The ecological environment is fragile in arid regions, and the direct and indirect impacts of continuing urbanization on vegetation growth in cities still need to be studied in depth. In this study, we focused on four provincial capital cities (Urumqi, Lanzhou, Yinchuan, and Hohhot) in arid regions of China. We used continuous 30 m land cover and vegetation greenness (VG) data from 1990 to 2021 to extract the impact of urbanization on vegetation growth by separating the impact of natural conditions. Our results showed that the study area’s urban area (UA) had expanded rapidly at a rate of 39.2 km²/a, increasing by 3.39 times between 1990 and 2021. While urban expansion occurred rapidly, the overall VG of the study area also increased (slope = 2.16 × 10⁻³), with the enhancement of VG increasing gradually from west to east. The VG and its trend in the UA were significantly higher than those in the natural vegetation area (NA). In addition, the duration of the urban vegetation growth season was longer than that of the NA, which also confirmed the positive impact of urbanization on the vegetation growth period. Furthermore, we found that the positive impact of urbanization on vegetation had continuously strengthened over time. In 1990 and 2021, the VG areas had 83% and 87% above the ‘zero-impact line’ in the UA, respectively, indicating a very significant impact of urbanization on vegetation growth in arid regions with fragile natural conditions. Our study identified the long-term dynamic trends in urbanization and VG in arid regions and clarified the non-linear relationship between the two concurrent growth factors. This has significant implications for correctly understanding the impact of urbanization on vegetation in arid regions and can provide a scientific reference for the ecological construction of urban environments in the region.

Land surface temperature (LST) is an important driving factor in the land-atmosphere energy cycle. To examine the spatiotemporal patterns of LST changes and the internal mechanisms driven by multiple factors, we used a trend analysis method on TRIMS LST data from 2000 to 2020 in the Qingling-Daba Mountains. The optimal parameter geographic detector (OPGD) model was used to detect the influence of twelve factors, including elevation, precipitation, albedo, relative humidity (RH) and normalized difference vegetation index (NDVI), on the spatial distribution of LST, as well as to explore the dominant factors affecting LST differentiation in the study area. The results showed that: (1) From 2000 to 2020, the average annual LST of the Qinling-Daba Mountains was 18.17 °C. The warming trend was obvious (0.034 °C/a), and the warming effect at nighttime (0.066 °C/a) was stronger than that during daytime (0.0004 °C/a). The difference between day and night temperature (DIF) was decreasing. (2) The seasonal changes in LST and DIF in the Qinling-Daba Mountains were significant, and the spatial distribution of their average values in the summer was slightly larger and fluctuated more than in the other seasons. (3) Elevation was the main driving factor affecting the spatial distribution of LST, with the contribution scores of 62.9% in the daytime and 92.7% in the nighttime. The controlling effects of these factors were generally stronger in the nighttime than in the daytime. (4) Nighttime elevation had the strongest interaction with precipitation (contribution score of 95%), while daytime elevation had the strongest interaction with albedo (contribution rate of 83%). We revealed the temporal and spatial variation in LST in the Qinling-Daba Mountains since 2000 and explored the main driving factors involved, thereby improving our understanding of LST changes in the Qinling-Daba Mountains. This study can provide a scientific basis for distinguishing dominant drivers of LST dynamics in the Qinling-Daba Mountains.

Haze occurred in Zhengzhou, a megacity in the northern China, with the PM_2.5 as high as 254 μg m⁻³ on 25 December 2019, despite the emergency response measure of restriction on the emission of anthropogenic pollutants which was implemented on December 19 for suppressing local air pollution. Air pollutant concentrations, chemical compositions, and the origins of particulate matter with aerodynamic diameter smaller than 2.5 µm (PM_2.5) between 5–26 December were investigated to explore the reasons for the haze occurrence. Results show that the haze was caused by efficient SO₂-to-suflate and NO_x-to-nitrate conversions under high relative humidity (RH) condition. In comparison with the period before the restriction (5–18 December) when the PM_2.5 was low, the concentration of PM_2.5 during the haze (19–26 December) was 173 µg m⁻³ on average with 51% contributed by sulfate (31 µg m⁻³) and nitrate (57 µg m⁻³). The conversions of SO₂-to-sulfate and NO_x-to-nitrate efficiently produced sulfate and nitrate although the concentration of the two precursor gases SO₂ and NO_x was low. The high RH, which was more than 70% and the consequence of artificial water-vapor spreading in the urban air for reducing air pollutants, was the key factor causing the conversion rates to be enlarged in the constriction period. In addition, the last 48 h movement of the air parcels on 19–26 December was stagnant, and the air mass was from surrounding areas within 200 km, indicating weather conditions favoring the accumulation of locally-originated pollutants. Although emergency response measures were implemented, high gas-to-particle conversions in stagnant and moisture circumstances can still cause severe haze in urban air. Since the artificial water-vapor spreading in the urban air was one of the reasons for the high RH, it is likely that the spreading had unexpected side effects in some certain circumstances and needs to be taken into consideration in future studies.