Black carbon (BC) is a part of anthropogenic aerosols in atmosphere, formed by the incomplete combustion of fossil fuels and biomass burning (Bond and Bergstrom, 2006; Petzold et al., 2013). Fossil fuel combustion is usually the dominant BC source in cities, especially over the Northern Hemisphere (Saha and Despiau, 2009). BC can absorb shortwave solar radiation, modulate snow reflectance and snowmelt, alter the cloud lifetime, penetrate into the lungs, and also carry a variety of toxic elements (Ackerman et al., 2000; Anenberg et al., 2011; Bond et al., 2013; Stohl et al., 2015; Schmale et al., 2017). BC influences the climate, weather, air quality, and people’s health. Hence, the temporal variation and sources of BC have become hot topics among the scientific community (Li C. L. et al., 2016; Liu et al., 2016; Winiger et al., 2016).

The variation of BC is very important because it can help us to understand the climate change and pollutant dynamics (Wang et al., 2016). A number of BC observation experiments have been performed worldwide, including the measurements of BC concentration in western United States and the Hindu–Kush–Himalayan region (Kaspari et al., 2014, 2015). In addition, the BC aerosol observation by Saha and Despiau (2009) displayed significant temporal variations over Toulon in the Mediterranean coast, southeast of France. The characteristics of BC were also studied at two different climatic regimes in India in the 2007 winter and spring (Srivastava et al., 2012). There were also reports of BC vertical profile measured by aircraft missions over North America, Europe, Arctic, and so on (Spackman et al., 2010; Schwarz et al., 2017). The in-situ measurements by Schwarz et al. (2008) indicated that the microphysical state of BC aerosol is different between fresh urban and biomass burning emissions. Reddington et al. (2013) compared the mass and number size distribution of BC over Europe, finding the model–observation biases in properties. The reliability and stability of different instruments were ascertained by comparing BC mass concentrations (Pan et al., 2011; Kanaya et al., 2013; Irwin et al., 2015).

For the Asian region, many scientists have found that East Asia is a major source of BC, even relevant to the BC particles over the Pacific and Arctic (Zhang et al., 2009; Kurokawa et al., 2013; Zhang J. et al., 2015). However, studies of BC observations in East Asia are limited, although some research reports have been presented in recent years (Pan et al., 2011; Zhang et al., 2012; Chuang et al., 2014). For example, long-term observations of atmospheric BC at Fukue Island in Japan provided the data of precipitation and the emission strength of important source regions in East Asia (Kanaya et al., 2016). Cao et al. (2004) investigated the spatial and seasonal variations of atmospheric organic carbon and elemental carbon over China’s Pearl River delta region in the winter and summer of 2002. Meanwhile, other researchers determined the carbonaceous aerosol composition over different parts of China in 2006 (Zhang et al., 2008a). There were also discontinuous measurements of BC concentration in the atmosphere of Qilian Mountain in Northwest China from May 2009 to March 2011 (Zhao et al., 2012). Scientists also found that BC concentration can rise up to a high level during heavy pollution events (Wang et al., 2014; Zhang Y. L. et al., 2015). Regarding the heterogeneous BC emissions, not many studies have involved in the BC temporal variation at the background stations of China. More observational data are essential for elucidating the atmospheric status (Kanaya et al., 2016).

The source area of observed BC data is important and should be determined quantitatively for developing appropriate emission reduction strategies (Hirdman et al., 2009; Hirdman et al., 2010; Pfaffhuber et al., 2012). Some studies focused on observations and possible sources of BC at several unban sites in China (Li et al., 2005; Tao et al., 2009; Chen et al., 2013; Zhuang et al., 2014; Zhang Y. L. et al., 2015). The sources of observed pollutants are usually identified based on air mass trajectories (Polissar et al., 2001; Sharma et al., 2006; Zhao et al., 2012). For example, four potential BC source regions at Hok Tsui were identified by the hybrid single-particle Lagrangian integrated trajectories (HYSPLIT) model and the potential source contribution function (PSCF) (Cheng et al., 2006). In addition, there were studies on source sectors and regional contributions to BC in central Asia and in China by using chemical transport model (Kulkarni et al., 2015; Li K. et al., 2016). However, compared with individual trajectories, the Lagrangian particle dispersion model is more accurate and quantitative (Han et al., 2005; Hirdman et al., 2010). Thus, in this paper, we will do statistical analysis of the BC sources in large areas around the two regional background stations, that is, Lin’an (LAN) and Longfengshan (LFS), depending on the Lagrangian particle dispersion model. We will also investigate the temporal variation of atmospheric BC at LAN and LFS on diurnal, monthly, and yearly timescales. The Lagrangian particle dispersion model will be combined with BC observation data to find the potential source regions.

