Ventilation and Indoor Environment Control for Animal Health, Welfare, Food safety, and Energy Efficiency Lingying Zhao

Transcription

1 Ventilation and Indoor Environment Control for Animal Health, Welfare, Food safety, and Energy Efficiency Lingying Zhao Associate Professor Air Quality and Bioenvironmental Engineering Lab Department of Food, Agricultural and Biological Engineering The Ohio State University 1

2 Overview Introduction of my overall research areas Example projects related to animal environment and air quality control Application of PIV (particle image velocimetry) airflow measurement technology to measure indoor airflow and evaluate ventilation systems, Wireless sensor network for animal facilities, Measurement and analysis of air quality of and emission from animal facilities. Spray wet scrubber for ammonia recovery at animal facilities, ESP for dust control at animal facilities, Electrostatic scrubber for dust control at animal facilities, and elearning modules and a text book on Controlled Environment Animal Production (eceap) Future research plan 2

3 My major research areas are: Introduction 1.Measurement, modeling and mitigation of air emissions from CAFOs to reduce their health and environmental impacts. 2.Ventilation and indoor environmental quality control to improve animal health, welfare, food safety, and energy efficiency Monitoring of ventilation operation, thermal environment, new alternative environmental control systems, and association of indoor environment with animal health, production, and energy efficiency. 3.Educational curriculum development and research on the effectiveness of elearning in NIFA challenge areas related controlled environment animal production to future workforce competences The animal industry needs a trained workforce with knowledge and technological competency to transform industry challenges into opportunities to make animal production sustainable 3

4 Application of Particle Image Velocimetry (PIV) Technology for Indoor Airflow Measurement, Validation of CFD Models, and Evaluation of Ventilation Systems. 4

5 Schematic of a 2-D PIV system Seed Illuminate Record Process 5

6 Room height (mm) Air velocity vector map mm/s Room width (mm) 6

7 Schematic of a 3-D PIV system Test room Illumination system Glass wall Camera 1 Camera 2 Synchronizer Bubble generator Computer Laser Printer/ Display 7

8 Processed images of particle streaks Photo 1, t 1 =0.5s Photo 2, t 2 =0.25s 8

9 Y(m) Frame Jan D airflow pattern in the z=1.78m (5.84 ft) plane X(m) Z(m) 5 3 9

10 Room height (mm) Evaluation of Ventilation Systems and Validation of CFD models m/s Room width (mm) 10

11 Wireless Sensor Networks for Monitoring Indoor Environment of Animal Facilities Lingying Zhao Matt Darr, Assistant Professor, Iowa State University Hui Li, Graduate Student, OSU Sponsors: Ohio Agricultural Research and Development Center 11

12 Traditional Sensors and Data Acquisition Data may not be synchronized easily The placement of these sensors in large scale and distributed space is a challenge Significant errors can occur due to insufficient measurement density Data Acquisition Sensor Sensor Sensor Sensor Sensor Sensor Sensor Sensor 12

13 New Monitoring Technology Requirements Reduced sampling lines and installation efforts in widely distributed environment Increase data reliability Increase flexibility to add and/or remove sampling nodes when needed. Mass, long-term data storage and real time access to current sensor values. 13

14 Wireless Sensor Networks for Animal Environment Temperature Sensor Data Sink Vibration and Pressure Sensor 14

15 Thermal Risk for Salmonella in Swine By: Julie Funk, DVM, MS, PhD, Michigan State University Lingying Zhao, Ph.D., The Ohio State University Sponsors: USDA: NRI Epidemiologic Approaches for Food Safety 15

16 Instrumentation Layout 16 16

17 Farm 1: Four barns in separate buildings, with cold weather mechanical ventilation for weather and natural ventilation for warm weather ventilation. One building was monitored for two years 17 17

18 Pigs were allocated into 40 pens (20-25 pigs per pen). Dry feeders were shared in every two pens (20 feeders per barn) and Each pen had two nipple waterers

19 Curtain Wall Curtain Wall Exit Door Sensor Layout of Barn P/V S S P/V LEG Sink and Pressur Vibrati Wireles Tempera Node Hobo Te Datalog Vibratio Sensor Box Air 10 9 CO CO 2 XX Carbon Sensor Pen Nu Entrance Door 19

20 Farm 2: Four barns grouped in two double-wide buildings Mechanical ventilation: box inlet winter ventilation and tunnel ventilation for warm weather. Each barn housed approximately 1000 pigs. One barn was monitored for two years

21 12 pens; ten pens were initially stocked with pigs at placement (eight pens with a range of pigs and two pens with a range of pigs). The remaining two pens were used for sick pens Double tube feeders (wet/dry) were located in 8 larger pens and single tube feeders (wet/dry) in 4 smaller pens. Pens were separated by open, metallic gates and a central alley divided the barn

