Source signatures from combined isotopic analyses of PM2.5 carbonaceous and nitrogen aerosols at the peri-urban Taehwa Research Forest, South Korea in summer and fall

Fossil and non-fossil sources of the carbonaceous component of PM2.5 in forest and urban areas

Atmospheric particulate matter (PM_2.5) can damage human health. Biogenic organic compounds emitted from trees may increase the concentration of PM_2.5 via formation of secondary aerosols. Therefore, the role of biogenic emissions in PM_2.5 formation and the sources of PM_2.5 need to be investigated. Dual carbon isotope and levoglucosan analyses are powerful tools to track the sources of total carbon (TC) in PM_2.5. We collected a total of 47 PM_2.5 samples from 2019 to 2020 inside a pine forest and in urban areas in South Korea. The average δ¹³C and Δ¹⁴C of TC in PM_2.5 at the Taehwa Research Forest (TRF) were - 25.7 and - 380.7‰, respectively, which were not significantly different from those collected at Seoul National University (SNU) in urban areas. Contribution of fossil fuel, C₃-, and C₄- plants to carbonaceous component of PM_2.5 were 52, 27, and 21% at SNU, whereas those were 46, 35, and 19% at TRF, respectively. The biomass burning tracer, levoglucosan, was most abundant in winter and correlated with the contribution of C₄ plants derived carbon. Results indicate that biogenic aerosols emitted from trees is less likely to be an important source of PM_2.5 and that trees can act as a bio-filter to reduce PM_2.5.

Stable C and N isotopes of PM2.5 and size-segregated particles emitted from incense stick and cigarette burning

This work measured the δ¹³C and δ¹⁵N signatures in PM_2.5 and size-segregated particles emitted from incense stick and cigarette burning in different brands or nicotine contents for pollution source identification indoors. Three popular brands of incense stick and cigarette were selected for experiments. A personal environmental monitoring sampler and a Sioutas cascade impactor were used to collect PM_2.5 and size-segregated particles, respectively, for isotopic signatures analyses. Our data showed that both δ¹³C and δ¹⁵N values were heavier from incense stick burning (δ¹³C: 27.3 ± 0.5; δ¹⁵N: 8.63 ± 1.35) than cigarette (δ¹³C: 28.5 ± 0.2; δ¹⁵N: 4.15 ± 0.69). The scatter plots of δ¹³C and TC/PM_2.5 and of δ¹⁵N and TN/PM_2.5 can be applied to distinguish particle pollution sources and assess the influence of cigarette burning to PM_2.5 according to different nicotine contents. The δ¹³C values in size-segregated particles were similar to incense stick or cigarette burning; the δ¹³C values in PM_2.5 were significantly higher than those in size-segregated particles. However, the nitrogen amount was too low in most of the size-segregated particles to analyze δ¹⁵N from incense stick and cigarette burning. These results suggest that the δ¹³C signatures on PM_2.5 cannot represent the isotopic characteristics of size-segregated particles and δ¹⁵N has limitation for pollution source identification of different particle sizes.

Robust Evidence of 14C, 13C, and 15N Analyses Indicating Fossil Fuel Sources for Total Carbon and Ammonium in Fine Aerosols in Seoul Megacity

