Next Article in Journal
Improving Intra-Urban Prediction of Atmospheric Fine Particles Using a Hybrid Deep Learning Approach
Previous Article in Journal
The Relationship between Ambient Fine Particulate Matter (PM2.5) Pollution and Depression: An Analysis of Data from 185 Countries
Previous Article in Special Issue
Analysis of BC Pollution Characteristics under PM2.5 and O3 Pollution Conditions in Nanjing from 2015 to 2020
 
 
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/atmos14030598
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:
Article

High Wet Deposition of Black Carbon over the Sichuan Basin of China

by
Yu Zhou
1,2,
Xiaolin Zhang
1,2,3,* and
Yuanzhi Wang
1,2
1
Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Nanjing University of Information Science & Technology, Nanjing 210044, China
2
Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China
3
Department of Earth and Environmental Sciences, The University of Manchester, Manchester M13 9PL, UK
*
Author to whom correspondence should be addressed.
Atmosphere 2023, 14(3), 598; https://doi.org/10.3390/atmos14030598
Submission received: 22 January 2023 / Revised: 11 March 2023 / Accepted: 17 March 2023 / Published: 21 March 2023
(This article belongs to the Special Issue Carbonaceous Aerosols)
Browse Figures
Versions Notes

Abstract

:
The wet deposition flux of black carbon (BC) over the Sichuan Basin is studied on the basis of the MERRA-2 data from 1981 to 2020, aiming at investigating high BC wet deposition flux in China in terms of long-term spatial-temporal trends and influences of BC column mass density and precipitation. In China, the largest BC wet deposition flux with a regionally-averaged value of 1.00 × 10−2 μg m−2 s−1 over the Sichuan Basin is observed, especially in the western and southern regions of the Basin with values as high as 2.20 × 10−2 μg m−2 s−1. The seasonality of BC wet deposition flux over the Sichuan Basin depicts maximum levels in autumn, moderate levels in spring and winter, and minimum levels in summer. The monthly mean BC wet deposition flux varies almost twofold, ranging from the lowest average value of 8.05 × 10−3 μg m−2 s−1 in July to the highest 1.28 × 10−2 μg m−2 s−1 in October. This study suggests that BC column mass density and precipitation are two significant factors affecting high BC wet deposition flux, whereas BC wet deposition flux is more related to BC column mass density than to precipitation over the Sichuan Basin.

1. Introduction

Black carbon (BC) aerosols are mainly generated from the incomplete combustion of biomass and fossil fuels [1,2] and are one of the important components of atmospheric particulate matter with unique physicochemical properties [3]. BC is considered the second strongest warming factor (behind only carbon dioxide) on climate change in the present atmosphere [1]; thus, it has attracted a good deal of attention because of its important local and global climate impacts. Dry and wet depositions are the main pathways for the removal of BC particles from the atmosphere [4,5,6,7] and are the key processes in which regional emitted BC enter the surface ecosystem [8]. Dry deposition includes gravitational sedimentation and direct capture through contact with vegetation and other surface objects, while wet deposition is associated with rainfall or snowfall in which the particles serve as cloud condensation nuclei and there is a subsequent flush of particles during precipitation [9]. Wet deposition is even more significant than dry deposition in maintaining a balance between aerosol emissions and deposition [10,11,12,13]. The efficiency of removing aerosols by wet deposition depends on particle size [14]; wet deposition is most effective for a particle diameter larger than 2 μm, because aerosols are most easily captured by droplets due to a high collision efficiency coefficient [15,16].
Previous studies have examined atmospheric nitrogen and sulfur deposition, showing spatial variability in nitrogen or sulfur deposition as a result of natural and anthropogenic factors [17,18,19]. Meanwhile, multiple studies have reported the spatial and seasonal variations in the wet deposition of carbonaceous aerosols including organic carbon (OC) and elemental carbon (EC) [8,20,21]. At present, most studies are conducted to calculate the wet deposition flux through the EC and OC concentrations in precipitation measured by different measurement methods [22,23,24,25,26]. The global wet deposition of dissolved organic carbon accounts for 430 Tg C/year [27], while the wet deposition of black carbon is about 80% of the global BC deposition [20,28]. Wet deposition is the main way to remove atmospheric particulates [6], and precipitation affects the wet deposition of black carbon [29]. Wet deposition has different characteristics in urban and rural areas [8,18]. For example, the high value of dissolved OC wet deposition is observed in rural areas of the Amazon [30]. The analysis of backward trajectory shows that the long-distance transportation of air mass is also an important factor affecting wet deposition [31,32]. Zhao et al. present the short-term time change in wet deposition of EC and water-insoluble organic carbon measured by the thermo-optic method in Xiamen [33]. Wet deposition in northern China shows similar seasonal changes [34], and this may be due to seasonal variations in human activities or weather conditions such as temperature and precipitation [35]. Because of the extensive emission of BC, the study of BC deposition is particularly important in areas with frequent human activities [36]. Although significant studies regarding short-term BC wet deposition have been performed [29,37,38], there have been few studies reporting long-term spatial-temporal patterns of wet deposition in China.
Here, long-term characteristics of BC wet deposition flux in the Sichuan Basin based on the MERRA-2 data during 1981–2020 are studied. The aim of this paper is to evaluate the spatial distribution of BC wet deposition in China and to assess the long-term spatial-temporal patterns regarding annual, seasonal, and monthly variations in high BC wet deposition in the Sichuan Basin, as well as impacts by BC column mass density and precipitation. The results can help us better understand black carbon removal in the atmosphere so as to provide a scientific basis for the atmospheric environment and ecological balance.

2. Methodology

2.1. Targeted Area

The geographical location of the selected research area is shown in Figure 1. Located in southwestern China, the Sichuan Basin (28° N–32° N, 103° E–108° E) covers about 260,000 km2. The Sichuan Basin has one of the severest cases of air pollution in China, with dense population and industry distribution due to strong anthropogenic emissions and special terrains [39]. Moreover, the Sichuan Basin has the highest topographic relief across the basin [40].

