Investigation of selective catalytic reduction for control of nitrogen oxides in full-scale dairy energy production

Investigation of selective catalytic reduction for control of nitrogen oxides in full-scale dairy energy production

Applied Energy 106 (2013) 328–336 Contents lists available at SciVerse ScienceDirect Applied Energy journal homepage: www.elsevier.com/locate/apener...

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Applied Energy 106 (2013) 328–336

Contents lists available at SciVerse ScienceDirect

Applied Energy journal homepage: www.elsevier.com/locate/apenergy

Investigation of selective catalytic reduction for control of nitrogen oxides in full-scale dairy energy production Mary Kay Camarillo a,⇑, William T. Stringfellow b,c, Jeremy S. Hanlon b, Kyle A. Watson d a

Civil Engineering Department, School of Engineering & Computer Science, University of the Pacific, 3601 Pacific Avenue, Stockton, CA 95211, USA Ecological Engineering Research Program, School of Engineering & Computer Science, University of the Pacific, 3601 Pacific Avenue, Stockton, CA 95211, USA c Earth Sciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA d Mechanical Engineering Department, School of Engineering & Computer Science, University of the Pacific, 3601 Pacific Avenue, Stockton, CA 95211, USA b

h i g h l i g h t s

g r a p h i c a l a b s t r a c t

" Selective catalytic reduction reduced

" "

"

"

NOx emissions from a dairy biogasfueled engine. NOx production during combustion of dairy biogas was variable. Performance was improved by realtime data collection and automated process control. Air–fuel ratio impacted NOx removal; other engine conditions were less influential. Catalysts demonstrated stable performance.

a r t i c l e

i n f o

Article history: Received 16 August 2012 Received in revised form 22 January 2013 Accepted 23 January 2013 Available online 28 February 2013 Keywords: Selective catalytic reduction (SCR) Nitrogen oxides (NOx) Dairy manure Anaerobic digestion Combined heat power

a b s t r a c t Selective catalytic reduction (SCR) was used to reduce exhaust gas nitrogen oxides (NOx) from the emissions of a 710 kW combined heat and power system fueled by dairy biogas. Exhaust gas NOx was reduced from 63.1 ± 31.9 to 14.2 ± 17.5 ppmvd @ 15% O2 such that emissions were 0.33 ± 0.40 g kW1 h1, based on data averaged over 15 min intervals. Online exhaust gas sensors with integrated process control algorithms were effective in improving NOx removal by automated control of urea, the ammonia source used for catalysis of NOx reduction reactions. Pre-SCR NOx was most strongly correlated with equivalence ratio (R2 = 0.39), indicative of the air–fuel ratio. A concave relationship between NOx production and thermal conversion efficiency was not observed since lean-burn operation of the engine was consistent and only altered under low engine load. Following installation of pre- and post-SCR NOx sensors, average daily exhaust gas NOx reduction in the SCR was 82.6 ± 8.5%. Post-SCR NOx emissions were typically impacted by pre-SCR NOx (R2 = 0.36), suggesting that altered operation of the anaerobic digesters or modifications to the engine would be effective in reducing NOx emissions as well as urea demand. After nearly three years of operation, the SCR catalyst remains in service without requiring replacement. Average daily urea demand was 31.8 ± 16.3 L d1 for the system that produced 369 ± 136 kW of electricity. During the second year of observation the regulatory limit of 0.804 g kW1 h1 was met 94% of the time while the regulatory target of 0.201 g kW1 h1 was only met 45% of the time, based on data averaged over 15 min intervals. These results provide guidance for dairy energy projects in locations with stringent NOx emissions standards. Ó 2013 Elsevier Ltd. All rights reserved.

