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Ambient peroxyacyl nitrate concentration and regional transportation in Beijing
Accepted Manuscript Ambient peroxyacyl nitrate concentration and regional transportation in Beijing Boya Zhang, Bu Zhao, Peng Zuo, Huang Zhi, Jianbo Zhang PII:
S1352-2310(17)30502-2
DOI:
10.1016/j.atmosenv.2017.07.053
Reference:
AEA 15467
To appear in:
Atmospheric Environment
Received Date: 13 December 2016 Revised Date:
26 July 2017
Accepted Date: 29 July 2017
Please cite this article as: Zhang, B., Zhao, B., Zuo, P., Zhi, H., Zhang, J., Ambient peroxyacyl nitrate concentration and regional transportation in Beijing, Atmospheric Environment (2017), doi: 10.1016/ j.atmosenv.2017.07.053. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Ambient Peroxyacyl Nitrate Concentration and Regional Transportation in
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Beijing
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Boya Zhang1*, Bu Zhao2*, Peng Zuo1, Huang Zhi1, Jianbo Zhang1
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1 State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of
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Environmental Sciences and Engineering, Peking University, Beijing, 100871, P.R.China;
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[email protected] (B.Z.), [email protected] (J.Z), [email protected] (P.Z.),
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[email protected] (Z.H)
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2 School of Environment, Tsinghua University, Beijing 100084;
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P.R.China;[email protected] (B.Z.)
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* These authors contributed equally to this work.
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Corresponding Author:
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Jianbo Zhang, State Key Joint Laboratory of Environmental Simulation and Pollution Control,
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College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, P.R.
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China
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Tel: +86-13661161078; E-mail: [email protected]
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ACCEPTED MANUSCRIPT Abstract: Peroxyacyl nitrates (PANs) are photochemical secondary pollutants that play a key role
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in the atmospheric chemistry of the troposphere. However, there have been few studies on the
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long-term variation and inter-regional transport of PANs. In this study, summertime ambient PAN
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concentrations were monitored at urban and rural sites in Beijing and Hebei, China, between 2006
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and 2014. In Beijing, the peak concentrations of PAN and PPN were in the range of 6–17 ppbv and
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0.6–2.2 ppbv, respectively, higher than concentrations in other provinces. The nitrogen oxide (NOx)
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concentration decreased at a rate of 1.7 ppbv/yr (~4% yr-1), and the PAN concentration decreased at
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a rate of 0.03 ppbv/yr (~3% yr-1), while the ozone (O3) concentration increased at a rate of 1.5
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ppbv/yr (~4% yr-1). Trajectory clustering analyses showed that high concentrations of PAN were
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mainly affected by low air masses transported medium/short distances from South Beijing, and the
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potential source contribution function maps showed that the likely pollution source area was
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concentrated in the southern region of Beijing. These findings provide a theoretical basis for
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pollution control in this region.
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Key words: PAN; concentration; CPF; PSCF; regional transport
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1 Introduction
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Peroxyacyl nitrates (PANs, RC(O)OONO2), secondary pollutants produced by a photochemical
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reaction between nitrogen oxide (NOx) and volatile organic compounds (VOCs), play a key role in
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the atmospheric chemistry of the troposphere. As there are no direct anthropogenic emissions, PANs
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are the ideal indicators of atmospheric photochemical pollution (Fischer et al., 2014; Tang et al.,
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2006; Kleindienst, 1994). Among PANs, peroxyacetyl nitrate (PAN, R=CH3) and peroxypropionyl
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nitrate (PPN, R=CH3CH2) are the most important substances with the highest concentrations in the
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atmosphere (Seinfeld and Pandis, 2012). PANs have many toxic effect including irritation,
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mutagenicity and chromosome teratogenicity (Dugger et al., 1963), which may have adverse effects
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on plant growth and human health at high concentrations (Vyskocil et al., 1998). Furthermore, PAN
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is also an important reservoir of tropospheric NOx (NOx = NO + NO2) (Singh et al., 1985), which is
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stable at low temperatures, but can be transported by air masses and can generate NO2 through
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thermal decomposition. This reaction changes the distribution of the ozone (O3) and hydroxyl (OH)
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radicals affecting the atmospheric photochemical pollution levels of different regions (Nielsen et al.,
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1981). Monitoring studies during recent decades have shown that PANs are ubiquitous in the global
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atmosphere. Existing data show that, although concentrations in polar regions are relatively low, the
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peak concentration of PANs in the atmosphere is generally at ppbv level (Fadnavis et al.,2014;
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Pandey et al., 2014; Phillips et al., 2013). The basic physical and chemical properties of PANs also
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determine that their long-distance transport with air masses affects photochemical reactions in other
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regions. This means that atmospheric photochemical pollutants such as PAN can be transported
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between rural areas and cities. The first studies related to PANs in China were conducted in the
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1990s, and the number of studies has been increasing in recent years (Zhang G et al., 2014; Zhang
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G et al., 2015; Zhang H L et al., 2014; Xue et al., 2014; Gao et al., 2009; Williams et al., 2000).
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PANs have been monitored in various provinces including Gansu (Zhang J M et al., 2009),
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Shanghai (Han et al., 2013), Guangdong (Wang et al., 2010; Zhou et al., 2013), and Fujian (Wang et
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al., 2014). However, the monitoring sites in these studies were widely scattered, and the monitoring
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periods were too short, so the data only reflected the local concentration levels at a specific time.
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There have been few studies on the long-term variation and inter-regional transport of PANs in
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China.
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In this study, long-term PAN atmospheric concentrations in summer in Beijing were observed
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and variations in concentration were analyzed. By calculating the conditional probability function
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(CPF) and the potential source contribution function (PSCF), we analyzed the local pollution
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emissions and regional pollution transport, and evaluated the level of atmospheric photochemical
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pollution to provide a theoretical basis for pollution control in this region.
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2 Methods and Materials
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2.1 Monitoring sites and instrument
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The urban site monitoring was conducted in August between 2006 and 2014. The site (39.99°N,
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116.31°E) was located on the top of the Science Building (∼25 m above ground level [AGL]) at
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Peking University (PKU) at the eastern end of Zhongguancun Street, north of the fourth ring road
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(Fig. 1). This urban site was surrounded by low university buildings to the north and west. There
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was no major source of pollution around the site. The monitoring data included concentrations of 3
ACCEPTED MANUSCRIPT PAN and conventional air pollutants (CO, SO2, NO, NO2, O3, PM2.5) and meteorological parameters
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[temperature (TEMP), relative humidity (RH), wind speed (WS), and wind direction (WD)] which
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are shown in Supporting Information (Table. S1). The rural site monitoring was conducted from
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June 4 to July 8, 2014. The observation site (38.66°N, 115.21°E) was located in Wangdu County,
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Baoding, Hebei Province, approximately 180 km from urban (Beijing, PKU) site (Fig. 1). This rural
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site was distant from urban areas and was located in agricultural land. Monitoring data included SO2,
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CO, CO2, CH4, NH3, NOx, HOx, HONO, HNO3, NO3, N2O5, PAN, VOCs, O3, and PM2.5.
