Investigating the differences between receptor and dispersion modeling for concentration prediction and health risk assessment of volatile organic compounds from petrochemical industrial complexes.

Receptor and dispersion models both provide important information to help understand the emissions of volatile organic compounds (VOCs) and develop effective management strategies. In this study, differences between the predicted concentrations of two models and the associated impacts on the estimated health risks due to different theories behind two models were investigated. Two petrochemical industrial complexes in Kaohsiung city of southern Taiwan were selected as the sites for this comparison. Although the study compares the approaches by applying the methods to this specific area, the results are expected to be adopted for other areas or industries. Ninety-nine VOC concentrations at eight monitoring sites were analyzed, with the effects of diurnal temperature and seasonal humidity variations being considered. The Chemical Mass Balance (CMB) receptor model was used for source apportionment, while the Industrial Source Complex (ISC) dispersion model was used to predict the VOC concentrations at receptor sites. In the results of receptor modeling, 54% ± 11% and 49% ± 20% of the monitored concentrations were contributed by process emissions in two complexes, whereas the numbers increased to 78% ± 41% and 64% ± 44% in the results of dispersion modeling. Significant differences were observed between two model predictions (p < 0.05). The receptor model was more reproducible given the smaller variances of its results. The effect of seasonal humidity variation on two model predictions was not negligible. Similar findings were observed given that the cancer and non-cancer risks estimated by the receptor model were lower but more reproducible. The adverse health risks estimated by the dispersion model exceeded and were 75.3%-132.4% of the values estimated by using the monitored data, whereas the percentages were lowered to the range from 27.4% to 53.8% when the prediction was performed by using the receptor model. As the results of different models could be significantly different and affect the final health risk assessment, it is important to carefully choose an appropriate model for prediction and to evaluate by monitoring to avoid providing false information for appropriate management.

Complete nucleotide sequence and genome organization of a Chinese isolate of Tobacco vein distorting virus.

Tobacco bushy top disease is caused by tobacco bushy top virus (TBTV, a member of the genus Umbravirus) which is dependent on tobacco vein-distorting virus (TVDV) to act as a helper virus encapsidating TBTV and enabling its transmission by aphids. Isometric virions from diseased tobacco plants were purified and disease symptoms were reproduced after experimental aphid transmission. The complete genome of TVDV was determined from cloned RT-PCR products derived from viral RNA. It was 5,920 nucleotides (nts) long and had the six major open reading frames (ORFs) typical of a member of the genus Polerovirus. Sequence comparisons showed that it differed significantly from any of the other species in the genus and this was confirmed by phylogenetic analyses of the RdRp and coat protein. SDS-PAGE analysis of purified virions gave two protein bands of about 26 and 59 kDa both of which reacted strongly in Western blots with antiserum produced to prokaryotically expressed TVDV CP showing that the two forms of the TVDV CP were the only protein components of the capsid.