Qi Zhang

Qi Zhang

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

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

Representative Publications

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18 May 2017 in Reviews of Geophysics
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Manish  ShrivastavaManish Shrivastava
Manish Shrivastava
CCChristopher D. Cappa
Christopher D. Cappa
JFJiwen Fan
Jiwen Fan
AGAllen H. Goldstein
Allen H. Goldstein
AGAlex Guenther
Alex Guenther
QZQi Zhang
Qi Zhang
Anthropogenic emissions and land use changes have modified atmospheric aerosol concentrations and size distributions over time. Understanding preindustrial conditions and changes in organic aerosol due to anthropogenic activities is important because these features (1) influence estimates of aerosol radiative forcing and (2) can confound estimates of the historical response of climate to increases in greenhouse gases. Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, represents a major fraction of global submicron‐sized atmospheric organic aerosol. Over the past decade, significant advances in understanding SOA properties and formation mechanisms have occurred through measurements, yet current climate models typically do not comprehensively include all important processes. This review summarizes some of the important developments during the past decade in understanding SOA formation. We highlight the importance of some processes that influence the growth of SOA particles to sizes relevant for clouds and radiative forcing, including formation of extremely low volatility organics in the gas phase, acid‐catalyzed multiphase chemistry of isoprene epoxydiols, particle‐phase oligomerization, and physical properties such as volatility and viscosity. Several SOA processes highlighted in this review are complex and interdependent and have nonlinear effects on the properties, formation, and evolution of SOA. Current global models neglect this complexity and nonlinearity and thus are less likely to accurately predict the climate forcing of SOA and project future climate sensitivity to greenhouse gases. Efforts are also needed to rank the most influential processes and nonlinear process‐related interactions, so that these processes can be accurately represented in atmospheric chemistry‐climate models.

5 October 2011 in Analytical and Bioanalytical Chemistry
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QZQi Zhang
Qi Zhang
JJJose L. Jimenez
Jose L. Jimenez
MCManjula R. Canagaratna
Manjula R. Canagaratna
IUIngrid M. Ulbrich
Ingrid M. Ulbrich
NNNga L. Ng
Nga L. Ng
YSYele Sun
Yele Sun
Organic species are an important but poorly characterized constituent of airborne particulate matter. A quantitative understanding of the organic fraction of particles (organic aerosol, OA) is necessary to reduce some of the largest uncertainties that confound the assessment of the radiative forcing of climate and air quality management policies. In recent years, aerosol mass spectrometry has been increasingly relied upon for highly time-resolved characterization of OA chemistry and for elucidation of aerosol sources and lifecycle processes. Aerodyne aerosol mass spectrometers (AMS) are particularly widely used, because of their ability to quantitatively characterize the size-resolved composition of submicron particles (PM1). AMS report the bulk composition and temporal variations of OA in the form of ensemble mass spectra (MS) acquired over short time intervals. Because each MS represents the linear superposition of the spectra of individual components weighed by their concentrations, multivariate factor analysis of the MS matrix has proved effective at retrieving OA factors that offer a quantitative and simplified description of the thousands of individual organic species. The sum of the factors accounts for nearly 100% of the OA mass and each individual factor typically corresponds to a large group of OA constituents with similar chemical composition and temporal behavior that are characteristic of different sources and/or atmospheric processes. The application of this technique in aerosol mass spectrometry has grown rapidly in the last six years. Here we review multivariate factor analysis techniques applied to AMS and other aerosol mass spectrometers, and summarize key findings from field observations. Results that provide valuable information about aerosol sources and, in particular, secondary OA evolution on regional and global scales are highlighted. Advanced methods, for example a-priori constraints on factor mass spectra and the application of factor analysis to combined aerosol and gas phase data are discussed. Integrated analysis of worldwide OA factors is used to present a holistic regional and global description of OA. Finally, different ways in which OA factors can constrain global and regional models are discussed.

