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Emissions factors from distributed, small-scale biomass gasification power generation: Comparison to open burning and large-scale biomass power generation
Atmospheric Environment 200 (2019) 221–227
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Emissions factors from distributed, small-scale biomass gasification power generation: Comparison to open burning and large-scale biomass power generation
T
Omar Y. Ahmed, Matthew J. Ries, William F. Northrop∗ Department of Mechanical Engineering, University of Minnesota, 111 Church Street SE, Minneapolis, MN, 55455, USA
G R A P H I C A L A B S T R A C T
A R T I C LE I N FO
A B S T R A C T
Keywords: Biomass gasification Criteria pollutants Open burning Waste biomass
Waste woody biomass is one of the most readily available yet underutilized renewable energy sources. Small quantities of wood waste in remote locations are often openly burned when they are not economical to transport and burn in large-scale facilities. Small-scale (10–100 kW) distributed gasifier-generator systems offer an alternative use for this biomass. In this work, we present emissions factors experimentally measured from a commercially available gasifier-generator system. Average emissions factors per mass of dry biomass with high quality producer gas were found to be 1.53 kg-CO2, 11.3 g-CO, 8.7 g-CH4, 2.4 g-NOx, and 0.01 g-soot per kg of feedstock. On an energy basis, emissions were 2.04 kg-CO2, 30.3 g-CO, 18.6 g-CH4, 5.0 g-NOx, and 0.02-g soot per kWh of electricity produced at a maximum load of 15 kW. Our research found that producer gas heating value is inversely proportional to both power output and biomass moisture content. Low quality producer gas was found to significantly increase CO, CH4 and soot emissions from the system but decrease NOx emissions. Small-scale biomass gasification emits less CO2, CO, and soot than open burning, but further improvements are required before emissions from small-scale systems are competitive with emissions from large-scale biomass power generation.
1. Introduction
global energy usage if fully utilized (Parikka, 2004). Biomass is predominantly used in large-scale power generation (> 1 MW), accounting for 1.6% of total U.S. electricity generation in 2016 (Electric Power Monthly, 2017). Steam boiler and fluidized bed systems are the most
An estimated 100 EJ of energy can be sustainably produced annually from biomass sources worldwide, enough to comprise 30% of
∗
Corresponding author. E-mail addresses: [email protected] (O.Y. Ahmed), [email protected] (M.J. Ries), [email protected] (W.F. Northrop).
https://doi.org/10.1016/j.atmosenv.2018.12.024 Received 7 September 2018; Received in revised form 12 December 2018; Accepted 14 December 2018 Available online 19 December 2018 1352-2310/ © 2018 Elsevier Ltd. All rights reserved.
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common, although integrated gasification combined cycle (IGCC) plants have also recently been implemented. Both types of facilities emit CO2, CO, CH4, NOx, and particulate matter (AP-42 Section 1.6, 2003; Well-to-Wheels Analysis, 2011). In addition, these plants often use biomass from farmed sources, whose sustainability is contested because using arable land for bioenergy production directly competes with natural ecosystems and the food sector (Nuss et al., 2013). Waste residue is gaining interest as an alternative bioenergy source to farmed sources. Derived from tree trimming, wood-borne pest remediation, and forest fire risk reduction, waste residue has the potential to comprise up to 70% of available biomass usage (Langholtz et al., 2016). However, it currently accounts for only 19% of consumed biomass in the U.S. (Langholtz et al., 2016). Since most waste biomass is spatially distributed and cannot be economically transported to largescale energy facilities, it is left to decompose or more often burned in open piles. Piling is done to either remove dry organic matter that could feed wildfires or to clear land for agriculture. Emissions produced from open burning vary widely but include CO2, CH4, CO, NOx, SOx, particulates, volatile organic compounds, and black carbon (Akagi et al., 2011; Petrov et al., 2017; Permadi and Oanh, 2013). Any remaining biomass that is not used by people or consumed in natural fires eventually decomposes, a process that emits the greenhouse gases CO2, CH4, and N2O (Wihersaari, 2005). Biomass gasification has emerged as an alternative pathway to open burning and decomposition. Gasification uses pyrolysis to generate producer gas that is combusted for heat and power. Gasification is also accompanied by pollutant emissions including CO, NOx, soot, and tars, while emitted CO2 and CH4 are significant greenhouse gases (Climate Change 2007, 2007; Raub et al., 2000; Kampa and Castanas, 2008; Likens and Bormann, 1974; Harrison and Yin, 2000). Still, it has potential to be used in small-scale applications, providing environmentally and economically competitive energy for rural areas by using locally available waste biomass. For example, in Brazil waste biomass gasification could offset natural gas in electricity production, reducing greenhouse gas emissions by as much as 58% compared to other pathways for biomass (Campbell and Block, 2010). Additionally, biochar produced as a byproduct of gasification can be used as a soil amendment to improve long-term carbon sequestration and soil fertility (Niu et al., 2017). Although small-scale gasification has been presented as a viable option for wood waste, no study to date has characterized emissions factors from these systems for use in regional models or environmental impact studies. This work explores the emissions from a 20-kW integrated gasifiergenerator designed to convert woody biomass to electricity. The focus of the experiments was to determine steady-state emissions of the full system as a function of electrical power output. These emissions factors were compared to existing waste biomass usage paths like open burning, decomposition, and large-scale power generation, including compensation for biomass feedstock processing and transportation.
Fig. 1. Commercial gasifier-generator system diagram, including gas sampling points A and B. A more detailed process flow diagram is included in the supplementary material accompanying this paper.
The two-step filtration process contains a cyclone and a packed charcoal filter. The cyclone is the primary solid particle reduction mechanism and the packed bed filter removes tars and remaining particulates from the gas stream. An earlier iteration of this filter design had been shown to collect as much as 99% of particulates from the producer gas and eliminate 75% or higher of common tars (Hamilton et al., 2014). The current generation filter used for this study includes an extra layer of feedstock. The engine used in the system is a commercially available GM Vortec 3.0L 4-stroke natural gas engine modified to accept producer gas as a fuel with a fixed spark timing of 42° BTDC and a constant speed of 1800 RPM. The engine is attached to a MeccAlte NPE32 E/4 12-wire 4Pole generator. The equivalence ratio for the engine is controlled to a setpoint of λ = 1.05 using feedback from an oxygen sensor installed in the exhaust. A locally harvested mixture of hardwood/softwood chips was used as feedstock for experiments. Woodchips were stored outside and exposed to sunlight to facilitate moisture evaporation. Abnormally large woodchips were filtered out with a 1.5-inch mesh to avoid jamming the hopper, and manual sifting ensured extremely wet chips were not used. The mass of a small woodchip sample was measured before and after warming in an oven at 105 °C for 24 h. The difference in mass was used to estimate moisture content. A more accurate real-time moisture calculation, discussed in supplementary material found in Appendix A, was also implemented. The average moisture content of the feedstock varied from 23 to 26% throughout testing.
