The detailed formation mechanism of an increased number of haze
events in China is still not very clear. Here, we found that reduced surface
visibility from 1980 to 2010 and an increase in satellite-derived columnar
concentrations of inorganic precursors from 2002 to 2012 are connected with each
other. Typically, higher inorganic mass fractions lead to increased aerosol
water uptake and light-scattering ability in elevated relative humidity.
Satellite observation of aerosol precursors of NO2 and
SO2 showed increased concentrations during the study period. Our
in situ measurement of aerosol chemical composition in Beijing also confirmed
increased contribution of inorganic aerosol fraction as a function of
the increased particle pollution level. Our investigations demonstrate that the
increased inorganic fraction in the aerosol particles is a key component in
the frequently occurring haze days during the study period, and particularly
the reduction of nitrate, sulfate and their precursor gases would contribute
towards better visibility in China.
Introduction
As one of the most heavily polluted regions in the world, China has suffered
from air pollution for decades (Hao et al., 2007; Zhang et al., 2015).
Aerosol particles, as a major air pollutant, have significant effects on human
health (Lelieveld et al., 2015). The general public and the central
government of China have realized the severe situation and have taken some
actions to improve the air quality nationwide in recent years. For
example, the state council published a plan for air pollution control, in
September 2013, aimed at reducing PM2.5 concentrations by
10 %–25 % in different regions of
China. The successful implementation requires a sufficient knowledge of haze
formation mechanisms (Kulmala, 2015) and a comprehensive observation network
(Kulmala, 2018). Our understanding of haze events with high PM2.5
concentrations in China is still limited due to the spatial–temporal
variation of aerosol properties and limited observation information (Wang et
al., 2016). Recent studies found that secondary aerosol components were
important during the intense haze events in Beijing, Xi'an, Chengdu and
Guangzhou during January of 2013, and the reduction of aerosol precursors is
a key step to reduce particle pollution (Guo et al., 2014; Huang et al.,
2014). The analysis of longer time series data from Nanjing shows that
secondary particles are typically dominating even the number concentrations
in polluted conditions (Kulmala, 2016). A recent study has suggested
significantly decreased trends of PM2.5 and SO2 in China from
2015 to 2017 by analyzing data sets from the Ministry of Ecology and Environment of
China (Silver et al., 2018). The column NO2 concentration obtained
from the Ozone Monitoring Instrument (OMI) showed an increased trend during 2005–2011, while a decreasing trend
was shown during 2012–2015 (Itahashi et al., 2016). The SO2 concentration
has decreased around 50 % from 2012 to 2015 in the North China Plain due to
economic slowdown and government efforts to restrain emissions from power
and industrial sectors (Krotkov et al., 2016). However, the most abundant
mass fractions of atmospheric aerosol are inorganic and organic components,
which have large spatiotemporal variation (Jimenez et al., 2009).
Identifying the most abundant as well as critical aerosol species that
contribute to the haze formation in a long time perspective is important to
draw up effective plans for the air pollution control.
Here, comprehensive data sets were used to reveal that an increasing trend
of inorganic components in atmospheric aerosol may be a pivotal factor, at
least, which leads to frequently occurring haze events in China from
1980 to 2010. We suggests that the control of inorganic aerosol components
of nitrate, sulfate and their precursors should be a high priority due to
their strong water uptake abilities and therefore light-scattering ability
in high relative humidity (RH) conditions.
Methodology
The daily averaged visibility and relative humidity data in 262 sites in
China are obtained from the Integrated Surface Dataset (ISD) from the National
Oceanic and Atmospheric Administration National Climate Data Center of the
USA from 1980 to 2010 (https://www.ncdc.noaa.gov/isd, last
access: 30 April 2019). The visibility
observations were made three times a day at 8 h intervals beginning at 00:00 LT by
well-trained technicians. They measured visual range using distinctive
markers, such as tall buildings, mountains and towers, to which the distance
from the meteorological monitoring stations is known.
The distribution of the average surface visibility ratio in dry and
wet conditions based on observations at 262 surface observation sites in
China. The aerosol in the industrialized regions of China in the east are
more hygroscopic than aerosol particles in the west of China.
We quantified the importance of relative humidity to visibility as the
hygroscopic inorganic compounds typically grow in size in high humidity
(Swietlicki et al., 2008). Aerosol size growth and composition change in the
high-humidity condition are highly related to light-scattering ability (Zhang et al.,
2015). Studies always use f(RH), a parameter which is defined as the
ratio of light-scattering coefficient under high RH to that under low RH. f(RH) is a unitless number, which usually ranges from 1 to 2. At ambient RH
around 80 %, a higher f(RH) value usually corresponds to higher
inorganic aerosol fraction, while a lower value usually corresponds to high
organic fraction. The reason is that inorganic aerosol compounds of
nitrate, sulfate and ammonium have stronger water uptake ability than
organic compounds. In addition, the high-humidity condition at ambient RH prefers the formation of inorganic aerosol from precursors of NO2
and SO2 (Wang et al., 2014). In this study, for a given site and
given year, we defined a f(RH)-like parameter, Ri, using the observed
annual visibility (V) as a ratio (Ri) between visibility values from
the surface observation stations, when the daily average RH was below
40 % for more than 20 d. In the corresponding high-humidity cases, daily
RH was between 80 % and 90 % for more
than 20 d each year at a given observation site:
Ri=VdryVwet.
We use this ratio to infer a long trend of aerosol hygroscopicity information.
In addition, we calculate anomaly (A) from the ratio for a given year i
as a difference from the 30-year period (R30yr) from 1980 to 2010:
A=Ri-R30yr.
Our spatial focus is placed on the North China Plain, Yangtze River Plain and
Sichuan Basin due to frequent haze events (Zhang et al., 2012). The stations
in the Pearl River Delta region and other southern China stations were not
included due to limited days with the daily average RH below 40 %.
The atmospheric column amount of NO2 and SO2 data is
obtained from 2002 to 2012 and 2004 to 2012, respectively, from SCIAMACHY
(Scanning Imaging Absorption Spectrometer for Atmospheric Chartography)
satellite products. SCIAMACHY is an atmospheric sensor aboard the European
satellite Envisat. It was launched in March 2002 as a joint project of
Germany, the Netherlands and Belgium. It measures atmospheric absorption in
spectral bands from the ultraviolet to the near infrared (240–2380 nm) and
allows to retrieve atmospheric column concentrations of O3, BrO,
OClO, ClO, SO2, H2CO, NO, NO2, NO3,
CO, CO2, CH4, H2O, N2O, aerosols,
radiation and cloud properties (Boersma et al., 2004). Aerosol chemical
composition from the Goddard Earth Observing System chemical
transport model (GEOS-Chem) combined with satellite aerosol optical depth (AOD) products in China during
1998–2012 is used. The model utilizes assimilated meteorology data and
regional emission inventories with a horizontal resolution of 2∘×2∘ with 47 vertical levels from the surface to 80 km. The
PM2.5 concentration was retrieved from AOD of satellite and the
relationship between PM2.5 and AOD in GEOS-Chem. The detailed
information about the model can be found in Boys et al. (2014). Aerosol
chemical composition of organic aerosol, sulfate, nitrate, ammonium and chloride were
measured with a high-resolution time-of-flight aerosol mass spectrometers
during an intensive campaign in urban Beijing from November 2010 to
January 2011 (DeCarlo et al., 2006). Detailed information on data analysis,
collection efficiencies (CEs) and relative ionization efficiencies is
presented in Zhang et al. (2014).
Anomalies and trends of the ratio of visibility in the North China Plain,
Yangtze River Plain, Sichuan Basin and China as a whole. The relative
contribution of hygroscopic aerosols to the visibility reduction has
increased from 1980 to 2010 in China.
