Biochar greatly enhances methane oxidation in urban green roof substrate

Biochar greatly enhances methane oxidation in urban green roof substrate | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Biochar greatly enhances methane oxidation in urban green roof substrate Imrul Kayes, Mohammad Halim, Wenxi Liao, Md Rezaul Karim, Melanie Sifton, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8093549/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Green roofs are increasingly implemented in cities to manage stormwater and urban cooling, yet their potential role in greenhouse gas (GHG) mitigation remains unclear. Methane, a potent GHG, is only weakly oxidized by roof substrates, and ways to enhance this sink remain unexplored despite its significance at the city-scale. We report a long-term (2020–2024) field study on biochar effects on CH₄ fluxes in extensive Sedum green roofs, where biochar-amended modules (~5% v/v; 20 t ha⁻¹) maintained consistently higher CH₄ uptake, peaking in spring 2023 at nearly fivefold greater than controls (−1.91 ± 0.25 vs. −0.40 ± 0.10 nmol·m⁻²·s⁻¹). Notably, biochar did not increase CO₂ emissions, indicating enhanced CH₄ uptake without compromising carbon efficiency. Enhanced CH 4 uptake correlated with higher substrate moisture and H₂O flux, suggesting a moisture–evaporation co-regulated diffusivity mechanism facilitating microbial CH₄ oxidation, highlighting biochar as a scalable means to enhance climate-mitigation capacity of urban green infrastructure. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Climate sciences/Climate change/Climate-change mitigation green roofs biochar methane urban greenhouse gas fluxes urban green infrastructure nature-based solutions urban sustainability Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION Methane (CH₄), a potent greenhouse gas (GHG) with a short atmospheric lifetime yet strong warming potential, is a major driver of near-term climate forcing 1,2 . While agriculture and wetlands are the dominant biogenic sources, urban environments increasingly function as complex mosaics of CH₄ sources and sinks 3,4 . This dual role underscores the need to quantify CH₄ fluxes in urban green infrastructures and develop strategies to reduce sources while enhancing sinks. Green roofs are an innovative component of urban green infrastructures that have received considerable attention in recent years for multiple ecosystem services. Originally designed for stormwater management by retaining precipitation, they also improve energy efficiency, extend roof lifespan, enhance biodiversity, and help mitigate urban heat-island effects 5–7 . The potential climate benefits of green roofs through carbon sequestration are also significant, as both vegetation and the organic carbon embedded in green roof substrates are increasingly recognized as important carbon sinks within urban green infrastructure systems 8,9 . The capacity of green roofs to influence non-CO 2 GHG dynamics, particularly CH₄, has only recently begun to attract scientific attention 10 . While a growing body of research has examined their carbon sequestration potential, GHG fluxes from roof substrates remain a critical but underexplored component in assessing their net climate effects. In particular, studies on substrate GHG flux in extensive green roofs (typically with vegetation mats of Sedum or closely related Phedimus species) are limited, with only a handful addressing overall GHG fluxes and even fewer focusing specifically on CH 4 . A growing body of research highlights the importance of organic matter content in these systems because high–organic matter substrates, often used to enhance plant performance and water retention 11,12 , may also emit CH₄ at rates comparable to organic mulches 13 , highlighting the need to quantify the rate of flux and better understand the mechanisms regulating CH₄ exchange in these systems. In general, biogenic CH₄ flux is a balance between methanogenesis in strictly anoxic or strongly hypoxic microsites and methanotrophy, biological process of CH 4 oxidation, in oxic zones; both are influenced by microbial communities and soil physical and chemical properties 14,15 . Among them, moisture and temperature are dominant controls. In upland soils, CH₄ oxidation typically shows a hump-shaped response to soil water content, peaking at intermediate saturation and declining when soils are either too wet (limited O₂ diffusion) or too dry (microbial water stress) 16,17 . In green roof substrates, moisture and temperature have likewise been identified as the dominant physical drivers regulating CH₄ uptake 18,10 . Soil pH is also an important chemical control; while earlier studies suggested optimal methanotrophic activity near neutrality (pH 6.6–7.5) 19 , subsequent work has shown active CH₄ oxidation under both acidic and alkaline conditions 20,21 . Soil texture and structure modulate CH₄ fluxes primarily by altering gas diffusivity through changes in air‑filled porosity; accordingly, surface evaporation can indirectly influence CH₄ oxidation via moisture–diffusivity effects 22,23 . Because methanotrophs convert CH₄ to CO₂, a portion of CO₂ efflux can derive from subsurface CH₄ oxidation, and CH₄ and CO₂ fluxes may covary through both stoichiometric coupling and shared environmental drivers 24,25 . Moreover, evaporation and moisture together regulate gas diffusion dynamics in soil. High moisture reduces air-filled pore space, whereas evaporation promotes the formation of air-filled microsites within the substrate, thereby influencing gas diffusivity 26 . Consequently, a relationship between H₂O flux and other soil gases is expected. While soil physical and chemical properties regulate GHG flux, this regulation can be strongly seasonal, as episodic events such as spring freeze–thaw cycles in temperate regions have been found to influence biogenic emissions 27 . Because temperature is a dominant driver of biogeochemical cycles, quantifying CH₄ fluxes across seasons is essential. Given these controls, amendments that alter substrate properties should predictably modify CH₄ exchange, particularly in engineered systems such as green roof media, yet this remains unexplored. Green roof substrates are engineered to meet structural load limits, combining lightweight organic matter with porous inorganic aggregates such as expanded shale, clay, or crushed brick 28 . While these materials support drainage and plant survival, they are prone to compaction, which reduces porosity and water retention 29,30 , potentially altering microbial communities and CH₄ flux patterns. Rooftop exposure also increases evaporation, often requiring irrigation. Hailm et al. (2022) 10 found that irrigated green roofs exhibited greater CH₄ uptake than non-irrigated systems, demonstrating the role of substrate moisture in regulating fluxes. More broadly, GHG dynamics in green roofs appear strongly dependent on substrate properties, with vegetation might exerting an interactive influence. While green roof substrates generally emit CO₂, they function as weak CH₄ sinks, and potential means of strengthening this sink capacity remain largely unexplored. Biochar, a carbon-rich material produced by pyrolysis, has been shown to enhance CH₄ uptake in agricultural, forest, and urban soils 13,31–33 . However, its potential in green roof substrates remains untested, despite evidence that biochar improves plant performance, stormwater retention, and nutrient availability 34,35 . Its porous structure improves both water retention and aeration 36,37 , reducing compaction and maintaining drainage. By altering bulk density, electrical conductivity, and pH, biochar can create a stable and favorable environment for methane-oxidizing microbes. These properties make biochar a promising amendment for extensive Sedum green roofs, particularly where moisture and porosity limit gas exchange. Several studies have reported biochar’s benefits in promoting plant growth, enhancing stormwater retention, and increasing nutrient availability in green roofs 34,38,35 . Although biochar is highly recalcitrant, with carbon half-lives of centuries 39 , its labile fraction may transiently increase CO₂ release 40 , and its low density makes it susceptible to wind erosion on exposed roofs 41 , emphasizing the need for long-term evaluation. Urban areas now host more than half of the global population 42 , yet their contribution to global biogeochemical cycles remains poorly constrained. While natural soils are recognized as CH₄ sinks, urban ecosystems are often overlooked. Green roofs are widely promoted for stormwater retention, energy savings, and biodiversity, but their role in regulating GHG fluxes is rarely examined. Biochar is known to enhance soil carbon sequestration and stimulate CH₄ oxidation in terrestrial systems, but evidence for its function in green infrastructure remains scarce. A recent meta-analysis found that biochar generally improves ecosystem functions across green infrastructure types, including reduced CO₂ and N₂O emissions, though CH₄ responses were variable 38 . Most studies directly testing biochar–GHG interactions have been limited to constructed wetlands, where elevated CH₄ emissions are common 43,44 . Whether biochar can similarly modulate GHG dynamics in green roof substrates remains unknown. Demonstrating that biochar can transform green roofs into functional CH₄ sinks would reveal a new pathway for integrating climate mitigation into urban landscape design. In this study, we quantified, for the first-time, CH₄, CO₂, and H₂O fluxes across biochar-amended and control Sedum green roofs over a 5-year period. We hypothesize that biochar amendment will enhances CH₄ uptake in extensive green roofs by modifying substrate physicochemical properties. We further expect that this effect will be mediated by changes in substrate H 2 O and CO₂ fluxes, and while the direction of the effect will remain consistent over time, its magnitude will fluctuate seasonally. Results Biochar amendment strengthens CH₄ uptake across seasons Linear mixed-effects models (LMMs) showed that biochar treatment had a highly significant effect on CH₄ flux (F₁,₂₅₅ = 136.52, p < 0.001) in Sedum green roof substrates. The main effect of season was not significant (F₁₁,₂₅₅ = 0.59, p = 0.84); however, the interaction between treatment and season was significant (F₁₁,₂₅₅ = 3.67, p < 0.001), indicating that the effect of treatment on CH₄ flux varied across seasons (Table S2). CH₄ fluxes from Sedum green roof substrates showed clear treatment and seasonal variations across measurement years (Figure 1; Table S3). During the initial measurement years (2020–2021), CH₄ uptake was modest in both treatments, but by summer 2021 biochar-amended modules exhibited significantly stronger uptake than those without biochar ( p < 0.001). From 2022 onward, biochar consistently enhanced CH₄ uptake relative to the no-biochar treatment across all seasons (all p < 0.05). The strongest treatment differences occurred in spring 2023, when CH₄ uptake in biochar-amended Sedum modules reached –1.91 ± 0.25 nmol·m⁻²·s⁻¹ compared with –0.40 ± 0.10 nmol·m⁻²·s⁻¹ in modules without biochar ( t = –5.84, p < 0.001). Significant treatment contrasts also occurred in