Advanced Strategies for Mitigating Particulate Matter Generations in Poultry Houses
Abstract
:1. Introduction
2. Dust Composition and Mixture
Sources | PM Type | PM Constitute | References |
---|---|---|---|
Broilers | TSP | Feathers, skin, bacteria, fungus, fecal matter, spilled feed, mold spores, and bedding fragments | [16] |
Broilers | PM2.5 PM10 | 72.1% manure, 21.3% feathers, 5.8% wood shaving, and 0.7% ambient PM 95.6% manure and 4.4% feathers | |
Layers | PM2.5 PM10 | 63.7% manure and 36.3% feathers 69.6% manure, 30.0% feathers, and 0.4% ambient PM | [17] |
Layers | PM2.5 PM10 | 54.2% manure, 23.2% feed, 17.0% feathers, and 5.5% ambient PM 85.5% manure and 14.5% feathers | |
Turkey | PM2.5 PM10 | 39.1% feathers, 34.8% manure, 26.1% wood shavings, and 0.1% ambient PM 51.9% manure, 25.1% feathers, and 22.9% wood shavings | |
Broilers | TSP | 50% excreta, 30% litter, 15% feed, and 5% feathers | [18] |
Poultry | TSP | 90% organic composition like a feather, feeds, urine mineral crystal, manure, and bedding materials | [25] |
Poultry | TSP | Organic and inorganic particles: excreta, feathers, mites, dander, bacteria, fungi, fungal spores, and endotoxins | [33] |
Poultry | TSP | Bedding materials and floor | [34] |
Poultry | TSP | Feed, excreta, hair, and dander | [35] |
3. Factors Affecting Dust Generations
3.1. Effect of Housing Systems on PM
3.2. Effect of Bedding Materials on PM Levels
3.3. Effect of Lighting and Seasonal Variations on PM Levels
3.4. Effect of Ventilation System
3.5. Effect of Indoor Temperature and Relative Humidity
3.6. Other Factors
3.6.1. Manure Cleaning Methods
3.6.2. Bird Age, Stocking Density, and Behaviors
4. Impacts of PM on the Health and Welfare of Chickens and Farm Workers
4.1. Impacts on Birds’ Health, Behaviors, and Welfare
4.2. Human Health, Behaviors, and Welfare
4.3. Poultry Production
5. Mitigation Strategies Suppressing PM Levels in Poultry Houses
6. Particulate Matter Emission Mitigating Strategies
6.1. Housing Systems and Cleaning
6.2. Oil and Water Spraying
6.3. Filtration and Biofiltration
Filter/Biofilter | PM Size | PM Reduction (%) | References |
---|---|---|---|
Wood-chip Bio-filter 127 mm 254 mm | PM10 TSP | 62 and 89.7 62.9 and 96.3 | [9] |
Stuffnix dry filter U-bend baffle filter | PM2.5 and PM10 | 41 and 64 19 and 22 | [44] |
Dry filter | PM concentrations PM emissions | 55 72 | [62] |
Dry filter | PM2.5 PM10 | 7.1 40.7 | [66] |
Biotrickling filter and denitrification EBRT * = 3 s EBRT = 0.71 s EBRT = 3.6 s | PM10 | 38 60 69 | [124] |
Stuffnix dry filter | Fine dust | 20–60 | [125] |
Trickling biofilter using acidified water | PM10 | >80 | [126] |
Bio-filter | TSP | 79–96 | [127] |
6.4. Bedding Materials
6.5. Scrubbers
6.6. Electrostatic Ionization
6.7. Other Management Practices
6.7.1. Aeration and Ventilation System
6.7.2. Lighting Management
6.7.3. Precision Control of Indoor Temperature and Relative Humidity
7. Summary
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Housing System | Location | Bird Density | Monitoring Device | PM Size | PM Emission (g day−1AU−1) | PM Concentration (mg m−3) | References |
---|---|---|---|---|---|---|---|
