ARPALData:用于检索和分析来自伦巴第 ARPA(意大利)的空气质量和天气数据的 R 软件包

IF 3 4区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Environmental and Ecological Statistics Pub Date : 2024-03-01 DOI:10.1007/s10651-024-00599-6
Paolo Maranzano, Andrea Algieri
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引用次数: 0

摘要

我们介绍的 ARPALData 是一个 R 软件包,可帮助国际用户检索、处理和分析伦巴第大区(意大利北部)的空气质量和天气数据。该软件提供了一个用户友好型工具,可直接查询地区环保机构的平台,并确保使用标准化语法实时更新信息。该软件以标准统计格式提供数据。最后,所有测量数据、元数据和后续分析工具都以英文提供给用户,方便国际和国内用户使用。数据收集自伦巴第大区环境保护局(即 ARPA Lombardia)的开放式数据库。ARPALData 返回通过 ARPA Lombardia 管理的空气质量和天气地面监测网络收集到的多个时间频率(从每小时到每年)的测量数据,以及多个污染物的市级估计值。除了数据下载功能外,ARPALData 还提供了用于探索、描述、分析和以图形表示空气质量和天气数据的功能。特别是,用户可以使用这些功能计算关键的描述性统计数据和输入数据图、按时间汇总测量数据、检测异常值以及研究缺失值(间隙长度)模式。在此,我们将讨论该软件包的目的、目标和功能,并介绍三个指导性示例和案例研究,在这些示例和案例研究中,该软件被用于描述不同环境下的空气质量和气象特征。这些示例旨在为使用 ARPALData 中包含的最相关工具完成分析提供逐步指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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ARPALData: an R package for retrieving and analyzing air quality and weather data from ARPA Lombardia (Italy)

We present ARPALData, an R package that can help international users retrieve, handle, and analyze air quality and weather data in the Lombardy region (Northern Italy). The software provides a user-friendly tool that directly inquires into the platform of the regional environmental protection agency and ensures real-time updating of information using standardized syntax. The software provides data in standard statistical formats. Eventually, all measurements, metadata, and subsequent analytical tools are provided to users in English, facilitating accessibility to international and domestic users. Data are collected from the open database of the Regional Agency for Environmental Protection of Lombardy, namely ARPA Lombardia. ARPALData returns measurements at several temporal frequencies (infra-hourly to yearly) collected through air quality and weather ground monitoring networks managed by ARPA Lombardia, as well as estimates of several pollutants at the municipal level. In addition to data download functions, ARPALData provides functions to explore, describe, analyze, and graphically represent air quality and weather data. In particular, users are provided with functions to compute key descriptive statistics and input data maps, temporally aggregate measurements, detect outliers, and study missing-value (gap length) patterns. Herein, we discuss purposes, goals, and functioning of the package, and present three guided examples and case studies in which the software is used to characterize air quality and meteorology in different settings. The examples are designed to provide a step-by-step guide for accomplished analyses using the most relevant tools included in ARPALData.

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来源期刊
Environmental and Ecological Statistics
Environmental and Ecological Statistics 环境科学-环境科学
CiteScore
5.90
自引率
2.60%
发文量
27
审稿时长
>36 weeks
期刊介绍: Environmental and Ecological Statistics publishes papers on practical applications of statistics and related quantitative methods to environmental science addressing contemporary issues. Emphasis is on applied mathematical statistics, statistical methodology, and data interpretation and improvement for future use, with a view to advance statistics for environment, ecology and environmental health, and to advance environmental theory and practice using valid statistics. Besides clarity of exposition, a single most important criterion for publication is the appropriateness of the statistical method to the particular environmental problem. The Journal covers all aspects of the collection, analysis, presentation and interpretation of environmental data for research, policy and regulation. The Journal is cross-disciplinary within the context of contemporary environmental issues and the associated statistical tools, concepts and methods. The Journal broadly covers theory and methods, case studies and applications, environmental change and statistical ecology, environmental health statistics and stochastics, and related areas. Special features include invited discussion papers; research communications; technical notes and consultation corner; mini-reviews; letters to the Editor; news, views and announcements; hardware and software reviews; data management etc.
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