15 October 2014 in Atmospheric Chemistry and Physics
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KTKostas Tsigaridis
Kostas Tsigaridis
NDNikos Daskalakis
Nikos Daskalakis
MKMaria Kanakidou
Maria Kanakidou
PAP. J. Adams
P. J. Adams
Paulo ArtaxoPaulo Artaxo
Paulo Artaxo
XZX. Zhang
X. Zhang
This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a−1 (range 34–144 Tg a−1) and the median SOA source strength (natural and anthropogenic) is 19 Tg a−1 (range 13–121 Tg a−1). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a−1 (range 16–121 Tg a−1), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a−1; range 13–20 Tg a−1, with one model at 37 Tg a−1). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a−1 (range 28–209 Tg a−1), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at the surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately.

18 February 2011 in Atmospheric Chemistry and Physics
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YSYele Sun
Yele Sun
QZQi Zhang
Qi Zhang
JSJ. J. Schwab
J. J. Schwab
KDK. L. Demerjian
K. L. Demerjian
WCW.-N. Chen
W.-N. Chen
YLY.-C. Lin
Y.-C. Lin
Submicron aerosol particles (PM1) were measured in-situ using a High-Resolution Time-of-Flight Aerosol Mass Spectrometer during the summer 2009 Field Intensive Study at Queens College in New York, NY. Organic aerosol (OA) and sulfate are the two dominant species, accounting for 54% and 24%, respectively, of the total PM1 mass. The average mass-based size distribution of OA presents a small mode peaking at ~150 nm (Dva) and an accumulation mode (~550 nm) that is internally mixed with sulfate, nitrate, and ammonium. The diurnal cycles of both sulfate and OA peak between 01:00–02:00 p.m. EST due to photochemical production. The average (±σ) oxygen-to-carbon (O/C), hydrogen-to-carbon (H/C), and nitrogen-to-carbon (N/C) ratios of OA in NYC are 0.36 (±0.09), 1.49 (±0.08), and 0.012 (±0.005), respectively, corresponding to an average organic mass-to-carbon (OM/OC) ratio of 1.62 (±0.11). Positive matrix factorization (PMF) of the high resolution mass spectra identified two primary OA (POA) sources, traffic and cooking, and three secondary OA (SOA) components including a highly oxidized, regional low-volatility oxygenated OA (LV-OOA; O/C = 0.63), a less oxidized, semi-volatile SV-OOA (O/C = 0.38) and a unique nitrogen-enriched OA (NOA; N/C = 0.053) characterized with prominent CxH2x + 2N+ peaks likely from amino compounds. Our results indicate that cooking and traffic are two distinct and mass-equivalent POA sources in NYC, together contributing ~30% of the total OA mass during this study. The OA composition is dominated by secondary species, especially during high PM events. SV-OOA and LV-OOA on average account for 34% and 30%, respectively, of the total OA mass. The chemical evolution of SOA in NYC appears to progress with a continuous oxidation from SV-OOA to LV-OOA, which is further supported by a gradual increase of O/C ratio and a simultaneous decrease of H/C ratio in total OOA. Detailed analysis of NOA (5.8% of OA) presents evidence that organic nitrogen species such as amines might have played an important role in the atmospheric processing of OA in NYC, likely involving both acid-base chemistry and photochemistry. In addition, analysis of air mass trajectories and satellite imagery of aerosol optical depth (AOD) indicates that the high potential source regions of secondary sulfate and aged OA are mainly located in regions to the west and southwest of the city.

