Next Article in Journal
Temporal Variation of NO2 and O3 in Rome (Italy) from Pandora and In Situ Measurements
Previous Article in Journal
Apportionment of PM2.5 Sources across Sites and Time Periods: An Application and Update for Detroit, Michigan
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Atmosphere
Volume 14
Issue 3
10.3390/atmos14030593
atmosphere-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Communication

Seasonal Characteristics of Fine Particulate Carbonaceous Species in Taiyuan, North China

by
Wenbo Li
*,
Xinya Zhao
,
Fengbo Guo
and
Kankan Liu
School of Environment and Safety Engineering, North University of China, Taiyuan 030051, China
*
Author to whom correspondence should be addressed.
Atmosphere 2023, 14(3), 593; https://doi.org/10.3390/atmos14030593
Submission received: 23 February 2023 / Revised: 15 March 2023 / Accepted: 20 March 2023 / Published: 21 March 2023
(This article belongs to the Section Aerosols)
Browse Figures
Versions Notes

Abstract

:
To characterize seasonal carbonaceous aerosol pollution in Taiyuan, a typical city in North China that mainly relies heavily on coal, a total of 124 PM2.5 samples were collected from August 2018 to the next May. The annual mean PM2.5 concentration was 83.8 ± 48.5 μg m−3, with a seasonal rank of winter (117.4 ± 47.6 μg m−3) > spring (79.2 ± 34.3 μg m−3) > fall (67.3 ± 34.7 μg m−3) > summer (31.8 ± 6.5 μg m−3), suggesting that fine particulate pollution was still serious in cold seasons. Organic carbon (OC) and elemental carbon (EC) showed similar seasonal patterns with PM2.5. The mean concentration values of OC in summer, fall, winter, and spring were 5.1 ± 0.9, 11.8 ± 6.4, 22.1 ± 14.9, and 12.2 ± 6.7 μg m−3, respectively. The mean concentration values of EC in summer, fall, winter, and spring were 1.5 ± 0.3, 2.5 ± 1.6, 4.4 ± 2.8, and 2.4 ± 1.5 μg m−3, respectively. The proportion of total carbon aerosol (TCA) was about 31.7%, 33.8%, 30.0%, and 27.0% in PM2.5 in summer, fall, winter, and spring, respectively. The good correlation between OC vs. EC and the high value of OC/EC suggests that coal and biomass combustion were the main emissions in cold seasons, aggravated by adverse meteorological conditions and the dustpan-shaped terrain. The mean annual secondary organic carbon (SOC) concentration was 6.1 ± 7.1μg m−3, representing 38.7% of the OC content. The present results presented the serious carbonaceous particulate pollution, which might affect haze pollution in cold seasons.

1. Introduction

Fine particulate matter (PM2.5) is currently one of the major pollutants which can essentially cause severe haze pollution and threaten public health [1,2]. In recent years, heavy haze episodes have occurred frequently in large areas of China [3,4,5], and numerous in-depth studies have been conducted in those urban agglomerations with those economically developed 1st/2nd-tier cities, such as North China Plain [3,6,7,8], Guanzhong Plain [9], Yangtze and Pearl River Deltas [10,11], and Sichuan Basin [12,13] in the context of the national government’s vigorous air pollution control. As a result, air quality in many megacities have significantly improved in recent years [14,15]. However, there are still many areas where pollution is very serious, especially in some small/medium-sized cities [4]. This suggests that China still has a long way to go to combat air pollution.
In 2018, Fenwei Plain (i.e., the general name for Fenhe & Weihe Plains) was included for the first time in the main battlefield of “The Blue-Sky Defense War”, launched by the Ministry of Ecology and Environment of China (MEEC). This is mainly related to its fragile ecological environment, more coal, oil, and other chemical enterprises, and serious atmospheric pollution. Taiyuan is the provincial capital city of Shanxi Province and is located in the northernmost part of the Fenhe Plain. Strong emission sources, such as metallurgy and coking, and unfavorable topography and meteorological conditions, made urban ambient air pollution in the Fenhe Plain very serious. According to MEEC (www.mee.gov.cn, accessed on 1 June 2021), the annual average percentage of good/excellent days with an air quality index (AQI) less than 100 [14,16] in the Fenwei Plain was only 54.3%, and Taiyuan air quality ranked 7th from the bottom in cities across the country in 2018. However, comprehensive information on ambient carbonaceous aerosol pollution in the Fenhe Plain is relatively few.
Previous studies have shown that about 20–50% of PM2.5 mass concentration was carbonaceous aerosols in urban regions [17,18,19,20]. Carbon-containing aerosol usually exists in the form of EC and OC. EC is a primary pollutant usually emitted by incomplete combustion of fossil fuels and biomass fuels, while OC can be both a primary and a secondary pollutant [21]. Many studies have shown that carbon aerosols significantly affect the environment and human health. For example, EC has a strong heat and light absorption effect, and OC has a scattering effect on light. When combined, they will seriously damage the radiative balance of climate change in the ground-air system of atmospheric visibility. In addition, OC is a mixture of hundreds of organic compounds, some of which are mutagenic and/or carcinogenic and can seriously harm human health [22,23]. Therefore, to grasp the carbonaceous composition of atmospheric fine particles in Taiyuan and provide suggestions for the local government to formulate emission control policies, this study investigated the seasonal information of fine particulate, and its carbonaceous species has been conducted in Taiyuan from August 2018 to May 2019.

