Department of Civil Engineering and Centre for Environmental Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, 208016, India.
Department of Civil Engineering and Centre for Environmental Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, 208016, India.
Chemosphere. 2023 Sep;336:139195. doi: 10.1016/j.chemosphere.2023.139195. Epub 2023 Jun 16.
This study estimates global PM and anthropogenic and biogenic Secondary Organic Aerosols (a-SOA and b-SOA) and sources contributing to their formation. The global landscape was divided into eleven domains (North America (NAM); South America (SAM); Europe (EUR); North Africa and Middle East (NAF); Equatorial Africa (EAF); South of Africa (SAF); Russia and Central Asia (RUS); Eastern Asia (EAS); South Asia (SAS); Southeast Asia (SEA) and Australia (AUS)) and 46 cities based on varying populations. Three inventories for global emissions were considered: Community Emissions Data System, Model of Emission of Gases and Aerosol, and Global Fire Emissions Database. WRF-Chem model coupled with atmospheric reactions and the secondary organic aerosol model was employed for estimating PM, a-SOA, and b-SOA for 2018. No city attained WHO's annual PM guideline of 5 μg/m. Delhi, Dhaka, and Kolkata (63-92 μg/m) in south Asia were the most polluted, and seven cities (mostly in EUR and NAM) met the WHO target IV (10 μg/m). The highest SOA levels (2-9 μg/m) were in the cities of SAS and Africa, but with a low SOA contribution to PM (3-22%). However, the low levels of SOA (1-3 μg/m) in EUR and NAM had a higher contribution of SOA to PM (20-33%). b-SOA were consistent with the region's vegetation and forest cover. The SOA contribution was dominated by residential emissions in all domains (except in the NAF and AUS) (maximum in SAS). The non-coal industry was the second highest contributor (except in EAF, NAF, and AUS) and EUR had the maximum contribution from agriculture and transport. Globally, residential and industry (non-coal and coal) sectors showed the maximum contribution to SOA, with a-SOA and b-SOA being nearly equal. Ridding of biomass and residential burning of solid fuel is the single most action benefiting the PM and SOA concerns.
本研究估算了全球 PM 和人为源及生物源二次有机气溶胶（a-SOA 和 b-SOA）的浓度，并分析了其形成的原因。全球景观根据不同的人口分布，划分为 11 个区域（北美（NAM）；南美（SAM）；欧洲（EUR）；北非和中东（NAF）；热带非洲（EAF）；南非（SAF）；俄罗斯和中亚（RUS）；东亚（EAS）；南亚（SAS）；东南亚（SEA）和澳大利亚（AUS））和 46 个城市。我们考虑了三种全球排放清单：社区排放数据系统、气体和气溶胶排放模型以及全球火灾排放数据库。WRF-Chem 模型与大气反应和二次有机气溶胶模型耦合，用于估算 2018 年的 PM、a-SOA 和 b-SOA。没有一个城市达到世界卫生组织的年 PM 指导值 5μg/m。南亚的德里、达卡和加尔各答（63-92μg/m）污染最为严重，七个城市（主要在 EUR 和 NAM）达到世界卫生组织目标四（10μg/m）。SOA 浓度最高（2-9μg/m）的是 SAS 和非洲的城市，但 SOA 对 PM 的贡献较低（3-22%）。然而，EUR 和 NAM 的 SOA 浓度较低（1-3μg/m），SOA 对 PM 的贡献较高（20-33%）。b-SOA 与该地区的植被和森林覆盖率一致。在所有区域（除了 NAF 和 AUS 外），SOA 的主要来源是居民排放（在 SAS 中最高）。非煤炭工业是第二大贡献者（除了 EAF、NAF 和 AUS 外），而 EUR 则主要来自农业和交通。在全球范围内，居民和工业（非煤炭和煤炭）部门对 SOA 的贡献最大，其中 a-SOA 和 b-SOA 几乎相等。消除生物质和居民燃烧固体燃料是解决 PM 和 SOA 问题的最有效措施。
