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Integrated Experimental, Transport, and Risk Modeling Assessment of the Environmental Fate of PM₂.₅ Bound Potentially Toxic Elements (PTEs) from Low-Temperature Thermal Wood Processing


Authors : Appiah, Mark Kubi

Volume/Issue : Volume 11 - 2026, Issue 3 - March


Google Scholar : https://tinyurl.com/mr4ad6hu

Scribd : https://tinyurl.com/yuhjm9mz

DOI : https://doi.org/10.38124/ijisrt/26mar109

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Abstract : Thermal modification of wood at low-level temperatures is increasingly adopted as a sustainable alternative to chemical preservation for improving dimensional stability and durability. However, thermochemical processing of biomass can emit fine particulate matter (PM₂.₅) laden with potentially toxic elements (PTEs), creating significant risks to both environmental health and occupational safety. This study quantified PM₂.₅-bound PTE emissions during lowtemperature thermal wood processing and evaluated their atmospheric transport and health implications. A multi-phase methodology integrated gravimetric PM₂.₅ sampling using PTFE filters, hotplate wet acid digestion, and determining the concentration of the PTEs using an Inductively Coupled Plasma Optical Emission Spectrometer. Ambient occupational PM₂.₅ concentrations were calculated from filter mass differentials and sampled air volumes. A mechanistic Thermo– Particulate Metal Fate and Transport Model (TPM-FTM) was developed to couple thermochemical emission processes, particle–metal partitioning, atmospheric dispersion, deposition, and receptor exposure. Model performance was evaluated using statistical metrics, and uncertainty propagation was assessed through Monte Carlo simulation. Detectable concentrations of PTE-associated PM₂.₅ were observed under low-temperature operational conditions, with size-resolved partitioning influencing atmospheric mobility and inhalation exposure. Occupational environments exhibited higher exposure levels compared with near-field community locations. Evaluations against established regulatory standards confirmed that exposure to these emissions poses no significant carcinogenic or non-carcinogenic health risks, with values generally falling within acceptable limits; localized emission intensities and ventilation conditions increased exposure variability. This study provides an integrated experimental–modeling framework for assessing particulate-bound metal emissions from thermally modified wood processing and offers evidence-based guidance for emission mitigation, occupational safety management, and regulatory evaluation.

Keywords : PM₂.₅; Potentially Toxic Elements (PTEs); Thermal Modification of Wood; ICP-OES; PTFE Filter Sampling; Thermochemical Emissions ; Atmospheric Fate and Transport; Monte Carlo Simulation; Occupational Exposure; Environmental Risk Assessment; TPM-FTM Model.

References :