For the arrangement of this paper, the observation stations, observations, and statistical analysis method are introduced in Section 2. Section 3 presents the results and discussion, consisting of two parts: (1) temporal variation of BC and (2) source region identification. Finally, summary and conclusions are provided in Section 4.

LAN and LFS observation stations are the regional atmospheric background stations of the World Meteorological Organization/Global Atmosphere Watch (WMO/GAW), representing the atmospheric situation of the Yangtze River delta economic zone and Northeast China (An et al., 2013). The two stations are typically located about 50–100 km away from local pollutant sources (Zhang et al., 2008a). The geographical locations of LAN and LFS stations and the BC emissions of the Hemispheric Transport of Air Pollution (HTAP) dataset for year 2010 are shown in Fig. 1.

Figure 1 BC emissions of the Hemispheric Transport of Air Pollution (HTAP) dataset for year 2010 and geographical locations of LAN (Lin’an) and LFS (Longfengshan). LAN and LFS are regional background sites of WMO/GAW.

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The LAN station (30.30°N, 119.73°E, 138.6 m a.s.l.) is in the southern part of Yangtze River Delta, lying on the top of a small hill within Lin’an City of Zhejiang Province in southern China, about 50 km to the west of Hangzhou, 150 km to the southwest of Shanghai, and 300 km to the southeast of Nanjing (Xia et al., 2015). This station is surrounded by woodland, farming areas, and hilly lands, belonging to distinct subtropical monsoon climate. The prevailing winds are northeasterly and southwesterly winds with the influence of atmospheric circulation (Pu et al., 2014).

The LFS station (44.73°N, 127.60°E, 330.5 m a.s.l.) is located on the top of the Longfengshan Mountain within Wuchang of Heilongjiang Province, which is approximately 40 km to the southeast of Wuchang and 175 km to the southeast of Harbin City (Fang et al., 2014). LFS is situated in the transition zone of agriculture and forestry areas. The north and west of LFS is Songnen Plain, where rice and corn are planted most. The east and south of LFS are covered by extensive forests. No big cities and industrial zones exist within 40 km ranges around the station, and climate there is typical temperate monsoon climate (Liu et al., 2009).

Black carbon (BC) concentration is continuously monitored at the stations of China Meteorological Administration (CMA) Atmosphere Watch Network. The AE-31 Aethalometer (Magee Scientific Corporation, USA), a commonly used observation instrument, has been installed to measure atmospheric BC concentration at seven wavelengths of 370, 470, 520, 590, 660, 880, and 950 nm (Zhao et al., 2012). The instrument is composed of air sampling system, filter fiber-advance structure, optical system, and data collection and processing system. Aerosol samples with a time resolution of 5 min have been collected from the 10- and 6-m tall buildings at LAN and LFS respectively by using the inlet tube and pump operated at a stable airflow rate about 3.9 L min^–1 for 24 h day^–1. BC data are then aggregated from 5-min values to hourly averages.

Due to strong optical absorption of BC particles, BC concentrations can be derived from the linear relationship between BC concentration and extinction coefficient. The light beam transmits separately through referenced (blank) spot and the sampling spot. The transmission of the light is detected by photoelectric diode. Extinction coefficient is converted into BC concentration with absorption efficiency. Attenuation absorption coefficient ATN(λ) and BC concentrations C_BC are calculated as follows (Cheng et al., 2006):

where I₀ and I are separately transmission light intensities of the reference and the sample beams at time period of t (s), A (m²) is the area of the sampling spot on the filter, k (m² g^–1) is absorption efficiency that varies as a function of wavelength, and Q (L min^–1) is the sampling airflow rate. Generally, the real BC concentration in the atmosphere is calculated at 880 nm with absorption efficient of 12.6 m² g^–1 (Bodhaine, 1995; Zhang et al., 2008b; Wang et al., 2016). At this wavelength, the light-absorbing contribution of other particle matters can be approximately neglected (Yang et al., 2009).

To ensure the data quality, the instrument, that is, AE-31 Aethalometer, is examined and maintained routinely by professional staff in order to make it work in the good condition. The filter tape for collecting the aerosol sample is automatically advanced when its optical density attains a pre-set value. We also note the possible loading and scattering effects of Aethalometer data. With regard to loading effects, corrections have been partly made to the data to account for changes in attenuation with the accumulation of material on the tape (Virkkula et al., 2007; Cape et al., 2012). Aerosol scattering effects are not taken into account in this work. Therefore, the term “optical absorption” is implicitly to represent absorption derived from attenuation measured on the filter tape of the Aethalometer. Despite the influence of above effects, the Aethalometer data are suitable to use in general. Totally, 644 and 606 daily data of BC were collected at LAN and LFS from 1 January 2009 to 31 December 2010，respectively. The instrument at LAN station stopped working in March and April 2010 and the one at LFS station failed to work in August, September, and November 2009.

