DOI: 10.1016/j.atmosenv.2014.06.021
Scopus记录号: 2-s2.0-84902464414
论文题名: New functions for estimating AOT40 from ozone passive sampling
作者: De Marco A ; , Vitale M ; , Kilic U ; , Serengil Y ; , Paoletti E
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2014
卷: 95 起始页码: 82
结束页码: 88
语种: 英语
英文关键词: AOT40
; Loibl function
; Ozone monitoring
; Passive sampling
; Tropospheric ozone
Scopus关键词: Ozone
; Regression analysis
; Risk assessment
; Active measurement
; AOT40
; European Standards
; Non-linear regression
; Ozone monitoring
; Passive sampling
; Remote environment
; Tropospheric ozone
; Monitoring
; ozone
; atmospheric modeling
; atmospheric pollution
; concentration (composition)
; data set
; estimation method
; measurement method
; ozone
; sampling
; article
; environmental monitoring
; forest
; Italy
; latitude
; longitude
; nonlinear system
; prediction
; priority journal
; rural area
; simulation
; statistical model
; suburban area
; Italy
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: AOT40 is the present European standard to assess whether ozone (O3) pollution is a risk for vegetation, and is calculated by using hourly O3 concentrations from automatic devices, i.e. by active monitoring. Passive O3 monitoring is widespread in remote environments. The Loibl function estimates the mean daily O3 profile and thus hourly O3 concentrations, and has been proposed to calculate AOT40 from passive samplers. We investigated whether this function performs well in inhomogeneous terrains such as over the Italian country. Data from 75 active monitoring stations (28 rural and 47 suburban) were analysed over two years. AOT40 was calculated from hourly O3 data either measured by active measurements or estimated by the Loibl function applied to biweekly averages of active-measurement hourly data. The latter approach simulated the data obtained from passive monitoring, as two weeks is the usual exposure window of passive samplers. Residuals between AOT40 estimated by applying the Loibl function and AOT40 calculated from active monitoring ranged from+241% to-107%, suggesting that the Loibl function is inadequate to accurately predict AOT40 in Italy. New statistical models were built for both rural and suburban areas by using non-linear models and including predictors that can be easily measured at forest sites. The modelled AOT40 values strongly depended on physical predictors (latitude and longitude), alone or in combination with other predictors, such as seasonal cumulated ozone and elevation. These results suggest that multi-variate, non-linear regression models work better than the Loibl-based approach in estimating AOT40. © 2014 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81322
Appears in Collections: 气候变化事实与影响
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作者单位: Italian National Agency for New Technologies, Energy and The Environment (ENEA), C.R. Casaccia, Via Anguillarese 301, 00123 S. Maria di Galeria, Rome, Italy; Department of Environmental Biology, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy; University of Istanbul, Faculty of Forestry, Department of Watershed Management, Bahcekoy-Sariyer, Istanbul, Turkey; IPSP-CNR, Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy
Recommended Citation:
De Marco A,, Vitale M,, Kilic U,et al. New functions for estimating AOT40 from ozone passive sampling[J]. Atmospheric Environment,2014-01-01,95