Miles Natasha L, Davis Kenneth J, Richardson Scott J, Lauvaux Thomas, Martins Douglas K, Deng A J, Balashov Nikolay, Gurney Kevin R, Liang Jianming, Roest Geoff, Wang Jonathan A, Turnbull Jocelyn C
Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, PA, 16802, USA.
Earth and Environmental Systems Institute, The Pennsylvania State University, University Park, PA, 16802, USA.
Carbon Balance Manag. 2021 Jan 30;16(1):4. doi: 10.1186/s13021-020-00166-z.
Networks of tower-based CO mole fraction sensors have been deployed by various groups in and around cities across the world to quantify anthropogenic CO emissions from metropolitan areas. A critical aspect in these approaches is the separation of atmospheric signatures from distant sources and sinks (i.e., the background) from local emissions and biogenic fluxes. We examined CO enhancements compared to forested and agricultural background towers in Indianapolis, Indiana, USA, as a function of season and compared them to modeled results, as a part of the Indianapolis Flux (INFLUX) project.
At the INFLUX urban tower sites, daytime growing season enhancement on a monthly timescale was up to 4.3-6.5 ppm, 2.6 times as large as those in the dormant season, on average. The enhancement differed significantly depending on choice of background and time of year, being 2.8 ppm higher in June and 1.8 ppm lower in August using a forested background tower compared to an agricultural background tower. A prediction based on land cover and observed CO fluxes showed that differences in phenology and drawdown intensities drove measured differences in enhancements. Forward modelled CO enhancements using fossil fuel and biogenic fluxes indicated growing season model-data mismatch of 1.1 ± 1.7 ppm for the agricultural background and 2.1 ± 0.5 ppm for the forested background, corresponding to 25-29% of the modelled CO enhancements. The model-data total CO mismatch during the dormant season was low, - 0.1 ± 0.5 ppm.
Because growing season biogenic fluxes at the background towers are large, the urban enhancements must be disentangled from the biogenic signal, and growing season increases in CO enhancement could be misinterpreted as increased anthropogenic fluxes if the background ecosystem CO drawdown is not considered. The magnitude and timing of enhancements depend on the land cover type and net fluxes surrounding each background tower, so a simple box model is not appropriate for interpretation of these data. Quantification of the seasonality and magnitude of the biological fluxes in the study region using high-resolution and detailed biogenic models is necessary for the interpretation of tower-based urban CO networks for cities with significant vegetation.
世界各地的不同团队已在城市及其周边部署了基于高塔的一氧化碳摩尔分数传感器网络，以量化大都市区的人为一氧化碳排放量。这些方法的一个关键方面是将来自遥远源和汇（即背景）的大气特征与本地排放和生物源通量区分开来。作为印第安纳波利斯通量（INFLUX）项目的一部分，我们研究了美国印第安纳州印第安纳波利斯市与森林和农业背景塔相比的一氧化碳增强情况，作为季节的函数，并将其与模拟结果进行比较。
在INFLUX城市塔站点，生长季白天每月时间尺度上的增强量高达4.3 - 6.5 ppm，平均是休眠季的2.6倍。增强量因背景选择和年份时间的不同而有显著差异，与农业背景塔相比，使用森林背景塔时，6月的增强量高2.8 ppm，8月低1.8 ppm。基于土地覆盖和观测到的一氧化碳通量的预测表明，物候和吸收强度的差异导致了测量到的增强量差异。使用化石燃料和生物源通量进行的正向模拟一氧化碳增强表明，对于农业背景，生长季模型 - 数据不匹配为1.1±1.7 ppm，对于森林背景为2.1±0.5 ppm，分别对应模拟一氧化碳增强量的25 - 29%。休眠季模型 - 数据的总一氧化碳不匹配较低，为 - 0.1±0.5 ppm。
由于背景塔处生长季的生物源通量很大，必须将城市增强量与生物源信号区分开来，如果不考虑背景生态系统的一氧化碳吸收，生长季一氧化碳增强量的增加可能会被误解为增加的人为通量。增强量的大小和时间取决于每个背景塔周围的土地覆盖类型和净通量，因此简单的箱式模型不适用于解释这些数据。对于有大量植被的城市，使用高分辨率和详细的生物源模型来量化研究区域生物通量的季节性和大小，对于解释基于高塔的城市一氧化碳网络是必要的。
