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/lp/springer-journals/adsorption-of-methane-on-biochar-for-emission-reduction-in-oil-and-gas-8VmenFtPGH
- Publisher
- Springer Journals
- Copyright
- Copyright © His Majesty the King in Right of Canada, as represented by the Minister of Natural Resources 2023
- ISSN
- 2524-7972
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- 2524-7867
- DOI
- 10.1007/s42773-023-00209-x
- Publisher site
- See Article on Publisher Site
Abstract
1 Introduction Administration 2022). The United States leads the Global warming driven by greenhouse gas emissions is global effort of mitigating methane emissions. A large progressing at an alarming pace. Methane has been rec- source of methane emissions is the oil and gas industry. ognized as a greenhouse gas with high global warming Canada is aiming to reduce methane emissions from the oil and gas industry by at least 75% below 2012 lev potential (US Environmental Protection Agency 2016). - Meanwhile, large quantities of methane have been els by 2030 (Environment and Climate Change Canada emitted into the atmosphere, which is responsible for 2021; Schummer 2022). one-quarter of the warming that we experience today In oil and gas industry, gas venting (releasing to (Environmental Defense Fund 2020). Methane concen- atmosphere) and flaring (burning) are increasingly trations in the atmosphere have reached a record high adding to the global emission problem. Natural gas is a by-product of oil fields and is vented or flared level in 2021, which is nearly three times the pre-indus- when it is uneconomical to collect and sell. CH trial levels (US National Oceanic and Atmospheric is the 4 Ko et al. Biochar (2023) 5:15 Page 3 of 12 main component of vented natural gas. Each ton of Reddy 2014, 2015a, b, c; Shafawi et al. 2021), although not CH causes over 70 times more global warming over for oil and gas field applications. There are abundant for - 20 years than a ton of CO (Forster et al. 2007). Flaring estry and agricultural wastes which can be used to make can reduce the global warming effect, but the resultant biochar adsorbents. Biochar may have lower C H adsorp- CO is still a greenhouse gas. Moreover, C H is a clean tion capacity than activated carbons, and hence a larger 2 4 and valuable energy source that should not be wasted. volume of biochar is needed to store the same quantity We have been exploring collecting and storing instead of CH . However, compared to vehicle applications, cost of venting and flaring natural gas, and using the gas could be more important than volume or space for oil as on-site fuel to provide heat and power in oil and gas and gas fields. Besides, the spent biochar adsorbents may fields. Gas engines, diesel engines, and dual fuel engines be used for combustion and soil amendment. Thus, the can all work with CH . However, for a steady gas sup- overall advantage of using biochar for C H capture and 4 4 ply to the engines, an efficient and cost-effective means storage can be significant. of storage is needed. Adsorbed natural gas (ANG) can In this work, we studied CH adsorption behavior of be a competitive technology for fuel storage in natural biochars that were produced from forestry wastes, and gas vehicles (Alhasan et al. 2016), and would be more discussed the effectiveness of the biochars as adsorbents economical compared to liquefied natural gas (LNG) for the targeted application in oil and gas fields. or compressed natural gas (CNG) for oil and gas fields. Biochars can make low-cost adsorbents (Bamdad et al. 2 Materials and methods 2018; Dissanayake et al. 2020; La et al. 2019; Nanda et al. 2.1 Adsorption measurement 2016; Zhang et al. 2019). Such adsorbents may store Measurement of the adsorption was carried out with natural gas at ambient temperature and moderate pres- a volumetric method. A commercial sorption analyzer sure and eliminate the need for high-pressure compres- PCT-Pro manufactured by Setaram Inc. was used for sion the associated large compressors and thick-walled