Results and discussionDecreasing trend in visibility in high relative humidity
conditions
According to the geographical division, our study sites are mainly in the North
China Plain (NCP), Sichuan Basin (SCB) and Yangtze River Plain (YRP), as
shown in Fig. 1. The average visibility in low RH in NCP, SCB, YRP and China
is 18.2, 21.4, 19.5 and 23.3 km, while the values in high-RH conditions are
10.6, 13.7, 13.7 and 17.4 km, respectively. In general, visibility in the low-RH
condition has a fluctuating trend, particularly in the North China Plain, Sichuan
Basin and Yangtze River Plain region, whereas visibility in high-RH
conditions showed a decreasing trend, as shown in Fig. S1a and b. The average
ratio of visibility in low RH to that in high RH from 1980 to 2010 is presented
in Fig. 1. The maximum ratios were identified in eastern China and in some
western Chinese cities. Three heavily polluted regions, the North China Plain,
Sichuan Basin and Yangtze River Plain, were identified based on values of high
Ri, which are also consistent with aerosol
mass concentrations and haze-day distributions (van Donkelaar et al., 2010; Xin et al., 2015). That is,
the higher ratios occurred in more severe air pollution areas, like the North
China Plain, Sichuan Basin and the city of Ürümqi, where the contribution of
hygroscopic aerosol is more pronounced in comparison with non-hygroscopic
dust particles. The average Ri values during 1980–1984 in the North China
Plain, Sichuan Basin and Yangtze River Plain are 1.62, 1.41, 1.29 and 1.31,
respectively, contrasting with the values of 1.98, 1.81, 1.70 and 1.52 during
2006–2010. The increments are 22.3 %, 27.3 %, 31 % and 16 %,
respectively. It is worth noting that the Ri in the Yangtze River Plain
region exhibits the most increments, which implies the increased emissions
with rapid economic growth. Long time trends of this ratio at a specific site
can reveal the variation of inorganic aerosol fraction and organic fraction
due to their different hygroscopicity and water uptake capacity and
associated light extinction ability. That is, the mass fractions and
concentrations of sulfate, nitrate and ammonium may have increased over the study
period as they dominate water uptake ability compared with other components
(e.g., organic aerosol, black carbon, dust and metal elements; see Table S1) in the
atmospheric aerosol (Wang et al., 2015). For the selected regions, we have
calculated the anomaly as a regional average, as shown in Fig. 2. The ratio
showed increasing trends over three regions of China and the maximum trends
occurred in the North China Plain with the value of 0.0168 per year, which
indicates an increase of hygroscopic aerosol in these regions during the
30-year observation period.
Trends of NO2 concentration over China from SCIAMACHY for
the years 2002–2012 (1015 mol cm-2).
Trends of SO2 concentration over China from SCIAMACHY for
the years 2004–2012 (1000 × DU, Dobson unit).
To corroborate our results, Yang et al. (2011) showed an increasing fraction
of inorganic components by 20 % in Beijing from 1998 to 2008 using in situ
offline aerosol chemical composition measurement, especially in summer, while
the fractions of hydrophobic components such as organic aerosol and black carbon
decreased in the aerosol phase. A study by Boys et al. (2014) revealed that
increasing fraction of secondary inorganic aerosol is dominated in the
increased mass concentration of PM2.5 in China from 1998 to 2012 using
the GEOS-Chem model combined satellite results. By using observed meteorology
data sets, Fu et al. (2014) revealed that the number of haze days has
significantly increased in the past three decades over the North China Plain due
to the increase in hygroscopic inorganic aerosol composition.
Enhanced emissions of inorganic aerosol precursors
The long-term trends of aerosol precursors and their spatial variability can
improve our understanding of the trends in aerosol chemical composition.
Figures 3 and 4 show atmospheric column trends of NO2 and
SO2 observed from SCIAMACHY. The column NO2 level can be
a good proxy for vehicle and coal burning emissions associated with oil and
coal consumption (Richter et al., 2005). The column amount of NO2
showed pronounced increasing trends in three regions of China, particularly
in northern China with the value of 0.14×1015 mol cm-2 year-1 from
2002 to 2011. This is probably associated with the increase in power plant and
on-road vehicle emissions (Wu et al., 2012; Krotkov et al., 2016). The
average NO2 concentration in northern China increased by more than
2-fold, while the Yangtze River Plain region experienced a considerably
smaller trend in NO2, with the value of 9.7×1015 mol cm-2 in 2010 and 6.4×1015 mol cm-2 in 2002. It is worth noting a decreased trend
occurred during the year 2008, which is mainly due to emission reduction during
the Olympic Games and economic downturn (Lin and McElroy, 2011). As a whole,
the column NO2 concentration in China doubled from 2002 to 2010, with
the values of 1.4×1015 mol cm-2 in 2002 and 2.8×1015 mol cm-2 in 2010, respectively.
