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Do green spaces affect the spatiotemporal changes of PM2.5 in Nanjing?

Overview of attention for article published in Ecological Processes, May 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#16 of 262)
  • High Attention Score compared to outputs of the same age (91st percentile)

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2 news outlets
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Title
Do green spaces affect the spatiotemporal changes of PM2.5 in Nanjing?
Published in
Ecological Processes, May 2016
DOI 10.1186/s13717-016-0052-6
Pubmed ID
Authors

Jiquan Chen, Liuyan Zhu, Peilei Fan, Li Tian, Raffaele Lafortezza

Abstract

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 (R (2) > 0.85) with green cover in spring at 1-2 km scales, highly correlated (R (2) > 0.6) in autumn and winter at 4 km scale, and moderately correlated in summer (R (2) > 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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Unknown 78 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 19%
Student > Master 13 16%
Researcher 8 10%
Student > Postgraduate 5 6%
Student > Doctoral Student 4 5%
Other 9 11%
Unknown 25 32%
Readers by discipline Count As %
Environmental Science 19 24%
Agricultural and Biological Sciences 11 14%
Earth and Planetary Sciences 4 5%
Engineering 3 4%
Psychology 2 3%
Other 10 13%
Unknown 30 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 24. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 March 2022.
All research outputs
#1,417,474
of 23,365,820 outputs
Outputs from Ecological Processes
#16
of 262 outputs
Outputs of similar age
#27,205
of 337,507 outputs
Outputs of similar age from Ecological Processes
#1
of 2 outputs
Altmetric has tracked 23,365,820 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 262 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 337,507 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them