Atmospheric Environment 66 (2013) 8e16
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Concentration and particle size distribution of particulate matter inside tunnel-ventilated high-rise layer operation houses Lingjuan Wang-Li a, *, Zihan Cao a, Qianfeng Li a, Zifei Liu a, David B. Beasley b a b
Department of Biological and Agricultural Engineering, North Carolina State University, Raleigh, NC 27695, USA College of Engineering, Arkansas State University, AR 72467, USA
a r t i c l e i n f o
a b s t r a c t
Article history: Received 1 November 2011 Received in revised form 8 March 2012 Accepted 9 March 2012
Particulate matter (PM) is a criteria pollutant emitted from animal feeding operation (AFO) facilities, especially from poultry operation buildings. Fundamental data regarding AFO PM either do not exist, or are not representative of different animal production systems or housing types. This field study investigated particle size distributions (PSDs) and concentrations of total suspended particulate (TSP) in a tunnel ventilated high-rise layer house under different operational conditions. Six low-volume (1 m3 h1) TSP samplers were used to collect PM samples on two floors of the high-rise layer houses across four seasons through day/night sampling protocols. The day/night sampling design was to examine animal activity impact. The PM samples were analyzed by a multi-wave length laser diffraction particle size analyzer (LS13 320) for PSDs characterized by mass median diameters (MMDs) and geometric standard deviations (GSDs). It was discovered that the mean TSP concentrations ranged from 1.0 0.5 mg m3 to 5.33 0.36 mg m3 (mean SD). TSP concentrations in winter were higher than in summer; concentrations on the 2nd floor were higher than that on the 1st floor; concentrations of daytime samples were higher than those of nighttime samples. Animal activity (represented by day/ night samples) had the highest impact on TSP concentration as compared to other influential factors (spatial, seasonal, ventilation). No significant seasonal variations of MMD and GSD were observed in most of samples. Majority of day/night MMDs and GSDs demonstrated no significant differences. Thus the impact of animal activity (day vs. night) on MMD and GSD were not significant. Mean MMDs SDs ranged from 16.81 1.57 mm to 20.26 3.53 mm, whereas means SDs of GSDs ranged from 2.38 0.20 to 2.81 0.30. Mean PM2.5 fractions SDs ranged from 5.03 1.60% to 8.93 0.97%, whereas mean PM10 fractions SDs ranged from 23.25 5.18% to 38.55 2.96%. Significant seasonal variation in both PM10 and PM2.5 mass fractions were observed. Ó 2012 Elsevier Ltd. All rights reserved.
Keywords: Animal feeding operations Hen layer operation Particulate matter TSP Particle size distribution
1. Introduction As one of the six criteria pollutants defined in the National Ambient Air Quality Standards (NAAQS) (EPA, 2008), particulate matter (PM) is a major pollutant emitted from animal feeding operation (AFO) facilities, especially from poultry operation buildings. In animal environments, PM particles may carry gaseous pollutants, bacteria, and viruses, and transport potentially harmful materials to the ambient environment. While PM emissions from AFO buildings have been considered to be significant sources of the atmospheric PM in rural areas (NRC, 2003), significant knowledge gaps still exist regarding characteristics of PM emitted from AFOs. Housing type and growing conditions greatly influence the nature
* Corresponding author. Tel.: þ1 919 515 6762; fax: þ1 919 515 7760. E-mail address:
[email protected] (L. Wang-Li). 1352-2310/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2012.03.064
and magnitude of PM emissions from AFO buildings. The dynamics of animal housing/biological systems make the characteristics of PMemissions from AFOs different from other industrial pollutants. Studies of PM health impacts, emission estimation, fate and transport, and development of new control technologies require knowledge of characteristics of the PM. While there have been a few studies focusing on PM emission associated with AFOs, limited research has been conducted to characterize AFO PM (Maghirang et al., 1997; Capareda et al., 2005; Ellen et al., 2000; Predicala et al., 2001; Chen et al., 1995; Lee, 2009). Fundamental data regarding AFO PM either do not exist, or are not representative of different animal production systems or housing types. One example of the lack of information about AFO PM is the missing information about particle size distribution (PSD), which is perhaps the most important physical parameter governing particle behavior (Hinds, 1998). In addition, chemical composition, and the biological nature of AFO PM also remain to be investigated.