adsorption experiments. The analyzer can measure heavy vessels. This would be particularly attractive to adsorption under pressure up to 200 bar, with sample small and medium-sized oil and gas producers for cost size up to 5 ml. The PCT-Pro is a Sievert-type analyzer. A savings. Moreover, adsorbed gas can be moved easily schema tic diagram of the measurement system is shown to where it will be used, without the need for pipelines. in Fig. 1. This is another benefit because pipelines are typically not The free volume of the sample reservoir was calibrated equipped in oil fields for transporting gas (Collins 2019). with helium at the experimental temperature for each There are a large number of studies on CH adsorbents, adsorbent sample. C H was pressurized in the reference 4 4 including activated carbons, for vehicle applications. reservoir, then released into the sample reservoir con- Compared to activated carbons, biochar would be more taining the adsorbent sample for adsorption to take place. cost-effective for oil and gas fields. Biochar is cheap and The amount of CH adsorption was calculated by the widely available. It has been forecasted that the world’s difference between the equilibrium pressure before and biochar market will double by 2026 (Blooming Burg- after gas injection into the sample reservoir. To obtain spring 2022). Biochar adsorbents for greenhouse gases an adsorption isotherm, the pressure could be increased including methane have been actively studied (Delgado stepwise automatically through a computer program of et al. 2017; Dicko et al. 2018; Durán-Jiménez et al. 2021; the analyzer. Gargiulo et al. 2018; Greco et al. 2022; Sadasivam and Fig. 1 A schematic diagram of the Sievert measurement system Ko et al. Biochar (2023) 5:15 Page 4 of 12 The molar amount of gas admitted into the reference analysis; bulk density were determined using a sam- reservoir and the molar amount of gas remaining at the ple cell with a known volume, and skeletal density were adsorption equilibrium were determined by pressure– determined by a pycnometer (Micromeritics, Accupyc volume–temperature relations before and after adsorp- II 1340). Compositional analyses including proximate tion using non-ideal gas equations incorporated in the analysis (moisture, ash, volatile matter, and fixed carbon), computer program. The difference of CH adsorbed at ultimate analysis (C, H, N, O, and S) and X-ray fluores - each pressure step in the sample was calculated by the cence (XRF) metal oxide analyses are shown in Table 2. computer program from the pressure difference between In the above materials BC refers to biochar and AC the equilibrium adsorptions. The pressure decrease of refers to activated carbon. The biochars are all from CH gas in the sample reservoir corresponded to the forestry wastes which are abundant. BC-Ash is an ash adsorption to the sample. The quantity of gas is related residue collected from a waste-wood boiler by FPInnova- to pressure by the gas law. Gas compressibility factor is tions, a not-for-profit R&D organization. BC-Biocarb and determined for different pressure and temperature condi - BC-Elkem are commercial biochar products for metal- tions using the National Institute of Standards and Tech- lurgic uses. BC-Birch was prepared in the laboratory of nology (NIST) database Thermophysical Properties of CanmetENERGY-Ottawa by pyrolyzing a wood (birch) −1 Fluid Systems. residue with a heating rate of 5 ℃ min up to 600 ℃ and holding for 3 h in argon. AC-FW, AC-F400 and AC- CABOT are commercial activated carbons. 2.2 Materials Four biochars were studied in this work. Three activated 3 Results and discussion carbons were also studied for comparison. Physical prop-3.1 Adsorption capacity erties of these materials are shown in Table 1, where BET Experimental results for adsorption of C H on the bio- surface area, pore volume and average pore width were chars are shown in Fig. 2. All the four biochars showed determined using a porosimetry analyzer (Micromerit- similar patterns of adsorption. It is clear that the amount ics, ASAP2020); particle size were determined by sieve of adsorption increased with pressure generally and Table 1 Properties of adsorbent materials Sample Type BET surface Pore volume Average pore Particle size (mm) Bulk density Skeletal 2 −1 3 −1 −1 area (m g ) (cm g ) width (Å)(g ml ) density −1 (g ml ) BC-Ash Non-commercial 490 0.25 19.98 1.18–1.70 0.06 2.00 BC-Birch Lab-made 34 0.02 24.07 1.18–3.36 0.10 – BC-Biocarb Commercial 525 0.29 22.26 1.70–3.36 0.13 1.86 BC-Elkem Commercial 3.72 0.06 646.4 1.18–1.70 0.16 1.42 AC-FW Commercial 970 0.65 26.66 1.18–1.70 0.06 2.05 AC-CABOT Commercial 551 0.54 39.44 1.18–1.70 0.40 2.06 AC-F400 Commercial 907 0.52 22.80 1.18–1.70 0.59 2.14 BC denotes biochar and AC denotes activated carbon Table 2 Compositional analysis of adsorbent materials (by weight percentage) a b Sample Moisture Ash VM FC C H N S O SiO Al O Fe O TiO P O CaO MgO SO Na O K O 2 2 3 2 3 2 2 5 3 2 2 BC-Ash 8.68 12.03 12.88 66.41 71.8 0.64 0.31 < 0.05 6.56 13.6 4.4 2.7 0.2 1.8 28.0 4.3 13.9 3.4 12.7 BC-Birch 4.54 5.00 n/a n/a 73.1 1.98 0.55 0.20 14.5 n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a BC- Biocarb 6.31 6.21 6.01 87.78 89.2 0.85 0.51 0.0 3.19 41.6 7.3 14.7 14.7 0.9 13.0 3.1 0.9 1.9 7.3 BC-Elkem 3.32 1.43 26.56 72.01 79.9 3.80 0.29 0.0 14.6 7.2 2.4 2.1 0.1 1.5 35.2 5.4 1.01 0.3 11.4 AC-FW 1.92 2.25 2.46 93.37 92.3 0.44 0.68 < 0.05 2.39 1.9 1.5 1.5 < 0.03 3.4 29.5 5.8 30.9 0.3 13.9 AC-CABOT 7.77 19.57 5.15 67.51 67.7 0.49 0.63 0.72 3.14 70.2 15.7 1.4 2.3 0.1 1.4 1.0 2.4 2.8 1.3 AC-F400 3.93 5.94 2.98 87.15 86.9 0.19 0.84 0.64 1.56 n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a VM denotes volatile matter FC denotes fixed carbon Ko et al. Biochar (2023) 5:15 Page 5 of 12 Fig. 2 Adsorption of CH on biochars and activated carbons as a function of pressure decreased with temperature. BC-Biocarb showed the excess adsorption (Mosher et al. 2013; Myers and Mon- highest adsorption capacity, followed by BC-Ash. The son 2002). This will be discussed in the appendix. other two biochars showed lower adsorption capac- The results for adsorption of CH on the three acti- ity. It is worth noting that C H adsorption by BC- vated carbons are also shown in Fig. 2 for compari- Elkem at 303 K (30 °C) increased with pressure first son. AC-FW showed the highest adsorption capacity, but after a maximum value it decreased with pressure which was over twice that of the biochars. AC-CABOT and approached zero adsorption. BC-Biocarb and BC- showed the lowest adsorption capacity. Its capacity at Birch also showed a trend of decreasing adsorption with 295 K was higher than that of BC-Biocarb and BC-Ash increasing pressure after a maximum value at 303 K. biochars by only a small degree. However, unlike the Such pressure dependence has been reported for C H case of the biochars, the capacity of AC-CABOT did not adsorption on coal and shale (Hu and Mischo 2022; depend strongly on temperature. The weak temperature Mosher et al. 2013), and could be described in terms of dependence was also exhibited by the other two activated Ko et al. Biochar (2023) 5:15 Page 6 of 12 carbons. This suggested that the activated carbons could give more stable performance in ambient tem- perature range. By contrast, the adsorption capacities of the biochars decreased substantially as the temperature increased from 295 to 303 K. However, for Canadian oil and gas fields, the temperature could be below 295 K and biochars could have considerable CH adsorption capac- ity (the temperature effect is discussed in more detail later). Moreover, activated carbon would cost at least several hundred dollars per ton whereas some biochar wastes, such as BC-Ash, would have zero or negative cost because the cost for disposal is avoided. Considering the cost issue, there is incentive to explore using biochars for Fig. 4 CH adsorption isotherms of 4 different models for biochar CH capture and storage. BC-Ash at 295 K Among the four biochars studied in this work, BC- Biocarb has the highest methane