  1. Abdul Chevidenkandy, A., Bhasi, D., Thayyil, S., & Almarri, A. (2026). Quantification of heavy metals in wastewater: A critical appraisal of sophisticated analytical tools. IntechOpen. https://doi.org/10.5772/intechopen
  2. Alloway, B. J. (2013). Heavy metals in soils: Trace metals and metalloids in soils and their bioavailability (3rd ed.). Springer.
  3. APHA (2017). Standard Methods for the Examination of Water and Wastewater. American Public Health Association, Washington, DC.
  4. Appiah, M. K. (2026). Quantitative Risks Associated with Polycyclic Aromatic Hydrocarbons (PAHs) and Potential Toxic Elements (PTEs) Released from Thermally Modified Wood Processing: A Review. International Journal of Innovative Science and Research Technology, 11(1), 279–303. https://doi.org/10.38124/ijisrt/26jan074
  5. Arrhenius, S. (1889). On the reaction rate of the inversion of cane sugar by acids. Zeitschrift für Physikalische Chemie, 4, 226–248.
  6. Artur J. Badyda, A. J., Widziewicz, K., Rogula-Kozłowska, W., Majewski, G., & Jureczko, I. (2017). Inhalation exposure to PM-bound polycyclic aromatic hydrocarbons released from barbecue grills powered by gas, lump charcoal, and charcoal briquettes. In Air pollution and health effects (pp. xx–xx). Springer. https://doi.org/10.1007
  7. Arya, S. P. (1999). Air Pollution Meteorology and Dispersion. Oxford University Press.
  8. Aydinalp, C., FitzPatrick, E. A., & Cresser, M. S. (2005). Heavy metal pollution in some soil and water resources of Bursa Province, Turkey. Communications in Soil Science and Plant Analysis, 36(1–3), 123–135. https://doi.org/10.1081/CSS
  9. Becker, J. S. (2007). Inorganic Mass Spectrometry: Principles and Applications. John Wiley & Sons.
  10. Bosompemaa, P. (2025). Projecting water availability in semi-arid agricultural regions under future climate scenarios (Doctoral dissertation, University of Kansas).
  11. Boss, C. B., & Fredeen, K. J. (2004). Concepts, instrumentation and techniques in inductively coupled plasma optical emission spectrometry (3rd ed.). PerkinElmer Life and Analytical Sciences.
  12. Bridgwater, A. V. (2012). Review of fast pyrolysis of biomass and product upgrading. Biomass and Bioenergy, 38, 68–94.
  13. Cheng, Y., He, K., Zhang, Q., et al. (2013). Size-resolved source apportionment of urban aerosols in China. Atmospheric Chemistry and Physics, 13(1), 1–17.
  14. Cheng, Y., He, K., Zhang, Q., et al. (2013). Size-resolved source apportionment of urban aerosols in China. Atmospheric Chemistry and Physics, 13(1), 1–17.
  15. Chow, J. C., Watson, J. G., & Lowenthal, D. H. (2005). Filter artifact formation and correction in particulate matter sampling. Atmospheric Environment, 39, 5319–5333.
  16. Conover, W. J. (1999). Practical Nonparametric Statistics. Wiley.
  17. Demirbas, A. (2009). Biomass energy and the influence of moisture content on combustion. Energy Sources, Part A, 31, 113–121.
  18. Devore, J. L. (2012). Probability and Statistics for Engineering and the Sciences. Brooks/Cole.
  19. Esteves, B., & Pereira, H. (2009). Wood modification by heat treatment: A review. BioResources, 4(1), 370–404.
  20. Esteves, B., Domingos, I., Pereira, H., & Candeias, A. (2012). Thermally modified wood: Process and properties. European Journal of Wood and Wood Products, 70, 317–324.
  21. Eurachem (2014). The Fitness for Purpose of Analytical Methods – A Laboratory Guide to Method Validation and Related Topics.
  22. Faulkner, W. B. (2007). Sampler placement to determine emission factors from ground level area sources. Atmospheric Environment, 41(25), 5289–5298. https://doi.org/10.1016/j.atmosenv.2007.02.018
  23. Gamble, J. F., Nicolich, M. J., & Martin, J. (2014). Toxicology and particle exposure assessment. Journal of Toxicology and Environmental Health, 77(3), 107–123.
  24. Ghasemi, A., & Zahediasl, S. (2012). Normality tests for statistical analysis. International Journal of Endocrinology and Metabolism, 10(2), 486–489.
  25. Gifford, F. A. (1961). Use of meteorological data for estimating atmospheric diffusion. Journal of the Air Pollution Control Association, 11(4), 303–306.
  26. Gonzalez-Pena, M., Hale, M., & Boon, J. (2013). Impact of wood orientation on heat penetration and emissions in thermal treatment. Wood Science and Technology, 47, 1015–1030.
  27. Guo, C., Cai, X., Yu, Z., Zhang, Q., Fu, J., Zhu, G., Fu, J., Zhang, H., Yang, X., Liu, Q., & Jiang, G. (2026). Lithium in typical coastal drinking water systems: Occurrence, drivers, and exposure risk. Environment & Health. https://doi.org/10.1016
  28. Hammersley, J. M., & Handscomb, D. C. (1964). Monte Carlo Methods. Methuen.
  29. Hanna, S. R. (1983). Applications in diffusion modeling. Atmospheric Environment, 17(1), 1–21.
  30. Hanna, S. R., Briggs, G. A., & Hosker, R. P. (1982). Handbook on Atmospheric Diffusion. DOE/TIC-11223.
  31. Harris, D. C. (2016). Quantitative chemical analysis (9th ed.). W. H. Freeman and Company.
  32. Harrison, R. M., Jones, A. M., & Lawrence, R. G. (2001). Aerosol Measurement and Chemical Analysis for Health Studies. Atmospheric Environment, 35(30), 5367–5379.
  33. Hass, P., Militz, H., & Höltzer, M. (2010). Thermal treatment of wood: Process optimization and emissions characterization. Holzforschung, 64, 471–478.
  34. Heinrich, U., Fuhst, R., Rittinghausen, S., et al. (2005). Chronic inhalation exposure of rats to diesel engine exhaust: effects on the respiratory system. Inhalation Toxicology, 17(4–5), 235–248.