⇑ Corresponding author. Tel.: +1 209 946 3056; fax: +1 209 946 3086. E-mail address: [email protected]fic.edu (M.K. Camarillo). 0306-2619/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.apenergy.2013.01.066

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1. Introduction Biogas produced at dairy farms through anaerobic digestion of manure and co-digestates, including agricultural wastes and bioenergy crops, is used beneficially in power plants to produce mechanical energy, transferable heat, and electricity [1]. Use of dairy energy results in reduced greenhouse gas emissions, waste stabilization, reduced odors, and utilization of renewable energy, and as a result of these benefits there is increased interest in dairy energy and the number of projects has increased globally [2]. Biogas-derived energy production is also implemented at other types of livestock facilities, landfills, and domestic wastewater treatment facilities where similar benefits are realized [3]. Despite the multiple benefits of biogas energy, environmental concerns persist that have not been adequately addressed by the scientific community. These concerns have caused delays in implementation of biogas projects and in the establishment of clear regulatory policies. In California, USA serious environmental concerns have arisen regarding air emissions from biogas power plants [4]. This study examines the magnitude of NOx emissions from a full-scale dairy-based biogas energy plant and investigates the efficiency of state-mandated air pollution control technology. Dairy energy projects often use combined heat and power (CHP) systems consisting of internal combustion engines and electricity generators that are powered using methane-rich biogas that is generated in anaerobic digesters [5,6]. Constituents in the biogas and in the air injected into the engine are transformed during combustion to form air pollutants. For example, ammonia (NH3) and nitrogen gas (N2) are oxidized to nitrogen oxides (NOx), which have health impacts, lead to formation of ground-level ozone and particulate matter, and cause acid rain [7,8]. The undesirable characteristics of NOx necessitate mitigation in large power plants and automobiles [9]. Reduction of NOx in emissions from dairy energy projects has not been aggressively pursued although it is an issue in regions with stringent air quality regulations [4,10]. In the Central Valley of California, the Regional Air Resources Board is requiring NOx controls for dairy-based anaerobic digester projects. Various strategies exist for NOx reduction in engine emissions; the appropriate use of technology is dependent on the gas source and the regulatory limits established by the governing environmental agency [11]. Combustion process modifications include staged combustion, ignition modifications, flue gas recirculation, combustion zone modifications to improve residence time and mixing, fuel modifications, blending of multiple fuel types, and adjustment of the air–fuel ratio [9,11]. Anaerobic digesters can be operated to reduce biogas NH3 [12]. Although biogas NH3 content in biogas is typically low, concentration as high as 332 ppm have been observed [12]. In addition to NH3, N2 and N2O are present in the biogas and in the air introduced during combustion, contributing to NOx emissions. In addition to preventing NOx formation in combustion, exhaust gas can be treated using technologies such as non-selective catalytic reduction, selective catalytic reduction, and selective non-catalytic reduction [11]. Additional treatment methods include use of activated carbon, photocatalytic reactions, algae scrubbers, and plasma technologies [13–16]. In California the regulatory approach to reducing air emissions statewide has been to establish Best Available Control Technologies (BACTs) for the removal of various air pollutants and to enforce the use of such technologies where appropriate [17]. Reduction of air pollutants has been aggressively pursued in California where air quality is poor; for example, in 2012 six of the ten worst locations for short-term air particle pollution in the USA were located in California [18]. Regional approaches to improving air quality in California are under investigation and additional emissions regulations are anticipated [19]. Globally,

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air pollution is a significant issue and other locations may adopt similar strategies for addressing air pollutants in biogas-derived emissions. Selective catalytic reduction (SCR) is used extensively for exhaust gas NOx reduction [20,21], and it is considered a BACT [17]. A reducing agent is necessary, and an ammonia source is frequently used [21]. In an SCR process, NOx is reduced to N2 and H2O following NH3 addition in the presence of a catalyst. Ammonia can be added as a gas or as urea [(NH2)2CO]. SCR system functionality is contingent on an appropriate operating temperature [21]. Exhaust temperature should be at least 300 °C to prevent precipitation of ammonium sulfates, NH4HSO4 and (NH4)2SO4 [22]. Ammonium nitrate (NH4NO3) may also form at low temperatures [20]. Although removal mechanisms are still being actively investigated [23,24], the overall SCR reactions consist of [20]:

