标题: Cooking emissions dominated the high-resolution spatial variations of ultrafine particles (PM0.1) in a Chinese megacity
作者: Yang, QR (Yang, Qiren); Cao, ZZ (Cao, Zezheng); Wei, S (Wei, Sheng); Wang, HQ (Wang, Haoqian); Xu, CY (Xu, Chunyu); Xue, BD (Xue, Baode); Zhang, Q (Zhang, Qiang); Liu, YQ (Liu, Yanqun); Huang, DD (Huang, Dandan); Yu, K (Yu, Kuai); Cheng, HR (Cheng, Hairong); Jiang, JK (Jiang, Jingkun); Li, XX (Li, Xiaoxiao)
来源出版物: ATMOSPHERIC ENVIRONMENT 卷: 363 文献号: 121635 DOI: 10.1016/j.atmosenv.2025.121635 Early Access Date: DEC 2025 Published Date: 2025 DEC 15
摘要: Long-term exposure to ultrafine particles (PM0.1/UFPs) is proposed to be related with many diseases. Large-scale epidemic studies related with UFPs are scarce due to the lack of UFP spatial distributions. While existing research predominantly stressed the dominant influences of vehicular sources, the impact of cooking emissions might be significant in Chinese megacities, due to high-emitting cooking styles. This study performed high-density spatial measurements (0.40 km2/site) of UFPs using 3 electric motorcycles carrying 3 condensation particle counters (CPCs) at 153 sites in Wuchang District in the megacity Wuhan, central China. We analyzed particle number (PN) distributions across different types of sites, quantified distance-decay relationships between UFPs and cooking sources, and developed high-resolution (25 m x 25 m grid) land-use regression (LUR) models linking PN con-centrations with geographic predictors. Key findings include: (1) Restaurant-adjacent sites exhibited the highest PN levels (significantly exceeding traffic-adjacent sites), one of the key reasons is that the density of restaurants is highly related with dense buildings which hinders dispersion; (2) PN concentrations decay exponentially with the distance from the nearest restaurant; (3) Traffic-adjacent sites have lower-than-average PN concentrations, benefiting from favorable ventilation conditions of the wide roads; (4) The most important buffer size for restaurant variables, traffic variables, and diffusion variables are <= 50 m, 100-200 m, and 500 m, respectively, reflecting the higher spatial heterogeneity caused by cooking emissions in typical Chinese megacities. Thus, to catch the hot spots caused by restaurants, the resolution of the LUR model needs to be <= 50 m. These findings provide novel insights into urban UFP source apportionment and emphasize the necessity of incorporating cooking emission dynamics in environmental exposure assessments for rapidly urbanizing regions.
作者关键词: Ultrafine particles; Cooking emissions; Vehicle emissions; Land use regression model; Mobile measurements; High-resolution concentration map
KeyWords Plus: USE REGRESSION-MODELS; EXPOSURE ASSESSMENT; AMBIENT ULTRAFINE; BLACK CARBON; POLLUTION; AEROSOL; NANOPARTICLES; ATMOSPHERE; AUGSBURG; NETWORK
地址: [Yang, Qiren; Cao, Zezheng; Wei, Sheng; Wang, Haoqian; Xu, Chunyu; Cheng, Hairong; Li, Xiaoxiao] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China.
[Xue, Baode; Yu, Kuai] Huazhong Univ Sci & Technol, Tongji Med Coll, Sch Publ Hlth,Minist Educ, Dept Occupat & Environm Hlth,Key Lab Environm & Hl, Wuhan, Peoples R China.
[Xue, Baode; Yu, Kuai] Huazhong Univ Sci & Technol, Tongji Med Coll, Sch Publ Hlth,Minist Educ, Dept Epidemiol & Biostat,Key Lab Environm & Hlth, Wuhan, Peoples R China.
[Xue, Baode; Yu, Kuai] Huazhong Univ Sci & Technol, Tongji Med Coll, Sch Publ Hlth, State Key Lab Environm Hlth Incubating, Wuhan, Peoples R China.
[Zhang, Qiang] Beijing NaKe Environm Technol Co Ltd, Beijing 100084, Peoples R China.
[Liu, Yanqun] Wuhan Univ, Sch Nursing, Ctr Womens & Childrens Hlth Res, Res Ctr Lifespan Hlth, Wuhan 430071, Peoples R China.
[Huang, Dandan; Li, Xiaoxiao] Shanghai Acad Environm Sci, State Environm Protect Key Lab Format & Prevent Ur, Shanghai 200233, Peoples R China.
[Jiang, Jingkun] Tsinghua Univ, Sch Environm, State Key Joint Lab Environm Simulat & Pollut Cont, Beijing 100084, Peoples R China.
通讯作者地址: Li, XX (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China.
电子邮件地址: [email protected]
影响因子：3.7