Variation of (a)NO2, SO2,
(b) chemical composition and (c) mass fraction of organic aerosol, nitrate, sulfate,
ammonium and chloride with decreased visibility during the intensive campaign
in Beijing.
Relationship between RH and volume fractions of
(a) ammonium sulfate, (b) ammonium nitrate and (c)
organic aerosol.
A schematic picture illustrating the process of enhanced emission of
inorganic aerosol precursors and formation of inorganic aerosol components,
leading to increased hygroscopicity and aerosol water uptake ability, leading
to considerable visibility degradation in China. The plus symbols represent
the strengthening of a specific process.
Figure 4 depicts the trend in SO2 concentration in four regions of
China from 2004 to 2010. The SO2 concentration showed increasing
trends in the North China Plain, Sichuan Basin and Yangtze River Plain but
increased mostly in China from 2004 to 2012. A decreasing trend was observed
during the years 2008 and 2009, especially in the North China Plain. This
may be due to a combination of Chinese economic downturn and emission
reduction during the Olympic Games (Lin and McElroy, 2011) (Wang et al.,
2010). Anyway, as an important aerosol precursor, NO2 showed the
most increasing trend in China from 2002 to 2012, consistent with the trend of
increased aerosol concentration by modelling result (Xing et al., 2015).
Figure S3 shows the annual trends of inorganic aerosol fraction in PM2.5
mass concentration from 1998 to 2012 with the GEOS-Chem model combined with
satellite results in China. The results indicate that the North China Plain area
suffered the most from heavy pollution, consistent with our surface
observations (Xin et al., 2015). Aerosol concentrations have increased
considerably from 1980 to 2010. The modelling combined with satellite results
by Boys et al. (2014) shows that concurrently the fraction of inorganic
aerosol has increased more rapidly. Consequently, the water uptake of the
aerosol has increased, leading to reduced visibility as we suggested, which
is consistent with ground-based observations (Yang et al., 2011).
Validation of increased inorganic aerosol components with elevated air
pollution level with in situ measurement
To validate our hypothesis that the increased inorganic components contribute
to visibility degradation, we used 4 months of aerosol chemical
composition and visibility data from urban Beijing from November 2010 to
February 2011. As shown in Fig. 5, we divided the visibility values into four
bins, which correspond to clean time to heavy pollution time and to
conditions in between. The inorganic aerosol precursors of SO2 and
NO2 nearly doubled as the visibility decreased from more than
10 km (clean time) to less than 2 km (heavily polluted time). At the same
time, the mass concentrations of nitrate, sulfate and ammonium components
increased to 13.5, 15.5 and 10.6 µg m-3, respectively.
Meanwhile, the mass fraction of these inorganics increased from 11.3 % to
17.3 %, from 13.0 % to 19.9 % and from 9.6 % to 13.6 %,
respectively. At the same time, the mass concentration and fraction of
organic components changed from 12.2 to 33.4 µg m-3 and
60 % to 46 %, respectively.
We also investigated the relationship between RH and
volume fractions of ammonium sulfate, ammonium nitrate and organic aerosols
as shown in Fig. 6. The results indicated that ammonium nitrate increased
most significantly with elevated RH. On the contrary, ammonium sulfate, as
another inorganic compound, showed only a moderate positive correlation with
RH and a decrease in the volume fraction was observed in RH values larger
than 75 %. This might be associated with liquid-phase oxidation of
SO2 under the high-RH condition to sulfate aerosol. Increasing RH may
provide more atmospheric oxidants and reaction media for the aqueous-phase
oxidation (Zhang et al., 2015). The volume fraction of organic aerosol showed
a negative correlation with increasing RH, as presented in Fig. 6c, which was
maybe due to a faster increasing volume fraction of inorganic aerosol than
organic aerosol.
This direct observation shows that the contribution of inorganic components
increased during this campaign. It is plausible that the increased
concentrations of SO2 and NO2 are highly associated with
this, giving rise to the long-term trends observed in Fig. 2 (Pan et al.,
2016; Wang et al., 2014).
