Field Testing of Low-Cost PM Sensors in Animal Production Facilities

Yıl 2025, Cilt: 22 Sayı: 3, 732 - 747, 29.09.2025

Seyit Uğuz , Pradeep Kumar , Shalini Tiwari , Young Chang , Xufei Yang

https://doi.org/10.33462/jotaf.1555650

Öz

The measurement of particulate matter (PM) in animal housing environments is crucial for ensuring the health and well-being of both animals and human workers. High concentrations of PM can lead to respiratory issues, reduced productivity, and compromised animal welfare. The affordability and compact design of low-cost PM sensors present an opportunity to enhance spatiotemporal resolution in PM measurements. However, these low-cost sensors have certain limitations and require characterization in dusty environments such as animal production facilities. This study examines eight low-cost PM sensors (PMS5003, PMS7003, OPC-R2, OPC-N3, Gravity, SDS011, GP2Y1010, and PPD42) for their performance in monitoring PM1, PM2.5, and PM10 concentrations in animal houses. It details sensor components, hardware integration, and field deployment, along with preliminary testing in farm office and production room environments. A GRIMM 11-D aerosol spectrometer was used as the reference monitor. The OPC-N3 sensor showed high linearity against the reference monitor in the office, with R2 values higher than 0.97, but this correlation dropped to 0.40-0.59 in the production room due to increased particle concentration affecting sensor sensitivity. Meanwhile, the PMS7003 sensor excelled in PM1 measurements with an R² value of 0.90, performing well in production settings, in contrast to its performance in the office. The SDS011 sensor also demonstrated good performance in production environments. Preliminary results suggest that while these sensors effectively measure PM levels under certain conditions, their performance varies significantly depending on environmental factors such as dust concentration, temperature, and relative humidity. The necessity for rigorous field testing and calibration is emphasized to enhance the reliability and accuracy of these sensors in monitoring indoor air quality in agricultural settings. Further research and field testing are essential to validate sensor performance and ensure their effectiveness across diverse environmental conditions.

Anahtar Kelimeler

Particulate matter , Low-cost sensors , Air quality , Animal houses , Measurement

Etik Beyan

There is no need to obtain permission from the ethics committee for this study.

Destekleyen Kurum

This work is supported by the Foundation for Food and Agriculture Research (Award No. 22-000286), the United States. The efforts of Dr. Uguz were sponsored by The Scientific and Technological Research Council of Türkiye (TUBITAK).

Proje Numarası

22-000286

Düşük Maliyetli PM Sensörlerinin Hayvansal Üretim Tesislerinde Test Edilmesi

Öz

Hayvan barınakları iç ortamında partikül maddelerin (PM) izlenmesi hem barındırılan hayvanların hem de çiftlik çalışanlarının sağlık ve refahının sağlanması için oldukça önemlidir. Yüksek düzeyde organic partiküllere ve kirletici gazlara maruz kalan çiftlik çalışanları, yaşlandıkça solunum yolu hastalıklarına daha duyarlı hale gelmektedirler. Düşük maliyetli sensörlerin ekonomikliği ve kompakt tasarımı, PM ölçümlerinde uzamsal-zamansal çözünürlüğü artırmak için bir fırsat sunmaktadır. Bu çalışmada, hayvan barınaklarından salınan PM1, PM2.5 ve PM10 konsantrasyonlarının izlenmesi için düşük maliyetli PM sensörlerinin geliştirilmesi ve geliştirilen sistemin ön denemelerinin yapılması amaçlanmıştır. Çalışmada, düşük maliyetli 8 adet PM sensörlerinin (PMS5003, PMS7003, OPC-R2, OPC-N3, Gravity, SDS011, GP2Y1010, PPD42) donanım, sensör bileşenleri ve kurulum süreçlerinin yanı sıra hayvansal üretim tesislerinde ofis ve barınak ortamında ön testleri ve referans PM ölçer ile karşılaştırması yapılmıştır. OPC-N3 sensörü, ofis ortamında referans monitörle yüksek korelasyon göstermiştir (0.97-0.98) ancak bu korelasyon barınak iç ortamında 0.40-0.59 değerlerine düşmüştür. Bunun sebebi ise barınak iç ortamında artan partikül konsantrasyonlarının sensor hassasiyetini etkilediği düşünülmektedir. Bu arada PMS7003 sensörü PM1 ölçümlerinde yüksek korelasyon değeri ile (R²: 0.90) ile ofis ortamının aksine barınak iç ortamında daha iyi bir performans göstermiştir. SDS011 sensörü de barınak iç ortamında daha iyi performans göstermiştir. Ön sonuçlar, bu sensörlerin belirli çevre koşulları altında PM seviyelerini etkili bir şekilde ölçerken, performanslarının toz, sıcaklık ve bağıl nem gibi çevresel faktörlere bağlı olarak önemli ölçüde değiştiğini göstermektedir. Hayvansal üretim yapılarında iç mekân hava kalitesinin izlenmesinde bu sensörlerin güvenilirliğini ve doğruluğunu artırmak için detaylı saha testleri ve kalibrasyonunun gerekliliği vurgulanmaktadır. Düşük maliyetli PM sensörlerinin performansının doğrulanması ve farklı çevresel koşullarda etkinliklerinin arttırılması için daha fazla araştırma ve saha testi yapılması gerekmektedir.

