摘要
利用曲线拟合的方法建立了空气中PM2.5浓度以及质量的预测和评价的高斯扩散模型。模型考虑了数据相对于风力、湿度、时间的变化情况、数据之间存在着相互联系,对未来西安市PM2.5的情况进行了合理的预测。通过曲线拟合和非线性回归并利用统计软件SPSS,数学软件MATLAB、1stOpt 1.5以及绘图软件Sufer进行编程计算,给出了问题的解答:西安地区PM2.5的浓度从一月到四月逐渐降低。对西安市13个监测点四个月的PM2.5的浓度分区进行了初步污染评估:小寨和临潼区属于中度污染区;高压开关厂、兴庆小区和纺织城等9个监测点属于重度污染区;高新西区和草滩属于严重污染区。
This article was built with the method of curve fitting and PM 2.5 concentration in the air quality prediction and evaluation of Gaussian diffusion model .In the model ,account was taken into the data relative to the change of wind ,humidity ,time ,existing interconnected data ,the reasonable forecast to PM 2.5 of Xi＇an in the future has carried on .In this article ,through curve fitting and non‐linear regression and the use of the statistics software SPSS ,mathematical software MATLAB ,1st Opt 1.5 and drawing software Sufer programming calculation ,the solution of the problem was given as follows ：the concentration of PM2.5 in Xi＇an region gradually reduces from January to April ,the preliminary evaluation of 13 monitoring stations of Xi＇an ,four months PM2.5 pollution concentration zoning was carried on ：Xiaozhai and Lintong districts were attributed to moderate pollution areas ;High voltage switch factory ,Xingqing district and Textile city belong to high level of pollution of the nine monitoring areas ;Western high-tech zone end and Grass land belong to the serious pollution ar‐eas .
出处
《广西师范学院学报（自然科学版）》
2014年第4期96-102,共7页
Journal of Guangxi Teachers Education University(Natural Science Edition)
关键词
曲线拟合
偏相关分析法
高斯扩散模型
非线性规划模型
curve fitting
partial correlation analysis method
Gaussian diffusion model
nonlin-ear programming model
