Unexpected Increases of Severe Haze Pollution During the Post COVID‐19 Period: Effects of Emissions, Meteorology, and Secondary Production

Zhou, Wei; Lu, Ling; Du, Aodong; Zhang, Zhiqiang; Li, Yan; Yang, Yang; Tang, Guiqian; Chen, Chun; Xu, Weiqi; Sun, Jiaxing; Li, Zhijie; Fu, Pingqing; Wang, Zifa; Sun, Yele

doi:10.1029/2021jd035710

Cited by 25 publications

(8 citation statements)

References 65 publications

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“…The results suggest that the conversion efficiency of secondary aerosols was highest during stage 3 under the most serious pollution, which is consistent with the results of other studies of heavy haze (Huang et al, 2014;Zhou et al, 2022;Shang et al, 2021).…”

Section: Temporal Variation Of the Qda Results In Different Stagessupporting

confidence: 92%

A quantitative decoupling analysis (QDA v1.0) method for assessing the contributions of meteorology, emissions, and chemistry to fine particulate pollution

Wang

Chen

et al. 2023

Preprint

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Abstract. A comprehensive understanding of the effects of meteorology, emissions, and chemistry on severe haze is critical in the mitigation of air pollution. However, such an understanding is greatly hindered by the nonlinearity of atmospheric systems. In this study, we developed the quantitative decoupling analysis (QDA) method to quantify the effects of emissions, meteorology, chemical reactions, and their nonlinear interactions on fine particulate matter (PM2.5) pollution by running built-in scenario simulations in each model step. Different from previous methods, the QDA method achieves a fully decomposed analysis of hourly changes in the PM2.5 concentration during pollution events into seven parts, including the pure meteorological contribution (M), the pure emissions contribution (E), the pure chemistry contribution (C), and the interactions among these processes (i.e., ME, MC, EC, and MCE). Via embedding the QDA method into the Weather Research and Forecasting–Nested Air Quality Prediction Modeling System, we employed this method and combined it with the Integrated Process Rate method to study a typical heavy haze episode in Beijing. We evaluate the model performance against in situ meteorological and air quality observations and describe the QDA analytical factors of this case. Results showed that M varied most significantly at different stages of the episode, from 0.21 µg⋅m−3⋅h−1 during the accumulation stage to −11.82 µg⋅m−3⋅h−1 during the removal stage, indicating that the pure meteorological contribution dominated the hourly fluctuation amplitude of the PM2.5 concentration. M acted as the most important cleaner for PM2.5 in non-polluting periods but stopped being effective at this and instead became a contributor in the accumulation stage such that PM2.5 tended to grow rapidly under the superimposed influence of emissions and chemical processes, which would probably mark the beginning of a heavy pollution event. The contribution of E ranged from 0.63 to 0.88 µg⋅m−3⋅h−1 owing to the diurnal variation of emissions. The pure chemical contribution was shown to increase with the level of haze, becoming the largest (0.37 µg⋅m−3⋅h−1) in the maintenance period, which was 25 % higher than during the pre-contamination period. And C+CE made a significant contribution in the accumulation and maintenance stages, indicating that chemical reactions are more important in the polluted period than in other periods. Nonnegligible nonlinear effects exist among the processes of meteorology, emissions, and chemistry on PM2.5 concentrations (−1.83 to 2.44 µg⋅m−3⋅h−1) – something that has generally been ignored in previous studies and during the development of heavy-pollution control strategies. The nonlinear effects are helpful in eliminating the interference of other processes and obtaining a more purified result of the target process and have important indicative significances. The ratio of CE to C is positively correlated with the chemical speed. For precursors like NH3, the smaller value of CE in the most polluted period indicated that NH3 was more deficient, and thus reducing emissions of it in that period would have had the most efficient controlling effect on the PM2.5. This study highlights that the QDA method can be used to realize an in-depth understanding of the effects of adverse meteorological conditions in haze and to judge whether the precursors are excessive or not. Not only can the QDA method provide researchers and policymakers with valuable information for understanding the key factors behind heavy pollution, but it can also help modelers to identify the sources of uncertainties in numerical models.

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Section: Temporal Variation Of the Qda Results In Different Stagessupporting

confidence: 92%

A quantitative decoupling analysis (QDA v1.0) method for assessing the contributions of meteorology, emissions, and chemistry to fine particulate pollution

Wang

Chen

et al. 2023

Preprint

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“…The variations of aerosol species can be affected by the changes of both meteorological conditions and emissions. − As a result, chemical transport models are often used to estimate the relative impacts of meteorology and emissions from different sources by performing controlled simulations. For example, Zhou et al found that the decreases in OA and sulfate in cold season from 2013 to 2017 were mainly due to the emission reductions, while the changes in nitrate were mainly caused by meteorological variations.…”

Section: Introductionmentioning

confidence: 99%

Significant Reductions in Secondary Aerosols after the Three-Year Action Plan in Beijing Summer

Li,

Lei,

Sun

et al. 2023

Environ. Sci. Technol.

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Air quality in China has continuously improved during the Three-Year Action Plan (2018−2020); however, the changes in aerosol composition, properties, and sources in Beijing summer remain poorly understood. Here, we conducted real-time measurements of aerosol composition in five summers from 2018 to 2022 along with WRF-Community Multiscale Air Quality simulations to characterize the changes in aerosol chemistry and the roles of meteorology and emission reductions. Largely different from winter, secondary inorganic aerosol and photochemicalrelated secondary organic aerosol (SOA) showed significant decreases by 55−67% in summer, and the most decreases occurred in 2021. Comparatively, the decreases in the primary aerosol species and gaseous precursors were comparably small. While decreased atmospheric oxidation capacity as indicated by ozone changes played an important role in changing SOA composition, the large decrease in aerosol liquid water and small increase in particle acidity were critical for nitrate changes by decreasing gas-particle partitioning substantially (∼28%). Analysis of meteorological influences demonstrated clear and similar transitions in aerosol composition and formation mechanisms at a relative humidity of 50−60% in five summers. Model simulations revealed that emission controls played the decisive role in reducing sulfate, primary OA, and anthropogenic SOA during the Three-Year Action Plan, while meteorology affected more nitrate and biogenic SOA.

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“…Non-refractory submicron aerosol (NR-PM 1 ) species, including organics (Org), sulfate (SO 4 ), nitrate (NO 3 ), ammonium (NH 4 ) and chloride (Chl) were measured in the V-mode at a time resolution of 1 min. In addition, the NR-PM 2.5 species were measured by a CV-ACSM operated in parallel at a time resolution of 2 min, which was detailed in Zhou et al (2022) . SO 2 , O 3 , CO and NO x concentrations were measured by a suite of gas analyzers (models 43i, 49i, 48i and 42i, respectively, Thermo Scientific).…”

Section: Methodsmentioning

confidence: 99%

Changes in primary and secondary aerosols during a controlled Chinese New Year

Zhou

et al. 2022

Environmental Pollution

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Unexpected Increases of Severe Haze Pollution During the Post COVID‐19 Period: Effects of Emissions, Meteorology, and Secondary Production

Cited by 25 publications

References 65 publications

A quantitative decoupling analysis (QDA v1.0) method for assessing the contributions of meteorology, emissions, and chemistry to fine particulate pollution

A quantitative decoupling analysis (QDA v1.0) method for assessing the contributions of meteorology, emissions, and chemistry to fine particulate pollution

Significant Reductions in Secondary Aerosols after the Three-Year Action Plan in Beijing Summer

Changes in primary and secondary aerosols during a controlled Chinese New Year

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