22 Curtain Wall Exit Door 6 P/V S 12 LEGEND Sensor Layout of Barn S P/V Sink and Datalogger Pressure and Fan Vibration Wireless Sensor Node Temperature Wireless Node Hobo Temperature- RH Dataloggers 4 10 Vibration Sensor Box Air Inlets CO 2 CO 2 Carbon Dioxide Sensor 3 9 XX Pen Number Entrance Door 22 22

23 Data Collection and Calculation Two-years of continuous T and RH data at the sampling locations were used to calculate: 1. Hourly average temperature and variations (1d, 2d, 3d, 1wk, 1m); 2. maximum lagged temperature 3. minimum lagged temperature 4. the cumulative degrees and hours below and above the comfort zone temperatures; 5. temperature humidity index (THI); 6. the cumulative degrees and hours above the THI threshold (72) for finishing pigs

24 Thermal Stress Evaluation Lower and Upper Critical Temperatures of Comfort Zone for Finishing Pigs (Harmon and Xin, 1995) Hourly average of Temperature-Humidity Index (THI) was calculate as (Lucas et al, 2000): THI = 0.63Tw +1.17Td +32 Upper Critical THI (UCTHI) value of 72 ( St-Pierre et all 2003) was used to calculate the number of hours and degrees above UCTHI for heat stress 24 evaluation. 24

25 Summer Temperatures 25 25

26 THI in Summer Months 26 26

27 Conclusions The WSN enables intensive and extensive precision monitoring of thermal environments of swine facilities. The wireless mess network has 97% reliability. It will significantly enable precision animal productions and effective management of animal production environment. Preliminary evaluation showed tunnel mechanical ventilation resulted in low air temperature in hot summer month than the natural ventilation system, but the THIs are similar. There are no statistical differences in the feed conversion rate, ADG, mortality rate, treatment rates, and number of subject pigs. Cold exposure (temperatures below the thermal neutral zone) and exposure to a THI > 72 were both positively associated with risk Salmonella shedding. Alternatively, thermal parameters may be used to identify groups of pigs at high risk for Salmonella shedding. 27

28 Measurement of Air Quality of and Emissions from Animal Facilities 28

29 Characterization and Abatement of NH 3, PM, Pathogen and Odor Emissions from Manure-Belt and Composting Layer Production Facilities By: Lingying Zhao, Associate Professor, The Ohio State University Matt Darr and Roderick Manuzon, Research Associates, OSU Dr. Albert Heber, Professor, Purdue University Dr. Ji-Qin Ni, Technical Director, Purdue University Sponsor: USDA NRI air quality program 29

30 A Mobil Air Emission Lab 30

31 Monitoring Plan for Mt. Victory, Ohio S OFIS Pit Pit Barn 1 Barn 2 Cages Thermocouple Air sampling (1-13) Anemometer (SVA) RH/Temp probe Static pressure port TEOM PM monitor F50 F47 F38 F29 F25 F50 F25 F22 F47 F22 Fan number Floor plan (201 m x 21 m) 9 Barn 2 1 Fan stage Instrument shelter Barn Vibration sensor on each fan F13 F13 S F38 13 Activity sensor Wind sensor S Solar sensor F4 F29 F26 F1 F26 Floor plan (201 m x 21 m) F4 F

32 Sampling Probe C 32

33 TEOM Sampling in a Barn C 33

34 Sampling probes, m long Bypass pumping system 9.5 mm OD, 6.4 mm ID Teflon M1 P: pump S: solenoid M: manifold F: filter P1 Vinyl Vinyl 6.4 mm OD 3.2 mm ID vinyl Exhaust Flow dp (+/-) p Analyzers S1 M2 Pressure sensor p Mass flow meter f M3 F F NH 3 H 2 S FTIR P3 C f F Mass flow meter S13 S12 Calibration line 9.5 mm OD, 6.4 mm ID Teflon Gas Sampling System B P2 Flow restrictors 6-port manifold 6-port diluter (5 L/min) CH 4 /NMHC Cal gas circuit Cal gases C 6 H 14 /CH 4 SO H 2 S 2 NH 3 NO CO 2 Zero air 34

35 Air Flow Measurements Fan activity was measured using vibration sensors (left), Fan airflow was indirectly estimated by means of manufacturer fan curve and building pressure measurements, and Fan curves were calibrated using Flow Assessment Numerations System (FANS) (right). Vibration sensors Flow Assessment Numeration System (FANS) 35 35

36 Mitigation of Air Emissions from Animal Facilities 36

37 Wet Scrubbers for Recovering NH 3 Emissions from AFOs for Nitrogen Fertilizer Lingying Zhao Lara Jane Hadlocon, Roderick Manuzon, Yebo Li, and Jon Rausch Department of Food, Agricultural and Biological Engineering, The Ohio State University Jun Zhu Department of Biosystems and Agricultural Engineering, University of Minnesota This project was supported by National Research Initiative Competitive Grant no from the USDA Cooperative State Research, Education, and Extension Service Air Quality Program. 37

38 A Poultry Manure Composting Facility Compost house exhaust streams: NH 3 Concentration: ppm v Air flow Rate: 18,000 m 3 /h per fan Estimated NH 3 Emission: 100 tons/yr A composting house in Ohio processing manure from 4 adjacent manure-belt layer barns housing 828,000 laying hens. 38

39 Acid Spray Scrubbers for Animal Facilities Two full-scale acid spray scrubbers were installed after the exhaust fans of: A deep-pit swine facility A commercial poultry manure compositing facility 39

40 Principles Behind Acid Spray Scrubbers Exhaust Air QG CNH3,out Uses spray nozzles to generate liquid droplets for absorbing NH Gas absorption with chemical reaction Acid & Water Supply Recirculation Dilute sulfuric acid solution is used as scrubbing liquid Overall chemical reaction: NH3-Laden Air QG Liquid Tank CNH3,in Pump 2NH 3 +H 2 SO 4 yields NH 4 2 SO 4 40

41 Scrubber Performance (Summer 2012) 120 Ammonia Concentrations and Collection Efficiencies Poultry Site Scrubber: SU 2012 (07/13/12 to 07/27/12) 500 Inlet NH 3 (ppm v ) Ave: (±44.93) Ammonia (NH 3 ) Collection Efficiency (%) Ammonia Concentration (ppm v ) Outlet NH 3 (ppm v ) Ave: (±20.40) Efficiency (%) Min: Max: 100 Ave: (±18.33) Legend: 07/13/12 07/15/12 07/17/12 07/19/12 07/21/12 07/23/12 07/25/12 07/27/12 Inlet NH 3 Concentration Outlet NH 3 Concentration Run Time Efficiency 41

42 Challenges Significant Challenges Encountered: Freezing during winter operation Pump failure due to acid solution and high pressure liquid flow Nozzle clogging due to dust Solutions developed: Installation of heating tapes prevented line freezing during winter Use of a magnetic drive chemical pump provided reliable and smooth operation. Installation of air filters and appropriately sized water filters Development of ESP low air resistance dust control devices. 42

43 Scrubber Effluent and Commercial Fertilizer Sources:

44 Conclusions A full-scale acid spray scrubber prototype has been developed in lab, scaled-up to a full wet scrubber for poultry operation, and evaluated in a commercial poultry farm for its ammonia absorption performance, operation and maintenance cost. NH 3 scrubbing efficiency varied from 75% to 87% in lab as ammonia concentrations varied from 100 to 400 ppm v. However, in field operation, the efficiency varied from 63% to 80% seasonally. The average scrubber operating conditions were: gal/min liquid flow, psi liquid pressure, and 9.5 Pa pressure drop. A preliminary breakeven economic analysis was conducted. The breakeven point was about 1 year operation (648 tons). A stable wet scrubber operation would result in a net income from production of ammonium fertilizer. 44

45 Electrostatic Precipitation (ESP) for Control of PM emissions from Poultry Barns Roderick Manuzon and Lingying Zhao ASHRAE Graduate In Aid Grant 45

46 Objectives 1. Determine significant parameters affecting ESP collection efficiency of PM and develop an empirical models for predicting ESP performance 2. Determine the optimized conditions for effective ESP design and operation 3. Field test performance of the ESP at poultry layer facilities 46

47 ESP Principles Particulate and Ammonia Laden Gas Flowing In Cleaned Gas Flowing Out Discharge Electrode Insulating Layer Corona and Ionizing Field Collection Electrodes (Plates), Either Wet or Dry 47

48 The ESP Unit Two-stage ESP Module collector 5 kv E-I Characteristic Curve Sparking Limit airflow charger 7-10 kv Table 1. Specifications of the two-stage ESP module. Dimensions (W x H) in cm 40x64 Weight (kg) 2.26 Number of Plates 71 Number of Ionizers 9 Design Ionizer Voltage (Vdc) 8150 Design Collector Voltage (Vdc) 4075 Pressure Drop at 680 m 3 h -1 (Pa) 12.5 Plate Width (cm) 7.6 Collector plate Spacing (cm) 0.36 Charger plate to wire spacing (cm)

49 The Lab Simulation Apparatus PM Sensors Variable Speed Centrifugal Blower Venturi Nozzle Inlet Sample ESP Module Outlet Sample Air Outlet Turntable Dust Feeding System PM Filter PM Filter Air Inlet 49

50 E-v Response Curves KEY OBSERVATIONS: PM Collection Efficiency Increases as voltage (E) is increased and velocity (v) is decreased Above 9kV and below 2.5 m/s, the average collection efficiency was 90% for all particles larger than 1µm in diameter. 50

51 Field Testing of the ESP Airflow Direction (e) Fan (h) Switching Solenoid Valves (g) PLC controls (d)outlet Dustrak (i) Vacuum Cleaner (j) Dust Drain (c) Inlet Dustrak (k) High Voltage Power Supply 51

52 Collection Efficiency (%) PM Concentration (mg/m 3 ) 100 Field Testing of the ESP Efficiency Outlet Inlet /8/12 7/7/12 7/6/12 7/5/12 7/4/12 7/3/12 7/2/12 Run Time (days) 52

53 Conclusions ESP collection efficiency increases with voltage and decreases with air velocity ESP performance declines with time due to the reentrainment of coagulated particles near the collector plates The type of PM affects collection in ESP An optimized operating conditions of the ESP are: 13.6 KV, 1.7 m/s for 90% PM collection efficiency in lab and 82% in field. 53

54 A Preliminary Study of Electrostatic Spray Wet Scrubber for Dust Removal at Animal Facilities Yu Ru, Visiting Scholar Lingying Zhao, Associate Professor Heping Zhu, Adjunct Professor Ramdon Sanjay K, Research Assistant Lara Jane Hadlocon, Post-Doctoral Researcher 54

55 Electrostatic Spray Web Scrubber Operation Electrostatic spray wet scrubber An electrostatically assisted particulate wet scrubber (EPWS) for swine facilities (Almuhanna et al. 2008) Combining advantages of electrostatic precipitators (ESP) and inertial wet scrubbers (WS). (Anatol et al., 2006) enhanced dust capturing using charged droplets high efficiency of small particle removal low cost for electricity and water usage The electrostatic PM cleaning technologies are promising to be both effective and economical for PM control at animal facilities. 55

56 Objectives Develop an lab simulation unit of an electrostatic wet scrubber (ESWS) for PM emissions at and from animal facilities; Test effects of dust concentration, droplet size, droplet charge, and airflow velocity on the ESWS PM removal efficiency; Modeling the PM removal efficiency with the affecting factors for ESWS operation in controlling agricultural dust particles; and Quantify the energy and water consumption of the ESWS operation for a preliminary economic assessment. 56

57 Conclusions Using the lab simulation ESWS unit, the preliminary screened ESWS operating conditions are: charge voltage higher than 7 kv, air velocities of m/s and average droplet size of μm. Correlation analyses shows that superficial air velocity (V) and charged voltage (U) had strong effect on ESWS performance in removal of PM 10. Charged voltage (U) and dust concentration (C 2.5 ) had strong effects on ESWS removal of PM 2.5. The simulation unit achieved a PM Removal efficiency of about 90% with a PM concentration of 5 mg/m 3, a droplet size about 150μm, a charging voltage of 7kV, and an air velocity of 0.5 m/s. Power consumption of the unit was only 21watts. Further optimization studies are needed to fully optimize the design and operating parameters of the ESWS for its application in various animal facilities. 57

58 Create elearning in NIFA Challenge Areas to Transform Education of Controlled Environment Animal Production (eceap) For Sustainability By: Lingying Zhao 1, Xinlei Wang 2, Richard Stowell 3, Lingjuan Wang- Li 4, and Ralph Noble 5 and many other co-pis 1 The Ohio State University 2 University Of Illinois At Champain-Urbana 3 Univeristy of Nebraska-Lincoln 4 North Carolina State University 5 North Carolina A&T State University Sponsors: USDA NIFA Higher Education Challenge Grant 58

59 Objectives Our long term goal is to enable the animal industry to achieve sustainable operations by integrating research and educational efforts in Controlled Environment Animal Production (CEAP). The objectives of this project are to: develop new elearning modules on CEAP (eceap) in the NIFA challenge areas; establish an online platform for educational material exchange and innovative delivery of eceap content; write a digital textbook on eceap for Sustainability, develop and conduct faculty training on the new elearning modules and delivery methods, and develop and offer experiential-learning workshops and internships for underrepresented minority students to stimulate their study and career interests in NIFA challenge areas. 59

60 List of the elearning Module Topics 60

61 Future Works In area 1, the future works will be further development of 1) air emission and dispersion models for typical type of animal feeding operations and 2) hybrid mitigation devices for mitigation of multi-air emissions at animal facilities. In area 2, the future work will be 1) further development of a wireless sensor network for monitoring heat stress in large animal buildings, 2) development of innovative ventilation and cooling systems to abate animal heat stress, and 3) use renewable energy for environmental control of animal buildings. In area 3, with support of a USDA Higher Education Challenge grant, the work will be to create new elearning modules in NIFA challenge areas related controlled environment animal production and conduct research on effects of new digital teaching technologies on student learning In collaboration with peers from four universities. 61

62 Thank You. Questions? 62