2. Experiments

2.1. Sample Collection and Analysis

The sampling site was located on the roof of a commercial building (~65 m above ground) in downtown Taiyuan city with some institutions, major traffic roads (Riverside Roads in the west and Yingze Street in the north) and Fen River (The second largest tributary of the Yellow River) adjacent to it (Figure 1).
The 90 mm quartz membrane prebaked at 600 °C for 4 h was used for particulate matter collection using a mid-volume particle collector with a flux of 100 L min-1 (KC-6120). A total of 124 effective membrane samples, of which 15 (1–15 August), 41(16–20, 22–30 September; 9–23 October; 4–15 November), 36 (12–29 December 2018; 1–9 January 2019; 21–29 February) and 32 (15–22 March; 15–23 April; 1–15 May) in summer, fall, winter and spring, respectively, were collected and analyzed.
The mass concentration of PM2.5 was determined using an electronic balance (FA1004, Lichen, China) after equilibration in a chamber at constant relative humidity (~35%) and temperature (~23 °C) for 24 h. In addition, a DRI (2001A) thermal/optical reflectance carbon analyzer was used to analyze fine particulate carbonaceous species. The minimum determined limits of DRI were 0.20 μgC cm−2 and 0.82 μgC cm−2 for EC and OC, respectively [2].

2.2. Meteorological Parameters

The meteorological characteristics include ambient temperature (T), relative humidity (RH), wind speed (WS) and direction (WD), visibility (V) and rainfall (RF), solar irradiance (SI) and sunshine hours (SH). WS/WD and T/RH were monitored using a self-recording anemometer (ZCF-5, Sipeik, Shanghai, China) and hygrothermograph (SW-572, SNDWAY, Qingdao, China) at the sampling site. V and RF were obtained from the WusuAirport (WIA, 12.9 km from the sampling site). SI and SH were obtained from the agrometeorological station (AS, 21.5 km from the sampling site) (Figure 1) [24].

3. Results and discussion

3.1. PM2.5 Levels and Its Carbonaceous Species

The daily mass concentrations of PM2.5, OC and EC and total carbonaceous aerosol (TCA) contribution percentage to PM2.5 are illustrated in Figure 2 and summarized by season in Table 1. The annual mean concentration of PM2.5 was 83.8 ± 48.7 μg m−3, with a range of 14.3~269.7 μg m−3, which was about 2.4-fold greater than the 2nd annual limit value (35 μg m−3) according to China National Ambient Air Quality Standard (NAAQS) (GB3098-2012). The seasonal mean PM2.5 concentration was the highest in winter (117.4 ± 47.6 μg m−3), followed by spring (79.2 ± 34.3 μg m−3) and fall (67.3 ± 34.7 μg m−3), and the lowest in summer (31.8 ± 6.5 μg m−3). Compared to 2009–2010 in Taiyuan, reported by He et al. (2015) [25], the PM2.5 concentration has dropped by 77%, 63%, 55% and 68% reduction in summer, fall, winter and spring. However, fine particle pollution in the present study was still relatively serious, especially in the heating seasons. It can be seen that only the summer PM2.5 concentration was within the first order ambient air quality standard daily limit (35 μg m−3) of MEPC while that in winter, spring and fall were about 3.4, 1.9 and 2.3 times that of the limit.
OC and EC generally presented similar patterns of changes with PM2.5 on a timescale. The daily OC concentrations in summer, autumn, winter, and spring were 4.1~7.1 μg m−3, 3.3~26.5 μg m−3, 2.9~62.0 μg m−3, and 2.8~14.8 μg m−3, with the seasonal mean values of 5.1 ± 0.9 μg m−3, 11.8 ± 64 μg m−3, 22.1 ± 14.9 μg m−3, and 12.2 ± 6.7 μg m−3, respectively. The daily EC were 1.0~2.1 μg m−3, 0.9~3.9 μg m−3, 0.4~12.9 μg m−3, and 0.6~6.7 μg m−3, with the seasonal mean values of 1.5 ± 0.3 μg m−3, 2.5 ± 1.6 μg m−3, 4.4 ± 2.8 μg m−3, and 2.4 ± 1.5 μg m−3, respectively. This seasonal variation was in line with other studies [21,26,27,28]. The OC and EC concentration levels were four times and twice as high in winter compared to summer and other seasons. Compared to 2009–2010 (13.2~62.7 μg m−3 for OC, 8.8~25.4 μg m−3 for EC) [25], the OC and EC concentration levels in Taiyuan decreased by about 59–68% and 83–89%, respectively, suggesting significant pollutant reduction have been achieved.
Exacerbation of the pollutants in cold seasons may be due to the source strength and topographic and prevailing meteorological conditions in Taiyuan. The higher levels of PM2.5, OC and EC concentrations in cold seasons can be attributed to the heating period from November to March. In addition, the adverse meteorological conditions in cold seasons and the dustpan-shaped terrain of Taiyuan, with the mouth in the south and mountains in other directions, were not conducive to the adventive diffusion of atmospheric pollutants [29]. Figure 3 shows seasonal wind roses with the intensity of atmospheric temperature inversion. It can be seen that the dominant wind usually came from west-north-east, of which only north wind with fast speed may dilute the pollutants under the condition of the dustpan terrain. Furthermore, the intensity of atmospheric temperature inversion was strong in cold seasons (Figure 3 and Table 1) and was liable to accumulate pollutants.
TCA represents the sum of EC and the sum of organic matter which is about 1.6 ± 0.2 times that of OC in urban atmospheric aerosols [17,23,30]. In this study, TCA showed a similar seasonal change pattern to PM2.5, OC, and EC (Table 1), while asynchronous variation was presented by the percentage of TCA in PM2.5. TCA accounted for averaged 33.8%, 31.7%, 30.0% and 27.0% of PM2.5 mass in fall, summer, winter, and spring, respectively, with an annual mean TCA contribution percentage of 30.4% to PM2.5 mass. The present seasonal rank of TCA/PM2.5 was partly inconsistent with that in Taiyuan about a decade ago (winter > spring > fall > summer) [25]. The lowest TCA/PM2.5 percentage in the present work may be affected by frequent dust storms in spring, especially in dry spring seasons, such as April and May [23,31]. TCA contribution to PM2.5 in this study was in line with that in Chongqing [32], the Western Taiwan Strait Region [21] and Taiyuan a decade ago reported by He et al. (2015) [25], but much less than that in Beijing-Tianjin-Hebei integration [33].
OC and EC concentrations in this study were compared with those measured in other Chinese cities [23,32,34,35] in Table 2. In spring, the OC concentrations in Taiyuan were lower than in Shanghai and Beijing but higher than in Chongqing and Lvliang. However, the EC concentrations were lower than that in the remaining 4 cities. In summer, the concentrations of carbonaceous species in PM2.5 in Taiyuan were lower than in other Chinese cities. In the fall, the concentrations of carbonaceous species in PM2.5 in Taiyuan were higher than that measured in Lvliang but lower than that measured in Chongqing, Shanghai, and Beijing. In winter, the OC concentration was lower than that in Chongqing and Beijing but higher than that in Shanghai and Lvliang. However, the EC concentration was lower than that in Chongqing, Beijing, and Lvliang but higher than that in Shanghai. Therefore, several conclusions could be summarized: (1) In summer and fall, the concentrations of carbonaceous species in PM2.5 in Taiyuan were at a much lower level; (2) For the full year, the OC concentrations in Taiyuan were at a moderate level, and the EC concentrations of PM2.5 were at a lower level.