Anahtar Kelimeler

Partiküler madde , Düşük maliyetli sensör , Hava kalitesi , Hayvan barınakları , Ölçme

Etik Beyan

Bu çalışma için etik kuruldan izin alınmasına gerek yoktur.

Destekleyen Kurum

This work is supported by the Foundation for Food and Agriculture Research (Award No. 22-000286), the United States. The efforts of Dr. Uguz were sponsored by The Scientific and Technological Research Council of Türkiye (TUBITAK).

Proje Numarası

22-000286

Kaynakça

• Afroz, R., Guo, X., Cheng, C. W., Omar, S., Carney, V. L., Zuidhof, M. J. and Zhao, R. (2024). Assessments and application of low-cost sensors to study indoor air quality in layer facilities. Environmental Technology & Innovation, 36: 103773.
• Arulmozhi, E., Bhujel, A., Deb, N. C., Tamrakar, N., Kang, M. Y., Kook, J., Kang, D. Y., Seo, E. W. and Kim, H. T. (2024). Development and Validation of Low-Cost Indoor Air Quality Monitoring System for Swine Buildings. Sensors, 24(11): 3468.
• Badura, M., Batog, P., Drzeniecka-Osiadacz, A. and Modzel, P. (2019). Regression methods in the calibration of low-cost sensors for ambient particulate matter measurements. Discover Applied Sciences, 1(6): 622.
• Bist, R. B. and Chai, L. (2022). Advanced strategies for mitigating particulate matter generations in poultry houses. Applied Sciences, 12(22): 11323.
• Bulot, F. M. J., Russell, H. S., Rezaei, M., Johnson, M. S., Ossont, S. J., Morris, A. K. R., Basford, P. J., Easton, N. H. C., Mitchell, H. L., Foster, G. L., Loxam, M. and Cox, S. J. (2023). Laboratory comparison of low-cost particulate matter sensors to measure transient events of pollution—part B—particle number concentrations. Sensors, 23(17): 7657.
• Cambra-López, M., Hermosilla, T., Lai, H. T., Aarnink, A. J. A. and Ogink, N. W. M. (2011). Particulate matter emitted from poultry and pig houses: source identification and quantification. Transactions of the ASABE, 54(2): 629-642.
• Correia, C., Martins, V., Matroca, B., Santana, P., Mariano, P., Almeida, A. and Almeida, S. M. (2023). A low-cost sensor system installed in buses to monitor air quality in cities. International Journal of Environmental Research and Public Health, 20(5): 4073.
• Crilley, L. R., Shaw, M., Pound, R., Kramer, L. J., Price, R., Young, S., Lewis, A. C. and Pope, F. D. (2018). Evaluation of a low-cost optical particle counter (Alphasense OPC-N2) for ambient air monitoring. Atmospheric Measurement Techniques, 11(2): 709-720.
• Delgado, L., Feliciano, M., Frare, L., Furst, L., Leitão, P. and Igrejas, G. (2020). Construction and Validation of a Low-Cost System for Indoor Air Quality Measurements in Livestock Facilities. Sustainable Energy for Smart Cities: First EAI International Conference, 4–6 December 2019, pp. 232-245, Braga, Portugal.
• Dobson, R., O’Donnell, R., McGibbon, M. and Semple, S. (2023). Second-hand smoke exposure among home care workers (HCWs) in Scotland. Annals of Work Exposures and Health, 67(2): 208-215.
• Dubey, R., Patra, A. K., Joshi, J., Blankenberg, D., Kolluru, S. S. R., Madhu, B. and Raval, S. (2022). Evaluation of low-cost particulate matter sensors OPC N2 and PM Nova for aerosol monitoring. Atmospheric Pollution Research, 13(3): 101335.
• Fernández, A. P., Demmers, T., Tong, Q., Youssef, A., Norton, T. and Berckmans, D. (2018). Real-time monitoring of indoor particulate matter concentration in a commercial broiler house. 10th International Livestock Environment Symposium (ILES X). 25-27 September, Omaha, Nebraska, U.S.A.
• Gao, M., Cao, J. and Seto, E. (2015). A distributed network of low-cost continuous reading sensors to measure spatiotemporal variations of PM2.5 in Xi'an, China. Environmental Pollution, 199: 56-65.
• Ghamari, M., Soltanpur, C., Rangel, P., Groves, W. A. and Kecojevic, V. (2022). Laboratory and field evaluation of three low‐cost particulate matter sensors. IET Wireless Sensor Systems, 12(1): 21-32.