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Fig. 1 Location of the sampling site in Beijing and Hebei
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PAN and PPN were measured using a PAN online monitor (Scott-Marrin, Inc., CA, USA). The
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selected column consisted of a 0.53-mm-inner diameter fused silica capillary coated with 1-μm
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cross-linked liquid-phase trifluoropropyl silicone (RTX-200), whose temperature was controlled at
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about 15°C. The temperature of the electron capture detector (ECD) was kept at 40°C. The carrier
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gas and tail gas were high-purity helium and high-purity nitrogen, respectively. The detection limit
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of the instrument was 5–10 pptv, and the time resolution was 5 minutes. PAN standard gas was
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prepared using the following process: Nitric oxide standard gas was mixed with acetone standard
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gas (Scott-Marrin, Inc.) and the mixture was placed under ultraviolet light (wavelength, 285 nm) to
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complete irradiation photolysis. The product was then mixed with PAN-free zero gas. PPN standard
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gas was prepared from PPN liquid solution using the volatile sources. Details of the instruments and
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calibration process are given in previous reports by Williams and Yang (Williams et al., 2000; Yang
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et al., 2009). O3, NOx, SO2, CO, and PM2.5 were measured using a Model 49i Ozone Analyzer, Model
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42i-TL Nitrogen Oxide Analyzer, Model 43i-TLE Sulfur Dioxide Analyzer, Model 48C Carbon
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Monoxide Analyzer, and a TEOM1400a Particulate Matter Monitor (Thermo Fisher Scientific, MA,
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USA), respectively (Zhang Q et al., 2014).
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2.2 Analysis of regional pollution transportation
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1）CPF pollution roses
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To examine the effects of local emissions on PAN concentrations, we calculated pollution roses
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based on the PAN concentration, wind direction, and wind speed data during the observation period.
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In this study, wind directions were divided into 16 sectors (Dimitriou and Kassomenos, 2015). The
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pollution roses were given by the following equation:
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CPFi
mi ni
(1)
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where mi represents the number of exceedances of an hourly PAN threshold (85th percentile)
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concentration during the prevalence of winds from the (i) Δθ sector, and ni represents the total
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number of hourly data from the same wind sector. Hourly wind speed values equal to or less than
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0.3 m/s were defined as calm conditions and were not included in the CPF results.
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2）Cluster analysis and PSCF
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Meteorological data were obtained from the Global Data Assimilation System (GDAS) of the
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US National Center for Environmental Prediction (NCEP). Using the Trajstas software program
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(Wang et al., 2009) and the HYSPLIT-4 trajectory model (Draxler and Hess, 1997), we calculated
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the 24h backward trajectories of the air masses arriving at the monitoring site from 2006 to 2014,
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using a time interval of 1 h and a height of 25 m AGL. The major air pollutant transmission path
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and potential sources were determined by cluster analysis and PSCF.
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The PSCF was based on the development of the CPF to estimate the potential source areas.
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ACCEPTED MANUSCRIPT The PSCF indicated the range of potential sources by combining the trajectories of the air masses
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and the pollutant concentrations at the monitoring site. The study area (38–42°N, 114–118°E) was
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analyzed on a 0.1°×0.1° resolution grid, and a threshold (85th percentile) was set for the PAN
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concentration. When the corresponding PAN concentration was higher than this threshold, the
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trajectory was confirmed as a contaminant trajectory. The PSCF was defined by Eq. (2), as follows: PSCFij
1.0 0.7 Wij 0.4 0.2
nij
(2)
3nave nij 1.5nave nij 3nave nave nij 1.5nave nij nave
(3)
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where mij represents the number of endpoints belonging to trajectories contained in the ijth cell, and
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nij represents the total number of endpoints included in the ijth cell. Sparse trajectory coverage of
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the more distant grid cells may result in highly uncertain extreme values of the PSCF. Thus, to
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ensure statistical stability, the PSCF was multiplied by an arbitrary weight function Wij [Eq. (3)], in
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which nave is the average number of trajectory points of all grid cells.
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3 Results and Discussion
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3.1 Annual variation in PAN concentrations at Beijing site
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From 2006 to 2014, the peak concentrations of PAN and PPN were 6–17 ppbv, and 0.6–2.2
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ppbv, respectively. The concentrations of PAN were higher than the reported peak levels in other
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provinces, such as 9.1 ppbv in Lanzhou (Gansu ) from June to July 2006 (Zhang J M et al., 2009);
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5.5 ppbv in Pudong (Shanghai) from April to August 2006 (Han et al., 2013); 4.7 ppbv in Heshan
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(Guangdong) in August 2012 (Zhou et al., 2013) and 3.9 ppbv in Xiamen (Fujian) from April to
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May 2013. The peak concentrations of PAN and PPN in California, USA, decreased from 60–70
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ppbv and 5–6 ppbv in 1960 to 5–10 ppbv and 1 ppbv in 1997, respectively (Grosjean, 2003).
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Therefore, the peak concentration of PAN in Beijing was higher than that in other parts of China,
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but lower than the highest levels reported in the USA.
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The monthly averages of pollutants were calculated based on the observations of PAN, PPN,
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were determined using the linear regression method. The results showed that the concentrations of
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NOx decreased by 1.7 ± 0.7 ppbv /yr (R2 = 0.40; r =-0.69; ~4% yr-1), the concentrations of PAN
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decreased by 0.03 ± 0.02 ppbv/yr (R2 = 0.32; r = -0.56; ~3% yr-1), the concentrations of PPN
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decreased by 0.010 ± 0.005 ppbv/yr (R2 = 0.62; r =-0.78; ~6% yr-1), and the O3 concentrations
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increased at a rate of 1.5 ± 0.5 ppbv/ yr- (R2 = 0.49; r = 0.72; ~4% yr-1).
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The monthly averages of PAN and PPN were lower due to the decreases in NOx and VOCs.
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However, the slight increases in the value of PAN/NOx and the concentration of O3 showed that
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there was no significant decrease in the atmospheric oxidizability. Meanwhile, the decreasing
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concentrations of NOx, CO, and SO2 (Fig. 2, right-hand panel) indicated that the air pollution
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control measures taken by the Beijing authorities in recent years have been effective in controlling
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the emission of primary pollutants.
