Seasonal dynamics and impact factors of atmospheric CO2 concentration over subtropical forest canopies: observation from eddy covariance tower and OCO-2 satellite in Northwest Himalaya, India

Unrevealing the coupling coordination degree between atmospheric CO2 concentration and human activities from geospatial and temporal perspectives

Anthropogenic activities exhibit intricate and significant relationships with atmospheric CO2 concentration. Dissecting the spatiotemporal patterns and potential drivers of their coupling coordination relationships from geospatial and temporal perspectives contributes to the benign coordinating development between the two. The coupling coordination degree (D) and types, and their potential influencing factors in China were explored using a coupling coordination model, emerging hotspot analysis, and Multiscale Geographically Weighted Regression model. Results revealed D was dominated by basic coordination in China with notable spatial disparities. Generally, D exhibited higher values in the eastern regions and lower values in the western regions divided by the Hu Line. Furthermore, Central and East China exhibited lower coordination degrees compared to other eastern regions. A total of 15 spatiotemporal dynamic patterns were identified across China. Hot spot patterns were concentrated in the eastern regions of the Hu Line, while cold spots were mainly observed in the western regions. The coupling coordination types exhibited a distinct pattern of "coordination in the east and incoherence in the west, divided by the Hu Line". Over time, there was a shift from lower-level to more benign coordinated types. Additionally, the D and coupling coordination types demonstrated significant spatial agglomeration characteristics, and intercity alliances and enhanced collaborations are essential for sustaining low-carbon improvements. The mechanisms and intensities of various factors on D exhibited spatiotemporal differences. The key drivers influencing coupling coordination types varied depending on the specific type. Additionally, the scales of these drivers affecting D changed over time. It is essential to consider natural and meteorological factors and their scaling effects when developing policies to enhance coupling coordination level. These results have significant implications for assessing the relationship between atmospheric CO2 and human activities and provide guidance for implementing effective low-carbon development policies.

Atmospheric CO2 in the megacity Hangzhou, China: Urban-suburban differences, sources and impact factors

Limited observation sites and insufficient monitoring of atmospheric CO2 in urban areas restrict our comprehension of urban-suburban disparities. This research endeavored to shed light on the urban-suburban differences of atmospheric CO2 in levels, diurnal and seasonal variations as well as the potential sources and impact factors in the megacity of Hangzhou, China, where the economically most developed region in China is. The observations derived from the existing Hangzhou Atmospheric Composition Monitoring Center Station (HZ) and Lin'an Regional Atmospheric Background Station (LAN) and the newly established high-altitude Daming Mountain Atmospheric Observation Station (DMS), were utilized. From November 2020 to October 2021, the annual averages of HZ, LAN and DMS were 446.52 ± 17.01 ppm, 441.56 ± 15.42 ppm, and 422.02 ± 10.67 ppm. The difference in atmospheric CO2 mole fraction between HZ and LAN was lower compared to the urban-suburban differences observed in other major cities in China, such as Shanghai, Nanjing, and Beijing. Simultaneous CO2 enhancements were observed at HZ and LAN, when using DMS observations as background references. The seasonal variations of CO2 at LAN and DMS exhibited a high negative correlation with the normalized difference vegetation index (NDVI) values, indicating the strong regulatory of vegetation canopy. The variations in boundary layer height had a larger influence on the low-altitude HZ and LAN stations than DMS. Compared to HZ and LAN, the atmospheric CO2 at DMS was influenced by emissions and transmissions over a wider range. The potential source area of DMS in autumn covered most areas of the urban agglomeration in eastern China. DMS measurements could provide a reliable representation of the background level of CO2 emissions in the Yangtze River Delta and a broader region. Conventional understanding of regional CO2 level in the Yangtze River Delta through LAN measurements may overestimate background concentration by approximately 10.92 ppm.