3.2. Relationship between OC and EC

The OC/EC ratio can indicate the source of carbonaceous matter and its transformation information [21,25]. The mean OC/EC ratios were 3.5, 5.1, 5.2 and 4.8 in the four seasons (Table 1), representing the dominant emissions from gasoline and diesel vehicles in summer while coal and even biomass combustion in other seasons [36,37]. The current OC/EC ratios were in the ranges of those in the 14 Chinese cities reported by Cao et al. (2007) but much higher than those in Taiyuan (1.5~2.5) a decade ago [25]. Seasonal correlations between OC and EC in PM2.5 in Figure 4 may initially distinguish the main sources of carbon elements in the atmosphere and can partly reflect the relationship between both sources [38]. As shown, OC had high correlations with EC in spring (R2 = 0.78), fall (R2 = 0.74), and winter (R2 = 0.61), which indicates that they mainly came from similar sources. In spring, the low temperature and particulate, chemical activity, and weak secondary generation, and frequent dust storm pollution input could make the OC mass concentration more affected by the primary emission source.
The highest OC/EC in fall with a strong correlation should be ascribed to staged biomass burning after harvest [25,36,39], (He et al., 2015; Huang et al., 2018b; Schaap and Denier, 2007) and rural heating ahead of urban, which might increase OC/EC ratios because of combustion of raw coal [2]. The emission sources of OC and EC in winter were also homologous, mainly should be influenced by coal soot during the heating season. The lowest OC/EC value and poor correlation between them (R2 = 0.2) occurred in summer, which should be significantly influenced by photochemical quadratic sources and gaseous pollution emissions [40,41].

3.3. Estimation of SOC and SOA Levels

The presence of a second OC (SOC) is usually determined by using an OC/EC ratio higher than 2.0 [21,42,43]. However, the current OC/EC ratios were all higher than this value, and SOC was estimated via the current minimum value of OC/EC [44] (Table 1). The minimum values of OC/EC observed in the four seasons were 2.7, 3.5, 2.6 and 2.43. Thus, secondary organic aerosol (SOA) concentration can also be estimated at 1.6 times the SOC (Table 1).
As shown, Taiyuan’s average annual SOC concentration was 6.1 ± 7.1 μg m−3, representing 38.7% of the OC content. The mean SOC concentrations in the four seasons were 1.1 ± 0.9, 4.0 ± 3.7, 10.4 ± 10.6 and 6.4 ± 3.9 μg m−3, contributing about 20.2%, 31.1%, 43.3% and 52.0% to OC, respectively, which suggested SOC was an important component of OC in PM2.5 in Taiyuan. The present contribution percentage of SOC to OC was in line with that reported in the Western Taiwan Strait Region (23.8–39.4%) [21], Baotou (24.4–43.2%) [1], Beijing-Tianjin-Hebei integration (38–42%) [33]. Compared to 2009–2010 (22.9%, 42.8%, 56.2% and 25.9% in summer, fall, winter and spring, respectively) in Taiyuan [25], the percentage of SOC/OC in this work was almost equivalent to that in summer but much higher in spring and much lower in fall and winter, which again suggested the air atmospheric oxidation was enhanced in recent years. Notably, in contrast to the phenomena of higher SOC in summer than in other seasons [17,45], the highest concentration of SOC, as well as the SOC percentage of OC in this work, were not occurred in the expected summer [46] but in spring, which was similar to the SOC/OC percentage seasonal variation at an adjacent coal mining city in the North China Plain [27]. This phenomenon indicated enough secondary transformation occurred in the present sampling periods (especially in April and May) with conducive conditions to the photochemical reaction of semi-volatile and volatile organic compounds in Taiyuan. Figure 5 shows the dependence of the percentage of SOC in OC in the four seasons on solar radiation parameters. The increase in the average solar irradiance and daytime hours may be one of the key factors contributing to the increase in SOC/OC percentage. The average solar irradiance during daylight hours was 220.3 ± 36.9 W m−2, 153.9 ± 64.4 W m−2, 116.0 ± 35.1 W m−2 and 241.4 ± 58.0 W m−2 in the four seasons, respectively (Table 1). The present average light intensity during the current sampling period was greater in spring than in summer. Additionally, the higher SOC/OC percentages occurred in cold seasons, and the low positive associations between factors of SOC/OC percentages and solar irradiance (Figure 6) indicated that SOC production was limited by solar radiation and other causes [37]. Although winter has not provided favorable meteorological conditions for SOC production, the relatively higher SOC/OC percentage occurred in winter, which should be attributable to the emission of Volatile Organic Compounds (VOCs) increased for heating in Taiyuan and the stable atmospheric condition and dustpan-terrain condition [25,46]. Additionally, higher rainfall in summer (Table 1) may limit the formation of SOC [39,47].
From Table 1, the concentrations of SOA were 1.7 ± 1.4 μg m−3, 6.4 ± 5.9 μg m−3, 16.7 ± 16.9 μg m−3 and 10.2 ± 6.3 μg m−3, with the corresponding contribution of 5.5%, 9.6%, 11.5% and 13.1% to PM2.5, in summer, fall, winter and spring, respectively, which showed the same seasonal rank as SOC/OC. The annual mean percentage of SOA in PM2.5 was 10.5%, indicating that, as was the case a decade ago (12.2%) reported by He et al. (2015) [25], SOA accounted for a relatively small fraction of the PM2.5 mass in Taiyuan. However, the concentration of SOA in this study (9.8 ± 11.3 μg m−3) was about one-third of that of a decade ago (27.5 ± 30.3 μg m−3) [25].