2. Methods 2.1. Gasifier system The gasification system used in this experiment was a commercially available 20-kW Power Pallet integrated gasifier-generator system produced by All Power Labs (Berkeley, CA). The flow diagram of the system is shown in Fig. 1. The gasifier used in the system is an Imbert style downdraft reactor that uses preheated atmospheric air injected in the middle of the reactor to partially oxidize the fuel. Chipped woody biomass enters at the top of the reactor and flows down as pyrolysis, combustion, and tar cracking reactions occur to create producer gas. Ash is periodically removed at the bottom of the gasifier using an auger. The producer gas then preheats the incoming atmospheric air while being routed through the filtration processes.
2.2. Instrumentation The primary instrument used for measuring CO, H2, CO2, and CH4 was a Laser Gas Analyzer (LGA) (ARI, Eden Prairie, MN). The LGA uses Raman spectroscopy to differentiate between species (Raman 222
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spectroscopy, http://www.atmrcv.com/technology.html). The gas sample was sent through a cooler to drop out excess moisture to protect the instrument; a water correction analysis was implemented during analysis, the details of which are described in supplementary material. The LGA does not distinguish between different hydrocarbon species, but CH4 has been shown to be the dominant hydrocarbon present in producer gas (Akagi et al., 2011; Sinha et al., 2004; Bhattacharya et al., 2002). Thus, any hydrocarbons detected were assumed to be methane. Soot was measured using a Microsoot Sensor (MSS) analyzer (AVL, Gratz, Aus.). The MSS measures total soot mass concentration without differentiating by particle size (AVL, 2009). Prior to measurement, the sample was diluted with atmospheric air to reduce the dew point and condensation inside the instrument. NOx was measured using a 600 series CLD NOx analyzer (California Analytical Instruments, Orange, CA), which can differentiate between NO and NO2. A short, heated line held at 90 °C was used between the exhaust and instrument to minimize reactions prior to measurement. Temperature was measured using K-type thermocouples. The temperature measurement locations were at the top of the reactor and immediately after the filter. Pressure was monitored through the system's onboard Arduino controller, and was measured at the top of the reactor and on the producer gas leaving the reactor. Differential pressure was measured with an Omega PX653-10D5V transducer across an orifice plate through which the producer gas flowed after being filtered. Incoming reactor air and engine air flowrates were measured using two automotive B3H7 mass airflow (MAF) sensors (Green Motion, Irvine, CA). The flowrate of the producer gas post-filter was measured using the orifice plate and relevant LGA, temperature, and pressure readings to correct for density.
Fig. 2. CO, H2, CO2, and CH4 concentrations for one full sweep of LGA measurements as a function of time and electrical output power.
producer gas and gas with lower concentrations is referred to as low quality producer gas. Low quality producer gas, like that produced in the fourth load shown in Fig. 2, was observed to occur at high power output, when the reactor had difficulty keeping up with the engine's demanded flowrate. It also occurred with high feedstock moisture content because the reactor struggled to maintain high enough temperatures to sustain efficient gasification. Producer gas quality also had significant impact on the engine performance. High quality producer gas was more energy dense, thus resulting in higher combustion temperature and more complete burning than low quality gas, as discussed below.
2.3. Experimental methods Steady state data were collected at four different loads controlled by four 208 V, 16 A resistive heaters. Measurements were taken at 3.4, 6.8, 10.2, and 13.6 kW. Producer gas was sampled after the packed bed filter (location A in Fig. 1), while exhaust was sampled from the engine exhaust line prior to emission into the atmosphere (location B in Fig. 1). To achieve steady state readings, the gasifier was allowed 10 min to stabilize at each new load followed by 10 min sampling the producer gas and 10 min sampling the exhaust. Testing was completed over a period of three days; on each day data was collected for all four loads. This resulted in three sets of data for each load, or 12 sets total. Thermal efficiency of the system was calculated as the ratio of electrical power divided by the lower heating value (LHV) of the feedstock times the calculated feedstock mass consumption rate. The LHV value of woody biomass was taken as 16 MJ/kg on a dry basis (Telmo and Lousada, 2011). For all examined parameters, experimental uncertainty was estimated by propagating one standard deviation for each measurement through all necessary calculations using the method of sequential perturbation (Figliola and Beasley, 2000). Instrument error and bias were not considered in uncertainty calculations. While individual standard deviations for each measurement were small (< 5%), the final uncertainty on the emission factors became large (up to 20%) due to error propagation through the multistep moisture content calculations.
3.2. Emissions factors of criteria pollutants The gases CO2, CO, CH4, NOx, and soot were the primary emissions measured in the experiments. For all the figures given in this section, emissions are reported in two ways: as mass emissions factor in mass of pollutant per mass of biomass consumed on a dry basis, and as energy specific emissions factor in mass of pollutant per kW-hr of electricity produced. The primary greenhouse gas emission from the system was carbon dioxide because it is a product of complete combustion. As shown in Fig. 3, CO2 mass emissions per dry biomass input do not show a clear trend with electrical load and only vary by about 15%. This observation may be expected since the biomass has a fixed carbon content regardless of load and can only leave the system one of three ways: solid ash, liquid tar, or exhaust gas. The data indicate that the gasifier system had nearly constant ash and tar production as a function of electrical power output within measurement uncertainty. However, some trends were apparent. At low loads, the slightly lower CO2 emissions factor can be attributed to lower reactor temperatures causing a higher fraction of the feedstock to be converted to biochar rather than CO2. The decrease in CO2 emissions seen at the maximum load can be attributed to lower producer gas quality. The highest load required a higher producer gas flowrate into the engine to maintain speed, so the residence time of reactants in the gasifier decreased. Quality decreased due to shorter residence time, resulting in more incomplete combustion products, where some carbon was emitted as CO and CH4 instead of as CO2. The energy specific emissions of CO2 showed a clear downward trend as a function of electrical power output. This is due to the strong correlation between thermal efficiency and load, as shown in Fig. 4. Low overall thermal efficiency for the system at low electrical output
3. Results and discussion 3.1. Producer gas Fig. 2 shows time-resolved gas concentrations from a selected fourstep load sweep. Periods of elevated CO, H2, and CH4 concentrations indicate a producer gas measurement period, and high CO2 segments indicate an engine exhaust measurement period. For the remainder of the results discussed, producer gas with concentrations of CO and H2 both above 15% is referred to as high quality 223
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dominating factor, the biochar production and combustion efficiency effects discussed previously were still present. Carbon monoxide emissions factors exhibit very different trends than CO2, as given in Fig. 3 where it is clear that lower combustion efficiency led to higher CO emissions. As expected, the CO mass emissions factor was low when the producer gas quality was high and increased as gas quality became poorer at high electrical load. Conversely, the energy specific CO emissions initially reduced due to increasing thermal efficiency. At the higher loads, increasing CO from reducing producer gas quality overwhelmed the reduction effect caused by increasing thermal efficiencies, resulting in increased CO emissions for the highest two load settings. CH4 and CO emissions showed similar trends, as shown in Fig. 3, because both are products of incomplete combustion. NOx formation in combustion is a strong function of temperature based on the well-known Zel'dovich thermal mechanism. NOx emissions for the system are given in Fig. 3. At low loads, combustion temperatures inside the engine were lowest so NOx emissions were also minimized. As the load increased, in-cylinder temperatures increased and NOx concentrations correspondingly rose. Nearing peak electrical load, NOx emissions plateaued due to poorer producer gas quality. A tradeoff between increasing thermal efficiency with electrical output and increasing NOx per kg of feedstock led to near constant energy specific NOx emissions. Fig. 5 shows soot emissions from two different runs plotted together on the same axis for comparison. Total soot emissions were found to be highly dependent on the quality of the producer gas and were not a strong function of electrical power output. Average soot concentrations with high quality producer gas were typically below 0.02 mg/m3 regardless of load. This translates to 0.7 mg soot per kg of dry biomass, which is low even compared to large-scale biomass power plants as will be discussed in section 3.4. Soot emissions increased by orders of magnitude when the gasifier produced low quality producer gas. Fig. 5 highlights an extreme case of low quality producer gas when using very wet feedstock, where soot emissions exceeded 1.7 mg/m3 for short periods. These spikes occurred at the times of low engine output. During these periods, H2 and CO concentrations in the producer gas were not sufficient to retain high enough flammability for spark-ignition combustion, causing misfire and incomplete burning. While the spikes exhibited by the low-quality producer gas were nearly 100 times higher than the standard operating soot concentration, the peak soot levels were still within reasonable
Fig. 3. Mean mass and energy specific emissions factors of CO2, CO, CH4, and NOx as a function of electrical load for the gasifier generator system.