L. Wang-Li et al. / Atmospheric Environment 66 (2013) 8e16
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Fig. 1. Layout of the farm and the locations of TSP sampler placement (round dots in houses 3 and 4).
This project aimed to fill the knowledge gap on physical characteristics of PM emitted from layer operation (also known as egg production) buildings. The specific objectives of this study were to: Determine concentrations of total suspended particulate (TSP) in tunnel ventilated high-rise layer houses under different operational conditions. Determine PSDs of TSP in tunnel ventilated high-rise layer houses under different operational conditions. Estimate the mass fractions of PM10 and PM2.5 in TSP samples collected in tunnel ventilated high-rise layer houses. Investigate factors that might cause variations in TSP concentration and PSD in the layer houses. These factors include animal activity, ventilation, spatial and seasonal variations. 2. Methodology 2.1. PM sampling site e the layer operation farm The TSP sampling was conducted on a commercial layer operation farm located in North Carolina. As shown in Fig. 1, this
layer operation farm consisted of 9 egg production houses with capacity of housing approximate 1 million laying hens. Houses 1e4 were tunnel-ventilated high-rise barns, houses 5 and 6 are cross-ventilated high-rise barns, houses 93,102, 103 were naturally-ventilated shallow-pit barns. In the high-rise barns, laying hens were housed in six (houses 1e4) or eight (houses 5e6) rows of 4-tier curtain back cages in the upper floor (referred to as 2nd floor). Manure fell onto the curtain back and then down into the pit (referred to as 1st floor), where it was stored for up to one year. In the shallow pit barns, laying hens were housed in four rows of 3-tier curtain back cages. Manure fell onto the curtain back and then down on the concrete floor, where it was flushed out twice a day to waste treatment lagoon systems (solid trap plus lagoon). During the period of September 2007 through September 2009, two tunnel-ventilated high-rise houses (3 and 4) were monitored for the baseline emissions of PM, NH3, H2S, CO2 and volatile organic compounds (VOC) under the National Air Emission Monitoring Study (NAEMS), which was overseen by the US.EPA (EPA, 2005;Wang-Li et al., submitted for publication; Wang et al., 2010; Heber et al., 2008). To take advantage of NAEMS, the TSP sampling for this reported study was also carried out in these two houses, in which animal activity data, ventilation
House 2
S
House 3
High-rise houses (18m x 175m)
S
House 4
S Solar sensor
Instrument shelter
Static pressure port
Thermocouple
Anemometer
RH/Temp probe
Air sampling
Exhaust fan
Activity sensor
PM monitor
Air inlet
Heated raceway
Loadout doors
Wind sensor
Fig. 2. To view of the monitored houses (3 & 4) and the monitoring sensor locations (Wang et al., 2010).
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L. Wang-Li et al. / Atmospheric Environment 66 (2013) 8e16
Fig. 3. Illustration of the internal and external views of a tunnel ventilated high-rise house. [A]: ventilation fans on east endwall; [B]: laying hens on the 2nd floor; [C]: manure on the 1st floor.
rate and indoor environmental data were available to the project team from the NAEMS. The TSP sampling was conducted for four seasons in 2009. The monitored houses were typical tunnel ventilated high-rise barns with dimensions of 175 m (580ft) long by 18 m (58ft) wide housing approximate 95,000 laying hens. Ventilation air entered the 2nd floor of the house through 36.5 m (120ft) long air inlets centered on north and south walls of the house. As shown in Figs. 2 and 3, each endwall (east or west) was equipped with seventeen, 1.2-m (48-in) diameter, 480 VAC, 3-phase, belt-driven ventilation fans (Chore-time, Milford, IN). Among these seventeen fans, eight fans were located in the 2nd floor, and nine fans were in the 1st floor. Each house had 34 fans in total, and was ventilated in 11 stages. Two stage-1 fans (minimum ventilation fans) were located in the middle of each endwall (east, or west) in the 1st floor. These stage-1 fans were also known as the primary representative exhaust fans (PREFs).
