[Characteristics and Source Apportionment of VOCs of High Pollution Process at Chemical Industrial Area in Winter of China].

Online GC was adopted to monitor VOCs of high pollution process near a chemical industrial area in winter. PMF model was used to identify the major sources of VOCs and evaluate their contributions. The result showed that the main components during the period of observation were toluene, xylene, C3-C4 hydrocarbon and chloroform, etc. Organic sulfur compounds were the major odor pollutants at the chemical industrial area. The compounds including isobutane, n-butane, propane and acrylonitrile were enriched during two pollution periods. VOCs and NOx had the diurnal features of high concentration in the evening versus lower concentration during daytime, indicating the main influence from chemical industrial sources. While O3 had the diurnal features reflecting the photochemical reaction at chemical industrial area in winter. The PMF result showed that 48.0% of the total VOCs concentrations were attributed to synthetic materials industry, 24.0% to industrial organic sulfur process and wastewater treatment (including three sources), 14.7% to industrial organic solvent usage, and 13.3% to petrochemical process. So the wastewater treatment unit was a major source of odor pollution at chemical industrial area.

[Characteristics and sources of organic carbon and elemental carbon in PM2.5 in Shanghai urban area].

Organic carbon (OC) and elemental carbon (EC) in PM2.5 samples collected in Shanghai urban area during June 2010 to May 2011 were analyzed with IMPROVE-TOR protocol. The results showed that the annual average concentrations of OC and EC in PM2.5 were 8.6 µg.m-3 ± 6.2 µg.m-3 and 2.4 µg.m-3 ± 1.3 µg.m-3 respectively, accounting for 20% of PM2.5 mass concentration. The seasonal average concentrations of OC and EC were highest in winter and lowest in summer. And the percentages of OC and EC in PM2.5 were highest in autumn. The annual average OC/EC ratio was 3. 54 ± 1. 14. The concentrations of secondary organic carbon (SOC) were evaluated by the minimum OC/EC ratio method and the annual average concentration of SOC was 3.9 µg.m(-3) ±4.2 µg.m(-3), accounting for 38.9% of OC. In summer, the concentrations of SOC were relatively low and were correlated well with the maximum hourly concentrations of ozone, which indicated that the photochemical reaction was an important way of SOC formation. In autumn and winter when the west wind direction was predominant, the concentrations of SOC were higher than that in windless condition, which meant the transportation of SOC. The carbonaceous components were associated with source contributions using the principal component analysis (PCA) with eight thermally-derived carbon fractions, OC1, OC2, OC3, OC4, EC1, EC2, EC3 and OPC. Motor vehicle, coal-fired units, biomass burning and road dust were four main sources of OC and EC in PM2.5 in Shanghai urban area, which contributing 69. 8% - 81. 4% of carbonaceous aerosols. The contribution of motor vehicle was high throughout the year. Biomass burning contributed about 15% -20% of OC and EC. The influence of road dust was relatively obvious in spring and autumn. And the contribution of coal-fired units was higher in winter than those in other seasons.

[Estimation of the formation potential of ozone and secondary organic aerosol in Shanghai in spring].

The concentration and speciation of ambient volatile organic compounds (VOCs) in Shanghai downtown and suburban areas were analyzed and measured by using online gas chromatography with flame ionization detection systems (GC-FID) during the spring period (from Mar. 1st to Mar. 31st, 2013) and 55 kinds of VOCs were detected. Maximum ozone formation potential (PhiOFP) and Fractional aerosol coefficients (FAC) were also used to estimate the formation potential of ozone (O3) and secondary organic aerosols (SOA). The results showed that the average concentrations of VOCs were respectively 33.9 x 10(-9) and 20.2 x 10(-9) in the downtown and suburban of shanghai. The main components were alkanes (14.7 x 10(-9)), aromatics (7.7 x 10(-9)) and alkenes (9.3 x 10(-9)) in the downtown; and the main components were alkanes (4.3 x 10(-9)), aromatics (13.9 x 10(-9)) and alkenes (1.8 x 10(-9)) in the suburban. Furthermore, PhiOFP (in the downtown) was 0.58 times of the PhiOFP (in the suburban), while PhiOFP (alkanes) and PhiOFP (alkenes) were 2.2 and 2.1 times in the downtown than suburban, but aromatics was only 0.34 times in the downtown than suburban. Fractional aerosol coefficients (FAC) were also used to estimate the potential formation of secondary organic aerosols (SOA) and the SOA concentration values in the downtown and suburban were 2.04 and 4.04 microg x m(-3), respectively. SOA formations from aromatics and alkanes in the downtown contributed 13.2% and 86. 8% and in the suburban contributed 2.7% and 97.3% to the total SOA formation potential. Aromatics and high-C alkanes were the main components that contributed to the SOA formations in both downtown and suburban of Shanghai in spring.

