The recent severe and frequent PM2.5 (i.e., fine particles smaller than 2.5 µm) pollution in China has aroused unprecedented public concern. The first two years of PM2.5 measurements in China are reported and compared with those of Europe and the United States. The average PM2.5 concentration in China is approximately 5 times that over Europe and America. The contribution of atmospheric dispersion to such air quality is evaluated in this study. Air stagnation or its absence is a good indicator of the atmosphere’s capability to disperse its pollutants, but the NOAA definition of an air stagnation event is found to not be applicable to China since it depends on vertical mixing that is weakened in China by the effects of terrain. To address this deficiency, a new threshold for air stagnation events is proposed that depends on the 10-m wind speed, boundary layer height, and occurrence of precipitation. This newly defined air stagnation closely tracks the day-to-day variation of PM2.5 concentrations. Such events are more frequent over China than over Europe and the United States during autumn and winter, especially over the Sichuan basin and Jing-Jin-Ji region of China. If China had the same frequency of air stagnation as the United States or Europe, 67% and 82% of its stations would improve their current air quality during autumn and winter (e.g., an average of 12% decrease in PM2.5 concentrations for the Jing-Jin-Ji region in wintertime). Its severe pollution and frequent air stagnation conditions make controls on emission less effective in China than elsewhere.

This study compared the diurnal and seasonal cycles of atmospheric and surface urban heat islands (UHIs) based on hourly air temperatures (T_a) collected at 65 out of 262 stations in Beijing and land surface temperature (T_s) derived from Moderate Resolution Imaging Spectroradiometer in the years 2013–2014. We found that the nighttime atmospheric and surface UHIs referenced to rural cropland stations exhibited significant seasonal cycles, with the highest in winter. However, the seasonal variations in the nighttime UHIs referenced to mountainous forest stations were negligible, because mountainous forests have a higher nighttime T_s in winter and a lower nighttime T_a in summer than rural croplands. Daytime surface UHIs showed strong seasonal cycles, with the highest in summer. The daytime atmospheric UHIs exhibited a similar but less seasonal cycle under clear‐sky conditions, which was not apparent under cloudy‐sky conditions. Atmospheric UHIs in urban parks were higher in daytime. Nighttime atmospheric UHIs are influenced by energy stored in urban materials during daytime and released during nighttime. The stronger anthropogenic heat release in winter causes atmospheric UHIs to increase with time during winter nights, but decrease with time during summer nights. The percentage of impervious surfaces is responsible for 49%–54% of the nighttime atmospheric UHI variability and 31%–38% of the daytime surface UHI variability. However, the nighttime surface UHI was nearly uncorrelated with the percentage of impervious surfaces around the urban stations.

Atmospheric visibility is often used as a proxy for ambient air quality. However, in addition to the concentrations of particulate matter, visibility is also affected by meteorological conditions. The relative contributions of PM_2.5 concentrations and meteorological conditions to visibility are not yet clear. In this study, the individual contributions of PM_2.5 concentrations and the relative humidity (RH) to the visibility are measured based on observations at 12 stations in Beijing. We find that visibility decreases quickly as PM_2.5 concentrations increase at clean condition and decreases slowly when PM_2.5 concentrations exceed 100 μg/m³. The visibility decreases linearly as PM_2.5 concentrations increase when PM_2.5 concentrations lower than 50 μg/m³; however, there tends to be an exponential relationship as PM_2.5 concentrations increase. The PM_2.5 concentrations can explain 50% of the variance in visibility in clean and high‐humidity environments, whereas this fraction decreases to 10–15% when the PM_2.5 concentrations exceed 200 μg/m³. In contrast, RH has little effect on visibility under dry conditions. When the RH exceeds 40%, atmospheric visibility tends to display an inversely proportional and exponential relationship with RH under polluted and clean conditions, respectively. Under high‐humidity and highly polluted conditions, up to 40% of the variance in visibility is associated with RH. The PM_2.5 concentrations dominate the variations in visibility under dry or low PM_2.5 concentrations, and the contributions of RH become increasingly important as PM_2.5 concentrations and humidity increase. The difference of aerosol types and weather conditions increase the uncertainties of correlation coefficients between visibility and PM_2.5/RH. This study emphasizes the atmospheric conditions when employing visibility as a proxy for air pollution.

