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Carbohydrates observations in suburb Nanjing, Yangtze River of Delta during 2017-2018: Concentration, seasonal variation, and source apportionment

机译:碳水化合物在南京郊区观测,2017 - 2018年长江长江:集中,季节性变化和来源分配

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摘要

The temporal characteristic and source apportionment analyses on carbohydrates in this study are useful for understanding PM2.5 sources in Yangtze River Delta (YRD) region. Carbohydrates are important consistent of primary organic aerosol (POA) and some of them are widely used as tracers for source apportionment of fine particle (PM2.5). In this study, ambient concentrations of 10 carbohydrates (levoglucosan, arabitol, mannitol, sucrose, fructose, glucose, inositol, threitol, 2-methyl-threitol, and trehalose) in PM2.5 at a suburb site of Nanjing during 2017-2018 were quantified by a high-performance liquid chromatography tandem mass spectrum/mass spectrum (HPLC-MS/MS). Among all measured carbohydrates, Levoglucosan, with the average concentration of 337.6 ng m(-3), was the dominant one, contributing 89% of the total 10 carbohydrates concentration. The concentration of levoglucosan in 2017 was 412.4 ng m(-3), higher than that of 2018 (232.5 ng m(-3)). Similarly, the average concentration for other 9 carbohydrates was 43.6 ng m(-3) in 2017, slightly higher than 2018 (38.32 ng m(-3)). Levoglucosan concentrations presented a similar seasonal variation in both 2017 and 2018, which values were high in winter and autumn, and went down in summer and spring. As for the other 9 carbohydrates, their overall concentrations presented different seasonal variation patterns between 2017 and 2018. During 2017, their concentrations were the highest in summer, followed by spring, autumn, and winter. However, the richest concentrations occurred in spring, followed by autumn, summer and winter during 2018. Positive matrix factorization (PMF) model was then applied for sources apportionment of carbohydrates. Seven sources were identified, including airborne pollen, fungal spores and soil dust, plants debris, biomass burning, biogenic secondary organic aerosol (SOA), threitol-rich source, and inositol-rich source. Biomass burning contributed the most to the measured concentrations of 10 carbohydrates, with relative contribution of 57.9%, followed by airborne pollen (12.9%), 2-methyl-threitol rich source (10.0%), fungal spores and soil dust (9.4%), plant debris (6.3%), threitol-rich source (2.4%), and inositol-rich source (1.1%). Relative contributions of biomass burning showed a significant decrease from 68.8% in 2017 to 50% in 2018, suggesting that biomass burning in YRD region was well controlled in 2018 compared to 2017.
机译:本研究中碳水化合物的时间特征和源分配分析可用于了解长江三角洲(YRD)地区的PM2.5来源。碳水化合物是主要有机气溶胶(POA)的重要一致,其中一些是广泛用作细颗粒源分配的示踪剂(PM2.5)。在本研究中,2017-2018期间南京郊区现场的PM2.5在PM2.5中,在PM2.5中,10个碳水化合物(Levoglucosan,阿拉伯醇,甘露醇,蔗糖,果糖,葡萄糖,血糖,糖酚,2-甲基 - 血糖和海藻糖)是通过高效液相色谱串联质谱/质谱(HPLC-MS / MS)量化。在所有测量的碳水化合物中,左旋葡聚糖,平均浓度为337.6 ng m(-3),是主要的含量,有助于总10碳水化合物浓度的89%。 2017年左葡葡萄酒的浓度为412.4ng m(-3),高于2018(232.5 ng m(-3))。类似地,2017年其他9个碳水化合物的平均浓度为43.6ng m(-3),略高于2018(38.32ng m(-3))。 Levoglucosan浓度在2017年和2018年呈现出类似的季节性变化,冬季和秋季的价值高,夏季和春季下降。至于其他9个碳水化合物,它们的整体浓度在2017年和2018年之间呈现了不同的季节变异模式。2017年期间,它们的浓度在夏天最高,其次是春季,秋季和冬季。然而,最富有的浓度发生在春天,随后是2018年秋季,夏季和冬季。然后施用正基质分子(PMF)模型以供碳水化合物分配的来源。鉴定了七种来源,包括空中花粉,真菌孢子和土壤粉尘,植物碎片,生物量燃烧,生物学二次有机气溶胶(SOA),富含血清源和肌醇丰富的源泉。生物质燃烧最多的10个碳水化合物的浓度最大,相对贡献为57.9%,其次是空气载花粉(12.9%),2-甲基 - 血液富源(10.0%),真菌孢子和土壤粉尘(9.4%) ,植物碎片(6.3%),富含血糖源(2.4%)和富含肌醇的源(1.1%)。生物质燃烧的相对贡献显示2017年的68.8%至2018年的50%显着下降,这表明与2017年,yrd地区的生物量燃烧在2017年。

著录项

  • 来源
    《Atmospheric environment》 |2020年第12期|117843.1-117843.12|共12页
  • 作者单位

    Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Atmospher Environm & Equip Sch Environm Sci & Engn Jiangsu Key Lab Atmospher Environm Monitoring & P Nanjing 210044 Peoples R China;

    Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Atmospher Environm & Equip Sch Environm Sci & Engn Jiangsu Key Lab Atmospher Environm Monitoring & P Nanjing 210044 Peoples R China;

    Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Atmospher Environm & Equip Sch Environm Sci & Engn Jiangsu Key Lab Atmospher Environm Monitoring & P Nanjing 210044 Peoples R China;

    Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Atmospher Environm & Equip Sch Environm Sci & Engn Jiangsu Key Lab Atmospher Environm Monitoring & P Nanjing 210044 Peoples R China;

    Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Atmospher Environm & Equip Sch Environm Sci & Engn Jiangsu Key Lab Atmospher Environm Monitoring & P Nanjing 210044 Peoples R China;

    Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Atmospher Environm & Equip Sch Environm Sci & Engn Jiangsu Key Lab Atmospher Environm Monitoring & P Nanjing 210044 Peoples R China;

    Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Atmospher Environm & Equip Sch Environm Sci & Engn Jiangsu Key Lab Atmospher Environm Monitoring & P Nanjing 210044 Peoples R China;

    Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Atmospher Environm & Equip Sch Environm Sci & Engn Jiangsu Key Lab Atmospher Environm Monitoring & P Nanjing 210044 Peoples R China;

    Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Atmospher Environm & Equip Sch Environm Sci & Engn Jiangsu Key Lab Atmospher Environm Monitoring & P Nanjing 210044 Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Carbohydrates; HPLC-MS/MS; Aerosol; PMF;

    机译:碳水化合物;HPLC-MS / MS;气溶胶;PMF;

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