Dispersion Normalized PMF Provides Insights into the Significant Changes in Source Contributions to PM<sub>2.5</sub> after the COVID-19 Outbreak

Dai, Qili; Liu, Baoshuang; Bi, Xinhui; Wu, Jianhui; Liang, Danni; Zhang, Yufen; Feng, Yinchang; Hopke, Philip K.

doi:10.1021/acs.est.0c02776

Cited by 173 publications

(110 citation statements)

References 50 publications

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“…Brazil: (Dantas et al, 2020;Krecl et al, 2020;Nakada and Urban, 2020;Siciliano et al, 2020a) Other: (Mendez-Espinosa et al, 2020;Pacheco et al, 2020;Zalakeviciute et al, 2020;Zambrano-Monserrate and Ruano, 2020) Europe Multiple countries: (Baldasano, 2020;Collivignarelli et al, 2020;Filippini et al, 2020;Gautam, 2020a;Giani et al, 2020;Gualtieri et al, 2020;Higham et al, 2020;Ljubenkov et al, 2020;Sicard et al, 2020;Tobías et al, 2020;Martorell-Marugán et al, 2021) Oceania Australia: (Fu et al, 2020) New Zealand: (Patel et al, 2020) Africa Morocco: (Ass et al, 2020;Otmani et al, 2020) This includes the "discussed but not corrected" and "not discussed or corrected" categories in Figure 2. (Zheng et al, 2020), and Tianjin (Dai et al, 2020), China. Conventional PMF analysis may suffer from information loss due to nonlinear dilution variations.…”

Section: Southeast Asiamentioning

confidence: 99%

“…Conventional PMF analysis may suffer from information loss due to nonlinear dilution variations. Dai et al (2020) incorporated the ventilation coefficient into their dispersion-normalized PMF, which reduced the dilution effect. The advantages of using PMF were highlighted in all studies, and their findings supported the substantial contribution of secondary sources, as well as the influence of local primary sources, to PM pollution.…”

Section: Southeast Asiamentioning

confidence: 99%

“…By the literature cutoff time of this review (September 30, 2020), only a few studies had been published that investigated the effects of secondary chemistry and local primary emissions on PM levels and composition in China (Chang et al, 2020;Chen et al, 2020a;Cui et al, 2020;Dai et al, 2020;Sun et al, 2020;, Bangladesh (Masum and Pal, 2020), and South Africa (Williams et al, 2020). More studies will be essential to understand the complexity of PM 2.5 pollution.…”

Section: Observed Changes In Pm Compared With Estimates Based On the mentioning

confidence: 99%

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The global impacts of COVID-19 lockdowns on urban air pollution

Gkatzelis

Gilman

Brown

et al. 2021

Elementa: Science of the Anthropocene

137

154

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The coronavirus-19 (COVID-19) pandemic led to government interventions to limit the spread of the disease which are unprecedented in recent history; for example, stay at home orders led to sudden decreases in atmospheric emissions from the transportation sector. In this review article, the current understanding of the influence of emission reductions on atmospheric pollutant concentrations and air quality is summarized for nitrogen dioxide (NO2), particulate matter (PM2.5), ozone (O3), ammonia, sulfur dioxide, black carbon, volatile organic compounds, and carbon monoxide (CO). In the first 7 months following the onset of the pandemic, more than 200 papers were accepted by peer-reviewed journals utilizing observations from ground-based and satellite instruments. Only about one-third of this literature incorporates a specific method for meteorological correction or normalization for comparing data from the lockdown period with prior reference observations despite the importance of doing so on the interpretation of results. We use the government stringency index (SI) as an indicator for the severity of lockdown measures and show how key air pollutants change as the SI increases. The observed decrease of NO2 with increasing SI is in general agreement with emission inventories that account for the lockdown. Other compounds such as O3, PM2.5, and CO are also broadly covered. Due to the importance of atmospheric chemistry on O3 and PM2.5 concentrations, their responses may not be linear with respect to primary pollutants. At most sites, we found O3 increased, whereas PM2.5 decreased slightly, with increasing SI. Changes of other compounds are found to be understudied. We highlight future research needs for utilizing the emerging data sets as a preview of a future state of the atmosphere in a world with targeted permanent reductions of emissions. Finally, we emphasize the need to account for the effects of meteorology, emission trends, and atmospheric chemistry when determining the lockdown effects on pollutant concentrations.

