Abstract. The characteristics of n-alkanes and the contributions of various sources of fine particulate matter (PM2.5) in the atmosphere in Beijing were investigated. PM2.5 samples were collected at Minzu University of China between November 2020 and October 2021, and n-alkanes in the samples were analyzed by gas chromatography mass spectrometry. A positive matrix factorization analysis model and source indices (the main carbon peaks, carbon preference indices, and plant wax contribution ratios) were used to identify the sources of n-alkanes, to determine the contributions of different sources, and to explain the differences. The n-alkane concentrations were 4.51–153 ng m−3 (mean 32.7 ng m−3), and the particulate-bound n-alkane and PM2.5 concentrations varied in parallel. There were marked seasonal and diurnal differences in the n-alkane concentrations (p<0.01). The n-alkane concentrations in the different seasons decreased in the order of winter > spring > summer > fall. The mean concentration of each homolog was higher at night than in the day in all seasons. Particulate-bound n-alkanes were supplied by common anthropogenic and biogenic sources, and fossil fuel combustion was the dominant contributor. The positive matrix factorization model results indicated five sources of n-alkanes in PM2.5, which were coal combustion, diesel vehicle emissions, gasoline vehicle emissions, terrestrial plant release, and mixed sources. Vehicle emissions were the main sources of n-alkanes, contributing 57.6 %. The sources of PM2.5 can be indicated by n-alkanes (i.e., using n-alkanes as organic tracers). Vehicle exhausts strongly affect PM2.5 pollution. Controlling vehicle exhaust emissions is key to controlling n-alkanes and PM2.5 pollution in Beijing.

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Abstract. The characteristics of n-alkanes and the contributions of various sources of fine particulate matter (PM2.5) in the atmosphere in Beijing were investigated. PM2.5 samples were collected at Minzu University of China between November 2020 and October 2021, and n-alkanes in the samples were analyzed by gas chromatography mass spectrometry. A positive matrix factorization analysis model and source indices (the main carbon peaks, carbon preference indices, and plant wax contribution ratios) were used to identify the sources of n-alkanes, determine the contributions of different sources, and explain the differences. The n-alkane concentrations were 4.51–153 ng/m, (mean 32.7 ng/m3), and the particulate-bound n-alkane and PM2.5 concentrations varied in parallel. There were marked seasonal and diurnal differences in the n-alkane concentrations (p<0.01). The n-alkane concentrations in the different seasons decreased in the order winter>spring>summer>fall. The mean concentration of each homolog was higher at night than in the day in all seasons. Particulate-bound n-alkanes were supplied by common anthropogenic and biogenic sources, and fossil fuel combustion was the dominant contributor. The positive matrix factorization model results indicated five sources of n-alkanes in PM2.5, which were coal combustion, diesel vehicle emissions, gasoline vehicle emissions, higher plants, and dust. Vehicle emissions were the main sources of n-alkanes, contributing 57.6 %. The sources of PM2.5 can be indicated by n-alkanes (i.e., using n-alkanes as organic tracers). Air quality in Beijing needs to be improved. Vehicle exhausts strongly affect PM2.5 pollution. Controlling vehicle exhaust emissions is key to controlling n-alkane and PM2.5 pollution in Beijing.

Abstract. Fine particulate matter (PM2.5) samples were collected between November 2020 and October 2021 at the Minzu University of China in Beijing and the n-alkyl nitrate concentrations in the PM2.5 samples were determined to investigate n-alkyl nitrate pollution and formation mechanisms. C9–C16 n-alkyl nitrate standards were synthesized and the n-alkyl nitrate concentrations in PM2.5 were determined by gas chromatography triple quadrupole mass spectrometry. Temporal trends in and correlations between particulate-bound n-alkyl nitrate, ozone, PM2.5, and nitrogen dioxide concentrations were investigated to assess the relationships between particulate-bound n-alkyl nitrate concentrations and photochemical reactions and identify the n-alkyl nitrate formation mechanisms. The n-alkyl nitrate concentrations in the PM2.5 samples were 9.67–2730 pg/m3, and the mean was 578 pg/m3. The n-alkyl nitrate homologue group concentrations increased as the carbon chain length increased, i.e, long-chain n-alkyl nitrates contributed more than short-chain n-alkyl nitrates to the total n-alkyl nitrate concentrations in PM2.5. The n-alkyl nitrate concentrations clearly varied seasonally and diurnally, the concentrations decreasing in the order winter > spring > autumn > summer and the mean concentrations being higher at night than in the day. The particulate-bound n-alkyl nitrate and ozone concentrations significantly negatively correlated despite gas-phase alkyl nitrate and ozone concentrations previously being found to positively correlate. This indicated that long-chain alkyl nitrates may not be produced during photochemical reactions. The particulate-bound n-alkyl nitrate concentrations followed the same trends as and significantly positively correlated with the PM2.5 and nitrogen dioxide concentrations. Nitrogen dioxide is an important contributor of nitrates in particulate matter. This indicated that particulate-bound n-alkyl nitrates may form through reactions between alkanes and nitrates on particulate matter surfaces. Particulate-bound n-alkyl nitrates are important components of PM2.5 during haze events and strongly affect atmospheric visibility. Particulate-bound n-alkyl nitrates are secondary pollutants that strongly influence haze pollution.