[Secondary aerosol formation through photochemical reactions estimated by using air quality monitoring data in the downtown of Pudong, Shanghai].

Analyses of diurnal patterns of PM10 in the downtown of Pudong, Shanghai have been performed in this study at different daily ozone maximum concentrations (O(3,max)) from May to October, 2010. In order to evaluate secondary aerosol formation at different ozone levels, CO was used as a tracer for primary aerosol, and 0(3, max) was used as an index for photochemical activity. Results show that along with increasing of O3 concentration, the concentration of primary and secondary aerosol was increased respectively from 0. 036 to 0.044 mg x m(-3) and from 0.018 to 0.055 mg x m(-3). The ratio of secondary to primary aerosol was increased from 49.8% to 124.5%. Furthermore, along with the increase of O(3, max) the forming time of O(3,max) and secondary aerosol was changed respectively from 13:00 to 14:00 and from 11:00-20:00 to 09:00-20:00. At the same time, the chemical composition of PM2.5 was different at different photochemical levels. PM(2.5) was composed of 12.0% organic carbon (OC), 18.7% sulfate (SO4(2-1)), 13.1% nitrate (NO3-) and 4.5% element carbon (EC) when O(3, max) was < 0.10 mg x m(-3) and PM2.5 was composed of 20.0% organic carbon (OC), 22.9% sulfate, 23.1% nitrate and 4.7% element carbon (EC) with O(3, max) > 0. 20 mg x m(-3). These results approved that the photochemical reactivity promoted the production of SO4(2-), NO3- and OC.

[Characteristics of ambient VOCs and their role in O3 formation: a typical air pollution episode in Shanghai urban area].

The concentration, speciation and chemical reactivity of ambient volatile organic compounds (VOCs) in shanghai city were analyzed and measured by using online gas chromatography with flame ionization detection systems (GC-FID) during a typical air pollution episode (from Oct. 30th to Nov. 2nd, 2010) and 55 kinds of VOCs were detected. The results show that averaged concentrations of VOCs was 27 x 10(-9) before the episode, and then dramatically increased by 3 times (87 x 10(-9)) in the episode than the former, the main components were alkanes (35.2 x 10(-9)), aromatics (30.0 x 10(-9)), alkenes (21.6 x 10(-9)). Furthermore, the maximum ozone formation potential (PhiOFP) is analyzed and showed that PhiOFP (in the episode) > PhiOFP (after the episode) PhiOFP (before the episode). Before the episode, the percent of PhiOFP for aromatics 53.0% , alkenes 36. 1% and alkanes 11.7%; in the episode, the percent of PhiOFP for aromatics 54.7%, alkenes 36.7% and alkanes 9.8%; after the episode, the percent of PhiOFP for alkenes 52.7%, aromatics 36.0% and alkanes 13.2%. Alkenes (C2-C4) and aromatics (C6-C8) are the main components for the ozone formation, namely toluene, m,p-xylene, 1,3-butadiene, propene, ethene et al. In addition, the relationship is negative and nonlinear between the O3 and PhiOFP. And efficiencies of PhiOFP formed into O3 are below 20. 0% in different stage of episode. This is very important and meaningful for the quantitative evaluate the influence of VOCs towards O3.