aerosol chemistry; aethalometer; rotating drum impactor; China; air pollution; black carbon; X-ray fluorescence spectrometry; source apportionment
Rai Pragati, Furger Markus, Slowik Jay G., Zhong Haobin, Tong Yandong, Wang Liwei, Duan Jing, Gu Yifang, Qi Lu, Huang Ru-Jin, Cao Junji, Baltensperger Urs, Prévôt André S.H. (2021), Characteristics and sources of hourly elements in PM10 and PM2.5 during wintertime in Beijing, in
Environmental Pollution, 116865-116865.
Rai Pragati, Slowik Jay G., Furger Markus, El Haddad Imad, Visser Suzanne, Tong Yandong, Singh Atinderpal, Wehrle Günther, Kumar Varun, Tobler Anna K., Bhattu Deepika, Wang Liwei, Ganguly Dilip, Rastogi Neeraj, Huang Ru-Jin, Necki Jaroslaw, Cao Junji, Tripathi Sachchida N., Baltensperger Urs, Prévôt André S. H. (2021), Highly time-resolved measurements of element concentrations in PM<sub>10</sub> and PM<sub>2.5</sub>: comparison of Delhi, Beijing, London, and Krakow, in
Atmospheric Chemistry and Physics, 21(2), 717-730.
Rai Pragati, Furger Markus, El Haddad Imad, Kumar Varun, Wang Liwei, Singh Atinderpal, Dixit Kuldeep, Bhattu Deepika, Petit Jean-Eudes, Ganguly Dilip, Rastogi Neeraj, Baltensperger Urs, Tripathi Sachchida Nand, Slowik Jay G., Prévôt André S.H. (2020), Real-time measurement and source apportionment of elements in Delhi's atmosphere, in
Science of The Total Environment, 742, 140332-140332.
Wang Liwei, Slowik Jay G., Tripathi Nidhi, Bhattu Deepika, Rai Pragati, Kumar Varun, Vats Pawan, Satish Rangu, Baltensperger Urs, Ganguly Dilip, Rastogi Neeraj, Sahu Lokesh K., Tripathi Sachchida N., Prévôt André S. H. (2020), Source characterization of volatile organic compounds measured by proton-transfer-reaction time-of-flight mass spectrometers in Delhi, India, in
Atmospheric Chemistry and Physics, 20(16), 9753-9770.
Puthussery Joseph V, Singh Atinderpal, Rai Pragati, Bhattu Deepika, Kumar Varun, Vats Pawan, Furger Markus, Rastogi Neeraj, Slowik Jay G., Ganguly Dilip, Prevot Andre S.H., Tripathi Sachchida Nand, Verma Vishal (2020), Real-Time Measurements of PM2.5 Oxidative Potential Using a Dithiothreitol Assay in Delhi, India, in
Environmental Science {&} Technology Letters, 7(7), 504-510.
Rai Pragati, Furger Markus, Slowik Jay G., Canonaco Francesco, Fröhlich Roman, Hüglin Christoph, Minguillón María Cruz, Petterson Krag, Baltensperger Urs, Prévôt André S. H. (2020), Source apportionment of highly time-resolved elements during a firework episode from a rural freeway site in Switzerland, in
Atmospheric Chemistry and Physics, 20(3), 1657-1674.
Furger Markus, Rai Pragati, Slowik Jay G., Cao Junji, Visser Suzanne, Baltensperger Urs, Prévôt André S.H. (2020), Automated alternating sampling of PM10 and PM2.5 with an online XRF spectrometer, in
Atmospheric Environment: X, 5, 100065-100065.
Alternating sampling of ambient particulate matter in two size classes
| Author |
Furger, Markus |
| Publication date |
05.02.2020 |
| Persistent Identifier (PID) |
10.17632/76tfsbpgz5.1 |
| Repository |
Mendeley Data
|
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| Author |
Rai, Pragati |
| Publication date |
26.03.2020 |
| Persistent Identifier (PID) |
https://doi.org/10.5281/zenodo.3727703 |
| Repository |
Zenodo
|
| Abstract |
Data to accompany "Source apportionment of highly time-resolved elements during a firework episode from a rural freeway site in Switzerland" publication in Atmospheric Chemistry and Physics. This repository contains measurement data in Härkingen, Switzerland, a permanent station of the Swiss National Air Pollution Monitoring Network (NABEL). Sampling was performed from 23 July to 13 August 2015. This repository has excel file (all data.xlsx) for all the raw data measured during campaign. In addition, it has data corresponding to each figures presented in main text published version.