• Guo, L., Zhao, B., Jia, Y., He, F. and Chen, W. (2022). Mitigation strategies of air pollutants for mechanical ventilated livestock and poultry housing—A review. Atmosphere, 13(3): 452.
• Holstius, D. M., Pillarisetti, A., Smith, K. R. and Seto, E. (2014). Field calibrations of a low-cost aerosol sensor at a regulatory monitoring site in California. Atmospheric Measurement Techniques, 7(4): 1121-1131.
• Hoque, M., Kabir, H. and Jony, M. H. (2018). Design and construction of a bowden extruder for a FDM 3D Printer Uses 1.75 Mm filament. International Journal of Technical Research & Science, 3: 282-288.
• Huang, J., Kwan, M. P., Cai, J., Song, W., Yu, C., Kan, Z. and Yim, S. H. L. (2022). Field evaluation and calibration of low-cost air pollution sensors for environmental exposure research. Sensors, 22(6): 2381.
• Jayaratne, R., Liu, X., Thai, P., Dunbabin, M. and Morawska, L. (2018). The influence of humidity on the performance of a low-cost air particle mass sensor and the effect of atmospheric fog. Atmospheric Measurement Techniques, 11(8): 4883-4890.
• Johnson, K. K., Bergin, M. H., Russell, A. G., and Hagler, G. S. (2018). Field test of several low-cost particulate matter sensors in high and low concentration urban environments. Aerosol and Air Quality Research, 18(3): 565.
• Kobziar, L. N., Pingree, M. R., Watts, A. C., Nelson, K. N., Dreaden, T. J. and Ridout, M. (2019). Accessing the life in smoke: a new application of unmanned aircraft systems (UAS) to sample wildland fire bioaerosol emissions and their environment. Fire, 2(4): 56.
• Kortoçi, P., Motlagh, N. H., Zaidan, M. A., Fung, P. L., Varjonen, S., Rebeiro-Hargrave, A., Niemi, J. V., Nurmi, P., Hussein, T., Petaja, T., Kulmala, M. and Tarkoma, S. (2022). Air pollution exposure monitoring using portable low-cost air quality sensors. Smart Health, 23: 100241.
• Laltrello, S., Amiri, A. and Lee, S. H. (2022). Indoor particulate matters measured in residential homes in the Southeastern United States: Effects of pandemic lockdown and holiday cooking. Aerosol and Air Quality Research, 22(5): 210302
• Li, J., Li, H., Ma, Y., Wang, Y., Abokifa, A. A., Lu, C. and Biswas, P. (2018). Spatiotemporal distribution of indoor particulate matter concentration with a low-cost sensor network. Building and Environment, 127: 138-147.
• Liu, H. Y., Schneider, P., Haugen, R. and Vogt, M. (2019). Performance assessment of a low-cost PM2. 5 sensor for a near four-month period in Oslo, Norway. Atmosphere, 10(2): 41.
• Lovanh, N., Loughrin, J. and Silva, P. (2016). The effect of aged litter materials on polyatomic ion concentrations in fractionated suspended particulate matter from a broiler house. Journal of the Air & Waste Management Association, 66(7): 707-714.
• Lowther, S. D., Jones, K. C., Wang, X., Whyatt, J. D., Wild, O. and Booker, D. (2019). Particulate matter measurement indoors: a review of metrics, sensors, needs, and applications. Environmental Science & Technology, 53(20): 11644-11656.
• Macías-Hernández, B. A., Tello-Leal, E., Barrios, O., Leiva-Guzmán, M. A. and Toro, R. (2023). Effect of environmental conditions on the performance of a low-cost atmospheric particulate matter sensor. Urban Climate, 52: 101753.
• Magi, B. I., Cupini, C., Francis, J., Green, M., and Hauser, C. (2020). Evaluation of PM2. 5 measured in an urban setting using a low-cost optical particle counter and a Federal Equivalent Method Beta Attenuation Monitor. Aerosol Science and Technology, 54(2): 147-159.
• Mahajan, S., and Kumar, P. (2020). Evaluation of low-cost sensors for quantitative personal exposure monitoring. Sustainable Cities and Society, 57: 102076.
• Manikonda, A., Zíková, N., Hopke, P. K. and Ferro, A. R. (2016). Laboratory assessment of low-cost PM monitors. Journal of Aerosol Science, 102: 29-40.
• Mei, H., Han, P., Wang, Y., Zeng, N., Liu, D., Cai, Q., Deng, Z., Wang, Y., Pan, Y., and Tang, X. (2020). Field evaluation of low-cost particulate matter sensors in Beijing. Sensors, 20(16): 4381.
• Ouimette, J., Arnott, W. P., Laven, P., Whitwell, R., Radhakrishnan, N., Dhaniyala, S., Sandink, M., Tryner, J. and Volckens, J. (2024). Fundamentals of low-cost aerosol sensor design and operation. Aerosol Science and Technology, 58(1): 1-15.
• Raheja, G., Nimo, J., Appoh, E. K., Essien, B., Sunu, M., Nyante, J., Amegah, M., Quansah, R., Arku, R. E., Penn, S. L., Giordano, M. R., Zheng, Z., Jack, D., Chillrud, S., Amegah, K., Subramanian, R., Pinder, R., Appah-Sampong, E., Tetteh, E. N., Borketey, M. A., Hughes, A. F. and Westervelt, D. M. (2023). Low-cost sensor performance intercomparison, correction factor development, and 2+ years of ambient pm2.5 monitoring in Accra, Ghana. Environmental Science & Technology, 57(29): 10708-10720.
• Samad, A., Melchor Mimiaga, F. E. Laquai, B., and Vogt, U. (2021). Investigating a low-cost dryer designed for low-cost PM sensors measuring ambient air quality. Sensors, 21(3): 804.
• Sayahi, T., Butterfield, A. and Kelly, K. E. (2019). Long-term field evaluation of the Plantower PMS low-cost particulate matter sensors. Environmental Pollution, 245: 932-940.
• Shen, D., Wu, S., Dai, P. Y., Li, Y. S. and Li, C. M. (2018). Distribution of particulate matter and ammonia and physicochemical properties of fine particulate matter in a layer house. Poultry Science, 97(12): 4137-4149.
• Silva, P. J., Cress, T., Drover, R., Michael, C., Docekal, G., Larkin, P., Godoy, A., Cavero, D. A., Sin, C., Waites, J., Mahmood, R., Cohron, M. and Purvis-Roberts, K. L. (2023). Characterization of particle size distributions and water-soluble ions in particulate matter measured at a broiler farm. Agriculture, 13(7), 1284.
• Singh, N., Elsayed, M. Y., and El-Gamal, M. N. (2022). Towards the world’s smallest gravimetric particulate matter sensor: A miniaturized virtual impactor with a folded design. Sensors, 22(5): 1727.
• Soms, J. and Soms, H. (2021). Application of Low-Cost Optical PM Sensor for Monitoring of Particulate Matter Air Pollution in the Urban Environment: A Case Study in Esplanāde Housing Estate, Daugavpils City. 13th International Scientific and Practical Conference, pp. 223-229, 17-18 June, Rēzekne, Latvia.
• Sousan, S., Regmi, S. and Park, Y. M. (2021). Laboratory evaluation of low-cost optical particle counters for environmental and occupational exposures. Sensors, 21(12): 4146.
• Tsameret, S., Furuta, D., Saha, P., Kwak, N., Hauryliuk, A., Li, X., Presto, A. A. and Li, J. (2024). Low-Cost indoor sensor deployment for predicting PM2. 5 exposure. ACS ES&T Air, 1(8): 767-779.
• Wang, Y., Li, J., Jing, H., Zhang, Q., Jiang, J. and Biswas, P. (2015). Laboratory evaluation and calibration of three low-cost particle sensors for particulate matter measurement. Aerosol Science and Technology, 49(11): 1063-1077.
• Yang, X., Haleem, N., Osabutey, A., Cen, Z., Albert, K. L. and Autenrieth, D. (2022). Particulate matter in swine barns: A comprehensive review. Atmosphere, 13(3): 490.
• Yasmeen, R., Ali, Z., Tyrrel, S. and Nasir, Z. A. (2019). Estimation of particulate matter and gaseous concentrations using low-cost sensors from broiler houses. Environmental Monitoring and Assessment, 191: 1-10.
• Zhang, S., Zhou, L., Jia, L., Li, J., Liu, B. and Yuan, Y. (2022). Numerical simulation on particulate matter emissions from a layer house during summer in northeast china. Atmosphere, 13(3): 435.
• Zheng, T., Bergin, M. H., Johnson, K. K., Tripathi, S. N., Shirodkar, S., Landis, M. S., Sutaria, R., and Carlson, D. E. (2018). Field evaluation of low-cost particulate matter sensors in high-and low-concentration environments. Atmospheric Measurement Techniques, 11(8), 4823-4846.