National Research Council, Institute of Biometeorology (CNR-IBIMET), Via G. Caproni 8, 50145, Florence, Italy.
Institute of Ecology, University of Innsbruck, Sternwartestrasse 15, 6020, Innsbruck, Austria.
Environ Monit Assess. 2018 Feb 22;190(3):165. doi: 10.1007/s10661-018-6531-8.
CO remains the greenhouse gas that contributes most to anthropogenic global warming, and the evaluation of its emissions is of major interest to both research and regulatory purposes. Emission inventories generally provide quite reliable estimates of CO emissions. However, because of intrinsic uncertainties associated with these estimates, it is of great importance to validate emission inventories against independent estimates. This paper describes an integrated approach combining aircraft measurements and a puff dispersion modelling framework by considering a CO industrial point source, located in Biganos, France. CO density measurements were obtained by applying the mass balance method, while CO emission estimates were derived by implementing the CALMET/CALPUFF model chain. For the latter, three meteorological initializations were used: (i) WRF-modelled outputs initialized by ECMWF reanalyses; (ii) WRF-modelled outputs initialized by CFSR reanalyses and (iii) local in situ observations. Governmental inventorial data were used as reference for all applications. The strengths and weaknesses of the different approaches and how they affect emission estimation uncertainty were investigated. The mass balance based on aircraft measurements was quite succesful in capturing the point source emission strength (at worst with a 16% bias), while the accuracy of the dispersion modelling, markedly when using ECMWF initialization through the WRF model, was only slightly lower (estimation with an 18% bias). The analysis will help in highlighting some methodological best practices that can be used as guidelines for future experiments.
CO 仍然是对人为全球变暖贡献最大的温室气体，其排放量的评估对研究和监管目的都非常重要。排放清单通常可以提供相当可靠的 CO 排放量估计。然而，由于这些估计存在内在的不确定性，因此对照独立估计值验证排放清单非常重要。本文描述了一种综合方法，该方法通过考虑位于法国比加诺斯的 CO 工业点源，结合了飞机测量和烟羽扩散建模框架。通过应用质量平衡法获得了 CO 密度测量值，而 CO 排放估算则是通过实施 CALMET/CALPUFF 模型链得出的。对于后者，使用了三种气象初始化：（i）由 ECMWF 再分析初始化的 WRF 模型输出；（ii）由 CFSR 再分析初始化的 WRF 模型输出；（iii）本地现场观测。政府清单数据被用作所有应用的参考。研究了不同方法的优缺点以及它们如何影响排放估算的不确定性。基于飞机测量的质量平衡在捕捉点源排放强度方面非常成功（在最坏的情况下存在 16%的偏差），而扩散建模的准确性，特别是当通过 WRF 模型使用 ECMWF 初始化时，仅略低（估计存在 18%的偏差）。该分析将有助于突出一些方法上的最佳实践，这些实践可以作为未来实验的指南。