| Author |
Rai, Pragati |
| Publication date |
08.12.2020 |
| Persistent Identifier (PID) |
https://doi.org/10.5281/zenodo.4311854 |
| Repository |
Zenodo
|
| Abstract |
Data presented in the manuscript "Highly time-resolved measurements of element concentrations in PM10 and PM2.5: Comparison of Delhi, Beijing, London, and Krakow" (https://doi.org/10.5194/acp-2020-618) by Rai et al. (2020).
Real-time measurement and source apportionment of elements in Delhi's atmosphere
| Author |
Rai, Pragati |
| Publication date |
25.06.2020 |
| Persistent Identifier (PID) |
10.5281/zenodo.3907250 |
| Repository |
Zenodo
|
| Abstract |
Here we present semi-continuous and real-time measurements of elemental composition for PM2.5 and PM10 aerosols in Delhi, India, at a time resolution of 30 min to 1 h during two consecutive winters in 2018 and 2019, to identify the prevailing sources. Nine different aerosol sources were identified during both winters using positive matrix factorization (PMF), including dust, brake wear, a S-rich factor, two solid fuel combustion (SFC) factors and four industrial/combustion factors related to plume events (Cr-30 Ni-Mn, Cu-Cd-Pb, Pb-Sn-Se and Cl-Br-Se). Most of these sources had the highest relative contributions during late night (22:00 local time (LT)) and early morning hours (between 03:00 to 08:00 LT), which is consistent with enhanced emissions into a shallow boundary layer. Modelling of airmass source geography revealed that the pollutants enter Delhi via three distinct air corridors during winters including Nepal and Uttar Pradesh (India) in the east, and Pakistan, Punjab (India) and Haryana (India) in the north-west, during winter, when the national capital’s air quality is at its worst.
Characteristics and sources of hourly elements in PM10 and PM2.5 during wintertime in Beijing
| Author |
Rai, Pragati |
| Publication date |
05.03.2021 |
| Persistent Identifier (PID) |
10.5281/zenodo.4584586 |
| Repository |
Zenodo
|
| Abstract |
Data presented in the manuscript "Characteristics and sources of hourly elements in PM10 and PM2.5 during wintertime in Beijing" (https://doi.org/10.1016/j.envpol.2021.116865) by Rai et al. (2021).
Air pollution in Chinese cities is one of the environmental problems China has to address to mitigate the impacts on human health, air quality and climate. Average concentrations of particulate matter exceed 100 µg/m3 in many places in China, and the government is developing and implementing strategies to reduce the load of pollutants by various measures. A characterization of airborne particulate matter (PM), especially its composition and sources, will help in optimizing reduction and mitigation strategies for air pollution. The project aims at studying the temporal variation of major component and trace element concentrations in airborne particulate matter (PM) and their sources in two megacities in China (People’s Republic of China, PRC). Statistical source apportionment techniques will be applied to data collected during two summer and winter field campaigns each in Xian and Beijing. Ambient aerosols will be sampled with 3-stage rotating drum impactors (RDI) segregating the aerosol into the size classes 10-2.5 µm, 2.5 - 1.0 µm, 1.0 - 0.1 µm, in combination with black carbon measurements with aethalometers. The samples are analyzed with synchrotron radiation induced X-ray fluorescence spectrometry (SR-XRF), which yields concentration time series for more than 20 elements (Na to Pb). Pairwise sampling (two RDI/aethalometer combinations at two sites in the same city) will allow for the identification of local and regional pollution, long-range transport, urban increments, and other PM characteristics. The 30-min time resolution allows for the quantitative analysis of diurnal and weekly variations of PM concentrations. Combination of trace elements with aethalometer black carbon and 14C promises to improve the identification of coal combustion, traffic and other industrial sources by their fossil/non-fossil characteristics. Trace elements combined with organics from aerosol mass spectrometry improves the source apportionment of organics in PM.Trace element analyses will be performed with the analysis system developed at the Laboratory of Atmospheric Chemistry (LAC), the Spectrum Analysis for Multiple Instruments (SAMI-XRF) tool for spectrum analysis and quantification, and the statistical Source-Finder (SoFi) tool for source apportionment.