To identify the possible source regions of the observed BC, a statistical method is employed through 3-h backward simulations with the FLEXible PARTicle dispersion model (FLEXPART；Stohl, 2006). In the FLEX-PART model, 50000 particles are released at the measurement point at the interval of every 3 hours and followed backward for 7 days to calculate an emission sensitivity (s), under the assumption that removal processes could be neglected. The variable s is determined by the particle residence time in grid cell and reflects the potential impact of BC sources on the observation site, which can also be explained as the transport climatology (Hirdman et al., 2010). The distribution of s with the 1° × 1° horizontal resolution in a 100-m vertical layer adjacent to the surface is used as an input to our statistical analysis of possible source region. The method is performed in following steps.

If the number of selected BC data is M, the process of s calculation will be repeated M times. The variable s(i, j, m)，which corresponds to the mth BC concentration，is the mth (m = 1, …, M) emission sensitivity in a particular surface grid cell (i, j). The total (M) emission sensitivity s_tot (i, j) is calculated as

Next, we select the subset of the data with the highest 25% (or, respectively, lowest 25%) of measured BC concentrations and calculate

where the suffix p can be either 25 or 75, indicating the percentile. Generally, both s_tot and s_p decrease with distance away from the observation site. The relative fraction R_p is calculated to remove this bias. The ratio

can be used for identifying grid cells which are the likely sources of BC. If air mass transport patterns are the same for the data subset and for the full data set, we will expect R_p(i, j) = 0.25 for all (i, j) grid cells. Information on the sources of BC is contained in the deviation from this expected value. When using the top 25% of the measurement data, R₇₅(i, j) > 0.25 indicates that high measured BC concentration is preferentially associated with transport through grid cell ( i, j), making (i, j) a potential source. Conversely, R₇₅(i, j) < 0.25 indicates that cell ( i, j) is a possible sink or less likely to be a source. On the contrary, when using the lowest 25% of the measurement data, R₂₅(i, j) > 0.25 indicates a likely sink in grid cell ( i, j), and R₂₅(i, j) < 0.25 a likely source or at least the absence of a sink. We emphasize that the “sink” region mentioned below means source free region or where the transported air would experience strong scavenging by precipitation.

In principle, the statistical method introduced above for identifying possible BC source regions is similar to the trajectory residence time analysis but takes advantage of the superior quality of FLEXPART output (Ashbaugh, 1983; Crawford et al., 2007; Wang et al., 2009; Hirdman et al., 2010; Qu et al., 2010). Not all features of the R_p field are statistically significant. Therefore, R_p(i, j) is only calculated in grid cells where s_tot (i, j) > s_T. This threshold s_T is a compromise between the need to remove spurious values and the desired large spatial coverage.

The diurnal variation of BC mass concentration is shown in Fig. 2. Compared with LFS station, the BC concentration at LAN station is higher on the whole, which is mainly attributed to more anthropogenic emissions in Yangtze River delta than in Northeast China. The mean diurnal variations of BC mass concentration at LAN and LFS during 2009–10 (Figs. 2a, b) present two peaks, which resemble the previous observations at other locations (Srivastava et al., 2012). The two peaks appear at about 0800 and 1900 BT (Beijing Time) for both stations. The morning peak at LAN is probably attributed to the morning build-up of local anthropogenic emissions, such as the morning traffic activities. However, the morning peak at LFS is weak, and the reason is not clear. As solar heating increases in the day, the turbulent effect leads to faster dispersion of aerosols (Latha and Badarinath, 2004). Therefore, lower values of BC may occur during afternoon hours (around 1400 BT) owing to deeper boundary layer. After that, the BC mass concentration begins to increase, reaching the second peak, higher than the morning peak. The mean BC concentration is in the diurnal range of 3.53–5.19 μg m^–3 at LAN, bigger than the value 2.64–3.65 μg m^–3 at LFS. However, the mean BC concentration is always bigger than the median values at either LAN or LFS station. The difference between the mean and the median concentration of BC is uniform on the whole in different months at LAN, which is apparently bigger at night than in the daytime for LFS station. The hourly standard deviation at LAN is relatively uniform and smaller than the corresponding value at LFS, especially at night. The characteristics of the above BC diurnal variation imply that anthropogenic activities are much more at LAN than at LFS, and the two stations are affected by different high emission factors, such as industrial production, the morning and evening traffic activities, and heating at night in winter in Northeast China (Zhang et al., 2012; Zhuang et al., 2014).