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Fig. 2 (Left) Variations in monthly average concentrations of PAN, PPN, NOx, and O3 in Beijing in August,
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2006-2014; (right) variations in hourly average concentrations of CO and SO2, 2007-2013.
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During the entire monitoring period, the PAN concentrations reached their highest level in
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2007, which was related to the variation in VOC concentration. In 2007, the concentrations of
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VOCs measured at urban (Beijing, PKU) site were markedly higher than those in 2006, especially
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those of the aromatic hydrocarbons, which increased by about 50%. As the active aromatic 7
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changes in the NOx concentrations and the meteorological conditions, the concentrations of PANs
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were also about 50% higher compared to 2006. Thus, the decrease in PAN concentrations in 2008
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can be mainly attributed to a series of measures taken by the Chinese government to control air
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pollutant emissions during the 2008 Beijing Olympic Games.
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3.2 Correlations of PAN, PPN and O3
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As PAN and PPN are both the products of photochemical reaction, PAN showed a certain
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correlation with PPN (R2 > 0.9). As showed in Fig. 3, the slope of the regression curve of PAN and
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PPN from 2006 to 2014 is between 5.6 and 7.2. PAN and PPN have different sources of precursor
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VOCs. The precursor VOCs of PAN are from both natural sources and human sources, while those
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for PPN are only from the human source. Thus, according to the ratio of PAN/PPN, the main
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sources of VOCs in the local atmosphere can be roughly deduced. The lower the slope of PAN/PPN
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is, the higher the proportion of anthropogenic VOCs is getting involved in the photochemical
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reaction (Williams et al., 1997). When the slope of PPN/PAN is between 5.8 and 7.4, it indicates
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that the photochemical process in this area is mainly affected by anthropogenic VOCs (Roberts et
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al., 1998). Thus, in our research, the photochemical process in Beijing Zhongguancun area was
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mainly affected by anthropogenic VOCs. However, the slope of the regression curve gradually
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increased from 2006 to 2014, indicating the decrease of anthropogenic VOCs and the effect of
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intense air pollution control in Beijing.
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Fig. 3 Correlations of PAN , PPN and O3.
Beside of it, O3 is also a typical product of atmospheric photochemical reaction. The
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concentrations of PAN and O3 are closely related to light conditions and have typical diurnal
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variation characteristics. As showed in Fig. 4, due to the absence of photochemical reaction, almost
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no PAN was produced during the night and the existing PAN was mainly converted to NOx by
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thermal decomposition degradation. The NO/NO2 ratio was gradually increased and the
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concentrations of PAN, PPN and O3 were all in relative low level and reached their lowest between
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6:00am-7:00am. Later, NOx accumulated and its concentration gradually increased, which showed a
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bimodal characteristic with the peak at 23:00pm and 7: 00am. With the strengthening of sunlight
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after 7:00am, NO was gradually oxidized to NO2. The ratio of NO/NO2 decreased and the intensity
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of photochemical reaction increased. The concentrations of PAN, PPN and O3 also started to
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rebound. The concentrations of PAN and PPN reached the peak at 14:00 and the peak value of O3
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was slightly later at 15:00. At this time, the NOx concentration and NO/NO2 ratio were in their
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lowest level.
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Fig. 4 Diurnal cycles of PAN, PPN, O3, NOx, NO/NO2, ambient air temperature (TEMP), relative humidity (RH) and wind speed (WS) in Beijing, August between 2006 and 2014.
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The slope of the regression curve of PAN and O3 concentrations from 2006 to 2013 is in the
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range of 0.02-0.08, as shown in Fig. 3. This result is similar to that reported in other researches,
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such as the average of 0.03 in Mexico City (Marley et al., 2003). Most of the VOCs can be used as
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precursor of O3, while those VOCs which were also the PAN precursor can produce CH3CO free
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radicals. Thus, the ratio of PAN/O3 can roughly determine the composition changes of VOCs. When
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the slope of PAN/O3 decreased, it means that the proportion of VOCs which led to the PAN
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production decreased.
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3.3 Regional transport of PAN
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Based on the monitoring data, the meteorological conditions at the monitoring site such as
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temperature, relative humidity, wind direction, and wind speed were relatively stable from 2006 to
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2013 (Fig. 5). Only the average wind speed in August 2009 was higher than that in the other years.
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ACCEPTED MANUSCRIPT The correlation analysis showed that these meteorological factors had no significant effect on the
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annual variation in PAN concentration; thus, the regional transport of PAN may explain this annual
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variation.
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Fig. 5 Meteorological conditions at Beijing urban site in August between 2006 and 2013.
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The CPF pollution roses of PAN are shown in Fig.6. During the observation period from 2006
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to 2013, high concentrations of PAN mainly came from south (including the southwest and the
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southeast) of the monitoring site. As urban (Beijing, PKU) site was located in the northwest of
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Beijing, the high concentration of short-range transported PAN mainly came from the central area
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of the city, including Xicheng, Dongcheng, Haidian, Shijingshan, and Fengtai districts. The high
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value of CPF in the northeast direction in 2007 and the increased concentration of VOCs mentioned
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above were possibly caused by the large amounts of VOCs released from paint used during the
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construction of the Beijing Olympic venues.
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ACCEPTED MANUSCRIPT 2006
2007 NNE
NW
N
NNW NE
WNW
NW
0
0.2
0.4
WSW SW
E
W
ESE
WSW
SE SSW
1
NE
0
N
0.5 E
0.25
SW
N
NNW NE
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0.15
WSW SW
E
W
ESE
WSW
SE S
NNW
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W
ESE
WSW
SE SSW
S
ESE
WSW
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S
E
SE SSW
NNW
0.2
SSE
S
SSE
N
NNE
NW
0.4
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SSW
0.5
SW
2006 2007 2008 2009 2011 2012 2013
ENE WNW
0
0.25
ESE
NE
SW
SSE
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2006-2013
NW
0.4
NE
NNE
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SW
SSE
SSE
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2013
0.2
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NNE
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SW
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SSE
S
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2012 NNE
WNW
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NW
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SSE
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2011 NNW
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Fig. 6 CPF pollution roses of PAN in Beijing in August between 2006 and 2013.
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Using the HYSPLIT-4 trajectory model, we calculated 5,616 effective backward trajectories
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and clustered them according to year (Fig. 7). In general, the air masses affecting Beijing in August
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each year were divided into two categories: long-range sinking air masses from the north or
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northwest, such as I, and IV, which accounted for one quarter of the total air masses; and
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short-range low air masses from the south, southwest, and southeast, such as II, III and V, which
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accounted for about three quarters of the total air masses. The number of short-range low air masses
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was significantly higher than that of the long-range sinking air masses, indicating that Beijing was
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mainly affected by southeasterly air masses in August during the sampling period.