Fig. 4. Mean thermal efficiency of the gasifier generator system as a function of electrical load.
load was mainly a function of constant heat losses from the gasifier system and lower engine efficiency, and was consistent with our previous work with a similar gasifier-generator system (Hamilton et al., 2014). Less biomass required to produce an equal amount of electricity led to lower CO2 emissions. While the measured producer gas flowrates agreed with the CO2 emissions on a per kWh basis and were clearly the
Fig. 5. Soot emissions versus time for the gasifier-generator system when operated over selected periods with high and low quality producer gas. 224
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incomplete combustion. This incomplete combustion lowered engine combustion temperatures which in turn reduced NO production. The data reported here also agrees with previous studies that have concluded downdraft gasifiers are particularly susceptible to feedstock conditions when compared to other gasifier designs (Bridgwater, 1995). During the set of experiments conducted in this study, NOx mole fraction temporarily passed 1100 ppm (7.25 g/kg dry) when an unusually dry patch of feedstock was in the reactor. Although very dry feedstock is preferable for high power output and system stability, potentially high output NOx emissions illustrate the need for exhaust aftertreatment or three-way catalysts. 3.4. Emissions comparison to other waste wood utilization methods Here we present a comparison of emissions factors from small-scale gasification power generation to alternative biomass utilization methods. These methods include decomposition, open burning, use in a residential stove, and use in a large-scale plant. Open burning and residential emission factors were selected from literature, and estimates from the GREET 2016 (v1.3.0.13107) model were used to determine emissions factors for large-scale power generation. The emissions reported for gasification are given as a range from low to high electrical output power with high producer gas quality. Open-air decomposition is highly dependent on the surrounding environment. It was assumed that 5% of the feedstock's carbon content were in a wet and/or poorly aerated environment such as piles created during forestry management practices (Wihersaari, 2005). Drier and more exposed biomass would tend to produce higher CO2 and lower CH4 levels during decomposition. The total greenhouse impact, indicated as ‘Total CO2e’ in Table 1, was calculated using the 100-year GWP values recommended by the IPCC as shown in Equation (1) (Climate Change, 2007, 2007).
Fig. 6. Mean moisture content effects on emissions as a function of electrical output load.
operating bounds compared to other biomass burning methods, at approximately 0.26 g/kg dry feedstock. This study focused on species emitted into the atmosphere, and thus biochar and liquid tar production are not reported. However, a rough estimate based on the total amount of biochar produced throughout the length of the experiment indicates that about 2% of the initial feedstock was eventually converted into biochar and removed through the system's cyclone or ash container. Additional study is required to measure biochar production more quantitatively.
CO2 e = CO2 + 44/28 ∗ CO + 25CH4 + 298N2 O#
(1)
While CO is not a direct greenhouse gas, it has been shown to be further oxidized to CO2 in the atmosphere (Lashof and Ahuja, 1990). Under the right conditions, CO can also contribute to a rise in atmospheric methane due to a reduction in the amount of OH present in the atmosphere, raising CO's effective GWP value. CO's relationship with atmospheric methane is dependent on environmental factors and is not well documented (Lashof and Ahuja, 1990). For simplicity, CO was assumed to oxidize into CO2 in the atmosphere, leading to a GWP of 44/ 28 (ratio of molecular weights). Large-scale plants have higher thermal efficiency compared to smaller plants due to lower heat losses per unit energy consumption which leads to the highest CO2 emissions, while open burning and residential usage have lower combustion efficiencies either by design (restricted airflow in the case of residential furnaces) or environment (local oxygen deficiencies during an open burn) that lead to leftover charcoal and increased carbon emitted as CO, soot and CH4. As previously stated, NOx formation is a function of combustion temperature, which tends to rise with combustion efficiency; however, large-scale plants typically include NOx aftertreatment on their exhaust, thus
3.3. Emissions dependence on biomass moisture content Feedstock moisture content was one of the most significant factors in determining producer gas quality, and thus electrical output. While moisture content was between 20% and 30% for each load on each day, the effects are still apparent in the emissions data. Fig. 6 shows CO and NOx emissions factors for each of the three days along with corresponding feedstock moisture content. Fig. 6 shows that while CO emissions factors from the gasifier generator system increased with increasing moisture content, NOx emissions had the opposite trend. Excess CO is an indicator of
Table 1 Mass emission factor comparisons for various paths of biomass usage on a dry mass basis compared to small-scale gasification power generation (Well-to-Wheels Analysis, 2011; Akagi et al., 2011; Wihersaari, 2005; Sinha et al., 2004; Bhattacharya et al., 2002; Christian et al., 2003; Aurell et al., 2015; Liu et al., 2014; Yokelson et al., 2011; Ozgen et al., 2014). Pathway
CO2 (kg/kg)
NOx (g/kg)
CO (g/kg)
CH4 (g/kg)
Soot (g/kg)
N2O (g/kg)
CO2e (g/kg)
Open Burning Residential Decomposition IGCC Turbine Steam Turbine Gasifier (this work)
1.62 1.56–1.62 1.74 1.84 1.83 1.34–1.60
2.9 0.05–2.7 – 0.17 1.13 1.6–3.6
97.2 19–154 – 0.16 5.82 9.6–21.6
4.6 6–10 33.3 0.07 0.60 8.6–13.3
15.5 1.2–10 – 0.05 2.57 0–0.26
– – 0.04 – – –
1888 1740–2112 2584 1841 1854 1570–1966
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Table 2 Emission factors from three biomass power generation technologies including small-scale gasification from this work on a kWh basis (Well-to-Wheels Analysis, 2011). Power Generation Method
CO2 (kg/kWh)
NOx (g/kWh)
CO (g/kWh)
CH4 (g/kWh)
Soot (g/kWh)
IGCC Turbine (η = 40%) Steam Turbine (η = 22%) Gasifier (this work) (η = 5–12%)
0.83 1.49 2.1–4.6
0.08 0.92 4.8–5.5
0.07 4.73 22.8–32.6
0.03 0.49 17.5–29.6
0.02 2.09 0–0.78
Table 3 Processing and transportation emissions factors used in the analysis (Well-to-Wheels Analysis, 2011). Process
CO2 (g/kg)
CO (mg/kg)
CH4 (mg/kg)
NOx (mg/kg)
PM (mg/kg)
Collection + On-Site Chipping Transportation (per 100 mi.)
