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The Impact of aerosols in Jizi Bay of the Yellow River on the Total Primary Productivity of Vegetation |
SHI Jian-yang, LIU Min-xia, PAN Jing-hu, LI Yu, GUAN Cheng-xuan |
School of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China |
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Abstract Based on multi-source remote sensing data of the Jizi Bay of the Yellow River from 2006 to 2020, the temporal and spatial variations of AOD-PAR-GPP were analyzed using Pearson correlation coefficient and standardized ellipse analysis. Subsequently, a GWR-SEM model was constructed by coupling structural equation modeling and geographical weighted regression to quantify the impact of AOD on GPP. Methods such as Sen trend analysis, MK significance test, and grey prediction model were employed to explore the future trends of AOD and GPP. The results indicated that: (1) In terms of time, AOD, PAR, and GPP exhibited a synchronous upward trend, with AOD reaching its lowest value of 0.17 and highest value of 0.46 in 2008 and 2020, respectively. GPP reached its lowest value of 266.4867.04gC/(m2·a) and highest value of 408.87gC/(m2·a) in 2007 and 2018, respectively, with significant seasonal differences observed. It was found that there was a light saturation point for GPP in June during the vegetation growing season. (2) Spatially, high AOD values were mainly distributed in Alxa League; the distribution of PAR was similar to that of AOD and negatively correlated with GPP. GPP showed a pattern of decreasing from north to south, with the expansion of its high-value range reflecting an enhanced contribution from Yan’an. Ordos and Yulin served as the main sources of AOD pollution, diffusing overall from west to east in a counterclockwise direction. The contributing area for GPP was in Yulin, exhibiting a northwest to southeast trend. (3) GPP in areas such as Xilin Gol, Datong, and Yinchuan was mainly influenced by AOD, PAR, and precipitation, while GPP in areas like Baotou, Shuozhou, and Zhongwei was influenced by PAR and precipitation. The standardized total effect of AOD on GPP generated by the model was 0.758, with GPP variation primarily influenced by temperature, followed by AOD, PAR, and precipitation, with PAR playing a key role in various indirect pathways. (4) In terms of trend prediction, there was a further acceleration trend in AOD in the northern Jizi Bay and GPP in the southeastern part represented by Yulin. The upward trend in AOD from 2021 to 2030 was relatively slow, while the upward trend in GPP was faster.
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Received: 27 November 2023
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