2.2. PM samplers Six low-volume (LV) TSP samplers were used in this study to collect PM samples from two layer houses 3 and 4 on the first floors, or from two floors of the house 3. This LV-TSP sampler was originally designed and manufactured by the research group at Texas A&M University (Wangjura et al., 2005) following the US EPA’s specifications of the engineering design parameters for a high volume TSP sampler in 40 CFR Part 50 Appendix B (CFR, 1987). As shown in Fig. 4, a LV TSP sampler consisted of a TSP inlet head with 47 mm filter holder and a flow control system. In this sampling system, the pump pulled the PM-laden air through the inlet opening of the TSP head and then through a 47 mm filter. The PM in the sampled air was then captured on the filter, and the
filtered air passed through a flow control system and then was discharged. In the sampler’s flow control system, an orifice meter was used to control the system air flow rate at 16.7 l min1. The pressure drop across the orifice meter was monitored using a magnehelic differential pressure gauge during the sampling period. This pressure drop was pre-set at a target value to ensure flow rate of 16.7 l min1 at the beginning of each sampling event using Eq. (1). During the sampling period, the pressure drop was randomly checked. If a change in the pressure drop across orifice meter was observed (which was not often observed), a needle valve in the sampling system was used to adjust the flow to maintain constant pressure drop across the orifice meter at the target value such that air flow rate stayed unchanged. 4
Q ¼ 1:252*10
*K*D2o *
sffiffiffiffiffiffiffi DP
ra
(1)
where Q is the airflow rate through the orifice meter (m3 h1), the target flow rate was 1 m3 h1 (16.7 l m1), K is the orifice flow coefficient (dimensionless), and was determined through system flow calibration, Do is the orifice diameter (m), DP is pressure drop cross the orifice (mm H2O), and ra is the air density (kg m3) at the sampling time. Eq. (1) was used to calculate the sampling system air flow rates (Q) corresponding to measurements of pressure drops across the orifice at the beginning and ending time. The average of the beginning and the ending system flow rates was used for the concentration calculation. 2.3. Determination of TSP concentrations TSP concentrations were determined using the following equation:
Con:TSP ¼
Fig. 4. Low-volume TSP sampling system (the TSP sampler) (Wangjura et al., 2005).
Wf Wi Q *t
(2)
where Con.TSP is the TSP concentration (mg m3), Wi is filter preweight (mg), Wf is the filter post-weight (mg), Q is average sampling system air flow rate (m3 min1), and t is the sampling duration (min). Filters used in this study were 47 mm (2.5 mm) ZefluorÔ supported PTEF filters (Pall Corporation, Ann Arbor, Michigan). All the
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Fig. 5. Placement of the LV-TSP samplers at the east end inside the house 3. [A]: three LV-TSP samplers collocated with a TEOM sampler on the 1st floor; [B]: three LV-TSP samplers on the 2nd floor.
filters were conditioned in an environmentally controlled chamber at (20e23) C and (30e40)% RH for 48 hours before they were weighed for pre- and post- weights. 2.4. Field sampling protocols To achieve specific research of objectives, following two sampling protocols were designed and carried out for this study. The first set of PM sample collection events was designed to investigate variations in PSD of PM in two layer houses (3 & 4). The sample collection was conducted once per week in October and November, 2008. Three LV-TSP samplers were co-located in house 3 and two LW-TSP samplers were co-located in house 4 at identical locations. All the samplers were placed inside the houses immediately upstream of the exhaust fans (2.5 m away) on the east endwalls. For this set of sample collection, six sampling events were conducted with five hours daytime duration per sampling event. The second set of sample collection events was designed to investigate variations in both concentration and PSD of PM in a layer house (barn 3) over different sampling times (daytime and nighttime) and across different seasons, (winter, spring, summer, and fall). This group of sample collection was conducted through a sampling campaign for four consecutive days (four days and three