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The average concentrations of PAN, O3, and NOx with different types of trajectories are listed
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in Table 1. The results showed that the concentrations of PAN, O3, and NO3 in II and III were
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generally higher than those in I. Therefore, although the II and III air masses moved relatively
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slowly, they had a greater impact on the air quality in Beijing compared to the I air masses, which
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moved faster and caused less pollution.
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Table 1. The average concentrations (ppbv) of PAN, O3, and NOx in different types of trajectories in August
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between 2006 and 2013
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II
III
2006
0.86
1.90
0.89
2007
1.32
2.42
2.51
2008
0.71
2009
1.01
0.73 0.72
1.37
1.32
0.89
1.19
2013
0.96
1.20
2014
0.61
1.32
Average
0.93
2006
15.60
2007
25.30
2008
31.45
2009
41.01
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2014 Average
0.88 1.35
0.57
1.09
0.30 1.27
0.87
II
III
IV
V
40.00
24.13
22.23
27.07
35.39
40.20
41.51
27.66
40.94
36.30
42.12
43.10
45.78
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1.32
39.80
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31.51
40.70
35.82
40.73
36.59
I
II
III
IV
V
2006
42.88
40.79
43.98
2007
31.49
48.83
39.95
2008
20.11
2009
33.70
NOx Year
2011
44.24
24.37 32.66
31.71
34.51
33.49
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21.35 31.26 32.40
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23.06
29.83
2013
31.50
27.28
30.50
33.34
26.87 19.66
2014 Average
31.62
25.41
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The PSCF of the high-concentration PAN was calculated based on the trajectories of the air
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masses and the PAN monitoring data. The annual PSCF distribution is shown in Fig. 7. A higher
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PSCF value indicated greater contribution of a specific grid point to the Beijing urban area. High
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PSCF values were mainly located in southern Beijing. The main potential sources of high
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concentrations of PAN were the industrial areas in neighborhoods including the Daxing and
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Fangshan districts in Beijing, Baoding and Langfang in Hebei, and an industrial park in Tianjin.
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Fig. 7 Annual PSCF distribution and trajectory results in August between 2006 and 2014.
3.4 Simultaneous monitoring of Beijing and Hebei sites
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The air quality of neighboring areas had a significant impact on Beijing air quality. To
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investigate the mechanisms of this influence, a large-scale simultaneous observation project called 14
ACCEPTED MANUSCRIPT CAREBeijing-NCP-2014 (Campaign of Air Quality Research in Beijing and North China Plain
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2014), a collaboration of several research institutions, was implemented that examined the various
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pollutants in the neighboring areas of Beijing between June and July 2014. This monitoring project
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provided a significant contribution to elucidating the status and formation mechanisms of
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photochemical pollution in these areas.
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The daily averages of the PAN concentrations during the monitoring period are shown in Fig. 8.
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During this period, the average concentration of PAN at the urban site was 1.5 ppbv, with a
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maximum value of 6.6 ppbv; the daily average fluctuated in the range of 0.5–3.0 ppbv. The average
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concentration of PAN at the rural site was 1.7 ppbv, with a maximum value of 7.1 ppbv; the daily
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average fluctuated in the range of 0.7–3.1 ppbv. The concentrations of PAN detected in Hebei
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(Wangdu) were significantly higher than those in other regions of China, indicating high levels of
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photochemical pollution in Hebei.
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Fig. 8 Comparison of the daily average PAN concentrations at the Beijing (PKU) and Hebei
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(Wangdu) sites (the two ends of the error line represent the maximum and minimum values,
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respectively).
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From Fig. 8, it can be seen that the trends in the daily average PAN concentrations at the two
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sites are consistent. During the period from June 13 to June 19, high concentrations were observed
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at both sites, which indicated high pollution-level conditions, and the PAN concentrations were
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similar at the two sites. However, the concentrations at the rural (Hebei, Wangdu) site were 15
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generally higher than those at the urban (Beijing, PKU) site, implying that photochemical pollution
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occurred across the entire North China Plain and that the pollutants were transported northward.
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The high levels of photochemical pollution were mainly due to straw burning during the wheat
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harvest season.
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4 Conclusions
The peak concentrations of PAN and PPN in Beijing during the summertime from 2006 to
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2014 were 6–17 ppbv, and 0.6–2.2 ppbv, respectively. The concentrations of PAN in Beijing were
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higher than those recorded in other provinces. The O3 concentrations increased at a rate of 1.5
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ppbv/yr (~4% yr-1), the NOx concentrations decreased at a rate of 1.7 ppbv/yr (~4% yr-1), and the
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PAN concentrations decreased at a rate of 0.03 ppbv/yr (~3% yr-1), which suggests that the
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measures taken to control NOx during this period were effective in controlling the PAN
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concentrations, but more effective control of VOC emissions and NOx concentrations is necessary
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to reduce O3 concentrations.
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The CPF pollution roses showed that the high concentrations of PAN at the urban (Beijing,
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PKU) site were mainly derived from the central area of Beijing, including the Xicheng, Dongcheng,
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Haidian, Shijingshan, and Fengtai districts. Additionally, the PSCF maps revealed that the potential
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pollution source areas were concentrated in the southern region of Beijing and that the high
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pollution-level conditions between June 13 and June 19 characterized by high concentrations of
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PAN in Beijing were partly due to air mass transport from Hebei.
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Acknowledgment
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Funding This work was supported by the "State Key R & D Program, Impact of Reactive Organic
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Compounds on Air Quality and Environmental Benefits", 2016YFC0202200
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(PAN) and peroxypropionyl nitrate (PPN) in the Pearl River Delta, China. International Journal of
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acetyl nitrate formation. Environmental Pollution, 2014, 195: 39-47.
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PAN and PPN in Beijing. Acta Scientiarum Naturalium Universitatis Pekinensis, 2009, (1):
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ACCEPTED MANUSCRIPT Zhang G, Mu Y, Zhou L, et al. Summertime distributions of peroxyacetyl nitrate (PAN) and
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peroxypropionyl nitrate (PPN) in Beijing: Understanding the sources and major sink of PAN.
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Atmospheric Environment, 2015, 103(1):289-296.