4. Conclusions

Although significant air pollutant reductions have been achieved during this decade, PM2.5 pollution was still very serious in cold seasons. Only the summer PM2.5 concentration was within the first order ambient air quality standard daily limit, while that in winter, spring and fall were about 3.4, 1.9 and 2.3 times that of the limit. The mass of OC and EC in PM2.5 presented synchronous variation with PM2.5 with the seasonal mean concentrations of 5.1 ± 0.9 μg m−3, 11.8 ± 64 μg m−3, 22.1 ± 14.9 μg m−3, and 12.2 ± 6.7 μg m−3, for OC and 1.5 ± 0.3 μg m−3, 2.5 ± 1.6 μg m−3, 4.4 ± 2.8 μg m−3, and 2.4 ± 1.5 μg m−3 for EC in summer, fall, winter and spring, respectively. The mean OC/EC ratios of 3.5, 5.1, 5.2 and 4.8 in the four seasons and well correlations between OC and EC indicated that coal and biomass combustion was the dominant emissions in cold seasons, aggravated by the adverse meteorological conditions and the dustpan-shaped terrain. The present higher SOC concentration and SOC/OC percentage suggested that the air atmospheric oxidation was enhanced in recent years, and the production of SOC was influenced by solar radiation, heating in cold seasons, stable atmospheric condition, rainfall, etc. Overall, carbon aerosol pollution has reduced significantly in the last decade, but there is still a long way to go for local air pollution control.

Author Contributions

Conceptualization, W.L. and X.Z.; methodology, X.Z.; data curation, W.L. and F.G.; writing—original draft preparation, W.L., X.Z. and F.G.; writing—review and editing, W.L.; funding acquisition, K.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Fundamental Research Program of Shanxi Province, China, grant number 20210302123043.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data used in this paper can be provided by the correspondent author.

