Nitrate (NO3−) is a major contributing species to haze formation in Northern China. So far, formation processes and source apportionments of nitrate aerosols during haze pollution have not yet been well understood. In this study, the PM2.5 samples were collected in Beijing from 13 November to 24 December 2018. In addition to water‐soluble ions, oxygen (δ18O‐NO3−) and nitrogen (δ15N‐NO3−) isotopes in particulate NO3− were also determined, in order to investigate the formation pathways and potential sources of NO3− aerosols. The results showed that NO3− was a dominant species (43%) of secondary inorganic aerosols during the sampling period. The δ18O‐NO3− and δ15N‐NO3− values averaged at 83.8 ± 13.4 and 11.5 ± 5.0‰, respectively. Combining isotope compositions and Bayesian isotope mixing model, we found that heterogeneous reaction and gas phase oxidation contributed equally to nitrate formation during the sampling period. However, the contribution of heterogeneous processes to nitrate increased from 39% during the clean period to 64% during the haze period. On average, coal combustion, biomass burning, vehicle emissions, and soil emission contributed 50%, 26%, 20%, and 4%, respectively, to nitrate aerosols during the sampling period. Compared to the result in 2013, the significant decrease (~21%) of relative contribution of coal combustion to nitrate was due to strict reduction of coal consumption in Beijing. Finally, the relative contribution of traffic emissions to nitrate increased from 18% during the clean period to 30% during the haze period, suggesting that control of traffic emissions would be an important way to decrease nitrate concentrations and improve the air quality in Beijing.

This study reports the size‐resolved characterization of the chromophores in atmospheric particulate matter in Linfen, a typical coal‐burning city in China. The optical properties of both the water‐soluble and water‐insoluble chromophores in atmospheric particulates are studied using excitation‐emission matrix spectroscopy and follow the parallel factor analysis of excitation‐emission matrix data. The mass absorption efficiency and normalized fluorescence volume by mass concentration of the organic carbon in methanol‐soluble matter in the particulate samples are stronger than that of the water‐soluble matter. We found that the total absorption (Abs), fluorescence volume (FV), mass absorption efficiency, and normalized fluorescence volume of particle extracts with sizes less than 10 μm increased with the decreasing particle size. The total concentration of the selected seven polycyclic aromatic hydrocarbons was positively correlated with the Abs365 and FV of both the water‐soluble matter and methanol‐soluble matter, but the average contribution of the selected polycyclic aromatic hydrocarbons to the total Abs and FV was very small (<3%). This study is the first to report a size‐resolved characterization of the chromophores in atmospheric particulate matter. Humic‐like substances tend to be present in small particles, and tryptophan‐like and tyrosine‐like components tend to increase with increasing particle size.