Carbon- and nitrogen-containing aerosols are ubiquitous in urban atmospheres and play important roles in air quality and climate change. We determined the ¹⁴C fraction modern (f_M) and δ¹³C of total carbon (TC) and δ¹⁵N of NH₄⁺ in the PM_2.5 collected in Seoul megacity during April 2018 to December 2019. The seasonal mean δ¹³C values were similar to -25.1‰ ± 2.0‰ in warm and -24.2‰ ± 0.82‰ in cold seasons. Mean δ¹⁵N values were higher in warm (16.4‰ ± 2.8‰) than in cold seasons (4.0‰ ± 6.1‰), highlighting the temperature effects on atmospheric NH₃ levels and phase-equilibrium isotopic exchange during the conversion of NH₃ to NH₄⁺. While 37% ± 10% of TC was apportioned to fossil-fuel sources on the basis of f_M values, δ¹⁵N indicated a higher contribution of emissions from vehicle exhausts and electricity generating units (power-plant NH₃ slip) to NH₃: 60% ± 26% in warm season and 66% ± 22% in cold season, based on a Bayesian isotope-mixing model. The collective evidence of multiple isotope analysis reasonably supports the major contribution of fossil-fuel-combustion sources to NH₄⁺, in conjunction with TC, and an increased contribution from vehicle emissions during the severe PM_2.5 pollution episodes. These findings demonstrate the efficacy of a multiple-isotope approach in providing better insight into the major sources of PM_2.5 in the urban atmosphere.

Source apportionment of carbonaceous aerosols in diverse atmospheric environments of China by dual-carbon isotope method

Carbonaceous aerosols are major components in PM_2.5 of both polluted and clean atmosphere. Accurate source apportionment of carbonaceous aerosols may support effective PM_2.5 control. Dual-carbon isotope method (¹⁴C and ¹³C) was adopted to identify the contribution of three main air pollution sources biogenic and biomass (f_bb), liquid fossil (f_liq.fossil) and coal (f_coal). The aerosol samples were collected at three types of sites with distinctly different degree of air pollution: urban, rural and regional background. The seasonal variation of source apportionment of the carbonaceous aerosols in urban Beijing was discussed. Modern biogenic and biomass made an absolute dominance of 92.9 ± 0.5% contribution to the carbonaceous aerosols at the background site Mt. Yulong due to long-range transport from Southeast Asia. The three main sources contributed jointly to the atmospheric carbonaceous aerosols at the rural site Wangdu and the urban site Beijing. The biogenic and biomass source was the major contribution in summer (47.0 ± 0.3%) and autumn (49.3 ± 0.3%) of Beijing, while coal source increased from summer (26.8 ± 13.8%) to autumn (34.7 ± 11.5%). Heating significantly increased the coal source to the dominant contribution (47.0 ± 16.9%) in winter of Beijing. Separate day and night time coal contributions were used to evaluate the two origins of coal combustion: industrial use vs. residential use. The results of source apportionment for carbonaceous aerosols provide scientific support for the prevention and control of air pollution.

Radiocarbon in the atmospheric gases and PM10 aerosol around the Paks Nuclear Power Plant, Hungary

Our study shows a one-year-long, monthly integrated continuous monitoring campaign of gaseous radiocarbon emission and ambient air compared with 4 event-like, weekly (168 h) atmospheric aerosol radiocarbon data in every season of 2019, at 4 locations (n = 16 aerosol sample) around the Paks Nuclear Power Plant, Hungary. The study shows the first aerosol radiocarbon results around a nuclear power plant measured by accelerator mass spectrometry in Hungary. There was no dominant contribution detected in the atmospheric CO₂ gas fraction, but we could detect excess radiocarbon in the total gaseous carbon fraction at almost every sampling point around the Paks Nuclear Power Plant. The highest Δ¹⁴C value in the total gaseous carbon form was 157.9 ± 4.6‰ in November and the highest Δ ¹⁴C value in the CO₂ fraction was 86.1 ± 4.0‰ in December during 2019. Observed ¹⁴C activity excess is not higher than previously published values around the Paks Nuclear Power plant at the same sampling points (Molnár et al., 2007; Varga et al., 2020). Our aerosol radiocarbon measurements show that there is no significant contribution from the nuclear power plant to the atmospheric PM₁₀ fraction. We could not detect a Δ ¹⁴C value higher than 0‰ in any season. The results show that the simple aerosol sampling, without pre-treatment of the filters, is appropriate for the measurement of excess radiocarbon at the vicinity of nuclear power plants. The applied preparation and measurement method can be applicable for detection of hot (¹⁴C) particles and early identification of radiocarbon emission from nuclear power plants in the PM₁₀ fraction.

