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

doi:10.13287/j.1001-9332.201903.010

摘要/Abstract

摘要： 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.

关键词: 大气污染物, 土地利用回归模型, 土地利用样本区, 中心城区

Abstract: 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.

Key words: land-use regression (LUR) models, land use sample area, central urban area, atmospheric pollutant

梁照凤, 陈文波, 郑蕉, 卢陶捷. 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[J]. 应用生态学报, 2019, 30(3): 1005-1014.

LIANG Zhao-feng, CHEN Wen-bo, ZHENG Jiao, LU Tao-jie. Simulation of the distribution of main atmospheric pollutants and the influence of land use on them in central urban area of Nanchang City, China[J]. Chinese Journal of Applied Ecology, 2019, 30(3): 1005-1014.

参考文献

[1] China Association of Mayors (中国市长协会). The Report of 2013-2014 China Urban Development. Beijing: China City Press, 2014 (in Chinese)
[2] Liu L-L (刘乐乐), Zhao X-F (赵小锋), Zhao Y-C (赵颜创), et al. Ningbo atmospheric environment ana-lysis and regulating countermeasure based on Urban Climatic Map. Acta Ecologica Sinica (生态学报), 2017, 37(2): 606-618 (in Chinese)
[3] Environmental Protection Department of the People’s Republic of China (中华人民共和国环境保护部). 2013 Environmental Status bulletin: Atmospheric envi-ronment [EB/OL]. (2014-06-05) [2017-12-15]. http://www.zhb.gov.cn/hjzl/zghjzkgb/lssj/2013nzghjzkgb/.html (in Chinese)
[4] Wang T, Jiang F, Deng J, et al. Urban air quality and regional haze weather forecast for Yangtze River Delta region. Atmospheric Environment, 2012, 58: 70-83
[5] Kelly FJ, Fussell JC. Air pollution and public health: Emerging hazards and improved understanding of risk. Environmental Geochemistry and Health, 2015, 37: 631-649
[6] Shi Y (史宇), Zhang J-H (张建辉), Luo H-J (罗海江), et al. Analysis of characteristics of atmospheric particulate matter pollution in Beijing during the fall and winter of 2012 to 2013. Ecology and Environmental Sciences (生态环境学报), 2013, 22(9): 1571-1577 (in Chinese)
[7] Gorai AK, Tuluri F, Tchounwou PB. A GIS based approach for assessing the association between air pollution and asthma in New York State, USA. International Journal of Environmental Research and Public Health, 2014, 11: 4845-4869
[8] Su W (苏维), Zhang S-J (张帅珺), Lai X-Y (赖新云), et al. Spatiotemporal dynamics of atmospheric PM_2.5 and PM₁₀ and its influencing factors in Nanchang, China. Chinese Journal of Applied Ecology (应用生态学报), 2017, 28(1): 257-265 (in Chinese)
[9] Martins H, Miranda AI, Borrego C. Atmospheric Modelling Under Urban Land Use Changes: Meteorological and Air Quality Consequences. Dordrecht: Springer, 2012
[10] Aziz A, Anjum GA. Sensitizing land uses to control motor vehicular air pollution: A case study of Lahore in connection with Paris. Environmental Modelling & Assessment, 2016, 21: 419-435
[11] Zhang R-S (张润森), Pu L-J (濮励杰), Liu Z (刘振). Advances in research on atmospheric environment effects of land use and land cover change. Areal Research and Development (地域研究与开发), 2013, 32(4): 123-128 (in Chinese)
[12] Yan S, Cao H, Chen Y, et al. Spatial and temporal characteristics of air quality and air pollutants in 2013 in Beijing. Environmental Science and Pollution Research, 2016, 23: 13996-14007
[13] Jia M-W (贾梦唯), Zhao T-L (赵天良), Zhang X-Z (张祥志), et al. Seasonal variations in major air pollutants in Nanjing and their meteorological correlation analyses. China Environmental Science (中国环境科学), 2016, 36(9): 2567-2577 (in Chinese)
[14] Ching JKS. A perspective on urban canopy layer modeling for weather, climate and air quality application. Urban Climate, 2013, 3: 13-39
[15] Yan Y-L (闫雨龙), Wen Y-P (温彦平), Feng X-Y (冯新宇), et al. Variation and the influence factors of ozone in urban area in Taiyuan. Environmental Chemistry (环境化学), 2016, 35(11): 2261-2268 (in Chinese)
[16] Jiang X-H (姜新华), Liu X (刘霞), Xue H-R (薛河儒), et al. Analysis of air quality based on stepwise regression method: Take Huhhot City for instance. Journal of Inner Mongolia Agricultural University (Natural Science) (内蒙古农业大学学报:自然科学版), 2015, 36(2): 123-126 (in Chinese)
[17] Li M-S (李名升), Sun Y (孙媛), Chen Y-H (陈远航), et al. Establishment and application of pollutant discharge: Environment quality model. Environmental Science (环境科学), 2014, 35(3): 1198-1204 (in Chinese)
[18] Xie W-D (谢舞丹), Wu J-S (吴健生). Effects of land use and urban landscape pattern on PM_2.5 concentration: A Shenzhen case study. Acta Scientiarum Naturalium Universitatis Pekinensis (北京大学学报:自然科学版), 2017, 53(1): 160-170 (in Chinese)