&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; Black carbon (BC) measured by a multi-wavelength Aethalometer can be apportioned to traffic and wood burning. The method is based on the differences in the dependence of aerosol absorption on the wavelength of light used to investigate the sample, parameterized by the source-specific &amp;#197;ngstr&amp;#246;m absorption exponent (&amp;#945;). While the spectral dependence (defined as &amp;#945; values) of the traffic-related BC light absorption is low, wood smoke particles feature enhanced light absorption in the blue and near ultraviolet. Source apportionment results using this methodology are hence strongly dependent on the &amp;#945; values assumed for both types of emissions: traffic &amp;#945;&lt;sub&gt;TR&lt;/sub&gt;, and wood burning &amp;#945;&lt;sub&gt;WB&lt;/sub&gt;. Most studies use a single &amp;#945;&lt;sub&gt;TR&lt;/sub&gt; and &amp;#945;WB pair in the Aethalometer model, derived from previous work. However, an accurate determination of the source specific &amp;#945; values is currently lacking and in some recent publications the applicability of the Aethalometer model was questioned. &lt;br&gt;&lt;br&gt; Here we present an indirect methodology for the determination of &lt;sub&gt;WB&lt;/sub&gt; and &amp;#945;&lt;sub&gt;TR&lt;/sub&gt; by comparing the source apportionment of BC using the Aethalometer model with &lt;sup&gt;14&lt;/sup&gt;C measurements of the EC fraction on 16 to 40&amp;#8201;h filter samples from several locations and campaigns across Switzerland during 2005&amp;#8211;2012, mainly in winter. The data obtained at eight stations with different source characteristics also enabled the evaluation of the performance and the uncertainties of the Aethalometer model in different environments. The best combination of &amp;#945;&lt;sub&gt;TR&lt;/sub&gt; and &amp;#945;&lt;sub&gt;WB&lt;/sub&gt; (0.9 and 1.68, respectively) was obtained by fitting the Aethalometer model outputs (calculated with the absorption coefficients at 470&amp;#8201;nm and 950&amp;#8201;nm) against the fossil fraction of EC (ECF/EC) derived from &lt;sup&gt;14&lt;/sup&gt;C measurements. Aethalometer and &lt;sup&gt;14&lt;/sup&gt;C source apportionment results are well correlated (&lt;i&gt;r&lt;/i&gt; = 0.81) and the fitting residuals exhibit only a minor positive bias of 1.6&amp;#8201;% and an average precision of 9.3&amp;#8201;%. This indicates that the Aethalometer model reproduces reasonably well the &lt;sup&gt;14&lt;/sup&gt;C results for all stations investigated in this study using our best estimate of a single &amp;#945;&lt;sub&gt;WB&lt;/sub&gt; and &amp;#945;&lt;sub&gt;TR&lt;/sub&gt; pair. Combining the EC, &lt;sup&gt;14&lt;/sup&gt;C and Aethalometer measurements further allowed assessing the dependence of the mass absorption cross section (MAC) of BC on its source. Results indicate no significant difference in MAC at 880&amp;#8201;nm between BC originating from traffic or wood burning emissions. Using ECF/EC as reference and constant a priori selected &amp;#945;&lt;sub&gt;TR&lt;/sub&gt; values, &amp;#945;&lt;sub&gt;WB&lt;/sub&gt; was also calculated for each individual data point. No clear station-to-station or season-to-season differences in &amp;#945;&lt;sub&gt;WB&lt;/sub&gt; were observed, but &amp;#945;&lt;sub&gt;TR&lt;/sub&gt; and &amp;#945;&lt;sub&gt;WB&lt;/sub&gt; values are interdependent. For example, an increase in &amp;#945;&lt;sub&gt;TR&lt;/sub&gt; by 0.1 results in a decrease in &amp;#945;&lt;sub&gt;WB&lt;/sub&gt; by 0.1. The fitting residuals of different &amp;#945;&lt;sub&gt;TR&lt;/sub&gt; and &amp;#945;&lt;sub&gt;WB&lt;/sub&gt; combinations depend on ECF/EC such that a good agreement cannot be obtained over the entire ECF/EC range using other &amp;#945; pairs. Additional combinations of &amp;#945;&lt;sub&gt;TR&lt;/sub&gt; = 0.8, and 1.0 and &amp;#945;&lt;sub&gt;WB&lt;/sub&gt; = 1.8 and 1.6, respectively, are possible but only for ECF/EC between ~&amp;#8201;40&amp;#8201;% and 85&amp;#8201;%. Applying &amp;#945; values previously used in literature such as &amp;#945;&lt;sub&gt;WB&lt;/sub&gt; of ~&amp;#8201;2 or any &amp;#945;&lt;sub&gt;WB&lt;/sub&gt; in combination with &amp;#945;&lt;sub&gt;TR&lt;/sub&gt; = 1.1 to our data set results in large residuals. Therefore we recommend to use the best &amp;#945; combination as obtained here (&amp;#945;&lt;sub&gt;TR&lt;/sub&gt; = 0.9 and &amp;#945;&lt;sub&gt;WB&lt;/sub&gt; = 1.68) in future studies when no or only limited additional information like &lt;sup&gt;14&lt;/sup&gt;C measurements are available. However, these results were obtained for locations impacted by BC mainly from traffic consisting of a modern car fleet and residential wood combustion with well-constrained combustion efficiencies. For regions of the world with different combustion conditions, additional BC sources or fuels used further investigations are needed.&lt;/p&gt;

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Sulfate (SO4 2–) is a major species in atmospheric fine particles (PM2.5), inducing haze formation and influencing Earth’s climate. In this study, the δ34S values in PM2.5 sulfate (δ34S-SO4 2–) were measured in Hangzhou, east China, from 2015 September to 2016 October. The result showed that the δ34S-SO4 2– values varied from 1.6 to 6.4‰ with the higher values in the winter. The estimated fractionation factor (α34Sg→p) from SO2 to SO4 2– averaged at 3.9 ± 1.6‰. The higher α34Sg→p values in the winter were mainly attributed to the decrease of ambient temperature. We further compared the quantified source apportionments of sulfate by isotope techniques with and without the consideration of fractionation factors. The result revealed that the partitioned emission sources to sulfate with the consideration of the fractionation effects were more logical, highlighting that fractionation effects should be considered in partitioning emission sources to sulfate using sulfur isotope techniques. With considering the fractionation effects, coal burning was the dominant source to sulfate (85.5%), followed by traffic emissions (12.8%) and oil combustion (1.7%). However, the coal combustion for residential heating contributed only 0.9% to sulfate on an annual basis in this megacity.