Investigation of the sources and seasonal variations of secondary organic aerosols in PM2.5 in Shanghai with organic tracers

Feng, Jialiang; Li, Man; Zhang, Pan; Gong, S.; Zhong, Mian; Wu, Minghong; Zheng, Mei; Chen, Changhong; Wang, Hongli; Lou, Shengrong

doi:10.1016/j.atmosenv.2013.07.022

Cited by 121 publications

(121 citation statements)

References 49 publications

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“…In BTHA, most of the studies about PM 2.5 have been carried out in Beijing. Most studies have focused on the chemical composition (Ye et al 2003;Duan et al 2014), concentrations (Guo et al 2014), seasonal variations (Han et al 2010;Liu et al 2014;Yun et al 2013), or sources (Zheng et al 2005;Peng et al 2013). Zhao et al (2013) analyzed the characteristics of concentrations and chemical composition of PM 2.5 in the BTHA with the data of four urban monitoring sites (Gu et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Spatial-temporal characteristics and determinants of PM2.5 in the Bohai Rim Urban Agglomeration

2016

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Section: Introductionmentioning

confidence: 99%

Spatial-temporal characteristics and determinants of PM2.5 in the Bohai Rim Urban Agglomeration

2016

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“…Using a radiocarbon-based source apportionment method, the contribution of biomass burning emissions to OC in PM 2.5 was estimated to be 32Á40 % at a regional background site on Hainan Island, South China . During the 2-yr sampling period, the values of WSOC BB /WSOC were lower than those reported in Shanghai (11Á54 %, Feng et al, 2013), PRD region during fall-winter period (42Á47 %, Ding et al, 2013), and urban Beijing in winter and summer (23 % and 16 %, Yan et al, 2015). The underestimation of WSOC BB /WSOC in this study may be partly caused by the higher (LG/WSOC) BB of 17 % than those used in Shanghai (12.5 %) and PRD region (9 %) (Ding et al, 2013;Feng et al, 2013).…”

Section: Contributions Of Biomass Burning Based On Tracer Methods and mentioning

confidence: 51%

“…During the 2-yr sampling period, the values of WSOC BB /WSOC were lower than those reported in Shanghai (11Á54 %, Feng et al, 2013), PRD region during fall-winter period (42Á47 %, Ding et al, 2013), and urban Beijing in winter and summer (23 % and 16 %, Yan et al, 2015). The underestimation of WSOC BB /WSOC in this study may be partly caused by the higher (LG/WSOC) BB of 17 % than those used in Shanghai (12.5 %) and PRD region (9 %) (Ding et al, 2013;Feng et al, 2013). Radiocarbon measurements of WSOC in PM 2.5 at a background site in Yellow Sea in spring with outflow from northern China showed that the non-fossil source fraction (biogenic and biomass burning) to WSOC was estimated to be 30Á50 % (Kirillova et al, 2014).…”

Section: Contributions Of Biomass Burning Based On Tracer Methods and mentioning

confidence: 51%

“…In this study, we used a widely used (LG/OC) BB value of Â8.2 % in the estimation of biomass burning contributions to OC (OC BB ) (Zhang et al, 2008(Zhang et al, , 2012Sang et al, 2011;Mkoma et al, 2013;Ho et al, 2014;Zhu et al, 2015). Besides the (LG/OC) BB ratio, the LG to WSOC ratio (LG/WSOC) BB has also been used to estimate biomass burning derived WSOC (WSOC BB ) (Ding et al, 2013;Feng et al, 2013;Yan et al, 2015). The (LG/WSOC) BB ratio was reported as 9.94 % and 8.06 % for forest fire plume and rice straw residues open burning, respectively (Ding et al, 2008b;Viana et al, 2008).…”

Section: Contributions Of Biomass Burning Based On Tracer Methods and mentioning

confidence: 99%

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Biomass burning contributions to urban PM<sub>2.5</sub> along the coastal lines of southeastern China