  35. Helton, J. C., & Davis, F. J. (2003). Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems. Reliability Engineering & System Safety, 81(1), 23–69.
  36. Hill, C. A. S. (2006). Wood Modification: Chemical, Thermal and Other Processes. John Wiley & Sons.
  37. Hinds, W. C. (1999). Aerosol technology: Properties, behavior, and measurement of airborne particles (2nd ed.). Wiley-Interscience.
  38. Holmes, N. S., & Morawska, L. (2006). A review of dispersion modeling and its application to particle size distribution in air quality studies. Atmospheric Environment, 40(30), 527–556.
  39. Hopke, P. K. (2008). Review of receptor modeling methods for source apportionment. Journal of the Air & Waste Management Association, 58(2), 1–18.
  40. Hou, X., & Jones, B. T. (2000). Inductively coupled plasma/optical emission spectrometry. Encyclopedia of Analytical Chemistry. John Wiley & Sons. https://doi.org/10.1002/9780470027318.a1317
  41. Hou, X., & Jones, B. T. (2000). Inductively Coupled Plasma/Optical Emission Spectrometry. Encyclopedia of Analytical Chemistry, John Wiley & Sons.
  42. Hou, X., & Jones, B. T. (2000). Inductively coupled plasma–optical emission spectrometry. Encyclopedia of Analytical Chemistry.
  43. International Labour Organization. (2011). Occupational safety and health management systems: A practical guide. ILO.
  44. International Organization for Standardization (ISO) (1995). ISO 11466: Soil Quality — Extraction of Trace Elements.
  45. International Organization for Standardization (ISO) (2017). ISO/IEC 17025: General Requirements for the Competence of Testing and Calibration Laboratories.
  46. Jain, S., Sharma, S. K., Choudhary, N., & Masiwal, R. (2017). Chemical characteristics and source apportionment of PM2.5 using PCA/APCS, UNMIX, and PMF at an urban site in Delhi. Environmental Science and Pollution Research, 24, 14637–14656.
  47. Jolliffe, I. T., & Cadima, J. (2016). Principal component analysis: A review and recent developments. Philosophical Transactions of the Royal Society A, 374(2065), 20150202. https://doi.org/10.1098/rsta.2015.0202
  48. Kelly, F. J., Fuller, G. W., & Walton, H. A. (2012). Size-fractionated particle sampling and health impact studies. Environmental Health, 11, 59.
  49. Kirkpatrick, A. T. & Kuo, K. K. (2024). Principles of Combustion (3rd ed.). John Wiley & Sons.
  50. Li, N., Sioutas, C., Cho, A., Schmitz, D., Misra, C., Sempf, J., Wang, M., Oberley, T., Froines, J., & Nel, A. (2003). Ultrafine particulate pollutants induce oxidative stress and mitochondrial damage. Environmental Health Perspectives, 111(4), 455–460. https://doi.org/10.1289/ehp.6000
  51. Liu, H., Zhang, Y., & Li, J. (2017). Metal partitioning in size-segregated atmospheric particles. Environmental Pollution, 224, 393–402.
  52. Lu, L. (2025). Characterization of particle-bound reactive oxygen species (ROS) in urban environments (Doctoral dissertation, National University of Singapore).
  53. Marple, V. A., Rubow, K. L., & Behm, S. M. (1991). A Micro-Orifice Uniform Deposit Impactor (MOUDI): Description, Calibration, and Use. Aerosol Science and Technology, 14(4), 434–446.
  54. Marple, V. A., Rubow, K. L., & Behm, S. M. (1991). A Micro-Orifice Uniform Deposit Impactor (MOUDI): Description, Calibration, and Use. Aerosol Science and Technology, 14(4), 434–446.
  55. Militz, H. (2002). Thermal modification of wood: Recent developments in Europe. In Proceedings of the 5th International Wood Quality Workshop, 215–222.
  56. Miller, J. A., Kee, R. J., & Westbrook, C. K. (1990). Chemical kinetics and combustion modeling, Annual Review of Physical Chemistry, 41, 345–387.
  57. Miller, J. N., & Miller, J. C. (2018). Statistics and Chemometrics for Analytical Chemistry. Pearson.
  58. Miller, J. N., & Miller, J. C. (2018). Statistics and chemometrics for analytical chemistry (7th ed.). Pearson.
  59. Montaser, A. (1998). Inductively Coupled Plasma Mass Spectrometry Handbook. CRC Press.
  60. Montgomery, D. C., & Runger, G. C. (2014). Applied Statistics and Probability for Engineers. Wiley.
  61. Moreno, T., Querol, X., Alastuey, A., et al. (2015). Source apportionment of metals in PM2.5 and PM10. Environmental Science & Technology, 49(1), 105–113.
  62. Mundt, C., & Tjeerdsma, B. (2005). Effect of feedstock preparation on thermal wood modification and emissions. Holz als Roh- und Werkstoff, 63, 203–210.
  63. Nash, J. E., & Sutcliffe, J. V. (1970). River flow forecasting through conceptual models: Part I — A discussion of principles. Journal of Hydrology, 10(3), 282–290.
  64. Noble, C. A., Vanderpool, R. W., Peters, T. M., McElroy, F. F., Gemmill, D. B., & Wiener, R. W. (2001). Federal reference and equivalent methods for measuring fine particulate matter. Aerosol Science and Technology, 34(5), 457–464.
  65. Noble, E. (2024). A model for predicting the employability of young adults with traumatic brain injury of moderate severity in South Africa (Doctoral dissertation, University of South Africa).
  66. Oberdörster, G., Oberdörster, E., & Oberdörster, J. (2005). Nanotoxicology: An Emerging Discipline. Environmental Health Perspectives, 113(7), 823–839.
  67. Oliveira, G. S., Pereira, R. G. F. A., & Klammler, H. (2025). Background threshold values for soils and unsaturated zone sediments in the Camaçari industrial complex, Brazil. Environmental Monitoring and Assessment. https://doi.org/10.1007
  68. Pasquill, F. (1961). The estimation of the dispersion of windborne material. Meteorological Magazine, 90, 33–49.
