Data · dataset · 2022
Identifying the wintertime sources of volatile organic compounds (VOCs) from MAX-DOAS measured formaldehyde and glyoxal in Chongqing, southwest China
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Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations were performed from 27 December 2018 to 16 January 2019 in Changshou, one of subdistricts of Chongqing, China.
Description
Primary atmospheric pollutant in Changshou during wintertime was PM2.5, whose contribution averaged about 70.15% ± 9.5% of PM10. The ratio of PM2.5/PM10 decreased when PM2.5 pollution became worse, and it should attribute to biomass burning and the contribution of hygroscopic growth and enhanced heterogeneous chemistry under high relative humidity condition.
Moreover, nitrogen dioxide (NO2), formaldehyde (HCHO) and glyoxal (CHOCHO) vertical profiles during the campaign period were retrieved separately. TROPOMI HCHO vertical column densities (VCDs) and MAX-DOAS HCHO VCDs were correlated well (R = 0.93). In order to identify the sources of volatile organic compound (VOC) in Changshou, the ratio of CHOCHO to HCHO (RGF) in five different layers were estimated.
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The estimated daily averaged RGF were 0.0205 ± 0.0077, 0.0727 ± 0.0286, 0.0864 ± 0.0296, 0.0770 ± 0.0275 and 0.0746 ± 0.0263 in 0–100 m, 100–200 m, 300–400 m, 500–600 m and 700–800 m layers, respectively. The estimated RGF will increase when biomass burnings were dominated. Using NO2 as a tracer of anthropogenic emissions, we found the RGF values gradually decrease with the increase of NO2 levels.
RGF values in 0–100 m layer and all the other upper layers are 0.015–0.025 and 0.06–0.14, and that means the dominant sources of VOCs in 0–100 m layer and all the other upper layers are biogenic emission and anthropogenic emission (especially biomass burning), respectively. In addition, we found that RGF has site dependence which is in compliance with several previous studies.
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- DOI doi.org/10.57760/sciencedb.05232 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Climate change science 69%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.05232 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:3702 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (69%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |