, product yields, and bio-oil properties. A simulation, representing a pyrolyzer (480 °C, 1-s residence time), product recovery, and char combustion to meet FP energy demands, was built in Aspen Plus v.10 and validated against experimental data. A dataset correlating biomass compositions from 60 sources and FP outputs was obtained and analyzed, via two statistical methods, to detect similarities between feedstocks and correlate biomass inputs and process outputs. Hierarchical cluster analysis (HCA) separated the feedstocks into two main clusters: agricultural and woody biomasses. The main differences were associated with agricultural feedstocks having higher biomass H/C ratios, lower carbon and volatiles contents, and being of the CHL type (cellulose > hemicellulose > lignin), resulting in lower char and higher gas yields. As for correlations between inputs and outputs, HCA and principal component analysis (PCA) divided the parameters into five main groups: (i) biomass O/C ratio and cellulose content; (ii) bio-oil yield, heating value, and extractives content; (iii) biomass H/C ratio, hemicellulose content, and bio-oil quality metrics; (iv) ash content, char yield, and pyrolyzer heat duty; and (v) biomass lignin, volatiles, and heating value with gas yield and heating value. Several anticorrelations were also detected (e.g., bio-oil yield anticorrelated to bio-oil properties; char yield anticorrelated to gas yield). This work hopes to serve as a simplified roadmap for relationships between biomass properties and FP performance, providing guidelines for biomass selection for different bio-oil downstream applications and perspectives on future works on FP simulation.