南昌市中心城区主要大气污染物分布模拟及土地利用对其影响

随着我国城市化、工业化的快速推进,城市大气污染问题日益突出,研究城市大气污染物的分布情况及其土地利用影响对解决城市大气污染问题具有重要意义.本研究以南昌市中心城区为研究区,基于土地利用回归模型(LUR)模拟了PM_2.5、PM₁₀、SO₂、NO₂、CO、O₃等6种主要大气污染物浓度,并分析其时空分布特征;基于主导土地利用类型,选择南昌市中心城区内居住、商业、教育和工业用地各15个样本区,为了减少气象因子的影响,分四季统计各样本区6类大气污染物浓度,运用双因素方差分析和多重比较,定量分析土地利用(样本区)对6类大气污染物的影响.结果表明: 采用LUR模型模拟研究区PM_2.5、PM₁₀、SO₂、NO₂、CO、O₃浓度的平均绝对误差率分别为11.9%、13.4%、12.5%、12.0%、12.7%和13.5%,模型误差较小,方法可行.研究区6类污染物浓度具有明显的时空分布特征,PM_2.5、PM₁₀、SO₂、NO₂和CO浓度在冬季最高,春季和秋季次之,夏季最低;O₃浓度则为夏季高,春季和秋季次之,冬季低.PM_2.5、PM₁₀、SO₂、NO₂、CO浓度整体呈现从城区中心到郊区递减的趋势,而O₃浓度则反之.不同季节与不同土地利用样本区间6种大气污染物浓度差异显著,表明在中心城区尺度上,气象条件和土地利用都对大气污染物有显著影响.不同土地利用对主要大气污染物浓度分布有不同程度的影响,其中,对PM_2.5、NO₂和O₃的影响较大,对CO的影响较小.

Simulation of the distribution of main atmospheric pollutants and the influence of land use on them in central urban area of Nanchang City,China

With the rapid urbanization and industrialization in China, atmospheric pollution becomes increasingly urgent. It is of great importance to examine the distribution of atmospheric pollutants and the influence of land use for sake of reducing pollution. We simulated and analyzed the temporal and spatial distribution characteristics of the six main atmospheric pollutants in the central urban area of Nanchang City, i.e. PM_2.5, PM₁₀, SO₂, NO₂, CO and O₃ based on land-use regression models (LUR). Four types of area, i.e. residential, commercial, educational and industrial area, were defined according to dominated land use type. Fifteen samples from each type were collected. The concentration of six air pollutants of fifteen sample areas for each type and each season were averaged to reduce the influence of meteorological factors. By means of double factor varian-ce analysis and multiple comparisons, we analyzed the effects of land use (expressed by sample area) on those atmospheric pollutants. The results showed that the concentrations of all the six atmospheric pollutants were well simulated by LUR model, with an average absolute error were 11.9%, 13.4%, 12.5%, 12.0%, 12.7% and 13.5% respectively. The concentration of six atmospheric pollutants showed obvious temporal and spatial distribution characteristics, with O₃ presenting the highest in summer, then spring, autumn, and winter in order, and the remaining five pollutants peaked in winter, then spring, autumn and summer in order. The concentrations of PM_2.5, PM₁₀, SO₂, NO₂ and CO showed a decreasing trend from urban center to suburb, while the concentration of O₃ was the opposite. The concentrations of varied seasons or land use sample areas were all significantly different, indicating that both meteorology and land use had significant effects on air pollution. The effects of land use on main atmospheric pollutants varied, with stronger effects on PM_2.5, NO₂ and O₃ than on CO.