nights) in each season. Three LV-TSP samplers were co-located on the first floor and the other three LV-TSP samplers were co-located on the second floor of the same house immediately upstream of the exhaust fans on the east endwall. This sampling design generated three replicates in TSP samples on each floor for each sampling event with total of 13 sampling events for each of four day sampling campaign in the winter, spring and fall, respectively, and 12 sampling events in summer. The placement of the TSP samplers is illustrated in Fig. 5. To investigate animal activity impact on concentration and PSD of PM in the house, the sample collections were carried out following the lighting schedule in the house. Daytime samples were collected from 3:00am to 8:00pm when all the in-house lights were on and the chickens were quite active, whereas nighttime samples were collected from 8:00pm to 3:00am when the in-house lights were off and chicken activity was at minimum. The detailed sampling duration and sampling time are list in Table 1. As it is known, the ventilation system is a major factor influencing PM concentration in the house. Each house was ventilated in 11 stages and had eight temperature sensors (not shown in Fig. 2) to guide the control of the ventilation stages. Two stage-1 fans located in the middle of each endwall (east, or west) in the 1st floor were
Table 1 Sampling timetable for the second set of PM sampling events.a Winter 2009
Spring 2009
Summer 2009
Fall 2009
Date
Time
Shift
Date
Time
Shift
Date
Time
Shift
Date
Time
Shift
Day 1 01/30/09
10ame3pm 3pme8pm 8pme3am
Dayb Day Nightc
Day 1 04/03/09
10ame3pm 3pme8pm 8pme3am
Day Day Night
Day 1 07/21/09
10ame3pm 3pme8pm 8pme3am
Day Day Night
Day 1 10/06/09
10ame3pm 3pme8pm 8pme3am
Day Day Night
Day 2 01/31/09
3ame8am 8ame2pm 2pme8pm 8pme3am
Day Day Day Night
Day 2 04/04/09
3ame8am 8ame2pm 2pme8pm 8pme3am
Day Day Day Night
Day 2 07/22/09
3ame8am 8ame2pm 2pme8pm 8pme3am
Day ed e e
Day 2 10/07/09
3ame8am 8ame2pm 2pme8pm 8pme3am
Day Day Day Night
Day 3 02/01/09
3ame8am 8ame2pm 2pme8pm 8pme3am
Day Day Day Night
Day 3 04/05/09
3ame8am 8ame2pm 2pme8pm 8pme3am
Day Day Day Night
Day 3 07/23/09
3ame8am 8ame2pm 2pme8pm 8pme3am
e e Day Night
Day 3 10/08/09
3ame8am 8ame2pm 2pme8pm 8pme3am
Day Day Day Night
Day 4 02/02/09
3ame8am 8ame2pm
Day Day
Day 4 04/06/09
3ame8am 8ame2pm
Day Day
Day 4 07/24/09
3ame8am 8ame8pm 8pme10am
Day Day Night
Day 4 10/09/09
3ame8am 8ame2pm
Day Day
Day 5 07/27/09
10ame8pm 8pme3am
Day Night
Day 6 07/28/09
3ame8am
Day
a b c d
In winter, spring and fall, 10 daytime & 3 nighttime sampling events were conducted; in summer, 8 daytime & 4 nighttime sampling events were conducted. Day: daytime sampling event. Night: nighttime sampling event. No sample was taken due to the in-house manure cleanout event.
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the primary representative exhaust fans (PREFs), or minimum ventilation fans, and they were on running all the time. Each of the next six stages (i.e. stages 2e7) added 2 fans when the in-house temperature increased by 2 C. The stages 8e9 added four fans each, and the stage 10e11 added the final 6 fans. More information about the ventilation settings for the monitored houses may be found in Wang-Li et al. (submitted for publication). The operational status (on/off) of all the ventilation fans were monitored 24/7 for two years (Sept. 2007eSept. 2009) using either a magnetic Halleffect RPM sensor (Cherry sensors, MP100701 hall-effect rpm sensor) or a current switch (CR9380-NPN current switch, CR Magnetic Inc.). To investigate ventilation rate impact on PM concentrations and PSDs in the house, fan running times and numbers of running fans during each sampling event were incorporated to develop an equivalent flow rate factor for data analysis. The equivalent flowrate factor (EFF) is defined by Eqs. (3) and (4) (Cao, 2009). The EFF is the sum of all fans’ running time divided by sampling duration for each sampling event, assuming that all fans have the same flow rate.
t þ tF10 þ // þ tF17 EFFð1st floorÞ ¼ F9 t
tF1 þ tF2 þ // þ tF8 : t
rffiffiffiffiffi AED ¼ ESD
rP c
(5)
where rp is the particle density, measured by a pycnometer (AccuPyc1330, Micromeritics, Norcross, GA), c is the shape factor of a particle and was assumed to be 1 in this study (Cao, 2009). 2.6. Mass fractions of PM10 and PM2.5
(3)
where tFn is the nth fan’s running time (s) and n is the fan number on the 1st floor i.e. 9, 10, .17, t is sampling duration (s).
