点中心变差法评价空气质量监测点的空间代表性

IF 0.5 4区 环境科学与生态学 Q4 ENVIRONMENTAL SCIENCES
O. Kracht, M. Gerboles
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引用次数: 2

摘要

我们提出了一种基于点中心半变方差的地质统计技术,该技术可用于获得有关空气质量监测点空间代表性的有价值信息。经典地质统计学根据变异函数描述浓度场的空间相关结构,而以点为中心的变异函数是基于从特定中心点和域中所有其他点的集合形成的成对观察到的浓度差的平方的平均值。因此,它将监测站置于当地或区域空气质量模式的背景下。我们展示了以点为中心的变差函数的数学反演如何提供监测站点的代表性区域范围的估计。该方法的应用在安特卫普市的一组建模数据上进行了测试,该数据用于FAIRMODE/AQUILA空间代表性评估方法的相互比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial representativeness evaluation of air quality monitoring sites by point-centred variography
We propose a geostatistical technique based on point-centred semi-variograms that can be used to derive valuable information about the spatial representativeness of air quality monitoring sites. Whereas classical geostatistics describes the spatial correlation structure of a concentration field in terms of the variogram, point-centred variography is based on the average of squared concentration differences observed in pairs formed from a particular central point and the set of all other points in the domain. It thereby places a monitoring station in the context of the local or regional air quality pattern. We demonstrate how a mathematical inversion of the point-centred variogram can provide estimates of the extent of the representativeness area of a monitoring site. The application of this approach is tested on a set of modelling data from the city of Antwerp, which was used for the FAIRMODE/AQUILA intercomparison exercise of methods for the assessment of spatial representativeness.
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来源期刊
CiteScore
1.10
自引率
0.00%
发文量
3
审稿时长
4.5 months
期刊介绍: IJEP provides an international forum in the field of environment and pollution and addresses early and medium-term challenges involving scientific prediction, modelling and assessment. It focuses on ground-breaking research in the science of environmental pollution, at the early scientific stage. It is one of three key journals which together offer complete coverage of environmental issues: IJETM focuses on technical/engineering, policy and management solutions for environmental problems, and IJGEnvI focuses on future, longer-term environmental scenarios, ecological economics, climate change and biodiversity.
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