Conclusion and implication for atmospheric air pollution
control
Atmospheric pollution and associated haze events have a dramatic effect on
climate change, human health and visibility degradation (Ding et al., 2013;
Petäjä et al., 2016; Wang et al., 2015; Zhang et al., 2015). Here,
long-term visibility measurements combined with satellite data sets, in situ
measurements and model results revealed that increased fractions of inorganic
aerosol components in the particle matter are crucial in contributing to more
haze events from 1980 to 2010. In this way, aerosol hygroscopic growth has
occurred in lower relative humidity conditions than before due to more
ammonium nitrate aerosol, and the light-scattering ability of atmospheric
aerosol was enhanced, as shown in Fig. 7. Another mechanism is that high
concentration of NOx can promote the conversion of
SO2 to form sulfate aerosol via aqueous-phase oxidation during
intensive pollution periods (He et al., 2014; Wang et al., 2016). Considering
the vast energy consumption in the future decades and the sources of
inorganic components in atmospheric aerosol, we demonstrate that the
reduction of nitrate, sulfate, ammonium and their precursors should be continued
to obtain better visibility in China.
Data availability
The meteorology data and visibility data were acquired from
the Integrated Surface Dataset (ISD) from the National Oceanic and
Atmospheric Administration National Climate Data Center of the USA
(https://www.ncdc.noaa.gov/isd, NOAA, 2019). The NO2 and
SO2 data from the SCIAMACHY sensor were obtained from
http://www.temis.nl (TEMIS, 2019). The aerosol chemical composition
data can be acquired by requesting them from the corresponding author.
The supplement related to this article is available online at: https://doi.org/10.5194/acp-19-5881-2019-supplement.
Author contributions
YHW had the original idea. LLW and CSG provided and processed
satellite and visibility data. YSW provided measurements of aerosol chemical
composition data. YHW, YSW, LLW, TP and MK interpreted the data and wrote the
paper. All the authors commented on the paper.
Competing interests
The authors declare that they have no conflict of
interest.
Special issue statement
This article is part of the special issue “Pan-Eurasian
Experiment (PEEX)”. It is not associated with a conference.
Acknowledgements
We acknowledge Brian Boys and Randall Martin of Dalhousie University for
providing GEOS-Chem model results in China. We acknowledge the free use of
tropospheric NO2 and SO2 column data from the SCIAMACHY
sensor from http://www.temis.nl, last access: 30 April 2019. This work
was supported by the Ministry of Science and Technology of China
(no. 2017YFC0210000), the National Research Program for key issues in air
pollution control (DQGG0101), the National Natural Science Foundation of
China (no. 41775162) and Academy of Finland via Center of Excellence in
Atmospheric Sciences and the National Natural Science Foundation of China
(41605119).
Review statement
This paper was edited by Dominick Spracklen and reviewed by
two anonymous referees.
References
Boersma, K. F., Eskes, H. J., and Brinksma, E. J.: Error analysis for
tropospheric NO 2 retrieval from space , J. Geophys. Res.-Atmos., 109,
D04311, doi:10.1029/2003jd003962, 2004.
Boys, B. L., Martin, R., van Donkelaar, A., MacDonell, R., Hsu, C., Cooper,
M., Yantosca, R., Lu, Z., G Streets, D., Zhang, Q., and Wang, S.:
Fifteen-Year Global Time Series of Satellite-Derived Fine Particulate Matter,
Environ. Sci. Technol., 48, 11109–11118, 2014.
DeCarlo, P., Kimmel, J., Trimborn, A., Northway, J. M., Jayne, T. J., Aiken,
A., Gonin, M., Fuhrer, K., Horvath, T., Docherty, S. K., Worsnop, R. D., and
Jimenez, L. J.: Field-Deployable, High-Resolution, Time-of-Flight Aerosol Mass
Spectrometer, Anal. Chem., 78, 8281–8289, 2006.
Ding, A. J., Fu, C. B., Yang, X. Q., Sun, J. N., Petäjä, T.,
Kerminen, V.-M., Wang, T., Xie, Y., Herrmann, E., Zheng, L. F., Nie, W., Liu,
Q., Wei, X. L., and Kulmala, M.: Intense atmospheric pollution modifies
weather: a case of mixed biomass burning with fossil fuel combustion
pollution in eastern China, Atmos. Chem. Phys., 13, 10545–10554,
https://doi.org/10.5194/acp-13-10545-2013, 2013.
Fu, G. Q., Xu, W. Y., Yang, R. F., Li, J. B., and Zhao, C. S.: The
distribution and trends of fog and haze in the North China Plain over the
past 30 years, Atmos. Chem. Phys., 14, 11949–11958,
https://doi.org/10.5194/acp-14-11949-2014, 2014.
Guo, S., Hu, M., Zamora, M. L., Peng, J., Shang, D., Zheng, J., Du, Z., Wu,
Z., Shao, M., Zeng, L., Molina, M. J., and Zhang, R.: Elucidating severe
urban haze formation in China, P. Natl. Acad. Sci. USA, 111, 17373–17378,
2014.
Hao, J., He, K., Duan, L., Li, J., and Wang, L.: Air pollution and its
control in China, Front. Environ. Sci. En., 1, 129–142, 2007.He, H., Wang, Y., Ma, Q., Ma, J., Chu, B., Ji, D., Tang, G., Liu, C., Zhang,
H., and Hao, J.: Mineral dust and NOx promote the conversion
of SO2 to sulfate in heavy pollution days, Sci. Rep., 4, 4172,
10.1038/srep04172, 2014.
Huang, R.-J., Zhang, Y., Bozzetti, C., Ho, K. F., Cao, J., Han, Y.,
Daellenbach, K., G Slowik, J., Platt, S., Canonaco, F., Zotter, P., Wolf, R.,
Pieber, S., Bruns, E., Crippa, M., Ciarelli, G., Piazzalunga, A.,
Schwikowski, M., Abbaszade, G., and Prevot, A.: High secondary aerosol
contribution to particulate pollution during haze events in China, Nature,
514, 218–222, 2014.
Itahashi, S., Muto, T., Irie, H., Uno, I., and Kurokawa, J.: Turnaround of
Tropospheric Nitrogen Dioxide Pollution Trends in China, Japan, and South
Korea, Sola, 12, 170–174, doi:10.2151/sola.2016-035, 2016.
Jimenez, J. L., Canagaratna, M. R., Donahue, N. M., Prevot, A. S. H., Zhang,
Q., Kroll, J. H., DeCarlo, P. F., Allan, J. D., Coe, H., Ng, N. L., Aiken, A.
C., Docherty, K. S., Ulbrich, I. M., Grieshop, A. P., Robinson, A. L.,
Duplissy, J., Smith, J. D., Wilson, K. R., Lanz, V. A., Hueglin, C., Sun, Y.
L., Tian, J., Laaksonen, A., Raatikainen, T., Rautiainen, J., Vaattovaara,
P., Ehn, M., Kulmala, M., Tomlinson, J. M., Collins, D. R., Cubison, M. J.,
Dunlea, J., Huffman, J. A., Onasch, T. B., Alfarra, M. R., Williams, P. I.,
Bower, K., Kondo, Y., Schneider, J., Drewnick, F., Borrmann, S., Weimer, S.,
Demerjian, K., Salcedo, D., Cottrell, L., Griffin, R., Takami, A., Miyoshi,
T., Hatakeyama, S., Shimono, A., Sun, J. Y., Zhang, Y. M., Dzepina, K.,
Kimmel, J. R., Sueper, D., Jayne, J. T., Herndon, S. C., Trimborn, A. M.,
Williams, L. R., Wood, E. C., Middlebrook, A. M., Kolb, C. E., Baltensperger,
U., and Worsnop, D. R.: Evolution of Organic Aerosols in the Atmosphere,
Science, 326, 1525–1529, 2009.Krotkov, N. A., McLinden, C. A., Li, C., Lamsal, L. N., Celarier, E. A.,
Marchenko, S. V., Swartz, W. H., Bucsela, E. J., Joiner, J., Duncan, B. N.,
Boersma, K. F., Veefkind, J. P., Levelt, P. F., Fioletov, V. E., Dickerson,
R. R., He, H., Lu, Z., and Streets, D. G.: Aura OMI observations of regional
SO2 and NO2 pollution changes from 2005 to 2015, Atmos. Chem.
Phys., 16, 4605–4629, https://doi.org/10.5194/acp-16-4605-2016, 2016.
Kulmala, M.: China's choking cocktail, Nature, 526, 497–499, 2015.
Kulmala, M.: Build a global Earth observatory, Nature, 553, 21–23, 2018.
Kulmala, M., Luoma, K., Virkkula, A., Petäjä, T., Paasonen, P.,
Kerminen, V.-M., Nie, W., Qi, X., Shen, Y., Chi, X., and Ding, A.: On the
mode-segregated aerosol particle number concentration load: contributions of
primary and secondary particles in Hyytiälä and Nanjing, Boreal Env.
Res., 21, 319–331, 2016.
Lelieveld, J., Evans, J. S., Fnais, M., Giannadaki, D., and Pozzer, A.: The
contribution of outdoor air pollution sources to premature mortality on a
global scale, Nature, 525, 367–71, 2015.
Lin, J.-T. and McElroy, M. B.: Detection from space of a reduction in
anthropogenic emissions of nitrogen oxides during the Chinese economic
downturn, Atmos. Chem. Phys., 11, 8171–8188,
https://doi.org/10.5194/acp-11-8171-2011, 2011.NOAA: The meteorology data and visibility data, available at:
https://www.ncdc.noaa.gov/isd, last access: 30 April 2019.
Pan, Y., Wang, Y., Zhang, J., Liu, Z., Wang, L., Tian, S., Tang, G., Gao, W.,
Ji, D., Tao, S., and Wang, Y.: Redefining the importance of nitrate during
haze pollution to help optimize an emission control strategy, Atmos.
Environ., 141, 197–202, 2016.Petaja, T., Jarvi, L., Kerminen, V. M., Ding, A. J., Sun, J. N., Nie, W.,
Kujansuu, J., Virkkula, A., Yang, X. Q., Fu, C. B., Zilitinkevich, S., and
Kulmala, M.: Enhanced air pollution via aerosol-boundary layer feedback in
Chin, Sci. Rep., 6, 18998, 10.1038/srep18998, 2016.
Richter, A., Burrows, J. P., Nusz, H., Granier, C., and Niemeier, U.:
Increase in tropospheric nitrogen dioxide over China observed from space,
Nature, 437, 129–132, 2005.Silver, B., Reddington, C. L., Arnold, S. R., and Spracklen, D. V.:
Substantial changes in air pollution across China during 2015–2017, Environ.
Res. Lett., 13, 114012, 10.1088/1748-9326/aae718, 2018.
Swietlicki, E., Hansson, H. C., HäMeri, K., Svenningsson, B., Massling,
A., McFiggans, G., H. Mcmurry, P., PetäJä, T., Tunved, P., Gysel, M.,
Do, T., Weingartner, E., Baltensperger, U., Rissler, J., Wiedensohler, A.,
and Kulmala, M.: Hygroscopic properties of submicrometer atmospheric aerosol
particles measured with H-TDMA instruments in various environments – a
review, Tellus B, Chem.
Phys. Meteorol., 60, 432–469, 2008.TEMIS: Tropospheric data products, avaiable at: http://www.temis.nl, last access: 30 April 2019.
van Donkelaar, A., Martin Randall, V., Brauer, M., Kahn, R., Levy, R.,
Verduzco, C., and Villeneuve Paul, J.: Global estimates of ambient fine
particulate matter concentrations from satellite-based aerosol optical depth:
development and application, Environ, Health Perspect., 118, 847–855, 2010.
Wang, G., Zhang, R., Gomez, M. E., Yang, L., Levy Zamora, M., Hu, M., Lin,
Y., Peng, J., Guo, S., Meng, J., Li, J., Cheng, C., Hu, T., Ren, Y., Wang,
Y., Gao, J., Cao, J., An, Z., Zhou, W., Li, G., Wang, J., Tian, P.,
Marrero-Ortiz, W., Secrest, J., Du, Z., Zheng, J., Shang, D., Zeng, L., Shao,
M., Wang, W., Huang, Y., Wang, Y., Zhu, Y., Li, Y., Hu, J., Pan, B., Cai, L.,
Cheng, Y., Ji, Y., Zhang, F., Rosenfeld, D., Liss, P. S., Duce, R. A., Kolb,
C. E., and Molina, M. J.: Persistent sulfate formation from London Fog to
Chinese haze, P. Natl. Acad. Sci. USA, 113, 13630–13635, 2016.