fall 2021 ( p = 0.02), summer 2022 ( p = 0.001), and spring 2024 ( p = 0.007), confirming the persistence of enhanced CH₄ oxidation in biochar-treated substrates. Across the five-year period, CH₄ fluxes exhibited strong temporal structure, with uptake peaks in spring and fall and weaker uptake in mid-summer, reflecting concurrent variation in substrate moisture and temperature (supplementary Figure S2). By 2024, although CH₄ uptake had slightly weakened relative to 2023, biochar-treated modules still maintained higher uptake rates (–1.26 ± 0.17 nmol·m⁻²·s⁻¹) than the no-biochar controls (–0.03 ± 0.19 nmol·m⁻²·s⁻¹; p < 0.001) across all seasons (Figure 1; Table S3). Bare substrate fluxes were also measured but excluded from formal statistical analyses due to lower replication; their descriptive trends, showing minimal CH₄, CO₂, and H₂O exchange relative to vegetated modules, are summarized in supplementary Tables S3–S5. CO₂ flux varies seasonally with limited biochar effect Results from LMMs showed that biochar treatment had no significant effect on CO₂ flux (F₁,₂₂ = 0.32, p = 0.58). In contrast, the main effect of season was highly significant (F₁₁,₂₃₃ = 37.66, p < 0.001), indicating substantial seasonal variation in CO₂ flux. The interaction between treatment and season was also significant (F₁₁,₂₃₃ = 1.99, p = 0.03), suggesting that treatment effects on CO₂ flux varied modestly across seasons (Table S2). CO₂ fluxes substrates varied significantly across seasons and years, with moderate emissions during early establishment (2020–2021) and pronounced temporal fluctuations thereafter (Figure 2a; Table S4). Biochar treatment did not exert a consistent effect on CO₂ flux ( p > 0.05 for most comparisons), though significant seasonal interactions were evident (Figure S3). In fall 2022, modules without biochar exhibited the highest CO₂ emissions (15.7 ± 1.2 µmol·m⁻²·s⁻¹), significantly exceeding those from biochar-amended modules (11.4 ± 1.6 µmol·m⁻²·s⁻¹; p = 0.01). By spring 2023, both treatments showed comparable fluxes (~9–10 µmol·m⁻²·s⁻¹; p > 0.3), and this pattern persisted through 2024, with modest seasonal peaks in spring and fall (Figure 2a; Table S4). Overall, CO₂ fluxes followed a strong seasonal pattern, peaking in spring and fall and declining in summer, with interannual variability. Biochar increases evapotranspiration through enhanced surface flux Results from LMMs showed that biochar amendment had a highly significant effect on H₂O flux in Sedum roof substrates (F₁,₂₂ = 29.00, p < 0.001). The main effect of season was also highly significant (F₁₁,₂₃₄ = 12.62, p < 0.001), indicating strong seasonal variation in evapotranspiration. In addition, the interaction between treatment and season was significant (F₁₁,₂₃₄ = 3.63, p < 0.001), suggesting that the influence of treatment on H₂O flux varied across seasons (Table S2). H₂O fluxes exhibited strong seasonal and interannual variation, with consistently higher fluxes in biochar-amended modules than in those without biochar (Figure 2b; Table S4). During the establishment years (2020–2021), H₂O fluxes were already elevated in biochar-treated modules (e.g., summer 2020: 564 ± 25 µmol·m⁻²·s⁻¹) compared with controls (306 ± 3 µmol·m⁻²·s⁻¹; p = 0.05). The largest treatment differences occurred in spring 2023, when mean fluxes in biochar modules (1211 ± 192 µmol·m⁻²·s⁻¹) exceeded those without biochar (528 ± 63 µmol·m⁻²·s⁻¹; p < 0.001). Fluxes generally peaked in spring and summer and declined in fall (Figure S4). By 2024, both treatments showed reduced fluxes, though biochar-amended modules maintained higher evapotranspiration (390 ± 178 µmol·m⁻²·s⁻¹) than controls (170 ± 27 µmol·m⁻²·s⁻¹; p = 0.03). Overall, biochar addition enhanced H₂O fluxes throughout the study period, especially during warm and moist seasons when evaporative potential was highest. CH₄ uptake covaries with CO₂ and H₂O fluxes CH₄ uptake increased significantly with both CO₂ flux ( R² = 0.05, p < 0.01) and H₂O flux ( R² = 0.16, p < 0.001) (Figure 3). These positive relationships were stronger in biochar-amended modules, which consistently exhibited greater CH₄ uptake than those without biochar. Linear regressions between substrate moisture, temperature, EC, and pH with CH₄ flux are shown in Supplementary Figure S5. Integrated pathway analysis reveals controls on GHGs fluxes The piecewise SEM showed an adequate fit (Fisher’s C = 3.15, df = 4, p = 0.53) and explained 53% of the variance in CH₄ flux and 42% in CO₂ flux, with smaller proportions for intermediate variables (moisture = 0.11; temperature = 0.03; EC = 0.14; pH = 0.01; H₂O flux = 0.11) (Figure 4). Biochar addition directly enhanced CH₄ uptake (β = –0.82) by increasing substrate moisture (β = 0.65, p < 0.05) and reducing EC (β = –0.67, p < 0.05). Higher substrate moisture, in turn, promoted H₂O flux (β = 0.17) but suppressed CH₄ and CO₂ flux (β = –0.35 and β = –0.16, respectively). Temperature positively influenced H₂O (β = 0.17) and CO₂ flux (β = 0.24) while inhibiting CH₄ uptake (β = –0.22). H₂O flux exerted a strong positive effect on CO₂ flux (β = 0.48) and a weaker negative effect on CH₄ flux (β = –0.22). Substrate pH had minor but significant negative effects on both CO₂ (β = –0.16) and CH₄ flux (β = –0.12). Discussion Over five years of measurements on extensive Sedum green roofs, biochar amendment substantially enhanced CH₄ uptake compared with non-amended substrates. Uptake varied seasonally and with substrate age, supporting the hypothesis that biochar promotes conditions favorable for methanotrophy in organic-rich media. Biochar also increased surface evaporation but did not elevate CO₂ emissions. The sustained enhancement of CH₄ uptake across seasons was closely associated with higher substrate moisture and greater H₂O flux, suggesting improved gas diffusivity and sustained microbial CH₄ oxidation in aerobic substrate layers. The CH₄ uptake rates in biochar-amended substrates (up to –1.9 nmol m⁻² s⁻¹) were higher than those typically reported for agricultural soils (–0.1 to –1.0; 15 ) and urban soils (often negligible to –1.0; 45 ), but lower than temperate forest soils (–2.5 to –4.0; 46,47 ), highlighting the potential of biochar-amended green roofs to function as significant CH₄ sinks within urban infrastructures. Only a handful of studies have measured GHG fluxes from green roof substrates, most reporting minimal CH₄ uptake 10 . While biochar application in urban green infrastructure has gained attention, its effect on CH₄ flux in extensive Sedum systems had not been previously tested. Prior research in agricultural and urban soils largely focused on short-term experiments, where biochar generally reduced CH₄ emissions 13,33 , but evidence for long-term persistence has been scarce. Our study provides the first demonstration that biochar can enhance the CH₄ sink strength of green roof substrates over the long term, adding a new climate co-benefit to the ecosystem services of urban green infrastructures. Our results showed that biochar enhanced CH₄ uptake primarily through direct effects, while significant indirect effects were mediated by higher substrate moisture and H₂O flux, which together created conditions favorable for methanotrophy. Previous studies across paddy fields 33 , urban soils 13 and landfills 48 similarly found biochar increasing CH₄ uptake, attributed to its porous structure and large surface area that provide methanotroph habitat and improve aeration. Our findings align with this mechanism, as biochar’s high porosity facilitates gas exchange and supports microbial activity conducive to CH₄ oxidation. The structural equation model revealed a strong relationship between substrate moisture and CH₄ uptake, and between biochar and substrate moisture, indicating that biochar improved water retention and thereby enhanced CH₄ oxidation. Soil moisture strongly regulates biogeochemical processes: excessive moisture limits air-filled pore space and creates anaerobic microsites, while low moisture imposes water stress on methanotrophs 16,17 . Maximum CH₄ uptake rates have been recorded in forest and grassland soils at 20–60% saturation 49–51 . While green roof substrates are unique, we found moisture generally remained within this optimal range in both treatments but was consistently higher in biochar-amended modules, indicating that biochar maintains conditions favorable for CH₄ uptake under dry conditions. We observed a positive relationship between substrate temperature and CH₄ uptake (Figure 4), suggesting that higher temperatures stimulated methane oxidation. Structural equation modeling indicated that biochar exerted a positive but non-significant effect on temperature, possibly due to its low albedo increasing heat absorption, offset by greater evaporative cooling. This thermal balance resembles prior observations of biochar effects on green roof microclimates 34 . We observed non-significant relationships between CH₄ oxidation and substrate EC but a significant effect of pH (Figure 4). The average pH in biochar-treated modules (6.57 ± 0.04 to 7.53 ± 0.05; Table S5) was near-neutral, within the optimal range (6–8) for CH₄ oxidation 52 . We also found a significant relationship between CH₄ and H₂O flux (Figure 4), with biochar consistently enhancing H₂O flux across seasons (Figure 2), suggesting that greater evaporation was linked to increased CH₄ oxidation. These pathways can be attributed to higher moisture availability maintained in biochar-amended modules. In rooftop environments with high atmospheric demand, biochar likely enhances capillary continuity and pore connectivity 36 , improving gas diffusivity in oxic layers and facilitating microbial CH₄ oxidation 23,53 . This dual effect, greater water storage with improved gaseous exchange, appears to have enabled sustained moisture and enhanced oxygen diffusion in biochar-rich substrates, stimulating long-term CH₄ uptake. Thus, we propose that biochar-mediated CH₄ oxidation in green roofs results from coupled moisture–evaporation dynamics rather than a linear response to water content. Biochar application did not significantly increase CO₂ emissions (Figure 2a). The tested green roof substrate was already rich in organic matter, and any transient CO₂ pulse from labile carbon likely occurred before monitoring (modules installed in 2019; measurements began 2020). CO₂ efflux showed strong seasonal patterns, higher in spring and summer, lower in fall, with temperature exerting a significant positive effect 54,55 . Seasonal variation of CO 2 flux also reflects Sedum root respiration during active growth 56 . We found a significant positive relationship between CO₂ and CH₄ flux, implying that part of the CO₂ efflux originates from CH₄ oxidation by methanotrophs 52,57 , in addition to microbial and root respiration. A similar positive link between H₂O flux and CH₄ uptake further supports evaporation–aeration co-regulation of methanotrophy. During Stage-I evaporation, capillary continuity sustains moisture while surface water removal increases air-filled porosity, creating oxic micro-layers with enhanced gas diffusivity 53 . Because CH₄ oxidation occurs near the surface above wetter layers, even slight increases in air-filled pores can strongly