Data · dataset · 2024
A Dataset of CO2 and particulate matter (PM) concentration with a 30-meter resolution on urban expressways in Guangzhou City
Listed in ScienceDB
The concentration data of urban atmospheric CO2 and particulate matter (PM) is the basic data for measuring urban air quality, providing important information for conducting urban environmental remediation and public health research.
Description
At present, environmental data such as CO2 and particulate matter (PM) are often sourced from fixed point monitoring, remote sensing images, and econometric models such as environmental monitoring stations.
The spatiotemporal resolution is generally insufficient, making it difficult to reveal the spatiotemporal distribution of CO2 and particulate matter (PM) on the urban road scale. This dataset adopts a walking monitoring method, taking the Inner Ring Road in the central urban area of Guangzhou as the research area. Three typical periods of work from April to June 2023 (morning peak, noon peak, and evening peak) were selected, and CO2 and particulate matter (PM1.0, PM2.5, and PM10) concentration data were collected multiple times with a time accuracy of 1 second.
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The dataset was compiled into a high spatiotemporal resolution dataset for CO2 and particulate matter (PM) concentration on urban roads, This dataset reveals the refined distribution pattern of greenhouse gases and atmospheric pollutants on the urban road scale, which has practical significance for achieving refined road spatial governance and improving the quality of urban living environment.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.j00001.00952 ↗
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
- Image 65% · Pollution and contamination 69% · Satellite remote sensing 65%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.j00001.00952 | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:4105 | 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 | |
| concepts[modality].local:modality:image | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[modality].local:modality:remote-sensing | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |