شبیه سازی اوزون تابستان و میزان حساسیت آنها
ترجمه نشده

شبیه سازی اوزون تابستان و میزان حساسیت آنها

عنوان فارسی مقاله: شبیه سازی اوزون تابستان و میزان حساسیت آنها به تغییرات انتشار در چین
عنوان انگلیسی مقاله: Simulation of summer ozone and its sensitivity to emission changes in China
مجله/کنفرانس: تحقیقات آلودگی هوایی - Atmospheric Pollution Research
رشته های تحصیلی مرتبط: مهندسی محیط زیست
گرایش های تحصیلی مرتبط: آلودگی هوا، آلودگی های محیط زیست
کلمات کلیدی فارسی: اوزون، نقاط هم ارتفاع، حساسیت، CMAQ، چین
کلمات کلیدی انگلیسی: Ozone، Isopleth، Sensitivity، CMAQ، China
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.apr.2019.05.003
دانشگاه: Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge LA, 70803, USA
صفحات مقاله انگلیسی: 10
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 3/269 در سال 2018
شاخص H_index: 29 در سال 2019
شاخص SJR: 0/818 در سال 2018
شناسه ISSN: 1309-1042
شاخص Quartile (چارک): Q1 در سال 2018
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E13034
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

1- Introduction

2- Method

3- Results

4- Conclusion

References

بخشی از مقاله (انگلیسی)

Abstract

Rapid economic growth and associated emission increase in China have led to severe air pollution in recent decades. As fine particulate matter concentration is decreasing due to strict control measures, ozone (O3) concentration has an increasing trend with adverse effects on human health and ecosystems. In this study, the Community Multi-scale Air Quality (CMAQ) model was used to investigate the formation of O3 in China during three high concentration episodes in summer 2013 and analyzed its sensitivity to emission changes. Compared with observation data, O3 performance met the EPA criteria of mean normalized bias (MNB) within ±0.15 in major parts of China including five megacities. The diurnal variation of O3 had similar trend with temperature. The August episode (6–12) had the highest daily maximum 1-h O3 of ∼100 ppb in North China Plain (NCP), while the July episode (11–19) had the lowest concentrations of ∼50 ppb. The O3 production rates (OPR) were higher at NCP and the Yangzi River Delta (YRD), but O3 production efficiencies (OPE) acted in contrary. O3 isopleth showed that NOx controlled O3 concentration in most areas of China. Reducing VOC would have minor effects on O3 concentrations while reducing NOx could largely reduce O3 concentration except for urban areas such as Shanghai and Guangzhou. Linear correlations were observed between secondary organic aerosol (SOA) and Ox (O3+NO2) concentrations in August at Shanghai and Guangzhou, indicating correlations between O3 and other photochemical compounds. This study provides valuable information for designing effective control strategies for O3 in China.

Introduction

Atmospheric pollution has been severe in recent decades in China due to the increase of industries, population, and urbanization. Among different air pollutants, ozone (O3) is secondarily formed in photochemical reactions of nitrogen oxides (NOx) and volatile organic compounds (VOCs) with the existence of sunlight, and it is adverse to human health and ecosystems (WHO, 2006). China started to publish real-time concentration of six criteria pollutants (carbon monoxide, lead, nitrogen dioxide, O3, particulate matter, and sulfur dioxide) from the ambient air quality monitoring networks since 2013 (Sun et al., 2014) after several extreme air pollution events occurred in past 10 years (Guo et al., 2017; Wang et al., 2014b). However, the monitoring system only includes criteria pollutants and the precursors of O3 production such as VOCs, which are important to understand the sources of air pollution and form effective O3 concentration controls, are not measured. The limited information of detailed chemical composition of air pollutants narrows our capability to investigate the formation mechanisms of O3. Also, the majority of observation sites are located in urban areas but suburban and rural regions also have large population and experience high concentrations of air pollutants, especially O3 (Wen et al., 2015).