Guoshun Zhuang

Guoshun Zhuang


Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 March 2016 in Atmospheric Chemistry and Physics
Verified
Journal Article
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Yunhua ChangYunhua Chang
Yunhua Chang
ZZZhong Zou
Zhong Zou
CDCongrui Deng
Congrui Deng
KHKan Huang
Kan Huang
Jeff CollettJeff Collett
Jeff Collett
GZGuoshun Zhuang
Guoshun Zhuang
Agricultural activities are a major source contributing to NH3 emissions in Shanghai and most other regions of China; however, there is a long-standing and ongoing controversy regarding the contributions of vehicle-emitted NH3 to the urban atmosphere. From April 2014 to April 2015, we conducted measurements of a wide range of gases (including NH3) and the chemical properties of PM2.5 at hourly resolution at a Shanghai urban supersite. This large data set shows NH3 pollution events, lasting several hours with concentrations 4 times the annual average of 5.3 µg m−3, caused by the burning of crop residues in spring. There are also generally higher NH3 concentrations (mean ± 1 σ) in summer (7.3 ± 4.9 µg m−3; n = 2181) because of intensive emissions from temperature-dependent agricultural sources. However, the NH3 concentration in summer was only an average of 2.4 µg m−3 or 41 % higher than the average NH3 concentration of other seasons. Furthermore, the NH3 concentration in winter (5.0 ± 3.7 µg m−3; n = 2113) was similar to that in spring (5.1 ± 3.8 µg m−3; n = 2198) but slightly higher, on average, than that in autumn (4.5 ± 2.3 µg m−3; n = 1949). Moreover, other meteorological parameters like planetary boundary layer height and relative humidity were not major factors affecting seasonal NH3 concentrations. These findings suggest that there may be some climate-independent NH3 sources present in the Shanghai urban area. Independent of season, the concentrations of both NH3 and CO present a marked bimodal diurnal profile, with maxima in the morning and the evening. A spatial analysis suggests that elevated concentrations of NH3 are often associated with transport from regions west–northwest and east–southeast of the city, areas with dense road systems. The spatial origin of NH3 and the diurnal concentration profile together suggest the importance of vehicle-derived NH3 associated with daily commuting in the urban environment. To further examine vehicular NH3 emissions and transport, sampling of the NH3 concentration was performed in (from the entrance to the exit of the tunnel) and out (along a roadside transect spanning 310 m perpendicular to the tunnel) of a heavily trafficked urban tunnel during the spring of 2014. NH3 concentrations in the tunnel exit were over 5 and 11 times higher than those in the tunnel entrance and in the ambient air, respectively. Based on the derived mileage-based NH3 emission factor of 28 mg km−1, a population of 3.04 million vehicles in Shanghai produced around 1300 t NH3 in 2014, which accounts for 12 % of total NH3 emissions in the urban area. Collectively, our results clearly show that vehicle emissions associated with combustion are an important NH3 source in Shanghai urban areas and may have potential implications for PM2.5 pollution in the urban atmosphere.

2 January 2012 in Atmospheric Chemistry and Physics
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Journal Article
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KHK. Huang
K. Huang
GZGuoshun Zhuang
Guoshun Zhuang
YLY. Lin
Y. Lin
JFJ. S. Fu
J. S. Fu
QWQ. Wang
Q. Wang
BCB. Cao
B. Cao
An intensive aerosol and gases campaign was performed at Shanghai in the Yangtze River Delta region over Eastern China from late March to early June 2009. This study provided a complementary picture of typical haze types and the formation mechanisms in megacities over China by using a synergy of ground-based monitoring, satellite and lidar observations. During the whole study period, several extreme low visibility periods were observed with distinct characteristics, and three typical haze types were identified, i.e. secondary inorganic pollution, dust, and biomass burning. Sulfate, nitrate and ammonium accounted for a major part of PM2.5 mass during the secondary inorganic pollution, and the good correlation between SO2/NOx/CO and PM2.5 indicated that coal burning and vehicle emission were the major sources. Large-scale regions with high AOD (aerosol optical depths) and low Ångström exponent were detected by remote-sensing observation during the dust pollution episode, and this episode corresponded to coarse particles rich in mineral components such as Al and Ca contributing 76.8% to TSP. The relatively low Ca/Al ratio of 0.75 along with the air mass backward trajectory analysis suggested the dust source was from Gobi Desert. Typical tracers for biomass burning from satellite observation (column CO and HCHO) and from ground measurement (CO, particulate K+, OC, and EC) were greatly enhanced during the biomass burning pollution episode. The exclusive linear correlation between CO and PM2.5 corroborated that organic aerosol dominated aerosol chemistry during biomass burning, and the high concentration and enrichment degree of arsenic (As) could be also partly derived from biomass burning. Aerosol optical profile observed by lidar demonstrated that aerosol was mainly constrained below the boundary layer and comprised of spheric aerosol (depolarization ratio <5%) during the secondary inorganic and biomass burning episodes, while thick dust layer distributed at altitudes from near surface to 1.4 km (average depolarization ratio = 0.122 ± 0.023) with dust accounting for 44–55% of the total aerosol extinction coefficient during the dust episode. This study portrayed a good picture of the typical haze types and proposed that identification of the complicated emission sources is important for the air quality improvement in megacities in China.

5 December 2012 in Atmospheric Chemistry and Physics
Verified
Journal Article
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KHK. Huang
K. Huang
GZGuoshun Zhuang
Guoshun Zhuang
YLY. Lin
Y. Lin
QWQ. Wang
Q. Wang
JFJ. S. Fu
J. S. Fu
QFQ. Fu
Q. Fu
The Chinese Spring Festival is one of the most important traditional festivals in China. The peak transport in the Spring Festival season (spring travel rush) provides a unique opportunity for investigating the impact of human activity on air quality in the Chinese megacities. Emission sources are varied and fluctuate greatly before, during and after the Festival. Increased vehicular emissions during the "spring travel rush" before the 2009 Festival resulted in high level pollutants of NOx (270 μg m−3), CO (2572 μg m−3), black carbon (BC) (8.5 μg m−3) and extremely low single scattering albedo of 0.76 in Shanghai, indicating strong, fresh combustion. Organics contributed most to PM2.5, followed by NO3−, NH4+, and SO42−. During the Chinese Lunar New Year's Eve and Day, widespread usage of fireworks caused heavy pollution of extremely high aerosol concentration, scattering coefficient, SO2, and NOx. Due to the "spring travel rush" after the festival, anthropogenic emissions gradually climbed and mirrored corresponding increases in the aerosol components and gaseous pollutants. Secondary inorganic aerosol (SO42−, NO3−, and NH4+) accounted for a dominant fraction of 74% in PM2.5 due to an increase in human activity. There was a greater demand for energy as vast numbers of people using public transportation or driving their own vehicles returned home after the Festival. Factories and constructions sites were operating again. The potential source contribution function (PSCF) analysis illustrated the possible source areas for air pollutants of Shanghai. The effects of regional and long-range transport were both revealed. Five major sources, i.e. natural sources, vehicular emissions, burning of fireworks, industrial and metallurgical emissions, and coal burning were identified using the principle component analysis. The average visibility during the whole study period was less than 6 km. It had been estimated that 50% of the total light extinction was due to the high water vapor in the atmosphere. This study demonstrates that organic aerosol was the largest contributor to aerosol extinction at 47%, followed by sulfate ammonium, nitrate ammonium, and EC at 22%, 14%, and 12%, respectively. Our results indicated the dominant role of traffic-related aerosol species (i.e. organic aerosol, nitrate and EC) on the formation of air pollution, and suggested the importance of controlling vehicle numbers and emissions in mega-cities of China as its population and economy continue to grow.

16 April 2010 in Journal of Geophysical Research: Atmospheres
Verified
Journal Article
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KHKan Huang
Kan Huang
GZGuoshun Zhuang
Guoshun Zhuang
JLJuan Li
Juan Li
QWQiongzhen Wang
Qiongzhen Wang
YSYele Sun
Yele Sun
JFJoshua S. Fu
Joshua S. Fu

20 June 2013 in Atmospheric Chemistry and Physics
Verified
Journal Article
Open access
PDF file
KHK. Huang
K. Huang
GZGuoshun Zhuang
Guoshun Zhuang
YLY. Lin
Y. Lin
QWQ. Wang
Q. Wang
JFJ. S. Fu
J. S. Fu
CDC. Deng
C. Deng
Three field campaigns were conducted before, during, and after the 2010 World Expo in Shanghai, aiming to understand the response of secondary aerosol components to both control measures and human activities. In spring, PM2.5 (particulate matter) averaged 34.5 ± 20.9 μg m−3 with a severe pollution episode influenced by a floating dust originating from northwestern China on 26–28 April, right before the opening of the expo. With the approaching expo a significant increasing trend of SNA (SO42−, NO3−, and NH4+) concentrations was observed from 22 April to 2 May, attributed to the enhanced human activities. Nitrate had the most significant daily increasing rate of 1.1 μg m−3d−1 due to enhanced vehicle emission. In summer, two intensive pollution episodes were found to be a mixed pollution of SNA with biomass burning due to loose control of post-harvest straw burning. In the autumn phase of the expo, before the closing of the expo (20–30 October), the air quality over Shanghai was much better than ever before. However, the air quality rapidly plummeted as soon as the expo was announced closed. SNA increased 3–6 fold to be 42.1 and 68.2 μg m−3 on 31 October and 1 November, respectively, as compared to 20–30 October. Of which, nitrate increased most ~5–8 fold, indicating the serious impact from enhanced vehicle emission. Compared to the spring and summer of 2009, NO3− increased 12–15% while SO42− showed reductions of 15–30%. Continuous desulfurization of SO2 emission from power plants in recent years was responsible for the lowered SO42−, while increased traffic emission from the tremendous number of expo visitors was the major contributor to the increased NO3−. Compared to the autumn of 2009, all the ion components increased in 2010, owing to the lifting of emission control measures after the expo. SO42− was found least increased while NO3− and Ca2+ had tremendous increases of 150 and 320%, respectively. The anthropogenic Ca as a tracer from construction dust increased from 2.88 ± 1.85 μg m−3 during the expo to 6.98 ± 3.19 μg m−3 during the post-expo period, attributed to the resumption of construction works after the expo. The lack of successive control measures with the loose regulations after the expo were responsible for this jump of the bad quality. The ratio of NO3−/SO42− in PM2.5 over Shanghai had a significant increasing trend from ~0.3 in the early 2000s to more than 1.0 in 2010, indicating the increasing role of mobile sources. Reducing NOx emission will be China's priority in the future in order to improve the air quality over the megacities. In addition, lowering mineral aerosol components (e.g., Ca2+) was also demonstrated to be beneficial for alleviating air pollution in China. This study demonstrated that stringent emission control measures aiming at mega-events in China could achieve positive benefits on improving the air quality in a short term. However, persistent efforts of curbing the anthropogenic emission remain a long way to go in the future.

16 April 2010 in Journal of Geophysical Research: Atmospheres
Verified
Journal Article
Closed access
PDF file
YSYele Sun
Yele Sun
GZGuoshun Zhuang
Guoshun Zhuang
KHKan Huang
Kan Huang
JLJuan Li
Juan Li
QWQiongzhen Wang
Qiongzhen Wang
XZXiujuan Zhao
Xiujuan Zhao