Fossil-driven secondary inorganic PM2.5 enhancement in the North China Plain: Evidence from carbon and nitrogen isotopes

Measuring isotopic ratios in aerosol particles is a powerful tool for identifying major sources, particularly in separating fossil from non-fossil sources and investigating aerosol formation processes. We measured the radiocarbon, stable carbon, and stable nitrogen isotopic composition of PM_2.5 in Beijing (BJ) and Changdao (CD) in the North China Plain (NCP) from May to mid-June 2016. The mean PM_2.5 concentrations were 48.6 ± 28.2 μg m^-3 and 71.2 ± 29.0 μg m^-3 in BJ and CD, respectively, with a high contribution (∼66%) from secondary inorganic aerosol (SIA; NO₃^-, NH₄⁺, and SO₄^2-). The mean δ¹³C of total carbon (TC) and δ¹⁵N of total nitrogen (TN) values differed significantly between the two sites (p-value of <0.001): -25.1 ± 0.3‰ in BJ and -24.5 ± 0.4‰ in CD and 10.6 ± 1.8‰ in BJ and 5.0 ± 3.1‰ in CD, respectively. In BJ, the average δ¹⁵N (NH₄⁺) and δ¹⁵N (NO₃^-) values were 12.9 ± 2.3‰ and 5.2 ± 3.5‰, respectively. The ionic molar ratios and isotopic ratios suggest that NO₃^- in BJ was formed through the phase-equilibrium reaction of NH₄NO₃ under sufficient NH_{3 (g)} conditions, promoted by fossil-derived NH_{3 (g)} transported with southerly winds. In BJ, fossil fuel sources comprised 52 ± 7% of TC and 45 ± 28% of NH₄⁺ on average, estimated from radiocarbon (¹⁴C) analysis and the δ¹⁵N and isotope mixing model, respectively. These multiple-isotopic composition results emphasize that PM_2.5 enhancement is derived from fossil sources, in which vehicle emissions are a key contributor. The impact of the coal source was sporadically noticeable. Under regional influences, the fossil fuel-driven SIA led to the PM_2.5 enhancements. Our findings demonstrate that the multiple-isotope approach is highly advantageous to elucidate the key sources and limiting factors of secondary inorganic PM_2.5 aerosols.

Spatiotemporal Big Data for PM2.5 Exposure and Health Risk Assessment during COVID-19

The coronavirus disease 2019 (COVID-19) first identified at the end of 2019, significantly impacts the regional environment and human health. This study assesses PM_2.5 exposure and health risk during COVID-19, and its driving factors have been analyzed using spatiotemporal big data, including Tencent location-based services (LBS) data, place of interest (POI), and PM_2.5 site monitoring data. Specifically, the empirical orthogonal function (EOF) is utilized to analyze the spatiotemporal variation of PM_2.5 concentration firstly. Then, population exposure and health risks of PM_2.5 during the COVID-19 epidemic have been assessed based on LBS data. To further understand the driving factors of PM_2.5 pollution, the relationship between PM_2.5 concentration and POI data has been quantitatively analyzed using geographically weighted regression (GWR). The results show the time series coefficients of monthly PM_2.5 concentrations distributed with a U-shape, i.e., with a decrease followed by an increase from January to December. In terms of spatial distribution, the PM_2.5 concentration shows a noteworthy decline over the Central and North China. The LBS-based population density distribution indicates that the health risk of PM_2.5 in the west is significantly lower than that in the Middle East. Urban gross domestic product (GDP) and urban green area are negatively correlated with PM_2.5; while, road area, urban taxis, urban buses, and urban factories are positive. Among them, the number of urban factories contributes the most to PM_2.5 pollution. In terms of reducing the health risks and PM_2.5 pollution, several pointed suggestions to improve the status has been proposed.