Acknowledgments

This work was partially supported by the Fundamental Research Program of Shanxi Province, China, grant number 20210302123043.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Zhou, H.; He, J.; Zhao, B.; Zhang, L.; Fan, Q.; Lü, C.; Liu, T.; Yuan, Y. The Distribution of PM10 and PM2.5 Carbonaceous Aerosol in Baotou, China. Atmos. Res. 2016, 178, 102–113. [Google Scholar] [CrossRef]
  2. Liu, K.; Ren, J. Seasonal characteristics of PM2.5 and its chemical species in the northern rural China. Atmos. Pollut. Res. 2020, 11, 1891–1901. [Google Scholar] [CrossRef]
  3. Liu, P.; Zhang, C.; Mu, Y.; Liu, C.; Xue, C.; Ye, C.; Liu, J.; Zhang, Y.; Zhang, H. The possible contribution of the periodic emissions from farmers’ activities in the North China Plain to atmospheric water-soluble ions in Beijing. Atmos. Chem. Phys. 2016, 16, 10097–10109. [Google Scholar] [CrossRef] [Green Version]
  4. Wang, Q.; Li, J.; Yang, J.; Chen, Y.; Li, Y.; Li, S.; Xie, C.; Chen, C.; Wang, L.; Wang, L.; et al. Seasonal characterization of aerosol composition and sources in a polluted city in Central China. Chemosphere 2020, 258, 127310. [Google Scholar] [CrossRef] [PubMed]
  5. Zhang, Y.; Baltensperger, U.; Schnelle-Kreis, J.; An, Z.; Han, Y.; Crippa, M.; Zotter, P.; Platt, S.M.; Cao, J.-J.; Ho, K.-F.; et al. High secondary aerosol contribution to particulate pollution during haze events in China. Nature 2014, 514, 218–222. [Google Scholar] [CrossRef]
  6. Liu, P.; Zhang, C.; Xue, C.; Mu, Y.; Liu, J.; Zhang, Y.; Tian, D.; Ye, C.; Zhang, H.; Guan, J. The Contribution of Residential Coal Combustion to Atmospheric Pm2. 5 in Northern China During Winter. Atmos. Chem. Phys. 2017, 17, 11503–11520. [Google Scholar] [CrossRef] [Green Version]
  7. Huang, R.-J.; Wang, Y.; Cao, J.; Lin, C.; Duan, J.; Chen, Q.; Li, Y.; Gu, Y.; Yan, J.; Xu, W.; et al. Primary emissions versus secondary formation of fine particulate matter in the most polluted city (Shijiazhuang) in North China. Atmos. Chem. Phys. 2019, 19, 2283–2298. [Google Scholar] [CrossRef] [Green Version]
  8. Khan, J.Z.; Sun, L.; Tian, Y.; Shi, G.; Feng, Y. Chemical Characterization and Source Apportionment of PM1 and PM2.5 in Tianjin, China: Impacts of Biomass Burning and Primary Biogenic Sources. J. Environ. Sci. 2021, 99, 196–209. [Google Scholar] [CrossRef]
  9. Huang, R.-J.; Yang, L.; Cao, J.; Chen, Y.; Chen, Q.; Li, Y.; Duan, J.; Zhu, C.; Dai, W.; Wang, K.; et al. Brown Carbon Aerosol in Urban Xi’an, Northwest China: The Composition and Light Absorption Properties. Environ. Sci. Technol. 2018, 52, 6825–6833. [Google Scholar] [CrossRef]
  10. Wu, S.-P.; Schwab, J.; Yang, B.-Y.; Zheng, A.; Yuan, C.-S. Two-Years PM2.5 Observations at Four Urban Sites along the Coast of Southeastern China. Aerosol Air Qual. Res. 2015, 15, 1799–1812. [Google Scholar] [CrossRef] [Green Version]
  11. Zhong, Y.; Chen, J.; Zhao, Q.; Zhang, N.; Feng, J.; Fu, Q. Temporal Trends of the Concentration and Sources of Secondary Organic Aerosols in PM2.5 in Shanghai During 2012 and 2018. Atmos. Environ. 2021, 261, 118596. [Google Scholar] [CrossRef]
  12. Yin, D.; Zhao, S.; Qu, J.; Yu, Y.; Kang, S.; Ren, X.; Zhang, J.; Zou, Y.; Dong, L.; Li, J.; et al. The vertical profiles of carbonaceous aerosols and key influencing factors during wintertime over western Sichuan Basin, China. Atmos. Environ. 2020, 223, 117269. [Google Scholar] [CrossRef]
  13. Feng, T.; Wang, F.; Yang, F.; Li, Z.; Lu, P.; Guo, Z. Carbonaceous Aerosols in Urban Chongqing, China: Seasonal Variation, Source Apportionment, and Long-Range Transport. Chemosphere 2021, 285, 131462. [Google Scholar] [CrossRef] [PubMed]
  14. He, J.; Gong, S.; Yu, Y.; Yu, L.; Wu, L.; Mao, H.; Song, C.; Zhao, S.; Liu, H.; Li, X.; et al. Air pollution characteristics and their relation to meteorological conditions during 2014–2015 in major Chinese cities. Environ. Pollut. 2017, 223, 484–496. [Google Scholar] [CrossRef]
  15. Hou, X.; Zhu, B.; Kumar, K.R.; Lu, W. Inter-annual variability in fine particulate matter pollution over China during 2013–2018: Role of meteorology. Atmos. Environ. 2019, 214, 116842. [Google Scholar] [CrossRef]
  16. Chen, W.; Tang, H.; Zhao, H. Urban air quality evaluations under two versions of the national ambient air quality standards of China. Atmos. Pollut. Res. 2016, 7, 49–57. [Google Scholar] [CrossRef]