2.2. MERRA-2 Dataset

We used version 2 of the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2) reanalysis dataset produced by the Goddard Earth Observing System Model, Version 5 (GEOS-5) [41]. The MERRA-2 includes for the first time analyzed aerosol fields that are radiatively coupled to the atmosphere, and aerosol and meteorological observations are jointly assimilated in the MEERA-2 with the aim of producing integrated Earth system analysis [42,43]. The MERRA-2 provides a spatial resolution of 0.5° × 0.625° and 72 vertical model levels from 1000 hPa to 0.1 hPa; in addition, there are 1-hourly, 3-hourly, and monthly MERRA-2 products [44]. The MERRA-2 is the most significant long-term global reanalysis and represents their interaction with other physical processes in the climate system [45]. The monthly MERRA-2 datasets for BC wet deposition flux, as well as BC column mass density and precipitation, are employed in this study.

2.3. Pearson Correlation Coefficient

The study shows that BC column mass density and precipitation are the two most important influencing factors in response to BC wet deposition flux [29,34]. Therefore, this study considers BC column mass density and precipitation as the main influential factors affecting the space-time change in BC wet deposition flux for conducting correlation analysis. The correlation coefficient Rxy is calculated as follows:
R x y = ∑ i = 1 n x i − x - y i − y - ∑ i n x i − x - 2 · ∑ i = 1 n y i − y - 2 ,
where Rxy is the correlation coefficient of variables x and y; Xi is BC wet deposition flux in the ith year; Yi is the value of the impact factor in the ith year; BC column mass density (unit: mg m−2) and precipitation (unit: μg m−2 s−1) are the impact factors; and x - and y - are the mean values of BC wet deposition flux and influence factors during n years, respectively.

3. Results and Discussion

3.1. Annual Trends of BC Wet Deposition

As shown in Figure 1, significantly larger BC wet deposition fluxes are observed over the Sichuan Basin than in other areas of China, with a particular concentration in the western and southern regions of the Sichuan Basin. The characteristics of BC wet deposition fluxes in the Sichuan Basin are systematically investigated in the following. Figure 2 shows the spatial distributions of decade mean BC wet deposition flux in the Sichuan Basin from 1981 to 2020. The distributions of BC wet deposition flux depict high values exceeding 1.20 × 10−2 μg m−2 s−1 in the western and southern regions of the Sichuan Basin. For decade variation, the distributions of BC wet deposition flux show similar patterns, and the areas with high BC wet deposition flux become slightly smaller during the recent decade of 2011–2020. The BC wet deposition flux is probably related to BC emissions and the amount of precipitation [46]. The BC wet deposition flux obtained in the Sichuan Basin is higher than that over the Changbai Mountains, which are in a range of 0.09–1.44 μg cm−2 mouth−1 [24].
The annual variations in BC wet deposition flux in the Sichuan Basin from 1981 to 2020 are shown in Figure 3. In the past 40 years, mean BC wet deposition flux in the Sichuan Basin is found to be 1.00 × 10−2 μg m−2 s−1. The annual-averaged BC wet deposition flux in the Sichuan Basin is higher than that in the urban city of Tokyo [47], in the rural city of Averiro, and in a mountain region in Germany [10]. The high wet deposition flux in the Sichuan Basin may have a negative impact on the environmental ecosystem in the Basin. As shown in Figure 3a, the highest value of BC wet deposition flux is 1.44 × 10−2μg m−2 s−1 in 2004, and the lowest is 6.53 × 10−3 μg m−2 s−1 in 1982. The annual trend of BC wet deposition flux is generally similar to the trends of NO3– in Zhang et al. [48] and Cao et al. [49]. This is probably due to the annual trends of BC concentration. As shown in Figure 3b, the BC wet deposition flux during 2001–2010 is the highest among the four decades with a mean value of 1.29 × 10−2 μg m−2 s−1. Low BC wet deposition fluxes are seen during the periods of 1981–1990 and 1991–2000, with the average values being 7.80 × 10−3 and 8.31 × 10−3 μg m−2 s−1, respectively. Since 2000, industry and energy have developed rapidly in China, and various particulate matters including black carbon have increased. To reduce the generation of particulate matter, the Chinese government is taking action regarding the reduction in greenhouse gas emission during the “12th Five-Year Plan” (2011–2015) and the intensity of carbon emissions during the “13th Five-Year Plan” (2016–2020) periods [50]. This may be one of the reasons for the decrease in BC wet deposition flux from 2011 to 2020.

