Chemical characterization and source apportionment of PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; in Beijing: seasonal perspective

Zhang, Renjian; Jing, Jiwu; Tao, Jun; Hsu, Shih Chieh; Wang, Gehui; Cao, Jun; Lee, C. S. L.; Zhu, Lailai; Chen, Z.; Zhao, Yibing

doi:10.5194/acpd-13-9953-2013

Cited by 96 publications

(123 citation statements)

References 118 publications

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“…The air quality in this region dramatically changed because of the emissions of air pollutants coupled with CO 2 from house heating, traffic and industrial activities (Zhao et al, 2012;Chan and Yao, 2008). Studies on the air quality in Beijing have focused on the physicochemical properties and sources of atmospheric pollutants (Gao et al, 2014, Guo et al, 2012Zhang et al, 2013;Zhao et al, 2013), temporal and spatial distribution characteristics Schleicher et al, 2013;Zhao et al, 2009), and formation and evolution mechanisms Liu et al, 2013;Zhao et al, 2013). Some studies have paid attention to the isotopic composition of water vapor and precipitation in Beijing (Wen et al, 2012(Wen et al, , 2010(Wen et al, , 2008 and the hydrochemical and isotopic characteristics of atmospheric precipitation (Zhai et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Mixing ratio and carbon isotopic composition investigation of atmospheric CO 2 in Beijing, China

Pang

Wen

Sun

2016

Science of The Total Environment

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• Continuous measurement of atmospheric CO 2 and δ 13 C in Beijing. • δ 13 C depleted in heating season and enriched in vegetative season.• Diurnal variation of δ 13 C showed two peaks in heating season.• Coal combustion was the main local CO 2 source. • δ 13 C showed significant liner relationship with air quality index (AQI). G R A P H I C A L A B S T R A C Ta b s t r a c t a r t i c l e i n f o The stable isotope composition of atmospheric CO 2 can be used as a tracer in the study of urban carbon cycles, which are affected by anthropogenic and biogenic CO 2 components. Continuous measurements of the mixing ratio and δ 13 C of atmospheric CO 2 were conducted in Beijing from Nov. 15, 2012 to Mar. 8, 2014 including two heating seasons and a vegetative season. Both δ 13 C and the isotopic composition of source CO 2 (δ 13 C S ) were depleted in the heating seasons and enriched in the vegetative season. The diurnal variations in the CO 2 mixing ratio and δ 13 C contained two peaks in the heating season, which are due to the effects of morning rush hour traffic. Seasonal and diurnal patterns of the CO 2 mixing ratio and δ 13 C were affected by anthropogenic emissions and biogenic activity. Assuming that the primary CO 2 sources at night (22:00-04:00) were coal and natural gas combustion during heating seasons I and II, an isotopic mass balance analysis indicated that coal combustion had average contributions of 83.83 ± 14.11% and 86.84 ± 12.27% and that natural gas had average contributions of 16.17 ± 14.11% and 13.16 ± 12.27%, respectively. The δ 13 C of background CO 2 in air was the main error source in the isotopic mass balance model. Both the mixing ratio and δ 13 C of atmospheric CO 2 had significant linear relationships with the air quality index (AQI) and can be used to indicate local air pollution conditions. Energy structure optimization, for example, reducing coal consumption, will improve the local air conditions in Beijing.

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Section: Introductionmentioning

confidence: 99%

Mixing ratio and carbon isotopic composition investigation of atmospheric CO 2 in Beijing, China

Pang

Wen

Sun

2016

Science of The Total Environment

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“…중국에서 PM 2.5 질량농도 측정은 주로 tapered element oscillating microbalance (TEOM) 방법 또는 beta- Many monitoring sites are overlaid in this map (Ma et al, 2014 mass balance) 모델과 PMF (positive matrix factorization) 모델이 활용되고 있다 Gao et al, 2013;Wang et al, 2013b;Yu et al, 2013;Zhang et al, 2013b). Chen et al, 2011), log-linear 모델 (Huang et al, 2012b;Huang et al, 2009), lag non-linear 모델 (Geng et al, 2013), generalized additive model (GAM) (Dai et al, 2004)을 이용하며 시간-층화된 (time-stratified) 환자교 차 (case-crossover) 연구방법도 제안되었다 (Yang et al, 2012;.…”

