Polycyclic aromatic hydrocarbons (PAHs) associated with PM2.5 within boundary layer: Cloud/fog and regional transport

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

et al. 2018

Abstract. PM2.5 pollution is an environmental issue results from various natural and socioeconomic factors, frequently witnessed in the spring and winter across mainland China. However, the dominant influence of natural and socioeconomic factors within a city on PM2.5 is not extensively studied yet. In this study, the Random Forest Regression (RFR) is utilized to quantify the relationships between PM2.5 and potential factors within Wuhan city on a typical day turn from winter to spring. Technically, the 24-hour average PM2.5 concentration in downtown area on February 17th 2017 are collected at 9 sites. In the meantime, we retrieve simultaneous aerosol depth optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS). The ground measured PM2.5 and AOD are coupled for the retrieval of near-surface PM2.5 concentration by Spatial-temporal CoKriging (STCK) with Normalized Vegetation Index (NDVI), Modified Normalized Water Index (MNDWI), Normalized Building Index (NDBI) from Landsat-8 and DEM from Shuttle Radar Topography Mission (SRTM). As the geospatial big data booms, the Internet-collected volunteered geographic information (VGI), representing the urban form and function, are integrating for the regression to obtain the spatial variables importance measures (VIMs) by RFR both in centre and sub-urban region of Wuhan. The results reveal that terrain characteristics and the density of industrial enterprises have obvious relationships with the accumulation of PM2.5 while the density of roads also contributes to this.

Section: Introductionmentioning

confidence: 99%

Quantifying the Relationship Between Natural and Socioeconomic Factors and With Fine Particulate Matter (PM2.5) Pollution by Integrating Remote Sensing and Geospatial Big Data

Yang

Zhan

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

et al. 2018

“…In addition to changes in emission sources, the relatively strong photochemical degradation reactions in summer increase the degradation rate of PAHs and NPAHs, causing low concentrations in summer [25,26]. In winter, temperature inversion likely occurs in the boundary layer, which also increases the concentrations of PAHs and NPAHs [27].…”

Section: Concentrations and Composition Of Pahs And Npahsmentioning

confidence: 99%

Characteristics and Health Risks of Polycyclic Aromatic Hydrocarbons and Nitro-PAHs in Xinxiang, China in 2015 and 2017

Yang

et al. 2021

IJERPH

Self Cite

Fine particulate matter (PM2.5) samples were collected in the summer and winter of 2015 and 2017 in Xinxiang, China. Nine polycyclic aromatic hydrocarbons (PAHs) and three nitro-PAHs (NPAHs) in PM2.5 were detected via high-performance liquid chromatography (HPLC). The PAHs concentration in summer and winter decreased from 6.37 ± 1.30 ng/m3 and 96.9 ± 69.9 ng/m3 to 4.89 ± 2.67 ng/m3 and 49.8 ± 43.4 ng/m3 from 2015 to 2017. NPAHs decreased in winter (from 1707 ± 708 pg/m3 to 1192 ± 1113 pg/m3), but increased in summer from 2015 (336 ± 77.2 pg/m3) to 2017 (456 ± 312 pg/m3). Diagnostic ratios of PAHs indicated that petroleum combustion was the main emission source in summer, and pollutants originating from the combustion of petroleum, coal and biomass dominated in winter. The 2-nitrofluoranthene (2-NFR)/2-nitropyrene (2-NP) ratio in this study demonstrated that the OH radical pathway was the main pathway for the formation of 2-NP and 2-NFR. The mean total benzo[a]pyrene-equivalent concentrations (BaPeq) and incremental lifetime cancer risk (ILCR) values decreased from 2013 to 2017. The high value of total BaPeq in the winter of 2017 in Xinxiang revealed that a high-risk of cancer remained for residents. The results of this study demonstrate that the decreases in PAHs and NPAHS concentrations from 2015 to 2017. Combined with reducing gaseous pollutants concentration, the reduction in this study might be attributable to emissions reductions by implementing the air pollution control regulations in Xinxiang city in 2016.

Surface & Interface Analysis

“…12 This process may enhance the toxicity of some pollutants, and studies have shown that particulate matter with a diameter of 0.1 to 2.5 μm is the most harmful to human health. 9,[13][14][15][16] The most widely used analysis methods for fine particulate matter in the atmosphere are atomic absorption spectroscopy, X-ray fluorescence analysis, 17 electron microscopy, 18,19 gas chromatography, 20 and high-performance liquid chromatography, 21 etc. Time-offlight secondary ion mass spectrometry (ToF-SIMS) is a relatively new method in this area, but due to its high surface sensitivity and remarkable lateral/depth resolution, ToF-SIMS has become a useful tool for the analysis of chemical composition of PM and even single particles.…”

Section: Funding Informationmentioning

confidence: 99%

ToF‐SIMS analysis of chemical composition of atmospheric aerosols in Beijing

Jia

Che

et al. 2019

Atmospheric aerosols collected from each season in urban Beijing have been studied using time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS). The chemical composition of atmospheric aerosol particles during various atmospheric pollution levels was analyzed and distinguished by principal component analysis (PCA). The differences and sources of the components of the aerosol particles were explored. The results showed that the fine particulate matter from heavily polluted days mainly consists of inorganic salts and organic compounds, such as hydrocarbons, nitrogen‐ or sulfur‐containing hydrocarbons, and their oxides. Samples collected from clean days in the four seasons were also analyzed. Only the samples collected in spring showed a significant difference from the other three seasons. We concluded that the main source of pollution in the Beijing urban area was fossil fuel combustion from motor vehicles.