In addition, the diurnal variation of hourly mean BC concentration in weekdays (Monday–Friday), Saturday, and Sunday at LAN and LFS are given in Figs. 2c, d. The BC concentration tends to change in similar trends, especially at LAN. However, there are very different characteristics in detail. At LAN, the BC concentration is apparently higher on Saturday than in the other days, and the morning peak is from about 0800 BT (during weekdays and Saturday) to about 0700 BT (Sunday). Besides, taking the BC concentration at LAN for two periods of 0000–0700 and 1700–2300 between weekdays and Sunday into consideration, we can infer that more people stay outdoors for leisure activities in the rest days (Chen et al., 2012). At LFS station, the diurnal variation of BC mass concentration is similar between Saturday and weekdays on the whole, except the slightly higher and lower BC concentrations on Saturday for several hours before and after 1600 BT respectively. The morning BC peak at LFS is less pronounced on Sunday, that is, the BC concentration is kept in a higher concentration during 0800–1100 BT. The afternoon valley and evening peak of BC at LFS are nearly 2 h later on Sunday than in weekdays. Compared with LAN, the traffic density is lower and more people are willing to stay indoors as the result of cold weather (particularly in winter) at LFS. Therefore, the weekdays/ weekend effect could be probably attributed to the influence of different daily lives (Saha and Despiau, 2009).

Further, the hourly data for the entirely identical months in 2009 and 2010 are grouped together to investigate the BC diurnal cycle in different months at LAN and LFS (Figs. 2e, f). The evening peak is stronger than the morning peak due to the additive effects of emissions peak and shallow boundary layer dynamics (Chen et al., 2013). The morning peak might be influenced by local sunrise and traffic density (Saha and Despiau, 2009). The diurnal variation of BC mass concentration is related to different months (Cheng et al., 2006). The BC concentration at LAN shows strong morning and evening peaks from January to December. The morning peak at LAN occurs at about 0800 BT every month, and the evening peak varies during 1800–2000 BT. Particularly, the lower BC concentration and diurnal variation in February and the higher counterparts in April at LAN are possibly caused by the changes of anthropogenic emissions, such as the reduction of industry production during the Spring Festival (Zhang et al., 2008a). However, the morning and evening peaks at LFS are unapparent or almost absent from March to September. At LFS, there is a shift about 2 h in the morning peak for the rest of the year and pronounced evening peak owing to heating during the winter.

Figure 2 (a) Diurnal variation of BC concentrations from all the data collected during 2009–10 at LAN. The curves with squares, bars, and dots present the arithmetic mean, standard deviation, and median concentration for that time, respectively. (c) Diurnal variation of BC mass concentration for weekdays, Saturday, and Sunday at LAN. Each point represents the average concentration for that time for the respective days. (e) Monthly mean diurnal variation of BC mass concentration from January to December at LAN. Each grid represents the average concentration for that time for the whole month. BC values for identical months in 2009 and 2010 are averaged. (b), (d), and (f) As in (a), (c), and (e), but for LFS.

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The monthly BC concentrations from all the data collected at LAN and LFS stations during 2009–10 present the trend of seasonal variation apparently (Fig. 3). There are some different characteristics at the two stations. The ranges of seasonal variation at the two sites are close to each other, but the level of BC concentration is higher at LAN than at LFS. The median BC concentration shows the highest value in April (7.1 μg m^–3) and the lowest in July (2.2 μg m^–3) at LAN, while the highest monthly median concentration of 5.0 μg m^–3 is in January and the lowest of 0.6 μg m^–3 in July at LFS. Monthly variation of BC concentrations at LAN presents double-peak distribution, different from the single peak at LFS. The monthly average BC mass concentrations are always bigger than the median values. The difference between the arithmetic mean and the median concentration of BC at LAN hardly changes with month. But the same difference at LFS is markedly bigger in heating months (from October to next April) than in other time, which implies that there are more high emission events during this period. The monthly standard deviations at LAN and LFS present similar variation features to the differences mentioned above. The BC concentrations at LAN and LFS are higher in winter than in summer, similar to that in Pearl River delta region, China (Cao et al., 2004).

To further analyze the seasonal variation of BC concentration, the monthly anthropogenic emissions of BC in the 0.1°×0.1° LAN and LFS grid cells are extracted from the HTAP emissions inventory for the year 2010, shown by squares and lines in Figs. 3c, d. The relative contributions of main sectors (transport, industry, residential, and energy) are also shown by stack columns in Figs. 3c, d. The monthly BC emissions in the LAN grid cell are nearly 8 times stronger than that of LFS, probably leading to the different levels of observed BC concentration. In addition to propitious conditions for pollutant dispersion (Saha and Despiau, 2009), the emissions influencing the observed BC might be lower in summer than in winter. Meanwhile, the contribution of various sectors to BC concentration varies with seasons (Li K. et al., 2016). Residential contribution is predominant at LFS, especially in the heating season. Generally, the seasonal variation of observed BC concentration at LFS is mainly controlled by residential emission. Industry at LAN may be the biggest contributor to BC emission except in January and February. The seasonal variation of industry and total BC emissions at LAN seems in an opposite phase. At LAN, the peak and valley of BC observation in April and February are caused possibly by the change of industrial production during holidays, such as the Spring Festival in China. In addition, the observed BC concentrations at regional background station are influenced by specific regional emissions, not just by the single grid cell emission (Cheng et al., 2015).