13.4 40.2
47 36.2
25.8 44
96.4 97
7.4 1.6
On an energy specific basis, small-scale gasification has much higher emissions compared to large-scale power production methods due to its lower thermal efficiency as given in Table 2. For reference, coal-fired steam turbines operating at similar efficiencies to biomasspowered turbines can be expected to produce higher carbon emissions per kWh because coal has much higher carbon content than biomass. Data presented in Tables 1 and 2 consider only on-site emissions from different biomass consumption processes. To get a more detailed understanding of the entire associated lifecycle, additional processing and transportation emissions need to be considered to compare smallscale gasification versus large-scale power generation systems. Table 3 shows the emissions factors used in the analysis taken from the GREET analysis software. The emissions due to collection and chipping are required for both large-scale and small-scale usage, but the transportation distance is a key differentiator. Large-scale plants continually require biomass from a large geographic area to maintain operation, while small-scale gasification requires less transportation as a smaller land area is required. Fig. 7 presents CO2 emission factors for various pathways as a function of transportation distance. Since open burning does not require biomass transport, its emission factor remains constant. Fig. 7 shows that gasification emits less CO2 than open burning so long as the transport radius is smaller than 16 mi. Therefore, this work makes the distinction that small-scale gasifiers should source biomass from less than 16 mi. away. Large-scale turbine plants emit more CO2 than other paths regardless of transport radius. Table 4 shows modified emission factors, assuming large-scale plants require an average of 100 mi. of transportation and small-scale gasification requires only 10 mi. Comparing the values in Table 4 to those from Table 1, CO2 is most noticeably impacted by taking transportation into account, although its impact is less than 3% for a 100-mi. collection radius. Due to the relatively small effect of transportation on emissions, it is more likely that economic costs associated with the supply chain, rather than environmental impact, would restrict biomass collection from larger radii to feed large-scale plants. The analysis shows that overall, biochar production is the main reason for lower CO2 emissions from small-scale gasification on a mass of feedstock basis.
Fig. 7. CO2 emissions factor for four biomass pathways as a function of biomass transport distance. A vertical marker at 16 mi shows where gasification begins emitting more CO2 than open burning.
resulting in a lower emissions factor. Small-scale gasification power generation has the lowest estimated CO2 emissions, largely due to the carbon removed from the system in the form of biochar; it does not necessarily indicate poor combustion efficiency. As seen in Table 1, the CO and soot emissions from the gasifier system, and consequently combustion efficiency, fall between those of open burning/residential use and the large-scale plants. Smallscale gasification has higher CH4 than other power generation methods mainly due to incomplete combustion of the high methane-containing producer gas. The largest emitter of total estimated CO2e is decomposition, with CH4 comprising roughly half of its greenhouse gas emissions. The residential use, open burning, and large-scale generation are all comparable in CO2e because large-scale systems use all the available carbon in the feedstock, while the other systems have charcoal as a byproduct but are offset by the increased CH4 emission. The gasification system's total CO2e is dependent on the output load but was found to be the lowest at low loads due to high combustion efficiency and high rates of biochar production.
Table 4 Modified biomass emission factors including feedstock preparation. Pathway
CO2 (kg/kg)
NOx (g/kg)
CO (g/kg)
CH4 (g/kg)
Soot/PM (g/kg)
Total CO2e (g/kg)
IGCC Turbine (100 mi.) Steam Turbine (100 mi.) Gasifier (10 mi.)
1.90 1.89 1.36–1.62
0.37 1.33 1.7–3.7
0.24 5.90 9.7–21.7
0.07 0.60 8.6–13.3
0.054 2.58 0.01–0.27
1902 1914 1590–1987
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4. Conclusions
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This work characterized the emissions of a small-scale gasifiergenerator and compared the potential impact of gasifying distributed waste biomass for power generation to the impact of other pathways for waste residue. Ultimately, although small-scale gasification has the potential for the lowest overall greenhouse gas emissions potential of energy production processes considered here and has a considerable emissions benefit over open burning, these benefits may not be significant enough to outweigh economic factors associated with capital cost, operational expenses, and feedstock supply chain requirements. A complete techno-economic analysis should be conducted to fully explore the relative advantages of small-scale gasification systems over large-scale energy production from distributed waste biomass. Declarations of interest None. Acknowledgments This work was supported by the State of Minnesota Legislative Citizen Commission on Minnesota Resources under appropriation M.L. 2015, Chp. 76, Sec. 2, Subd. 07b. The authors thank Darrick Zarling and other colleagues at the University of Minnesota's T.E. Murphy Engine Research Laboratory for their technical guidance and support. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.atmosenv.2018.12.024. References Akagi, S.K., Yokelson, R.J., Wiedinmyer, C., Alvarado, M.J., Reid, J.S., Karl, T., Crounse, J.D., Wennberg, P.O., 2011. Emission factors for open and domestic biomass burning for use in atmospheric models. Atmos. Chem. Phys. 11, 4039–4072. AP-42 Section 1.6, 2003. Wood Residue Combustion in Boilers. U.S. Environmental Protection Agency, Washington, DC. Aurell, J., Gullett, B.K., Tabor, D., 2015. Emissions from southeastern U.S. grasslands and pine savannas: comparison of aerial and ground field measurements with laboratory burns. Atmos. Environ. 111, 170–178. AVL, 2009. AVL Micro Soot Sensor Operating Manual/Product Guide. Bhattacharya, S.C., Albina, D.O., Salam, P.A., 2002. Emission factors of wood and charcoal-fired cookstoves. Biomass Bioenergy 23, 453–469. Bridgwater, A.V., 1995. The technical and economic feasibility of biomass gasification for power generation. Fuel 74 (5), 631–653. Campbell, J.E., Block, E., 2010. Land-use and alternative bioenergy pathways for waste biomass. Environ. Sci. Technol. 44 (22), 8665–8669. Christian, T.J., Kleiss, B., Yokelson, R.J., Holzinger, R., Crutzen, P.J., Hao, W.M., Saharjo,
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Emissions factors from distributed, small-scale biomass gasification power generation: Comparison to open burning and large-scale biomass power generation
T
Omar Y. Ahmed, Matthew J. Ries, William F. Northrop∗ Department of Mechanical Engineering, University of Minnesota, 111 Church Street SE, Minneapolis, MN, 55455, USA
G R A P H I C A L A B S T R A C T
A R T I C LE I N FO
A B S T R A C T
Keywords: Biomass gasification Criteria pollutants Open burning Waste biomass
Waste woody biomass is one of the most readily available yet underutilized renewable energy sources. Small quantities of wood waste in remote locations are often openly burned when they are not economical to transport and burn in large-scale facilities. Small-scale (10–100 kW) distributed gasifier-generator systems offer an alternative use for this biomass. In this work, we present emissions factors experimentally measured from a commercially available gasifier-generator system. Average emissions factors per mass of dry biomass with high quality producer gas were found to be 1.53 kg-CO2, 11.3 g-CO, 8.7 g-CH4, 2.4 g-NOx, and 0.01 g-soot per kg of feedstock. On an energy basis, emissions were 2.04 kg-CO2, 30.3 g-CO, 18.6 g-CH4, 5.0 g-NOx, and 0.02-g soot per kWh of electricity produced at a maximum load of 15 kW. Our research found that producer gas heating value is inversely proportional to both power output and biomass moisture content. Low quality producer gas was found to significantly increase CO, CH4 and soot emissions from the system but decrease NOx emissions. Small-scale biomass gasification emits less CO2, CO, and soot than open burning, but further improvements are required before emissions from small-scale systems are competitive with emissions from large-scale biomass power generation.
