Dergiler / Atmospheric Pollution Research / 2019 / Cilt: 10 - Sayı: 4

VOC characteristics and source apportionment at a PAMS site near an industrial complex in central Taiwan

Sayfa
1060–1074
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Actually, seasonal wind directions having only north and north-northwest directions played an important role.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Hourly data of volatile organic compounds (VOCs) were collected for three consecutive years from photochemical assessment monitoring stations (PAMS) in Taixi, Taiwan.
📊
Temel Bulgular & Veri:The VOC concentrations and characteristics were analyzed for temporal variations over a three-year period 2014 to 2016.
💡
Sonuç & Katkı:Actually, seasonal wind directions having only north and north-northwest directions played an important role.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:2014 Verileri
⚙️Değişkenler:Alan Parametreleri

Özet

Hourly data of volatile organic compounds (VOCs) were collected for three consecutive years from photochemical assessment monitoring stations (PAMS) in Taixi, Taiwan. Analysis of the VOC data allows for apportionment of the anthropogenic sources of VOCs. The VOC concentrations and characteristics were analyzed for temporal variations over a three-year period 2014 to 2016. Out of 54 VOCs detected, 21 VOC compounds from 55 to 99% were below the method detection level; others ranged from 100% occurrence (ethane) to 56–61% for trimethylbenzene. In order to have meaningful statistical results, this paper only used results from 33 VOCs where they were detected at least 65% of the time. This was a requirement to be able to determine statistical parameters such as means and standard deviations. The highest VOC average concentrations observed for three consecutive years, in order, for the period were toluene (3.7–4.3 μg m−3 ), then propane (2.5–2.6 μg m−3 ), ethane (2.2–2.5 μg m−3 ), ethylene (1.1–1.5 μg m−3 ) and propylene (0.8–1.1 μg m−3 ). A positive matrix factorization (PMF) receptor model was used to evaluate VOC sources in the area. Six factors were identified by PMF analysis, including solvent use, vehicle exhaust, diesel exhaust, petrochemical, refinery and aged air mass. The conditional probability function indicates that the VOCs in six factors were emitted from their source locations via different wind directions. The contribution of the northwest industrial complex to the PAMS data is linked to the VOCs observed. Actually, seasonal wind directions having only north and north-northwest directions played an important role.

🔖

Bu Makaleye Atıf Yap

CHEN, C., CHUANG, Y., HSİEH, C., LEE, C. (2019). VOC characteristics and source apportionment at a PAMS site near an industrial complex in central Taiwan. Atmospheric Pollution Research, Cilt: 10 - Sayı: 4, 1060–1074. https://ajindex.com/articles/162640

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (10)

  1. Atkinson, R., Arey, J., 2003. Atmospheric degradation of volatile organic compounds. Chem. Rev. 103, 4605–4638.
  2. Baek, J., Hu, Y.T., Odman, M.T., Russell, A.G., 2011. Modeling secondary organic aerosol in CMAQ using multigenerational oxidation of semi-volatile organic compounds. J. Geophys. Res. 116, D22204. https://doi.org/10.1029/2011JD015911.
  3. Baker, A.K., Beyersdorf, A.J., Doezema, L.A., Katzenstein, A., Meinardi, S., Simpson, I.J., Blake, D.R., Rowland, F.S., 2008. Measurements of nonmethane hydrocarbons in 28 United States cities. Atmos. Environ. 42, 170–182.
  4. Batterman, S., Su, F.C., Li, S., Mukherjee, B., Jia, C., 2014. Personal exposure to mixtures of volatile organic compounds: modeling and further analysis of the RIOPA Data. Res. Rep. Health Eff. Inst. 181, 3–63.
  5. Baudic, A., Gros, V., Sauvage, S., Locoge, N., Sanchez, O., Sarda-Estève, R., Kalogridis, C., Petit, J.-E., Bonnaire, N., Baisnée, D., Favez, O., Albinet, A., Sciare, J., Bonsang, B., 2016. Seasonal variability and source apportionment of volatile organic compounds (VOCs) in the Paris megacity (France). Atmos. Chem. Phys. 16, 11961–11989.
  6. Belis, C.A., Karagulian, F., Larsen, B.R., Hopke, P.K., 2013. Critical review and metaanalysis of ambient particulate matter source apportionment using receptor models in Europe. Atmos. Environ. 69, 94–108. Bretón, J.G.C., Bretón, R.M.C., Ucan, F.V., Baeza, C.B., Fuentes, M.D.L.L.E., Lara, E.R., Marrón, M.R., Pacheco, J.A.M., Guzmán, A.R., Chi, M.P.U., 2017. Characterization and sources of aromatic hydrocarbons (BTEX) in the atmosphere of two urban sites located in Yucatan Peninsula in Mexico. Atmosphere 8, 107. https://doi.org/10. 3390/atmos8060107. Brown, S.G., Frankel, A., Hafner, H.R., 2007. Source apportionment of VOCs in the Los Angeles area using positive matrix factorization. Atmos. Environ. 41, 227–237.
  7. Bullock, K.R., Duvall, R.M., Norris, G.A., McDow, S.R., Hays, M.D., 2008. Evaluation of the CMB and PMF models using organic molecular markers in fine particulate matter collected during the Pittsburgh air quality study. Atmos. Environ. 586, 917–928.
  8. Buzcu, B., Fraser, M.P., 2006. Source identification and apportionment of volatile organic compounds in Houston, TX. Atmos. Environ. 40, 2385–2400.
  9. Cai, C., Geng, F., Tie, X., Yu, Q., An, J., 2010. Characteristics and source apportionment of VOCs measured in Shanghai, China. Atmos. Environ. 44, 5005–5014.
  10. Canonaco, F., Crippa, M., Slowik, J.G., Baltensperger, U., Prévôt, A.S.H., 2013. SoFi, an IGOR-ba