Figure 3 Monthly BC concentration from all the data collected during 2009–10 and statistics of 0.1° × 0.1° HTAP emission inventory for year 2010. (a) The curves with squares, bars, and dots present the arithmetic mean, standard deviation, and median value of observed BC concentration at LAN station, respectively. (c) The squares and lines denote the anthropogenic emissions of BC in the LAN grid cell. Stack columns denote the relative contributions to grid-cell BC emissions from individual sectors. (b, d) As in (a, c), but for LFS.

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BC concentrations are continuously observed at LAN and LFS stations. As shown in Fig. 4a, the annual arithmetic mean concentrations and standard deviations of LAN and LFS are 3.47 ± 2.28 and 2.94 ± 4.25 μg m^–3 in 2010, respectively. Compared with the mean values in 2009, the BC concentrations decrease sharply at LAN (1.63 μg m^–3) and slightly at LFS (0.26 μg m^–3). But compared with the annual averaged daily concentrations for Elemental Carbon (EC) during 2006 at LAN (4.8 μg m^–3) and LFS (2.4 μg m^–3), the variations of BC concentrations are different (Zhang et al., 2008a, 2012). The decrement might respond to reduction of emissions, such as industry and transport. The median concentration is always smaller than the mean value, representing the influence of frequent high emission events to BC observation. The standard deviation is obviously bigger at LFS than at LAN, probably reflecting the difference of BC source emissions.

In order to eliminate local source and sink influences, background concentrations are obtained by two methods of robust extraction of background signal (REBS) and frequency statistics (FS) (Ruckstuhl et al., 2012; Xu et al., 2014), which represent the fully mixing regional atmospheric condition. The time series of hourly observed BC concentrations are screened into background and non-background with the bandwidth of 60 days by REBS method. The Gaussian fitting is applied to relative frequency distribution of hourly observed BC concentrations, and then the background value is matched with the BC concentration at the maximum relative frequency. The annual BC background concentration and standard deviation are shown in Figs. 4b, c. They are much bigger than the BC background concentrations in western China (Tang et al., 1999; Ming et al., 2010; Zhao et al., 2012), but smaller than the annual mean BC concentrations at urban site in Nanjing of China in 2012 (Zhuang et al., 2014). Although BC background concentration is congruous at the same station, both of the two methods reveal that BC background concentration at LAN is twice higher than that at LFS. Maybe the BC background at LAN represents the air pollutant situation in Yangtze River delta, one of the rapid development regions of economy in China. However, the BC background at LFS represents atmospheric condition in Northeast China. As shown in Fig. 4c, the BC background at LAN changes with the bigger standard deviation than that at LFS, which is opposite to the characteristic of observed BC standard deviation in Fig. 4a. Thus, we can infer that there are extremely high values at LFS, which might be attributed to heating in winter.

Furthermore, the anthropogenic emissions of BC in the LAN and LFS grid cells are extracted from the HTAP emissions inventory for years 2008 and 2010, shown by squares and lines in Fig. 4d. The HTAP dataset consists of 0.1° × 0.1° grid-maps of yearly and monthly BC emitted by various sectors (air, shipping, energy, industry, transport, and residential) (Li K. et al., 2016). The relative contribution ratio of each sector to total BC emission in the site grid cell is also shown in Fig. 4d. Due to the difference in geographical location and climate, emissions strength and sector contribution are very different at the two stations. Emission strength is over eight times stronger at LAN than at LFS. Industry is the major source at LAN station, almost contributing 0.46–0.48 to the total emissions in 2008 and 2010. Residential emissions are the dominant source at LFS station, contributing more than 0.71 to the total emissions in 2008 and 2010. Transport is the second major emissionssource for the two stations, contributing 0.22–0.35. Owing to different source contributions, the emissions reduction can lead to different decrements of BC concentration. What needs to be noted is that the contribution of biomass burning is not taken into account.

Figure 4 BC concentration and statistics of emission inventory at LAN and LFS stations. (a) The square, bar, and dot respectively show the annual arithmetic mean, standard deviation, and median value of observed BC concentration in 2009 and 2010. (b) The square and bar show the annual arithmetic mean and standard deviation of BC background concentrations with the method of REBS. (c) The square and bar show BC background concentration and standard deviation with the method of FS. (d) The squares and lines denote the anthropogenic emissions of BC in the LAN and LFS grid cells from 0.1° × 0.1° HTAP emissions inventory for 2008 and 2010. Stack columns denote the relative contributions to total BC emission in two site grid cells from individual emission sectors.