Section: 연구기법unclassified

“…관측과 모델링 연구와 더불어 베이징, 상하이 (Shanghai) 및 광저우 (Guangzhou) 등지에서 PM 2.5 의 배출원 기여도를 산정하는 연구 Gao et al, 2013;Wang et al, 2013b;Yu et al, 2013;Zhang et al, 2013b)를 통해 그 원인을 규명하려고 노력하고 있다.…”

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Review on the Recent PM<sub>2.5</sub> Studies in China

Kim¹,

Kim²,

Lee³

et al. 2015

Journal of Korean Society for Atmospheric Environment

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“…작용 때문에 오래전부터 많은 관심을 가져왔다 (Sun et al, 2014;Tian et al, 2014;Park et al, 2013a;Zhang et al, 2013;Duan et al, 2012;Tan et al, 2009;Kang et al, 2004 (Park et al, 2013a;Won et al, 2010;Park et al, 2005), SO 4 2-입자는 주로 광역적 오염원의 장거리 이동 중 SO 2 의 대기변환과정을 통하여 생성되 며 여름에 발생하는 PM 2.5 의 고농도 현상의 원인물질 이 된다 (Won et al, 2010). 관련이 있다고 하였다 (Zhang et al, 2013;Duan et al, 2012;Okuda et al, 2004).…”

Section: 연무 오염은 인간의 건강 시정 지구 기후에 대한 부unclassified

“…관련이 있다고 하였다 (Zhang et al, 2013;Duan et al, 2012;Okuda et al, 2004). 따라서 국내에서 대기 중의 (Park et al, 2013a;Park and Cho, 2011 Yu et al, 2015).…”

Section: 연무 오염은 인간의 건강 시정 지구 기후에 대한 부unclassified

Investigation of PM<sub>2.5</sub> Pollution Episodes in Gwangju

Yu¹,

Cho²,

Bae³

et al. 2015

Journal of Korean Society for Atmospheric Environment

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Abstract24-hr integrated PM 2.5 measurements were performed between December 2013 and October 2014 at an urban site in Gwangju and the collected samples were analyzed for organic carbon (OC), elemental carbon (EC), ionic species, and elemental species. Objectives of this study were to identify PM 2.5 pollution episodes, to characterize their chemical components, and to examine their probable origins. Over the course of the study period, average PM 2.5 concentration was 37.7±23.6 (6.0~121.5) μg/m 3 . Concentrations of secondary ionic species; NH 4 + , NO 3 -, and SO 4 2-was on average 5.54 μg/m 3 (0.28~20.86), 7.60 μg/m 3 (0.45~33.53), and 9.05 μg/m 3 (0.50~34.98), accounting for 13.7% (4.6~22.7), 18.6% (2.9~44.8), and 22.9% (4.9~55.1) of the PM 2.5 concentration, respectively. Average OC and EC concentrations were 5.22 μgC/m 3 and 1.54 μgC/m 3 , taking possession of 4.6 and 22.2% (as organic mass) of the PM 2.5 , respectively. Frequencies at which 24-hr averaged PM 2.5 exceeded a 24-hr averaged Korean PM 2.5 standard of 50 μg/m 3 (termed as an "episode" in this study) were 30, accounting for 21.3% of total 141 measurements. These pollution episodes were mostly associated with haze phenomenon and weak surface wind speed. It is suggested that secondary formation of aerosol was one important formation mechanism of the episodes. The episodes were associated with enhancements of organic mass, NO 3 -and SO 4 2-in winter, of NO 3 -and SO 4 2-in spring, and of SO 4 2-in summer. Potential source contribution function results indicate also that PM 2.5 episodes were likely attributed to local and regional haze pollution transported from northeastern China in winter, to atmospheric processing of local emissions rather than long-range transport of air pollutants in spring, and to the SO 4 2-driven by photochemistry of SO 2 in summer.

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Chemical characterization and source apportionment of PM<sub>2.5</sub> in Beijing: seasonal perspective

Cited by 96 publications

References 118 publications

Mixing ratio and carbon isotopic composition investigation of atmospheric CO 2 in Beijing, China

Mixing ratio and carbon isotopic composition investigation of atmospheric CO 2 in Beijing, China

Review on the Recent PM<sub>2.5</sub> Studies in China

Investigation of PM<sub>2.5</sub> Pollution Episodes in Gwangju

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