stimulate methanotrophic activity 23 . Collectively, these findings demonstrate the interconnected biophysical processes through which biochar enhances CH₄ uptake in engineered substrates. Extending this mechanistic understanding into practical design applications is an important next step. We tested one biochar type (sugar maple, fixed dosage), but biochar properties vary widely with production conditions. Establishing dose–response relationships across feedstocks will help identify thresholds where benefits plateau or unintended effects arise. Future work should link flux responses to microbial population dynamics using molecular approaches such as functional gene assays. Beyond these methodological gaps, biochar should be considered within a multi-objective substrate design framework that integrates stormwater retention, plant performance, and GHG mitigation. While this study focused on Sedum systems, future research should evaluate biochar in native plant roofs, where diverse root–microbe interactions may further influence CH₄ sink strength and ecosystem functions. Our findings also connect to urban wood-waste management. Converting forestry residues into biochar for engineered substrates could provide durable carbon storage and broader ecosystem co-benefits compared to conventional mulching. To summarize, CH₄ flux in pre-grown Sedum green roofs was generally low, but biochar significantly enhanced CH₄ uptake, with effects persisting for up to four years. Although uptake declined slightly in the fifth year, it remained higher than in unamended substrates. Biochar-mediated CH₄ enhancement was driven by improved substrate moisture and gas diffusivity, emphasizing the role of aeration-evaporation interactions in sustaining methanotrophy. These findings show that a single biochar amendment can maintain elevated CH₄ oxidation over multiple years while improving hydrological function. More broadly, biochar’s demonstrated the enhancement of CH 4 oxidation, highlights its potential to integrate GHG mitigation with stormwater and plant performance benefits, advancing green roofs as multifunctional, climate-resilient urban infrastructure. Methods Green roof design and substrates The experiment was installed in Fall of 2019 at the Green Roof Innovation Testing Laboratory (GRIT Lab II) at 1, Spadina Crescent at University of Toronto’s downtown St. George Campus, in Toronto, Ontario, Canada (Fig. S1a). GRIT Lab II’s green roof modules were sized 1.83 m ×1.83 m, with 15 cm substrate depth and slope of 2°. While GRIT Lab II consists a total of 50 roof modules, the focus of this study was only on 24 green roof modules cultivated over the course of the trial using pre-grown stonecrop Sedum mats. The Sedum mats were dominated (> 95%) by orange stonecrop [ Phedimus kamtschaticus (Fisch. & C.A.Mey.) 't Hart], with small amounts of white stonecrop [ Sedum album L.), and tasteless stonecrop [ Sedum sexangulare L.]. The green roof Sedum mat system used is hereinafter referred to as Sedum modules. The experimental green roof media was a lightweight high-organic green roof mix (“Eco-blend” supplied by Bioroof Systems Inc., Burlington, Canada) with an organic matter content of 75 ± 2% (mean ± SE) 35 . The biochar amendment was created using sugar maple ( Acer saccharum L.) sawdust pyrolyzed at ~700 ◦C, with 10–15 minutes of residence time (Haliburton Forest and Wildlife Reserve, Canada). Biochar and substrate properties are presented in supplementary Table S1. Experimental design Green roof modules were arranged in a completely randomized design with one factor (biochar present vs. no biochar) and 12 replicates per level (n = 24). Two non-vegetated bare-substrate modules of identical dimensions were also included for reference. Greenhouse gas (GHG) flux measurements were conducted from summer (June–August) 2020 through fall (September–November) 2024 , spanning five growing seasons. Measurements for spring (March–May) 2022 and summer 2023 were not collected due to logistical constraints and were therefore excluded from the formal analysis. Biochar was incorporated into each treated green roof module at a rate of 20 t ha⁻¹ (equivalent to 5.4% v/v), an application level previously identified as optimal for enhancing plant performance 58 . Initially, the Sedum modules were dominated by Phedimus kamtschaticus , comprising over 95% of total cover, with minor contributions from Sedum sexangulare L. and Sedum album L. (hereafter referred to as Sedum modules). Each green roof module received uniform irrigation of 20–30 L of municipal water twice weekly during the growing season. This irrigation regime was designed primarily to sustain plant survival during dry periods and generally did not generate any surface runoff from the modules. Data collection In each replicate green roof module, one PVC collar (10 cm diameter, 10 cm height) was inserted into the substrate in early May 2020, prior to initiating seasonal gas flux measurements conducted from Summer 2020 through Fall 2024. For non-vegetated bare substrate references, three collars were installed per module to increase the statistical power for subsequent analyses. The collars were inserted 3–5 cm deep into the substrate to prevent leakage, following the method of Jovani-Sancho et al. (2018) 59 , and placed at least 30 cm away from the module's edge to avoid interference from plant roots. Any aboveground plant material rooted within the collar was trimmed off at the time of installation and subsequent gas flux measurements to eliminate aboveground plant mediated gas fluxes. For gas-exchange measurements, we used Los Gatos Ultraportable Greenhouse Gas Analyzer (UGGA: Los Gatos Research, San Jose, CA, USA) connected to a pressure-equilibrated chamber (LI-8100-102 opaque survey chamber, volume 854.2 cm³; LI-COR Environmental, Lincoln, NE, USA) in a closed dynamic system with a nominal flow rate of 0.5 L/min. This setup provided real-time measurements of CH 4 , CO 2 , and water vapor (H 2 O), with respective accuracies of 2, 300, and 100 ppb, using off-axis integrated cavity output spectroscopy. Substrate temperature was recorded adjacent to each sampling location at a depth of ~5 cm using a Flip Thermometer (PC, Toronto, Canada; Model 21010083) with a precision of 0.5 °C. The substrate moisture content was measured at a depth of ~5 cm using a CS-SM2 soil moisture sensor (accuracy: ±2.5%) (CredoSense Inc., Toronto, Canada). Measurements were scheduled to avoid precipitation and irrigation in the preceding 48 hours, mitigating transient gas flux effects related to the "Birch effect" 60,61 . Each measurement session lasted approximately three minutes, with data logged at one-second intervals. A subset of substrates was sampled during every gas measurement event to determine pH and EC (electrical conductivity) in laboratory. The pH and EC were determined in a 1:2 suspension of substrates in deionized water at room temperature using a pH/mV Meter (IQ Scientific Instruments, USA) and an Orion Star A112 benchtop conductivity meter (Thermo Scientific, USA), respectively. In each case, triplicate measures were conducted. Flux Calculations Output files from the LGR gas analyzer were post-processed using R version 4.3.2 (R Core Team 2024) using an algorithm to estimate flux rates ( dc/dt ) of concentrations of CH 4 , CO 2 and H 2 O 10,62 . First, a “dead band” of initial 30s was eliminated from each measurement, which is affected by artifacts triggered by the closing of the chamber 63,62 . After this exclusion, we applied a straightforward algorithm using the Pearson correlation coefficient ( r ) between concentration and time, focusing specifically on CO 2 concentration data to identify the optimal time window (50–60 seconds) for flux calculations. The time window yielding the highest ‘ r’ value for CO 2 was selected for both CO 2 and CH 4 gases in subsequent flux calculations. We selected CO 2 -based time window for CH 4 because CO 2 fluxes tend to exhibit less noise than CH 4 , allowing potential leakage or pressure artifacts to be more easily detected from CO 2 data than from CH 4 . Figure S1 shows example slope calculation from the raw data stream followed by algorithm described above. To determine dc/dt for calculating CO 2 and CH 4 fluxes, we used either linear or non-linear regression 64 depending on the statistical properties of the concentration data. If the quadratic coefficient of the concentration data was not statistically significant (p > 0.05), we used linear regression to determine dc/dt and calculated the flux as LI-COR, (2015) 65 : Statistical analysis Statistical analyses were conducted to evaluate the effects of biochar treatment and measurement period (season × year) on CH₄, CO₂, and H₂O fluxes across the study years. To evaluate these effects, a linear mixed-effects model (LMMs) was applied using the “ lmer ” function from the lme4 package in R 66 . Fixed effects included biochar treatment, season and their interaction ( treatment × season ). To account for repeated measurements, Collar was included as a random intercept, while season nested within year was included to capture temporal dependence across years. Residual diagnostics were inspected to verify normality and homoscedasticity assumptions. The significance of fixed effects was evaluated using Type III Analysis of Variance (ANOVA) with Satterthwaite’s method for estimating denominator degrees of freedom, implemented through the “ anova ” function in the “ lmerTest ” package 67 . To further explore significant fixed effects and interactions, pairwise post hoc comparisons were performed using estimated marginal means (EMMs) obtained from the fitted linear mixed-effects models with the “ emmeans ” package in R. Treatment contrasts were evaluated within each season, and Sidak adjustment was applied to control for multiple comparisons (α = 0.05). This model-based approach retains the random-effects structure, providing statistically robust and interpretable pairwise inferences. Non-vegetated bare-substrate modules were excluded from the formal statistical analysis due to the limited number of replicates, which precluded adequate statistical power; their results are therefore presented descriptively only. Structural equation modeling We used structural equation modeling (SEM) to investigate direct and indirect effects of biochar treatment , substrate properties, and CO 2 flux regulate CH₄ flux . Because measurements were repeated within collars and across seasons, we first fit a piecewise SEM in R (v4.4.0) using linear mixed-effects models ( lme4 ) with random intercepts for collar and season to account for non-independence 68–70 . Treatment was coded as an exogenous binary predictor ( 0 = No biochar , 1 = biochar ). Moisture , temperature , EC , and pH were specified as mediators; H 2 O, CO₂ flux and CH₄ flux were endogenous responses. The hypothesized model specified that biochar affected substrate moisture, temperature, electrical conductivity (EC), and pH, which in turn influenced H₂O flux, CO₂ efflux, and CH₄ flux. Based on preliminary independence tests, we incorporated additional pathways where biologically justified, including H 2 O flux ~ EC and H₂O flux ~ CO₂ efflux, reflecting physical controls on evaporation and microbial respiration. CH₄ flux was modelled as a function of substrate properties, CO₂ efflux, and H₂O flux. All component models were fit as linear mixed-effects regressions ( lme4 package) with random intercepts for sampling collar and season to account for repeated measurements. Model adequacy was evaluated with Fisher’s C statistic, where non-significant values (p > 0.05) indicate consistency between model and data. Standardized path coefficients, marginal R² values, and graphical representations were used to interpret the final model. Declarations Data availability The source data used to generate all graphs and charts presented in this study are publicly available via the Scholars Portal Dataverse repository at: https://doi.org/10.5683/SP3/CANT7Q Acknowledgements This research was supported by the NSERC-CREATE Discovery Grant awarded to S.C. Thomas . The authors gratefully acknowledge Professors Jennifer Drake and Liat Margolis , co-principal investigators on the broader research project, for their valuable leadership and logistical support. We are grateful to Malaika Mitra , Katie Monat , Jennifer Barrett , Liam Douglas , and Jovana Shrestha for their assistance in fieldwork. We thank Tony Ung for his support in maintaining the green-roof experiment. We also acknowledge Haliburton Forest and Wildlife Reserve Ltd. , Gro-Bark Inc. , and Bioroof Systems Inc. for providing materials and product information. Authors contribution IK: Conceptualization, Data collection, Data Curation, Software, Formal analysis; Writing- Original draft. MAH: Data collection, Software, Writing-editing and reviewing; WL: Data collection, Writing-editing and reviewing; MRK: Data collection, Writing-editing and reviewing; MS: Data collection, Writing-editing and reviewing; SCT: Conceptualization, Writing-editing and reviewing, Validation, Administration, Fund acquisition, Supervision. Competing interests The authors declare no competing interests. References Mar, K. A., Unger, C., Walderdorff, L. & Butler, T. Beyond CO2 equivalence: The impacts of methane on climate, ecosystems, and health. Environ. Sci. Policy 134 , 127–136 (2022). Saunois, M. et al. The Global Methane Budget 2000–2017. Earth Syst. Sci. Data 12 , 1561–1623 (2020). Vollrath, C., Xing, Z., Hugenholtz, C. H., Barchyn, T. E. & Winter, J. 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Mediation analysis with structural equation models: Combining theory, design, and statistics. Eur. J. Soc. Psychol. 45 , 460–481 (2015). Gunzler, D., Chen, T., Wu, P. & Zhang, H. Introduction to mediation analysis with structural equation modeling. Shanghai Arch. Psychiatry 25 , 390–394 (2013). Lefcheck, J. S. piecewiseSEM: Piecewise structural equation modelling in r for ecology, evolution, and systematics. Methods Ecol. Evol. 7 , 573–579 (2016). Additional Declarations There is NO Competing Interest. Supplementary Files Supplementarymaterials.docx Biochar greatly enhances methane oxidation in urban green roof substrate Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8093549","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":544631390,"identity":"583a48f5-d46b-4c01-ae82-ae8c03d2e2aa","order_by":0,"name":"Imrul Kayes","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFUlEQVRIiWNgGAWjYBACNhDxgCEBRDE+YGCQkCFOSwJEC7MBUAsPkAbLSODVB9XCBlJFWAuf2NlnEgkMafIGx9ufVd2oseBhkMg/+Lii4k4dPwPzww/YHCadbgbUkmO44cwZs9s5x4AOk0hmNjxz5pmEZAObMTar2KTT2IBaKhg33Mhhu53DBtbCJtnYdljC4AAPVtfBtNhvuP/8WXHOP1QtzD9wa8lJ3HCDwYw5tw1VCxsOW5gtEgzSkmeeyTGWzu2T4GHjeWxs2HDmsOTMZjYzCyxa5GenMd74UJFs23f8+MPPOd/q5PjZEx8+bKg4zM/P3vz4Bq6QZgDGocIBmL1wUWac6qHWNRBQMApGwSgYBSMXAADTMVWZO8E4zAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-8486-5244","institution":"Institute of Forestry and Conservation, John H. 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Daniels Faculty of Architecture, Landscape and Design, University of Toronto","correspondingAuthor":false,"prefix":"","firstName":"Md","middleName":"Rezaul","lastName":"Karim","suffix":""},{"id":544631394,"identity":"af3eb652-61f6-4408-a1a1-b15899bd66de","order_by":4,"name":"Melanie Sifton","email":"","orcid":"","institution":"Institute of Forestry and Conservation, John H. Daniels Faculty of Architecture, Landscape and Design, University of Toronto","correspondingAuthor":false,"prefix":"","firstName":"Melanie","middleName":"","lastName":"Sifton","suffix":""},{"id":544631395,"identity":"60f6e361-4ed6-40c7-9f8c-57990a2b1d44","order_by":5,"name":"Sean Thomas","email":"","orcid":"https://orcid.org/0000-0002-0686-2483","institution":"University of Toronto","correspondingAuthor":false,"prefix":"","firstName":"Sean","middleName":"","lastName":"Thomas","suffix":""}],"badges":[],"createdAt":"2025-11-12 08:00:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8093549/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8093549/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96261723,"identity":"405a3a77-2f8c-4106-9f46-725b4105a090","added_by":"auto","created_at":"2025-11-19 07:59:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":70295,"visible":true,"origin":"","legend":"\u003cp\u003eSeasonal variation in mean (±SE) methane (CH₄) flux from \u003cem\u003eSedum\u003c/em\u003e green roof modules with and without biochar amendment from summer 2020 to fall 2024. Bars represent estimated marginal means derived from a linear mixed-effects model using Sidak-adjusted pairwise comparisons. Within each measurement period (season–year), different letters indicate significant differences (p \u0026lt; 0.05) between biochar and no-biochar treatments. Negative flux values indicate net CH₄ uptake by the substrate.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8093549/v1/b2a80503bc4ff3351a9aaccb.png"},{"id":96261731,"identity":"ef0a29a5-64ce-411a-a227-d35aaeaaefdc","added_by":"auto","created_at":"2025-11-19 08:00:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":114287,"visible":true,"origin":"","legend":"\u003cp\u003eSeasonal variation in mean (± SE) \u003cstrong\u003e(a)\u003c/strong\u003e CO₂ and \u003cstrong\u003e(b)\u003c/strong\u003e H₂O fluxes from \u003cem\u003eSedum\u003c/em\u003e green roof modules with and without biochar amendment between summer 2020 and fall 2024. Bars represent estimated marginal means from linear mixed-effects models including treatment and season as fixed factors and collar as a random effect. Different letters within a season denote significant differences between treatments (Sidak-adjusted \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8093549/v1/582c3918f36d9f10a7348490.png"},{"id":96261718,"identity":"c36185c7-658f-4ed0-8aab-848498216d0c","added_by":"auto","created_at":"2025-11-19 07:59:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":113871,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships between CH₄ flux and (a) CO₂ flux and (b) H₂O flux from \u003cem\u003eSedum\u003c/em\u003e green roof substrates, based on pooled data measured across all seasons between 2020 and 2024. Regression equations, coefficients of determination (R²), and significance levels are shown. The shaded area around the fitted regression line represents the 95% confidence interval. Solid line indicates significant model fit while dashed line indicates non-significant fit.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8093549/v1/f39ce21c35bef857254fa6d0.png"},{"id":96261724,"identity":"aa8d0ac4-edec-41db-a673-f5bceca25138","added_by":"auto","created_at":"2025-11-19 07:59:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":73619,"visible":true,"origin":"","legend":"\u003cp\u003ePiecewise structural equation model (SEM) showing the significant pathways (p \u0026lt; 0.05) linking biochar addition, environmental drivers, and CH₄ flux from green roof substrates. Green arrows represent positive standardized path coefficients and red arrows represent negative standardized path coefficients, with arrow thickness proportional to effect size. Numbers adjacent to paths are standardized coefficients. Endogenous (response) variables are shown with their conditional R² values, representing variance explained by predictors. The single grey dotted line indicates a residual correlation between CO₂ flux and CH₄ flux. Non-significant p-value indicating adequate model fit (Fisher’s C = 3.15, df = 4, p = 0.53). Non-significant causal paths are excluded here but are presented in supplementary Fig. S3. Negative CH₄ flux values indicate CH\u003csub\u003e4 \u003c/sub\u003euptake.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8093549/v1/1ddafaf1a432820a1a034f83.png"},{"id":98426688,"identity":"e411900b-2068-4355-8e1f-73a8b71baaf7","added_by":"auto","created_at":"2025-12-17 16:38:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1719849,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8093549/v1/820ce656-8818-41f6-9771-b89cef84ebb3.pdf"},{"id":96261716,"identity":"116a006d-d6fd-4464-a91e-ae80f3fad3a5","added_by":"auto","created_at":"2025-11-19 07:59:43","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":6903416,"visible":true,"origin":"","legend":"Biochar greatly enhances methane oxidation in urban green roof substrate","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-8093549/v1/6753008abfd58b3d47f3c026.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Biochar greatly enhances methane oxidation in urban green roof substrate","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eMethane (CH₄), a potent greenhouse gas (GHG) with a short atmospheric lifetime yet strong warming potential, is a major driver of near-term climate forcing\u0026nbsp;\u003csup\u003e1,2\u003c/sup\u003e. While agriculture and wetlands are the dominant biogenic sources, urban environments increasingly function as complex mosaics of CH₄ sources and sinks\u0026nbsp;\u003csup\u003e3,4\u003c/sup\u003e. This dual role underscores the need to quantify CH₄ fluxes in urban green infrastructures and develop strategies to reduce sources while enhancing sinks.\u003c/p\u003e\n\u003cp\u003eGreen roofs are an innovative component of urban green infrastructures that have received considerable attention in recent years for multiple ecosystem services. Originally designed for stormwater management by retaining precipitation, they also improve energy efficiency, extend roof lifespan, enhance biodiversity, and help mitigate urban heat-island effects\u0026nbsp;\u003csup\u003e5–7\u003c/sup\u003e. The potential climate benefits of green roofs through carbon sequestration are also significant, as both vegetation and the organic carbon embedded in green roof substrates are increasingly recognized as important carbon sinks within urban green infrastructure systems\u0026nbsp;\u003csup\u003e8,9\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe capacity of green roofs to influence non-CO\u003csub\u003e2\u003c/sub\u003e GHG dynamics, particularly CH₄, has only recently begun to attract scientific attention\u0026nbsp;\u003csup\u003e10\u003c/sup\u003e. While a growing body of research has examined their carbon sequestration potential, GHG fluxes from roof substrates remain a critical but underexplored component in assessing their net climate effects. In particular, studies on substrate GHG flux in extensive green roofs (typically with vegetation mats of \u003cem\u003eSedum\u003c/em\u003e or closely related \u003cem\u003ePhedimus\u003c/em\u003e species) are limited, with only a handful addressing overall GHG fluxes and even fewer focusing specifically on CH\u003csub\u003e4\u003c/sub\u003e. A growing body of research highlights the importance of organic matter content in these systems because high–organic matter substrates, often used to enhance plant performance and water retention\u0026nbsp;\u003csup\u003e11,12\u003c/sup\u003e, may also emit CH₄ at rates comparable to organic mulches\u0026nbsp;\u003csup\u003e13\u003c/sup\u003e, highlighting the need to quantify the rate of flux and better understand the mechanisms regulating CH₄ exchange in these systems.\u003c/p\u003e\n\u003cp\u003eIn general, biogenic CH₄ flux is a balance between methanogenesis in strictly anoxic or strongly hypoxic microsites and methanotrophy, biological process of CH\u003csub\u003e4\u003c/sub\u003e oxidation, in oxic zones; both are influenced by microbial communities and soil physical and chemical properties\u0026nbsp;\u003csup\u003e14,15\u003c/sup\u003e. Among them, moisture and temperature are dominant controls. In upland soils, CH₄ oxidation typically shows a hump-shaped response to soil water content, peaking at intermediate saturation and declining when soils are either too wet (limited O₂ diffusion) or too dry (microbial water stress)\u0026nbsp;\u003csup\u003e16,17\u003c/sup\u003e. In green roof substrates, moisture and temperature have likewise been identified as the dominant physical drivers regulating CH₄ uptake\u0026nbsp;\u003csup\u003e18,10\u003c/sup\u003e. Soil pH is also an important chemical control; while earlier studies suggested optimal methanotrophic activity near neutrality (pH 6.6–7.5)\u0026nbsp;\u003csup\u003e19\u003c/sup\u003e, subsequent work has shown active CH₄ oxidation under both acidic and alkaline conditions\u0026nbsp;\u003csup\u003e20,21\u003c/sup\u003e. Soil texture and structure modulate CH₄ fluxes primarily by altering gas diffusivity through changes in air‑filled porosity; accordingly, surface evaporation can indirectly influence CH₄ oxidation via moisture–diffusivity effects\u0026nbsp;\u003csup\u003e22,23\u003c/sup\u003e. Because methanotrophs convert CH₄ to CO₂, a portion of CO₂ efflux can derive from subsurface CH₄ oxidation, and CH₄ and CO₂ fluxes may covary through both stoichiometric coupling and shared environmental drivers\u0026nbsp;\u003csup\u003e24,25\u003c/sup\u003e. Moreover, evaporation and moisture together regulate gas diffusion dynamics in soil. High moisture reduces air-filled pore space, whereas evaporation promotes the formation of air-filled microsites within the substrate, thereby influencing gas diffusivity\u0026nbsp;\u003csup\u003e26\u003c/sup\u003e. Consequently, a relationship between H₂O flux and other soil gases is expected. While soil physical and chemical properties regulate GHG flux, this regulation can be strongly seasonal, as episodic events such as spring freeze–thaw cycles in temperate regions have been found to influence biogenic emissions\u0026nbsp;\u003csup\u003e27\u003c/sup\u003e. Because temperature is a dominant driver of biogeochemical cycles, quantifying CH₄ fluxes across seasons is essential. Given these controls, amendments that alter substrate properties should predictably modify CH₄ exchange, particularly in engineered systems such as green roof media, yet this remains unexplored.\u003c/p\u003e\n\u003cp\u003eGreen roof substrates are engineered to meet structural load limits, combining lightweight organic matter with porous inorganic aggregates such as expanded shale, clay, or crushed brick\u0026nbsp;\u003csup\u003e28\u003c/sup\u003e. While these materials support drainage and plant survival, they are prone to compaction, which reduces porosity and water retention\u0026nbsp;\u003csup\u003e29,30\u003c/sup\u003e, potentially altering microbial communities and CH₄ flux patterns. Rooftop exposure also increases evaporation, often requiring irrigation. Hailm et al. (2022) \u003csup\u003e10\u003c/sup\u003e found that irrigated green roofs exhibited greater CH₄ uptake than non-irrigated systems, demonstrating the role of substrate moisture in regulating fluxes. More broadly, GHG dynamics in green roofs appear strongly dependent on substrate properties, with vegetation might exerting an interactive influence. While green roof substrates generally emit CO₂, they function as weak CH₄ sinks, and potential means of strengthening this sink capacity remain largely unexplored.\u003c/p\u003e\n\u003cp\u003eBiochar, a carbon-rich material produced by pyrolysis, has been shown to enhance CH₄ uptake in agricultural, forest, and urban soils\u0026nbsp;\u003csup\u003e13,31–33\u003c/sup\u003e. However, its potential in green roof substrates remains untested, despite evidence that biochar improves plant performance, stormwater retention, and nutrient availability\u0026nbsp;\u003csup\u003e34,35\u003c/sup\u003e. Its porous structure improves both water retention and aeration\u0026nbsp;\u003csup\u003e36,37\u003c/sup\u003e, reducing compaction and maintaining drainage. By altering bulk density, electrical conductivity, and pH, biochar can create a stable and favorable environment for methane-oxidizing microbes. These properties make biochar a promising amendment for extensive \u003cem\u003eSedum\u003c/em\u003e green roofs, particularly where moisture and porosity limit gas exchange.\u0026nbsp;Several studies have reported biochar’s benefits in promoting plant growth, enhancing stormwater retention, and increasing nutrient availability in green roofs\u0026nbsp;\u003csup\u003e34,38,35\u003c/sup\u003e. Although biochar is highly recalcitrant, with carbon half-lives of centuries\u0026nbsp;\u003csup\u003e39\u003c/sup\u003e, its labile fraction may transiently increase CO₂ release\u0026nbsp;\u003csup\u003e40\u003c/sup\u003e, and its low density makes it susceptible to wind erosion on exposed roofs\u0026nbsp;\u003csup\u003e41\u003c/sup\u003e, emphasizing the need for long-term evaluation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUrban areas now host more than half of the global population\u0026nbsp;\u003csup\u003e42\u003c/sup\u003e, yet their contribution to global biogeochemical cycles remains poorly constrained. While natural soils are recognized as CH₄ sinks, urban ecosystems are often overlooked. Green roofs are widely promoted for stormwater retention, energy savings, and biodiversity, but their role in regulating GHG fluxes is rarely examined. Biochar is known to enhance soil carbon sequestration and stimulate CH₄ oxidation in terrestrial systems, but evidence for its function in green infrastructure remains scarce. A recent meta-analysis found that biochar generally improves ecosystem functions across green infrastructure types, including reduced CO₂ and N₂O emissions, though CH₄ responses were variable\u0026nbsp;\u003csup\u003e38\u003c/sup\u003e.\u0026nbsp;Most studies directly testing biochar–GHG interactions have been limited to constructed wetlands, where elevated CH₄ emissions are common\u0026nbsp;\u003csup\u003e43,44\u003c/sup\u003e. Whether biochar can similarly modulate GHG dynamics in green roof substrates remains unknown. Demonstrating that biochar can transform green roofs into functional CH₄ sinks would reveal a new pathway for integrating climate mitigation into urban landscape design.\u003c/p\u003e\n\u003cp\u003eIn this study, we quantified, for the first-time,\u0026nbsp;CH₄, CO₂, and H₂O fluxes across biochar-amended and control \u003cem\u003eSedum\u0026nbsp;\u003c/em\u003egreen roofs over a 5-year period.\u0026nbsp;We hypothesize that biochar amendment will enhances CH₄ uptake in extensive green roofs by modifying substrate physicochemical properties. We further expect that this effect will be mediated by changes in substrate H\u003csub\u003e2\u003c/sub\u003eO and CO₂ fluxes, and while the direction of the effect will remain consistent over time, its magnitude will fluctuate seasonally.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBiochar amendment strengthens CH₄ uptake across seasons\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLinear mixed-effects models (LMMs) showed that biochar\u0026nbsp;\u003cstrong\u003etreatment had a highly significant effect on CH₄ flux\u003c/strong\u003e (F₁,₂₅₅ = 136.52,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) in \u003cem\u003eSedum\u003c/em\u003e green roof substrates. The\u0026nbsp;\u003cstrong\u003emain effect of season\u003c/strong\u003e was not significant (F₁₁,₂₅₅ = 0.59,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = 0.84); however, the\u0026nbsp;\u003cstrong\u003einteraction between treatment and season\u003c/strong\u003e was significant (F₁₁,₂₅₅ = 3.67,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), indicating that the effect of treatment on CH₄ flux varied across seasons (Table S2).\u003c/p\u003e\n\u003cp\u003eCH₄ fluxes from Sedum green roof substrates showed clear treatment and seasonal variations across measurement years (Figure 1; Table S3). During the initial measurement years (2020–2021), CH₄ uptake was modest in both treatments, but by summer 2021 biochar-amended modules exhibited significantly stronger uptake than those without biochar (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). From 2022 onward, biochar consistently enhanced CH₄ uptake relative to the no-biochar treatment across all seasons (all\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). The strongest treatment differences occurred in spring 2023, when CH₄ uptake in biochar-amended Sedum modules reached –1.91 ± 0.25 nmol·m⁻²·s⁻¹ \u0026nbsp;compared with –0.40 ± 0.10 nmol·m⁻²·s⁻¹ \u0026nbsp;in modules without biochar (\u003cem\u003et\u003c/em\u003e = –5.84,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). Significant treatment contrasts also occurred in fall 2021 (\u003cem\u003ep\u003c/em\u003e = 0.02), summer 2022 (\u003cem\u003ep\u003c/em\u003e = 0.001), and spring 2024 (\u003cem\u003ep\u003c/em\u003e = 0.007), confirming the persistence of enhanced CH₄ oxidation in biochar-treated substrates. Across the five-year period, CH₄ fluxes exhibited strong temporal structure, with uptake peaks in spring and fall and weaker uptake in mid-summer, reflecting concurrent variation in substrate moisture and temperature (supplementary Figure S2). By 2024, although CH₄ uptake had slightly weakened relative to 2023, biochar-treated modules still maintained higher uptake rates (–1.26 ± 0.17 nmol·m⁻²·s⁻¹) than the no-biochar controls (–0.03 ± 0.19 nmol·m⁻²·s⁻¹;\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) across all seasons (Figure 1; Table S3). Bare substrate fluxes were also measured but excluded from formal statistical analyses due to lower replication; their descriptive trends, showing minimal CH₄, CO₂, and H₂O exchange relative to vegetated modules, are summarized in supplementary Tables S3–S5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCO₂ flux varies seasonally with limited biochar effect\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResults from LMMs showed that biochar\u0026nbsp;\u003cstrong\u003etreatment had no significant effect on CO₂ flux\u003c/strong\u003e (F₁,₂₂ = 0.32,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = 0.58). In contrast, the\u0026nbsp;\u003cstrong\u003emain effect of season\u003c/strong\u003e was highly significant (F₁₁,₂₃₃ = 37.66,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), indicating substantial seasonal variation in CO₂ flux. The\u0026nbsp;\u003cstrong\u003einteraction between treatment and season\u003c/strong\u003e was also significant (F₁₁,₂₃₃ = 1.99,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = 0.03), suggesting that treatment effects on CO₂ flux varied modestly across seasons (Table S2).