CC | Midwest, US | 200,000 | TEOMs | PM2.5 PM10 | N/A | 0.04 0.59 | [3] |
CC | Midwest, US | 200,000 | TEOMs | PM2.5 PM10 | 0.9 * 15.7 * | N/A | [40] |
CC | France | 45,257 ± 18,800 | Stationary captor | PM2.5 | N/A | 0.11 | [41] |
CC | Germany | 1350 | Glass fiber filter | TSP | N/A | 0.6 1.25 | [42] |
Caged layer | South Korea | 5636 | Gravimetric method and air sampling pump | TSP | N/A | 3.66 1.99 | [43] |
Caged hen | UK | N/A | TEOMs, Micro Orifice Uniform Deposit Impactors | PM2.5 PM10 | 6.9 * 16.9 * | N/A | [44] |
Furnished cages | Sweden | 7500 | Battery powered pump | TSP | N/A | 2.3 | [45] |
Battery caged | Toledo, Spain | 100,000 | TEOMs | PM2.5 PM10 | N/A | 0.55 ± 0.38 | [46] |
EC | Midwest, US | 50,000 | TEOMs | PM2.5 PM10 | 1.7 * 15.6 * | N/A | [40] |
EC | Midwest, US | 50,000 | TEOMs | PM2.5 PM10 | N/A | 0.41 3.95 | [3] |
EC | Toledo, Spain | 100,000 | TEOMs | PM2.5 PM10 | N/A | 0.024 ± 0.025 | [46] |
EC | Germany | 1500 | Glass fiber filter | PM2.5 PM10 | N/A | 0.5 1.95 | [42] |
EC | France | 45,257 ± 18,800 | Stationary captor | PM2.5 | N/A | 0.15 | [41] |
CF | Beijing, China | 1800 | Arduino Mega2560 microcontroller, DFRobot sensor shield | PM2.5 PM10 TSP | N/A | 0.04 ± 0.03 0.42 ± 0.10 1.92 ± 1.91 | [47] |
CF | Midwest, US | 50,000 | TEOMs | PM2.5 PM10 | 8.8 * 100.3 * | N/A | [40] |
CF | Midwest, US | 50,000 | TEOMs | PM2.5 PM10 | N/A | 0.14 3.95 | [3] |
CF | France | 20,750 ± 10,250 | Stationary captor | PM2.5 | N/A | 1.19 | [41] |
CF | IOWA, USA | 50,000 | TEOMs | PM10 PM2.5 | 29.5 ± 11 2.1 ± 1.7 | 2.30 ± 1.60 0.25 ± 0.26 | [48] |
CF | Netherlands | 35,000 and 24,712 | Virtual cascade impactors, DustTrack aerosol monitor | PM10 | N/A | 3.06 ± 1.54 | [17] |
CF | Germany | 2300 | Glass fiber filter | PM2.5 PM10 | N/A | 2.3 5.4 | [42] |
FR | France | 40,780 ± 16,804 | Stationary captor | PM2.5 | N/A | 0.37 | [41] |
FR broiler | UK | N/A | TEOMs, Micro Orifice Uniform Deposit Impactors | PM2.5 PM10 | N/A | 0.66 2.99 | [44] |
FR | Sweden | 6900 | Battery powered pump | TSP | N/A | 12 | [45] |
FR | Netherlands | 16,500 and 3850 | Virtual cascade impactors, DustTrack aerosol monitor | PM10 | N/A | 3.94 ± 0.69 | [17] |
Broiler | Netherlands | 50,400 and 2675 | Virtual cascade impactors, DustTrack aerosol monitor | PM10 | N/A | 1.96 ± 0.55 | [17] |
Broiler | South Korea | 5636 | Gravimetric method and air sampling pump | TSP | N/A | 5.08 2.75 | [43] |
Broilers | UK | N/A | TEOMs, Micro Orifice Uniform Deposit Impactors | PM2.5 PM10 | 5.1 31.6 * | N/A | [44] |
Free-range hen | UK | N/A | TEOMs, Micro Orifice Uniform Deposit Impactors | PM2.5 PM10 | 36.4 * 139 * | N/A | [44] |
Turkey | Netherlands | 5000 and 4040 | Virtual cascade impactors, DustTrack aerosol monitor | PM10 | N/A | 2.32 ± 0.99 | [17] |
Two Commercial laying hen | Ontario, CA | 65,000 70,000 | DustTrak aerosol analyzers | PM10 PM2.5 | 2.55 ± 2.10 1.10 ± 1.52 | 0.19 ± 0.17 0.03 ± 0.03 | [37] |
MB layer | South Korea | 5636 | Gravimetric method and air sampling pump | TSP | N/A | 4.42 2.25 | [43] |
MB 1 MB 2 | Indiana, USA | 200,000 180,000 | Tapered Element Oscillating Microbalances (TEOM) | PM10 | N/A | 0.42 ± 0.43 0.76 ± 0.66 | [9] |
Two HR. | Midwest, USA | 250,000 per HR | TEOMs | Total | 20.6 ± 22.5 * | N/A | [5] |
HR layer | North Carolina, USA | 103,000 | TEOMs | PM2.5 PM10 TSP | 0.12 ± 0.26 6.03 ± 2.63 14.2 ± 5.23 | N/A | [49] |
HR 1 HR 2 | Indiana, USA | 200,000 180,000 | Tapered Element Oscillating Microbalances (TEOM) | PM10 | N/A | 0.54 ± 0.30 0.55 ± 0.34 | [9] |
HR layers | California, USA | 32,500 | Tapered element oscillating microbalance (TEOM) | PM2.5 PM10 TSP | 5.9 ± 12.6 33.4 ± 27.4 78.0 ± 42.7 | N/A | [30] |
HR layers | IOWA, USA | 250,000 | TEOMs | PM10 PM2.5 | 8.16 ± 4.94 1.13 ± 1.16 | 0.39 ± 0.26 0.044 ± 0.04 | [50] |
Multilevel system | Sweden | 13,500 | Battery powered pump | TSP | 1.8 | [45] |
Bedding Material | Source | PM Sizes | PM Emission (mg/m3) | References |
---|---|---|---|---|
Cornstalk chip | Broiler | TSP | 6.5 | [58] |
Sugarcane top chips | Broiler | TSP | 6.8 | [58] |
Wood shaving | Laying hens | TSP | 2.3 | [56] |
Wood shaving | Broiler | PM2.5 * PM10 * | 1.05 20.3 | [55] |
Sawdust | Dairy farm | TSP | 0.51 | [59] |
Wheat straw | Broiler | TSP | 6.9 | [58] |
Rapeseed straw | Broiler | PM2.5 * PM10 * | 0.98 20.6 | [55] |
Rapeseed straw | Broiler | PM2.5 * PM10 * | 0.97 and 20.5 | [55] |
Clover straw | Broiler | TSP | 6.7 | [58] |
Chopped straw | Laying hens | TSP | 2.1 | [56] |
Straw | Dairy farm | TSP | 0.53 | [59] |
Chopped palm spines | Broiler | TSP | 6.5 | [58] |
Corn ear husks | Broiler | TSP | 6.8 | [58] |
Silage maize | Broiler | PM2.5 * PM10 * | 0.85 21.0 | [55] |
Chopped paper | Laying hens | TSP | 2.6 | [56] |
Peat | Laying hens | TSP | 1.7 | [56] |
Compost | Dairy farm | TSP | 1.38 | [59] |
Clay pellets | Laying hens | TSP | 1.8 | [56] |
Gravel | Laying hens | TSP | 4.7 | [56] |
PM Size | Fall | Winter | Spring | Summer | References |
---|---|---|---|---|---|
PM1 | 0.01 | 0.03 | N/A | 0.02 | [63] |
PM1 | 75.6 ± 14.1 | 136.0 ± 12.8 | 53.5 ± 6.3 | 14.9 ± 1.2 | [64] |
PM1 | N/A | 0.12 ± 0.00 * | 0.09 ± 0.00 * | N/A | [65] |
PM2.5 | 81.6 ± 15.1 | 144.2 ± 14.5 | 58.1 ± 6.9 | 15.8 ± 1.1 | [64] |
PM2.5 | 0.05 | 0.10 | N/A | 0.07 | [63] |
PM2.5 | 0.09–0.11 a | 0.09–0.20 a | 0.07–0.12 a | 0.06–0.10 a | [61] |
PM2.5 | 0.29 ± 0.22 | 0.43 ± 0.27 | N/A | 0.067 ± 0.055 | [38] |
PM2.5 | 0.23 ± 0.15 # | 0.30 ± 0.19 # | 0.81 ± 0.87 # | 2.46 ± 2.04 # | [37] |
PM2.5 | 0.04 ± 0.02 | 0.06 ± 0.03 | 0.04 ± 0.03 | 0.08 ± 0.04 | |
PM2.5 | N/A | 0.16 ± 0.006 * | 0.10 ± 0.00 * | N/A | [65] |
PM4 | 0.32 ± 0.23 | 0.48 ± 0.31 | N/A | 0.074 ± 0.060 | [38] |
PM10 | 0.10 | 0.24 | N/A | 0.15 | [63] |
PM10 | 0.51–0.69 a | 0.71–0.88 a | 0.24–1.01 a | 0.15–0.21 a | [61] |
PM10 | 94.8 ± 15.6 | 385.2 ± 16.6 | 183.0 ± 18.5 | 30.1 ± 1.9 | [64] |
PM10 | 0.53 ± 0.35 | 0.69 ± 0.4 | N/A | 0.119 ± 0.011 | [38] |
PM10 | 2.73 ± 1.91 # | 2.82 ± 2.42 # | 2.23 ± 2.08 # | 2.51 ± 2.08 # | [37] |
PM10 | 0.50 ± 0.31 | 0.49 ± 0.43 | 0.16 ± 0.09 | 0.14 ± 0.08 | |
PM10 | N/A | 0.49 ± 0.02 * | 0.63 ± 0.02 * | 0.56 ± 0.02 * | [65] |
TSP | N/A | 2.22–4.96 a | N/A | 0.34–0.48 a | [61] |
TSP | 147.8 ± 18.3 | 983.2 ± 86.1 | 413.2 ± 39.8 | 49.6 ± 3.6 | [64] |
TSP | 4.16 ± 2.19 | 4.98 ± 2.29 | 4.41 ± 2.14 | 4.00 ± 1.94 | [43] |
