CAPSULEThe Desert Environment and Climate Observation Network (DECON) could promote collaborative research on desert dust-storms, boundary-layer and land-atmosphere interactions to better understand the status and role of the Taklimakan desert.
Land surface temperature (LST) is an important parameter that affects the water cycle, environmental changes, and energy balance at global and regional scales. Herein, a time series analysis was conducted to estimate the monthly, seasonal, and interannual variations in LST during 2001–2019 in the Tarim Basin, China. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) LST, air temperature, air pressure, relative humidity, wind speed, precipitation, elevation, and land-cover type data, we analyzed the spatio-temporal change characteristics of LST and the influencing factors. High LSTs occurred in the desert and plains and low LSTs occurred in surrounding mountain regions. The highest LST was recorded in July (25.1 °C) and the lowest was in January (−9.5 °C). On a seasonal scale, LST decreased in the order: summer > spring > autumn > winter. Annual LST showed an increasing trend of 0.2 °C/10 a in the desert and mountain areas, while the plains indicated a decreasing trend. In spring and autumn, western regions were dominated by a downward trend, whereas in winter a downward trend occurred in eastern regions. In summer, areas covered by vegetation were dominated by a downward trend, and desert and bare lands were dominated by an upward trend. Random forest (RF) model analysis showed that elevation was the most significant influencing factor (22.1%), followed by mean air temperature (20.1%). Correlation analysis showed that the main climatic factors air temperature, relative humidity, and elevation have a good correlation with the LST. Land-cover type also affected LST; during February–December the lowest LST was observed for permanent glacier snow and the highest was observed in the desert. El Nino and La Nina greatly influenced the LST variations. The North Atlantic Oscillation and Pacific Decadal Oscillation indices were consistent with the mean LST anomaly, indicating their considerable influence on LST variations.
Reactive gases (O3, CO, NO2, and SO2) were collected hourly at the Akedala regional background station in northwestern China during September 2017 to August 2018. Wind rose, cluster analysis, potential source contribution function (PSCF), and concentration-weighted trajectory (CWT) methods were adopted for identifying the transport pathways and potential source regions of these atmosphere components at Akedala. The average O3, CO, NO2, and SO2 mixing ratios detected were 29.65 ± 11.44 ppb, 123.78 ± 73.35 ppb, 3.79 ± 0.98 ppb, and 4.59 ± 0.88 ppb during the observation period, and the statistical results of the monthly mean values revealed that there were differences during the highest pollution period, with O3 and CO mainly peaking in February, with mixing ratios of 38.03 ± 7.10 ppb and 208.50 ± 106.50 ppb, respectively. Meanwhile, NO2 peaked in March (4.51 ± 0.54 ppb) and SO2 in January (5.70 ± 1.92 ppb). The most obvious diurnal variation of CO and SO2 was observed in the winter, with maximum levels reaching between 13 : 00 and 14 : 00. The diurnal variations of O3 exhibited low values during the night and maximum values in the afternoon (16 : 00–18 : 00). Diurnal variation was not significant in the case of NO2. Cluster analysis showed that six main paths affected the Akedala atmosphere. In turn, the PSCF and CWT analysis results indicated that the Akedala reactive gas was affected by both local and foreign sources. The high PSCF value of the reactive gas potential source areas appeared in eastern Kazakhstan, northern Xinjiang, Western Mongolia, and Southern Russia. The WCWT (weighted concentration-weight trajectory) values of CO and SO2 in winter were the highest, totaling 180–240 ppb and 5–6.5 ppb, respectively. The WCWT value of O3 in the spring and summer was higher than that in the autumn and winter. The main source area of O3 was about 32–36 ppb in the spring and summer, and the main source area of NO2 in the summer had a low WCWT value of 3–3.5 ppb, whereas the NO2 WCWT value was concentrated at 4–4.5 ppb in the other seasons.
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