11 July 2016 in Atmospheric Chemistry and Physics
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YSYele Sun
Yele Sun
Wei DuWei Du
Wei Du
PFPingqing Fu
Pingqing Fu
QWQingqing Wang
Qingqing Wang
JLJie Li
Jie Li
ZWZifa Wang
Zifa Wang
Winter has the worst air pollution of the year in the megacity of Beijing. Despite extensive winter studies in recent years, our knowledge of the sources, formation mechanisms and evolution of aerosol particles is not complete. Here we have a comprehensive characterization of the sources, variations and processes of submicron aerosols that were measured by an Aerodyne high-resolution aerosol mass spectrometer from 17 December 2013 to 17 January 2014 along with offline filter analysis by gas chromatography/mass spectrometry. Our results suggest that submicron aerosols composition was generally similar across the winter of different years and was mainly composed of organics (60 %), sulfate (15 %) and nitrate (11 %). Positive matrix factorization of high- and unit-mass resolution spectra identified four primary organic aerosol (POA) factors from traffic, cooking, biomass burning (BBOA) and coal combustion (CCOA) emissions as well as two secondary OA (SOA) factors. POA dominated OA, on average accounting for 56 %, with CCOA being the largest contributor (20 %). Both CCOA and BBOA showed distinct polycyclic aromatic hydrocarbons (PAHs) spectral signatures, indicating that PAHs in winter were mainly from coal combustion (66 %) and biomass burning emissions (18 %). BBOA was highly correlated with levoglucosan, a tracer compound for biomass burning (r2 = 0.93), and made a considerable contribution to OA in winter (9 %). An aqueous-phase-processed SOA (aq-OOA) that was strongly correlated with particle liquid water content, sulfate and S-containing ions (e.g. CH2SO2+) was identified. On average aq-OOA contributed 12 % to the total OA and played a dominant role in increasing oxidation degrees of OA at high RH levels (> 50 %). Our results illustrate that aqueous-phase processing can enhance SOA production and oxidation states of OA as well in winter. Further episode analyses highlighted the significant impacts of meteorological parameters on aerosol composition, size distributions, oxidation states of OA and evolutionary processes of secondary aerosols.

11 September 2015 in Atmospheric Chemistry and Physics
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YSYele Sun
Yele Sun
ZWZ. F. Wang
Z. F. Wang
Wei DuWei Du
Wei Du
QZQi Zhang
Qi Zhang
QWQ. Q. Wang
Q. Q. Wang
DWD. R. Worsnop
D. R. Worsnop
High concentrations of fine particles (PM2.5) are frequently observed during all seasons in Beijing, China, leading to severe air pollution and human health problems in this megacity. In this study, we conducted real-time measurements of non-refractory submicron aerosol (NR-PM1) species (sulfate, nitrate, ammonium, chloride, and organics) in Beijing using an Aerodyne Aerosol Chemical Speciation Monitor for 1 year, from July 2011 to June 2012. This is the first long-term, highly time-resolved (~ 15 min) measurement of fine particle composition in China. The seasonal average (±1σ) mass concentration of NR-PM1 ranged from 52 (±49) μg m−3 in the spring season to 62 (±49) μg m−3 in the summer season, with organics being the major fraction (40–51 %), followed by nitrate (17–25 %) and sulfate (12–17 %). Organics and chloride showed pronounced seasonal variations, with much higher concentrations in winter than in the other seasons, due to enhanced coal combustion emissions. Although the seasonal variations of secondary inorganic aerosol (SIA, i.e., sulfate + nitrate + ammonium) concentrations were not significant, higher contributions of SIA were observed in summer (57–61 %) than in winter (43–46 %), indicating that secondary aerosol production is a more important process than primary emissions in summer. Organics presented pronounced diurnal cycles that were similar among all seasons, whereas the diurnal variations of nitrate were mainly due to the competition between photochemical production and gas–particle partitioning. Our data also indicate that high concentrations of NR-PM1 (> 60 μg m−3) are usually associated with high ambient relative humidity (RH) (> 50 %) and that severe particulate pollution is characterized by different aerosol composition in different seasons. All NR-PM1 species showed evident concentration gradients as a function of wind direction, generally with higher values associated with wind from the south, southeast or east. This was consistent with their higher potential as source areas, as determined by potential source contribution function analysis. A common high potential source area, located to the southwest of Beijing along the Taihang Mountains, was observed during all seasons except winter, when smaller source areas were found. These results demonstrate a high potential impact of regional transport from surrounding regions on the formation of severe haze pollution in Beijing.