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The total emissions sensitivity s_tot for different seasons represents the seasonal transport climatology at LAN station, shown in the first column of Fig. 5. There is a pronounced seasonal variation. In summer, the distribution of higher s_tot values (s_tot > 2) is like a “bird” from southeast to northwest, due to the influence of the summer monsoon ( Fig. 5a₂). Air masses transported to LAN station are frequently from the sea with less BC during the last 7 days. The distribution of core area of s_tot values (s_tot > 3) shows that the local BC source is primarily in Zhejiang Province. The transport climatology in winter ( Fig. 5a₄) is absolutely different from that in summer. The distribution of the higher s_tot values (s_tot > 2) is like an “arrow”, pointing to southeast. Air streams from the relatively colder land masses are most likely to reach LAN station on a 7-day timescale. Consequently, the BC concentration could be strongly affected by BC sources in the east of China. Unfortunately, a large proportion of BC emissions in China gather in this area. Meanwhile, the core area of s_tot (s_tot > 3) is larger in winter than in summer. In spring, although northwest cold airstreams still play the leading role of transport, the influence of air masses in southeast starts ( Fig. 5a₁). The higher s_tot values (s_tot > 2) are distributed in the coastal provinces of eastern China. Once the source emissions increase in these regions, BC concentration is likely to show peaks. In autumn ( Fig. 5a₃), the distribution of higher s_tot values (s_tot > 2) is similar to that in spring. The atmospheric circulation switching between seasons is consistent with the results obtained by trajectory analysis ( Lu et al., 2012).

To find the potential source region in different seasons, the fields of R₇₅ and R₂₅ are also calculated for BC at LAN by using the method mentioned in Section 2.3 (Figs. 5b₁–b₄, c₁–c₄). For the statistical significance, the threshold (s_T) is determined by the 0.002 times of maximum value of individually seasonal s_tot to eliminate spurious R_p values. The fields of R₇₅ and R₂₅ are combined together for the same station to analyze the source of BC concentration. In summer (Figs. 5b₂, c₂), the area of R₇₅ bigger than 0.25 corresponds to where R₂₅ is smaller than 0.25, and vice versa. Therefore, the potential source regions are distributed in northwest and south of LAN, even containing south of Taiwan and Shanxi provinces of China. It is clear that the “sink” regions are mainly dominated by a long range of transport from the sea in the southwest, southeast, and northeast of the LAN station. In addition to relatively clean air mass, warm moist airflows produce rainfalls as a result of summer monsoon, weeding out BC in the atmosphere. The area of “sink” region is bigger than that of source region. In winter (Figs. 5b₄, c₄), there is a clear source–sink boundary inferred from the matched fields of R₇₅ and R₂₅. The potential source region is concentrated in the west and south of LAN station, which is comparable with that in summer. The “sink” regions might be controlled by the northwest or north cold air mass. Even if the purification capacity of air is different between summer and winter, the Yangtze River delta is always the primarily potential source region. In spring (Figs. 5b₁, c₁), the potential source region covers most of the area limited by threshold s_T during the last 7 days. Actually, there are a lot of anthropogenic BC emissions in these regions. Then it is possible that BC concentration presents a peak in spring. The distribution of source and “sink” regions in autumn (Figs. 5b₃, c₃) is similar to the one in winter. But the source area is smaller, compared with the area of “sink” region. In this transition season, we should especially pay attention to the reduction of BC emissions in the northwest and south of LAN station when we hope that BC concentrations decrease in the atmosphere.

Figure 5 (a1–a4) The total emissions sensitivity stot for different seasons and the corresponding fields of (b1–b4) R75 and (c1–c4) R25 for measurements of BC at LAN station from March 2009 to February 2010 for (a1–c1) spring, (a2–c2) summer, (a3–c3) autumn, and (a4–c4) winter. The location of LAN is marked with a black dot.