adsorption capacity, fol- lowed by BC-Ash. However, in the discussion hereafter and temperature than compressed gas. By contrast, the we focused on BC-Ash instead of BC-Biocarb, because capacity for compressed gas was essentially independ- BC-Ash has lower cost. BC-Ash is a waste material ent of temperature at ambient conditions, as suggested by obtained from combustion ash of waste wood, which oth- Fig. 3. In Canadian oil and gas fields, the temperature can erwise requires disposal. It also has a reasonable adsorp- be below 295 K. To adsorb gas at low to medium pres- tion capacity. This material has a high skeletal density of −3 sure, large compressors and thick-walled vessels which nearly 2 g cm . With this density the adsorption capac- are necessary for compressed natural gas (CNG) are not ity in terms of the volume that the solid portion occupies required (Kumar et al. 2017). Higher storage capacity of (i.e., the excess adsorption per skeletal volume) was cal- biochar adsorbents than that of CNG with lower pressure culated and compared with the volume of compressed would allow smaller and light-walled vessels, and, because methane under the same pressure, as shown in Fig. 3. As of lower pressure, reduce leaking potential and explosion can be seen, the capacity for accommodating CH by the risk. In consequence, the advantage of adsorbed natural skeletal volume of this biochar was considerably higher gas (ANG) with biochar adsorbents over CNG would be than compressed CH that occupied the same volume more significant for Canadian oil and gas fields. It should in the pressure range up to 75 bar. This suggested that, be noted that there was no evidence suggesting that BC- with the same volume, the biochar would be able to store Ash would be the most promising biochar for methane more CH than compressed methane in our targeted capture and storage. Other low-cost biochar materials, application for oil and gas fields. The storage capacity of which give better performance in adsorption of methane, biochar was increasingly higher with decreasing pressure may exist. Alternatively, the performance of the current biochar may be improved, through surface modification, for example. To describe the C H adsorption behavior, we have examined several common adsorption isotherm mod- els including Langmuir, Freundlich, Sips, BET and Toth models (shown in Appendix 2). Langmuir model is the mostly used adsorption isotherm model for activated carbons, and can be derived theoretically for mon- olayer adsorption. BET model is applicable for mul- tilayer adsorption, but below critical temperature of adsorbates. Hence, it is not applicable for C H under the conditions of our study. Freundlich model, which is empirical, can be used for non-uniform surface Fig. 3 Comparison of storage capacity for biochar BC-Ash and adsorption. Sips model is a combination of Langmuir compressed gas. The lines represent the storage capacity of vessels and Freundlich models. Toth model is a temperature for pressurized CH at 295 K, 298 K, and 303 K. The three lines at these temperatures essentially overlap with each other dependent isotherm model which has six parameters. Ko et al. Biochar (2023) 5:15 Page 7 of 12 Freundlich, Sips and Toth models fit our experimental data well. However, they are empirical models thus the results could not provide insights to the behavior or be extrapolated beyond the range of the experiment condi- tions. Moreover, these models describe our experimen- tal data only slightly better than the Langmuir model, as illustrated in Fig. 4. The Langmuir model is useful for our study not only for describing the adsorption data but also for predicting adsorption capacity at other temperatures. In this work we use Langmuir model as the basis for discussion of the adsorption data. With the Langmuir model, the pressure dependence is given by N bp N = (1) 1 + bp where N is the amount of adsorbed gas molecules; p is gas pressure; N and b are Langmuir capacity and Langmuir constant, respectively, which are inde- pendent of gas pressure. The Langmuir constant b is regarded as an equilibrium constant, which depends on Fig. 5 Description of adsorption behavior by the Langmuir model temperature in the following way (Ruthven 1984): for biochar BC-Ash at 295 K, 298 K, and 303 K, respectively. a with temperature-independent N ; b with temperature-dependent N m m −�H b = b exp( ) (2) RT where T is absolute temperature; b is the value of b at a reference temperature; ΔH is the enthalpy change of gas molecules due to adsorption; R is the gas con- stant. For the temperature dependence of the Langmuir capacity N , there are different views. Some studies treat it as independent of temperature (Ruthven 1984), whereas other studies treat it as dependent on tempera- ture (Fianu et al. 2018). For BC-Ash, we have evaluated the two parameters assuming both a temperature- independent Nm, and a temperature-dependent N , respectively, as shown by Fig. 5. As can be seen, with a temperature-dependent N , the Langmuir model describes better the adsorption behavior of C H on the Fig. 6 Plots using Eq. (3) for CH adsorption data of biochar BC-Ash 4 4 in Fig. 2 biochar. This can also be understood from inspection of the adsorption data. Equation (1) can be rearranged into Figure 7 shows van’t Hoff plots for Langmuir con- p/N = 1/(N b) + p/N m (3) stant b with temperature-independent and tempera- ture-dependent Langmuir capacity cases, respectively. If the Langmuir equation describes the adsorption The plots are approximately linear in both cases, data, a plot of p/N against p should yield a straight line. which may be used for extrapolation for other Such plots for the isotherms at the three temperatures temperatures. are shown in Fig. 6. The plots are approximately linear The temperature dependence of N obtained from at all temperatures. However, their slopes suggest that Fig. 5 may be expressed by N is not constant, but decreases with increasing tem- perature, according to Eq. (3). Ko et al. Biochar (2023) 5:15 Page 8 of 12 Fig. 9 Comparison of predicted storage capacity at 293 K for adsorbed CH on Biochar BC-Ash and compressed CH . The open 4 4 circle represents experimental data at 295 K. The two curves represent the prediction in terms of constant Langmuir capacity and temperature-dependent Langmuir capacity, respectively. The triangle and cross symbols near the bottom represent the molar density of compressed CH at 293 K and 295 K, respectively A plot for N in terms of Eq. (5) is shown in Fig. 8. This Fig. 7 Van’t Hoff plots for b obtained from Fig. 5 for biochar BC-Ash. a plot is approximately linear and may be used to estimate With temperature-independent N ; b with temperature-dependent N values at other temperatures. As an application of the above analyses of the tempera- ture dependence, Fig. 9 shows predicted CH adsorp- tion capacity for BC-Ash at 293 K (20 °C) based on both N = N exp(χ/T ) m m0 (4) temperature-independent and temperature-dependent Langmuir capacity, in comparison to the capacity of where N is the N value at a reference temperature; χ m0 m compressed CH . The two treatments yielded somehow is a parameter which is independent of temperature. This 4 different pressure dependencies. However, the impor - expression has also been used for Langmuir model by oth- tant point is that in both cases an appreciable increase ers for adsorption of methane in shale (Fianu et al. 2018). in the adsorption capacity was predicted as a result of a Equation (4) can be rearranged into temperature decrease of merely 2 degrees. By contrast, lnN = lnN + χ/T m m0 (5) the change in the capacity of the compressed CH by the same degrees of temperature change was hardly observ- able. If the temperature decreases to below 20 °C, which is quite possible for Canadian oil and gas fields, the stor - age capacity of biochar for CH would be further higher than that of compressed gas. 3.2 Adsorption kinetics The time dependence of methane uptake is used to evalu - ate the rate of the adsorption process. Pseudo-first-order model (Eq. 5–1 and 5–2) and pseudo-second-order model (Eq. 6–1 and 6–2) have been used for analyzing adsorption kinetics of other adsor- bent-adsorbate systems (Ho and McKay 1998a, b; Jang et al. 2018): dQ = k (Q − Q ) (5-1) 1 e t Fig. 8 Plot for N in terms of Eq. (5) ( lnN = lnN + χ/T ) for m m m0 dt biochar BC-Ash Ko et al. Biochar (2023) 5:15 Page 9 of 12 where θ is the initial value of θ. ln(Q − Q ) = lnQ − k t e t e 1 (5-2) From Eq. (12), dQ k p t a −(k p+k )(t−t ) −(k p+k )(t−t ) a d 0 a d 0 = k(Q − Q ) (6-1) θ = 1 − e + θ e e t 0 dt k p + k a d t 1 t bp −k (1+bp)(t−t ) −k (1+bp)(t−t ) = + d 0 d 0 (6-2) = 1 − e + θ e 2 0 Q Q t k Q e 2 e 1 + bp (13) where Q is the amount of adsorbate at time t on the N bp adsorbent, and Q is the amount of adsorbate at equilib- −k (1+bp)(t−t ) −k (1+bp)(t−t ) d 0 d 0 N = 1 − e + N e rium. The disadvantage of such models for CH adsorp- 1 + bp (14) tion is that the degree of adsorption is not related to gas pressure. Moreover, the parameter Q would depend where N is the Langmuir capacity and N is the ini- m 0 on the pressure, with higher pressures giving higher Q tial value of N. With a sufficiently long time t, Eq. (14) values. becomes Eq. (1). The Langmuir adsorption model, which is used to Unlike the pseudo-first and second order models, describe adsorption equilibria, could also be used to Eq. (14) explicitly relates the adsorption to pressure, study adsorption kinetics (Wang et al. 2020). The Lang - and the parameters are independent of pressure. muir model is derived with the assumption of equi- Our sorption analyzer uses a computer program to librium between adsorption and the reverse process determine adsorption as a function of time automatically. desorption: The pressure is increased stepwise and the adsorption is calculated from the pressure of the sample holder, which k p(1 − θ ) = k θ a d (7) is connected to the reservoir. In principle, we could apply the equation to the real time data and evaluate the values where θ is the fraction of adsorption sites occupied by of the parameters. However, there is a problem associated adsorbed molecules; k is the rate constant for adsorp- with the analyzer. Each step of pressure increase starts with tion; k is the rate constant for desorption; p is gas a transient peak in pressure signal, as shown in Fig. 10. The pressure. corresponding adsorption reading generated by the com- Rearranging Eq. (7) into puter program exhibits a negative peak shown in Fig. 10. k p Such values are clearly not true values of adsorption. Thus, θ = (8) k p + k a d the time evolution from the start of the pressure increase is not known. We can fit the equation to the data by adjusting leads to Eq. (1), the Langmuir equation, N bp N = (1) 1 + bp where N/N = θ and b = k /k . m a d Equation (7) can be expressed as dθ = k p(1 − θ ) − k θ (9) a d dt For constant CH pressure p, dθ = dt (10) k p − (k p + k )θ a a d dln k p − k p + k θ [ ( ) ] a a d =−(k p + k )dt a d (11) k p − (k p + k )θ [ ] a a d k p − k p + k θ [ ( ) ] a a d ln =−(k p + k )(t − t ) a d 0 (12) Fig. 10 Time evolution of pressure (upper) and adsorption (lower) k p − (k p + k )θ [ ] a a d 0 during kinetic measurement for biochar BC-Ash Ko et al. Biochar (2023) 5:15 Page 10 of 12 the decrease of the free space that is occupied by the gas phase because of the increase of adsorbed phase. For volumetric and gravimetrical measurement of adsorption, the observed adsorption can be expressed by M = M (1 − ) (A1) where M is the observed adsorption or excess adsorption; M is the actual adsorption; ρ and ρ are g a the density of the gas phase and the adsorbed phase, Fig. 11 Description of the time evolution of CH adsorption for respectively. The observed adsorption is lower than biochar BC-Ash at 16 bar in terms of the Langmuir model the actual adsorption. The difference between M and M increases with increasing gas pressure as a result the starting time t and an example is shown in Fig. 11 for of increasing ρ . When ρ equals ρ the observed g g a 16 bar. Whereas Eq. (14) can be seen to give a reasonable