Rights statement: This document is the Accepted Manuscript version of a Published Work that appeared in final form in Environmental Science and Technology, copyright ©2015 American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see http://pubs.acs.org/doi/abs/10.1021/acs.est.5b00474
Accepted author manuscript, 6.38 MB, PDF document
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Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Environmental distributions of benzo[a]pyrene in China
T2 - current and future emission reduction scenarios explored using a spatially explicit multimedia fate model
AU - Zhu, Ying
AU - Tao, Shu
AU - Price, Oliver R.
AU - Shen, Huizhong
AU - Jones, Kevin C.
AU - Sweetman, Andrew J.
N1 - This document is the Accepted Manuscript version of a Published Work that appeared in final form in Environmental Science and Technology, copyright ©2015 American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see http://pubs.acs.org/doi/abs/10.1021/acs.est.5b00474
PY - 2015/12/1
Y1 - 2015/12/1
N2 - SESAMe v3.0, a spatially explicit multimedia fate model with 50 × 50 km(2) resolution, has been developed for China to predict environmental concentrations of benzo[a]pyrene (BaP) using an atmospheric emission inventory for 2007. Model predictions are compared with environmental monitoring data obtained from an extensive review of the literature. The model performs well in predicting multimedia concentrations and distributions. Predicted concentrations are compared with guideline values; highest values with some exceedances occur mainly in the North China Plain, Mid Inner Mongolia, and parts of three northeast provinces, Xi'an, Shanghai, and south of Jiangsu province, East Sichuan Basin, middle of Guizhou and Guangzhou. Two potential future scenarios have been assessed using SESAMe v3.0 for 2030 as BaP emission is reduced by (1) technological improvement for coal consumption in energy production and industry sectors in Scenario 1 (Sc1) and (2) technological improvement and control of indoor biomass burning for cooking and indoor space heating and prohibition of open burning of biomass in 2030 in Scenario 2 (Sc2). Sc2 is more efficient in reducing the areas with exceedance of guideline values. Use of SESAMe v3.0 provides insights on future research needs and can inform decision making on options for source reduction.
AB - SESAMe v3.0, a spatially explicit multimedia fate model with 50 × 50 km(2) resolution, has been developed for China to predict environmental concentrations of benzo[a]pyrene (BaP) using an atmospheric emission inventory for 2007. Model predictions are compared with environmental monitoring data obtained from an extensive review of the literature. The model performs well in predicting multimedia concentrations and distributions. Predicted concentrations are compared with guideline values; highest values with some exceedances occur mainly in the North China Plain, Mid Inner Mongolia, and parts of three northeast provinces, Xi'an, Shanghai, and south of Jiangsu province, East Sichuan Basin, middle of Guizhou and Guangzhou. Two potential future scenarios have been assessed using SESAMe v3.0 for 2030 as BaP emission is reduced by (1) technological improvement for coal consumption in energy production and industry sectors in Scenario 1 (Sc1) and (2) technological improvement and control of indoor biomass burning for cooking and indoor space heating and prohibition of open burning of biomass in 2030 in Scenario 2 (Sc2). Sc2 is more efficient in reducing the areas with exceedance of guideline values. Use of SESAMe v3.0 provides insights on future research needs and can inform decision making on options for source reduction.
U2 - 10.1021/acs.est.5b00474
DO - 10.1021/acs.est.5b00474
M3 - Journal article
C2 - 25942589
VL - 49
SP - 13868
EP - 13877
JO - Environmental Science and Technology
JF - Environmental Science and Technology
SN - 0013-936X
IS - 23
ER -