Automated SEM/EDX imaging for the in-depth characterization of non-exhaust traffic emissions from the Munich subway system

被引：3

作者：

Neukirchen, Carsten ^{[1
,4
]}

Meiners, Thorsten ^{[2
]}

Bendl, Jan ^{[1
,5
]}

Zimmermann, Ralf ^{[3
,4
]}

Adam, Thomas ^{[1
,3
]}

机构：

[1] Univ Bundeswehr Munich, Inst Chem & Environm Engn, Fac Mech Engn, Werner Heisenberg Weg 39, D-85577 Neubiberg, Germany

[2] Oxford Instruments GmbH, Borsigstr 15, D-652025 Wiesbaden, Germany

[3] Helmholtz Munich, Joint Mass Spectrometry Ctr JMSC Comprehens Mol An, Dept Environm Hlth, Gmunder Str 37, D-81379 Munich, Germany

[4] Univ Rostock, Inst Chem, Joint Mass Spectrometry Ctr JMSC Chair Analyt Chem, Albert Einstein Str 27, D-18059 Rostock, Germany

[5] Charles Univ Prague, Inst Environm Studies, Fac Sci, Benatska 2, Prague 12801, Czech Republic

来源：

SCIENCE OF THE TOTAL ENVIRONMENT | 2024年 / 915卷

关键词：

Automated particle classification; Train emissions; Personal exposure; Elemental composition; Algorithm-based particle classification; Scanning electron microscopy; WEAR PARTICLE EMISSIONS; NANOPARTICLES; IRON; SIZE;

D O I：

10.1016/j.scitotenv.2024.170008

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

A SEM/EDX based automated measurement and classification algorithm was tested as a method for the in-depth analysis of micro -environments in the Munich subway using a custom build mobile measurements system. Sampling was conducted at platform stations, to investigate the personal exposure of commuters to subway particulate matter during platform stays. EDX spectra and morphological features of all analyzed particles were automatically obtained and particles were automatically classified based on pre -defined chemical and morphological boundaries. Source apportionment for individual particles, such as abrasion processes at the wheel -brake interface, was partially possible based on the established particle classes. An average of 98.87 +/- 1.06 % of over 200,000 analyzed particles were automatically assigned to the pre -defined classes, with 84.68 +/- 16.45 % of particles classified as highly ferruginous. Manual EDX analysis further revealed, that heavy metal rich particles were also present in the ultrafine size range well below 100 nm.

引用

页数：13

共 8 条

[1] Non-exhaust traffic emissions: Sources, characterization, and mitigation measures
Piscitello, Amelia
Bianco, Carlo
Casasso, Alessandro
Sethi, Rajandrea
SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 766
[2] Characterisation of non-exhaust emissions from road traffic in Lisbon
Cunha-Lopes I.
Alves C.A.
Casotti Rienda I.
Faria T.
Lucarelli F.
Querol X.
Amato F.
Almeida S.M.
Atmospheric Environment, 2022, 286
[3] Characterisation of non-exhaust emissions from road traffic in Lisbon
Cunha-Lopes, I
Alves, C. A.
Rienda, I. Casotti
Faria, T.
Lucarelli, F.
Querol, X.
Amato, F.
Almeida, S. M.
ATMOSPHERIC ENVIRONMENT, 2022, 286
[4] Non-exhaust vehicle emissions of particulate matter and VOC from road traffic: A review
Harrison, Roy M.
Allan, James
Carruthers, David
Heal, Mathew R.
Lewis, Alastair C.
Marner, Ben
Murrells, Tim
Williams, Andrew
ATMOSPHERIC ENVIRONMENT, 2021, 262
[5] Development of a Static Model to Identify Best Management Practices for Trace Metals from Non-Exhaust Traffic Emissions
Matthew Fiala
Hyun-Min Hwang
Environmental Processes, 2019, 6 : 377 - 389
[6] Development of a Static Model to Identify Best Management Practices for Trace Metals from Non-Exhaust Traffic Emissions
Fiala, Matthew
Hwang, Hyun-Min
ENVIRONMENTAL PROCESSES-AN INTERNATIONAL JOURNAL, 2019, 6 (02): : 377 - 389
[7] Identification of atmospheric particulate matter derived from coal and biomass burning and from non-exhaust traffic emissions using zinc isotope signatures
Schleicher, Nina J.
Weiss, Dominik J.
ENVIRONMENTAL POLLUTION, 2023, 329
[8] Traffic generated non-exhaust particulate emissions from concrete pavement: A mass and particle size study for two-wheelers and small cars
Kaul, Aatmeeyata D. S.
Sharma, Mukesh
ATMOSPHERIC ENVIRONMENT, 2009, 43 (35) : 5691 - 5697

← 1 →