  69. Pio, C., Alves, C., & Faria, T. (2001). Size distribution and chemical composition of urban aerosols. Atmospheric Environment, 35(27), 4593–4603.
  70. Pizzi, A. (2016). Wood Modification and Thermal Treatment for Environmental Applications. Springer.
  71. Querol, X., Alastuey, A., Rodriguez, S., et al. (2001). Speciation and origin of PM10 and PM2.5 in Spain. Journal of Aerosol Science, 32(3), 299–312.
  72. Querol, X., Alastuey, A., Rodriguez, S., et al. (2001). Speciation and origin of PM10 and PM2.5 in Spain. Journal of Aerosol Science, 32(3), 299–312.
  73. Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., & Tarantola, S. (2008). Global sensitivity analysis: The primer. John Wiley & Sons.
  74. Seinfeld, J. H., & Pandis, S. N. (2016). Atmospheric chemistry and physics: From air pollution to climate change (3rd ed.). John Wiley & Sons.
  75. Seinfeld, J. H., & Pandis, S. N. (2016). Atmospheric Chemistry and Physics: From Air Pollution to Climate Change (3rd ed.). Wiley.
  76. Shin, H.-S. (2009). Sensitive analysis of malondialdehyde in human urine by derivatization with pentafluorophenylhydrazine followed by headspace GC–MS. Chromatographia, 70, 1389–1394. https://doi.org/10.1365/s10337-009-1313-5
  77. Skoog, D. A., Holler, F. J., & Crouch, S. R. (2014). Principles of instrumental analysis (6th ed.). Cengage Learning.
  78. Sreelesh, R., Asha Rani, G. V., Sreelash, K., & Maya, K. (2025). Seasonal dynamics, sources, and health risks of trace and heavy metals in the tropical critical zone of the Western Ghats, India. Environmental Geochemistry and Health.
  79. Stull, R. B. (1988). An Introduction to Boundary Layer Meteorology. Springer.
  80. Taylor, J. K. (1987). Quality Assurance of Chemical Measurements. CRC Press.
  81. Thomas, R. (2013). Practical guide to ICP-OES and ICP-MS: A tutorial for beginners (2nd ed.). CRC Press.
  82. Thomas, R., Amrhein, C., & Feng, X. (2012). Application of ICP-OES and ICP-MS for environmental trace metal analysis. Environmental Chemistry Letters, 10(1), 1–14.
  83. Turner, D. B. (1994). Workbook of atmospheric dispersion estimates: An introduction to dispersion modeling (2nd ed.). CRC Press.
  84. Turner, D. B. (1994). Workbook of Atmospheric Dispersion Estimates. CRC Press.
  85. World Meteorological Organization (WMO) (2018). Guide to Meteorological Instruments and Methods of Observation.
  86. Turns, S. R. (2012). An Introduction to Combustion: Concepts and Applications (3rd ed.). McGraw Hill.
  87. U.S. Environmental Protection Agency. (1994). Method 200.7: Determination of metals and trace elements in water and wastes by inductively coupled plasma–atomic emission spectrometry (ICP-AES). EPA.
  88. U.S. Environmental Protection Agency. (2014). Framework for human health risk assessment to inform decision making. EPA.
  89. U.S. Environmental Protection Agency. (2016). 40 CFR Part 50 Appendix L: Reference method for the determination of fine particulate matter (PM2.5) in the atmosphere.
  90. United States Environmental Protection Agency (USEPA) (1996). Method 3050B: Acid Digestion of Sediments, Sludges, and Soils.
  91. United States Environmental Protection Agency (USEPA) (2007). Guidance on Systematic Planning Using the Data Quality Objectives Process.
  92. United States Environmental Protection Agency (USEPA) (2014). Framework for Human Health Risk Assessment to Inform Decision Making.
  93. United States Environmental Protection Agency (USEPA) (2016). 40 CFR Part 50, Appendix L, Reference Method for the Determination of Fine Particulate Matter (PM₂.₅) in the Atmosphere.
  94. United States Environmental Protection Agency (USEPA). (2007). Test methods for evaluating solid waste, physical/chemical methods (SW-846). U.S. Environmental Protection Agency.
  95. United States Environmental Protection Agency (USEPA). (2009). Risk assessment guidance for superfund (RAGS), Volume I: Human health evaluation manual. U.S. Environmental Protection Agency.
  96. United States Environmental Protection Agency. (1994). Method 200.7: Determination of metals and trace elements in water and wastes by ICP-OES. https://www.epa.gov
  97. Venkatram, A., & Wyngaard, J. C. (1988). Lectures on Air Pollution Modeling. Springer.
  98. Warnatz, J., Maas, U., & Dibble, R. W. (2006). Combustion: Physical and Chemical Fundamentals, Modeling and Simulation, Experiments, Pollutant Formation. Springer.
  99. Welz, B., & Sperling, M. (1999). Atomic absorption spectrometry (3rd ed.). Wiley-VCH.
  100. Willmott, C. J., & Matsuura, K. (2005). Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Climate Research, 30(1), 79–82.
  101. World Health Organization (WHO) (2017). Guidelines for Drinking-Water Quality.
  102. World Health Organization (WHO) (2021). WHO Global Air Quality Guidelines.
  103. World Health Organization (WHO). (2013). Health effects of particulate matter: Policy implications for countries in Eastern Europe, Caucasus and Central Asia. WHO Regional Office for Europe.
  104. Zannetti, P. (1990). Air Pollution Modeling: Theories, Computational Methods and Available Software. Van Nostrand Reinhold.
  105. Zhang, Q., Jimenez, J. L., & Canagaratna, M. R. (2016). Atmospheric chemical composition and size-resolved metal distribution. Atmospheric Chemistry and Physics, 16, 6233–6245.
  106. Zhang, Y., Li, Z., & Chen, J. (2021). Trace metal contamination in atmospheric particulate matter. Atmosphere, 12(5), 602. https://doi.org/10.3390/atmos12050602G.