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Zhang H L, Xu X B, Lin W L, et al. Wintertime peroxyacetyl nitrate (PAN) in the megacity Beijing:
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role of photochemical and meteorological processes. Journal of Environmental Sciences (China),
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Zhang J M, Wang T, Ding A J, et al. Continuous measurement of peroxyacetyl nitrate (PAN) in
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suburban and remote areas of western China. Atmospheric Environment, 2009, 43(2): 228-237.
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Zhang Q, Yuan B, Shao M, et al. Variations of ground-level O3 and its precursors in Beijing in
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summertime between 2005 and 2011. Atmospheric Chemistry and Physics Discussions, 2014, 14(1):
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1019-1050.
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Zhou Y, Yue D L, Zhong L J, et al. Properties of atmospheric PAN pollution in Heshan during
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24-27.
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Highlights • Annual variation in PAN concentrations of Beijing was monitored from 2006 to 2014. • Main potential sources of high concentrations of PAN in Beijing was located. • Regional transport of PAN between Beijing and Hebei Province was analyzed.
S1352-2310(17)30502-2
DOI:
10.1016/j.atmosenv.2017.07.053
Reference:
AEA 15467
To appear in:
Atmospheric Environment
Received Date: 13 December 2016 Revised Date:
26 July 2017
Accepted Date: 29 July 2017
Please cite this article as: Zhang, B., Zhao, B., Zuo, P., Zhi, H., Zhang, J., Ambient peroxyacyl nitrate concentration and regional transportation in Beijing, Atmospheric Environment (2017), doi: 10.1016/ j.atmosenv.2017.07.053. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Ambient Peroxyacyl Nitrate Concentration and Regional Transportation in
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Beijing
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Boya Zhang1*, Bu Zhao2*, Peng Zuo1, Huang Zhi1, Jianbo Zhang1
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1 State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of
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Environmental Sciences and Engineering, Peking University, Beijing, 100871, P.R.China;
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[email protected] (B.Z.), [email protected] (J.Z), [email protected] (P.Z.),
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[email protected] (Z.H)
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2 School of Environment, Tsinghua University, Beijing 100084;
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P.R.China;[email protected] (B.Z.)
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* These authors contributed equally to this work.
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Corresponding Author:
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Jianbo Zhang, State Key Joint Laboratory of Environmental Simulation and Pollution Control,
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College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, P.R.
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China
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Tel: +86-13661161078; E-mail: [email protected]
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ACCEPTED MANUSCRIPT Abstract: Peroxyacyl nitrates (PANs) are photochemical secondary pollutants that play a key role
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in the atmospheric chemistry of the troposphere. However, there have been few studies on the
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long-term variation and inter-regional transport of PANs. In this study, summertime ambient PAN
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concentrations were monitored at urban and rural sites in Beijing and Hebei, China, between 2006
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and 2014. In Beijing, the peak concentrations of PAN and PPN were in the range of 6–17 ppbv and
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0.6–2.2 ppbv, respectively, higher than concentrations in other provinces. The nitrogen oxide (NOx)
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concentration decreased at a rate of 1.7 ppbv/yr (~4% yr-1), and the PAN concentration decreased at
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a rate of 0.03 ppbv/yr (~3% yr-1), while the ozone (O3) concentration increased at a rate of 1.5
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ppbv/yr (~4% yr-1). Trajectory clustering analyses showed that high concentrations of PAN were
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mainly affected by low air masses transported medium/short distances from South Beijing, and the
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potential source contribution function maps showed that the likely pollution source area was
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concentrated in the southern region of Beijing. These findings provide a theoretical basis for
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pollution control in this region.
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Key words: PAN; concentration; CPF; PSCF; regional transport
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1 Introduction
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Peroxyacyl nitrates (PANs, RC(O)OONO2), secondary pollutants produced by a photochemical
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reaction between nitrogen oxide (NOx) and volatile organic compounds (VOCs), play a key role in
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the atmospheric chemistry of the troposphere. As there are no direct anthropogenic emissions, PANs
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are the ideal indicators of atmospheric photochemical pollution (Fischer et al., 2014; Tang et al.,
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2006; Kleindienst, 1994). Among PANs, peroxyacetyl nitrate (PAN, R=CH3) and peroxypropionyl
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nitrate (PPN, R=CH3CH2) are the most important substances with the highest concentrations in the
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atmosphere (Seinfeld and Pandis, 2012). PANs have many toxic effect including irritation,
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mutagenicity and chromosome teratogenicity (Dugger et al., 1963), which may have adverse effects
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on plant growth and human health at high concentrations (Vyskocil et al., 1998). Furthermore, PAN
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is also an important reservoir of tropospheric NOx (NOx = NO + NO2) (Singh et al., 1985), which is
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stable at low temperatures, but can be transported by air masses and can generate NO2 through
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thermal decomposition. This reaction changes the distribution of the ozone (O3) and hydroxyl (OH)
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radicals affecting the atmospheric photochemical pollution levels of different regions (Nielsen et al.,
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1981). Monitoring studies during recent decades have shown that PANs are ubiquitous in the global
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atmosphere. Existing data show that, although concentrations in polar regions are relatively low, the
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peak concentration of PANs in the atmosphere is generally at ppbv level (Fadnavis et al.,2014;
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Pandey et al., 2014; Phillips et al., 2013). The basic physical and chemical properties of PANs also
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determine that their long-distance transport with air masses affects photochemical reactions in other
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regions. This means that atmospheric photochemical pollutants such as PAN can be transported
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between rural areas and cities. The first studies related to PANs in China were conducted in the
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1990s, and the number of studies has been increasing in recent years (Zhang G et al., 2014; Zhang
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G et al., 2015; Zhang H L et al., 2014; Xue et al., 2014; Gao et al., 2009; Williams et al., 2000).
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PANs have been monitored in various provinces including Gansu (Zhang J M et al., 2009),
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Shanghai (Han et al., 2013), Guangdong (Wang et al., 2010; Zhou et al., 2013), and Fujian (Wang et
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al., 2014). However, the monitoring sites in these studies were widely scattered, and the monitoring
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periods were too short, so the data only reflected the local concentration levels at a specific time.
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There have been few studies on the long-term variation and inter-regional transport of PANs in
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China.
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In this study, long-term PAN atmospheric concentrations in summer in Beijing were observed
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and variations in concentration were analyzed. By calculating the conditional probability function
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(CPF) and the potential source contribution function (PSCF), we analyzed the local pollution
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emissions and regional pollution transport, and evaluated the level of atmospheric photochemical
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pollution to provide a theoretical basis for pollution control in this region.
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2 Methods and Materials
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2.1 Monitoring sites and instrument
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The urban site monitoring was conducted in August between 2006 and 2014. The site (39.99°N,
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116.31°E) was located on the top of the Science Building (∼25 m above ground level [AGL]) at
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Peking University (PKU) at the eastern end of Zhongguancun Street, north of the fourth ring road
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(Fig. 1). This urban site was surrounded by low university buildings to the north and west. There
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was no major source of pollution around the site. The monitoring data included concentrations of 3
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[temperature (TEMP), relative humidity (RH), wind speed (WS), and wind direction (WD)] which
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are shown in Supporting Information (Table. S1). The rural site monitoring was conducted from
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June 4 to July 8, 2014. The observation site (38.66°N, 115.21°E) was located in Wangdu County,
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Baoding, Hebei Province, approximately 180 km from urban (Beijing, PKU) site (Fig. 1). This rural
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site was distant from urban areas and was located in agricultural land. Monitoring data included SO2,
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CO, CO2, CH4, NH3, NOx, HOx, HONO, HNO3, NO3, N2O5, PAN, VOCs, O3, and PM2.5.
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Fig. 1 Location of the sampling site in Beijing and Hebei
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PAN and PPN were measured using a PAN online monitor (Scott-Marrin, Inc., CA, USA). The
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selected column consisted of a 0.53-mm-inner diameter fused silica capillary coated with 1-μm
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cross-linked liquid-phase trifluoropropyl silicone (RTX-200), whose temperature was controlled at
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about 15°C. The temperature of the electron capture detector (ECD) was kept at 40°C. The carrier
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gas and tail gas were high-purity helium and high-purity nitrogen, respectively. The detection limit
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of the instrument was 5–10 pptv, and the time resolution was 5 minutes. PAN standard gas was
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prepared using the following process: Nitric oxide standard gas was mixed with acetone standard
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gas (Scott-Marrin, Inc.) and the mixture was placed under ultraviolet light (wavelength, 285 nm) to
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complete irradiation photolysis. The product was then mixed with PAN-free zero gas. PPN standard
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gas was prepared from PPN liquid solution using the volatile sources. Details of the instruments and
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calibration process are given in previous reports by Williams and Yang (Williams et al., 2000; Yang
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et al., 2009). O3, NOx, SO2, CO, and PM2.5 were measured using a Model 49i Ozone Analyzer, Model
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42i-TL Nitrogen Oxide Analyzer, Model 43i-TLE Sulfur Dioxide Analyzer, Model 48C Carbon
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Monoxide Analyzer, and a TEOM1400a Particulate Matter Monitor (Thermo Fisher Scientific, MA,
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USA), respectively (Zhang Q et al., 2014).
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2.2 Analysis of regional pollution transportation
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1）CPF pollution roses
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To examine the effects of local emissions on PAN concentrations, we calculated pollution roses
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based on the PAN concentration, wind direction, and wind speed data during the observation period.
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In this study, wind directions were divided into 16 sectors (Dimitriou and Kassomenos, 2015). The
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pollution roses were given by the following equation:
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mi ni
(1)
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where mi represents the number of exceedances of an hourly PAN threshold (85th percentile)
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concentration during the prevalence of winds from the (i) Δθ sector, and ni represents the total
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number of hourly data from the same wind sector. Hourly wind speed values equal to or less than
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0.3 m/s were defined as calm conditions and were not included in the CPF results.
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2）Cluster analysis and PSCF
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Meteorological data were obtained from the Global Data Assimilation System (GDAS) of the
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US National Center for Environmental Prediction (NCEP). Using the Trajstas software program
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(Wang et al., 2009) and the HYSPLIT-4 trajectory model (Draxler and Hess, 1997), we calculated
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the 24h backward trajectories of the air masses arriving at the monitoring site from 2006 to 2014,
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using a time interval of 1 h and a height of 25 m AGL. The major air pollutant transmission path
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and potential sources were determined by cluster analysis and PSCF.
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The PSCF was based on the development of the CPF to estimate the potential source areas.
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and the pollutant concentrations at the monitoring site. The study area (38–42°N, 114–118°E) was
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analyzed on a 0.1°×0.1° resolution grid, and a threshold (85th percentile) was set for the PAN
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concentration. When the corresponding PAN concentration was higher than this threshold, the
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trajectory was confirmed as a contaminant trajectory. The PSCF was defined by Eq. (2), as follows: PSCFij
1.0 0.7 Wij 0.4 0.2
nij
(2)
3nave nij 1.5nave nij 3nave nave nij 1.5nave nij nave
(3)
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mij
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where mij represents the number of endpoints belonging to trajectories contained in the ijth cell, and
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nij represents the total number of endpoints included in the ijth cell. Sparse trajectory coverage of
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the more distant grid cells may result in highly uncertain extreme values of the PSCF. Thus, to
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ensure statistical stability, the PSCF was multiplied by an arbitrary weight function Wij [Eq. (3)], in
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which nave is the average number of trajectory points of all grid cells.
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3 Results and Discussion
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3.1 Annual variation in PAN concentrations at Beijing site
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From 2006 to 2014, the peak concentrations of PAN and PPN were 6–17 ppbv, and 0.6–2.2
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ppbv, respectively. The concentrations of PAN were higher than the reported peak levels in other
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provinces, such as 9.1 ppbv in Lanzhou (Gansu ) from June to July 2006 (Zhang J M et al., 2009);
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5.5 ppbv in Pudong (Shanghai) from April to August 2006 (Han et al., 2013); 4.7 ppbv in Heshan
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(Guangdong) in August 2012 (Zhou et al., 2013) and 3.9 ppbv in Xiamen (Fujian) from April to
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May 2013. The peak concentrations of PAN and PPN in California, USA, decreased from 60–70
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ppbv and 5–6 ppbv in 1960 to 5–10 ppbv and 1 ppbv in 1997, respectively (Grosjean, 2003).
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Therefore, the peak concentration of PAN in Beijing was higher than that in other parts of China,
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but lower than the highest levels reported in the USA.
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The monthly averages of pollutants were calculated based on the observations of PAN, PPN,
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were determined using the linear regression method. The results showed that the concentrations of
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NOx decreased by 1.7 ± 0.7 ppbv /yr (R2 = 0.40; r =-0.69; ~4% yr-1), the concentrations of PAN
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decreased by 0.03 ± 0.02 ppbv/yr (R2 = 0.32; r = -0.56; ~3% yr-1), the concentrations of PPN
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decreased by 0.010 ± 0.005 ppbv/yr (R2 = 0.62; r =-0.78; ~6% yr-1), and the O3 concentrations
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increased at a rate of 1.5 ± 0.5 ppbv/ yr- (R2 = 0.49; r = 0.72; ~4% yr-1).
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The monthly averages of PAN and PPN were lower due to the decreases in NOx and VOCs.