Mixing layer height (h) is an important parameter for understanding the transport process in the troposphere, air pollution, weather and climate change. Many methods have been proposed to determine h by identifying the turning point of the radiosonde profile. However, substantial differences have been observed in the existing methods (e.g. the potential temperature (θ), relative humidity (RH), specific humidity (q) and atmospheric refractivity (N) methods). These differences are associated with the inconsistency of the temperature and humidity profiles in a boundary layer that is not well mixed, the changing measurability of the specific humidity and refractivity with height, the measurement error of humidity instruments within clouds, and the general existence of clouds. This study proposes a method to integrate the information of temperature, humidity and cloud to generate a consistent estimate of h. We apply this method to high vertical resolution (~ 30 m) radiosonde data that were collected at 79 stations over North America during the period from 1998 to 2008. The data are obtained from the Stratospheric Processes and their Role in Climate Data Center (SPARC). The results show good agreement with those from N method as the information of temperature and humidity contained in N; however, cloud effects that are included in our method increased the reliability of our estimated h. From 1988 to 2008, the climatological h over North America was 1675 ± 303 m with a strong east–west gradient: higher values (generally greater than 1800 m) occurred over the Midwest US, and lower values (usually less than 1400 m) occurred over Alaska and the US West Coast.

This study analyzed hourly mass concentration observations of PM_2.5 (particulate matters with diameter less than 2.5 μm) at 512 stations in China from December 2013 to May 2015. We found that the mean concentrations of PM_2.5 during the winter and spring of 2015 Dec. 2014 to Feb. 2015 and Mar. 2015 to May 2015) decreased by 20% and 14% compared to the previous year, respectively. Hazardous air-quality days decreased by 11% in 2015 winter, with more frequent good to unhealthy days; and the good and moderate air-quality days in 2015 spring increased by 9% corresponding to the less occurrence of unhealthy conditions. We compared the atmospheric diffusion conditions during these two years and quantified its contribution to the improvement of air quality during the first half of 2015 over China. Our results show that during the 2015 winter and spring, 70% and 57% of the 512 stations experienced more favorable atmospheric diffusion conditions compared to those of previous year. Over central and northern China, approximately 40% of the total decrease in PM_2.5 during the 2015 winter can be attributed to the favorable atmospheric diffusion conditions. The atmospheric diffusion conditions during the spring of 2015 were not as favorable as in winter; and the average contributions of the atmospheric conditions were slight.

The Chinese government has made many efforts to mitigate fine particulate matter pollution in recent years by taking strict measures on air pollutant reduction, which has generated the nationwide improvements in air quality since 2013. However, under the stringent air pollution controls, how the wintertime PM_2.5 concentration (i.e., the mass concentration of atmospheric particles with diameters less than 2.5 µm) varies and how much the meteorological conditions contribute to the interannual variations in PM_2.5 concentrations are still unclear, and these very important for the local government to assess the emission reduction of the previous year and adjust mitigation strategies for the next year. The effects of atmospheric circulation on the interannual variation in wintertime PM_2.5 concentrations over the Beijing–Tianjin–Hebei (BTH) region in the period of 2013–2018 are evaluated in this study. Generally, the transport of clean and dry air masses and an unstable boundary layer in combination with the effective near-surface horizontal divergence or pumping action at the top of the boundary layer benefits the horizontal or vertical diffusion of surface air pollutants. Instead, the co-occurrence of a stable boundary layer, frequent air stagnation, positive water vapor advection and deep near-surface horizontal convergence exacerbate the wintertime air pollution. Favorable circulation conditions lasting for 2–4 d are beneficial for the diffusion of air pollutants, and 3–7 d of unfavorable circulation events exacerbates the accumulation of air pollutants. The occurrence frequency of favorable circulation events is consistent with the interannual variation in seasonal mean PM_2.5 concentrations. There is better diffusion ability in the winters of 2014 and 2017 than in other years. A 59.9 % observed decrease in PM_2.5 concentrations in 2017 over the BTH region could be attributed to the improvement in atmospheric diffusion conditions. It is essential to exclude the contribution of meteorological conditions to the variation in interannual air pollutants when making a quantitative evaluation of emission reduction measurements.