1. Introduction
global energy usage if fully utilized (Parikka, 2004). Biomass is predominantly used in large-scale power generation (> 1 MW), accounting for 1.6% of total U.S. electricity generation in 2016 (Electric Power Monthly, 2017). Steam boiler and fluidized bed systems are the most
An estimated 100 EJ of energy can be sustainably produced annually from biomass sources worldwide, enough to comprise 30% of
∗
Corresponding author. E-mail addresses: [email protected] (O.Y. Ahmed), [email protected] (M.J. Ries), [email protected] (W.F. Northrop).
https://doi.org/10.1016/j.atmosenv.2018.12.024 Received 7 September 2018; Received in revised form 12 December 2018; Accepted 14 December 2018 Available online 19 December 2018 1352-2310/ © 2018 Elsevier Ltd. All rights reserved.
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common, although integrated gasification combined cycle (IGCC) plants have also recently been implemented. Both types of facilities emit CO2, CO, CH4, NOx, and particulate matter (AP-42 Section 1.6, 2003; Well-to-Wheels Analysis, 2011). In addition, these plants often use biomass from farmed sources, whose sustainability is contested because using arable land for bioenergy production directly competes with natural ecosystems and the food sector (Nuss et al., 2013). Waste residue is gaining interest as an alternative bioenergy source to farmed sources. Derived from tree trimming, wood-borne pest remediation, and forest fire risk reduction, waste residue has the potential to comprise up to 70% of available biomass usage (Langholtz et al., 2016). However, it currently accounts for only 19% of consumed biomass in the U.S. (Langholtz et al., 2016). Since most waste biomass is spatially distributed and cannot be economically transported to largescale energy facilities, it is left to decompose or more often burned in open piles. Piling is done to either remove dry organic matter that could feed wildfires or to clear land for agriculture. Emissions produced from open burning vary widely but include CO2, CH4, CO, NOx, SOx, particulates, volatile organic compounds, and black carbon (Akagi et al., 2011; Petrov et al., 2017; Permadi and Oanh, 2013). Any remaining biomass that is not used by people or consumed in natural fires eventually decomposes, a process that emits the greenhouse gases CO2, CH4, and N2O (Wihersaari, 2005). Biomass gasification has emerged as an alternative pathway to open burning and decomposition. Gasification uses pyrolysis to generate producer gas that is combusted for heat and power. Gasification is also accompanied by pollutant emissions including CO, NOx, soot, and tars, while emitted CO2 and CH4 are significant greenhouse gases (Climate Change 2007, 2007; Raub et al., 2000; Kampa and Castanas, 2008; Likens and Bormann, 1974; Harrison and Yin, 2000). Still, it has potential to be used in small-scale applications, providing environmentally and economically competitive energy for rural areas by using locally available waste biomass. For example, in Brazil waste biomass gasification could offset natural gas in electricity production, reducing greenhouse gas emissions by as much as 58% compared to other pathways for biomass (Campbell and Block, 2010). Additionally, biochar produced as a byproduct of gasification can be used as a soil amendment to improve long-term carbon sequestration and soil fertility (Niu et al., 2017). Although small-scale gasification has been presented as a viable option for wood waste, no study to date has characterized emissions factors from these systems for use in regional models or environmental impact studies. This work explores the emissions from a 20-kW integrated gasifiergenerator designed to convert woody biomass to electricity. The focus of the experiments was to determine steady-state emissions of the full system as a function of electrical power output. These emissions factors were compared to existing waste biomass usage paths like open burning, decomposition, and large-scale power generation, including compensation for biomass feedstock processing and transportation.
Fig. 1. Commercial gasifier-generator system diagram, including gas sampling points A and B. A more detailed process flow diagram is included in the supplementary material accompanying this paper.
The two-step filtration process contains a cyclone and a packed charcoal filter. The cyclone is the primary solid particle reduction mechanism and the packed bed filter removes tars and remaining particulates from the gas stream. An earlier iteration of this filter design had been shown to collect as much as 99% of particulates from the producer gas and eliminate 75% or higher of common tars (Hamilton et al., 2014). The current generation filter used for this study includes an extra layer of feedstock. The engine used in the system is a commercially available GM Vortec 3.0L 4-stroke natural gas engine modified to accept producer gas as a fuel with a fixed spark timing of 42° BTDC and a constant speed of 1800 RPM. The engine is attached to a MeccAlte NPE32 E/4 12-wire 4Pole generator. The equivalence ratio for the engine is controlled to a setpoint of λ = 1.05 using feedback from an oxygen sensor installed in the exhaust. A locally harvested mixture of hardwood/softwood chips was used as feedstock for experiments. Woodchips were stored outside and exposed to sunlight to facilitate moisture evaporation. Abnormally large woodchips were filtered out with a 1.5-inch mesh to avoid jamming the hopper, and manual sifting ensured extremely wet chips were not used. The mass of a small woodchip sample was measured before and after warming in an oven at 105 °C for 24 h. The difference in mass was used to estimate moisture content. A more accurate real-time moisture calculation, discussed in supplementary material found in Appendix A, was also implemented. The average moisture content of the feedstock varied from 23 to 26% throughout testing.
