TY - JOUR
T1 - Group Contribution Approach To Predict the Refractive Index of Pure Organic Components in Ambient Organic Aerosol
AU - Cai, Chen
AU - Marsh, Aleks
AU - Zhang, Yun-Hong
AU - Reid, Jonathan P
PY - 2017/9/5
Y1 - 2017/9/5
N2 - We introduce and assess a group contribution scheme by which the refractive index (RI) (λ = 589 nm) of non-absorbing components common to secondary organic aerosols can be predicted from molecular formula and chemical functionality. The group contribution method is based on representative values of ratios of the molecular polarizability and molar volume of different functional groups derived from data for a training set of 234 compounds. The training set consists of 106 nonaromatic compounds common to atmospheric aerosols, 64 aromatic compounds and 64 compounds containing halogens; a separate group contribution model is provided for each of these three classes of compound. The resulting predictive model reproduces the RIs of compounds in the training set with mean errors of ±0.58%, ±0.36% and ±0.30% for the non-aromatic, aromatic and halogen containing compounds, respectively. We then evaluate predictions from the group contribution model for compounds with no previously reported RI, comparing values with predictions from previous treatments and with measurements from single aerosol particle experiments. We illustrate how such comparisons can be used to further refine the predictive model. We suggest that the accuracy of this model is already sufficient to better constrain the optical properties of organic aerosol of known composition.
AB - We introduce and assess a group contribution scheme by which the refractive index (RI) (λ = 589 nm) of non-absorbing components common to secondary organic aerosols can be predicted from molecular formula and chemical functionality. The group contribution method is based on representative values of ratios of the molecular polarizability and molar volume of different functional groups derived from data for a training set of 234 compounds. The training set consists of 106 nonaromatic compounds common to atmospheric aerosols, 64 aromatic compounds and 64 compounds containing halogens; a separate group contribution model is provided for each of these three classes of compound. The resulting predictive model reproduces the RIs of compounds in the training set with mean errors of ±0.58%, ±0.36% and ±0.30% for the non-aromatic, aromatic and halogen containing compounds, respectively. We then evaluate predictions from the group contribution model for compounds with no previously reported RI, comparing values with predictions from previous treatments and with measurements from single aerosol particle experiments. We illustrate how such comparisons can be used to further refine the predictive model. We suggest that the accuracy of this model is already sufficient to better constrain the optical properties of organic aerosol of known composition.
UR - http://www.scopus.com/inward/record.url?scp=85028982995&partnerID=8YFLogxK
U2 - 10.1021/acs.est.7b01756
DO - 10.1021/acs.est.7b01756
M3 - Article (Academic Journal)
C2 - 28753320
AN - SCOPUS:85028982995
SN - 0013-936X
VL - 51
SP - 9683
EP - 9690
JO - Environmental Science and Technology
JF - Environmental Science and Technology
IS - 17
ER -