Advertisement

Environmental Science and Pollution Research

, Volume 26, Issue 3, pp 2314–2327 | Cite as

Field assessment of the effects of land-cover type and pattern on PM10 and PM2.5 concentrations in a microscale environment

  • Shuxin Fan
  • Xiaopeng Li
  • Li DongEmail author
Research Article
  • 38 Downloads

Abstract

The microscale environment is a very important human-scale outdoor spatial unit. Aimed at investigating the effects of microscale land-cover type and pattern on levels of PM10 and PM2.5, we monitored PM10 and PM2.5 concentrations among different land-cover type and pattern sites through field measurements, during four seasons (December 2015 to November 2016) in Beijing, China. Differences of daily PM10 and PM2.5 concentrations among seven typical land-cover types, and correlations between daily two-sized PM levels and various microscale land-cover patterns as explained by landscape metrics were analyzed. Results show that concentrations of the two-sized particles had stable daytime and seasonal trends. During the four seasons, there were various differences in daily PM10 and PM2.5 levels among the seven land-cover types. Overall, bare soil always had the highest daily PM10 level, whereas high canopy density vegetation and water bodies had low levels. Maximum PM2.5 levels were always found in high canopy density vegetation. Moderate canopy density vegetation and water bodies had lower concentrations. Correlations between different landscape metrics and daily levels of two-sized PM varied by season. Metrics reflecting the dominance and distribution of land-cover classifications had closer relationships with particle concentrations in the microscale environment. The patterns of pavement along with low and moderate canopy density vegetation had a greater impact on PM10 level. The responses of PM2.5 level to patterns of building and low and moderate canopy density vegetation were sensitive. Reasonable design of land-cover structure would be conducive to ameliorate air particle concentrations in the microscale environment.

Graphical abstract

Keywords

Microscale environment PM10 PM2.5 Land-cover type Land-cover pattern 

Notes

Acknowledgments

We thank Yu Cao, Jing Han, Yu Cai, Rui Jing, Jia Guo, and Shimingyue Qi for their help with monitoring data processing.

Funding

This work was financially supported by the Special Fund for Beijing Common Construction Project.

Supplementary material

11356_2018_3697_MOESM1_ESM.docx (17 kb)
ESM 1 (DOCX 16 kb)
11356_2018_3697_MOESM2_ESM.docx (17 kb)
ESM 2 (DOCX 16 kb)

