The difference in ozone (O₃) concentration between stations in the urban and southern mountainous areas of Urumqi was explored based on mathematical statistics and comparative analysis of pollutant concentrations. Besides, potential source contribution function (PSCF) analysis and concentration weighted trajectory (CWT) analysis were performed to identify the potential sources of PM_2.5 and O₃. The results showed that the daily and monthly mean O₃ concentrations in the urban area of Urumqi showed a bimodal variation from October 2017 to August 2018, and the O₃ concentration had obvious seasonal characteristics, with the highest in July (120.57 μg/m³) and the lowest in January (22.38 μg/m³). The overall variation of O₃ concentration in the mountainous area in the southern suburb of Urumqi was not significant (56.69–84.06 μg/m³), and the O₃ concentration was slightly higher in summer than in other seasons. The daily O₃ concentration in the urban area showed a unimodal variation in all seasons, and the daily variation was the smallest in winter and the largest in summer. However, the daily variation in the mountainous area was not significant. The O₃ concentration in the urban area showed a significant negative weekend effect in winter and a positive weekend effect in spring and summer. However, the O₃ concentration only showed a significant positive weekend effect in the mountainous area in summer. The PSCF and CWT analysis results of urban O₃ concentration showed that Urumqi, Shihezi, and Wusu were the main O₃ source areas. In addition, some areas bordering Kazakhstan in Xinjiang, China were also important source areas.

Air samples were collected by flasks and analyzed via a Picarro G2401 gas analyzer for carbon dioxide (CO₂) and carbon monoxide (CO) at the Akedala Atmospheric Background Station in Xinjiang, China, from September 2009 to December 2019, to analyze the changes in the characteristics of atmospheric CO₂ and CO and determine the sources. The results show that the annual average CO₂ concentration showed an increasing trend (growth rate: 1.90 ppm year⁻¹), ranging from 389.80 to 410.43 ppm, and the annual average CO concentration also showed an increasing trend (growth rate: 1.78 ppb year⁻¹), ranging from 136.30 to 189.82 ppb. The CO₂ concentration and growth rate were the highest in winter, followed by autumn, spring, and summer. The CO concentration and growth rate were also the highest in winter due to anthropogenic emissions, ecosystem effects, and diffusion conditions. The main trajectories of CO₂ and CO determined by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model were parallel to the Irtysh River valley and then passed through the Old Wind Pass. Furthermore, the main source regions of CO₂ and CO at the Akedala Station were eastern Kazakhstan, southern Russia, western Mongolia, and the Xinjiang Tianshan North Slope Economic Zone of China. This study reflects the characteristics of long-term changes in CO₂ and CO concentrations at the Akedala station and provides fundamental data for the studies on environmental changes and climate change in Central Asia.

Black carbon (BC) is a pollutant produced by the combustion of fossil fuels and biomass fuels, which has a huge impact on regional climate, atmospheric environment, and human health. In this study, based on MERRA-2 reanalysis data and ground-based observation data, the Mann-Kendall (MK) test and random forest (RF) model were used to explore the spatiotemporal variation characteristics of atmospheric BC concentration in Xinjiang, China and its correlation with meteorological and environmental covariates in 2010–2022. The results showed that the use of MERRA-2 reanalysis data to explore the spatiotemporal variation characteristics of BC concentration in Xinjiang had high reliability (relative average deviation (RAD) = 0.65). From 2010 to 2022, the annual average concentration of atmospheric BC in Xinjiang was 195.40 ± 15.55 ng/m³, and the multi-year average change rate was −0.05%. The winter season had the highest atmospheric BC concentration (145.52 ± 39.31 ng/m³), followed by autumn (124.95 ± 28.82 ng/m³), spring (74.05 ± 9.96 ng/m³), and summer (73.41 ± 5.69 ng/m³). The atmospheric BC concentration had a significant spatial variation, showing two high-BC-concentration areas on the northern slope of the Tianshan Mountains (centered on Urumqi-Changji-Shihezi region) and the urban agglomeration around the Tarim Basin (centered on Kashgar). The RF model analysis showed that meteorological factors including snow depth, surface temperature, and humidity as well as environmental factors including NO₂, PM₁₀, and SO₂ were the main factors affecting the BC concentration. This work is of great significance for clarifying the accumulation and spatial distribution characteristics of atmospheric BC in northwest China and the factors influencing the atmospheric BC concentration, and helps to raise public attention to the increasingly serious climate change and public health problems caused by BC.

Mole fractions of atmospheric carbon dioxide (CO₂), methane (CH₄) ,nitrous oxide (N₂O) and sulphur hexafluoride (SF₆) have been continuously measured since September 2009 at the Akdala station (47˚06′N, 87˚58′E, 563.3 masl) in China. The station is located in the Central Asia and northwest of China, and it is the only station in that region with background conditions for long-term greenhouse gas observations. Characteristics of the mole fractions, growth rates as well as influence of long-distance transport were studied considering data from September 2009 to December 2019. The greenhouse gases concentrations at Akedala Station show a trend of year-on-year growth, with CO₂ concentrations ranging from 389.80×10^-6 to 408.79×10^-6 (molar fraction of substances, same below), CH₄ concentrations ranging from1890.07×10^-9 to 1976.32×10^-9, N₂O concentrations ranging from 321.26×10^-9 to 332.03×10^-9, and SF₆ concentrations ranging from 7.04×10^-12 to 10.07×10^-12, the growth rate of which is similar to the decadal average growth rate in the northern hemisphere. There exist obvious seasonal variations, with CO₂ concentrations showing high in winter and low in summer and CH₄ showing a distinct “W”- shaped trend while N₂O and SF₆ showing little difference between the four seasons. A relatively strong correlation and homology exist among the four greenhouse gases except in summer, and the analysis based on backward trajectories model shows that the Akedala Station is influenced by the airflow from northwest or southwest throughout the year. The Akedala station is an important atmospheric background station in Central Asia, and its greenhouse gas concentration levels and variation characteristics are significantly different from those of the background stations in the monsoon region. It’s degree changes are closely related to local source emissions, monsoon transport, and atmospheric photochemical processes.