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However, the slight increases in the value of PAN/NOx and the concentration of O3 showed that
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there was no significant decrease in the atmospheric oxidizability. Meanwhile, the decreasing
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concentrations of NOx, CO, and SO2 (Fig. 2, right-hand panel) indicated that the air pollution
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control measures taken by the Beijing authorities in recent years have been effective in controlling
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the emission of primary pollutants.
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Fig. 2 (Left) Variations in monthly average concentrations of PAN, PPN, NOx, and O3 in Beijing in August,
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2006-2014; (right) variations in hourly average concentrations of CO and SO2, 2007-2013.
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During the entire monitoring period, the PAN concentrations reached their highest level in
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2007, which was related to the variation in VOC concentration. In 2007, the concentrations of
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VOCs measured at urban (Beijing, PKU) site were markedly higher than those in 2006, especially
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those of the aromatic hydrocarbons, which increased by about 50%. As the active aromatic 7
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changes in the NOx concentrations and the meteorological conditions, the concentrations of PANs
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were also about 50% higher compared to 2006. Thus, the decrease in PAN concentrations in 2008
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can be mainly attributed to a series of measures taken by the Chinese government to control air
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pollutant emissions during the 2008 Beijing Olympic Games.
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3.2 Correlations of PAN, PPN and O3
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As PAN and PPN are both the products of photochemical reaction, PAN showed a certain
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correlation with PPN (R2 > 0.9). As showed in Fig. 3, the slope of the regression curve of PAN and
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PPN from 2006 to 2014 is between 5.6 and 7.2. PAN and PPN have different sources of precursor
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VOCs. The precursor VOCs of PAN are from both natural sources and human sources, while those
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for PPN are only from the human source. Thus, according to the ratio of PAN/PPN, the main
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sources of VOCs in the local atmosphere can be roughly deduced. The lower the slope of PAN/PPN
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is, the higher the proportion of anthropogenic VOCs is getting involved in the photochemical
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reaction (Williams et al., 1997). When the slope of PPN/PAN is between 5.8 and 7.4, it indicates
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that the photochemical process in this area is mainly affected by anthropogenic VOCs (Roberts et
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al., 1998). Thus, in our research, the photochemical process in Beijing Zhongguancun area was
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mainly affected by anthropogenic VOCs. However, the slope of the regression curve gradually
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increased from 2006 to 2014, indicating the decrease of anthropogenic VOCs and the effect of
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intense air pollution control in Beijing.
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Fig. 3 Correlations of PAN , PPN and O3.
Beside of it, O3 is also a typical product of atmospheric photochemical reaction. The
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concentrations of PAN and O3 are closely related to light conditions and have typical diurnal
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variation characteristics. As showed in Fig. 4, due to the absence of photochemical reaction, almost
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no PAN was produced during the night and the existing PAN was mainly converted to NOx by
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thermal decomposition degradation. The NO/NO2 ratio was gradually increased and the
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concentrations of PAN, PPN and O3 were all in relative low level and reached their lowest between
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6:00am-7:00am. Later, NOx accumulated and its concentration gradually increased, which showed a
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bimodal characteristic with the peak at 23:00pm and 7: 00am. With the strengthening of sunlight
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after 7:00am, NO was gradually oxidized to NO2. The ratio of NO/NO2 decreased and the intensity
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of photochemical reaction increased. The concentrations of PAN, PPN and O3 also started to
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rebound. The concentrations of PAN and PPN reached the peak at 14:00 and the peak value of O3
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was slightly later at 15:00. At this time, the NOx concentration and NO/NO2 ratio were in their
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lowest level.
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Fig. 4 Diurnal cycles of PAN, PPN, O3, NOx, NO/NO2, ambient air temperature (TEMP), relative humidity (RH) and wind speed (WS) in Beijing, August between 2006 and 2014.
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The slope of the regression curve of PAN and O3 concentrations from 2006 to 2013 is in the
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range of 0.02-0.08, as shown in Fig. 3. This result is similar to that reported in other researches,
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such as the average of 0.03 in Mexico City (Marley et al., 2003). Most of the VOCs can be used as
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precursor of O3, while those VOCs which were also the PAN precursor can produce CH3CO free
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radicals. Thus, the ratio of PAN/O3 can roughly determine the composition changes of VOCs. When
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the slope of PAN/O3 decreased, it means that the proportion of VOCs which led to the PAN
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production decreased.
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3.3 Regional transport of PAN
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Based on the monitoring data, the meteorological conditions at the monitoring site such as
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temperature, relative humidity, wind direction, and wind speed were relatively stable from 2006 to
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2013 (Fig. 5). Only the average wind speed in August 2009 was higher than that in the other years.
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annual variation in PAN concentration; thus, the regional transport of PAN may explain this annual
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variation.
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Fig. 5 Meteorological conditions at Beijing urban site in August between 2006 and 2013.
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The CPF pollution roses of PAN are shown in Fig.6. During the observation period from 2006
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to 2013, high concentrations of PAN mainly came from south (including the southwest and the
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southeast) of the monitoring site. As urban (Beijing, PKU) site was located in the northwest of
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Beijing, the high concentration of short-range transported PAN mainly came from the central area
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of the city, including Xicheng, Dongcheng, Haidian, Shijingshan, and Fengtai districts. The high
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value of CPF in the northeast direction in 2007 and the increased concentration of VOCs mentioned
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above were possibly caused by the large amounts of VOCs released from paint used during the
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construction of the Beijing Olympic venues.
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ACCEPTED MANUSCRIPT 2006
2007 NNE
NW
N
NNW NE
WNW
NW
0
0.2
0.4
WSW SW
E
W
ESE
WSW
SE SSW
1
NE
0
N
0.5 E
0.25
SW
N
NNW NE
0
0.15
WSW SW
E
W
ESE
WSW
SE S
NNW
N
E
W
ESE
WSW
SE SSW
S
ESE
WSW
0
S
E
SE SSW
NNW
0.2
SSE
S
SSE
N
NNE
NW
0.4
SE
SSW
0.5
SW
2006 2007 2008 2009 2011 2012 2013
ENE WNW
0
0.25
ESE
NE
SW
SSE
W
ENE
2006-2013
NW
0.4
NE
NNE
ENE WNW
SW
SSE
SSE
S
2013
0.2
E
SE SSW
NE
0
NNE
E
W
ESE
WSW
0
0.25
NE ENE 0.5
E
ESE SW
SE SSW
S
SSE
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0.5
WSW
NNE
NW
0.3
0.25
SW
ENE WNW
W
0
SSE
S
N
NW ENE WNW
2012 NNE
WNW
NNW NE
W
SE SSW
NW
2009 NNE
NW
ESE
SSE
S
N
ENE WNW
2011 NNW
3
NNW
ENE WNW
W
2
2008 NNE
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Fig. 6 CPF pollution roses of PAN in Beijing in August between 2006 and 2013.