3.2. Seasonal and Monthly Patterns of BC Wet Deposition

The spatial distribution of BC wet deposition flux over the Sichuan Basin from 1981 to 2020 shows obvious seasonality, which is illustrated in Figure 4. BC wet deposition fluxes are generally much higher in the western regions than in the eastern regions of the Sichuan Basin in all seasons. High BC wet deposition fluxes in the southwestern regions of the Sichuan Basin are seen in spring, autumn, and winter, as opposed to high values in the northwestern regions in summer. Moreover, significantly evident spatial differences in BC wet deposition flux are seen between the western and eastern parts of the Sichuan Basin in summer (see Figure 4b). The strongest BC wet deposition fluxes are observed in the southwestern part of the Sichuan Basin in autumn, with values exceeding 2.0 × 10−2 μg m−2 s−1 (see Figure 4c). The Sichuan Basin shows a higher altitude in the northwest and a lower altitude in the southeast, and the north wind prevailing in winter can transport the pollutants from north to south; this probably results in higher BC wet deposition flux in the southern region attributed to the accumulation of BC pollutants caused by the long-distance transportation of air masses [51,52,53].
The seasonal distribution of mean BC wet deposition flux during the past 40 years is shown in Figure 5. As shown in Figure 5a, the autumn season shows the highest wet deposition flux, with an average value of 1.18 × 10−2 μg m−2 s−1, followed by spring and winter with values of 1.02 × 10−2 and 9.31 × 10−3 μg m−2 s−1, respectively, while summer has relatively lower wet deposition flux with a mean value of 8.81 × 10−3 μg m−2 s−1. The BC wet deposition fluxes during four decades show similar seasonality (see Figure 5b). The wet deposition of black carbon during 1981–2000 is lower than the average BC wet deposition in the past 40 years, and the BC wet deposition flux in each season is high during 2001–2020. High BC wet deposition fluxes in autumn are seen in all four decades. The high wet deposition flux occurring in fall possibly corresponds to the high level of BC concentration during this period over the Sichuan Basin [54]. In summer, the BC wet deposition flux is low while the precipitation and BC concentration are large [33]. It is documented that the sparse precipitation amount may induce low BC wet deposition flux in winter [55]. The BC wet deposition flux in the Sichuan Basin obtained in our study is significantly larger than that seen in Lhasa [20] but lower than that seen in Shanghai [8]. Compared with human activities in the Sichuan Basin and Shanghai, there are fewer human activities in Lhasa, indicating that human activities may have an impact on BC wet deposition flux.
The spatial distribution of monthly average BC wet deposition flux over the Sichuan Basin from 1981 to 2020 is illustrated in Figure 6. The monthly patterns of spatial distributions of BC wet deposition fluxes are generally in accordance with their seasonal patterns. High BC wet deposition fluxes in the northwestern parts of the Sichuan Basin are seen in July and August, whereas high values in the southwestern regions are observed in other months. Monthly BC wet deposition flux shows large variability, being mainly due to the variability in BC concentration and precipitation [20,46]. The monthly mean BC wet deposition fluxes over the Sichuan Basin from 1981 to 2020 are shown in Figure 7. Monthly mean BC wet deposition fluxes vary almost twofold, from the lowest average value of 8.05 × 10−3 μg m−2 s−1 in July to the highest 1.28 × 10−2 μg m−2 s−1 in October (see Figure 7a). Zhou et al. observes that the wet deposition flux of organic carbon is low in May and high in July in Changsha [56], which differs from the trends of BC wet deposition flux in our study. There is a significant correlation between wet deposition and precipitation in Changsha; the annual maximum precipitation of Changsha in July is more than 300 mm [56], which may be one of the reasons for the high wet deposition flux of Changsha in July. Organic carbon concentration of Changsha in May is relatively lower than those in other months [56], and therefore, the low value of wet deposition in Changsha may have some relation to organic carbon concentrations. The monthly variations in BC wet deposition flux in the four decades from 1981 to 2020 are shown in Figure 7b. The monthly-averaged BC wet deposition fluxes in the Sichuan Basin from 1981 to 1990 and from 1991 to 2000 are much smaller than those during 2001–2010 and 2011–2020. The BC wet deposition flux from 1981 to 1990 is slightly lower than that during 1991–2000. The BC wet deposition fluxes during the four decades generally show similar monthly variations, with high values in October and low values in July. The high temperature in July aggravates the weather disturbance and vertical mixing, resulting in a decrease in BC concentration; this may be part of the reason for the low BC wet deposition flux [57]. Biomass combustion occurs frequently in autumn, especially October [58], exacerbating the accumulation of BC concentration and leading to the high BC wet deposition flux in October.

3.3. Factors Influencing BC Wet Deposition

To a great extent, the wet deposition flux of black carbon is believed to be controlled by precipitation and BC loading in the atmosphere [46,55,59]. The relationships between BC wet deposition flux and BC column mass density and precipitation are illustrated in Figure 8. As shown in Figure 8a, a weak positive correlation is found between BC wet deposition flux and BC column mass density, indicating that more BC particles are a benefit for larger BC wet deposition flux. Positive correlations between concentrations of atmospheric compositions and their wet deposition flux are also found in Zhang et al. [60] and Yu et al. [61]. The relationship between BC wet deposition flux and precipitation is shown in Figure 8b, and a poor positive correlation is seen. Larger precipitation density can scavenge more BC aerosols and leads to a higher BC wet deposition flux. Similar impacts of precipitation on the wet depositions of aerosols and atmospheric compositions are presented in many previous studies [62,63,64]. Therefore, compared with precipitation, the distribution of BC wet deposition flux is more affected by BC column mass density.
The spatial distributions of the correlation coefficients of BC wet deposition flux with BC column mass density and precipitation over the Sichuan Basin are shown in Figure 9. As shown in Figure 9b,c, the values of the correlation coefficients reflect the significance of the correlations, and the BC wet deposition flux is highly correlated to BC column mass density or precipitation. However, the significance of the correlation of BC wet deposition flux to the BC column mass density or precipitation is not related to the values of the BC wet deposition flux, which is shown in Figure 9a. That is to say, a high correlation coefficient of BC wet deposition flux with BC column mass density or precipitation is not always relevant to large BC wet deposition flux, indicating complicated nonlinear impacts on BC wet deposition by BC concentration, precipitation, and other potential factors. As illustrated in Figure 9b, a high positive correlation coefficient between BC wet deposition flux and BC column mass density is seen at all the positions of the Sichuan Basin, and its values are in a range of 0.794–0.931. Small-scale secondary circulation and relatively lower thermal inversion caused by the plateau topography in the western part of the Sichuan Basin can lead to the accumulation of aerosols at 0.8–1.4 km above ground level [65]. The economic prosperity and large population in the northwestern part of the Sichuan Basin (e.g., the city of Chengdu) and many heavy industries in the southwestern region (e.g., the city of Leshan) produce plenty of black carbon. These generated BC may contribute to large BC wet deposition flux in the southwestern and northwestern parts of the Sichuan Basin, and a high correlation coefficient is seen. As shown in Figure 9c, the correlation coefficient of BC wet deposition flux with precipitation is smaller than its correlation coefficient with BC column mass density. For the spatial distribution, high BC wet deposition flux generally corresponds to a positive correlation coefficient of BC wet deposition flux with precipitation. This may indicate that precipitation contributes to high BC wet deposition due to the scavenging of BC particles by precipitation. In the process of precipitation, black carbon particles migrate through Brownian motion, inertial collision, and the effects of heat, turbulence, electric charge, and concentration gradient, and are finally captured by falling water droplets or ice crystals. However, it should be noted that excessive precipitation can inhibit the wet deposition of black carbon [64]. In general, BC column mass density and precipitation are two significant factors affecting the spatial and temporal distribution of BC wet deposition flux, and BC wet deposition flux is more related to BC column mass density than to precipitation over the Sichuan Basin.
To understand the high BC wet deposition flux over the western and southern parts of the Sichuan Basin, two areas with high BC wet deposition fluxes named region A (28° N–31° N, 103° E–104° E) and region B (28° N–29° N, 104° E–106° E) are selected and shown in Figure 1b. A wet deposition-concentration-precipitation (WETD-C-P) diagram is constructed for regions A and B with high BC wet deposition fluxes and is shown in Figure 10. The WETD-C-P diagrams in both regions show complicated features, indicating complex and combined effects of BC column mass density and precipitation on high BC wet deposition flux. As portrayed in Figure 10, larger BC column mass density or precipitation can generally result in higher BC wet deposition flux.

