Surface ozone trends and related mortality across the climate regions of the contiguous United States during the most recent climate period, 1991–2020

Mousavinezhad, Seyedali; Ghahremanloo, Masoud; Choi, Yunsoo; Pouyaei, Arman; Khorshidian, Nima; Sadeghi, Bavand

doi:10.1016/j.atmosenv.2023.119693

Cited by 8 publications

(2 citation statements)

References 101 publications

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“…Vehicular non‐exhaust particulate matter contains chemicals including polycyclic aromatic hydrocarbons (PAHs), heavy metals and emerging pollutants (EPs) which enhance the health impacts in animals and humans where they are deposited (Mousavinezhad et al., 2024; Niu et al., 2024; O'Sharkey et al., 2024; OECD, 2020; Wagner et al., 2024; WHO, 2021). Evidence shows that non‐exhaust poses more challenges to air quality than exhaust, but our understanding of it lags.…”

Section: Introductionmentioning

confidence: 99%

Real‐World Vehicular Source Indicators for Exhaust and Non‐Exhaust Contribution to PM_2.5 During Peak and Off‐Peak Hours Using Tunnel Measurement

Fang,

Fu,

Gao

et al. 2024

JGR Atmospheres

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The benefit of real‐world applicable indicators in resolving robust traffic‐related source contributions was investigated using tunnel measurement. PM2.5/CO was introduced as a metric to present evidence in non‐exhaust identification indirectly in terms of PM2.5 accumulation and dilution scenarios, and the rates (hourly variation of the difference between PM2.5 and PM2.5/CO) were 0.59−1.88 and −0.79 to −0.65, corresponding to peak and off‐peak hours, respectively. Real‐world PAHs indicators were examined, among which the exhaust indicators showed stable applicability from BghiP, and the non‐exhaust indication noted by BkF and DahA in peak hours were largely weakened in off‐peak hours, showing noticeable profile mixing between exhaust, brake and tyre wear. Source contributions were resolved by principal component analysis (PCA) with support of linear discriminant analysis (LDA) on inter‐group centroid diagnosis. The rate of vehicular non‐exhaust (brake and tyre wear) contribution lifted 10.3 times in peak hours compared with off‐peak hours, and its emission factor was noticeably enhanced 16 times, from 0.03 mg/(km·veh) to 0.48 mg/(km·veh). Guided by global vehicle electrification, the contribution of non‐exhaust in vehicular emissions were estimated to increase with larger ratio of emission factor between non‐exhaust and exhaust, and the growing market share of electric vehicles, under each mode of regenerative braking. The monetary impact of non‐exhaust caused by electric vehicles was calculated reaching the exhaust when electric vehicles increase to 50% in busy commuting megacities. The results provide applicable indicators for accurate source apportionment and support data for the refined control of non‐exhaust emission under rapid vehicle electrification.

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Section: Introductionmentioning

confidence: 99%

Real‐World Vehicular Source Indicators for Exhaust and Non‐Exhaust Contribution to PM_2.5 During Peak and Off‐Peak Hours Using Tunnel Measurement

Fang,

Fu,

Gao

et al. 2024

JGR Atmospheres

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“…S1) [14]. Tropospheric ozone can cause climate warming, and aerosols absorb and scatter shortwave and longwave radiation, affecting cloud radiation characteristics and precipitation characteristics, thus leading to climate change [15,16]. While climate change (such as wind speed, temperature, and rainfall) alters the transport of atmospheric pollutants, chemical reaction rates of secondary pollutants, and wet removal of aerosols by precipitation [17].…”

Section: Graphical Abstract 1 Introductionmentioning

confidence: 99%

Variation characteristics and coordinated emission reduction of air pollutants in megacity of Chengdu-Chongqing economic circle under dual carbon goal

Li,

Abdullah,

Sobri

et al. 2023

Environmental Engineering Research

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The air pollution process and impact mechanism of megacities located in complex terrain are particularly complex. As a typical megacity in China, Chengdu has unique topographical and meteorological conditions, and its pollution control is difficult. This study systematically elucidated the variation characteristics of six criteria air pollutants in Chengdu between 2014 and 2020. Besides, the PM2.5/PM10 and NO2/SO2 ratios were discussed. Furthermore, a detailed analysis of the correlation between air pollutants was carried out. Finally, the collaborative path of carbon reduction and air pollution control is discussed. The results indicated that SO2, PM2.5, PM10 and CO were significantly decreased by 62.9%, 50.8%, 45.5%, and 36.7%, respectively. PM2.5 and O3 compliance rates are very low, and O3 increases with fluctuations. SO2, NO2, CO, PM showed a “U-shaped” seasonal variation, and there was a “seesaw” phenomenon between O3 and PM2.5. The continuous changing trends also found in the ratios of PM2.5/PM10 and NO2/SO2. The results highlight the importance of coordinated reduction of carbon emissions and pollutants in Chengdu. This research can improve the prediction accuracy of air pollution in complex terrain areas under global warming, and improve the understanding of the formation mechanism of air pollution in special terrains around the world.

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Deep-BCSI: A deep learning-based framework for bias correction and spatial imputation of PM2.5 concentrations in South Korea

Singh,

Choi,

Park

et al. 2024

Atmospheric Research

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Surface ozone trends and related mortality across the climate regions of the contiguous United States during the most recent climate period, 1991–2020

Cited by 8 publications

References 101 publications

Real‐World Vehicular Source Indicators for Exhaust and Non‐Exhaust Contribution to PM_2.5 During Peak and Off‐Peak Hours Using Tunnel Measurement

Real‐World Vehicular Source Indicators for Exhaust and Non‐Exhaust Contribution to PM_2.5 During Peak and Off‐Peak Hours Using Tunnel Measurement

Variation characteristics and coordinated emission reduction of air pollutants in megacity of Chengdu-Chongqing economic circle under dual carbon goal

Deep-BCSI: A deep learning-based framework for bias correction and spatial imputation of PM2.5 concentrations in South Korea

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Surface ozone trends and related mortality across the climate regions of the contiguous United States during the most recent climate period, 1991–2020

Cited by 8 publications

References 101 publications

Real‐World Vehicular Source Indicators for Exhaust and Non‐Exhaust Contribution to PM2.5 During Peak and Off‐Peak Hours Using Tunnel Measurement

Real‐World Vehicular Source Indicators for Exhaust and Non‐Exhaust Contribution to PM2.5 During Peak and Off‐Peak Hours Using Tunnel Measurement

Variation characteristics and coordinated emission reduction of air pollutants in megacity of Chengdu-Chongqing economic circle under dual carbon goal

Deep-BCSI: A deep learning-based framework for bias correction and spatial imputation of PM2.5 concentrations in South Korea

Contact Info

Product

Resources

About

Real‐World Vehicular Source Indicators for Exhaust and Non‐Exhaust Contribution to PM_2.5 During Peak and Off‐Peak Hours Using Tunnel Measurement

Real‐World Vehicular Source Indicators for Exhaust and Non‐Exhaust Contribution to PM_2.5 During Peak and Off‐Peak Hours Using Tunnel Measurement