2. Methods 2.1. Gasifier system The gasification system used in this experiment was a commercially available 20-kW Power Pallet integrated gasifier-generator system produced by All Power Labs (Berkeley, CA). The flow diagram of the system is shown in Fig. 1. The gasifier used in the system is an Imbert style downdraft reactor that uses preheated atmospheric air injected in the middle of the reactor to partially oxidize the fuel. Chipped woody biomass enters at the top of the reactor and flows down as pyrolysis, combustion, and tar cracking reactions occur to create producer gas. Ash is periodically removed at the bottom of the gasifier using an auger. The producer gas then preheats the incoming atmospheric air while being routed through the filtration processes.
2.2. Instrumentation The primary instrument used for measuring CO, H2, CO2, and CH4 was a Laser Gas Analyzer (LGA) (ARI, Eden Prairie, MN). The LGA uses Raman spectroscopy to differentiate between species (Raman 222
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spectroscopy, http://www.atmrcv.com/technology.html). The gas sample was sent through a cooler to drop out excess moisture to protect the instrument; a water correction analysis was implemented during analysis, the details of which are described in supplementary material. The LGA does not distinguish between different hydrocarbon species, but CH4 has been shown to be the dominant hydrocarbon present in producer gas (Akagi et al., 2011; Sinha et al., 2004; Bhattacharya et al., 2002). Thus, any hydrocarbons detected were assumed to be methane. Soot was measured using a Microsoot Sensor (MSS) analyzer (AVL, Gratz, Aus.). The MSS measures total soot mass concentration without differentiating by particle size (AVL, 2009). Prior to measurement, the sample was diluted with atmospheric air to reduce the dew point and condensation inside the instrument. NOx was measured using a 600 series CLD NOx analyzer (California Analytical Instruments, Orange, CA), which can differentiate between NO and NO2. A short, heated line held at 90 °C was used between the exhaust and instrument to minimize reactions prior to measurement. Temperature was measured using K-type thermocouples. The temperature measurement locations were at the top of the reactor and immediately after the filter. Pressure was monitored through the system's onboard Arduino controller, and was measured at the top of the reactor and on the producer gas leaving the reactor. Differential pressure was measured with an Omega PX653-10D5V transducer across an orifice plate through which the producer gas flowed after being filtered. Incoming reactor air and engine air flowrates were measured using two automotive B3H7 mass airflow (MAF) sensors (Green Motion, Irvine, CA). The flowrate of the producer gas post-filter was measured using the orifice plate and relevant LGA, temperature, and pressure readings to correct for density.
Fig. 2. CO, H2, CO2, and CH4 concentrations for one full sweep of LGA measurements as a function of time and electrical output power.
producer gas and gas with lower concentrations is referred to as low quality producer gas. Low quality producer gas, like that produced in the fourth load shown in Fig. 2, was observed to occur at high power output, when the reactor had difficulty keeping up with the engine's demanded flowrate. It also occurred with high feedstock moisture content because the reactor struggled to maintain high enough temperatures to sustain efficient gasification. Producer gas quality also had significant impact on the engine performance. High quality producer gas was more energy dense, thus resulting in higher combustion temperature and more complete burning than low quality gas, as discussed below.
2.3. Experimental methods Steady state data were collected at four different loads controlled by four 208 V, 16 A resistive heaters. Measurements were taken at 3.4, 6.8, 10.2, and 13.6 kW. Producer gas was sampled after the packed bed filter (location A in Fig. 1), while exhaust was sampled from the engine exhaust line prior to emission into the atmosphere (location B in Fig. 1). To achieve steady state readings, the gasifier was allowed 10 min to stabilize at each new load followed by 10 min sampling the producer gas and 10 min sampling the exhaust. Testing was completed over a period of three days; on each day data was collected for all four loads. This resulted in three sets of data for each load, or 12 sets total. Thermal efficiency of the system was calculated as the ratio of electrical power divided by the lower heating value (LHV) of the feedstock times the calculated feedstock mass consumption rate. The LHV value of woody biomass was taken as 16 MJ/kg on a dry basis (Telmo and Lousada, 2011). For all examined parameters, experimental uncertainty was estimated by propagating one standard deviation for each measurement through all necessary calculations using the method of sequential perturbation (Figliola and Beasley, 2000). Instrument error and bias were not considered in uncertainty calculations. While individual standard deviations for each measurement were small (< 5%), the final uncertainty on the emission factors became large (up to 20%) due to error propagation through the multistep moisture content calculations.
3.2. Emissions factors of criteria pollutants The gases CO2, CO, CH4, NOx, and soot were the primary emissions measured in the experiments. For all the figures given in this section, emissions are reported in two ways: as mass emissions factor in mass of pollutant per mass of biomass consumed on a dry basis, and as energy specific emissions factor in mass of pollutant per kW-hr of electricity produced. The primary greenhouse gas emission from the system was carbon dioxide because it is a product of complete combustion. As shown in Fig. 3, CO2 mass emissions per dry biomass input do not show a clear trend with electrical load and only vary by about 15%. This observation may be expected since the biomass has a fixed carbon content regardless of load and can only leave the system one of three ways: solid ash, liquid tar, or exhaust gas. The data indicate that the gasifier system had nearly constant ash and tar production as a function of electrical power output within measurement uncertainty. However, some trends were apparent. At low loads, the slightly lower CO2 emissions factor can be attributed to lower reactor temperatures causing a higher fraction of the feedstock to be converted to biochar rather than CO2. The decrease in CO2 emissions seen at the maximum load can be attributed to lower producer gas quality. The highest load required a higher producer gas flowrate into the engine to maintain speed, so the residence time of reactants in the gasifier decreased. Quality decreased due to shorter residence time, resulting in more incomplete combustion products, where some carbon was emitted as CO and CH4 instead of as CO2. The energy specific emissions of CO2 showed a clear downward trend as a function of electrical power output. This is due to the strong correlation between thermal efficiency and load, as shown in Fig. 4. Low overall thermal efficiency for the system at low electrical output
3. Results and discussion 3.1. Producer gas Fig. 2 shows time-resolved gas concentrations from a selected fourstep load sweep. Periods of elevated CO, H2, and CH4 concentrations indicate a producer gas measurement period, and high CO2 segments indicate an engine exhaust measurement period. For the remainder of the results discussed, producer gas with concentrations of CO and H2 both above 15% is referred to as high quality 223
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dominating factor, the biochar production and combustion efficiency effects discussed previously were still present. Carbon monoxide emissions factors exhibit very different trends than CO2, as given in Fig. 3 where it is clear that lower combustion efficiency led to higher CO emissions. As expected, the CO mass emissions factor was low when the producer gas quality was high and increased as gas quality became poorer at high electrical load. Conversely, the energy specific CO emissions initially reduced due to increasing thermal efficiency. At the higher loads, increasing CO from reducing producer gas quality overwhelmed the reduction effect caused by increasing thermal efficiencies, resulting in increased CO emissions for the highest two load settings. CH4 and CO emissions showed similar trends, as shown in Fig. 3, because both are products of incomplete combustion. NOx formation in combustion is a strong function of temperature based on the well-known Zel'dovich thermal mechanism. NOx emissions for the system are given in Fig. 3. At low loads, combustion temperatures inside the engine were lowest so NOx emissions were also minimized. As the load increased, in-cylinder temperatures increased and NOx concentrations correspondingly rose. Nearing peak electrical load, NOx emissions plateaued due to poorer producer gas quality. A tradeoff between increasing thermal efficiency with electrical output and increasing NOx per kg of feedstock led to near constant energy specific NOx emissions. Fig. 5 shows soot emissions from two different runs plotted together on the same axis for comparison. Total soot emissions were found to be highly dependent on the quality of the producer gas and were not a strong function of electrical power output. Average soot concentrations with high quality producer gas were typically below 0.02 mg/m3 regardless of load. This translates to 0.7 mg soot per kg of dry biomass, which is low even compared to large-scale biomass power plants as will be discussed in section 3.4. Soot emissions increased by orders of magnitude when the gasifier produced low quality producer gas. Fig. 5 highlights an extreme case of low quality producer gas when using very wet feedstock, where soot emissions exceeded 1.7 mg/m3 for short periods. These spikes occurred at the times of low engine output. During these periods, H2 and CO concentrations in the producer gas were not sufficient to retain high enough flammability for spark-ignition combustion, causing misfire and incomplete burning. While the spikes exhibited by the low-quality producer gas were nearly 100 times higher than the standard operating soot concentration, the peak soot levels were still within reasonable
Fig. 3. Mean mass and energy specific emissions factors of CO2, CO, CH4, and NOx as a function of electrical load for the gasifier generator system.