4. Conclusions

In this study, we investigate long-term characteristics of wet deposition flux of black carbon over the Sichuan Basin during 1981–2020 on the basis of the MEERA-2 data. In China, the highest BC wet deposition flux is observed over the Sichuan Basin with an annual-averaged value of 1.00 × 10−2μg m−2 s−1. The seasonality of BC wet deposition flux depicts maximum mean levels in autumn (1.18 × 10−2 μg m−2 s−1), moderate levels in spring (1.02 × 10−2 μg m−2 s−1) and winter (9.31 × 10−3 μg m−2 s−1), and minimum levels in summer (8.81 × 10−3 μg m−2 s−1). The low BC wet deposition flux in summer is mainly due to the small BC concentration, while the low BC wet deposition flux in winter could be attributed to the sparse precipitation amount. The monthly mean BC wet deposition flux varies almost twofold, ranging from the lowest mean value of 8.05 × 10−3 μg m−2 s−1 in July to the highest 1.28 × 10−2 μg m−2 s−1 in October. BC column mass density and precipitation are two significant factors affecting the spatial and temporal distribution of BC wet deposition flux, and positive correlations of BC wet deposition flux with BC column mass density or precipitation are seen for high BC wet deposition. Nevertheless, BC wet deposition flux is found to be more related to BC column mass density than to precipitation over the Sichuan Basin.

Author Contributions

Conceptualization, Y.Z. and X.Z.; Methodology, Y.Z. and X.Z.; Software, Y.Z., X.Z. and Y.W.; Validation, Y.Z. and X.Z.; Formal analysis, Y.Z. and X.Z.; Investigation, Y.Z. and X.Z.; Resources, X.Z.; Data curation, Y.Z. and X.Z.; Writing—original draft, Y.Z.; Writing—review & editing, X.Z.; Visualization, Y.Z.; Project administration, X.Z.; Funding acquisition, X.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This paper is sponsored by the Qing Lan Project.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are available upon request.