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Section: Southeast Asiamentioning

confidence: 99%

Section: Southeast Asiamentioning

confidence: 99%

Section: Observed Changes In Pm Compared With Estimates Based On the mentioning

confidence: 99%

See 1 more Smart Citation

The global impacts of COVID-19 lockdowns on urban air pollution

Gkatzelis

Gilman

Brown

et al. 2021

Elementa: Science of the Anthropocene

137

154

View full text Add to dashboard Cite

show abstract

“…However, increased residential coal and biomass combustion also with spring festival emissions are also likely causes (Dai et al, 2020). Second, this study assumes similar meteorological conditions between 2020 and the previous years.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Global Air Quality and COVID-19 Pandemic: Do We Breathe Cleaner Air?

Torkmahalleh

Akhmetvaliyeva

Omran

et al. 2021

Aerosol Air Qual. Res.

Self Cite

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“…Investigating the PM oxidative potential (OP) in light of their major emission sources at various urban environments can then provide valuable information to instigate air pollution abatement policies limiting health outcomes. However, spatially-resolved PM source apportionment at a city-scale remains a challenging task (Dai et al, 2020b(Dai et al, , 2020aPandolfi et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Disparities in particulate matter (PM<sub>10</sub>) origins and oxidative potential at a city-scale (Grenoble, France) – Part I: Source apportionment at three neighbouring sites

Borlaza¹,

Weber²,

Uzu³

et al. 2020

Preprint

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Abstract. A fine-scale source apportionment of PM10 was conducted in three different urban sites (background, hyper-center, and peri-urban) within 15 km of the city in Grenoble, France using Positive Matrix Factorization (PMF 5.0) on measured chemical species from collected filters (24-hr) from February 2017 to March 2018. To improve the PMF solution, several new organic tracers (3-MBTCA, pinic acid, phthalic acid, MSA, and cellulose) were additionally used in order to identify sources that are commonly unresolved by classic PMF methodologies. An 11-factor solution was obtained in all sites including commonly identified sources from primary traffic, nitrate-rich, sulfate-rich, industrial, biomass burning, aged sea salt, sea/road salt, and mineral dust, and the newly found sources from primary biogenic, secondary biogenic oxidation, and MSA-rich. Generally, the chemical species exhibiting similar temporal trends and strong correlations showed uniformly distributed emission sources in the Grenoble basin. The improved PMF model was able to obtain and differentiate chemical profiles of specific sources even at high proximity of receptor locations confirming its applicability in a fine-scale resolution. In order to test the similarities between the PMF-resolved sources, the Pearson distance and standardized identity distance (PD-SID) of the factors in each site were compared. The PD-SID metric determined homogeneous sources (biomass burning, primary traffic, nitrate-rich, sulfate-rich, primary biogenic, MSA-rich, aged sea salt, and secondary biogenic oxidation) and heterogeneous sources (industrial, mineral dust, and sea/road salt) across different urban sites, thereby allowing to better discriminate localized characteristics of specific sources. Overall, the addition of the new tracers allowed the identification of substantial sources (especially in the SOA fraction) that would not have been identified or possibly mixed with other factors, resulting in an enhanced resolution and sound source profile of urban air quality at a city scale.

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Dispersion Normalized PMF Provides Insights into the Significant Changes in Source Contributions to PM_2.5 after the COVID-19 Outbreak

Cited by 173 publications

References 50 publications

The global impacts of COVID-19 lockdowns on urban air pollution

The global impacts of COVID-19 lockdowns on urban air pollution

Global Air Quality and COVID-19 Pandemic: Do We Breathe Cleaner Air?

Disparities in particulate matter (PM<sub>10</sub>) origins and oxidative potential at a city-scale (Grenoble, France) – Part I: Source apportionment at three neighbouring sites

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Dispersion Normalized PMF Provides Insights into the Significant Changes in Source Contributions to PM2.5 after the COVID-19 Outbreak

Cited by 173 publications

References 50 publications

The global impacts of COVID-19 lockdowns on urban air pollution

The global impacts of COVID-19 lockdowns on urban air pollution

Global Air Quality and COVID-19 Pandemic: Do We Breathe Cleaner Air?

Disparities in particulate matter (PM&lt;sub&gt;10&lt;/sub&gt;) origins and oxidative potential at a city-scale (Grenoble, France) – Part I: Source apportionment at three neighbouring sites

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Dispersion Normalized PMF Provides Insights into the Significant Changes in Source Contributions to PM_2.5 after the COVID-19 Outbreak

Disparities in particulate matter (PM<sub>10</sub>) origins and oxidative potential at a city-scale (Grenoble, France) – Part I: Source apportionment at three neighbouring sites