Environmental and Food Hygiene Laboratories (LIAA), Department of Medical, Surgical Sciences and Advanced Technologies "G.F. Ingrassia", University of Catania, via Santa Sofia 87, 95123, Catania, Italy.
Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Environ Sci Pollut Res Int. 2017 Mar;24(7):6426-6445. doi: 10.1007/s11356-016-8180-1. Epub 2017 Jan 4.
Even though clean air is considered as a basic requirement for the maintenance of human health, air pollution continues to pose a significant health threat in developed and developing countries alike. Monitoring and modeling of classic and emerging pollutants is vital to our knowledge of health outcomes in exposed subjects and to our ability to predict them. The ability to anticipate and manage changes in atmospheric pollutant concentrations relies on an accurate representation of the chemical state of the atmosphere. The task of providing the best possible analysis of air pollution thus requires efficient computational tools enabling efficient integration of observational data into models. A number of air quality models have been developed and play an important role in air quality management. Even though a large number of air quality models have been discussed or applied, their heterogeneity makes it difficult to select one approach above the others. This paper provides a brief review on air quality models with respect to several aspects such as prediction of health effects.
尽管清洁空气被认为是维持人类健康的基本要求，但在发达国家和发展中国家，空气污染仍然对健康构成重大威胁。对经典和新兴污染物的监测和建模对于我们了解暴露人群的健康结果以及预测这些结果的能力至关重要。预测和管理大气污染物浓度变化的能力依赖于对大气化学状态的准确描述。因此，提供对空气污染的最佳分析需要有效的计算工具，以便将观测数据有效地整合到模型中。已经开发了许多空气质量模型，并在空气质量管理中发挥着重要作用。尽管已经讨论或应用了大量空气质量模型，但它们的异质性使得很难选择一种方法优于其他方法。本文就空气质量模型在健康影响预测等方面进行了简要综述。