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The total emissions sensitivity s_tot and fields of R_p are shown in Fig. 6 for different seasons at LFS station. The distributions are very different in different seasons, which can represent the seasonal variation of transport climatology and potential sources. The post-processing method of R_p is also used as before for statistical significance. In summer (Fig. 6a₂), the area of relatively high s_tot values (s_tot > 2) is similar to the distribution at LAN station, but the former is smaller. Thus, the BC concentration at LFS is sensitive to the surface emissions in three provinces of Northeast China and the Sea of Japan. Combining the fields of R₇₅ and R₂₅ (Figs. 6b₂, c₂), we could infer that the potential source region of BC is distributed in the southwest of LFS station in summer, which is different from the pattern of source region at LAN. The BC source is associated with land masses of higher emissions. Lower BC concentrations in summer are mainly caused by relatively clean air mass from the sea and less anthropogenic BC emissions. In winter (Fig. 6a₄), the higher s_tot values (s_tot > 2) are in the northwest of LFS station. It is very different from the transport pattern in summer, but similar to the distribution at LAN station in winter. The colder land air streams are most likely to reach LFS station during the last 7 days, affecting BC concentrations. To find the source and “sink” areas, we also plot the fields of R₇₅ and R₂₅ (Figs. 6b₄, c₄). R₇₅ is bigger than 0.25 and R₂₅ is smaller than 0.25 in the northeast of the threshold area of s_tot. However, both of R₇₅ and R₂₅ are bigger than 0.25 in the southwest. An explanation could be that heating at night in winter results in anomalously high BC concentrations at LFS, disturbing the source region identification of BC (Li K. et al., 2016). So the threshold area of s_tot in the northeast is the source region in winter, which is opposite to the distribution in summer at LFS and different from the pattern in winter at LAN. The cold air mass in the northwest plays an important role in the purification of atmospheric BC at LFS (Fig. 6c₄). In spring (Fig. 6a₁), the air flow is clearly in the state of changing from winter to summer. According to the fields of R₇₅ and R₂₅ (Figs. 6b₁, c₁), the potential source region covers an area of inverse triangle. There are two “sink” regions in the northwest and southeast of the LFS station separately, probably attributed to less anthropogenic BC emissions. In autumn (Fig. 6a₃), the transport climatology is close to that in winter from the point of view of higher s_tot values (s_tot > 2). Based on the fields of R₇₅ and R₂₅ (Figs. 6b₃, c₃), the source and “sink” regions are in the southwest and northeast of the threshold area of s_tot, respectively. The area of source region is bigger than “sink”, opposite to the relationship of source and “sink” at LAN. In a word, the high BC concentrations at LFS station are mainly influenced by emissions from southwest and regional heating.

Figure 6 As in Fig. 5, but for the LFS station.

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The total emissions sensitivity s_tot at LAN and LFS for a whole year shows the overall sensitivity to surface emissions during the last 7 days of transport (Figs. 7a, d). High s_tot values at LAN are primarily limited to the Yangtze River delta, consisting of Anhui, Jiangsu, Zhejiang, Shanghai, the northeast of Jiangxi, the north of Fujian, and the adjacent sea (Fig. 7a; s_tot > 3). The area of s_tot > 2 in Fig. 7a is in a wide and long belt from northwest to southeast, consistent with general transport climatology (northwest airstream in winter and southeast summer monsoon) (Zhang et al., 2010). Air mass transport at LFS station is very different (Fig. 7d). The core area of s_tot (>3) is mostly limited to the northwest of LFS station and the distribution of highers_tot (> 2) is similar to a circular area, covering the three provinces in Northeast China (Fig. 7d). Emissions of the same strength outside these areas would have smaller influence to BC concentrations at LAN and LFS. In fact, the strength of BC sources is much stronger in the Yangtze River delta than in Northeast China (Li K. et al., 2016).

We calculate the field of R_p for both the lowest and the highest 25% of BC data for a whole year at LAN and LFS with the statistical method in Section 2.3 (Figs. 7b, c, e, f). The 0.002 times of s_tot maximum value are taken as the threshold (s_T) to eliminate spurious R_p values. When analyzing the source region of BC concentration at the same site, we take the fields of R₇₅ and R₂₅ into consideration for statistical significance. On yearly scale at LAN, the potential source regions are distributed in Zhejiang, southeastern Fujian, mid-western Anhui, Hubei, and mid-southern Henan in China where R₇₅ exceeds 0.25 and R₂₅ is under 0.25 (Figs. 7b, c). In contrast, the low R₇₅ and high R₂₅ values, corresponding to “sink” regions, are mainly dominated by long range transport from southern of Jiangxi, central Guangdong, northwestern Inner Mongolia, and the waters in the northeast of LAN. Moreover, the R_p field for LFS differs from that of LAN station completely (Figs. 7e, f). There is a clear boundary (about 45° of line) above/below 0.25 whether it is for R₇₅ or for R₂₅. The potential source regions on yearly scale are distributed to the west of the boundary, mainly containing Northeast China and east of Mongolia. The “sink” regions are to the east of the boundary, probably attributed to less source emissions in these areas. The differences of potential source region and emissions inventory of BC for the two stations lead to different BC concentrations in Figs. 4a–c. These results are consistent with source analysis of BC at nearby stations by trajectories (Cheng et al., 2006; Zhuang et al., 2014).

Figure 7 (a, d) The total emission sensitivity stot (lg s), fields of (b, e) R75 and (c, f) R25 for measurements of BC at (a, b, c) LAN and (d, e, f) LFS stations from March 2009 to February 2010. The locations of LAN and LFS are marked with black dot.