Acknowledgments

This paper is supported by the Qinglan Project. We used the data produced with the Giovanni data system and developed and maintained by the NASA GES DISC in this study. We also acknowledge the mission scientists and Principal Investigators who provided the data used in this research effort.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Bond, T.C.; Doherty, S.J.; Fahey, D.W.; Forster, P.M.; Berntsen, T.; DeAngelo, B.J.; Flanner, M.G.; Ghan, S.; Kärcher, B.; Koch, D.; et al. Bounding the role of black carbon in the climate system: A scientific assessment. J. Geophys. Res. Atmos. 2013, 118, 5380–5520. [Google Scholar] [CrossRef]
  2. Wang, Q.Y.; Huang, R.J.; Cao, J.J.; Tie, X.X.; Shen, Z.X.; Zhao, S.Y.; Han, Y.M.; Li, G.H.; Li, Z.Q.; Ni, H.Y.; et al. Contribution of regional transport to the black carbon aerosol during winter haze period in Beijing. Atmos. Environ. 2016, 132, 11–18. [Google Scholar] [CrossRef]
  3. Homann, K.H. Fullerenes and soot formation-new pathways to large particles in flames. Angew. Chem. Int. Ed. 1998, 37, 2434–2451. [Google Scholar] [CrossRef]
  4. Custodio, D.; Cerqueira, M.; Fialho, P.; Nunes, T.; Pio, C.; Henriques, D. Wet deposition of particulate carbon to the central North Atlantic Ocean. Sci. Total Environ. 2014, 496, 92–99. [Google Scholar] [CrossRef]
  5. Zhang, Y.L.; Cerqueira, M.; Salazar, G.; Zotter, P.; Hueglin, C.; Zellweger, C.; Pio, C.; Prevot, A.S.H.; Szidat, S. Wet deposition of fossil and non-fossil derived particulate carbon: Insights from radiocarbon measurement. Atmos. Environ. 2015, 115, 257–262. [Google Scholar] [CrossRef]
  6. Iavorivska, L.; Boyer, E.W.; DeWalle, D.R. Atmospheric deposition of organic carbon via precipitation. Atmos. Environ. 2016, 146, 153–163. [Google Scholar] [CrossRef] [Green Version]
  7. Sorokina, V.V.; Soier, V.G. Dry and wet atmospheric deposition of organic carbon in coastal and water areas of the northeastern part of the Sea of Azov. Oceanology 2016, 56, 733–741. [Google Scholar] [CrossRef]
  8. Wang, Q.; Feng, W.; Liu, M.; Xu, H. Atmospheric elemental carbon deposition from urban and suburban sites of Shanghai: Characteristics, sources and comparison with aerosols and soils. Atmos. Pollut. Res. 2021, 12, 193–199. [Google Scholar] [CrossRef]
  9. Warneck, P. Chemistry of the Natural Atmosphere, 2nd ed.; Academic Press: New York, NY, USA, 1999; p. 444. [Google Scholar]
  10. Cerqueira, M.; Pio, C.; Legrand, M.; Puxbaum, H.; Kasper-Giebl, A.; Afonso, J.; Preunkert, S.; Gelencsér, A.; Fialho, P. Particulate carbon in precipitation at European background sites. Aerosol Sci. 2010, 41, 51–61. [Google Scholar] [CrossRef] [Green Version]
  11. Kardel, F.; Wuyts, K.; Maher, B.A.; Samson, R. Intra-urban spatial variation of magnetic particles: Monitoring via leaf saturation isothermal remanent magnetization (SIRM). Atmos. Environ. 2012, 55, 111–120. [Google Scholar] [CrossRef]
  12. Yang, F.; Mitra, P.; Zhang, L.; Prak, L.; Verhertbruggen, Y.; Kim, J.S.; Sun, L.; Zheng, K.; Tang, K.; Auer, M. Engineering secondary cell wall deposition in plants. Plant Biotechnol. J. 2012, 11, 325–335. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Pan, Y.P.; Wang, Y.S. Atmospheric wet and dry deposition of trace elements at 10 sites in Northern China. Atmos. Chem. Phys. 2015, 15, 951–972. [Google Scholar] [CrossRef] [Green Version]
  14. Nho-Kim, E.; Michou, M.; Peuch, V. Parameterization of size-dependent particle dry deposition velocities for global modeling. Atmos. Environ. 2004, 38, 1933–1942. [Google Scholar] [CrossRef]
  15. Quérel, A.; Monier, M.; Flossmann, A.I.; Lemaitrea, P.; Porcherona, E. The importance of new collection efficiency values including the effect of rear capture for the below cloud scavenging of aerosol particles. Atmos. Res. 2014, 142, 57–66. [Google Scholar] [CrossRef]
  16. Sic, B.; Amraoui, L.E.; Marécal, V.; Josse, B.; Arteta, J.; Guth, J.; Joly, M.; Hamer, P.D. Modelling of primary aerosols in the chemical transport model MOCAGE: Development and evaluation of aerosol physical parameterizations. Geosci. Model Dev. 2015, 8, 381–408. [Google Scholar] [CrossRef] [Green Version]
  17. Zhu, J.X.; He, N.P.; Wang, Q.F.; Yuan, G.F.; Wen, D.; Yu, G.R.; Jia, Y.L. The composition, spatial patterns, and influencing factors of atmospheric wet nitrogen deposition in Chinese terrestrial ecosystems. Sci. Total Environ. 2015, 511, 777–785. [Google Scholar] [CrossRef]
  18. Luo, X.S.; Pan, Y.P.; Goulding, K.; Zhang, L.; Liu, X.J.; Zhang, F.S. Spatial and seasonal variations of atmospheric sulfur concentrations and dry deposition at 16 rural and suburban sites in China. Atmos. Environ. 2016, 146, 79–89. [Google Scholar] [CrossRef] [Green Version]
  19. Xu, W.; Zhao, Y.H.; Liu, X.J.; Dore, A.J.; Zhang, L.; Liu, L.; Cheng, M.M. Atmospheric nitrogen deposition in the Yangtze River basin: Spatial pattern and source attribution. Environ. Pollut. 2018, 232, 546–555. [Google Scholar] [CrossRef] [Green Version]
  20. Yan, F.; Wang, P.; Kang, S.; Chen, P.; Li, C. High particulate carbon deposition in Lhasa–a typical city in the Himalayan–Tibetan Plateau due to local contributions. Chemosphere 2020, 247, 125843. [Google Scholar] [CrossRef]
  21. Niu, Z.; Huang, Z.; Wang, S.; Feng, X.; Wu, S.; Zhao, H.; Lu, X. Characteristics and source apportionment of particulate carbon in precipitation based on dual-carbon isotopes (13C and 14C) in Xian, China. Environ. Pollut. 2022, 299, 118908. [Google Scholar] [CrossRef]
