气候变化领域集成服务门户(CCPortal): Are dense networks of low-cost nodes really useful for monitoring air pollution? A case study in Staffordshire

CCPortal

DOI	10.5194/acp-22-13949-2022
	Are dense networks of low-cost nodes really useful for monitoring air pollution? A case study in Staffordshire
	Frederickson, Louise Boge; Sidaraviciute, Ruta; Schmidt, Johan Albrecht; Hertel, Ole; Johnson, Matthew Stanley
发表日期	2022
ISSN	1680-7316
EISSN	1680-7324
起始页码	13949
结束页码	13965
卷号	22 期号:21 页码:17
英文摘要	Air pollution exhibits hyper-local variation, especially near emissions sources. In addition to people's time-activity patterns, this variation is the most critical element determining exposure. Pollution exposure is time-activity- and path-dependent, with specific behaviours such as mode of commuting and time spent near a roadway or in a park playing a decisive role. Compared to conventional air pollution monitoring stations, nodes containing low-cost air pollution sensors can be deployed with very high density. In this study, a network of 18 nodes using low-cost air pollution sensors was deployed in Newcastle-under-Lyme, Staffordshire, UK, in June 2020. Each node measured a range of species including nitrogen dioxide (NO2), ozone (O-3), and particulate matter (PM2.5 and PM10); this study focuses on NO2 and PM2.5 over a 1-year period from 1 August 2020 to 1 October 2021. A simple and effective temperature, scale, and offset correction was able to overcome data quality issues associated with temperature bias in the NO2 readings. In its recent update, the World Health Organization (WHO) dramatically reduced annual exposure limit values from 40 to 10 mu g m(-3) for NO2 and from 10 to 5 mu g m(-3) for PM2.5. We found that the average annual mean NO2 concentration for the network was 17.5 mu g m(-3) and 8.1 mu g m(-3) for PM2.5. While in exceedance of the WHO guideline levels, these average concentrations do not exceed legally binding UK/EU standards. The network average NO2 concentration was 12.5 mu g m(-3) higher than values reported by a nearby regional air quality monitoring station, showing the critical importance of monitoring close to sources before pollution is diluted. We demonstrate how data from a low-cost air pollution sensor network can reveal insights into patterns of air pollution and help determine whether sources are local or non-local. With spectral analysis, we investigate the variation of the pollution levels and identify typical periodicities. Both NO2 and PM2.5 have contributions from high-frequency sources; however, the low-frequency sources are significantly different. Using spectral analysis, we determine that at least 54.3 +/- 4.3 % of NO2 is from local sources, whereas, in contrast, only 37.9 +/- 3.5 % of PM2.5 is local.
学科领域	Environmental Sciences; Meteorology & Atmospheric Sciences
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:000877089500001
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/273008
作者单位	Aarhus University; Aarhus University; University of Copenhagen; Aarhus University
推荐引用方式 GB/T 7714	Frederickson, Louise Boge,Sidaraviciute, Ruta,Schmidt, Johan Albrecht,et al. Are dense networks of low-cost nodes really useful for monitoring air pollution? A case study in Staffordshire[J],2022,22(21):17.
APA	Frederickson, Louise Boge,Sidaraviciute, Ruta,Schmidt, Johan Albrecht,Hertel, Ole,&Johnson, Matthew Stanley.(2022).Are dense networks of low-cost nodes really useful for monitoring air pollution? A case study in Staffordshire.ATMOSPHERIC CHEMISTRY AND PHYSICS,22(21),17.
MLA	Frederickson, Louise Boge,et al."Are dense networks of low-cost nodes really useful for monitoring air pollution? A case study in Staffordshire".ATMOSPHERIC CHEMISTRY AND PHYSICS 22.21(2022):17.