# Spatial and Temporal Variation of GPP and Its Response to Urban Environmental Changes in Beijing
## 1 Introduction  
The carbon sequestration capacity of vegetation is a crucial component of the carbon cycle in terrestrial ecosystems. Investigating the drivers of GPP spatiotemporal variations and their underlying mechanisms benefits revealing the main forces of GPP variations, thus promoting ecosystem management aiming at increasing carbon sequestration of terrestrial ecosystems [1; 2; 3]. Gross primary production (GPP) is the total amount of organic carbon fixed by plants per unit of time through photosynthesis, which reflects the vegetation productivity status of terrestrial ecosystems. It is one of the key indicators for assessing the carbon sequestration capacity of vegetation and understanding the carbon cycle of the terrestrial ecosystem [4]. Therefore, quantifying GPP and its spatiotemporal variation is of priority in carbon cycle studies [5]. Research indicates that the spatiotemporal variation in vegetation's ability to capture carbon is influenced by multiple factors such as climatic conditions [6], vegetation cover [7], land use patterns [8], and soil properties [9]. The current studies on factors affecting GPP changes mainly focus on meteorological conditions and land use changes, etc. [10; 11]. However, in urban areas, the impact of urbanization on GPP is complex and multifaceted. On the one hand, urban expansion leads to changes in regional land cover and a decrease in vegetation coverage, which may directly reduce the productivity of vegetation [12]. On the other hand, human activities brought about by urbanization also have indirect positive impacts [13], such as the urban heat island effect, increased air pollution in the atmosphere, and more effective vegetation management and planning [14], which collectively promote the photosynthesis and carbon fixation capacity of vegetation. These indirect effects can offset the direct negative effects in some cases and even promote the growth of vegetation productivity in certain areas [15]. It has also been found that the effect of air pollution on GPP cannot be ignored. For example, O\({}_{3}\), which has strong oxidizing properties, is absorbed by plants and damages their cell membrane tissues, thus reducing vegetation GPP [16; 17], and aerosol particles can increase GPP by increasing scattered light [18], too much particulate matter can cause plant stomatal blockage instead of causing GPP reduction. For example, [PERSON] & [PERSON] [19], in their analysis of the effects of O\({}_{3}\) and aerosols on GPP during 2002-2011, found that O\({}_{3}\) led to a global GPP decrease of 0.91 \(\pm\) 0.44 PgCyr-1 and aerosols led to a global GPP increase of 0.05 \(\pm\) 0.30 PgCyr-1. Therefore, in this study, we used four types of air pollution, O\({}_{3}\), NO\({}_{2}\), CO, and PM2.5, as the influencing factors of human activities caused by urbanization. We used Land Surface Temperature (LST), Air Temperature (T), and Preparation (PRE) as environmental factors. With these factors considered, we can further our understanding of the responses of the carbon cycle to environmental change and human activities brought about by urbanization, especially for those fast-growing cities. Beijing, as a highly urbanized city in China and a pilot area for sustainable and low-carbon development, has seen the majority of GPP research focus on ecologically sensitive areas such as the Mentougou district. This focus has led to a neglect of the spatial and temporal dynamics of GPP and the factors influencing it. When assessing the impact of environmental factors on GPP, it is imperative to consider the spatial dependence characteristic to prevent biased evaluation outcomes. The urban environment and its suburban counterpart interact through wind patterns, suggesting that GPP in suburban areas may be influenced by urban various factors [10; 20; 21]. The Geographically Weighted Regression (GWR) model proposed by [PERSON] et al.