Fig. 4. Mean thermal efficiency of the gasifier generator system as a function of electrical load.
load was mainly a function of constant heat losses from the gasifier system and lower engine efficiency, and was consistent with our previous work with a similar gasifier-generator system (Hamilton et al., 2014). Less biomass required to produce an equal amount of electricity led to lower CO2 emissions. While the measured producer gas flowrates agreed with the CO2 emissions on a per kWh basis and were clearly the
Fig. 5. Soot emissions versus time for the gasifier-generator system when operated over selected periods with high and low quality producer gas. 224
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incomplete combustion. This incomplete combustion lowered engine combustion temperatures which in turn reduced NO production. The data reported here also agrees with previous studies that have concluded downdraft gasifiers are particularly susceptible to feedstock conditions when compared to other gasifier designs (Bridgwater, 1995). During the set of experiments conducted in this study, NOx mole fraction temporarily passed 1100 ppm (7.25 g/kg dry) when an unusually dry patch of feedstock was in the reactor. Although very dry feedstock is preferable for high power output and system stability, potentially high output NOx emissions illustrate the need for exhaust aftertreatment or three-way catalysts. 3.4. Emissions comparison to other waste wood utilization methods Here we present a comparison of emissions factors from small-scale gasification power generation to alternative biomass utilization methods. These methods include decomposition, open burning, use in a residential stove, and use in a large-scale plant. Open burning and residential emission factors were selected from literature, and estimates from the GREET 2016 (v1.3.0.13107) model were used to determine emissions factors for large-scale power generation. The emissions reported for gasification are given as a range from low to high electrical output power with high producer gas quality. Open-air decomposition is highly dependent on the surrounding environment. It was assumed that 5% of the feedstock's carbon content were in a wet and/or poorly aerated environment such as piles created during forestry management practices (Wihersaari, 2005). Drier and more exposed biomass would tend to produce higher CO2 and lower CH4 levels during decomposition. The total greenhouse impact, indicated as ‘Total CO2e’ in Table 1, was calculated using the 100-year GWP values recommended by the IPCC as shown in Equation (1) (Climate Change, 2007, 2007).
Fig. 6. Mean moisture content effects on emissions as a function of electrical output load.
operating bounds compared to other biomass burning methods, at approximately 0.26 g/kg dry feedstock. This study focused on species emitted into the atmosphere, and thus biochar and liquid tar production are not reported. However, a rough estimate based on the total amount of biochar produced throughout the length of the experiment indicates that about 2% of the initial feedstock was eventually converted into biochar and removed through the system's cyclone or ash container. Additional study is required to measure biochar production more quantitatively.
CO2 e = CO2 + 44/28 ∗ CO + 25CH4 + 298N2 O#
(1)
While CO is not a direct greenhouse gas, it has been shown to be further oxidized to CO2 in the atmosphere (Lashof and Ahuja, 1990). Under the right conditions, CO can also contribute to a rise in atmospheric methane due to a reduction in the amount of OH present in the atmosphere, raising CO's effective GWP value. CO's relationship with atmospheric methane is dependent on environmental factors and is not well documented (Lashof and Ahuja, 1990). For simplicity, CO was assumed to oxidize into CO2 in the atmosphere, leading to a GWP of 44/ 28 (ratio of molecular weights). Large-scale plants have higher thermal efficiency compared to smaller plants due to lower heat losses per unit energy consumption which leads to the highest CO2 emissions, while open burning and residential usage have lower combustion efficiencies either by design (restricted airflow in the case of residential furnaces) or environment (local oxygen deficiencies during an open burn) that lead to leftover charcoal and increased carbon emitted as CO, soot and CH4. As previously stated, NOx formation is a function of combustion temperature, which tends to rise with combustion efficiency; however, large-scale plants typically include NOx aftertreatment on their exhaust, thus
3.3. Emissions dependence on biomass moisture content Feedstock moisture content was one of the most significant factors in determining producer gas quality, and thus electrical output. While moisture content was between 20% and 30% for each load on each day, the effects are still apparent in the emissions data. Fig. 6 shows CO and NOx emissions factors for each of the three days along with corresponding feedstock moisture content. Fig. 6 shows that while CO emissions factors from the gasifier generator system increased with increasing moisture content, NOx emissions had the opposite trend. Excess CO is an indicator of
Table 1 Mass emission factor comparisons for various paths of biomass usage on a dry mass basis compared to small-scale gasification power generation (Well-to-Wheels Analysis, 2011; Akagi et al., 2011; Wihersaari, 2005; Sinha et al., 2004; Bhattacharya et al., 2002; Christian et al., 2003; Aurell et al., 2015; Liu et al., 2014; Yokelson et al., 2011; Ozgen et al., 2014). Pathway
CO2 (kg/kg)
NOx (g/kg)
CO (g/kg)
CH4 (g/kg)
Soot (g/kg)
N2O (g/kg)
CO2e (g/kg)
Open Burning Residential Decomposition IGCC Turbine Steam Turbine Gasifier (this work)
1.62 1.56–1.62 1.74 1.84 1.83 1.34–1.60
2.9 0.05–2.7 – 0.17 1.13 1.6–3.6
97.2 19–154 – 0.16 5.82 9.6–21.6
4.6 6–10 33.3 0.07 0.60 8.6–13.3
15.5 1.2–10 – 0.05 2.57 0–0.26
– – 0.04 – – –
1888 1740–2112 2584 1841 1854 1570–1966
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Table 2 Emission factors from three biomass power generation technologies including small-scale gasification from this work on a kWh basis (Well-to-Wheels Analysis, 2011). Power Generation Method
CO2 (kg/kWh)
NOx (g/kWh)
CO (g/kWh)
CH4 (g/kWh)
Soot (g/kWh)
IGCC Turbine (η = 40%) Steam Turbine (η = 22%) Gasifier (this work) (η = 5–12%)
0.83 1.49 2.1–4.6
0.08 0.92 4.8–5.5
0.07 4.73 22.8–32.6
0.03 0.49 17.5–29.6
0.02 2.09 0–0.78
Table 3 Processing and transportation emissions factors used in the analysis (Well-to-Wheels Analysis, 2011). Process
CO2 (g/kg)
CO (mg/kg)
CH4 (mg/kg)
NOx (mg/kg)
PM (mg/kg)
Collection + On-Site Chipping Transportation (per 100 mi.)
13.4 40.2
47 36.2
25.8 44
96.4 97
7.4 1.6
On an energy specific basis, small-scale gasification has much higher emissions compared to large-scale power production methods due to its lower thermal efficiency as given in Table 2. For reference, coal-fired steam turbines operating at similar efficiencies to biomasspowered turbines can be expected to produce higher carbon emissions per kWh because coal has much higher carbon content than biomass. Data presented in Tables 1 and 2 consider only on-site emissions from different biomass consumption processes. To get a more detailed understanding of the entire associated lifecycle, additional processing and transportation emissions need to be considered to compare smallscale gasification versus large-scale power generation systems. Table 3 shows the emissions factors used in the analysis taken from the GREET analysis software. The emissions due to collection and chipping are required for both large-scale and small-scale usage, but the transportation distance is a key differentiator. Large-scale plants continually require biomass from a large geographic area to maintain operation, while small-scale gasification requires less transportation as a smaller land area is required. Fig. 7 presents CO2 emission factors for various pathways as a function of transportation distance. Since open burning does not require biomass transport, its emission factor remains constant. Fig. 7 shows that gasification emits less CO2 than open burning so long as the transport radius is smaller than 16 mi. Therefore, this work makes the distinction that small-scale gasifiers should source biomass from less than 16 mi. away. Large-scale turbine plants emit more CO2 than other paths regardless of transport radius. Table 4 shows modified emission factors, assuming large-scale plants require an average of 100 mi. of transportation and small-scale gasification requires only 10 mi. Comparing the values in Table 4 to those from Table 1, CO2 is most noticeably impacted by taking transportation into account, although its impact is less than 3% for a 100-mi. collection radius. Due to the relatively small effect of transportation on emissions, it is more likely that economic costs associated with the supply chain, rather than environmental impact, would restrict biomass collection from larger radii to feed large-scale plants. The analysis shows that overall, biochar production is the main reason for lower CO2 emissions from small-scale gasification on a mass of feedstock basis.
Fig. 7. CO2 emissions factor for four biomass pathways as a function of biomass transport distance. A vertical marker at 16 mi shows where gasification begins emitting more CO2 than open burning.
resulting in a lower emissions factor. Small-scale gasification power generation has the lowest estimated CO2 emissions, largely due to the carbon removed from the system in the form of biochar; it does not necessarily indicate poor combustion efficiency. As seen in Table 1, the CO and soot emissions from the gasifier system, and consequently combustion efficiency, fall between those of open burning/residential use and the large-scale plants. Smallscale gasification has higher CH4 than other power generation methods mainly due to incomplete combustion of the high methane-containing producer gas. The largest emitter of total estimated CO2e is decomposition, with CH4 comprising roughly half of its greenhouse gas emissions. The residential use, open burning, and large-scale generation are all comparable in CO2e because large-scale systems use all the available carbon in the feedstock, while the other systems have charcoal as a byproduct but are offset by the increased CH4 emission. The gasification system's total CO2e is dependent on the output load but was found to be the lowest at low loads due to high combustion efficiency and high rates of biochar production.
Table 4 Modified biomass emission factors including feedstock preparation. Pathway
CO2 (kg/kg)
NOx (g/kg)
CO (g/kg)
CH4 (g/kg)
Soot/PM (g/kg)
Total CO2e (g/kg)
IGCC Turbine (100 mi.) Steam Turbine (100 mi.) Gasifier (10 mi.)
1.90 1.89 1.36–1.62
0.37 1.33 1.7–3.7
0.24 5.90 9.7–21.7
0.07 0.60 8.6–13.3
0.054 2.58 0.01–0.27
1902 1914 1590–1987
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4. Conclusions
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This work characterized the emissions of a small-scale gasifiergenerator and compared the potential impact of gasifying distributed waste biomass for power generation to the impact of other pathways for waste residue. Ultimately, although small-scale gasification has the potential for the lowest overall greenhouse gas emissions potential of energy production processes considered here and has a considerable emissions benefit over open burning, these benefits may not be significant enough to outweigh economic factors associated with capital cost, operational expenses, and feedstock supply chain requirements. A complete techno-economic analysis should be conducted to fully explore the relative advantages of small-scale gasification systems over large-scale energy production from distributed waste biomass. Declarations of interest None. Acknowledgments This work was supported by the State of Minnesota Legislative Citizen Commission on Minnesota Resources under appropriation M.L. 2015, Chp. 76, Sec. 2, Subd. 07b. The authors thank Darrick Zarling and other colleagues at the University of Minnesota's T.E. Murphy Engine Research Laboratory for their technical guidance and support. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.atmosenv.2018.12.024. References Akagi, S.K., Yokelson, R.J., Wiedinmyer, C., Alvarado, M.J., Reid, J.S., Karl, T., Crounse, J.D., Wennberg, P.O., 2011. Emission factors for open and domestic biomass burning for use in atmospheric models. Atmos. Chem. Phys. 11, 4039–4072. AP-42 Section 1.6, 2003. Wood Residue Combustion in Boilers. U.S. Environmental Protection Agency, Washington, DC. Aurell, J., Gullett, B.K., Tabor, D., 2015. Emissions from southeastern U.S. grasslands and pine savannas: comparison of aerial and ground field measurements with laboratory burns. Atmos. Environ. 111, 170–178. AVL, 2009. AVL Micro Soot Sensor Operating Manual/Product Guide. Bhattacharya, S.C., Albina, D.O., Salam, P.A., 2002. Emission factors of wood and charcoal-fired cookstoves. Biomass Bioenergy 23, 453–469. Bridgwater, A.V., 1995. The technical and economic feasibility of biomass gasification for power generation. Fuel 74 (5), 631–653. Campbell, J.E., Block, E., 2010. Land-use and alternative bioenergy pathways for waste biomass. Environ. Sci. Technol. 44 (22), 8665–8669. Christian, T.J., Kleiss, B., Yokelson, R.J., Holzinger, R., Crutzen, P.J., Hao, W.M., Saharjo,
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