西安市典型区CO2通量的变化特征和影响因素

Variation characteristics and inf luencing factors of CO2 f lux in typical areas of Xi’an City

关键词:  城市碳通量  新冠疫情  涡动相关法  季节变化  日变化

Key words:  urban carbon f lux  COVID-19  eddy covariance methods  seasonal variation  diurnal variation

摘要:

城市是碳排放的热点，研究城市CO₂通量的变化特征有助于服务国家碳减排工作。通过分析西安市高新区唐城墙遗址公园2021年1月—2022年1月CO₂通量的日变化、月变化、季节变化、新冠疫情和供暖期间CO₂通量的变化特征及影响因素，得到如下结果：（1）2021年观测点CO₂通量年均值为(1.5±1.5)×10² mol∙m⁻²∙a⁻¹，整体表现为碳源；在临时封控期（2021-12-23—2022-01-23），观测点CO₂通量出现明显谷值，解封后明显回升；（2）观测点CO₂通量季节变化特征明显，冬季均值高于其他季节；夏季CO₂通量均值最低，碳汇出现时间长于其他季节；（3）观测点CO₂通量具有明显的“双峰型”日变化特征，早晚高峰出现时间与上下班通勤高峰时间重叠；周末无明显早高峰，晚高峰较周内延迟1 h；供暖期CO₂通量小时均值均高于非供暖时期；（4）观测点CO₂通量主要受机动车排放影响，其源区贡献范围分布与观测点盛行风向一致，西南风对CO₂通量的贡献最高。

Abstract:

Background, aim, and scope Addressing global warming necessitates a thorough understanding of atmospheric CO₂ dynamics. Cities, as primary centers of anthropogenic activity, are significant sources of CO₂ emissions, making the monitoring of urban CO₂ dynamics is crucial for effective climate action. CO₂ flux measurements provide real-time data on carbon change, which are vital for formulating urban carbon reduction strategies. Therefore, this study analyzes a year-long (January 2021 to January 2022) dataset of CO₂ flux observed in Xi’an High-Tech Industries Development Zone. We investigate the daily, monthly and seasonal variations of CO₂ flux, and explore the environmental and socioeconomic drivers, to provide a scientific basis for formulating energy conservation and emission reduction policies. Materials and methods CO₂ flux data were collected from a flux tower located in the High-Tech Industries Development Zone (34.23°N, 108.89°E). The open path eddy covariance system consisted of a three-dimensional ultrasonic anemometer (WindMaster, GILL Inc., UK), an open path CO₂/H₂O gas analyzer (LI-7500, LI-COR Inc., USA), and a data collection unit. The gas analyzer was recalibrated semi-annually using standard CO₂ gases (0 and 395.46 μL·L⁻¹ CO₂) and a LI-COR LI-610 portable dew point generator. The instruments were mounted at a height approximately 1.5 times the mean height of the surrounding vegetation, with a sampling frequency of 10 Hz. Raw data were processed for quality control, including outlier removal and gap-filling via interpolation, prior to analysis. Results (1) The study site functioned as a net carbon source in 2021, with an annual average CO₂ flux of (1.5±1.5)×10² mol·m⁻²·a⁻¹. (2) The flux exhibited strong seasonal variations, being highest in winter ((20.7±12.8) mol·m⁻²·month⁻¹) and lowest in summer ((0.5±5.2) mol·m⁻²·month⁻¹), during which the site acted as a carbon sink for the longest duration. (3) A distinct “bimodal” diurnal variation was observed between weekdays and weekends. The weekend pattern showed an hour delay in the evening peak and an absent morning peak, without an obvious morning peak; the 24-hour average CO₂ flux during the heating period was higher, and the city acted as a carbon source; during the COVID-19 lockdown in Xi’an, the CO₂ flux showed a significant decrease (0.1—5.1 μmol·m⁻²·s⁻¹), but rapidly increased after the lockdown was lifted. (4) The CO₂ flux was mainly affected by motor vehicle emissions. The distribution of the contribution range of the observation point source area was consistent with the prevailing wind direction, with the strongest contribution from the southwest wind. Discussion (1) The observed seasonal patterns were attributed to the interplay between biogenic and anthropogenic factors. Peak photosynthetic activity of urban vegetation in summer led to periods of net carbon uptake, while intensified fossil fuel combustion for residential heating was the primary cause of the highest emissions in winter. (2) The spatial heterogeneity of emissions was confirmed by footprint analysis, which showed that the dominant flux contributions from the southwest sector corresponded to dense infrastructure and major roadways. In contrast, lower contributions from the northeast and southeast aligned with vegetated residential areas and a large park, respectively. (3) The bimodal diurnal flux pattern directly mirrored local traffic dynamics, with peaks coinciding with morning and evening commutes. Altered social schedules on weekends and during different seasons were reflected in shifts in these diurnal peaks. (4) Finally, the dramatic reduction in CO₂ flux during the COVID-19 lockdown provided a clear demonstration of the impact of reduced anthropogenic activities and primarily traffic on the urban carbon budget. Conclusions The urban CO₂ flux has obvious daily, monthly, and 24-hour patterns, which are driven by a complex interplay of meteorological conditions, biogenic processes, and, most significantly, anthropogenic activities. Recommendations and perspectives To achieve a more accurate analysis of the city carbon balance, future research should combine site data from different functional areas and ecosystem. Integrating these multi-site data will be essential for developing robust, spatially-explicit models of urban carbon metabolism and supporting more effective climate mitigation policies.