کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6971657 | 1453089 | 2014 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Assessing vanadium and arsenic exposure of people living near a petrochemical complex with two-stage dispersion models
ترجمه فارسی عنوان
ارزیابی وانادیوم و آرسنیک در معرض دید مردم در نزدیکی یک مجموعه پتروشیمی با مدل های دو مرحله ای پراکندگی
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
بهداشت و امنیت شیمی
چکیده انگلیسی
The goal of this study is to demonstrate that it is possible to construct a two-stage dispersion model empirically for the purpose of estimating air pollution levels in the vicinity of petrochemical plants. We studied oil refineries and coal-fired power plants in the No. 6 Naphtha Cracking Complex, an area of 2,603-ha situated on the central west coast of Taiwan. The pollutants targeted were vanadium (V) from oil refineries and arsenic (As) from coal-fired power plants. We applied a backward fitting method to determine emission rates of V and As, with 192 PM10 filters originally collected between 2009 and 2012. Our first-stage model estimated emission rates of V and As (median and 95% confidence intervals at 0.0202 (0.0040-0.1063) and 0.1368 (0.0398-0.4782) g/s, respectively. In our second stage model, the predicted zone-average concentrations showed a strong correlation with V, but a poor correlation with As. Our findings show that two-stage dispersion models are relatively precise for estimating V levels at residents' addresses near the petrochemical complex, but they did not work as well for As levels. In conclusion, our model-based approach can be widely used for modeling exposure to air pollution from industrial areas in countries with limited resources.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Hazardous Materials - Volume 271, 30 April 2014, Pages 98-107
Journal: Journal of Hazardous Materials - Volume 271, 30 April 2014, Pages 98-107
نویسندگان
Chia-Pin Chio, Tzu-Hsuen Yuan, Ruei-Hao Shie, Chang-Chuan Chan,