  22. Hegg, D.A.; Clarke, A.D.; Doherty, S.J.; Ström, J. Measurements of black carbon aerosol washout ratio on Svalbard. Tellus B Chem. Phys. Meteorol. 2011, 63, 891–900. [Google Scholar] [CrossRef] [Green Version]
  23. Mori, T.; Kondo, Y.; Ohata, S.; Moteki, N.; Matsui, H.; Oshima, N.; Iwasaki, A. Wet deposition of black carbon at a remote site in the East China Sea. J. Geophys. Res. Atmos. 2014, 119, 10485–10498. [Google Scholar] [CrossRef]
  24. Wang, Z.W.; Gallet, J.C.; Pedersen, C.A.; Zhang, X.S.; Ström, J.; Ci, Z.J. Elemental carbon in snow at Changbai Mountain, northeastern China: Concentrations, scavenging ratios, and dry deposition velocities. Atmos. Chem. Phys. 2014, 14, 14221–14248. [Google Scholar] [CrossRef] [Green Version]
  25. Hadley, O.L.; Corrigan, C.; Ramanathan, V. Measurements of Black Carbon in California Snow and Rain; California Energy Commission, PIER Energy-Related Environmental Research Program: Sacramento, CA, USA, 2007.
  26. Ohata, S.; Moteki, N.; Kondo, Y. Evaluation of a Method for measurement of the concentration and size distribution of black carbon particles suspended in rainwater. Aerosol Sci. Technol. 2011, 45, 1326–1336. [Google Scholar] [CrossRef] [Green Version]
  27. Willey, J.D.; Kieber, R.J.; Eyman, M.S.; Avery, G.B. Rainwater Dissolved Organic Carbon: Concentrations and Global Flux. Glob. Biogeochem. Cycles 2000, 14, 139–148. [Google Scholar] [CrossRef]
  28. Wu, M.X.; Liu, X.H.; Zhang, L.M.; Wu, C.L.; Lu, Z.; Ma, P.L.; Wang, H.L.; Tilmes, S.; Mahowald, N.; Matsui, H.; et al. Impacts of aerosol dry deposition on black carbon spatial distributions and radiative effects in the Community Atmosphere Model CAM5. J. Adv. Model. Earth Syst. 2018, 10, 1150–1171. [Google Scholar] [CrossRef] [Green Version]
  29. Matsumoto, K.; Kodama, S.; Sakata, K.; Watanabe, Y. Atmospheric deposition fluxes and processes of the water-soluble and water-insoluble organic carbon in central Japan. Atmos. Environ. 2022, 271, 118913. [Google Scholar] [CrossRef]
  30. Coelho, C.H.; Francisco, J.G.; Nogueira, R.F.P.; Campos, M.L.A.M. Dissolved Organic Carbon in Rainwater from Areas Heavily Impacted by Sugar Cane Burning. Atmos. Environ. 2008, 30, 7115–7121. [Google Scholar] [CrossRef]
  31. Zeng, J.; Yu, F.J.; Xia, M.; Wan, Z.J.; Wu, Q.X.; Qin, C.Q. Dissolved organic carbon in rainwater from a karst agricultural area of Southwest China: Variations, sources, and wet deposition fluxes. Atmos. Res. 2020, 245, 105140. [Google Scholar] [CrossRef]
  32. Niu, H.; Kang, S.C.; Shi, X.F.; Zhang, G.T.; Wang, S.J.; Pu, T. Dissolved organic carbon in summer precipitation and its wet deposition flux in the Mt. Yulong region, southeastern Tibetan Plateau. J. Atmos. Chem. 2019, 76, 1–20. [Google Scholar] [CrossRef]
  33. Zhao, H.H.; Chen, L.Q.; Yan, J.P.; Shi, P.; Li, Y.; Li, W. Characteristics of Particulate Carbon in Precipitation during the Rainy Season in Xiamen Island, China. Atmosphere 2016, 7, 140. [Google Scholar] [CrossRef] [Green Version]
  34. Pan, Y.P.; Wang, Y.S.; Xin, J.Y.; Tang, G.Q.; Song, T.; Wang, Y.H.; Li, X.R.; Wu, F.K. Study on Dissolved Organic Carbon in Precipitation in Northern China. Atmos. Environ. 2010, 44, 2350–2357. [Google Scholar] [CrossRef]
  35. Orlović-Leko, P.; Plavšić, M.; Bura-Nakić, E.; Kozarac, Z.; Ćosović, B. Organic Matter in the Bulk Precipitations in Zagreb and Šibenik, Croatia. Atmos. Environ. 2009, 43, 805–811. [Google Scholar] [CrossRef]
  36. Kanakidou, M.; Duce, R.A.; Prospero, J.M.; Baker, A.R.; Benitez-Nelson, C.; Dentener, F.J.; Hunter, K.A.; Liss, P.S.; Mahowald, N.; Okin, G.S. Atmospheric Fluxes of Organic N and P to the Global Ocean. Glob. Biogeochem. Cycles 2012, 26, 1–12. [Google Scholar] [CrossRef]
  37. Matsuda, K.; Sase, H.; Murao, N.; Fukazawa, T.; Khoomsub, K.; Chanonmuang, P.; Visaratana, T.; Khummongkol, P. Dry and wet deposition of elemental carbon on a tropical forest in Thailand. Atmos. Environ. 2012, 54, 282–287. [Google Scholar] [CrossRef]
  38. Jacobi, H.W.; Obleitner, F.; Da Costa, S.; Ginot, P.; Eleftheriadis, K.; Aas, W.; Zanatta, M. Deposition of ionic species and black carbon to the Arctic snowpack: Combining snow pit observations with modeling. Atmos. Chem. Phys. 2019, 19, 10361–10377. [Google Scholar] [CrossRef] [Green Version]
  39. Zhu, S.B.; Xiao, Z.S.; Che, H.Z.; Chen, Q.L. Impact of aerosols on warm clouds over the Sichuan Basin, China in winter based on the MERRA-2 reanalysis dataset. Atmos. Pollut. Res. 2022, 13, 101342. [Google Scholar] [CrossRef]
  40. Zhao, S.P.; Yu, Y.; Yin, D.Y.; Qin, D.H.; He, J.J.; Dong, L.X. Spatial patterns and temporal variations of six criteria air pollutants during 2015 to 2017 in the city clusters of Sichuan Basin, China. Sci. Total Environ. 2018, 624, 540–557. [Google Scholar] [CrossRef]
  41. Randles, C.A.; da Silva, A.M.; Buchard, V.; Colarco, P.R.; Darmenov, A.; Govindaraju, R.; Smirnov, A.; Holben, B.; Ferrare, R.; Hair, J.; et al. The MERRA-2 aerosol reanalysis, 1980 onward. Part I: System description and data assimilation evaluation. J. Clim. 2017, 30, 6823–6850. [Google Scholar] [CrossRef]
  42. Buchard, V.; Randles, C.A.; da Silva, A.M.; Darmenov, A.; Colarco, P.R.; Govindaraju, R.; Ferrare, R.; Hair, J.; Beyersdorf, A.J.; Ziemba, L.D.; et al. The MERRA-2 aerosol reanalysis, 1980 onward. Part II: Evaluation and case studies. J. Clim. 2017, 30, 6851–6872. [Google Scholar] [CrossRef]
  43. Gelaro, R.; McCarty, W.; Suárez, M.J.; Todling, R.; Molod, A.; Takacs, L.; Randles, C.A.; Darmenov, A.; Bosilovich, M.G.; Reichle, R.; et al. The Modern-Era retrospective analysis for research and applications, version 2 (MERRA-2). J. Clim. 2017, 30, 5419–5454. [Google Scholar] [CrossRef] [PubMed]