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Atmospheric BC observation data at LAN and LFS, the two background stations of CMA Atmosphere Watch Network, were employed in this paper. The characteristics of BC concentrations were analyzed on diurnal, monthly, and yearly timescales. The Lagrangian transport and dispersion model FLEXPART was used to calculate the transport climatology, that is, emissions sensitivity. The BC observation data at the two stations were combined with FLEXPART simulations and the BC sources were analyzed statistically. The study results are summarized as follows:

The mean diurnal variation of BC presents two peaks at LAN and LFS from 2009 to 2010. The evening peak is higher than the morning peak. This diurnal distribution at LAN is probably related to traffic activities and boundary layer. However, the reason is not clear for the weak peaks at LFS. The mean BC concentration is always bigger than the median values, changing in the diurnal range of 3.53–5.19 μg m^–3 at LAN and 2.64–3.65 μg m^–3 at LFS. Difference between the mean and median concentrations of BC is bigger at night for LFS station. According to the weekday/weekend effect, the BC concentration and peak might be correlated to different daily activities. Although there are still two peaks in the BC diurnal cycle for every month at LAN, the evening peak changes monthly during 1800–2000 BT. However, the morning and evening peaks at LFS are unapparent or almost absent from March to September. There is a shift about 2 h in the morning peak and pronounced evening peak for any other months at LFS.

Based on BC monthly median concentrations and mean values, we found that the seasonal variations of BC are obvious at LAN and LFS. The range of seasonal variation is close to each other at the two stations. There are double peaks at LAN, with the highest and lowest monthly median concentrations being 7.1 and 2.2 μg m^–3 in April and July. However, the seasonal variation of monthly median concentration has a single-peak distribution at LFS, with the maximum of 5.0 μg m^–3 in January and the minimum of 0.6 μg m^–3 in July. The monthly positive differences, between the average and median BC concentrations, and standard deviations imply that high emissions events often appear, especially during the heating months at LFS. The monthly anthropogenic emissions of BC are lower in summer than in winter, and nearly 8 times stronger at LAN than at LFS. The main sectors, such as residential emissions for LFS and industry for LAN, play dominant roles in the seasonal variation of BC concentration.

The annual arithmetic mean concentrations of BC at LAN and LFS stations are 3.47 ± 2.28 and 2.94 ± 4.25 μg m^–3 in 2010, decreasing by 1.63 and 0.26 μg m^–3 from 2009, respectively. Median concentrations of BC are always smaller than the annual mean due to high concentration events. By the screening methods of REBS and FS, the annual BC background concentration at LAN is twice higher than that at LFS, which is probably attributed to more anthropogenic emissions in the Yangtze River delta than in Northeast China. According to the HTAP emissions inventory, the emissions strength decreases from 2008 to 2010, consistent with the change of BC concentration. The major sources at LAN and LFS are industrial and residential emissions. The limitation of this paper is that we did not consider the contribution of biomass burning.

Through the studies of major source–sink regions in different seasons, we found that potential source region varies with seasons. Affected by summer monsoon, the sensitive emissions region of LAN station is like a “bird” from southeast to northwest. The potential source regions of LAN are distributed in the northwest and south, and the “sink” regions are mainly dominated by air mass through long-distance transport from the sea in the southwest, southeast, and northeast. With the similar distribution to LAN, the sensitive emissions region of LFS station in summer is in the three provinces of Northeast China and the Sea of Japan. But the potential source regions of LFS are mainly distributed in the southwest. In winter, LAN could be strongly influenced by emissions in eastern China. The source regions of BC at LAN are concentrated in the west and south. The source regions of BC at LFS are in the northeast of the threshold area of s_tot. The cold air mass in the northwest plays an important role in the purification of atmospheric BC in winter at LFS. In spring and autumn, the atmospheric circulation switches between summer and winter. The potential source region of BC at LAN covers most of the area limited by threshold s_T in spring. In autumn, the source region in the northwest and south of LAN is smaller than “sink” region. With two “sink” regions in the northwest and southeast of LFS, the potential source region covers an area of inverse triangle in spring. In autumn, the source region in the southwest of the threshold area of s_tot at LFS is bigger than the “sink” region in the northeast.

Based on the total emissions sensitivity s_tot during the last 7 days of transport at LAN and LFS for a whole year, it is demonstrated that LAN and LFS stations are highly sensitive to surface emissions in a wide and long belt from northwest to southeast and a circular area, respectively. The corresponding core areas for the two stations are located in the Yangtze River delta and in the northwest of LFS. The fields of R_p on yearly scale at LAN show that the source region is distributed in about five provinces in the northwest/southeast of LAN. There is a clear boundary between source and “sink” regions at LFS, which are separately distributed to the west and east of the boundary. These source regions are key areas when we hope to reduce atmospheric BC concentration or control air pollution.

Acknowledgments. We are grateful to the staff at LAN and LFS for BC observations and the efforts of the Emissions Database for Global Atmospheric Research team for providing the HTAP emissions. We are thankful to Norwegian Institute for Air Research for providing FLEXPART model.