\u003c/p\u003e\n\u003cp\u003eCO₂ fluxes substrates varied significantly across seasons and years, with moderate emissions during early establishment (2020–2021) and pronounced temporal fluctuations thereafter (Figure 2a; Table S4). Biochar treatment did not exert a consistent effect on CO₂ flux (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05 for most comparisons), though significant seasonal interactions were evident (Figure S3). In fall 2022, modules without biochar exhibited the highest CO₂ emissions (15.7 ± 1.2 µmol·m⁻²·s⁻¹), significantly exceeding those from biochar-amended modules (11.4 ± 1.6 µmol·m⁻²·s⁻¹;\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = 0.01). By spring 2023, both treatments showed comparable fluxes (~9–10 µmol·m⁻²·s⁻¹;\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.3), and this pattern persisted through 2024, with modest seasonal peaks in spring and fall (Figure 2a; Table S4). Overall, CO₂ fluxes followed a strong seasonal pattern, peaking in spring and fall and declining in summer, with interannual variability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiochar increases evapotranspiration through enhanced surface flux\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResults from LMMs showed that biochar\u0026nbsp;\u003cstrong\u003eamendment had a highly significant effect on H₂O flux\u003c/strong\u003e in \u003cem\u003eSedum\u003c/em\u003e roof substrates (F₁,₂₂ = 29.00,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). The\u0026nbsp;\u003cstrong\u003emain effect of season\u003c/strong\u003e was also highly significant (F₁₁,₂₃₄ = 12.62,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), indicating strong seasonal variation in evapotranspiration. In addition, the\u0026nbsp;\u003cstrong\u003einteraction between treatment and season\u003c/strong\u003e was significant (F₁₁,₂₃₄ = 3.63,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), suggesting that the influence of treatment on H₂O flux varied across seasons (Table S2).\u003c/p\u003e\n\u003cp\u003eH₂O fluxes exhibited strong seasonal and interannual variation, with consistently higher fluxes in biochar-amended modules than in those without biochar (Figure 2b; Table S4). During the establishment years (2020–2021), H₂O fluxes were already elevated in biochar-treated modules (e.g., summer 2020: 564 ± 25 µmol·m⁻²·s⁻¹) compared with controls (306 ± 3 µmol·m⁻²·s⁻¹;\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = 0.05). The largest treatment differences occurred in spring 2023, when mean fluxes in biochar modules (1211 ± 192 µmol·m⁻²·s⁻¹) exceeded those without biochar (528 ± 63 µmol·m⁻²·s⁻¹;\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). Fluxes generally peaked in spring and summer and declined in fall (Figure S4). By 2024, both treatments showed reduced fluxes, though biochar-amended modules maintained higher evapotranspiration (390 ± 178 µmol·m⁻²·s⁻¹) than controls (170 ± 27 µmol·m⁻²·s⁻¹;\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = 0.03). Overall, biochar addition enhanced H₂O fluxes throughout the study period, especially during warm and moist seasons when evaporative potential was highest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCH₄ uptake covaries with CO₂ and H₂O fluxes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCH₄ uptake increased significantly with both CO₂ flux (\u003cem\u003eR²\u003c/em\u003e = 0.05,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01) and H₂O flux (\u003cem\u003eR²\u003c/em\u003e = 0.16,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) (Figure 3). These positive relationships were stronger in biochar-amended modules, which consistently exhibited greater CH₄ uptake than those without biochar. Linear regressions between substrate moisture, temperature, EC, and pH with CH₄ flux are shown in Supplementary Figure S5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIntegrated pathway analysis reveals controls on GHGs fluxes\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe piecewise SEM showed an adequate fit (Fisher’s C = 3.15, df = 4,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = 0.53) and explained 53% of the variance in CH₄ flux and 42% in CO₂ flux, with smaller proportions for intermediate variables (moisture = 0.11; temperature = 0.03; EC = 0.14; pH = 0.01; H₂O flux = 0.11) (Figure 4). Biochar addition directly enhanced CH₄ uptake (β = –0.82) by increasing substrate moisture (β = 0.65,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) and reducing EC (β = –0.67,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Higher substrate moisture, in turn, promoted H₂O flux (β = 0.17) but suppressed CH₄ and CO₂ flux (β = –0.35 and β = –0.16, respectively). Temperature positively influenced H₂O (β = 0.17) and CO₂ flux (β = 0.24) while inhibiting CH₄ uptake (β = –0.22). H₂O flux exerted a strong positive effect on CO₂ flux (β = 0.48) and a weaker negative effect on CH₄ flux (β = –0.22). Substrate pH had minor but significant negative effects on both CO₂ (β = –0.16) and CH₄ flux (β = –0.12).\u003c/p\u003e"},{"header":"Discussion ","content":"\u003cp\u003eOver five years of measurements on extensive \u003cem\u003eSedum\u003c/em\u003e green roofs, biochar amendment substantially enhanced CH₄ uptake compared with non-amended substrates. Uptake varied seasonally and with substrate age, supporting the hypothesis that biochar promotes conditions favorable for methanotrophy in organic-rich media. Biochar also increased surface evaporation but did not elevate CO₂ emissions. The sustained enhancement of CH₄ uptake across seasons was closely associated with higher substrate moisture and greater H₂O flux, suggesting improved gas diffusivity and sustained microbial CH₄ oxidation in aerobic substrate layers. The CH₄ uptake rates in biochar-amended substrates (up to –1.9 nmol m⁻² s⁻¹) were higher than those typically reported for agricultural soils (–0.1 to –1.0;\u0026nbsp;\u003csup\u003e15\u003c/sup\u003e) and urban soils (often negligible to –1.0;\u0026nbsp;\u003csup\u003e45\u003c/sup\u003e), but lower than temperate forest soils (–2.5 to –4.0;\u0026nbsp;\u003csup\u003e46,47\u003c/sup\u003e), highlighting the potential of biochar-amended green roofs to function as significant CH₄ sinks within urban infrastructures.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOnly a handful of studies have measured GHG fluxes from green roof substrates, most reporting minimal CH₄ uptake\u0026nbsp;\u003csup\u003e10\u003c/sup\u003e. While biochar application in urban green infrastructure has gained attention, its effect on CH₄ flux in extensive \u003cem\u003eSedum\u003c/em\u003e systems had not been previously tested. Prior research in agricultural and urban soils largely focused on short-term experiments, where biochar generally reduced CH₄ emissions\u0026nbsp;\u003csup\u003e13,33\u003c/sup\u003e, but evidence for long-term persistence has been scarce. Our study provides the first demonstration that biochar can enhance the CH₄ sink strength of green roof substrates over the long term, adding a new climate co-benefit to the ecosystem services of urban green infrastructures.\u003c/p\u003e\n\u003cp\u003eOur results showed that biochar enhanced CH₄ uptake primarily through direct effects, while significant indirect effects were mediated by higher substrate moisture and H₂O flux, which together created conditions favorable for methanotrophy. Previous studies across paddy fields\u0026nbsp;\u003csup\u003e33\u003c/sup\u003e, urban soils\u0026nbsp;\u003csup\u003e13\u003c/sup\u003e and landfills\u0026nbsp;\u003csup\u003e48\u003c/sup\u003e similarly found biochar increasing CH₄ uptake, attributed to its porous structure and large surface area that provide methanotroph habitat and improve aeration. Our findings align with this mechanism, as biochar’s high porosity facilitates gas exchange and supports microbial activity conducive to CH₄ oxidation.\u003c/p\u003e\n\u003cp\u003eThe structural equation model revealed a strong relationship between substrate moisture and CH₄ uptake, and between biochar and substrate moisture, indicating that biochar improved water retention and thereby enhanced CH₄ oxidation. Soil moisture strongly regulates biogeochemical processes: excessive moisture limits air-filled pore space and creates anaerobic microsites, while low moisture imposes water stress on methanotrophs \u003csup\u003e16,17\u003c/sup\u003e.\u0026nbsp;Maximum CH₄ uptake rates have been recorded in forest and grassland soils at 20–60% saturation\u0026nbsp;\u003csup\u003e49–51\u003c/sup\u003e. While green roof substrates are unique, we found moisture generally remained within this optimal range in both treatments but was consistently higher in biochar-amended modules, indicating that biochar maintains conditions favorable for CH₄ uptake under dry conditions.\u003c/p\u003e\n\u003cp\u003eWe observed a positive relationship between substrate temperature and CH₄ uptake (Figure 4), suggesting that higher temperatures stimulated methane oxidation. Structural equation modeling indicated that biochar exerted a positive but non-significant effect on temperature, possibly due to its low albedo increasing heat absorption, offset by greater evaporative cooling. This thermal balance resembles prior observations of biochar effects on green roof microclimates\u0026nbsp;\u003csup\u003e34\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWe observed non-significant relationships between CH₄ oxidation and substrate EC but a significant effect of pH (Figure 4). The average pH in biochar-treated modules (6.57 ± 0.04 to 7.53 ± 0.05; Table S5) was near-neutral, within the optimal range (6–8) for CH₄ oxidation\u0026nbsp;\u003csup\u003e52\u003c/sup\u003e. We also found a significant relationship between CH₄ and H₂O flux (Figure 4), with biochar consistently enhancing H₂O flux across seasons (Figure 2), suggesting that greater evaporation was linked to increased CH₄ oxidation. These pathways can be attributed to higher moisture availability maintained in biochar-amended modules. In rooftop environments with high atmospheric demand, biochar likely enhances capillary continuity and pore connectivity\u0026nbsp;\u003csup\u003e36\u003c/sup\u003e, improving gas diffusivity in oxic layers and facilitating microbial CH₄ oxidation\u0026nbsp;\u003csup\u003e23,53\u003c/sup\u003e. This dual effect, greater water storage with improved gaseous exchange, appears to have enabled sustained moisture and enhanced oxygen diffusion in biochar-rich substrates, stimulating long-term CH₄ uptake. Thus, we propose that biochar-mediated CH₄ oxidation in green roofs results from coupled moisture–evaporation dynamics rather than a linear response to water content.