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Using the HYSPLIT-4 trajectory model, we calculated 5,616 effective backward trajectories
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and clustered them according to year (Fig. 7). In general, the air masses affecting Beijing in August
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each year were divided into two categories: long-range sinking air masses from the north or
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northwest, such as I, and IV, which accounted for one quarter of the total air masses; and
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short-range low air masses from the south, southwest, and southeast, such as II, III and V, which
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accounted for about three quarters of the total air masses. The number of short-range low air masses
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was significantly higher than that of the long-range sinking air masses, indicating that Beijing was
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mainly affected by southeasterly air masses in August during the sampling period.
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The average concentrations of PAN, O3, and NOx with different types of trajectories are listed
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in Table 1. The results showed that the concentrations of PAN, O3, and NO3 in II and III were
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generally higher than those in I. Therefore, although the II and III air masses moved relatively
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slowly, they had a greater impact on the air quality in Beijing compared to the I air masses, which
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moved faster and caused less pollution.
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Table 1. The average concentrations (ppbv) of PAN, O3, and NOx in different types of trajectories in August
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between 2006 and 2013
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II
III
2006
0.86
1.90
0.89
2007
1.32
2.42
2.51
2008
0.71
2009
1.01
0.73 0.72
1.37
1.32
0.89
1.19
2013
0.96
1.20
2014
0.61
1.32
Average
0.93
2006
15.60
2007
25.30
2008
31.45
2009
41.01
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2011
2014 Average
0.88 1.35
0.57
1.09
0.30 1.27
0.87
II
III
IV
V
40.00
24.13
22.23
27.07
35.39
40.20
41.51
27.66
40.94
36.30
42.12
43.10
45.78
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1.46
1.32
39.80
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0.78
1.38
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O3 Year
2.07
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V
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0.98
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Year
31.06 46.14 32.75 44.06 27.70
31.51
40.70
35.82
40.73
36.59
I
II
III
IV
V
2006
42.88
40.79
43.98
2007
31.49
48.83
39.95
2008
20.11
2009
33.70
NOx Year
2011
44.24
24.37 32.66
31.71
34.51
33.49
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21.35 31.26 32.40
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29.83
2013
31.50
27.28
30.50
33.34
26.87 19.66
2014 Average
31.62
25.41
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33.76
The PSCF of the high-concentration PAN was calculated based on the trajectories of the air
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masses and the PAN monitoring data. The annual PSCF distribution is shown in Fig. 7. A higher
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PSCF value indicated greater contribution of a specific grid point to the Beijing urban area. High
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PSCF values were mainly located in southern Beijing. The main potential sources of high
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concentrations of PAN were the industrial areas in neighborhoods including the Daxing and
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Fangshan districts in Beijing, Baoding and Langfang in Hebei, and an industrial park in Tianjin.
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Fig. 7 Annual PSCF distribution and trajectory results in August between 2006 and 2014.
3.4 Simultaneous monitoring of Beijing and Hebei sites
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The air quality of neighboring areas had a significant impact on Beijing air quality. To
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investigate the mechanisms of this influence, a large-scale simultaneous observation project called 14
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2014), a collaboration of several research institutions, was implemented that examined the various
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pollutants in the neighboring areas of Beijing between June and July 2014. This monitoring project
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provided a significant contribution to elucidating the status and formation mechanisms of
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photochemical pollution in these areas.
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The daily averages of the PAN concentrations during the monitoring period are shown in Fig. 8.
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During this period, the average concentration of PAN at the urban site was 1.5 ppbv, with a
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maximum value of 6.6 ppbv; the daily average fluctuated in the range of 0.5–3.0 ppbv. The average
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concentration of PAN at the rural site was 1.7 ppbv, with a maximum value of 7.1 ppbv; the daily
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average fluctuated in the range of 0.7–3.1 ppbv. The concentrations of PAN detected in Hebei
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(Wangdu) were significantly higher than those in other regions of China, indicating high levels of
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photochemical pollution in Hebei.
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Fig. 8 Comparison of the daily average PAN concentrations at the Beijing (PKU) and Hebei
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(Wangdu) sites (the two ends of the error line represent the maximum and minimum values,
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respectively).
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From Fig. 8, it can be seen that the trends in the daily average PAN concentrations at the two
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sites are consistent. During the period from June 13 to June 19, high concentrations were observed
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at both sites, which indicated high pollution-level conditions, and the PAN concentrations were
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similar at the two sites. However, the concentrations at the rural (Hebei, Wangdu) site were 15
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generally higher than those at the urban (Beijing, PKU) site, implying that photochemical pollution
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occurred across the entire North China Plain and that the pollutants were transported northward.
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The high levels of photochemical pollution were mainly due to straw burning during the wheat
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harvest season.
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4 Conclusions
The peak concentrations of PAN and PPN in Beijing during the summertime from 2006 to
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2014 were 6–17 ppbv, and 0.6–2.2 ppbv, respectively. The concentrations of PAN in Beijing were
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higher than those recorded in other provinces. The O3 concentrations increased at a rate of 1.5
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ppbv/yr (~4% yr-1), the NOx concentrations decreased at a rate of 1.7 ppbv/yr (~4% yr-1), and the
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PAN concentrations decreased at a rate of 0.03 ppbv/yr (~3% yr-1), which suggests that the
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measures taken to control NOx during this period were effective in controlling the PAN
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concentrations, but more effective control of VOC emissions and NOx concentrations is necessary
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to reduce O3 concentrations.
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The CPF pollution roses showed that the high concentrations of PAN at the urban (Beijing,
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PKU) site were mainly derived from the central area of Beijing, including the Xicheng, Dongcheng,
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Haidian, Shijingshan, and Fengtai districts. Additionally, the PSCF maps revealed that the potential
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pollution source areas were concentrated in the southern region of Beijing and that the high
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pollution-level conditions between June 13 and June 19 characterized by high concentrations of
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PAN in Beijing were partly due to air mass transport from Hebei.
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Acknowledgment
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Funding This work was supported by the "State Key R & D Program, Impact of Reactive Organic
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Compounds on Air Quality and Environmental Benefits", 2016YFC0202200
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Highlights • Annual variation in PAN concentrations of Beijing was monitored from 2006 to 2014. • Main potential sources of high concentrations of PAN in Beijing was located. • Regional transport of PAN between Beijing and Hebei Province was analyzed.