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Metals have been constantly introduced to urban environments via various point and non-point sources of pollution, and have contaminated different urban compartments (sample types). However, most research projects have focused on a single environmental compartment to characterize urban metal contamination. In the present study, an integrated sampling program that includes surface soils, different size fractions of soil and road dust (<50 μm, 50-100 μm, 100-250 μm, and 250-1000 μm), tree leaves, and grasses, was conducted in a typical urban area of Guangzhou, China. The aim of the study was to investigate the interrelationships among the metal pollutants in these samples. The concentrations of trace metals varied greatly among different sample types, and their distribution was generally in the following order: road dust > soil dust ≥ surface soils ≈ top soils > grasses ≥ tree leaves. As for the relationships among the trace metals, different combinations were seen among the sample types, indicating different loadings of trace metals in the sampling medium. Significant correlations of metal concentrations were found between tree leaves and the smallest (<50 μm) fraction of road dust, and between soil dust (50-100 μm) and surface soils, suggesting that trace metals in these samples may influence each other. urban environment, trace metals, soil, dust, tree leaf, grass Citation:Bi X Y, Liang S Y, Li X D. Trace metals in soil, dust, and tree leaves of the urban environment,

Gasoline evaporation is a potential source of ambient non-methane hydrocarbons (NMHCs) during summer, and thus the policy of encouraging vehicles to refuel at night has been implemented to control ground-level ozone (O3) and NMHCs. In this study, NMHCs and trace gases were observed online at an urban site of Ji’nan during May–July in 2019 and 2020 to assess the impact of this policy. After the implementation of this policy, the average concentration of daily maximum 8 h moving average O3 decreased from 198 μg/m3 to 181 μg/m3. Meanwhile, the average mixing ratio of NMHCs decreased from 19.89 ppbv to 18.02 ppbv. Sources of NMHCs were then apportioned using the positive matrix factorization model. Four factors were resolved and identified, including vehicle exhaust, paint and solvents usage, gasoline evaporation, and biogenic emission. Relative contributions of these four sources were 52.5%, 20.6%, 18.3%, and 8.6%, respectively. After the implementation of this policy, relative contributions of gasoline evaporation in 1:00–4:00 increased from 20.2–22.7% to 25.4–28.2%, while those for 16:00–18:00 decreased from 16.8–18.7% to 13.9–15.7%. The non-linear relationship of O3 with NMHCs and NOx was investigated using a box model based on observations. Results suggest that O3 production was mainly controlled by NMHCs. Aromatics and alkenes were the key NMHC species in O3 formation. Furthermore, two scenarios of encouraging vehicles to refuel at night were designed to evaluate their impact on O3. The relative decreases of O3 peak concentrations were lower than 1%, indicating that this policy had a limited impact on O3 during the observation period.

In recent years, ozone (O3) pollution has worsened in China and contributes frequently to air pollution problems. To support the implementation of coordinated control for ozone and fine particulate matter, it is essential to study the chemical compositions and sources of volatile organic compounds (VOCs), which are the crucial precursor of both ozone and fine particulate matter. In this study, 117 volatile organic compounds were monitored in 13 cities in Beijing-Tianjin-Hebei Urban Agglomeration and Fenwei plain. Concentrations of total volatile organic compounds ranged from 42 to 279 μg/m3 during the monitoring episode. In all 13 cities, alkanes, halogenated hydrocarbons, aromatics and oxygenated volatile organic compounds (OVOCs) were the dominant volatile organic compounds. Contributions of alkanes, halogenated hydrocarbons, aromatics and oxygenated volatile organic compounds to total ozone formation potential (OFP) were 21.7%–32.6%, 21.0%–27.9%, 24.3%–50.8% and 28.6%–52.3%, respectively. Furthermore, the results of source apportionment by positive matrix factorization (PMF) model indicated that solvent usage, gasoline evaporation, vehicle emissions, petrochemical industry and combustion were essential volatile organic compounds sources in 13 cities. Moreover, the sensitivity of ozone production was studied using an Empirical Kinetic Modeling Approach (EKMA) model, and it was found that ozone formation was volatile organic compounds limited in all 13 cities.

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