Long-Term Trends in Inferred Continental Background Ozone in Eastern Australia
A better understanding of background tropospheric ozone delivers multiple benefits. Robust estimates of regional background ozone are required to understand the limits of anthropogenic emissions controlling ozone reduction. Long-term estimates of background ozone assist in characterising changes in...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Atmosphere |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4433/14/7/1104 |
| _version_ | 1827734021430312960 |
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| author | Matthew L. Riley Ningbo Jiang Hiep Nguyen Duc Merched Azzi |
| author_facet | Matthew L. Riley Ningbo Jiang Hiep Nguyen Duc Merched Azzi |
| author_sort | Matthew L. Riley |
| collection | DOAJ |
| description | A better understanding of background tropospheric ozone delivers multiple benefits. Robust estimates of regional background ozone are required to understand the limits of anthropogenic emissions controlling ozone reduction. Long-term estimates of background ozone assist in characterising changes in atmospheric composition and can help quantify the influence of human activity on the atmosphere. Background tropospheric ozone measurements representative of continental air masses are scarce in Australia. Here, we use k-means clustering to identify a cluster of measurements from the long-term air quality monitoring station at Oakdale, NSW, which are likely to be representative of background air. The cluster is associated with NO<sub>x</sub>-limited air masses of continental origin. From this analysis, we estimate background ozone representative of Eastern Australia. We find recent (2017–2022) mean ozone mixing ratios of 28.5 ppb and identify a statistically significant (α = 0.05) trend in the mean of +1.8 (1.0–2.8) ppb/decade. Our methods demonstrate that some long-term monitoring stations within or near urban areas can provide suitable conditions and datasets for regional Global Atmosphere Watch monitoring. |
| first_indexed | 2024-03-11T01:19:38Z |
| format | Article |
| id | doaj.art-8635e17aac774de7ac50fa7fd770dd04 |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-11T01:19:38Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-8635e17aac774de7ac50fa7fd770dd042023-11-18T18:15:33ZengMDPI AGAtmosphere2073-44332023-07-01147110410.3390/atmos14071104Long-Term Trends in Inferred Continental Background Ozone in Eastern AustraliaMatthew L. Riley0Ningbo Jiang1Hiep Nguyen Duc2Merched Azzi3NSW Department of Planning and Environment, Climate and Atmospheric Science, Lidcombe, NSW 2141, AustraliaNSW Department of Planning and Environment, Climate and Atmospheric Science, Lidcombe, NSW 2141, AustraliaNSW Department of Planning and Environment, Climate and Atmospheric Science, Lidcombe, NSW 2141, AustraliaNSW Department of Planning and Environment, Climate and Atmospheric Science, Lidcombe, NSW 2141, AustraliaA better understanding of background tropospheric ozone delivers multiple benefits. Robust estimates of regional background ozone are required to understand the limits of anthropogenic emissions controlling ozone reduction. Long-term estimates of background ozone assist in characterising changes in atmospheric composition and can help quantify the influence of human activity on the atmosphere. Background tropospheric ozone measurements representative of continental air masses are scarce in Australia. Here, we use k-means clustering to identify a cluster of measurements from the long-term air quality monitoring station at Oakdale, NSW, which are likely to be representative of background air. The cluster is associated with NO<sub>x</sub>-limited air masses of continental origin. From this analysis, we estimate background ozone representative of Eastern Australia. We find recent (2017–2022) mean ozone mixing ratios of 28.5 ppb and identify a statistically significant (α = 0.05) trend in the mean of +1.8 (1.0–2.8) ppb/decade. Our methods demonstrate that some long-term monitoring stations within or near urban areas can provide suitable conditions and datasets for regional Global Atmosphere Watch monitoring.https://www.mdpi.com/2073-4433/14/7/1104background ozonek-means clusteringozone trendsair quality monitoring |
| spellingShingle | Matthew L. Riley Ningbo Jiang Hiep Nguyen Duc Merched Azzi Long-Term Trends in Inferred Continental Background Ozone in Eastern Australia Atmosphere background ozone k-means clustering ozone trends air quality monitoring |
| title | Long-Term Trends in Inferred Continental Background Ozone in Eastern Australia |
| title_full | Long-Term Trends in Inferred Continental Background Ozone in Eastern Australia |
| title_fullStr | Long-Term Trends in Inferred Continental Background Ozone in Eastern Australia |
| title_full_unstemmed | Long-Term Trends in Inferred Continental Background Ozone in Eastern Australia |
| title_short | Long-Term Trends in Inferred Continental Background Ozone in Eastern Australia |
| title_sort | long term trends in inferred continental background ozone in eastern australia |
| topic | background ozone k-means clustering ozone trends air quality monitoring |
| url | https://www.mdpi.com/2073-4433/14/7/1104 |
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