TSP | 1.93 ± 0.82 | 3.29 ± 1.68 | 2.35 ± 1.15 | 1.76 ± 0.84 | [43] |
Location | Ventilation Type | Sensors | PM Size | PM Emission (mg d−1 bird−1) | PM Concentration (mg m−3) | References |
---|---|---|---|---|---|---|
China | TBM equipment with the main ventilation system | TSI 9306 dust sampler | TSP | N/A | 18.65 (closed) 14.25 (open) | [39] |
China | Double-tunnel ventilation with air inlet | Self-developed portable device | PM2.5 PM10 | N/A | 0.06 0.04 | [67] |
Mississippi, USA | Negative pressure ventilation | TSI DustTrak 8533 | PM1 PM2.5 PM4 PM10 TSP | N/A | 0.148 0.149 0.151 0.160 0.169 | [68] |
North Carolina, USA | Tunnel-ventilation with 34 exhaust fans | Tapered element oscillating microbalance (TEOMs) | PM2.5 PM10 TSP | 0.37 ± 3.06 17.8 ± 14.9 43.1 ± 35.5 | N/A | [49] |
California, USA | Portable 122 cm exhaust fan | TEOMs | PM2.5 PM10 TSP | 0.006 ± 0.013 0.033 ± 0.027 0.078 ± 0.043 | N/A | [30] |
Saudi Arabia | Naturally | Particle counter device | PM2.5 PM10 TSP | N/A | 0.18 ± 0.06 4.81 ± 1.63 12.47 ± 5.2 | [69] |
Mechanically | Particle counter device | PM2.5 PM10 TSP | N/A | 0.09 ± 0.05 2.26 ± 1.27 4.61 ± 3.1 |
PM Sizes/Types | Effects of PM on Health, Behavior, and Welfare | References |
---|---|---|
PM2.5 | Consists of a high level of microorganisms and endotoxin, which affects health | [86] |
PM2.5 | Induces developmental cardiotoxicity in chicken embryos and hatchling chickens | [89] |
PM2.5 | Impaired lung function | [83] |
PM10 | Increased risk of mortality rates | |
PM10 | Increased risk of chronic bronchitis, cardiovascular illness, pneumonia lesions, asthma-like symptoms, and lung cancer | [21,22] |
TSP | Decreased daily weight gain, increased lung inflammatory factors level, and may cause lung injury | [90] |
Endotoxin+ dust | Decrease in cell-mediated immunity B-cell percentages | [87] |
PM Sizes/Types | Effects of PM on Health, Behavior, and Welfare | References |
---|---|---|
PM2.5 | Greater risk to human health | [12,14] |
PM2.5 | Damage human alveolar epithelial cells (A549 cells) and cause an inflammatory response | [95] |
PM2.5 (long-term exposure) | Increases the risk of cardiopulmonary mortality | [11,94] |
PM2.5 (10,000 mg/m3) | 24% increase in cardiovascular events and a 76% increase in mortality | [92] |
PM10 | Premature death in humans with heart or lung disease Nonfatal heart attacks, irregular heartbeats, aggravated asthma, decreased lung function, irritation of the airways, coughing or difficulty breathing | [12,13] |
PM10 (With endotoxin) | Affects the respiratory system, liver, kidneys, and nervous system, and may even enter the bloodstream | [12,14,82] |
PM10 | Respiratory problems Increased mortality and morbidity rates | [11,94] |
PM10 (High concentration) | Chronic bronchitis, asthma-like symptoms, cardiovascular disease, lung cancer, COPD, and pneumonia lesions. | [21,22,23] |
PM10 (every increase in 7000 mg/m3) | 33% increase in COPD incidence | [93] |
TSP | Higher asthmatic (42.5%) and nasal (51.1%) symptoms | [23] |
TSP | Over-shift increase in respiratory symptoms and a decrease in pulmonary function tests were found. Causes harmful effects on the bronchi | [96] |
PM > 0.1 mg/m3 | Coughing, chronic phlegm, and bronchitis | [97] |
Organic dust | Acute inflammation and chronic bronchitis | [98] |
Country/Organization | Occupational Exposure Limit | References |
---|---|---|
World Health Organization | PM2.5: 5 µg/m3 annual mean & 15 µg/m3 24-h mean (2011 standard) | [11] |
PM2.5: 10 µg/m3 annual mean & 25 µg/m3 24-h mean (2005 standard) | [106] | |
PM10: 15 µg/m3 annual mean & 45 µg/m3 24-h mean (2011 standard) | [11] | |
PM10: 20 µg/m3 annual mean & 50 µg/m3 24-h mean (2005 standard) | [106] | |
USA (EPA) | PM2.5: 35 µg/m3 24-h mean | [13] |
PM10: 150 µg/m3 24-h mean | [13] | |
PM2.5: 12 µg/m3 annual mean (primary standard *) | [103] | |
PM2.5: 15 µg/m3 annual mean (secondary standard *) | [103] | |
USA (Occupational Safety and Health Administration) | Total dust 10 mg/m3 and respirable friction dust 5 mg/m3 (regulator limit of 8-h time-weighted average) | [105] |
Australia | PM2.5: 50 µg/m3 (1 h average) & 25 µg/m3 (24-h average) | [104] |
UK | Total and respirable dust limits are 10 and 5 mg/m3, respectively | [107] |
Spray System | Working Principle | Oil or Water Type | Application Rate (mL m−2d−1) | PM Size | PM Reduction (%) | References |
---|---|---|---|---|---|---|
Electrospray | Engineered water nanostructures | Water | 1 × 105 # | PM15 | 83 | [115] |
BETE fog spray nozzle | Droplet confine particles in a litter | Acidic electrolyzed water (0.1% NaCl solution and addition of 85% phosphoric acid) | 125 250 375 | Total PM | 71 ± 3 81 ± 1 89 ± 1 | [24] |
Fixed oil spraying system + Driving oil spraying vehicle | A fog of oil droplets + A spray of fine droplets | Rapeseed oil | 12 15 30 | PM10 and PM2.5 | 60 and 53 21 and31 32 and 38 | [73] |
Hand-held spraying lance | A spray of fine droplets | Rapeseed oil | 15 30 45 | PM10 PM2.5 | 27, 62, 82 71, 83, 94 | [73] |
Full cone nozzles | Spraying | Rapeseed oil with water | 10% | Total dust | 30–50 | [54] |
Sprayers with electrolytic cell generator | Droplet confine particles in a litter | Neutral electrolyzed water (pH 8.2) | 216 * | Airborne dust | 34 | [116] |
Battery backpack sprayer | Water fogged | Water | 150 * 300 * 600 * | PM10 PM2.5 | 18 and 44 48 and 59 64 and 64 | [76] |
Fixed oil spraying system | A spray of fine droplets | Rapeseed oil | 6 24 | PM2.5 PM10 | 84 and 48 80 and 87 | [75] |
Spray nozzle | Droplets confine particles in a litter | Rapeseed oil + Water | 5 a | Airborne dust | 80–85 | [117] |
Full cone nozzles | Droplet confine particles in a litter | Rapeseed oil | 8 16 | PM10 PM2.5 | 59 and 64 81 and 74 | [74] |
Backpack sprayer | Sprinkling | Canola oil | 10–30 * | Total | 37–89 | [114] |
Backpack sprayer | Sprinkled | Canola oil | Six application rates | Respirable Inhalable | 71 76 | [114] |
Bedding Material | PM Sizes | PM Reduction (%) | References |
---|---|---|---|
Silage maize Wood shaving Wheat straw Rapeseed straw | PM2.5 * | 19%, but No significant difference between wood shaving, wheat straw, and rapeseed straw | [55] |
chopped straw gravel peat wood shaving chopped paper clay pellets | Total dust | 19–64% reduction by clay pellets and peat compared to other | [56] |
Wheat straw Clover straw Cornstalk chip Sugarcane top chips Chopped palm spines Corn ear husks | Airborne dust | No significant difference between materials | [58] |
Compost Straw Sawdust | Total dust | 61% (straw) and 63% (sawdust) than compost | [59] |
Chopped hay Chopped straw | Total dust | Significant effects | [131] |
Scrubbers | PM2.5 (%) | PM10 (%) | TSP (%) | Airborne Total Bacteria (%) | References |
---|---|---|---|---|---|
Electrostatic spray wet scrubber | 85–88 | 85–94 | N/A | N/A | [134] |
Chemical (90% NH3 reduction) Air Scrubber | 28 | 33 | N/A | N/A | [135] |
Chemical (70% NH3 reduction) Air Scrubber | 33 | 41 | N/A | N/A | [135] |
Multiple pollutants scrubber | 42 | 43 | N/A | N/A | [132] |
Disinfectant Scrubber media: water Peracetic acid Ozone | N/A | N/A | 88 78 48 | 70 | [136] |
Multi-stage scrubber | 47–90 | 61–93 | N/A | 46–85 | [133] |
Bio-scrubber | N/A | N/A | 22 | N/A | [127] |
Control Technology | Charging Units | Source | PM2.5 (%) | PM10 (%) | Total Dust (%) | Airborne Bacteria (%) | References |
---|---|---|---|---|---|---|---|
Prototype ESP under hot, warm and cold weather | 0.545 kV mm−1 | Poultry | 86.9 94.4 97.8 | 90.8 97.1 99.0 | N/A | N/A | [143] |
Electrostatic particle ionization | Electrode −30 kV with 2 mA current | HR hen house | 66 * 30 # | 68 * 36 # | 68 * 45 # | N/A | [68] |
Negative ionization system Positive ionization system | Electrode −30 kV with 2 mA current Electrode +30 kV with 2 mA current | Broiler | 49 6 | 68 0 | N/A | N/A | [73] |
ESP | Electrode +30 kV with 0.2–1.0 mA current | CF hen | 45.3 | 57.0 | N/A | N/A | [66] |
Optimized ESP | 9.6 to 13.6 KV with air velocity 0.8 to 2.2 m/s | Laying hen | 86 | 84 | 82 | N/A | [142] |
Prototype ESP | +30 kVdc and <1 mA | Laying hen | 45 | 57 | N/A | N/A | [140] |
Air Ionization | −30 kVdc and 0.9 mA | Broiler | 10 | 36 | N/A | N/A | [139] |
ESCS | 25K–30K Vdc and 2 mA | HR layer house | N/A | 36 | 48 | N/A | [144] |
ESCS | −30 kVdc and 2 mA | Broiler | N/A | N/A | 43 | N/A | [8] |
ESCS | −30 kVdc and <0.5 mA | Broiler breeder | N/A | N/A | 61 | 67 | [145] |
ESCS | −30 kVdc and 0.2 mA | Hatching cabinets | N/A | N/A | 77–79 | 93–96% Enterobacteriaceae 33–83% Salmonella | [138] |
ESCS | −20 kVdc and 0.5 mA | Hatching cabinets | N/A | N/A | 94 | 93% Enterobacteriaceae | [137] |
ESCS | N/A | Swine | N/A | N/A | 57–66 | N/A | [146] |
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Bist, R.B.; Chai, L. Advanced Strategies for Mitigating Particulate Matter Generations in Poultry Houses. Appl. Sci. 2022, 12, 11323. https://doi.org/10.3390/app122211323
Bist RB, Chai L. Advanced Strategies for Mitigating Particulate Matter Generations in Poultry Houses. Applied Sciences. 2022; 12(22):11323. https://doi.org/10.3390/app122211323
Chicago/Turabian StyleBist, Ramesh Bahadur, and Lilong Chai. 2022. "Advanced Strategies for Mitigating Particulate Matter Generations in Poultry Houses" Applied Sciences 12, no. 22: 11323. https://doi.org/10.3390/app122211323
APA StyleBist, R. B., & Chai, L. (2022). Advanced Strategies for Mitigating Particulate Matter Generations in Poultry Houses. Applied Sciences, 12(22), 11323. https://doi.org/10.3390/app122211323