A long-term analysis of atmospheric black carbon MERRA-2 concentration over China during 1980–2019
Introduction
Due to the rapid economic development, air pollution has become a prominent environmental problem in China, and particulate matter (PM) is considered as one of the most important pollutants (Shen et al., 2017). Black carbon (BC) formed by the incomplete combustion of fossil fuels, biofuels, and biomass, is considered as the strongest light-absorbing component of PM (Petzold et al., 2013; Ni et al., 2014; Li et al., 2016). Atmospheric BC can directly absorb and scatter solar radiation, and then affect the albedo of snow and clouds, which further influence the regional and global radiation balance and climate (Wang et al., 2014; Bond et al., 2004; Ma, 2015). In addition, the regional climate effects of BC may have been an important reason for the distribution of rainfall in China's southern floods and northern droughts in the past decade (Zhong LJ et al., 2007). In terms of direct radiative forcing, the warming effect of BC is about two-thirds of CO2, which is the second most important factor in global warming (Bond et al., 2004; IPCC, 2013; Gustafsson and Ramanathan, 2016). Meanwhile, BC has the characteristics of porosity and small particle size (Ding et al., 2016). It can adsorb volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs) and other carcinogens (Yuan et al., 2019; Bi et al., 2019; Cui et al., 2020), and then affect human health through respiration (Straif, 2012; Cai, 2013; Zhao, 2014; Kuang et al., 2015). BC was likely to be the main component of the lung toxicity in atmospheric particles (Rosa et al., 2014). Due to the dual impact of BC on environment and human health, the spatio-temporal pollution characteristics of atmospheric BC concentration and its source analysis have received extensive attention (Mbengue et al., 2020; Pavese et al., 2020).
At present, ground monitoring, numerical simulation and remote sensing reanalysis data are three main methods for obtaining atmospheric BC concentration. With optical absorption BC meter or thermal analysis method, BC observations from ground monitoring are usually used to analyze the carbon content in the BC sample, including fixed site monitoring (Zhang et al., 2020) and mobile transect monitoring (Li et al., 2015; Peng et al., 2017; Liu et al., 2018). Based on the atmospheric chemical transport model, numerical simulations describe the diffusion, transmission and transformation quantitatively about air pollutants with the consideration of BC emission sources, underlying surface distribution and horizontal transportation conditions etc. (Manoharan et al., 2011; Raman and Arellano, 2015; Wang, 2016). Satellite monitoring can acquire BC concentration in aerosol optical thickness (AOD) by remote sensing inversion technology (Schuster et al., 2005). However, ground monitoring is limited by instruments, site spatial representation and manual operation. Although satellite monitoring can observe a large area, it is highly susceptible to weather which results in parameters missing, overestimated, or underestimated. NASA's MERRA-2, a data source that assimilates modern satellite measurements to make atmospheric data more accessible (Kuo and Chao, 2017), are increasingly used widely (Qin et al., 2019; Xu et al., 2020). Zhuravleva et al. (2020) showed that the monthly-averaged MERRA-2 BC near-surface concentration can be used for climate assessments in northern Russia, which was hard to reach in the warm season, with an error of about 30%. Compared with single-point measurements, monthly-scale MERRA-2 BC data can more clearly reveal the anomalous increase in BC concentration during short-term smoke aerosol transmission across the entire observation area (Vinogradova et al., 2020).
As the largest developing country in the world, China's land area is over 9.6 million square kilometers. It's considered as a key area and main BC source due to its large emission accounting for 25%–30% of the global (Ni et al., 2014; Mao et al., 2016). Since pollutants can be transported from the Eurasian continent to North America through mid-latitude westerly winds, the higher BC emissions in Asia may have an impact on the global BC concentration (Wilkening et al., 2000), which brings huge pressure to China in the international climate and greenhouse effect negotiations. With the continuous acceleration of regional urbanization and industrialization, BC pollution has become one of the environmental problems in China that can't be ignored.
This study analyzed the long-term spatio-temporal variation of atmospheric BC concentration over China during 1980–2019 through MERRA-2 (Modern-era Retrospective Analysis for Research and Applications, Version 2) reanalysis data. The objectives of the current work were to (1) validate the applicability and accuracy of MERRA-2 BC with ground-based BC observations, (2) distinguish the spatio-temporal pattern of BC concentration, and (3) quantitatively evaluate the spatio-temporal variation of BC concentration at pixel scale. The work can provide reference for effectively controlling the emission of air pollutants in China, improving urban air quality, and providing a theoretical basis for identifying China's energy consumption structure.
Section snippets
MERRA-2 BC reanalysis data
The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) is a new reanalysis data released in 2017 by NASA's Global Modeling and Assimilation Office (GMAO) (Randles et al., 2017). It's based on the Goddard Earth Observing System Model, Version 5 (GEOS-5) and Data Assimilation System, Version 5.12.4 (ADAS-5.12.4). MERRA-2 assimilates and absorbs several AOD datasets including bias-corrected AOD of the Moderate Resolution Imaging Spectrometer (MODIS), the Advanced
Validation of MERRA-2 BC concentration with ground-based observations
The comparison between BC concentration data of MERRA-2 and ground observation (N = 852) from 64 observations in China was showed in Fig. 2. The correlation coefficient (R) between MERRA-2 BC and ground observations was 0.61, with quiet difference R values over six geographical regions. The correlation (R = 0.05) in the Central South was poor and the Southwest had the best correlation (R = 0.91) (Table 1). The overall slope was only 0.52, deviating from the 1:1 line, which indicated that
Conclusions
In this study, we investigated the spatio-temporal variation of MERRA-2 BC over China at the pixel scale during 1980–2019. The MERRA-2 BC concentration generally presented a good correlation with ground observations around China, with the highest accuracy in Southwest (R = 0.91) and the lowest in Central South (R = 0.05). In recent 40 years, the annual-averaged atmospheric MERRA-2 BC concentration was 1.10 ± 0.22 μg/m3, with a yearly rising rate of 1.52%. The monthly MERRA-2 BC concentrations
CRediT authorship contribution statement
Shanshan Cao: Conceptualization, Methodology, Formal analysis, Data curation, Writing – original draft, Visualization. Shiqing Zhang: Formal analysis, Writing – review & editing, Visualization. Chanchan Gao: Methodology, Validation. Yuanyuan Yan: Software, Formal analysis, Data curation. Jiehuan Bao: Writing – review & editing. Ling Su: Methodology, Validation. Mengqing Liu: Investigation. Nana Peng: Investigation. Min Liu: Methodology, Validation, Writing – review & editing.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (41977399, 31800424) and the National key research and development program (2017YFC0505801-01, 2016YFC0500204). The authors would thank the NASA's Global Modeling and Assimilation Office for providing the BC reanalysis data.
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