  44. Hung, W.T.; Lu, C.; Wang, S.H.; Chen, S.P.; Tsai, F.; Chou, C.K. Investigation of long-range transported PM2.5 events over Northern Taiwan during 2005–2015 winter seasons. Atmos. Environ. 2019, 217, 116920. [Google Scholar] [CrossRef]
  45. Global Modeling and Assimilation Office. Available online: https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/ (accessed on 3 July 2019).
  46. Chen, Y.T.; Gao, Y.; Wu, S.L.; Zhang, L.; Wang, Q.Q.; Yao, X.H.; Gao, H.W. Wet deposition of atmospheric selenium and sensitivity to emission and precipitation patterns. Sci. Total Environ. 2022, 835, 155402. [Google Scholar] [CrossRef]
  47. Huo, M.Q.; Sato, K.; Ohizumi, T.; Akimoto, H.; Takahashi, K. Characteristics of carbonaceous components in precipitation and atmospheric particle at Japanese sites. Atmos. Environ. 2016, 146, 164–173. [Google Scholar] [CrossRef]
  48. Zhang, X.Y.; Zhao, L.M.; Cheng, M.M.; Liu, H.L.; Wang, Z.; Wu, X.D.; Yu, H. Long-term changes in wet nitrogen and sulfur deposition in Nanjing. Atmos. Environ. 2018, 195, 104–111. [Google Scholar] [CrossRef]
  49. Cao, S.S.; Zhang, S.Q.; Gao, C.C.; Yan, Y.Y.; Bao, J.H.; Su, L.; Liu, M.Q.; Peng, N.N.; Liu, M. A long-term analysis of atmospheric black carbon MERRA-2 concentration over China during 1980–2019. Atmos. Environ. 2021, 264, 118662. [Google Scholar] [CrossRef]
  50. Yuan, X.; Zuo, J. Transition to low carbon energy policies in China—From the Five-Year Plan perspective. Energy Policy 2011, 39, 3855–3859. [Google Scholar] [CrossRef]
  51. Xu, X.F.; Yang, X.Y.; Zhu, B.; Tang, Z.W.; Wu, H.; Xie, L.F. Characteristics of MERRA-2 black carbon variation in east China during 2000–2016. Atmos. Environ. 2020, 222, 117140. [Google Scholar] [CrossRef]
  52. Wang, H.; Tian, M.; Chen, Y.; Shi, G.; Liu, Y.; Yang, F.; Zhang, L.; Deng, L.; Yu, J.; Peng, C.; et al. Seasonal characteristics, formation mechanisms and source origins of PM2.5 in two megacities in Sichuan Basin, China. Atmos. Chem. Phys. 2018, 18, 865–881. [Google Scholar] [CrossRef] [Green Version]
  53. Feng, X.; Wei, S.; Wang, S. Temperature inversions in the atmospheric boundary layer and lower troposphere over the Sichuan Basin, China: Climatology and impacts on air pollution. Sci. Total Environ. 2020, 726, 138579. [Google Scholar] [CrossRef]
  54. Yu, G.; Jia, Y.; He, N.; Zhu, J.; Chen, Z.; Wang, Q.; Piao, S.; Liu, X.; He, H.; Guo, X. Stabilization of atmospheric nitrogen deposition in China over the past decade. Nat. Geosci. 2019, 12, 424–429. [Google Scholar] [CrossRef]
  55. Yan, F.P.; He, C.L.; Kang, S.C.; Chen, P.F.; Hu, Z.F.; Han, X.W.; Gautam, S.; Yan, C.Q.; Zheng, M.; Sillanpaa, M.; et al. Deposition of Organic and Black Carbon: Direct Measurements at Three Remote Stations in the Himalayas and Tibetan Plateau. J. Geophys. Res. Atmos. 2019, 124, 9702–9715. [Google Scholar] [CrossRef]
  56. Zhou, W.B.; Xiang, W.H.; You, Y.Y.; Ouyang, S.; Zhao, Z.H.; Zhang, S.L.; Zeng, Y.L.; Li, J.R.; Wang, J.R.; Wang, K.L. Atmospheric Wet Deposition of Organic Carbon and Dissolved Nitrogen in City, Countryside and Nature Reserve of Subtropical China. J. Am. Water Resour. Assoc. 2020, 56, 1045–1058. [Google Scholar] [CrossRef]
  57. Zhang, X.; Huang, Y.; Rao, R. Aerosol characteristics including fumigation effect under weak precipitation over the southeastern coast of China. J. Atmos. Sol.-Terr. Phys. 2012, 84–85, 25–36. [Google Scholar] [CrossRef]
  58. Yang, F.; He, K.; Ye, B.; Chen, X.; Cha, S.H.; Cadle, S.H.; Chan, T.; Mulawa, P.A. One-year record of organic and elemental carbon in fine particles in downtown Beijing and Shanghai. Atmos. Chem. Phys. 2005, 5, 1449–1457. [Google Scholar] [CrossRef] [Green Version]
  59. Witkowska, A.; Lewandowska, A.; Falkowska, L.M. Parallel measurements of organic and elemental carbon dry (PM1, PM2.5) and wet (rain, snow, mixed) deposition into the Baltic Sea. Mar. Pollut. Bull. 2016, 104, 303–312. [Google Scholar] [CrossRef] [PubMed]
  60. Zhang, Q.Y.; Wang, Q.F.; Zhu, J.X.; Xu, L.; Chen, Z.; Xiao, J.F.; He, N.P. Spatiotemporal variability, source apportionment, and acid-neutralizing capacity of atmospheric wet base-cation deposition in China. Environ. Pollut. 2020, 262, 114335. [Google Scholar] [CrossRef] [PubMed]
  61. Yu, X.; Pan, Y.P.; Song, W.; Li, S.; Li, D.; Zhu, M.; Zhou, H.S.; Zhang, Y.L.; Li, D.J.; Yu, J.Z.; et al. Wet and Dry Nitrogen Depositions in the Pearl River Delta, South China: Observations at Three Typical Sites With an Emphasis on Water-Soluble Organic Nitrogen. J. Geophys. Res. Atmos. 2020, 125, e2019JD030983. [Google Scholar] [CrossRef]
  62. Chen, Z.L.; Huang, T.; Huang, X.H.; Han, X.X.; Yang, H.; Cai, Z.C.; Yao, L.; Han, X.; Zhang, M.G.; Huang, C.C. Characteristics, sources and environmental implications of atmospheric wet nitrogen and sulfur deposition in Yangtze River Delta. Atmos. Environ. 2019, 219, 116904. [Google Scholar] [CrossRef]
  63. Zhao, H.B.; Zheng, C.G. Monte Carlo solution of wet removal of aerosols by precipitation. Atmos Environ. 2006, 40, 1510–1525. [Google Scholar] [CrossRef]
  64. Wu, Y.N.; Liu, J.K.; Zhai, J.X.; Cong, L.; Wang, Y.; Ma, W.M.; Zhang, Z.M.; Li, C.Y. Comparison of dry and wet deposition of particulate matter in near-surface waters during summer. PLoS ONE 2018, 13, e0199241. [Google Scholar] [CrossRef] [PubMed]
  65. Yuan, L.; Zhang, X.L.; Che, Y.Z.; Xia, X.A.; Liu, X.; Zhao, T.L.; Song, M.H. Vertical profile and radiative forcing of black carbon in a winter pollution period over Chengdu, China. Atmos. Res. 2022, 265, 105896. [Google Scholar] [CrossRef]