Wu¹,

Zhang²,

Schwab³

et al. 2016

Tellus B: Chemical and Physical Meteorology

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A B S T R A C T Levoglucosan (LG), water soluble organic carbon (WSOC) and potassium (K '), and the light absorption at 365 nm (Abs 365 ) of the extracted WSOC are measured in PM 2.5 samples collected from November 2011 to July 2013 at four coastal urban sites in southeast China (Fuzhou, Putian, Quanzhou and Xiamen). These species are markers of biomass burning and used to determine the contributions of biomass burning to the PM 2.5 burden in these locations. LG and WSOC concentrations exhibited a clear seasonal pattern, with a large enhancement in winter and spring and a minimum in summer, and annual means across all sites of 59.2946.8 ng m (3 and 2.6991.21 mg C m (3 , respectively. The distinctive seasonal patterns of LG and WSOC are more explained by the East Asian monsoon than the upwind varying emission sources according to the HYSPLIT backward trajectories and MODIS fire spots. Observations produced significant correlation (at the p B0.01 level) between LG and non-sea salt K ' (nss-K ' ) at each site, but the correlations exhibited no clear seasonal trend. The LG/nss-K ' ratios ranged from 0.0390.01 to 0.2490.13 which lay within the limits for the crop residues and/or grass combustion smoke. Stronger correlations were found between WSOC or Abs 365 and sulphate than between WSOC and LG. This observation is consistent with the fact that biomass burning is a less important contributor to WSOC and/or brown carbon than is secondary organic aerosol formation and oxidation. The average relative contributions of biomass burning to OC and WSOC in PM 2.5 were 8.3 and 15.2 %, respectively, estimated by the measured LG to OC and WSOC (LG/OC and LG/WSOC) ratios in comparison to literature-derived LG/OC and LG/WSOC values for biomass burning smoke. Using the reported conversion factor of LG to PM 2.5 for crop straw burning smoke, the LG-estimated PM 2.5 contributions from biomass burning exhibited minimum values in summer and higher values in winter and spring. Positive Matrix Factorisation was used to analyse PM 2.5 sources, and seven major source factors including biomass burning emissions were resolved. The biomass burning sources contributed 3.75Á8.08 % to PM 2.5 mass as an annual average while exhibiting a seasonal variability similar to and higher than those of LG-estimated contributions. These results demonstrate that the contribution from biomass burning smoke to PM 2.5 Á while small Á is non-negligible, especially in the winter and spring sampling periods, that is, northeastern monsoon season.

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“…7, all of the OC fractions exhibited similar incremental patterns to WSOC in autumn and winter. There are deals of evidence (Feng et al, 2013;Fu and Kawamura, 2011;Kumagai et al, 2010) that the formation of WSOC is closely related to formation of biomass burning. The linkages of OC fractions and WSOC in this study also suggest that the effects of burning biomass need to be considered during autumn to winter.…”

Section: Temporal Variation Of Wsocmentioning

confidence: 99%

Seasonal Variation of PM2.5 Components Observed in an Industrial Area of Chiba Prefecture, Japan

Ichikawa¹,

Naito²,

Ishii³

et al. 2015

Asian J. Atmos. Environ

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In order to survey the seasonal variation of the chemical composition of particulate matter of 2.5 μm or less (PM 2.5 ), PM 2.5 was sampled from 8 February 2013 to 31 March 2014 in an industrial area of Chiba Prefecture, Japan. Chemical measurements of the sample included: ionic components (Na, Cl --, NO 3 --and SO 4 2--), carbonaceous components -organic carbon (OC) and elemental carbon (EC), and water-soluble organic carbon (WSOC). Also, secondary organic carbon (SOC) was measured based using the EC tracer method, and char-EC and soot-EC were calculated from the analytical results. The data obtained were interpreted in terms of temporal variation. Of the overall mean value of PM 2.5 mass concentration obtained during the study period, ionic components, OC and EC accounted for 45.3%, 19.7%, and 8.0%, respectively. NO 3 --showed a unique seasonal distribution pattern due to a dependence on temperature and absolute humidity. It was estimated that an approximate temperature of 14� C, and absolute humidity of 7 g/m 3 were critical for the reversible reaction of NH 4 NO 3 (p) NH 3 (g) + + HNO 3 (g). The amount of OC and EC contributing to the monthly PM 2.5 mass concentration was higher in autumn and winter compared to spring and summer. This result could be attributed to the impact of burning biomass, since WSOC and the ratio of char-EC/ soot-EC showed a similar pattern during the corresponding period. From the comparison of monthly WSOC/OC values, a maximum ratio of 83% was obtained in August (summer). The WSOC and estimated SOC levels derived from the EC tracer method correlated (R=0.77) in summer. The high occurrence of WSOC during summer was mainly due to the formation of SOC by photochemical reactions. Through long-term observation of PM 2.5 chemical components, we established that the degree to which the abovementioned factors influence PM 2.5 composition, fluctuates with seasonal changes.

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Investigation of the sources and seasonal variations of secondary organic aerosols in PM2.5 in Shanghai with organic tracers

Cited by 121 publications

References 49 publications

Spatial-temporal characteristics and determinants of PM2.5 in the Bohai Rim Urban Agglomeration

Spatial-temporal characteristics and determinants of PM2.5 in the Bohai Rim Urban Agglomeration

Biomass burning contributions to urban PM<sub>2.5</sub> along the coastal lines of southeastern China

Seasonal Variation of PM2.5 Components Observed in an Industrial Area of Chiba Prefecture, Japan

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