EFFð2nd floorÞ ¼
characterizing PSD of a lognormal distribution. The MMD for a PSD is defined as the diameter for which half the total mass of particles is larger and half is smaller than this size. The GSD is defined as the square root of d84.1 divided by d15.9. By definition, the d84.1 and d15.9 are the diameters that particles constituting 84.1% and 15.9% of the total mass of particles are smaller than these sizes (Hinds, 1998). PSD measured by LS13 320 is in the form of particle volume in equivalent spherical diameter (ESD), whereas EPA regulates PM in two size ranges (10 mm, or 2.5 mm) in the form of aerodynamic equivalent diameter (AED). So, the ESD obtained from the LS13 320 needs to be converted to the AED using the following equation (Hinds, 1998):
(4)
where, tFn is the nth fan’s running time (s) and n is the fan number on the 2nd floor, i.e. 1, 2, .8, t ¼ sampling duration (s). 2.5. Particle size distribution measurements 2.5.1. PM sample extraction PM samples collected on the 47 mm filters were extracted from filters into ethanol solution for PSD analysis using ultrasonic bath method. A preliminary study on determining optimum ultrasonic time was conducted and it was discovered that fifteen minutes was the time when the most coagulated particles were separated and yet no break-down of the particles was observed (Cao, 2009). As a result, all the PM samples were extracted through ultrasonic bath for 15 min. 2.5.2. Particle size analyzer A multi-wave length laser diffraction particle size analyzer (LS13 320, Beckman Coulter, Miami, FL), was used to analyze PSD of the PM samples collected by TSP samplers on the farm. Laser diffraction technique relies upon the fact that when particles are exposed to beams of light, the light scattering pattern of particles is directly related to particle size: larger particles scatter at smaller angles while smaller particles scatter at larger angles (Hinds, 1998). The LS13 320 optical bench multi-wave length laser diffraction particle size analyzer consists of a diffraction light source, a sample cell, a Fourier lens and a series of photo detectors. The analyzer is capable of detecting samples in the size range of 0.04 mme2000 mm. It measures the entire sample introduced to the instrument and automatically calculates mass median diameter (MMD) and geometric standard deviation (GSD) of a measured PSD. In application of light scattering principal for PSD measurement, refractive index (RI) of PM particles is required. Since no indices were available for AFO PM, a RI of 1.5 recommended by the technical support of the Beckman Coulter was used for this study. As it was reported, PSD of PM tends to follow a lognormal distribution (Hinds, 1998). MMD and GSD are two parameters
PM10 and PM2.5 are designated as indicators of PM in NAAQS due to their adverse health effects. By definition, PM10 and PM2.5 are the particles with AED smaller than or equal to 10 mm and 2.5 mm, respectively. When a PSD of a PM sample is measured by the PSD analyzer, the mass fractions of PM10 and PM2.5 are also obtained through the cumulative distribution of the PSD. In this study, to assess spatial and seasonal variations of PM10 and PM2.5, mass fractions of PM10 and PM2.5 were extracted from measured cumulative PSDs. These mass fractions were defined as the measured mass fractions of PM10 and PM2.5, and were analyzed statistically for comparisons of means over different seasons, floors, and sampling times. 2.7. Data analysis Statistical analysis of the data was performed using SAS version 9.2 (SAS Institute Inc., Cary, NC, USA). To investigate spatial (1st floor vs. 2nd floor) and seasonal (winterespringesummerefall) variations of TSP concentrations, PSDs represented by MMDs and GSDs, and PM10/PM2.5 mass fractions, data were subjected to paired
Table 2 Comparisons of MMDs (in AED)a and GSDs of the PM samples taken in two layer houses. Sampling date
House 3
10/16/2008 10/23/2008 10/24/2008 10/30/2008 11/13/2008 11/25/2008 12/04/2008 12/11/2008 Mean SD
House 4
MMD (mm)
GSD
MMDc (mm)
GSDc
19.63 19.53 20.86 18.07 16.78 19.92 18.83 ed 19.09 1.34
2.71 2.66 2.55 2.51 2.54 2.68 2.54 ed 2.60 0.08
18.01 17.90 20.24 18.18 20.32 21.50 18.91 19.40 19.31 1.30
2.74 2.59 2.58 2.80 2.56 2.43 2.61 2.58 2.61 0.11
b
b
a MMDs were analyzed using a LS 13320 multi-wave length laser diffraction particle size analyzer in ESD and then were converted to AED using Eq. (5) with an assumption of the particle shape factor in 1 and with a particle density of 1.48 g/cm3 measured by an AccuPyc 1330 Pycnometer. b Average of three replicates from TSP samples taken by three co-located TSP samplers. c Average of two replicates from TSP samples taken by two co-located TSP samplers. d Sample loading was too light and could not be measured by the LS13 320.
