Data for modelling spatial patterns and determinants of atmospheric carbon dioxide concentrations in Phoenix metro area

The purpose of this work is to describe determinants and spatial patterns of atmospheric carbon dioxide (CO2) in Phoenix, Arizona. Specifically, we use geographic information systems (GIS) and regression-based analyses to identify the human and biological factors that contribute to spatial and temporal variations in near-surface atmospheric CO2 levels. We use these factors to create estimated surfaces of CO2 for the urban area. We validate our surfaces using independently collected records of CO2 from several monitoring stations and transects. To investigate the temporal patterns and variations of CO2, we were able to generate CO2 surfaces for the early mornings and the afternoons, and on weekdays when traffic is heavy and spatially focused and on weekends when it is lighter and more spatially dispersed. Our findings suggest there is a distinct relationship between the structure of Phoenix CO2 levels and spatial patterns of human activities and vegetation densities. Morning CO2 levels are higher than afternoon levels and correspond closely to the density of traffic, population, and employment. The spatial structure of human activity explains the pattern of CO2 better on weekdays than on weekends. CO2 surfaces reflect declining densities of human activity with distance from the city center, the pattern of irrigated agriculture in the Phoenix area, and riparian habitats on the urban fringe. Spatial and temporal patterns of CO2 are useful in understanding urban climate and ecosystem processes.本研究旨在阐明亚利桑那州凤凰城大气二氧化碳（CO₂）的影响因子与空间分布格局。具体而言，本研究采用地理信息系统（GIS）与基于回归的分析方法，识别驱动近地表大气CO₂浓度时空变化的人为与生物因子。基于上述因子，我们生成了该城区的CO₂浓度估算空间分布面。随后，我们利用多个监测站点与样带独立采集的CO₂观测记录对该估算分布面进行验证。为探究CO₂的时间分布特征与变化规律，我们分别针对早间、午后，以及交通繁忙且空间聚集的工作日、交通流量较低且空间分布更分散的周末生成了CO₂空间分布面。研究结果显示，凤凰城CO₂浓度格局与人类活动结构、植被密度之间存在显著关联：早间CO₂浓度高于午后，且与交通密度、人口密度及就业密度高度契合。相较于周末，工作日的人类活动空间结构对CO₂分布格局的解释能力更强。CO₂空间分布面可反映出随距城市中心距离增加，人类活动密度逐渐降低的规律，同时也体现了凤凰城区域的灌溉农业格局，以及城市边缘的河岸栖息地分布特征。CO₂的时空分布特征可为理解城市气候与生态系统过程提供有效支撑。