adsorption becomes zero. In the present work, other description of the data, the parameter values would not two biochars (BC Biocarb and BC Birch) also show have high certainty. On the other hand, although it is dif- the trend of decreasing adsorption with increasing ficult to study the kinetics from the data, the equilibrium pressure at 303 K after a peak value, but the acti- adsorption values can be determined despite the transient vated carbons do not show such a behavior. This may peaks. Regarding the kinetics, our concern is whether be reconciled with the lower adsorption level of the the adsorption occurs too slowly. As the data reveal, the biochars at 303 K. Lower adsorption may suggest adsorption is quite fast and reaches equilibrium within two weaker attraction force between the adsorbents and minutes. u Th s, for the present biochar, the kinetic behavior the adsorbate, resulting in a larger distance between is not as important as the adsorption capacity. the surface of the adsorbents and the center of the adsorbed molecules. In consequence, the density of the adsorbed phase ρ is lower and results in the observed maximums. 4 Conclusions Biochar from forestry wastes shows promise for the cap- ture and storage of methane to contribute to the efforts Appendix 2: Adsorption models used in this work in methane emission reduction from oil and gas indus- The adsorption models that have been used to analyze try. In particular, biochar BC-Ash, which is a combustion the data are shown in Table 3. ash residue, showed a reasonable adsorption capacity and rapid methane take-up. Although the adsorption is lower by over 50% than activated carbon in the studied tem- Table 3 Equations and parameters of adsorption isotherm perature range 295–303 K, it could increase faster with models decreasing temperature. Moreover, the anticipated stor- Model Equations Parameters age capacity in terms of volume can be higher than that −1 Nm∗bp Langmuir N (mmol g ) of compressed methane for the targeted pressure and N = m 1+bp −1 b (bar ) temperature conditions in the oil and gas fields, suggest - −1 −1/n 1/n Freundlich K (mmol g bar ) N = Kp ing significant cost advantages. We hope our work will n (dimensionless) arouse more interest in this topic and stimulate more −1 1/n Sips N ∗(bp) N (mmol g ) N = 1 −1 investigations to contribute to the mitigation of methane n b (bar ) 1+(bp) n (dimensionless) emissions. −1 P 1 C−1 P BET N (mmol g ) = + ∗ N∗(P −P) N ∗C N ∗C P 0 m m 0 C (dimensionless) −1 Ns∗bp Toth Ns, Ns (mmol g ) N = 0 1/t −1 (1+(bp) ) b, b (bar ) Q T 0 Q/RT (dimensionless) Appendix 1: Decreasing methane adsorption b = b ∗ exp{ ∗ − 1 } RT T T (K) with increasing pressure shown by biochars t = t + α(1 − ) t, t (dimensionless) T 0 Decreasing methane adsorption with increasing pres- T α (dimensionless) Ns = Ns ∗ exp{χ(1 − )} χ (dimensionless) sure after a peak value has been reported for coal, shale and activated carbon. The behavior is related to Ko et al. Biochar (2023) 5:15 Page 11 of 12 Acknowledgementsmedia/ five- keys- oil- gas- compa nies- estab lish- credi ble- metha ne- reduc The authors are thankful to Ms. Maria Abbassi, Dr. Xianai Huang and Dr. Lia tion- targe ts Kouchachvili of CanmetENERGY-Ottawa, Natural Resources Canada, who have Fianu J, Gholinezhad J, Hassan M (2018) Comparison of temperature-depend- provided biochar and activated carbon samples along with various advices. ent gas adsorption models and their application to shale gas reservoirs. Energy Fuels 32(4):4763–4771 Author contributions Forster P, Ramaswamy V, Artaxo P, Berntsen T, et al (2007) Chapter 2: changes All authors contributed to this work. All authors read and approved the final in atmospheric constituents and radiative forcing, Climate Change 2013: manuscript. the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. 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Journal
Biochar – Springer Journals
Published: Mar 20, 2023
Keywords: Biochar; Adsorbent; Methane emissions; Greenhouse gas reduction; Adsorption behavior