模拟亚洲新污染物的大气化学和远距离迁移
Modelling atmospheric chemistry and long-range transport of emerging Asian pollutants
摘要：
建模是科学过程的一个非常重要的工具，需要长期的奉献、渴望和不断的反思。在这项工作中，我们讨论了建模的几个方面，以及这样做的原因。我们讨论了两个主要的建模系统，我们已经建立了在过去的10年。这是一个漫长而艰巨的过程，但理解的回报可能是巨大的，正如本书中的例子所展示的那样。我们发现，远程传输的新兴亚洲污染物可以解释使用拉格朗日框架风分析。更详细的过程仍然需要建模，但风结构的准确表示是最重要的事情。我们的长期化学积分揭示了IMS模式在气候尺度上模拟对流层化学的能力。这些长期的整合也为进一步的模型开发指明了方向。建模是一个定量的过程，只有当理论在模型中得到有力的检验，并与高质量的测量结果进行比较时，理解才能持续下去。我们也不应该忽视数据可视化技术的重要性。人类在看到事物时会感到更自信。因此，建模是一个令人难以置信的旅程，结合数据收集，理论制定，详细的计算机编码和利用计算机的力量。最好的还在后面。
英文摘要：
Modeling is a very important tool for scientific processes, requiring long-term dedication, desire, and continuous reflection. In this work, we discuss several aspects of modeling, and the reasons for doing it. We discuss two major modeling systems that have been built by us over the last 10 years. It is a long and arduous process but the reward of understanding can be enormous, as demonstrated in the examples shown in this work. We found that long-range transport of emerging Asian pollutants can be interpreted using a Lagrangian framework for wind analysis. More detailed processes still need to be modeled but an accurate representation of the wind structure is the most important thing above all others. Our long-term chemistry integrations reveal the capability of the IMS model in simulating tropospheric chemistry on a climate scale. These long-term integrations also show ways for further model development. Modeling is a quantitative process, and the understanding can be sustained only when theories are vigorously tested in the models and compared with high quality measurements. We should also not over look the importance of data visualization techniques. Humans feel more confident when they see things. Hence, modeling is an incredible journey, combining data collection, theoretical formulation, detailed computer coding and harnessing computer power. The best is yet to come.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
