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As air quality has improved rapidly in recent years, the public has become more interested in whether a famous snow peak, Yaomei Feng on the Tibetan Plateau, can be seen from Chengdu, a megacity located on the western plain of the Sichuan Basin, east of the plateau. Therefore, a threshold-method-based forecasting system for snow peak sighting was developed in this study. Variables from numerical models, including cloud–water mixing ratio, cloud cover over snow peak, water mixing ratio, PM2.5 concentration, and ground solar radiation, were used in the snow peak sighting forecast system. Terrain occlusion rate of each model grid was calculated. Monte Carlo simulations were applied for threshold determination. A WRF-CMAQ hindcast was conducted for 2020, owing to insufficient observation data, hindcast results on the snow peak sighting were compared with posts collected from social media. Estimations showed that the snow peak sighting forecast system performed well in reflecting the monthly trend of snow peak sightings, and the hindcast results matched the daily observations, especially from May to August. Accuracy of the snow peak sighting forecast model was 78.9%, recall value was 57.1%, and precision was 24.4%.

As a major gaseous pollutant, ozone (O3) adversely affects human health and ecosystems. In recent years, ozone pollution in China has gradually become a prominent issue, especially in the North China Plain (NCP). To study the long-term spatio-temporal variation patterns of O3 in the NCP, this study selected 230 monitoring stations in the NCP from 2016 to 2020 as research objects, used the Kriging interpolation method and global Moran’s index to discuss the spatial-temporal distribution of O3, combining meteorological and social statistical data to analyze the causes underlying regional differences. The temporal analysis demonstrated that the O3-8h average concentrations increased annually from 2016 to 2018 and decreased from 2019 to 2020. The O3 concentrations were higher in spring and summer (117.89–154.20 μg/m3) and lower in autumn and winter (53.81–92.95 μg/m3). The spatial analysis revealed that O3 concentrations were low in the north and south of the NCP but high in the central area. The spatial distribution of O3 exhibited considerable cross-seasonal variability. Both meteorological conditions of high temperature and low pressure increased O3 concentrations. The spatial distribution of O3 varied depending on the period. However, the central and western regions of the Shandong Province were constantly characterized by high O3 concentrations. This pattern has been likely formed by heavy industry in the Shandong Province, as large-scale industrial production and frequent traffic flows produce a large amount of precursors, thereby exacerbating regional O3 pollution. These characteristics were attributed to emission reduction policies, meteorological conditions, the emission intensity of anthropogenic sources, and regional transport in the NCP. Overall, for cities with heavy industrial facilities in the central NCP, a timely adjustment of the energy and industrial structure, effectively controlling the emission of precursors, promoting new clean energy, and strengthening regional joint prevention and control are effective ways to alleviate O3 pollution.

With the continuous progress of air pollution prevention and control in China, the study of the emission characteristics of vehicles has become increasingly important. An in situ experiment was performed in the Tianfu tunnel in Chengdu to determine the vehicle emissions of volatile organic compounds (VOCs). A total of 50 species of VOCs were quantified in the tunnel, with total concentrations in the range of 32.25–162.18 ppbv in the entrance and 52.90–233.92 ppbv in the exit, respectively. Alkanes were the most abundant group, followed by alkenes, aromatic hydrocarbons, oxygenated VOCs, alkynes and chlorocarbons. The general emission factors of the measured VOCs ranged from 141.71 mg veh−1 km−1 to 236.12 mg veh−1 km−1, and the average ± std was 177.31 ± 24.59 mg veh−1 km−1. The emission factors of diesel-fuelled vehicles, gasoline-fuelled vehicles and natural gas-fuelled vehicles were estimated based on linear regression analysis, with values of 272.39 ± 191.17 mg veh−1 km−1, 185.08 ± 12.85 mg veh−1 km−1 and 158.72 ± 3.21 mg veh−1 km−1, respectively. The results of roadside experiments indicate that the roadside ambience atmosphere contains many species characterized with vehicle emission features. Especially, there were fuel evaporation emission related substances, which were higher in content than tunnel samples.