Optimized Conditions of Acid Digestion Procedure for Metals Determination in PM2.5 Samples by ICP-OES
Keywords:
PM2.5, acid digestion, trace metals, method validation, ICP-OESAbstract
Background and Objectives : The limitations of chemical analysis in particulate samples for air pollution monitoring are limited sample amount and detection limits of some critical parameters, such as trace metals with low concentrations in the nanogram per milliliter level. This research aims to optimized conditions of acid digestion of particulate matter samples for trace metal determination by using inductively coupled plasma optical emission spectroscopy (ICP-OES).
Methodology : PM2.5 samples were collected during the Yi Peng Festival in 2019 with a high-volume air sampler, at a flow rate of 1000 liters per minute for 24 hours. A total of 7 samples with different concentrations of trace metals were used for optimization study for 5 methods of acid digestion conditions. Different parameters such as sample amount, type and amount of acid, heating methods were selected to obtain the best performance. The method validation was then evaluated for the determination of 11 types of metals, including Ca, Mg, K, Fe, Mn, Zn, Cu, Cr, Cd, Pb and Ni in PM2.5 samples by ICP-OES technique.
Main Results : The most suitable digestion method was found to be as follows : degesting 1 piece of PM2.5 samples with diameter 4.71 centimeter using a mixture of 16.75% hydrochloric acid and 5.55% nitric acid in a volume of 20 milliliters, heating the samples with a test tube heater at 95 degrees Celsius and adjusting to a final volume of 10 milliliters before the measurement. The validation of the analysis for 11 metals showed that the linearity range was between 0.001-10 ppm, with the correlation coefficients (r2) ranging from 0.9981 to 0.9998. The limits of detection (LOD) ranged from 0.015 to 0.154 ppm, and the limits of quantification (LOQ) ranged from 0.031 to 0.323 ppm. The accuracy in terms of percentage recovery (%Recovery) ranged from 80-120%. The precision in terms of relative standard deviation (%RSD) ranged from 2-7%, except for Ca, K, Mg, and Pb.
Conclusions : The optimized conditions of acid digestion can significantly enhance the ability of trace metal determinations in PM2.5 samples by ICP-OES. The method of metal analysis presented in this work would be useful for atmospheric chemistry research, particularly in assessing the sources of pollutants and their health impacts.
References
Chandra, S., Kulshrestha, M.J., Singh, R., & Singh, N. (2017). Chemical characteristics of trace metals in PM10 and their concentrated weighted trajectory analysis at Central Delhi, India. J. Environ. Sci. ,55, 184–196. https://doi.org/10.1016/j. jes.2016.06.028
Chansuebsri, S., Kolar, P., Kraisitnitikul, P., Kantarawilawan, N., Yabueng, N., Wiriya, W., Thepnuan, D., & Chantara, S. (2024). Chemical composition and origins of PM2.5 in Chiang Mai (Thailand) by integrated source apportionment and potential source areas. Atmospheric Environment, 327(March), 120517. https://doi.org/10.1016/j.atmosenv.2024.120517
Jain, S., Sharma, S.K., Mandal, T.K., & Saxena, M., (2018). Source apportionment of PM10 in Delhi, India using PCA/APCS, UNMIX and PMF. Particuology. ,37, 107–118. https://doi.org/10.1016/j.partic.2017.05.009
Kawichai, S., Bootdee, S., & Chantara, S. (2024). Health risk assessments and source apportionment of PM2.5 -bound heavy metals in the initial eastern economic corridor (EEC): A case study of. Atmospheric Pollution Research, 15(9), 102205. https://doi.org/10.1016/j.apr.2024.102205
Kraisitnitikul, P., Thepnuan, D., Chansuebsri, S., Yabueng, N., & Wiriya, W. (2024). Contrasting compositions of PM2.5 in Northern Thailand during La Niña ( 2017 ) and El Niño ( 2019 ). Journal of Environmental Sciences, 135, 585–599. https://doi.org/10.1016/j.jes.2022.09.026
Li, H., Qian, X., Hu, W., Wang, Y., & Gao, H. (2013). Chemical speciation and human health risk of trace metals in urban street dusts from a metropolitan city, Nanjing, SE China. Sci. Total Environ. ,456, 212–221. https://doi.org/10.1016/j.scitotenv.2013.03.094
Pant, P., & Harrison, R.M. (2012). Critical review of receptor modelling for particulate matter: a case study of India. Atmos. Environ. , 49, 1–12. https://doi.org/10.1016/j. atmosenv.2011.11.060
Phairuang, W., Inerb, M., Hata, M., & Furuuchi, M. (2022). Characteristics of trace elements bound to ambient nanoparticles (PM0.1) and a health risk assessment in southern Thailand. Journal of Hazardous Materials, 425, 127986. https://doi.org/10.1016/j.jhazmat.2021.127986
Pongpiachan, S., & Iijima, A. (2016). Assessment of selected metals in the ambient air PM10 in urban sites of Bangkok (Thailand). Environ. Sci. Pollut. Res. , 23 (3), 2948–2961. https://doi.org/10.1007/s11356-015-5877-5.
Qi, L., Zhang, Y., Ma, Y., Chen, M., Ge, X., Ma, Y., Zheng, J., Wang, Z., & Li, Z. (2016). Source identification of trace elements in the atmosphere during the second Asian Youth Games in Nanjing, China: influence of control measures on air quality. Atmos. Pollut. Res., 7 (3), 547–556. https://doi.org/10.1016/j.apr.2016.01.003
Saxena, M., Sharma, A., Sen, A., Saxena, P., Mandal, T.K., Sharma, S.K., & Sharma, C. (2017). Water soluble inorganic species of PM10 and PM2.5 at an urban site of Delhi, India: seasonal variability and sources. Atmos. Res., 184, 112–125. https://doi.org/10.1016/j.atmosres.2016.10.005
Thepnuan, D., & Chantara, S. (2020). Characterization of PM2.5–bound polycyclic aromatic hydrocarbons in Chiang Mai, Thailand during biomass open burning period of 2016. Applied Environmental Research, 42(3), 11–24. https://doi.org/10.35762/AER.2020.42.3.2
Thepnuan, D., Chantara, S., Lee, C. Te, Lin, N. H., & Tsai, Y. I. (2019). Molecular markers for biomass burning associated with the characterization of PM2.5 and component sources during dry season haze episodes in Upper South East Asia. Science of the Total Environment, 658, 708–722. https://doi.org/10.1016/j.scitotenv.2018.12.201
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