Thermal modification of wood at low-level temperatures is increasingly adopted as a sustainable alternative to chemical preservation for improving dimensional stability and durability. However, thermochemical processing of biomass can emit fine particulate matter (PM₂.₅) laden with potentially toxic elements (PTEs), creating significant risks to both environmental health and occupational safety. This study quantified PM₂.₅-bound PTE emissions during lowtemperature thermal wood processing and evaluated their atmospheric transport and health implications. A multi-phase methodology integrated gravimetric PM₂.₅ sampling using PTFE filters, hotplate wet acid digestion, and determining the concentration of the PTEs using an Inductively Coupled Plasma Optical Emission Spectrometer. Ambient occupational PM₂.₅ concentrations were calculated from filter mass differentials and sampled air volumes. A mechanistic Thermo– Particulate Metal Fate and Transport Model (TPM-FTM) was developed to couple thermochemical emission processes, particle–metal partitioning, atmospheric dispersion, deposition, and receptor exposure. Model performance was evaluated using statistical metrics, and uncertainty propagation was assessed through Monte Carlo simulation. Detectable concentrations of PTE-associated PM₂.₅ were observed under low-temperature operational conditions, with size-resolved partitioning influencing atmospheric mobility and inhalation exposure. Occupational environments exhibited higher exposure levels compared with near-field community locations. Evaluations against established regulatory standards confirmed that exposure to these emissions poses no significant carcinogenic or non-carcinogenic health risks, with values generally falling within acceptable limits; localized emission intensities and ventilation conditions increased exposure variability. This study provides an integrated experimental–modeling framework for assessing particulate-bound metal emissions from thermally modified wood processing and offers evidence-based guidance for emission mitigation, occupational safety management, and regulatory evaluation.

Keywords : PM₂.₅; Potentially Toxic Elements (PTEs); Thermal Modification of Wood; ICP-OES; PTFE Filter Sampling; Thermochemical Emissions ; Atmospheric Fate and Transport; Monte Carlo Simulation; Occupational Exposure; Environmental Risk Assessment; TPM-FTM Model.

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