Filonchyk Mikalai1, YAN Hao-wen2, Hurynovich Volha1, Stroi Anton3
（1. School of Environmental and Municipal Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China； 2. Department of Geographic Information Science, Lanzhou Jiaotong University, Lanzhou 730070, China； 3. School of Mathematics and Physics, Lanzhou Jiaotong University, Lanzhou 730070, China）
Abstract： In this article the approach was used to coherent assessment based on the intensity of air pollution sources impact on the impurity concentration at a few fixed points to monitor air quality. The numerical analogue of Duhamel's theorem was used to describe processes of propagation of impurity in the atmosphere. Such approach allows you to count on essential increase of calculation accuracy based on mathematical models of reasonable complexity. The inverse problem of pollutants propagation in the atmosphere based on the measurements of the impurity concentration in stationary or mobile control points was solved by the sequential function approximation. The solution was presented in the form of a digital filter.
Key words： air pollution; inverse problem; sequential function approximation; the equation of turbulent diffusion
CLD number： X830.2 Document code： A
Article ID： 1674-8042（2016）04-0375-04 doi： 10.3969/j.issn.1674-8042-2016-04-011
References
［1］Schnoor J L. Environmental modeling: fate and transport of pollutants in water, air, and soil. John Wiley and Sons, 1997, (3)： F9.
［2］Perdew J P. Density-functional approximation for the correlation energy of the inhomogeneous electron gas. Physical Review B, 1986, 33(12)： 8822.
［3］Gurney W, Nisbet R M. Ecological dynamics. New York： Oxford University Press, 1998.
［4］Salant R F, Cao B. Unsteady analysis of a mechanical seal using Duhamel’s method. Journal of tribology, 2005, 127(3)： 623-631.
［5］Thompson L G, Reynolds A C. Analysis of variable-rate well-test pressure data using Duhamel’s principle. SPE formation evaluation, 1986, 1(5)： 453-469.
［6］Golub G H, Van Loan C F. Matrix computations. Baltimore： Johns Hopkins University Press, 2012.
［7］Friedman J H. Greedy function approximation： a gradient boosting machine. Annals of statistics, 2001, 29(5)： 1189-1232.
［8］Beck J V, Blackwell B, Clair Jr C R S. Inverse heat conduction： III-posed problems. Wiley, 1985.
［9］Ministry of Environmental Protection of the People’s Republic of China. China National Ambient Air Quality Standards. Beijing: Ministry of Environmental Protection, 2012.
基于连续函数近似法的空气污染源管控
Filonchyk Mikalai1, 闫浩文2, Hurynovich Volha1, Stroi Anton3
（1. 兰州交通大学 环境与市政工程学院， 甘肃 兰州 730070； 2. 兰州交通大学 测绘与地理信息学院， 甘肃 兰州 730070； 3. 兰州交通大学 数理学院， 甘肃 兰州 730070）
摘要： 本文根据空气污染源强度对杂质浓度影响的一致性评价方法， 在几个固定点监测空气质量。 在对空气中杂质传播过程的描述当中运用Duhamel定理的数值模拟。 这种方法以合理复杂性的数学模型为基础， 使模拟结果的准确性得到增加。 根据静止或移动控制点中杂质浓度的测量结果， 使污染物在大气中传播的逆问题通过顺序函数的近似值得以解决， 且该解决方案以数字滤波器的形式提出。
关键词： 空气污染; 反问题; 连续函数近似法; 湍流扩散方程
引用格式：Filonchyk Mikalai, YAN Hao-wen, Hurynovich Volha, et al. Control of air pollution sources based on method of consecutive functional approximation. Journal of Measurement Science and Instrumentation, 2016, 7(4)： 375-378. ［doi： 10.3969／j.issn.1674-8042.2016-04-011］
[full text view]
