Abstract. Ammonia (NH₃) is a major source of nitrates in the atmosphere, and a major source of fine particulate matter. As such, there have been increasing efforts to measure the atmospheric abundance of NH₃ and its spatial and temporal variability. In this study, long-term measurements of NH₃ derived from multiscale datasets are examined. These NH₃ datasets include 16 years of total column measurements using Fourier transform infrared (FTIR) spectroscopy, three years of surface in-situ measurements, and 10 years of total column measurements from the Infrared Atmospheric Sounding Interferometer (IASI). The datasets were used to quantify NH₃ temporal variability over Toronto, Canada. The multiscale datasets were also compared to assess the observational footprint of the FTIR measurements. All three time series showed positive trends in NH₃ over Toronto: 3.34 ± 0.46 %/year from 2002 to 2018 in the FTIR columns, 8.88 ± 2.83 %/year from 2013 to 2017 in the surface in-situ data, and 8.38 ± 0.77 %/year from 2008 to 2018 in the IASI columns. To assess the observational footprint of the FTIR NH₃ columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was obtained with coincidence criteria of ≤ 25 km and ≤ 20 minutes, with r = 0.73 and a slope of 1.14 ± 0.06. Additionally, FTIR column and in-situ measurements were standardized and correlated. Comparison of 24-day averages and monthly averages resulted in correlation coefficients of r = 0.72 and r = 0.75, respectively, although correlation without resampling to reduce high-frequency variability led to a poorer correlation, with r = 0.39. The GEOS-Chem model, run at 2° × 2.5° resolution, was compared against FTIR and IASI to assess model performance and investigate correlation of observational data and model output, both with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (a domain spanning 35° N to 53° N, and 93.75° W to 63.75° W) resulted in r = 0.57, and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r² = 0.33, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r² = 0.13, indicating that a finer spatial resolution is needed for modeling NH₃.

中文翻译：

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加拿大多伦多附近的NH ₃多尺度观测

摘要。氨（NH ₃）是大气中硝酸盐的主要来源，也是细颗粒物的主要来源。因此，人们越来越努力地测量大气中NH _3的丰度及其时空变异性。在这项研究中，检查了从多尺度数据集中得出的NH ₃的长期测量值。这些NH ₃数据集包括使用傅里叶变换红外（FTIR）光谱进行16年的总色谱柱测量，进行表面原位测量的3年以及使用红外大气探测干涉仪（IASI）进行的色谱柱测量的总时间为10年。数据集用于量化NH ₃加拿大多伦多的时间变化。还比较了多尺度数据集，以评估FTIR测量的观测足迹。这三个时间序列均显示出多伦多的NH ₃呈正趋势：FTIR色谱柱从2002年至2018年为3.34±0.46％/年，2013年至2017年为地表原位数据为8.88±2.83％/年，以及8.38±0.77 IASI列中从2008年到2018年的百分比/年。为了评估FTIR NH ₃色谱柱的观测足迹，检查了数据集之间的相关性。用的≤25公里巧合标准和≤20分钟，得到的FTIR和IASI之间的最佳相关性，与ř = 0.73，斜率为1.14±0.06。此外，FTIR色谱柱和原位测量已标准化并关联。比较24天平均值和月平均值时，相关系数分别为r  = 0.72和r  = 0.75，尽管没有重新采样以降低高频可变性的相关导致较差的相关，r  = 0.39。将以2°×2.5°的分辨率运行的GEOS-Chem模型与FTIR和IASI进行了比较，以评估模型性能并研究观测数据与模型输出的相关性，包括局部柱测量（FTIR）和区域范围的测量（ IASI）。在区域范围比较（93.75°W到63.75°W域跨越35°N〜53°N，和）导致ř = 0.57，因此确定系数（表示模型的预测能力）为r ²  = 0.33，但是将单个模型网格点与FTIR进行比较会得出较差的相关性，其中r ²  = 0.13，表明建模NH ₃需要更好的空间分辨率。