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Fig. 6. Spatial and seasonal variations of TSP concentrations (mean SD) and the means of the equivalent flowrate factors over different seasons (Day-1st: daytime 1st floor; Day2nd: daytime 2nd floor; Night-1st: nighttime 1st floor; Night-2nd: nighttime 2nd floor).
t tests and ANOVA tests. To identify factors that may have significant impact on in-house TSP concentrations, a multiple liner regression model was constructed with SAS proc mixed and proc glmmix to assess effects of multiple independent variables on the dependent variable, i.e. TSP concentration. The independent variables include the following:
houses at the 0.05 level of significance (a). The average MMD and GSD of PM collected from both houses were 19.21 1.27 mm and 2.60 0.09, respectively.
Season: winter, spring, summer and fall, fixed effect Floor: 1st floor and 2nd floor, fixed effect, representing spatial effect DN: day and night, fixed effect, representing chicken activity effect EFF: fixed effect, representing ventilation effect Sampling day (season): sampling days were nested in season and they were randomly selected, thus they were random effect.
The means and standard deviation (SDs) of the TSP concentrations over different seasons, on different floors, and through different sampling times (daytime and nighttime) are illustrated in Fig. 6 (detailed TSP measurement results are presented in the appendix Tables A1eA2). As it was expected that house ventilation (represented by EFF) and animal activity (represented by day/ night sampling time) are two major factors influencing in-house TSP concentrations, the means of EFFs over different seasons, on different floors, and through different sampling times (daytime and nighttime) are also included in Fig. 6 (more details of EFFs are included in the appendix Table A7). Results of the statistic testing on the multiple linear regression model (Eq. (6)) are listed in Table 3. As indicated in Fig. 6 and Table 3, TSP concentrations varied with seasons, floors (1st vs. 2nd) and sampling times (day vs. night). Although the house ventilation had inevitable impact on in-house TSP concentration, the statistic tests revealed that
With assumption of different variances for different seasons, the multiple linear regression model in Eq. (6) was constructed to test (1) main effect (i.e. season, floor, DN, EFF), (2) interaction effect (two-way interactions of the factors), (3) random effect (sampling day, nested in season):
3.2. Spatial and seasonal variations of in-house TSP concentrations
TSPijkl ¼ m þ seasoni þ floorj þ DNk þ EFF þ seasoni *floorj þ seasoni *DNk þ seasoni *EFF þ floorj *DNk
Table 3 Statistic testing results of the effects of various factors on in-house TSP concentration.
þ floorj *EFF þ DNk *EFF þ Dayl ðseasoni Þ þ 3 ijkl (6) 3. Results and discussion 3.1. PSDs of the PM samples taken in two monitored houses The results of the PSDs of the PM samples taken in two monitored layer houses in fall 2008 are listed in Table 2. T-test was performed to determine if there were significant differences between the samples collected from these two layer houses with respect to MMDs and GSDs. No significant differences in MMDs (p ¼ 0.9219) and GSDs (p ¼ 0.4673) were detected between the two
Effect
Num DF
Den DF
F value
Pr > F
Season Floor DNa EFFb Season * Floor Season * DN Season * EFF Floor * DN Floor * EFF DN * EFF
3 1 1 1 3 3 3 1 1 1
14 62 62 62 62 62 62 62 62 62
17.64 23.22 65.47 3.19 11.40 21.14 2.51 3.13 0.53 0.13