\u003c/p\u003e\n\u003cp\u003eBiochar application did not significantly increase CO₂ emissions (Figure 2a). The tested green roof substrate was already rich in organic matter, and any transient CO₂ pulse from labile carbon likely occurred before monitoring (modules installed in 2019; measurements began 2020). CO₂ efflux showed strong seasonal patterns, higher in spring and summer, lower in fall, with temperature exerting a significant positive effect\u0026nbsp;\u003csup\u003e54,55\u003c/sup\u003e. Seasonal variation of CO\u003csub\u003e2\u003c/sub\u003e flux also reflects \u003cem\u003eSedum\u003c/em\u003e root respiration during active growth\u0026nbsp;\u003csup\u003e56\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe found a significant positive relationship between CO₂ and CH₄ flux, implying that part of the CO₂ efflux originates from CH₄ oxidation by methanotrophs \u003csup\u003e52,57\u003c/sup\u003e, in addition to microbial and root respiration. A similar positive link between H₂O flux and CH₄ uptake further supports evaporation–aeration co-regulation of methanotrophy. During Stage-I evaporation, capillary continuity sustains moisture while surface water removal increases air-filled porosity, creating oxic micro-layers with enhanced gas diffusivity\u0026nbsp;\u003csup\u003e53\u003c/sup\u003e. Because CH₄ oxidation occurs near the surface above wetter layers, even slight increases in air-filled pores can strongly stimulate methanotrophic activity\u0026nbsp;\u003csup\u003e23\u003c/sup\u003e. Collectively, these findings demonstrate the interconnected biophysical processes through which biochar enhances CH₄ uptake in engineered substrates. Extending this mechanistic understanding into practical design applications is an important next step.\u003c/p\u003e\n\u003cp\u003eWe tested one biochar type (sugar maple, fixed dosage), but biochar properties vary widely with production conditions. Establishing dose–response relationships across feedstocks will help identify thresholds where benefits plateau or unintended effects arise. Future work should link flux responses to microbial population dynamics using molecular approaches such as functional gene assays. Beyond these methodological gaps, biochar should be considered within a multi-objective substrate design framework that integrates stormwater retention, plant performance, and GHG mitigation. While this study focused on \u003cem\u003eSedum\u003c/em\u003e systems, future research should evaluate biochar in native plant roofs, where diverse root–microbe interactions may further influence CH₄ sink strength and ecosystem functions. Our findings also connect to urban wood-waste management. Converting forestry residues into biochar for engineered substrates could provide durable carbon storage and broader ecosystem co-benefits compared to conventional mulching.\u003c/p\u003e\n\u003cp\u003eTo summarize, CH₄ flux in pre-grown \u003cem\u003eSedum\u003c/em\u003e green roofs was generally low, but biochar significantly enhanced CH₄ uptake, with effects persisting for up to four years. Although uptake declined slightly in the fifth year, it remained higher than in unamended substrates. Biochar-mediated CH₄ enhancement was driven by improved substrate moisture and gas diffusivity, emphasizing the role of aeration-evaporation interactions in sustaining methanotrophy. These findings show that a single biochar amendment can maintain elevated CH₄ oxidation over multiple years while improving hydrological function. More broadly, biochar’s demonstrated the enhancement of CH\u003csub\u003e4\u003c/sub\u003e oxidation, highlights its potential to integrate GHG mitigation with stormwater and plant performance benefits, advancing green roofs as multifunctional, climate-resilient urban infrastructure.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eGreen roof design and substrates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experiment was installed in Fall of 2019 at the Green Roof Innovation Testing Laboratory (GRIT Lab II) at 1, Spadina Crescent at University of Toronto\u0026rsquo;s downtown St. George Campus, in Toronto, Ontario, Canada (Fig. S1a). GRIT Lab II\u0026rsquo;s green roof modules were sized 1.83 m \u0026times;1.83 m, with 15 cm substrate depth and slope of 2\u0026deg;. While GRIT Lab II consists a total of 50 roof modules, the focus of this study was only on 24 green roof modules cultivated over the course of the trial using pre-grown stonecrop \u003cem\u003eSedum\u003c/em\u003e mats. The \u003cem\u003eSedum\u003c/em\u003e mats were dominated (\u0026gt; 95%) by orange stonecrop [\u003cem\u003ePhedimus kamtschaticus\u003c/em\u003e (Fisch. \u0026amp; C.A.Mey.) \u0026apos;t Hart], with small amounts of white stonecrop [\u003cem\u003eSedum album\u003c/em\u003e L.), and tasteless stonecrop [\u003cem\u003eSedum sexangulare\u003c/em\u003e\u0026nbsp; \u0026nbsp;L.]. The green roof \u003cem\u003eSedum\u003c/em\u003e mat system used is hereinafter referred to as \u003cem\u003eSedum\u003c/em\u003e modules.\u003c/p\u003e\n\u003cp\u003eThe experimental green roof media was a lightweight high-organic green roof mix (\u0026ldquo;Eco-blend\u0026rdquo; supplied by Bioroof Systems Inc., Burlington, Canada) with an organic matter content of 75 \u0026plusmn; 2% (mean \u0026plusmn; SE) \u003csup\u003e35\u003c/sup\u003e. The biochar amendment was created using sugar maple (\u003cem\u003eAcer saccharum\u003c/em\u003e L.) sawdust pyrolyzed at ~700 ◦C, with 10\u0026ndash;15 minutes of residence time (Haliburton Forest and Wildlife Reserve, Canada). Biochar and substrate properties are presented in supplementary Table S1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExperimental design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGreen roof modules were arranged in a completely randomized design with one factor (biochar present vs. no biochar) and 12 replicates per level (n = 24). Two non-vegetated bare-substrate modules of identical dimensions were also included for reference. Greenhouse gas (GHG) flux measurements were conducted from\u0026nbsp;\u003cstrong\u003esummer (June\u0026ndash;August) 2020 through fall (September\u0026ndash;November) 2024\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003espanning five growing seasons. Measurements for\u0026nbsp;\u003cstrong\u003espring (March\u0026ndash;May) 2022\u003c/strong\u003e and\u0026nbsp;\u003cstrong\u003esummer 2023\u003c/strong\u003e were not collected due to logistical constraints and were therefore excluded from the formal analysis. Biochar was incorporated into each treated green roof module at a rate of 20 t ha⁻\u0026sup1; (equivalent to 5.4% v/v), an application level previously identified as optimal for enhancing plant performance\u0026nbsp;\u003csup\u003e58\u003c/sup\u003e.\u0026nbsp; Initially, the\u0026nbsp;\u003cem\u003eSedum\u003c/em\u003e modules were dominated by\u0026nbsp;\u003cem\u003ePhedimus kamtschaticus\u003c/em\u003e, comprising over 95% of total cover, with minor contributions from\u0026nbsp;\u003cem\u003eSedum sexangulare\u003c/em\u003e L. and\u0026nbsp;\u003cem\u003eSedum album\u003c/em\u003e L. (hereafter referred to as\u0026nbsp;\u003cem\u003eSedum\u003c/em\u003e modules). Each green roof module received uniform irrigation of 20\u0026ndash;30 L of municipal water twice weekly during the growing season. This irrigation regime was designed primarily to sustain plant survival during dry periods and generally did not generate any surface runoff from the modules.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn each replicate green roof module, one PVC collar (10 cm diameter, 10 cm height) was inserted into the substrate in early May 2020, prior to initiating seasonal gas flux measurements conducted from Summer 2020 through Fall 2024. For non-vegetated bare substrate references, three collars were installed per module to increase the statistical power for subsequent analyses. The collars were inserted 3\u0026ndash;5 cm deep into the substrate to prevent leakage, following the method of Jovani-Sancho et al. (2018)\u003csup\u003e59\u003c/sup\u003e, and placed at least 30 cm away from the module\u0026apos;s edge to avoid interference from plant roots. Any aboveground plant material rooted within the collar was trimmed off at the time of installation and subsequent gas flux measurements to eliminate aboveground plant mediated gas fluxes.\u003c/p\u003e\n\u003cp\u003eFor gas-exchange measurements, we used Los Gatos Ultraportable Greenhouse Gas Analyzer (UGGA: Los Gatos Research, San Jose, CA, USA) connected to a pressure-equilibrated chamber (LI-8100-102 opaque survey chamber, volume 854.2 cm\u0026sup3;; LI-COR Environmental, Lincoln, NE, USA) in a closed dynamic system with a nominal flow rate of 0.5 L/min. This setup provided real-time measurements of CH\u003csub\u003e4\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e, and water vapor (H\u003csub\u003e2\u003c/sub\u003eO), with respective accuracies of 2, 300, and 100 ppb, using off-axis integrated cavity output spectroscopy.\u003c/p\u003e\n\u003cp\u003eSubstrate temperature was recorded adjacent to each sampling location at a depth of ~5 cm using a Flip Thermometer (PC, Toronto, Canada; Model 21010083) with a precision of 0.5 \u0026deg;C. The substrate moisture content was measured at a depth of ~5 cm using a CS-SM2 soil moisture sensor (accuracy: \u0026plusmn;2.5%) (CredoSense Inc., Toronto, Canada). Measurements were scheduled to avoid precipitation and irrigation in the preceding 48 hours, mitigating transient gas flux effects related to the \u0026quot;Birch effect\u0026quot;\u0026nbsp;\u003csup\u003e60,61\u003c/sup\u003e. Each measurement session lasted approximately three minutes, with data logged at one-second intervals. A subset of substrates was sampled during every gas measurement event to determine pH and EC (electrical conductivity) in laboratory.\u0026nbsp;The pH and EC were determined in a 1:2 suspension of substrates in deionized water at room temperature using a pH/mV Meter (IQ Scientific Instruments, USA) and an Orion Star A112 benchtop conductivity meter (Thermo Scientific, USA), respectively. In each case, triplicate measures were conducted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFlux Calculations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOutput files from the LGR gas analyzer were post-processed using R version 4.3.2 (R Core Team 2024) using an algorithm to estimate flux rates (\u003cem\u003edc/dt\u003c/em\u003e) of concentrations of CH\u003csub\u003e4\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eO\u0026nbsp;\u003csup\u003e10,62\u003c/sup\u003e. First, a \u0026ldquo;dead band\u0026rdquo; of initial 30s was eliminated from each measurement,\u0026nbsp;which is affected by artifacts triggered by the closing of the chamber \u003csup\u003e63,62\u003c/sup\u003e.