  17. Cao, J.J.; Lee, S.-C.; Chow, J.C.; Watson, J.G.; Ho, K.F.; Zhang, R.J.; Jin, Z.D.; Shen, Z.X.; Chen, G.C.; Kang, Y.M.; et al. Spatial and seasonal distributions of carbonaceous aerosols over China. J. Geophys. Res. Atmos. 2007, 112, D22S11. [Google Scholar] [CrossRef] [Green Version]
  18. Pathak, R.K.; Wang, T.; Ho, K.; Lee, S. Characteristics of summertime PM2.5 organic and elemental carbon in four major Chinese cities: Implications of high acidity for water-soluble organic carbon (WSOC). Atmos. Environ. 2011, 45, 318–325. [Google Scholar] [CrossRef]
  19. Seibert, R.; Nikolova, I.; Volna, V.; Krejci, B.; Hladky, D. ‘Air Pollution Sources’ Contribution to PM(2.5)Concentration in the Northeastern Part of the Czech Republic. Atmosphere 2020, 11, 522. [Google Scholar] [CrossRef]
  20. Feng, J.; Hu, M.; Chan, C.K.; Lau, P.S.; Fang, M.; He, L.; Tang, X. A comparative study of the organic matter in PM2.5 from three Chinese megacities in three different climatic zones. Atmos. Environ. 2006, 40, 3983–3994. [Google Scholar] [CrossRef]
  21. Niu, Z.; Zhang, F.; Chen, J.; Yin, L.; Wang, S.; Xu, L. Carbonaceous species in PM2.5 in the coastal urban agglomeration in the Western Taiwan Strait Region, China. Atmos. Res. 2013, 122, 102–110. [Google Scholar] [CrossRef]
  22. Lin, P.; Hu, M.; Deng, Z.; Slanina, J.; Han, S.; Kondo, Y.; Takegawa, N.; Miyazaki, Y.; Zhao, Y.; Sugimoto, N. Seasonal and Diurnal Variations of Organic Carbon in Pm2.5 in Beijing and the Estimation of Secondary Organic Carbon. J. Geophys. Res.-Atmos. 2009, 114, D00G11. [Google Scholar] [CrossRef]
  23. Feng, Y.; Chen, Y.; Guo, H.; Zhi, G.; Xiong, S.; Li, J.; Sheng, G.; Fu, J. Characteristics of Organic and Elemental Carbon in PM2.5 Samples in Shanghai, China. Atmos. Res. 2009, 92, 434–442. [Google Scholar] [CrossRef]
  24. Ren, J.; Zhao, X.; Guo, X.; Guo, F.; Liu, K. Responses of Ambient Ozone and Other Pollutants to COVID-19 Lockdown in Taiyuan, North China. Pol. J. Environ. Stud. 2022, 31, 2823–2835. [Google Scholar] [CrossRef]
  25. He, Q.; Guo, W.; Zhang, G.; Yan, Y.; Chen, L. Characteristics and Seasonal Variations of Carbonaceous Species in PM2.5 in Taiyuan, China. Atmosphere 2015, 6, 850–862. [Google Scholar] [CrossRef] [Green Version]
  26. Chen, D.; Cui, H.; Zhao, Y.; Yin, L.; Lu, Y.; Wang, Q. A two-year study of carbonaceous aerosols in ambient PM2.5 at a regional background site for western Yangtze River Delta, China. Atmos. Res. 2017, 183, 351–361. [Google Scholar] [CrossRef]
  27. Xue, F.; Niu, H.; Hu, S.; Wu, C.; Zhang, C.; Gao, N.; Ren, X.; Li, S.; Hu, W.; Wang, J.; et al. Seasonal Variations and Source Apportionment of Carbonaceous Aerosol in PM2.5 from a Coal Mining City in the North China Plain. Energy Explor. Exploit. 2021, 40, 834–851. [Google Scholar] [CrossRef]
  28. Wang, M.; Tian, P.; Wang, L.; Yu, Z.; Du, T.; Chen, Q.; Guan, X.; Guo, Y.; Zhang, M.; Tang, C.; et al. High Contribution of Vehicle Emissions to Fine Particulate Pollutions in Lanzhou, Northwest China Based on High-Resolution Online Data Source Appointment. Sci. Total Environ. 2021, 798, 149310. [Google Scholar] [CrossRef]
  29. Liu, K.; Ren, J. Characteristics, sources and health risks of PM2.5-bound potentially toxic elements in the northern rural China. Atmos. Pollut. Res. 2019, 10, 1621–1626. [Google Scholar] [CrossRef]
  30. Turpin, B.J.; Huntzicker, J.J. Identification of secondary organic aerosol episodes and quantitation of primary and secondary organic aerosol concentrations during SCAQS. Atmos. Environ. 1995, 29, 3527–3544. [Google Scholar] [CrossRef]
  31. Fan, K.; Xie, Z.; Wang, H.; Xu, Z.; Liu, J. Frequency of spring dust weather in North China linked to sea ice variability in the Barents Sea. Clim. Dyn. 2017, 51, 4439–4450. [Google Scholar] [CrossRef]
  32. Zhang, L.; Huang, Y.; Liu, Y.; Yang, F.; Lan, G.; Fu, C.; Wang, J. Characteristics of Carbonaceous Species in PM2.5 in Wanzhou in the Hinterland of the Three Gorges Reservior of Northeast Chongqing, China. Atmosphere 2015, 6, 534–546. [Google Scholar] [CrossRef] [Green Version]
  33. Qi, M.; Jiang, L.; Liu, Y.; Xiong, Q.; Sun, C.; Li, X.; Zhao, W.; Yang, X. Analysis of the Characteristics and Sources of Carbonaceous Aerosols in Pm2.5 in the Beijing, Tianjin, and Langfang Region, China. Int. J. Environ. Res. Public Health 2018, 15, 1483. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Wang, Y.; Zhang, H.; Zhai, J.X.; Wu, Y.A.; Cong, L.; Yan, G.X.; Zhang, Z.M. Seasonal Variations and Chemical Characteristics of Pm2.5 Aerosol in the Urban Green Belt of Beijing, China. Pol. J. Environ. Stud. 2020, 29, 361–370. [Google Scholar] [CrossRef]
  35. Li, X.; Mu, L.; Liu, T.; Li, Y.; Feng, C.; Jiang, X.; Liu, Z.; Tian, M. Carbonaceous aerosols in Lvliang, China: Seasonal variation, spatial distribution and source apportionment. Environ. Chem. 2022, 19, 90–99. [Google Scholar] [CrossRef]
  36. Schaap, M.; van der Gon, H.D. On the variability of Black Smoke and carbonaceous aerosols in the Netherlands. Atmos. Environ. 2007, 41, 5908–5920. [Google Scholar] [CrossRef]
  37. Plaza, J.; Artíñano, B.; Salvador, P.; Gómez-Moreno, F.J.; Pujadas, M.; Pio, C.A. Short-term secondary organic carbon estimations with a modified OC/EC primary ratio method at a suburban site in Madrid (Spain). Atmos. Environ. 2011, 45, 2496–2506. [Google Scholar] [CrossRef]
  38. Mancilla, Y.; Herckes, P.; Fraser, M.P.; Mendoza, A. Secondary Organic Aerosol Contributions to PM2.5 in Monterrey, Mexico: Temporal and Seasonal Variation. Atmos. Res. 2015, 153, 348–359. [Google Scholar] [CrossRef]
  39. Huang, Y.; Liu, Y.; Zhang, L.; Peng, C.; Yang, F. Characteristics of Carbonaceous Aerosol in PM2.5 at Wanzhou in the Southwest of China. Atmosphere 2018, 9, 37. [Google Scholar] [CrossRef] [Green Version]
  40. Hayami, H.; Saito, S.; Hasegawa, S.; Shinji, S. Spatiotemporal Variations of Fine Particulate Organic and Elemental Carbons in Greater Tokyo. Asian J. Atmos. Environ. 2019, 13, 161–170. [Google Scholar] [CrossRef]
  41. Pyta, H.; Rogula-Kozłowska, W.; Mathews, B. Co-occurrence of PM2.5-bound mercury and carbon in rural areas affected by coal combustion. Atmos. Pollut. Res. 2017, 8, 127–135. [Google Scholar] [CrossRef]
  42. Chow, J.C.; Watson, J.G.; Lu, Z.; Lowenthal, D.H.; Frazier, C.A.; Solomon, P.A.; Thuillier, R.H.; Magliano, K. Descriptive analysis of PM2.5 and PM10 at regionally representative locations during SJVAQS/AUSPEX. Atmos. Environ. 1996, 30, 2079–2112. [Google Scholar] [CrossRef]
  43. Xu, M.; Liu, Z.; Hu, B.; Yan, G.; Zou, J.; Zhao, S.; Zhou, J.; Liu, X.; Zheng, X.; Zhang, X.; et al. Chemical Characterization and Source Identification of Pm2.5 in Luoyang after the Clean Air Actions. J. Environ. Sci. 2022, 115, 265–276. [Google Scholar] [CrossRef] [PubMed]
  44. Tao, J.; Gao, J.; Zhang, L.; Zhang, R.; Che, H.; Zhang, Z.; Lin, Z.; Jing, J.; Cao, J.; Hsu, S.-C. PM2.5 pollution in a megacity of southwest China: Source apportionment and implication. Atmos. Chem. Phys. 2014, 14, 8679–8699. [Google Scholar] [CrossRef] [Green Version]
  45. Gu, J.; Bai, Z.; Liu, A.; Wu, L.; Xie, Y.; Li, W.; Dong, H.; Zhang, X. Characterization of Atmospheric Organic Carbon and Element Carbon of PM2.5 and PM10 at Tianjin, China. Aerosol Air Qual. Res. 2010, 10, 167–176. [Google Scholar] [CrossRef] [Green Version]
  46. Zhao, P.S.; Dong, F.; Yang, Y.D.; He, D.; Zhao, X.J.; Zhang, W.Z.; Yao, Q.; Liu, H.Y. Characteristics of Carbonaceous Aerosol in the Region of Beijing, Tianjin, and Hebei, China. Atmos. Environ. 2013, 71, 389–398. [Google Scholar] [CrossRef]
  47. Shi, J.; Ding, X.; Zhou, Y.; You, R.; Huang, L.; Hao, J.; Xiang, F.; Yang, J.; Shi, Z.; Han, X.; et al. Characteristics of Chemical Components in PM2.5 at a Plateau City, South-West China. Front. Environ. Sci. Eng. 2016, 10, 4. [Google Scholar] [CrossRef]
Atmosphere 14 00593 g001 550
Figure 1. The sampling site (red star) in downtown Taiyuan city with the Wusu international airport (WIA, blue plane) and the agrometeorological station (AS, green pin).
Figure 1. The sampling site (red star) in downtown Taiyuan city with the Wusu international airport (WIA, blue plane) and the agrometeorological station (AS, green pin).
Atmosphere 14 00593 g001
Atmosphere 14 00593 g002 550
Figure 2. Daily PM2.5, OC, EC, and percentage of TCA in PM2.5 during the sampling period.
Figure 2. Daily PM2.5, OC, EC, and percentage of TCA in PM2.5 during the sampling period.
Atmosphere 14 00593 g002
Atmosphere 14 00593 g003 550
Figure 3. Seasonal wind roses with the intensity of atmospheric temperature inversion.
Figure 3. Seasonal wind roses with the intensity of atmospheric temperature inversion.
Atmosphere 14 00593 g003
Atmosphere 14 00593 g004 550
Figure 4. Seasonal correlations between OC and EC in PM2.5.
Figure 4. Seasonal correlations between OC and EC in PM2.5.
Atmosphere 14 00593 g004
Atmosphere 14 00593 g005 550
Figure 5. Seasonal SOC/OC percentage as a function of daily hours of sunlight and average solar irradiance during daylight hours.
Figure 5. Seasonal SOC/OC percentage as a function of daily hours of sunlight and average solar irradiance during daylight hours.
Atmosphere 14 00593 g005
Atmosphere 14 00593 g006 550
Figure 6. Scatter plots and linear regression equations of SOC/OC percentage vs. solar irradiance.
Figure 6. Scatter plots and linear regression equations of SOC/OC percentage vs. solar irradiance.
Atmosphere 14 00593 g006
Table
Table 1. Seasonal Mean ± SD values of PM2.5, carbonaceous species, and meteorological parameters.
Table 1. Seasonal Mean ± SD values of PM2.5, carbonaceous species, and meteorological parameters.
SeasonsSummer
(n = 15)		Fall
(n = 41)		Winter
(n = 36)		Spring
(n = 32)		Annual
(n = 124)
PM2.5 ζ31.8 ± 6.567.3 ± 34.7117.4 ± 47.679.2 ± 34.383.8 ± 48.7
OC ζ5.1 ± 0.911.8 ± 6.422.1 ± 14.912.2 ± 6.714.1 ± 10.9
EC ζ1.5 ± 0.32.5 ± 1.64.4 ± 2.82.4 ± 1.52.9 ± 2.2
TCA ζ9.7 ± 1.521.4 ± 11.639.8 ± 26.021.9 ± 12.125.5 ± 19.3
TCA/PM2.5 ξ31.7 ± 8.533.8 ± 10.730.0 ± 12.127.0 ± 5.830.4 ± 10.1
OC/EC3.5 ± 0.75.1 ± 1.85.2 ± 2.94.8 ± 2.55.1 ± 2.4
SOC ζ1.1 ± 0.94.0 ± 3.710.4 ± 10.66.4 ± 3.96.1 ± 7.1
SOC/OC ξ20.2 ± 14.331.1 ± 17.843.3 ± 21.052.0 ± 19.138.7 ± 21.4
SOC/PM2.5 ξ3.4 ± 2.96.0 ± 4.77.2 ± 5.18.2 ± 3.66.6 ± 4.6
SOA ζ1.7 ± 1.46.4 ± 5.916.7 ± 16.910.2 ± 6.39.8 ± 11.3
SOA/PM2.5 ξ5.5 ± 4.69.6 ± 7.511.5 ± 8.213.1 ± 5.810.5 ± 7.3
WS ς8 ± 56.9 ± 3.67.1 ± 4.610.3 ± 5.88.2 ± 4.8
T ς25.1 ± 2.610.6 ± 5.7-2.8 ± 3.813.5 ± 6.09.0 ± 10.0
RH ς66.7 ± 7.056.5 ± 14.041.1 ± 13.335.9 ± 15.546.5 ± 17.6
RF ς32.8 ± 31.29.4 ± 22.52.2 ± 2.79.4 ± 22.59.6 ± 21.7
V ς10.8 ± 3.410.8 ± 4.49.5 ± 4.512.6 ± 3.810.9 ± 4.3
ITI ς0.17 ± 0.301.0 ± 1.31.2 ± 1.91.37 ± 1.251.1 ± 1.47
SH ς5.47 ± 1.834.07 ± 1.453.00 ± 0.866.13 ± 1.564.50 ± 1.90
SI ς175.5 ± 50.6133.3 ± 51.2108.2 ± 16.4208.3 ± 50.3151.7 ± 61.2
Solar irradiance220.3 ± 36.9153.9 ± 64.4116.0 ± 35.1241.4 ± 58.0169.9 ± 72.2
ζ and ξ: The units for ζ and ξ are μg m−3 and %, respectively; ς: WS (km hr−1), T (°C), RH (%), RF (mm), V (km), ITI (°C (100 m)−1), SH (hours) and SR (W m−2) represent staged average wind speed, ambient temperature, relative humidity, rainfall, visibility, the intensity of temperature inversion, daily sunshine hours and average daytime solar irradiance during the sampling period, respectively.
Table
Table 2. Compare OC and EC concentrations in PM2.5 in Taiyuan with those in other Chinese cities.
Table 2. Compare OC and EC concentrations in PM2.5 in Taiyuan with those in other Chinese cities.
CityPeriodSite DescriptionOC ζEC ζOC/ECReference
TaiyuanSpring 2019Urban commercialtraffic12.22.44.8This study
Summer 20185.11.53.5
Fall 201811.82.55.1
Winter22.14.45.2
Annual14.12.95.1
Wanzhou, ChongqingSpring 2013Urban commercial-residential-cultural9.94.92.1[32]
Summer 20137.94.21.6
Fall 201313.95.13.3
Winter 201362.820.53.0
Annual23.68.72.5
Zha-bei district, ShanghaiSpring, 2006Urban traffic-residential-commercial14.13.14.5[23]
Summer, 20067.21.93.4
Fall, 200521.83.95.3
Winter, 200516.72.36.8
Annual14.72.85.0
BeijingSpring, April–May 2016, March 2017Olympic Forest Park28.49.92.9[34]
Summer 201626.412.62.1
Fall 201630.49.92.8
Winter, November 2016, January to February 201737.78.72.7
Annual30.710.22.6
Xiaoyi, LvliangSpring, 2019Suburban6.22.82.3[35]
Summer, 20195.52.62.1
Fall, 20183.71.92.2
Winter, 201815.010.71.5
Annual7.54.42.0
ζ: The unit for ζ is μg m−3.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Li, W.; Zhao, X.; Guo, F.; Liu, K. Seasonal Characteristics of Fine Particulate Carbonaceous Species in Taiyuan, North China. Atmosphere 2023, 14, 593. https://doi.org/10.3390/atmos14030593

AMA Style

Li W, Zhao X, Guo F, Liu K. Seasonal Characteristics of Fine Particulate Carbonaceous Species in Taiyuan, North China. Atmosphere. 2023; 14(3):593. https://doi.org/10.3390/atmos14030593

Chicago/Turabian Style

Li, Wenbo, Xinya Zhao, Fengbo Guo, and Kankan Liu. 2023. "Seasonal Characteristics of Fine Particulate Carbonaceous Species in Taiyuan, North China" Atmosphere 14, no. 3: 593. https://doi.org/10.3390/atmos14030593

APA Style

Li, W., Zhao, X., Guo, F., & Liu, K. (2023). Seasonal Characteristics of Fine Particulate Carbonaceous Species in Taiyuan, North China. Atmosphere, 14(3), 593. https://doi.org/10.3390/atmos14030593

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop