A long-term high-resolution air quality reanalysis with public facing air quality dashboard over the Contiguous United States (CONUS)

IF 11.2 1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Earth System Science Data Pub Date : 2024-06-06 DOI:10.5194/essd-2024-180
Rajesh Kumar, Piyush Bhardwaj, Cenlin He, Jennifer Boehnert, Forrest Lacey, Stefano Alessandrini, Kevin Sampson, Matthew Casali, Scott Swerdlin, Olga Wilhelmi, Gabriele G. Pfister, Benjamin Gaubert, Helen Worden
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Abstract

Abstract. We present a 14-year 12-km hourly air quality dataset created by assimilating satellite observations of aerosol optical depth (AOD) and carbon monoxide (CO) in an air quality model to fill gaps in the contiguous United States (CONUS) air quality monitoring network and help air quality managers understand long-term changes in county level air quality. Specifically, we assimilate the Moderate Resolution Imaging Spectroradiometer (MODIS) AOD and the Measurement of Pollution in the Troposphere (MOPITT) CO observations in the Community Multiscale Air Quality Model (CMAQ) every day from 01 Jan 2005 to 31 Dec 2018 to produce this dataset. The Weather Research and Forecasting (WRF) model simulated meteorological fields are used to drive CMAQ offline and to generate meteorology dependent anthropogenic emissions. Both the weather and air quality (surface fine particulate matter (PM2.5) and ozone) simulations are subjected to a comprehensive evaluation against multi-platform observations to establish the credibility of our dataset and characterize its uncertainties. We show that our dataset captures regional hourly, seasonal, and interannual variability in meteorology very well across the CONUS. The correlation coefficient between the observed and simulated surface ozone and PM2.5 concentrations for different Environmental Protection Agency (EPA) defined regions across CONUS are 0.77–0.91 and 0.49–0.79, respectively. The mean bias and root mean squared error for modeled ozone are 3.7–6.8 ppbv and 7–9 ppbv, respectively, while the corresponding values for PM2.5 are -0.9–5.6 µg/m3 and 3.0–8.3 µg/m3, respectively. We estimate that annual CONUS averaged maximum daily 8-hour average (MDA8) ozone and PM2.5 trends are -0.30 ppb/year and -0.24 μg/m3/year, respectively. Wintertime MDA8 ozone shows an increasing but statistically insignificant trend at several sites. We also found a decreasing trend in the 95th percentile of MDA8 ozone but an increasing trend in the 5th percentile. Most of the sites in the Pacific Northwest show an increasing but statistically insignificant trend during summer. An ArcGIS air quality dashboard has been developed to enable easy visualization and interpretation of county level air quality measures and trends by stakeholders, and a Python-based Streamlit application has been developed to allow the download of the air quality data in simplified text and graphic formats.
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长期高分辨率空气质量再分析,带面向公众的美国毗连区(CONUS)空气质量仪表板
摘要。我们通过在空气质量模型中同化气溶胶光学深度(AOD)和一氧化碳(CO)的卫星观测数据,创建了一个为期 14 年的 12 公里每小时空气质量数据集,以填补美国毗连地区(CONUS)空气质量监测网络的空白,帮助空气质量管理人员了解县级空气质量的长期变化。具体来说,我们在社区多尺度空气质量模型(CMAQ)中同化了中分辨率成像分光仪(MODIS)的AOD和对流层污染测量(MOPITT)的CO观测数据,时间跨度为2005年1月1日至2018年12月31日。天气研究与预报(WRF)模型模拟气象场用于离线驱动 CMAQ,并生成与气象相关的人为排放。天气和空气质量(表面细颗粒物(PM2.5)和臭氧)模拟都根据多平台观测数据进行了综合评估,以确定数据集的可信度及其不确定性。结果表明,我们的数据集能很好地捕捉到整个美国联邦的区域性每小时、季节和年际气象变化。在美国中部不同的环境保护局(EPA)定义区域,观测和模拟的地表臭氧和 PM2.5 浓度之间的相关系数分别为 0.77-0.91 和 0.49-0.79。模拟臭氧的平均偏差和均方根误差分别为 3.7-6.8 ppbv 和 7-9 ppbv,而 PM2.5 的相应值分别为-0.9-5.6 µg/m3 和 3.0-8.3 µg/m3。我们估计,CONUS 年平均最大日 8 小时平均值(MDA8)臭氧和 PM2.5 的趋势分别为-0.30 ppb/年和-0.24 μg/m3/年。多个地点的冬季 MDA8 臭氧呈上升趋势,但在统计上并不显著。我们还发现 MDA8 臭氧第 95 百分位数呈下降趋势,但第 5 百分位数呈上升趋势。西北太平洋地区的大多数站点在夏季都显示出上升趋势,但在统计上并不显著。我们还开发了一个 ArcGIS 空气质量仪表盘,方便利益相关者对县级空气质量指标和趋势进行可视化解读,并开发了一个基于 Python 的 Streamlit 应用程序,允许以简化的文本和图形格式下载空气质量数据。
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来源期刊
Earth System Science Data
Earth System Science Data GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
18.00
自引率
5.30%
发文量
231
审稿时长
35 weeks
期刊介绍: Earth System Science Data (ESSD) is an international, interdisciplinary journal that publishes articles on original research data in order to promote the reuse of high-quality data in the field of Earth system sciences. The journal welcomes submissions of original data or data collections that meet the required quality standards and have the potential to contribute to the goals of the journal. It includes sections dedicated to regular-length articles, brief communications (such as updates to existing data sets), commentaries, review articles, and special issues. ESSD is abstracted and indexed in several databases, including Science Citation Index Expanded, Current Contents/PCE, Scopus, ADS, CLOCKSS, CNKI, DOAJ, EBSCO, Gale/Cengage, GoOA (CAS), and Google Scholar, among others.
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