Atmosphere 14 00598 g001 550
Figure 1. Location of the site selected in this study (a). Black box denotes the study area of the Sichuan basin (28° N–32° N, 103° E–108° E) in China (b). Red boxes denote the study areas with high BC wet deposition values over the western (region A) and southern (region B) parts of Sichuan Basin. Unit: μg m−2 s−1.
Figure 1. Location of the site selected in this study (a). Black box denotes the study area of the Sichuan basin (28° N–32° N, 103° E–108° E) in China (b). Red boxes denote the study areas with high BC wet deposition values over the western (region A) and southern (region B) parts of Sichuan Basin. Unit: μg m−2 s−1.
Atmosphere 14 00598 g001
Atmosphere 14 00598 g002 550
Figure 2. Spatial distribution of decade mean black carbon wet deposition flux over the study area in the Sichuan Basin during 1981–1990 (a), 1991–2000 (b), 2001–2010 (c), and 2011–2020 (d). Unit: μg m−2 s−1.
Figure 2. Spatial distribution of decade mean black carbon wet deposition flux over the study area in the Sichuan Basin during 1981–1990 (a), 1991–2000 (b), 2001–2010 (c), and 2011–2020 (d). Unit: μg m−2 s−1.
Atmosphere 14 00598 g002
Atmosphere 14 00598 g003 550
Figure 3. Annual variations of area-averaged black carbon wet deposition flux over the Sichuan basin from 1981 to 2020 (a) and in four periods (b) during 1981–1990, 1991–2000, 2001–2010 and 2011–2020.
Figure 3. Annual variations of area-averaged black carbon wet deposition flux over the Sichuan basin from 1981 to 2020 (a) and in four periods (b) during 1981–1990, 1991–2000, 2001–2010 and 2011–2020.
Atmosphere 14 00598 g003
Atmosphere 14 00598 g004 550
Figure 4. Mean spatial distribution of black carbon wet deposition flux in spring (a), summer (b), autumn (c), and winter (d) over the Sichuan Basin during 1981–2020. Unit: μg m−2 s−1.
Figure 4. Mean spatial distribution of black carbon wet deposition flux in spring (a), summer (b), autumn (c), and winter (d) over the Sichuan Basin during 1981–2020. Unit: μg m−2 s−1.
Atmosphere 14 00598 g004
Atmosphere 14 00598 g005 550
Figure 5. Seasonal variations of area-averaged black carbon wet deposition flux over the Sichuan Basin from 1981 to 2020 (MAM, JJA, SON and DJF represent spring, summer, autumn, and winter, respectively) (a) and in four periods (b) during 1981–1990, 1991–2000, 2001–2010, and 2011–2020.
Figure 5. Seasonal variations of area-averaged black carbon wet deposition flux over the Sichuan Basin from 1981 to 2020 (MAM, JJA, SON and DJF represent spring, summer, autumn, and winter, respectively) (a) and in four periods (b) during 1981–1990, 1991–2000, 2001–2010, and 2011–2020.
Atmosphere 14 00598 g005
Atmosphere 14 00598 g006 550
Figure 6. Spatial distribution of monthly variations of black carbon wet deposition flux over the Sichuan Basin during 1981–2020. Unit: μg m−2 s−1.
Figure 6. Spatial distribution of monthly variations of black carbon wet deposition flux over the Sichuan Basin during 1981–2020. Unit: μg m−2 s−1.
Atmosphere 14 00598 g006
Atmosphere 14 00598 g007 550
Figure 7. Monthly variations of area-averaged black carbon wet deposition flux over the Sichuan basin from 1981 to 2020 (a) and in four periods (b) during 1981–1990, 1991–2000, 2001–2010, and 2011–2020.
Figure 7. Monthly variations of area-averaged black carbon wet deposition flux over the Sichuan basin from 1981 to 2020 (a) and in four periods (b) during 1981–1990, 1991–2000, 2001–2010, and 2011–2020.
Atmosphere 14 00598 g007
Atmosphere 14 00598 g008 550
Figure 8. Relations between BC wet deposition flux and BC column mass density (a), and precipitation (b).
Figure 8. Relations between BC wet deposition flux and BC column mass density (a), and precipitation (b).
Atmosphere 14 00598 g008
Atmosphere 14 00598 g009 550
Figure 9. The spatial distribution of BC wet deposition flux (unit: μg m−2 s−1) (a), and spatial distributions of correlation coefficients of BC wet deposition flux with BC column mass density (b) and precipitation (c) over the Sichuan basin.
Figure 9. The spatial distribution of BC wet deposition flux (unit: μg m−2 s−1) (a), and spatial distributions of correlation coefficients of BC wet deposition flux with BC column mass density (b) and precipitation (c) over the Sichuan basin.
Atmosphere 14 00598 g009
Atmosphere 14 00598 g010 550
Figure 10. The wet deposition-concentration-precipitation (WETD-C-P) relationships. The relationships of monthly BC wet deposition flux with precipitation and BC column mass density in region A (28° N–31° N, 103° E–104° E) (a) and region B (28° N–29° N, 104° E–106° E) (b).
Figure 10. The wet deposition-concentration-precipitation (WETD-C-P) relationships. The relationships of monthly BC wet deposition flux with precipitation and BC column mass density in region A (28° N–31° N, 103° E–104° E) (a) and region B (28° N–29° N, 104° E–106° E) (b).
Atmosphere 14 00598 g010
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

Zhou, Y.; Zhang, X.; Wang, Y. High Wet Deposition of Black Carbon over the Sichuan Basin of China. Atmosphere 2023, 14, 598. https://doi.org/10.3390/atmos14030598

AMA Style

Zhou Y, Zhang X, Wang Y. High Wet Deposition of Black Carbon over the Sichuan Basin of China. Atmosphere. 2023; 14(3):598. https://doi.org/10.3390/atmos14030598

Chicago/Turabian Style

Zhou, Yu, Xiaolin Zhang, and Yuanzhi Wang. 2023. "High Wet Deposition of Black Carbon over the Sichuan Basin of China" Atmosphere 14, no. 3: 598. https://doi.org/10.3390/atmos14030598

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