4NH3 þ 4NO þ O2 ! 4N2 þ 6H2 O

ð1Þ

2NH3 þ NO þ NO2 ! 2N2 þ 3H2 O

ð2Þ

8NH3 þ 6NO2 ! 7N2 þ 12H2 O

ð3Þ

The SCR system is considered selective because NH3 reacts with NOx instead of being oxidized to N2, N2O, and NO [20]. An issue with the SCR system is that excess added NH3 will contribute to emissions, referred to as ‘‘ammonia slip’’ [21]. One way to prevent ammonia slip is to place an additional catalyst downstream of the SCR to oxidize any remaining NH3 [25]. Performance of the SCR, including removal rates, urea dosage, optimal configuration, optimal catalyst material, and catalyst lifespan, are operational parameters that must be established for each application. A challenging aspect of using biogas as a fuel source is that the methane content of the biogas is variable [26], necessitating constant modification of the air–fuel ratio. The quantity of biogas produced in the anaerobic digesters is also variable, and is a function of digester loading rate, feedstock characteristics, digester temperature, hydraulic retention time, microbial population dynamics, and other factors [2,27]. The transient biogas quantity will impact the amount of air injected during combustion. Emissions and control of NOx and other pollutants from biogas engines have been studied on simulated biogas, but not full-scale systems [10,28–31]. To our knowledge, there have been no prior scientific studies examining SCR technology to control NOx in dairy energy plants. Scientific analysis of NOx removal using technologies such as SCR is needed to establish BACT and regulatory limits for dairy energy production. In this project a full-scale dairy biogas energy project using an SCR for NOx removal was studied for over one year. The objectives were to: (1) determine the level of NOx emissions from a dairy biogas energy plant, (2) determine if SCR technology can be used to reduce exhaust gas NOx from an engine fueled by dairy biogas, (3) identify parameters impacting NOx production and removal, and (4) determine engineering parameters for an SCR system operating in a dairy biogas setting. 2. Material and methods 2.1. Site description The site was previously described [27]. Briefly, two upright, above-ground, complete-mix anaerobic digesters with a combined operating capacity of 6400 m3 were located at a dairy farm in central California. A Guascor SFGLD-560 CHP with an internal combustion reciprocating engine and electric generator was used for power production (Fig. 1). The rated capacity of the generator when fired with biogas was 710 kW. The engine operated at

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Fig. 1. Schematic of dairy digester CHP and SCR systems.

1500 rpm, had 16 cylinders, a 175 mm stroke, and a 160 mm bore diameter. The engine was modified to operate on biogas with a lean-burn setting. The biogas methane content was manually entered into the engine computer system and the air–fuel ratio was automatically adjusted using a process control algorithm with engine data inputs. A lane flush manure collection system was used where washwater was screened in slope screens and settled prior to re-use for lane flushing. The digester temperature was approximately 38 °C and the design hydraulic retention time was 24–30 d. During the study, digester feedstocks consisted of thickened lane flush wastewater, manure solids from the slope screens, whey wastewater, waste animal feed, and sudan grass. A biological hydrogen sulfide removal system was located in the headspace of the anaerobic digesters: netting was suspended to support a biological community of sulfur oxidizing bacteria and a small amount of ambient air was injected to support biological sulfur oxidation. An SCR was located downstream of the engine. Urea was added to the SCR in a stream of compressed air. The SCR catalyst was a honeycomb design (approximately 30 cells cm2) containing oxides of vanadium, titanium, and tungsten. The urea feed was controlled by a process control algorithm with inputs of pre-SCR NOx (following installation of the sensor) and engine load (kW).

2.2. Data collection Biogas flow was measured continuously using an Endress + Hauser Prowirl vortex flow meter. A biogas dryer was located upstream of the flow meter and sample location, so that measurements were made on dry gas. Biogas temperature and pressure were measured in real-time during the last five months of the study period. Accordingly, biogas temperature was calculated for the previous time period using a linear regression based on published records for ambient air temperature [32]. The average measured biogas pressure was used in calculations where measured values were not available. Exhaust gas NOx and O2 upstream and downstream of the SCR was measured continuously on moist gas using online Siemens

VDO UniNOx sensors. Engine exhaust temperature was measured upstream and downstream of the SCR using type K thermocouples connected to a Panasonic FP0-TC4 analog-to-digital transducer. Exhaust backpressure was measured using an Omega Engineering PX4200-005GI pressure sensor connected to a Panasonic FP0A80-A analog-to-digital transducer. Measurements were recorded by a Panasonic AFPX-C14P PLC, and transferred to a Red Lion G306 human–machine interface at a frequency of once per minute. Measurements of biogas and exhaust gas were made monthly using handheld meters. Biogas was measured for CH4, CO2, O2, and H2S using a GasData GFM 416 Biogas Analyzer. Exhaust gas upstream and downstream of the SCR was measured for CO, CxHy, H2S, NOx, O2, and temperature using a Testo 350XL Emissions Analyzer.

2.3. Data analysis System data were analyzed from January 23, 2010 to December 31, 2011 although real-time measurement of pre-SCR NOx did not start until June 2, 2010. Online data was averaged over 15 min intervals for reporting although average daily values were used for plots, except as indicated otherwise. NOx data were analyzed when exhaust gas temperature was at least 400 °C and NOx readings were within the reportable range (0–1500 ppm). Gas volumes were adjusted to represent volumes at 0 °C and 100 kPa, standard conditions per the International Union of Pure and Applied Chemistry (IUPAC). Data from NOx sensors were modified to represent values in dry gas at 15% O2 (Eq. (4)) using inputs of O2 in dry gas and moisture content (MC), assuming 1% water vapor in the air added during combustion [33].

 NOx ; ppmvd @ 15% O2 ¼ NOx ; ppm



20:9  15:0 20:9  O2;d %

100 100  MC;%



ð4Þ Since exhaust gas O2 was measured on wet gas, sensor O2 data were converted to dry values prior to use in Eq. (4). Exhaust gas MC and flow rate (used for mass-based emissions) were calculated by

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balancing oxygen and water masses before and after combustion, assuming complete combustion. Mass-based emissions were calculated using nitrogen dioxide (NO2) to represent NOx. The equivalence ratio (u) was determined by dividing the actual fuel–air ratio by the fuel–air ratio that would result in complete combustion with no excess O2. Thermal conversion efficiency (TCE) was calculated as a ratio of the power produced by the methane volume combusted to the lower heating value of methane of 35.3 MJ Nm3 [34,35]. Statistical analyses were performed using JMP software. Significance of correlations was determined using ANOVA with p-values reported (e.g. p < 0.05). The non-parametric Wilcoxon signed rank test was also used to compare non-normal data sets, with results similar to those obtained using ANOVA. For p < 0.05, the null hypothesis that the groups were from populations with the same mean was rejected and the data sets were considered significantly different. Rejection of the null hypothesis (p < 0.05) was further verified using the Tukey Honestly Significant Difference (HSD) test. Results are reported throughout as mean ± standard deviation.

Table 2 Dairy biogas composition. Constituent

Measureda

Typicalb

CH4 (%) CO2 (%) H2O (%) O2 (%) N2 (%) NH3 (%) H2S

50.7 ± 3.9 45.3 ± 3.3 nac 0.93 ± 1.52 na na 297 ± 267 ppm

50–75 25–45 2–7 <2 <2 <1 <1%

a Data from online meters averaged over 15-min increments except CO2, which was measured during site visits (n = 21). Measurements made on dry biogas. All units are on a v v1 basis. Mean ± standard deviation reported. b Source: BMELV [33]. c na = not measured.

3. Results 3.1. NOx emissions and reduction using SCR Exhaust gas NOx was significantly reduced (ANOVA p < 0.05) in the SCR as evident from online data averaged over 15-min intervals (Table 1). A slight increase in O2 was expected due to the use of compressed air to inject urea, but the increase in O2 was not significant (p > 0.05). A limited number of hydrocarbon (CxHy) and carbon monoxide (CO) measurements were made during site visits, as the handheld exhaust gas meter was used to verify online sensor data. The SCR significantly reduced CO emissions (p < 0.05). Although CxHy increased in the SCR, the increase was not significant (p > 0.05). While the engine was running 399 ± 107 kW of power was generated as the result of 6130 ± 1460 m3 d1 of biogas production (0 °C, 100 kPa). The power plant was fully operational 86% of the time, resulting in average daily power production of 369 ± 136 kW. The TCE for electricity was 30.6 ± 3.1%, which is within the range of 28–40% expected for a gas-driven CHP where efficiency is a function of engine capacity, lean/rich burn setting, and other factors [36]. Biogas constituent concentrations were within the ranges expected [37], although CH4 was at the low end of the expected range and CO2 was at the high end (Table 2). Similar results were reported in a study of 37 full-scale facilities in Austria where median TCE was 31.8% and median CH4 content was 53.01%, although few details of the facilities were provided [38]. The u Table 1 Exhaust gas data.

a

Constituent

Pre-SCR

Post-SCR

NOx (ppmvd @ 15% O2)a O2 (%, v v1)a CxHy (ppm)b CO (ppm @ 15% O2)b Temperature (°C)a,c

63.1 ± 31.9 4.3 ± 0.6 659 ± 366 152.0 ± 5.6 440.9 ± 7.4

Pressure (kPa)a

4.79 ± 2.36

14.2 ± 17.5 4.4 ± 0.6 952 ± 292 17.1 ± 3.6 433.7 ± 8.3 434.9 ± 8.1 nad

Data from online measurements averaged over 15-min increments when engine was operating, exhaust temperature >400 °C, and NOx in reportable range (0–1500 ppm). Measurements made on wet gas. NOx measurements corrected to 15% O2 and dry gas conditions. All units are on a v v1 basis. Mean ± standard deviation reported. b Data measurements during site visits (CxHy, n = 4; CO, n = 5). c Two temperature measurements made after SCR. d na = not measured.

Fig. 2. NOx reduction using SCR as shown by (a) 15-min averages and (b) daily averages by month (starting with February 2010).

was 0.75 ± 0.03, indicating a lean-burn setting. Mass-based NOx emissions were 0.33 ± 0.40 g kW1 h1. Over time post-SCR NOx decreased (Fig. 2a). In June 2011 (month 5 in Fig. 2b) the pre-SCR sensor was installed, which

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Fig. 3. Influence of pre-SCR NOx on post-SCR NOx.

provided for a more robust process control algorithm for urea feed. The mass-based NOx emissions decreased from 0.64 ± 0.68 to 0.26 ± 0.27 g kW1 h1 (p < 0.05). Three operations and

maintenance events impacted SCR performance during the study period. These events were caused by a problem with the air compressor (8/21–22/2010), a malfunctioning air valve (3/24–28/ 2011), and running out of urea (6/28–29/2011). Excluding data from the days with maintenance problems, the average daily NOx removal following installation of the pre-SCR NOx sensor was 82.6 ± 8.5%, increasing from 80.8 ± 6.8% in 2010 to 83.6 ± 9.1% in 2011 (p < 0.05). An additional factor influencing operation of the SCR was the presence of ammonia deposits accumulating in the urea injection system, which was solved by altering the injection nozzles (occurring in month 10 in Fig. 2b). Post-SCR NOx demonstrated a weak, but significant relationship with pre-SCR NOx (Fig. 3). When the data from days where there were maintenance problems were removed, the R2 value increased to 0.36. In this project the regulatory limit for NOx emissions was 0.804 g kW1 h1, which was met 94% of the time while the regulatory target of 0.201 g kW1 h1 was met only 45% of the time. Regulatory enforcement is based on three consecutive 30 min tests, and 15 min average data were analyzed here to be slightly more conservative. The SCR performance improved over time such that in 2011 the regulatory limit was met 98% of the time while the regulatory target was met 51% of the time. In comparison, based on pre-SCR measurements, the regulatory limit for mass-based emissions was met only 2.0% of the time and the regulatory target was met 0.6% of the time, thereby indicating the effectiveness of this

Fig. 4. Relationship between power production and (a) temperature, (b) pressure, (c) TCE, and (d) u.

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Although the power plant capacity was 710 kW, production ranged from approximately 200–600 kW during the study. As production increased, exhaust gas temperature decreased while pressure increased (Fig. 4a and b). TCE was related to energy production (Fig. 4c), such that the system was more efficient at converting the thermal energy of the methane to useful work at loads closer to engine capacity. Fig. 4d shows that the engine was typically operated at a constant u although excess air was decreased at engine loads below 300 kW, resulting in increased u. Pre-SCR NOx was most strongly correlated with u, which is related to excess exhaust gas O2 (Fig. 5a). Previous studies have indicated a concave relationship between NOx and u, with the highest NOx emissions occurs at an u of approximately 1.0 [29,31]. The concavity of this relationship was not apparent here since the engine was always operated with a lean-burn setting although NOx production did increase as the amount of air added in combustion was lowered (Fig. 5a). The relationship between pre-SCR NOx and exhaust gas temperature was significant but weak (Fig. 5b). In a previous study the Arrhenius Law was used to model NOx and temperature [39]; a similar relationship was not present here

(R2 = 0.05). The influence of temperature on NOx production is complex, as there are concurrent relationships with temperature and u (Fig. 6a). It appears that increased air is lowering gas temperature, such that it is not possible to isolate temperature effects. A relationship between TCE and u also exists (Fig. 6b), which is likely impacted by concurrent relationships with power production (Fig. 4c and d). Previous researchers have observed concave relationships between u and efficiency and between u and NOx production in controlled bench-scale studies [29,31]. Here, a narrow range of u was applied and higher values were only used when the engine was operating at low load (Fig. 4d), where TCE is also low (Fig. 6b). At high engine load the system operates more efficiently and a higher air–fuel ratio is possible, decreasing preSCR NOx (Fig. 5a). Average daily pre-SCR NOx was typically below 100 ppmvd @ 15% O2, which represents the 94th percentile of the 15-min data set. The subset of data with higher pre-SCR NOx values was observed to determine any potential causative factors. On days with high preSCR NOx most operating parameters were not appreciably different than expected ranges with the exception of digester VS loading (10343 kg d1, higher than average of 6200 ± 2700 kg d1) and biogas CH4 (52.0%, higher than average of 50.7 ± 3.9%). During the study feedstocks and loading rates were consistent such that biogas production and methane content were also consistent. Daily average CH4 values greater than 56% appear to correspond with high

Fig. 5. Relationship between pre-SCR NOx and (a) u and (b) temperature.

Fig. 6. Relationship between u and (a) temperature and (b) TCE.

technique and the necessity of using post-combustion emissions controls. 3.2. Impact of operating parameters on NOx reduction

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Fig. 7. Relationship between pre-SCR NOx and biogas CH4.

NOx production (Fig. 7). When only data where pre-SCR NOx was greater than 100 ppmvd @ 15% O2 was considered, the correlation between pre-SCR NOx and CH4 improved (R2 = 0.31). Excluding the days with maintenance issues, NOx emissions were typically below 1.0 g kW1 h1 (Fig. 8). Post-SCR NOx emissions were largely insensitive to temperature in the range of temperatures observed (Fig. 8a). Post-SCR NOx emissions appear insensitive to exhaust gas O2 (Fig. 8b). However, excess O2 resulted in lower pre-SCR emissions (Fig. 5a), such that there was an inverse relationship between NOx removal and exhaust gas O2 (R2 = 0.10). Emissions of NOx were related to urea feed (Fig. 8c), as a reducing agent is necessary for catalytic reactions. However, the nature of the chemical reactions and the possibility of ammonia slip complicate the relationship between urea feed and NOx emissions. When only the data from 2011 are considered, the R2 value for the relationship between urea feed and NOx is 0.20. SCR performance improved following installation of the pre-SCR NOx sensor and integration of sensor data into the control algorithm. The subset of data where post-SCR NOx emissions were above 1.0 g kW1 h1 was examined to identify causative factors. There were 33 d when average daily NOx emissions were greater than 1.0 g kW1 h1. Of the 33 d with high emissions, 30 occurred in 2010 and 28 occurred prior to installation of the pre-SCR NOx sensor. As demonstrated by the data set, SCR performance improved as a result of the installed sensors (Fig. 2b). Of the 3 d with high emissions that occurred in 2011, on one of these days the engine load was low (202 kW) and the u was low as well (0.57), suggesting sub-optimal operating conditions. No contributing factors for the high NOx concentrations could be identified for the other 2 d. 3.3. SCR operating record The SCR system was installed in summer 2009 and had been in continuous operation as of summer 2012. The SCR represented 4.7% of the total capital cost, and during the first 15 months of operation urea purchases represented 9.7% of the total operations and maintenance budget [27]. Based on power production and engine settings observed in this study, average daily urea feed to the SCR was 31.8 ± 16.3 L d1. The originally installed catalysts are still in service after three years and have not yet required replacement. Linear regression of NOx removal over time (following installation of the pre-SCR sensor) yielded an R2 value of 0.00, suggesting that SCR performance is not deteriorating due to aged catalysts.

