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Understanding the effectiveness of long-term air pollution regulatory measures is important for control policy formulation. Efforts have been made using chemical transport modelling and statistical approaches to evaluate the efficacy of the Clean Air Action Plan (CAAP; 2013–2017) and the Blue Sky Protection Campaign (BSPC; 2018–2020) enacted in China. Changes in air quality due to reduction in emissions can be masked by meteorology, making it highly challenging to reveal the real effects of control measures. A knowledge gap still existed with respect to how sources changed before and after the CAAP and BSPC were implemented, respectively, particularly in coastal areas where anthropogenic emissions mixed with additional natural sources (e.g. marine aerosol). This work applied a machine-learning-based meteorological normalization approach to decouple the meteorological effects from air quality trend in a coastal city in northern China (Qingdao). Secondly, the relative changes in source contributions to ambient PM2.5 with a ∼ 10-year observation interval (2011–2012, 2016, and 2019) were also investigated. We discovered that the largest emission reduction section was likely from coal combustion as the meteorologically normalized SO2 dropped by ∼ 15.5 %yr-1 , and the annual average dispersion-normalized SO42- decreased by ∼ 41.5 %. Change in the meteorologically normalized NO2 was relatively stable (∼ 1.0 %yr-1), and NO3- changed inappreciably in 2016–2019 but was significantly higher than that prior to the CAAP. Crustal dust decreased remarkably after the CAAP began. Industrial emissions, for example, steel-related smelting, decreased after 2016 due to the relocation of steel-making enterprises. Note that vehicle emissions were increased in importance as opposed to the other primary sources. Similar to other megacities, Qingdao is also at risk of increased ozone pollution that in turn facilitates secondary-particle formation in the future. The policy assessment approaches applied in this work also work for other places where air quality management is highly in demand to reduce air pollution. [ABSTRACT FROM AUTHOR]

Samples of ambient PM 2.5 were collected in the Qingdao harbor area between 21 March and May 25, 2016, and analyzed to investigate the compositions and sources of PM 2.5 and to assess source-specific selected toxic element health risks to workers via a combination of positive matrix factorization (PMF) and health risk (HR) assessment models. The mean concentration of PM 2.5 in harbor area was 48 μg m−3 with organic matter (OM) dominating its mass. Zn and V concentrations were significantly higher than the other selected toxic elements. The hazard index (HI) and cancer risk (R i) of all selected toxic elements were lower than the United States Environmental Protection Agency (USEPA) limits. There were no non-cancer and cancer risks for workers in harbor area. The contributions from industrial emissions (IE), ship emissions (SE), vehicle emissions (VE), and crustal dust and coal combustion (CDCC) to selected toxic elements were 39.0%, 12.8%, 24.0%, and 23.0%, respectively. The HI values of selected toxic elements from IE, CDCC, SE, and VE were 1.85 × 10−1, 7.08 × 10−2, 6.36 × 10−2, and 3.37 × 10−2, respectively; these are lower than the USEPA limits. The total cancer risk (R t) value from selected toxic elements in CDCC was 2.04 × 10−7, followed by IE (6.40 × 10−8), SE (2.26 × 10−8), and VE (2.18 × 10−8). CDCC and IE were the likely sources of cancer risk in harbor area. The Bo Sea and coast were identified as the likely source areas for health risks from IE via potential source contribution function (PSCF) analysis based on the results of PMF-HR modelling. Although the source-specific health risks were below the recommended limit values, this work illustrates how toxic species in PM 2.5 health risks can be associated with sources such that control measures could be undertaken if the risks warranted it. Image 1 • Positive matrix factorization and health risk assessment model were combined for identifying risk sources. • Non-cancer and cancer risks for workers were not found in the Qingdao harbor area. • Crustal dust and coal combustion and industrial emissions were potential health-risk sources. • Bo Sea coast was the major source -area for health risks from industrial emissions. [ABSTRACT FROM AUTHOR]

Conventional source apportionments of ambient volatile organic compounds (VOCs) have been based on observed and initial concentrations after photochemical correction. However, these results have not been related to ozone (O 3) and secondary organic aerosol (SOA) formation. Thus, the apportioned contributions could not effectively support secondary pollution control development. Source apportionment of the VOCs consumed in forming O 3 and SOA is needed. A consumed VOC source apportionment approach was developed and applied to hourly speciated VOCs data from June to August 2022 measured in Laoshan, Qingdao. Biogenic emissions (56.3%), vehicle emissions (17.2%), and gasoline evaporation (9.37%) were the main sources of consumed VOCs. High consumed VOCs from biogenic emissions mainly occurred during transport from parks to the southwest and northwest of study site. During the O 3 pollution period, biogenic emissions (46.3%), vehicle emissions (24.2%), and gasoline evaporation (14.3%) provided the largest contributions to the consumed VOCs. However, biogenic emissions contribution increased to 57.1% during the non-O 3 pollution period, and vehicle emissions and gasoline evaporation decreased to 16.5% and 9.01%, respectively. Biogenic emissions and the mixed source of combustion sources and solvent use contributed the most to O 3 and SOA formation potentials during the O 3 pollution period, respectively. [Display omitted] • A consumed VOC source apportionment approach was developed. • Alkenes contributed 93.3% to the total VOCs photochemical loss. • Photochemical losses could lead to the loss of the impact of some key sources. • Biogenic and vehicle emissions were the main contributors to the consumed VOCs. [ABSTRACT FROM AUTHOR]