Do green spaces affect the spatiotemporal changes of PM(2.5) in Nanjing?
Do green spaces affect the spatiotemporal changes of PM(2.5) in Nanjing?
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DOI：
10.1186/s13717-016-0052-6
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发表时间：
2016
影响因子：
4.8
通讯作者：
Lafortezza R
中科院分区：
文献类型：
--
作者：
Chen J;Zhu L;Fan P;Tian L;Lafortezza R
其中最危险的污染物是PM2.5，它可以直接通过人体肺部进入血液系统。使用基于自然的解决方案，例如增加城市景观中的植被覆盖，是降低PM2.5浓度的可能解决方案之一。我们的研究目的是了解绿色空间在减少污染方面的重要性。为定量分析南京市PM2. 5浓度的时空变化及其与植被和景观结构的经验关系，采用人工采集的方法，对南京市9个监测站534 d的PM2. 5浓度进行了分析。9个监测站的日平均、最小和最大PM2.5浓度分别为74.0、14.2和332.0 μg m-3。在这534天中，记录为“优秀”和“良好”条件的天数主要出现在春季（30.7%）、秋季（25.6%）和夏季（24.5%），冬季只有19.2%。超过CNEMC安全标准的高PM2.5浓度主要发生在冬季（39.3- 100.0%）。我们的假设，绿色植被有潜力降低PM2.5浓度被接受在特定的季节和尺度。在1-2 km尺度上，春季PM2.5浓度与绿色覆盖高度相关（R2 > 0.85）;在4 km尺度上，秋季和冬季PM2.5浓度与绿色覆盖高度相关（R2> 0.6）;然而，当绿色覆盖水平>75 μg m−3时，发现其与PM2.5浓度之间的相关性不显著。从南京城市景观来看，东部和西南部的污染水平较高。虽然经验模型似乎只对春季有意义，但人们不应该贬低绿色植被在其他季节的重要性，因为植被，气象条件和人类活动往往使规则复杂化。
Among the most dangerous pollutants is PM2.5, which can directly pass through human lungs and move into the blood system. The use of nature-based solutions, such as increased vegetation cover in an urban landscape, is one of the possible solutions for reducing PM2.5 concentration. Our study objective was to understand the importance of green spaces in pollution reduction. Daily PM2.5 concentrations were manually collected at nine monitoring stations in Nanjing over a 534-day period from the air quality report of the China National Environmental Monitoring Center (CNEMC) to quantify the spatiotemporal change of PM2.5 concentration and its empirical relationship with vegetation and landscape structure in Nanjing. The daily average, minimum, and maximum PM2.5 concentrations from the nine stations were 74.0, 14.2, and 332.0 μg m−3, respectively. Out of the 534 days, the days recorded as “excellent” and “good” conditions were found mostly in the spring (30.7 %), autumn (25.6 %), and summer (24.5 %), with only 19.2 % of the days in the winter. High PM2.5 concentrations exceeding the safe standards of the CNEMC were recorded predominately during the winter (39.3–100.0 %). Our hypothesis that green vegetation had the potential to reduce PM2.5 concentration was accepted at specific seasons and scales. The PM2.5 concentration appeared very highly correlated (R2 > 0.85) with green cover in spring at 1–2 km scales, highly correlated (R2 > 0.6) in autumn and winter at 4 km scale, and moderately correlated in summer (R2 > 0.4) at 2-, 5-, and 6-km scales. However, a non-significant correlation between green cover and PM2.5 concentration was found when its level was >75 μg m−3. Across the Nanjing urban landscape, the east and southwest parts had high pollution levels. Although the empirical models seemed significant for spring only, one should not devalue the importance of green vegetation in other seasons because the regulations are often complicated by vegetation, meteorological conditions, and human activities.