School of Earth Sciences, The University of Melbourne, Australia; ARC Centre of Excellence for Climate System Science, Sydney, Australia.
School of Mathematics and Statistics, The University of Melbourne, Australia.
Environ Pollut. 2021 Apr 1;274:116498. doi: 10.1016/j.envpol.2021.116498. Epub 2021 Jan 13.
Poor air quality is an emerging problem in Australia primarily due to ozone pollution events and lengthening and more severe wildfire seasons. A significant deterioration in air quality was experienced in Australia's most populous cities, Melbourne and Sydney, as a result of fires during the so-called Black Summer which ran from November 2019 through to February 2020. Following this period, social, mobility and economic restrictions to curb the spread of the COVID-19 pandemic were implemented in Australia. We quantify the air quality impact of these contrasting periods in the south-eastern states of Victoria and New South Wales (NSW) using a meteorological normalisation approach. A Random Forest (RF) machine learning algorithm was used to compute baseline time series' of nitrogen dioxide (NO), ozone (O), carbon monoxide CO and particulate matter with diameter < 2.5 μm (PM), based on a 19 year, detrended training dataset. Across Victorian sites, large increases in CO (188%), PM (322%) and ozone (22%) were observed over the RF prediction in January 2020. In NSW, smaller pollutant increases above the RF prediction were seen (CO 58%, PM 80%, ozone 19%). This can be partly explained by the RF predictions being high compared to the mean of previous months, due to high temperatures and strong wind speeds, highlighting the importance of meteorological normalisation in attributing pollution changes to specific events. From the daily observation-RF prediction differences we estimated 249.8 (95% CI: 156.6-343.) excess deaths and 3490.0 (95% CI 1325.9-5653.5) additional hospitalisations were likely as a result of PM and O exposure in Victoria and NSW. During April 2019, when COVID-19 restrictions were in place, on average NO decreased by 21.5 and 8% in Victoria and NSW respectively. O and PM remained effectively unchanged in Victoria on average but increased by 20 and 24% in NSW respectively, supporting the suggestion that community mobility reduced more in Victoria than NSW. Overall the air quality change during the COVID-19 lockdown had a negligible impact on the calculated health outcomes.
空气质量差是澳大利亚一个新出现的问题,主要是由于臭氧污染事件以及野火季节的延长和加剧。由于 2019 年 11 月至 2020 年 2 月所谓的“黑色夏季”期间发生的火灾,澳大利亚人口最多的城市墨尔本和悉尼的空气质量显著恶化。在此之后,澳大利亚实施了社会、流动和经济限制措施,以遏制 COVID-19 疫情的传播。我们使用气象归一化方法来量化维多利亚州和新南威尔士州东南部这两个截然不同时期的空气质量影响。随机森林 (RF) 机器学习算法用于根据 19 年的去趋势训练数据集计算二氧化氮 (NO)、臭氧 (O)、一氧化碳 (CO) 和直径<2.5μm 的颗粒物 (PM) 的基线时间序列。在维多利亚州各地,2020 年 1 月,基于 RF 预测的 CO(188%)、PM(322%)和臭氧(22%)大幅增加。在新南威尔士州,RF 预测之上的污染物增加幅度较小(CO58%、PM80%、臭氧 19%)。这在一定程度上可以解释为由于高温和强风速,RF 预测值高于前几个月的平均值,这突出了气象归一化在将污染变化归因于特定事件方面的重要性。根据每日观测值与 RF 预测值的差异,我们估计维多利亚州和新南威尔士州 PM 和 O 暴露导致 249.8(95%CI:156.6-343)例超额死亡和 3490.0(95%CI 1325.9-5653.5)例额外住院治疗。2019 年 4 月,当 COVID-19 限制措施生效时,维多利亚州和新南威尔士州的 NO 平均分别下降了 21.5%和 8%。在维多利亚州,O 和 PM 平均基本保持不变,但在新南威尔士州,它们分别增加了 20%和 24%,这支持了这样一种说法,即与新南威尔士州相比,维多利亚州的社区流动性下降幅度更大。总的来说,COVID-19 封锁期间空气质量的变化对计算出的健康结果几乎没有影响。