土地利用/覆盖的空气污染效应分析
作者简介:许珊(1990-),女,硕士生,研究方向为土地利用/覆盖与空气污染特征变化。E-mail:936068568@qq.com
收稿日期: 2014-09-11
要求修回日期: 2014-10-28
网络出版日期: 2015-03-10
基金资助
国家自然科学基金项目(41201384)
湖南省自然科学基金项目(12JJ3034)
资源与环境信息系统国家重点实验室开放基金项目(A类)
上海市大气颗粒物污染防治重点实验室开放课题
地理空间信息工程国家测绘地理信息局重点实验室开放研究基金项目(201328、2014J07)
Impact Analysis of Land Use/Cover on Air Pollution
Received date: 2014-09-11
Request revised date: 2014-10-28
Online published: 2015-03-10
Copyright
以长株潭城市群核心区为对象,运用GIS和RS技术获取研究区土地利用/覆盖和空气污染分布格局,结合景观指数移动窗口分析结果,分年均和季节时间尺度分析NO2、PM10、O3、PM2.5浓度空间分布特征与土地利用格局的耦合关系。结果表明:长株潭城市群土地利用/覆盖,对空气污染物浓度的变化影响显著,具有季节效应。建设用地和道路面积占比与NO2、PM2.5浓度显著正相关,与O3浓度呈显著负相关;林地面积占比越大,NO2、PM2.5浓度越低;土地利用/覆盖对PM10浓度影响相对不稳定,易受不同季节局地尺度工业生产和建筑开发活动影响。从土地利用/覆盖微观配置角度,景观破碎程度越高,PM10浓度越高;散布与并列指数越大,NO2和PM2.5浓度越高、O3浓度越低;多样性指数与PM2.5浓度显著正相关。从优化土地利用降低空气污染角度创建的长株潭城市群生态绿心区的作用尚未真正展现。研究结果对明确反映土地利用/覆盖与空气污染特征间的关系,指导城市土地利用活动的合理开发具有重要的价值。
许珊 , 邹滨 , 蒲强 , 郭宇 . 土地利用/覆盖的空气污染效应分析[J]. 地球信息科学学报, 2015 , 17(3) : 290 -299 . DOI: 10.3724/SP.J.1047.2015.00290
Land use/cover changes generally have complex effects on air pollution situations. Taking Chang-Zhu-Tan urban agglomeration as an example, this study investigated how do the air pollution concentrations vary with the land use/cover changes. In this process, the land use/cover was firstly retrieved from Landsat 8 images and was consequently used to calculate and map the landscape metrics. Meanwhile, concentration surfaces of PM2.5, PM10, NO2, and O3 in January, May, August and October were generated separately with the observed data from 23 stationary sites. After that, Pearson correlation coefficient was utilized to measure the relationships between concentration surfaces and land use/cover, as well as its landscape metrics. Results reveal that the highest average NO2 concentration occurred in the built-up and road areas, while the green spaces generally had lower concentrations. This situation was almost repeated by PM2.5 concentration all through the year except in spring, but was completely opposite to that of O3. However, impacts of land use/cover on PM10 concentration are relatively undeterminable due to the locally intensive industrial activities and building constructions. Analysis of landscape metrics further demonstrates that the increased index values of Perimeter-Area Fractal Dimension (PAFRAC) and Shannon Diversity (SHDI) were basically accompanied with higher PM10 and PM2.5 concentrations, respectively. Interspersion and Juxtaposition Index (IJI) were positively correlated with the concentrations of PM10, NO2, and PM2.5, however it was found negatively correlated with O3 concentration. In addition, findings from the “Ecological Green Heart” demonstration district suggest that the optimization of land use/cover pattern contributed only slightly to the decline of air pollution concentrations in this area. Therefore, it can be concluded that the air pollution concentrations in Chang-Zhu-Tan urban agglomeration were certainly influenced by its land use/cover pattern, and rational land use development activities would be helpful for reducing the air pollution concentrations in this area.
Fig. 1 The land use/land cover map of Chang-Zhu-Tan urban agglomeration图1 长株潭城市群土地利用/覆盖图 |
Tab. 1 The area proportion of different land use/land cover types in Chang-Zhu-Tan urban agglomeration and its “Ecological Green Heart” district表1 长株潭城市群及其生态绿心区各类土地利用/覆盖类型占比 |
总面积 (km2) | 各类土地利用/覆盖类型面积占比(%) | |||||||
---|---|---|---|---|---|---|---|---|
建设用地 | 道路 | 裸地 | 耕地 | 水域 | 绿地 | 林地 | ||
长株潭城市群全区 | 3425.18 | 21.55 | 1.63 | 1.04 | 12.69 | 3.43 | 46.16 | 17.43 |
生态绿心区 | 522.87 | 11.60 | 1.06 | 0.63 | 9.31 | 4.32 | 55.08 | 18.00 |
Fig. 2 The spatial distribution patterns of landscape metrics in Chang-Zhu-Tan urban agglomeration图2 长株潭城市群景观指数空间分布格局 |
Fig. 3 The spatial distribution patterns of NO2、PM10、O3、PM2.5 concentrations in different seasons and the annual mean value in Chang-Zhu-Tan urban agglomeration图3 长株潭城市群NO2、PM10、O3、PM2.5季节和年均浓度空间分布格局 |
Fig. 4 The monthly concentration change of air pollution in Chang-Zhu-Tan urban agglomeration in 2013图4 长株潭城市群2013年空气污染浓度月均变化趋势 |
Fig. 5 Seasonal and mean annual concentrations of NO2、PM10、O3、PM2.5 under various land use/land cover types in Chang-Zhu-Tan urban agglomeration图5 长株潭城市群各类土地利用/覆盖类型NO2、PM10、O3、PM2.5季节和年均浓度统计均值(单位:ug/m3) |
Tab. 2 The correlation coefficients of air pollution concentrations and PLAND in Chang-Zhu-Tan urban agglomeration表2 长株潭城市群各类型土地占比(PLAND)与空气污染浓度的相关系数 |
NO2 | PM10 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
年均 | 春季 | 夏季 | 秋季 | 冬季 | 年均 | 春季 | 夏季 | 秋季 | 冬季 | ||
建设用地 | 0.34* | 0.31* | 0.23* | 0.22* | 0.27* | -0.08* | -0.06* | -0.02 | -0.07* | 0.03 | |
道路 | 0.21* | 0.13* | 0.19* | 0.29* | 0.07 | 0.09 | 0.05 | 0.17* | 0.11 | 0.06 | |
裸地 | -0.07 | -0.06 | -0.10 | -0.10 | 0.04 | -0.06 | -0.08 | 0.01 | -0.07 | 0.02 | |
耕地 | -0.16* | -0.15* | -0.14* | -0.14* | -0.11* | -0.07* | -0.01 | -0.16* | -0.08* | -0.08* | |
水域 | -0.03 | 0.03 | 0.04 | -0.07 | -0.06 | 0.05 | -0.04 | 0.03 | 0.06 | 0.06 | |
绿地 | -0.01 | -0.04 | -0.05* | 0.04 | 0.01 | 0.04 | 0.01 | 0.12* | 0.02 | 0.06* | |
林地 | -0.34* | -0.33* | -0.27* | -0.26* | -0.26* | 0.12* | 0.30* | -0.13* | -0.05 | 0.06 | |
O3 | PM2.5 | ||||||||||
年均 | 春季 | 夏季 | 秋季 | 冬季 | 年均 | 春季 | 夏季 | 秋季 | 冬季 | ||
建设用地 | -0.16* | -0.02 | -0.14* | -0.21* | -0.26* | 0.32* | 0 | 0.09* | 0.14* | 0.34* | |
道路 | -0.04 | -0.01 | -0.14* | 0.07 | -0.16* | 0.13* | 0 | 0.16* | -0.01 | 0.08 | |
裸地 | 0.11 | 0.14 | 0.13 | 0.04 | 0.07 | -0.07 | -0.12 | -0.19* | 0.13 | -0.02 | |
耕地 | -0.01 | -0.05 | 0.11* | 0.07* | -0.08* | -0.06 | 0.07* | -0.12* | -0.02 | -0.07* | |
水域 | 0.02 | 0.10* | 0 | 0.05 | -0.06 | 0.03 | -0.11* | -0.05 | 0.28* | -0.05 | |
绿地 | 0.08* | 0.02 | 0.03 | -0.07* | 0.29* | -0.16* | -0.06* | 0.03 | -0.22* | -0.07* | |
林地 | -0.20* | -0.31* | -0.02 | 0.16* | -0.21* | -0.19* | 0.30* | -0.14* | -0.24* | -0.26* |
*表示在0.01水平上显著相关 |
Tab. 3 The correlation coefficients of air pollution concentrations and landscape metrics in Chang-Zhu-Tan urban agglomeration表3 长株潭城市群土地利用景观指数与空气污染浓度的相关系数 |
NO2 | PM10 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
年均 | 春季 | 夏季 | 秋季 | 冬季 | 年均 | 春季 | 夏季 | 秋季 | 冬季 | ||
CONTAG | -0.02 | -0.02 | -0.05 | -0.05 | 0.09* | -0.02 | 0.04 | 0.00 | -0.04 | 0.05 | |
IJI | 0.10* | 0.11* | 0.12* | 0.07 | 0.01 | -0.05 | -0.05 | -0.04 | -0.05 | -0.05 | |
PAFRAC | -0.01 | -0.11* | 0.12* | 0.32* | -0.36* | 0.30* | 0.33* | 0.16* | 0.35* | -0.07 | |
AI | 0.00 | 0.03 | -0.02 | -0.11* | 0.11* | -0.04 | -0.06 | 0.02 | -0.08 | 0.08 | |
SHDI | 0.05 | 0.01 | 0.06 | 0.08 | -0.06 | 0.03 | -0.04 | 0.04 | 0.06 | 0.00 | |
O3 | PM2.5 | ||||||||||
年均 | 春季 | 夏季 | 秋季 | 冬季 | 年均 | 春季 | 夏季 | 秋季 | 冬季 | ||
CONTAG | 0.11* | 0.10* | 0.06 | -0.03 | 0.22* | -0.06 | -0.09* | 0.10* | -0.08 | -0.07 | |
IJI | -0.12* | -0.05 | -0.10* | 0.00 | -0.24* | 0.14* | 0.06 | 0.01 | 0.11* | 0.12* | |
PAFRAC | -0.02 | -0.10* | -0.22* | 0.28* | -0.11* | 0.04 | 0.19* | 0.17* | 0.01 | -0.11* | |
AI | 0.06 | 0.07 | 0.09* | -0.09* | 0.13* | -0.04 | -0.08 | -0.01 | -0.03 | 0.01 | |
SHDI | -0.05 | -0.02 | -0.06 | 0.06 | -0.18* | 0.13* | 0.06 | -0.08 | 0.17* | 0.11* |
*表示在0.01水平上显著相关 |
The authors have declared that no competing interests exist.
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