Wang, S., Zhao, M., Xing, J., Wu, Y., Zhou, Y., Lei, Y., He, K., Fu, L., and
Hao, J.: Quantifying the Air Pollutants Emission Reduction during the 2008
Olympic Games in Beijing, Environ. Sci. Technol., 44, 2490–2496, 2010.
Wang, Y., Li, Y., Wang, L., Liu, Z., Ji, D., Tang, G., Zhang, J., Sun, Y.,
Hu, B., and Xin, J.: Mechanism for the formation of the January 2013 heavy
haze pollution episode over central and eastern China, Sci. China Earth Sci.,
57, 14–25, 2014.
Wang, Y. H., Liu, Z. R., Zhang, J. K., Hu, B., Ji, D. S., Yu, Y. C., and
Wang, Y. S.: Aerosol physicochemical properties and implications for
visibility during an intense haze episode during winter in Beijing, Atmos.
Chem. Phys., 15, 3205–3215, https://doi.org/10.5194/acp-15-3205-2015, 2015.Wu, Y., Zhang, S. J., Li, M. L., Ge, Y. S., Shu, J. W., Zhou, Y., Xu, Y. Y.,
Hu, J. N., Liu, H., Fu, L. X., He, K. B., and Hao, J. M.: The challenge to
NOx emission control for heavy-duty diesel vehicles in China, Atmos. Chem.
Phys., 12, 9365–9379, https://doi.org/10.5194/acp-12-9365-2012, 2012.
Xin, J., Wang, Y., Pan, Y., Ji, D., Liu, Z., Wen, T., Wang, Y., Li, X., Sun,
Y., Sun, J., Wang, P., Wang, G., Wang, X., Cong, Z., Tao, S., Hu, B., Wang,
L., Tang, G., Gao, W., and Wang, L.: The Campaign on Atmospheric Aerosol
Research Network of China: CARE-China, B. Am. Meteorol. Soc., 96, 1137–1155,
2015.
Xing, J., Mathur, R., Pleim, J., Hogrefe, C., Gan, C.-M., Wong, D. C., Wei,
C., Gilliam, R., and Pouliot, G.: Observations and modeling of air quality
trends over 1990–2010 across the Northern Hemisphere: China, the United
States and Europe, Atmos. Chem. Phys., 15, 2723–2747,
https://doi.org/10.5194/acp-15-2723-2015, 2015.Yang, F., Tan, J., Zhao, Q., Du, Z., He, K., Ma, Y., Duan, F., Chen, G., and
Zhao, Q.: Characteristics of PM2.5 speciation in representative
megacities and across China, Atmos. Chem. Phys., 11, 5207–5219,
https://doi.org/10.5194/acp-11-5207-2011, 2011.
Zhang, J. K., Sun, Y., Liu, Z. R., Ji, D. S., Hu, B., Liu, Q., and Wang, Y.
S.: Characterization of submicron aerosols during a month of serious
pollution in Beijing, 2013, Atmos. Chem. Phys., 14, 2887–2903,
https://doi.org/10.5194/acp-14-2887-2014, 2014.
Zhang, R., Wang, G., Guo, S., Zamora, M. L., Ying, Q., Lin, Y., Wang, W., Hu,
M., and Wang, Y.: Formation of urban fine particulate matter, Chem. Rev.,
115, 3803–3855, 2015
Zhang, X. Y., Wang, Y. Q., Niu, T., Zhang, X. C., Gong, S. L., Zhang, Y. M.,
and Sun, J. Y.: Atmospheric aerosol compositions in China: spatial/temporal
variability, chemical signature, regional haze distribution and comparisons
with global aerosols, Atmos. Chem. Phys., 12, 779–799,
https://doi.org/10.5194/acp-12-779-2012, 2012.