[19] Wei J (韦晶), Sun L (孙林), Liu S-S (刘双双), et al. Response analysis of particulate air pollution to land-use and land-cover change. Acta Ecologica Sinica (生态学报), 2015, 35)16): 5495-5506 (in Chinese)
[20] Tang Y-K (唐昀凯), Liu S-H (刘胜华).Research on the correlation between urban land use types and PM_2.5 concentrations in Wuhan. Resources and Environment in the Yangtze Basin (长江流域资源与环境), 2015, 24(9): 1458-1463 (in Chinese)
[21] Liang Z-F (梁照凤), Chen W-B (陈文波), Zheng J (郑蕉). Influence of land intensive use level on main atmospheric pollutants in the central urban area of Nanchang City, China. Chinese Journal of Applied Ecology (应用生态学报), 2018, 29(5): 1705-1714 (in Chinese)
[22] Xu S (许珊), Zou B (邹滨), Pu Q (蒲强), et al. Impact analysis of land use/cover on air pollution. Journal of Geo-information Science (地球信息科学学报), 2015, 17(3): 290-299 (in Chinese)
[23] Kanaroglou PS, Soulakellis NA, Sifakis NI. Improvement of satellite derived pollution maps with the use of a geostatistical interpolation method. Journal of Geographi-cal Systems, 2002, 4: 193-208
[24] Yu M, Carmichael GR, Zhu T, et al. Sensitivity of predicted pollutant levels to anthropogenic heat emissions in Beijing. Atmospheric Environment, 2014, 89: 169-178
[25] Jiao L-M (焦利民), Xu G (许刚), Zhao S-L (赵素丽), et al. LUR-based simulation of the spatial distribution of PM_2.5 of Wuhan. Geomatics and Information Science of Wuhan University (武汉大学学报:信息科学版), 2015, 40(8): 1088-1094 (in Chinese)
[26] Wu J-S (吴健生), Xie W-D (谢舞丹), Li J-C (李嘉诚). Application of land-use regression models in spatial-temporal differentiation of air pollution. Environment Science (环境科学), 2016, 37(2): 413-419 (in Chinese)
[27] Geng R-Z (耿润哲), Yin P-H (殷培红), Yuan Q-D (原庆丹). Zonation for nonpoint source pollution control in Hongfenghu Reservoir watershed. Transactions of the Chinese Society of Agricultural Engineering (农业工程学报), 2016, 32(19): 219-225 (in Chinese)
[28] Wang H-Z (王会芝). Temporal-spatial distribution characteristics and influencing factors of atmospheric PM_2.5 in Tianjin. Urban Environment & Urban Ecology (城市环境与城市生态), 2016, 29(4): 12-14 (in Chinese)
[29] Yang H-O (阳海鸥), Chen W-B (陈文波), Liang Z-F (梁照凤). Relationship of PM_2.5 concentration and land use type in Nanchang City based on LUR simulation. Transactions of the Chinese Society of Agricultural Engineering (农业工程学报), 2017, 33(6): 232－239 (in Chinese)
[30] Han R-Y (汉瑞英), Chen J (陈健), Wang L (王彬). Application of LUR models for simulating the spatial distribution of PM_2.5 concentration in Hangzhou, China. Acta Scientiae Circumstantiae (环境科学学报), 2016, 36(9): 3379-3385 (in Chinese)
[31] Hoek G, Beelen R, De Hoogh K, et al. A review of land-use regression models to assess spatial variation of outdoor air pollution. Atmospheric Environment, 2008, 42: 7561-7578
[32] Chongqing Energy Conservation Network (重庆节能网). Rules for Evaluation of Intensive Use of Construction Land (TD/T 1018-2008) [EB/OL]. (2018-05-28) [2018-12-27]. http://www.cqjnw.org/article.php?id=12858/.html (in Chinese)
[33] Zhou H-J (周海军), Liu T (刘涛), Ren L-M (任丽敏), et al. Characteristics of atmospheric pollutants and influencing factors in Baotou. Research of Environmental Sciences (环境科学研究), 2017, 30(2): 202-213 (in Chinese)
[34] Zou B (邹滨), Xu S (许珊), Zhang J (张静). Spatial variation analysis of urban air pollution using GIS: A land use perspective. Geomatics and Information Science of Wuhan University (武汉大学学报:信息科学版), 2017, 42(2): 216-222 (in Chinese)
[35] Yan Y-L (闫雨龙), Wen Y-P (温彦平), Feng X-Y (冯新宇), et al. Variation and the influence factors of ozone in urban area in Taiyuan. Environmental Chemistry (环境化学), 2016, 35(11): 2261-2268 (in Chinese)
[36] Shi Y-Y (施媛媛), Li D-R (李仁东), Qiu J (邱娟), et al. Spatial distribution simulation and underlying surface factors analysis of NO₂ concentration based on land use regression. Journal of Geo-information Science (地球信息科学学报), 2017, 19(1): 10-19 (in Chinese)
[37] Zhu H-X (朱红霞), Zhao S-L (赵淑莉), Kan H-D (阚海东). Distribution characteristics of main atmospheric pollutants concentration in Chinese typical cities in 2013. Environmental Science & Technology (环境科学与技术), 2015, 38(6): 227-233 (in Chinese)
[38] Weber N, Haase D, Franck U. Assessing modelled outdoor traffic-induced noise and air pollution around urban structures using the concept of landscape metrics. Landscape and Urban Planning, 2014, 125: 105-116