The air quality of Handan, a typical industrial city in China, has been significantly improved through atmospheric pollution control, except for ozone (O₃) pollution. We found that, in summer, emissions of anthropogenic volatile organic compounds (VOCs) and NO_x decreased yearly in Handan, but the O₃ concentration significantly declined yearly during 2013–2015, whereas it experienced worsening O₃ pollution after 2015. Therefore, we used the Weather Research and Forecasting Community Multiscale Air Quality (WRF–CMAQ) modeling system to simulate the influence of the meteorological conditions and emission changes in Handan during the typical period (June) of O₃ pollution in 2013–2018. For benchmarked June 2013, the results showed that the reduction of the O₃ concentration in June of 2014–2016 was mainly caused by emission reduction, while in June of 2017–2018, the combined effect of changes in emissions and meteorological conditions led to aggravated O₃ pollution. Sensitivity analysis indicated that combined VOCs and NO_x emission controls would effectively reduce incremental O₃ formation when the abatement ratio of VOCs/NO_x should be no less than 0.84, and we found that VOCs reduction would continusouly bring about O₃ decreases under various NO_x reductions, but its positive sensitivity to O₃ would become smaller with NO_x reduction. However, the positive influence of NO_x reduction on O₃ would happen until NO_x reduction exceeding 45–60%. The findings will be helpful in formulating emission control strategies for coping with O₃ pollution in an industrial city.

Under the Air Pollution Prevention and Control Action Plan (APPCAP) implemented, China has witnessed an air quality change during the past five years, yet the main influence factors remain relatively unexplored. Taking the Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) regions as typical cluster cities, the Weather Research Forecasting (WRF) and Comprehensive Air Quality Model with Extension (CAMx) were introduced to demonstrate the meteorological and emission contribution and PM_2.5 flux distribution. The results showed that the PM_2.5 concentration in BTH and YRD significantly declined with a descend ratio of −39.6% and −28.1%, respectively. For the meteorological contribution, those regions had a similar tendency with unfavorable conditions in 2013–2015 (contribution concentration 1.6–3.8 μg/m³ and 1.1–3.6 μg/m³) and favorable in 2016 (contribution concentration −1.5 μg/m³ and −0.2 μg/m³). Further, the absolute value of the net flux’s intensity was positively correlated with the degree of the favorable/unfavorable weather conditions. When it came to emission intensity, the total net inflow flux increased, and the outflow flux decreased significantly across the border with the emission increasing. In short: the aforementioned results confirmed the effectiveness of the regional joint emission control and provided scientific support for the proposed effective joint control measures.

In this study, based on the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data, the reliability and performances of their application on clean days and polluted days (based on the PM_2.5 mass concentrations) in Beijing were assessed. Conventional meteorological factors and diagnostic physical quantities from the NCEP/FNL data were compared with the L-band radar observations in Beijing in the autumns and winters of 2017–2019. The results indicate that the prediction reliability of the temperature was the best compared with those of the relative humidity and wind speed. It is worth noting that the relative humidity was lower and the near-surface wind speed was higher on polluted days from the NCEP/FNL data than from the observations. As far as diagnostic physical quantity is concerned, it was revealed that the temperature inversion intensity depicted by the NCEP/FNL data was significantly lower than that from the observations, especially on polluted days. For example, the difference in the temperature inversion intensity between the NCEP/FNL data and the observation ranged from −0.56 to −0.77 °C on polluted days. In addition, the difference in the wind shears between the NCEP/FNL reanalysis data and the observations increased to 0.40 m/s in the lower boundary layer on polluted days compared with that on clean days. Therefore, it is suggested that the underestimation of the relative humidity and temperature inversion intensity, and the overestimation of the near-surface wind speed should be seriously considered in simulating the air quality in the model, particularly on polluted days, which should be focused on more in future model developments.