\u0026nbsp;After this exclusion, we applied a straightforward algorithm using the Pearson correlation coefficient (\u003cem\u003er\u003c/em\u003e) between concentration and time, focusing specifically on CO\u003csub\u003e2\u003c/sub\u003e concentration data to identify the optimal time window (50\u0026ndash;60 seconds) for flux calculations. The time window yielding the highest \u0026lsquo;\u003cem\u003er\u0026rsquo;\u003c/em\u003e value for CO\u003csub\u003e2\u003c/sub\u003e was selected for both CO\u003csub\u003e2\u003c/sub\u003e and CH\u003csub\u003e4\u003c/sub\u003e gases in subsequent flux calculations. We selected CO\u003csub\u003e2\u003c/sub\u003e-based time window for CH\u003csub\u003e4\u003c/sub\u003e because CO\u003csub\u003e2\u003c/sub\u003e fluxes tend to exhibit less noise than CH\u003csub\u003e4\u003c/sub\u003e, allowing potential leakage or pressure artifacts to be more easily detected from CO\u003csub\u003e2\u003c/sub\u003e data than from CH\u003csub\u003e4\u003c/sub\u003e. Figure S1 shows example slope calculation from the raw data stream followed by algorithm described above.\u003c/p\u003e\n\u003cp\u003eTo determine \u003cem\u003edc/dt\u003c/em\u003e for calculating CO\u003csub\u003e2\u003c/sub\u003e and CH\u003csub\u003e4\u003c/sub\u003e fluxes, we used either linear or non-linear regression \u003csup\u003e64\u003c/sup\u003e depending on the statistical properties of the concentration data. If the quadratic coefficient of the concentration data was not statistically significant (p \u0026gt; 0.05), we used linear regression to determine \u003cem\u003edc/dt\u003c/em\u003e and calculated the flux as LI-COR, (2015) \u003csup\u003e65\u003c/sup\u003e:\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analyses were conducted to evaluate the effects of biochar treatment and measurement period (season \u0026times; year) on CH₄, CO₂, and H₂O fluxes across the study years. To evaluate these effects, a linear mixed-effects model (LMMs) was applied using the \u003ccode\u003e\u0026ldquo;\u003cem\u003elmer\u003c/em\u003e\u0026rdquo;\u003c/code\u003e function from the \u003cstrong\u003elme4\u003c/strong\u003e package in R \u003csup\u003e66\u003c/sup\u003e. Fixed effects included biochar treatment, season and their interaction (\u003cem\u003etreatment \u0026times; season\u003c/em\u003e). To account for repeated measurements, \u003cem\u003eCollar\u003c/em\u003e was included as a random intercept, while \u003cem\u003eseason\u003c/em\u003e nested within \u003cem\u003eyear\u003c/em\u003e was included to capture temporal dependence across years. Residual diagnostics were inspected to verify normality and homoscedasticity assumptions.\u003c/p\u003e\n\u003cp\u003eThe significance of fixed effects was evaluated using \u003cstrong\u003eType III Analysis of Variance (ANOVA)\u003c/strong\u003e with \u003cstrong\u003eSatterthwaite\u0026rsquo;s method\u003c/strong\u003e for estimating denominator degrees of freedom, implemented through the \u0026ldquo;\u003cem\u003eanova\u003c/em\u003e\u0026rdquo; function in the \u0026ldquo;\u003cstrong\u003e\u003cem\u003elmerTest\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026rdquo;\u003c/strong\u003e package \u003csup\u003e67\u003c/sup\u003e. \u0026nbsp;To further explore significant fixed effects and interactions, pairwise post hoc comparisons were performed using \u003cstrong\u003eestimated marginal means (EMMs)\u003c/strong\u003e obtained from the fitted linear mixed-effects models with the \u0026ldquo;\u003cstrong\u003e\u003cem\u003eemmeans\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026rdquo;\u003c/strong\u003e package in R. Treatment contrasts were evaluated within each season, and \u003cstrong\u003e\u003cem\u003eSidak\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;adjustment\u003c/strong\u003e was applied to control for multiple comparisons (\u0026alpha; = 0.05). This model-based approach retains the random-effects structure, providing statistically robust and interpretable pairwise inferences. Non-vegetated bare-substrate modules were excluded from the formal statistical analysis due to the limited number of replicates, which precluded adequate statistical power; their results are therefore presented descriptively only.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStructural equation modeling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe used structural equation modeling (SEM) to investigate direct and indirect effects of\u0026nbsp;\u003cstrong\u003ebiochar treatment\u003c/strong\u003e, substrate properties, and CO\u003csub\u003e2\u003c/sub\u003e flux regulate\u0026nbsp;\u003cstrong\u003eCH₄ flux\u003c/strong\u003e. Because measurements were repeated within collars and across seasons, we first fit a\u0026nbsp;\u003cstrong\u003epiecewise SEM\u003c/strong\u003e in R (v4.4.0) using linear mixed-effects models (\u003cstrong\u003elme4\u003c/strong\u003e) with\u0026nbsp;\u003cstrong\u003erandom intercepts for collar and season\u003c/strong\u003e to account for non-independence\u0026nbsp;\u003csup\u003e68\u0026ndash;70\u003c/sup\u003e.\u0026nbsp;\u003cstrong\u003eTreatment\u003c/strong\u003e was coded as an exogenous binary predictor (\u003cstrong\u003e0 = No biochar\u003c/strong\u003e,\u0026nbsp;\u003cstrong\u003e1 = biochar\u003c/strong\u003e).\u0026nbsp;\u003cstrong\u003eMoisture\u003c/strong\u003e,\u0026nbsp;\u003cstrong\u003etemperature\u003c/strong\u003e,\u0026nbsp;\u003cstrong\u003eEC\u003c/strong\u003e, and\u0026nbsp;\u003cstrong\u003epH\u003c/strong\u003e were specified as mediators; H\u003csub\u003e2\u003c/sub\u003eO,\u0026nbsp;\u003cstrong\u003eCO₂ flux\u003c/strong\u003e and\u0026nbsp;\u003cstrong\u003eCH₄ flux\u003c/strong\u003e were endogenous responses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe hypothesized model specified that biochar affected substrate moisture, temperature, electrical conductivity (EC), and pH, which in turn influenced H₂O flux, CO₂ efflux, and CH₄ flux. Based on preliminary independence tests, we incorporated additional pathways where biologically justified, including H\u003csub\u003e2\u003c/sub\u003eO flux ~ EC and H₂O flux ~ CO₂ efflux, reflecting physical controls on evaporation and microbial respiration. CH₄ flux was modelled as a function of substrate properties, CO₂ efflux, and H₂O flux. All component models were fit as linear mixed-effects regressions (\u003cem\u003elme4\u003c/em\u003e package) with random intercepts for sampling collar and season to account for repeated measurements. Model adequacy was evaluated with Fisher\u0026rsquo;s C statistic, where\u0026nbsp;non-significant\u0026nbsp;values (p \u0026gt; 0.05) indicate consistency between model and data. Standardized path coefficients, marginal R\u0026sup2; values, and graphical representations were used to interpret the final model.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe source data used to generate all graphs and charts presented in this study are publicly available via the Scholars Portal Dataverse repository at: https://doi.org/10.5683/SP3/CANT7Q\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the\u0026nbsp;\u003cstrong\u003eNSERC-CREATE Discovery Grant\u003c/strong\u003e awarded to\u0026nbsp;\u003cstrong\u003eS.C. Thomas\u003c/strong\u003e. The authors gratefully acknowledge\u0026nbsp;\u003cstrong\u003eProfessors Jennifer Drake\u003c/strong\u003e and\u0026nbsp;\u003cstrong\u003eLiat Margolis\u003c/strong\u003e, co-principal investigators on the broader research project, for their valuable leadership and logistical support. We are grateful to\u0026nbsp;\u003cstrong\u003eMalaika Mitra\u003c/strong\u003e,\u0026nbsp;\u003cstrong\u003eKatie Monat\u003c/strong\u003e,\u0026nbsp;\u003cstrong\u003eJennifer Barrett\u003c/strong\u003e,\u0026nbsp;\u003cstrong\u003eLiam Douglas\u003c/strong\u003e, and\u0026nbsp;\u003cstrong\u003eJovana Shrestha\u003c/strong\u003e for their assistance in fieldwork. We thank\u0026nbsp;\u003cstrong\u003eTony Ung\u003c/strong\u003e for his support in maintaining the green-roof experiment. We also acknowledge\u0026nbsp;\u003cstrong\u003eHaliburton Forest and Wildlife Reserve Ltd.\u003c/strong\u003e,\u0026nbsp;\u003cstrong\u003eGro-Bark Inc.\u003c/strong\u003e, and\u0026nbsp;\u003cstrong\u003eBioroof Systems Inc.\u003c/strong\u003e for providing materials and product information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contribution\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIK: Conceptualization, Data collection, Data Curation, Software, Formal analysis; Writing- Original draft. MAH: Data collection, Software, Writing-editing and reviewing; WL: Data collection, Writing-editing and reviewing; MRK: Data collection, Writing-editing and reviewing; MS: Data collection, Writing-editing and reviewing; SCT: Conceptualization, Writing-editing and reviewing, Validation, Administration, Fund acquisition, Supervision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e"},{"header":"References ","content":"\u003col\u003e\n \u003cli\u003eMar, K. A., Unger, C., Walderdorff, L. \u0026amp; Butler, T. Beyond CO2 equivalence: The impacts of methane on climate, ecosystems, and health. \u003cem\u003eEnviron. Sci. 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Evol.\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, 573\u0026ndash;579 (2016).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"green roofs, biochar, methane, urban greenhouse gas fluxes, urban green infrastructure, nature-based solutions, urban sustainability ","lastPublishedDoi":"10.21203/rs.3.rs-8093549/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8093549/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGreen roofs are increasingly implemented in cities to manage stormwater and urban cooling, yet their potential role in greenhouse gas (GHG) mitigation remains unclear. Methane, a potent GHG, is only weakly oxidized by roof substrates, and ways to enhance this sink remain unexplored despite its significance at the city-scale. We report a long-term (2020–2024) field study on biochar effects on CH₄ fluxes in extensive \u003cem\u003eSedum\u003c/em\u003e green roofs, where biochar-amended modules (~5% v/v; 20 t ha⁻¹) maintained consistently higher CH₄ uptake, peaking in spring 2023 at nearly fivefold greater than controls (−1.91 ± 0.25 vs. −0.40 ± 0.10 nmol·m⁻²·s⁻¹). Notably, biochar did not increase CO₂ emissions, indicating enhanced CH₄ uptake without compromising carbon efficiency. Enhanced CH\u003csub\u003e4 \u003c/sub\u003euptake correlated with higher substrate moisture and H₂O flux, suggesting a moisture–evaporation co-regulated diffusivity mechanism facilitating microbial CH₄ oxidation, highlighting biochar as a scalable means to enhance climate-mitigation capacity of urban green infrastructure.\u003c/p\u003e","manuscriptTitle":"Biochar greatly enhances methane oxidation in urban green roof substrate","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-19 07:58:42","doi":"10.21203/rs.3.rs-8093549/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"13c9e7f4-39cc-4512-bd5c-330d497caf8c","owner":[],"postedDate":"November 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57946965,"name":"Earth and environmental sciences/Environmental sciences"},{"id":57946966,"name":"Earth and environmental sciences/Climate sciences/Climate change/Climate-change mitigation"}],"tags":[],"updatedAt":"2025-12-13T13:58:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-19 07:58:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8093549","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8093549","identity":"rs-8093549","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}