In this study, air pollutants were analyzed at a low-industry city on the Silk Road Economic Belt of Northwestern China from 2015 to 2018. The results show that SO2 and CO had a decreasing trend and NO2, O-3, PM2.5, and PM10 had an increasing trend during the study period. The primary characteristic pollutants were PM2.5 and PM10, which were higher than China's Grade II standard. SO2, NO2, CO, PM2.5, and PM10 concentrations showed similar seasonal variation patterns: the highest pollutant concentration was in winter and the lowest in summer. Those pollutants showed a similar diurnal pattern with two peaks, one at 7:00 to 9:00 and another at 21:00 to 22:00. However, O-3 concentration was highest in summer and lowest in winter, with a unimodal diurnal variation pattern. The annual average pollution concentrations in Tianshui in 2017 were substantially lower than the concentrations reported by most cities in China. By examining the meteorological conditions at a daily scale, we found that Tianshui was highly influenced by local emissions and a southwest wind. Potential source contributions and concentration weighted trajectory analyses indicated that the pollution from Gansu, Sichuan, Qinghai, and Shaanxi Province could affect the pollution concentration in Tianshui. The results provide directions for the government to take in formulating regional air pollution prevention and control measures and to improve air quality.

The formation mechanism of air pollution events in the Sichuan Basin (SB), which is the fourth most heavily polluted area in China, has not been fully revealed. This study investigated the formation mechanism of a severe air pollution event over the SB using synoptic approaches and model simulations. The results can be summarized as follows: (1) Heavy air pollution in the SB was characterized by low visibility, low atmospheric boundary layer (ABL) height, high temperature, high relative humidity, strong temperature inversion layer, subsidence in the troposphere, high water vapor content between 500 and 900 hPa, southerly winds in the low troposphere, and surface winds with low speed and irregular direction. (2) Air quality in the SB was closely related to the weather system at 700 hPa over the basin. When the 700 hPa weather system affecting the SB was a high-pressure system, the subsidence and stable atmospheric stratification increased the air pollutant concentrations near the ground. When the 700 hPa weather system affecting the SB was a low-pressure system and the basin was in front of this low-pressure system, southwesterly warm and moist airflow and adiabatic subsidence warming formed the thick temperature inversion layer over the basin. As a result, the temperature inversion layer trapped air pollutants in the basin and induced the heavy air pollution event. When the 700 hPa weather system over the SB was a low-pressure system and the basin was behind the low-pressure system, the dry and cold airflow from the north invaded southward to the basin and broke the temperature inversion layer. Consequently, air pollutants dispersed vertically, resulting in decreased concentrations near the ground. (3) Air pollutants from December 17, 2017 to January 4, 2018 were mainly from local emissions. (4) The WRF-Chem model not only reproduced the variations in PM2.5 concentrations, the ABL height, and the height-time cross-sections of temperature, water vapor content, and wind over Chengdu during the air pollution event, but also revealed the formation mechanism of this heavy air pollution event. The results of this study reveal the formation mechanism of winter heavy air pollution events over the SB and help develop effective regional air quality management strategies to reduce the likelihood of local air pollution events and minimize the adverse impacts of air pollution.

Analysis of climatic conditions for the period of instrumental measurement in Central Yakutia showed three periods with two different mean annual air temperature (MAAT) shifts. These periods were divided into 1930-1987 (base period A), 1988-2006 (period B) and 2007-2018 (period C) timelines. The MAAT during these three periods amounted -10.3, -8.6 and -7.4 degrees C, respectively. Measurement of active layer depth (ALD) of permafrost pale soil under the forest (natural) and arable land (anthropogenic) were carried out during 1990-2018 period. MAAT change for this period affected an early transition of negative temperatures to positive and a later establishment of negative temperatures. Additionally, a shortening of the winter season and an extension of the duration of days with positive temperatures was found. Since the permafrost has a significant impact on soil moisture and thermal regimes, the deepening of ALD plays a negative role for studied soils. An increase in the ALD can cause thawing of underground ice and lead to degradation of the ice-rich permafrost. This thaw process causes a change of the ecological balance and leads to the destruction of natural landscapes, sometimes with a complete or prolonged loss of their biological productivity. During this observation (1990-2018 period) the active layer of permafrost is characterized by high dynamics, depending on climatic parameters such as air temperature, as well as thickness and duration of snow cover. A significant increase in ALD of forest permafrost soils-by 80 cm and 65 cm-on arable land was measured during the observation period (28 years).

Black carbon (BC) is a major light absorption material that acts as a climate change driver with high radiative forcing and as an air pollutant that reduces visibility and air quality. Thus, reducing the emission and ambient concentration of BC could help address climate change and improve air quality simultaneously. In this study, the mass concentration of atmospheric BC was continuously measured by an aethalometer in Shanghai in 2017. The annual BC concentration was 2.19 +/- 1.28 mu g/m(3), with the highest loading in winter and the lowest loading in autumn. The BC concentrations varied with year and location when compared with previous studies in different locations in Shanghai. The hourly BC concentration had a bimodal distribution, with two peaks during the morning and evening traffic rush hours. Liquid fuels, biomass, and coal combustion contributed 65.7%, 21.5%, and 12.8%, respectively, of the total BC based on the advanced aethalometer model. The three sources varied in different seasons with a high contribution of liquid source in summer and more coal and biomass emissions in winter. High BC concentrations accumulated in the stable weather conditions in the four seasons and appeared when there were high wind speeds from the northwestern direction in winter. The Yangtze River Delta region was the most likely potential source region of high BC loading in the four seasons, and long-range transport from North China in winter was another likely source region based on the results of cluster analysis and potential source contribution function analysis of backward trajectories.