Fig. 8. Mass-based NOx emissions, excluding data where there were maintenance problems, and influence from (a) temperature, (b) exhaust gas O2, and (c) urea feed rate.

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4. Discussion The current study fills a gap in knowledge regarding NOx emissions and SCR use for NOx control in dairy energy production. Throughout the study, the SCR reduced NOx content and variability, resulting in lower and more stable NOx emissions (Figs. 2 and 3). The NOx production was most impacted by the air–fuel ratio (Fig. 5) and only slightly influenced by other engine conditions. High NOx production appeared related to high anaerobic digester loading rates and high biogas methane content (Fig. 7). Post-SCR NOx appeared most strongly correlated with pre-SCR conditions (Fig. 3) and urea feed rate (Fig. 8c). A slight decrease in SCR performance was observed at the upper temperature range (Fig. 8a). Development of process control algorithms following installation of both pre- and post-SCR online NOx sensors proved valuable in optimizing urea feed and improving NOx removal. Although installation of real-time sensors increased costs, these devices were critical for accurately metering urea into the catalyst. Overfeed of urea results in high chemical demand and ammonia slip that increases NOx emissions. Real-time data collection and process control feedback loops also accommodated more efficient engine operation (Fig. 4). The current work complements results from bench-scale studies of NOx production where biogas was used as a fuel. In a study of a small-scale engine operating on simulated biogas, NOx production decreased as biogas CO2 content increased [29]. In the current study a similar trend was observed where NOx production increased as biogas CH4 content increased (Fig. 7). In the studies of Huang and Crookes [29] and Porpatham et al. [31], a strong trend was observed for lean-burn conditions where NOx decreased with increasing air–fuel ratio although TCE was compromised as a result. The trade-off between TCE and NOx production was not apparent in the current data set (Figs. 5a and 6b). At higher engine load TCE increased and a lower u value was possible, thereby reducing NOx prior to the SCR. Previous work has indicated temperaturedependence for SCR reactions [23,24], suggesting that temperature control of the exhaust gas into the SCR is warranted. Here, the optimal range of 300–450 °C, as recommended by the manufacturer, was seldom exceeded although it does appear that temperatures above 450 °C were negatively impacting NOx emissions (Fig. 8a). In addition to post-combustion emissions controls, NOx emissions can be reduced by modifying engine settings and configurations. Huang and Crookes [29] and Porpatham et al. [31] found that increasing the compression ratio was an effective method for increasing engine efficiency although it was difficult to prevent a corresponding increase in emissions. Roubaud and Favrat [10] investigated use of a pre-combustion chamber and modification of engine settings to reduce NOx emissions to 73.7 ppmvd @ 15% O2 while maintaining a TCE of 37.7%. Optimization of engine settings appears warranted here to reduce pre-SCR NOx emissions since the current work suggests that post-SCR NOx emissions will also improve. However, engine modifications are not expected to eliminate the necessity of post-combustion emissions controls in locations with strict air standards. The current study has demonstrated long-term durability of the SCR system without replacement of the catalysts. Future investigations could be conducted to compare NOx removal in fresh and aged catalysts and to observe power production system durability. Previous studies have demonstrated that deposition and wear can be problematic in farm-based engines powered by biogas [40]. Future investigation of air pollutants other than NOx in emissions (e.g. CO, CxHy, N2O, NH3) is also warranted. 5. Conclusions  Exhaust gas NOx was significantly and reliably reduced using an SCR emissions control system.

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 Removal of NOx improved following installation of online NOx sensors and implementation of a urea control feedback algorithm.  Pre-SCR NOx was most strongly influenced by oxygen content.  Post-SCR NOx was correlated with pre-SCR NOx, suggesting that engine modifications may result in reduced pre- and post-SCR NOx concentrations.  SCR catalysts have functioned reliably for over three years without replacement.

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