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Temperature inversion (TI) is one of the meteorological conditions that significantly affect regional air quality. Knowledge gap regarding the impacts of TI on surface PM 2.5 in different topographies still existed. In the present study, the occurrence frequency, temperature lapse rate (TLR), depth, and the diurnal variations of TI, surface-based TI (SBTI), elevated TI (ElTI), and multiple layers of TIs (MultiTI) and their impacts on near-surface PM 2.5 concentrations over eastern China that covers a range of topographies and climates, are systematically investigated based on global reanalysis ERA5 and the nationwide monitoring PM 2.5 dataset from 2014 to 2020. TIs occurred mostly in the early morning. Different types of TIs present distinctive seasonal and spatial patterns. The majority of SBTIs and ElTIs occurred during nighttime in northern China and daytime in southern China, respectively, as the result of their formation mechanisms. SBTIs usually had larger TLR while ElTIs had deeper depth. SBTIs showed strong enhancement effects on PM 2.5 concentration over the study domain while ElTIs showed more obvious impacts on northern nocturnal PM 2.5. The peak time of PM 2.5 was found around 18:00-22:00 LST, and TLR and depth of TIs are thought to be more relevant to PM 2.5 peak concentration due to their coincident peak times. The strength of TIs is therefore more crucial in regulating PM 2.5 than its occurrence frequency. Based on statistical analysis, our study provided a large picture of the generic spatiotemporal patterns of TIs and illustrated the impacts of different TIs on surface PM 2.5 pollution on a diurnal basis. For a deeper understanding of the formation of PM 2.5 pollution, more attention needs to be paid to the nocturnal PM 2.5 not only at surface level but also at higher levels in the presence of TIs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The Comprehensive Air-quality Model with extensions (CAMx) was used to explore the sensitivity of PM 2.5 and O 3 concentrations to four selected meteorological factors: wind speed, temperature, water vapor mixing ratio (Q), and planetary boundary layer height (PBLH) during two pollution episodes over the North China Plain (NCP). We also investigated the impact pathways of different meteorological factors on the formation of PM 2.5 and O 3. It is found that PM 2.5 was more sensitive to the selected meteorological factors in the southeastern NCP, where high anthropogenic emissions and severe air pollution occur. Large variations were observed along the Taihang Mountains, where the height of the terrain changes dramatically. The sensitivity of O 3 to wind speed, PBLH, temperature, and Q was mainly determined by the inhibition effects of PM 2.5 in winter, while in summer, the complex chemical reactions were dominant. Significant diurnal variations of process analysis (PA) results were observed under various meteorological conditions. Higher temperature generally enhance heterogeneous chemistry and transport of NO 3 - through the top boundary layer during night-time in winter, however, in summer, the heterogeneous chemistry of NO 3 - and NH 4 + during daytime were the major pathways to the increased PM 2.5 due to increased temperature. Moreover, temperature alter PM 2.5 concentrations through affecting vertical diffusivity and relative humidity, and alter O 3 concentrations by affecting the gas phase chemistry and mass fluxes through the top boundary layer. Q mainly affects the rate of chemical reactions of PM 2.5 and O 3 . The different impact pathways suggest that it is essential to consider variations in meteorological factors, in addition to the direct impacts of wind speed and PBLH, more attention should be paid to the complex impacts of temperature and Q, when developing emission control strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Air pollution is the result of enormous emissions and unfavorable meteorological conditions. The role of meteorology, particularly extremely unfavorable meteorological events (EUMEs), in processing atmospheric PM 2.5 pollution has not been fully addressed. This work examined the variations of PM 2.5 mass and its chemical components associated with various meteorological parameters and three EUMEs based on meteorological observations and analysis combined with one-year long in situ measurement in 2018 in the suburban area of Tianjin, China. Analysis shows that the polluted days in 2018 were mostly related to the increase in sulfate, nitrate, and ammonium (SNA). Temperature between -2 to 13 °C is more favorable for the formation of SNA, while high temperature exceeding 28 °C is favorable for the formation of organic carbon and sulfate. Most of the ions and carbon components showed significant increase in concentrations when relative humidity exceeded 80%. The maximum decreasing rate of PM 2.5 concentrations due to increase in wind speed and planetary boundary height could be 15.35 μg m -3 (m s -1 ) -1 , and 34.37 μg m -3 (100 m) -1 , respectively. EUMEs showed significant impacts on PM 2.5 components, in which PM 2.5 concentrations showed the most significant increase under temperature inversion (TI) events, and surface-based TI (SBTI) events usually have much stronger impacts on PM 2.5 concentrations than elevated TI (ELTI). Nitrate was found to be the most sensitive component to EUMEs, especially under multiple EUMEs. The synthetic effects of multiple EUMEs could result in an increase of nitrate by 35.53 μg m -3 (523.3%). In addition, OC and sulfate are more sensitive to heat wave events. Our analysis provides improved understanding of the formation of PM 2.5 pollution with respect to meteorology, particularly EUMEs. Based on such information, more attention may be needed on the collaborative prediction of EUMEs and air pollution episodes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Rotational ambiguity in factor analyses prevents users from obtaining accurate source apportionment results. The rotational space in positive matrix factorization (PMF) can be reduced by constraining the solution with a prioriinformation such as source profiles. However, the only prior report on constraints using information on the source contributions was their use to ensure compatibility in the simultaneous analyses of PM 2.5 and PM 10 data. By combining data from three monitoring sites affected by a gear casting plant in Xi'an as an example, a methodology for improving the accuracy of PMF results by constraining source contributions using wind information was explored. Seven common factors derived from individual PMF analyses for each of the three sites (INDUS, URBAN, and RURAL) with different location characteristics, were then combined in a multisite PMF analysis. The factors were interpreted as nitrate with all site average contributions of 28.7%, sulfate (22.5%), coal combustion (19.3%), road traffic (12.8%), biomass burning (6.4%), soil (5.4%), and metallurgical industry (4.9%). Except for the INDUS site, contributions of metallurgical industry to the URBAN and RURAL sites were pulled down maximally to reduce the rotational space. The constrained solution substantially improved the results over the base run. The local and regional nature of the sources were identified by coefficient of divergence combined with Pearson correlation analysis, and further quantitatively estimated using Lenschow approach. On average, local sources contributed for 52.4% and 47.7% of the PM 2.5 mass concentrations at the INDUS and URBAN site respectively. The metallurgical industry showed the highest local contributions while sulfate was primarily regional. For the multisite analysis where there are considerable point source emissions, this methodology highlights the role of local wind directions to inform constraints on the results and obtaining more reliable solutions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)