References

  1. Beckett KP, FreerSmith PH, Taylor G (1998) Urban woodlands: their role in reducing the effects of particulate pollution. Environ Pollut 99:347–360CrossRefGoogle Scholar
  2. Beijing Meteorological Bureau (2017) Climatic characteristics of Beijing 2016. http://www.bjmb.gov.cn/info/842/4960266.html. Accessed 13 Jan 2017
  3. Brantley HL, Hagler GSW, Parikshit JD, Baldauf RW (2014) Field assessment of the effects of roadside vegetation on near-road black carbon and particulate matter. Sci Total Environ 468-469:120–129CrossRefGoogle Scholar
  4. Buccolieri R, Gromke C, Di SS, Ruck B (2009) Aerodynamic effects of trees on pollutant concentration in street canyons. Sci Total Environ 407:5247–5256CrossRefGoogle Scholar
  5. Buccolieri R, Sandberg M, Sabatino SD (2010) City breathability and its link to pollutant concentration distribution within urban-like geometries. Atmos Environ 44:1894–1903CrossRefGoogle Scholar
  6. Cavanagh JAE, Zawarreza P, Wilson JG (2009) Spatial attenuation of ambient particulate matter air pollution within an urbanised native forest patch. Urban For. Urban Green 8:21–30CrossRefGoogle Scholar
  7. Dimitriou K, Kassomenos P (2014) Local and regional sources of fine and coarse particulate matter based on traffic and background monitoring. Theor Appl Climatol 116:413–433CrossRefGoogle Scholar
  8. Escobedo FJ, Nowak DJ (2009) Spatial heterogeneity and air pollution removal by an urban forest. Landsc Urban Plan 90:102–110CrossRefGoogle Scholar
  9. Franzetti A, Gandolfi I, Gaspari E, Ambrosini R, Bestetti G (2011) Seasonal variability of bacteria in fine and coarse urban air particulate matter. Appl Microbiol Biotechnol 90:745–753CrossRefGoogle Scholar
  10. Freersmith PH, Beckett KP, Taylor G (2005) Deposition velocities to sorbus aria, acercampestre, populusdeltoides x trichocarpa ‘beaupre’, pinusnigra and x cupressocyparisleylandii for coarse, fine and ultra-fine particles in the urban environment. Environ Pollut 113:157–167CrossRefGoogle Scholar
  11. Garcia JNPM, Cerdeira RSDS, Tavares NA, Coelho LMR (2012) Studying street geometry influence in pm10 concentration. Int J Environ Pollut 50:283–292CrossRefGoogle Scholar
  12. Grimm NB, Faeth SH, Golubiewski NE, Redman CL, Wu J, Bai X, Briggs JM (2008) Global change and the ecology of cities. Science 319:756–760CrossRefGoogle Scholar
  13. Guo Y, Feng N, Christopher SA, Kang P, Zhan FB, Hong S (2014) Satellite remote sensing of fine particulate matter (pm) air quality over Beijing using modis. Int J Remote Sens 35:6522–6544CrossRefGoogle Scholar
  14. Hagler GS, Lin MY, Khlystov A, Baldauf RW, Isakov V, Faircloth J, Jackson LE (2012) Field investigation of roadside vegetative and structural barrier impact on near-road ultrafine particle concentrations under a variety of wind conditions. Sci Total Environ 419:7–15CrossRefGoogle Scholar
  15. Hallquist M, Wenger JC, Baltensperger U, Rudich Y, Simpson D, Claeys M, Dommen J, Donahue NM, George C, Goldstein AH, Hamilton JF, Herrmann H, Hoffmann T, Iinuma Y, Jang M, Jenkin M, Jimenez JL, Kiendler-Scharr A, Maenhaut W, McFiggans G, Mentel TF, Monod A, Prévôt ASH, Seinfeld JH, Surratt JD, Szmigielski R, Wildt J (2009) The formation, properties and impact of secondary organic aerosol: current and emerging issues. Atmos Chem Phys 9:5155–5236CrossRefGoogle Scholar
  16. Han L, Zhou W, Li W, Meshesha DT, Li L, Zheng M (2015) Meteorological and urban landscape factors on severe air pollution in Beijing. J Air Waste Manage Assoc 65:782–787CrossRefGoogle Scholar
  17. Hang J, Li Y, Sandberg M, Buccolieri R, Sabatino SD (2012) The influence of building height variability on pollutant dispersion and pedestrian ventilation in idealized high-rise urban areas. Build Environ 56:346–360CrossRefGoogle Scholar
  18. Hoek G, Beelen R, Hoogh KD, Vienneau D, Gulliver J, Fischer P, Briggs D (2008) A review of land-use regression models to assess spatial variation of outdoor air pollution. Atmos Environ 42:7561–7578CrossRefGoogle Scholar
  19. Janhäll S (2015) Review on urban vegetation and particle air pollution – deposition and dispersion. Atmos Environ 105:130–137CrossRefGoogle Scholar
  20. Karagiannidis A, Poupkou A, Giannaros T, Giannaros C, Melas D, Argiriou A (2015) The air quality of a mediterranean urban environment area and its relation to major meteorological parameters. Water Air Soil Pollut 226:1–13CrossRefGoogle Scholar
  21. Kashima S, Yorifuji T, Tsuda T, Doi H (2009) Application of land use regression to regulatory air quality data in Japan. Sci Total Environ 407:3055–3062CrossRefGoogle Scholar
  22. Li W (2015) Meteorological and urban landscape factors on severe air pollution in Beijing. J Air Waste Manage Assoc 65:782–787CrossRefGoogle Scholar
  23. Litschke T, Kuttler W (2008) On the reduction of urban particle concentration by vegetation – a review. Meteorol Z 17:229–240CrossRefGoogle Scholar
  24. Lou C, Liu H, Li Y, Li Y (2016) Research on the response of air particles ( pm2.5、pm10) to landscape structure: a review. Acta Ecol Sin 36:6719–6729Google Scholar
  25. Luo N, Zhao W, Xing Y, Gong Z, Xiong Q (2013) Study on influence of traffic and meteorological factors on inhalable particle matters of different size. Environ Sci 34:3741–3748Google Scholar
  26. Masiol M, Squizzato S, Rampazzo G, Pavoni B (2014) Source apportionment of PM 2.5, at multiple sites in Venice (Italy): spatial variability and the role of weather. Atmos Environ 98:78–88CrossRefGoogle Scholar
  27. McGarigal K, Cushman MCN, Ene E (2002) FRAGSTATS: spatial pattern analysis program for categorical maps. Computer software program produced by the authors at the University of Massachusetts–Amherst. http://www.umass.edu/landeco/research/fragstats/fragstats.html
  28. Mei D, Deng Q, Wen M, Fang Z (2016) Evaluating dust particle transport performance within urban street canyons with different building heights. Aerosol Air Qual Res 16:1483–1496CrossRefGoogle Scholar
  29. Pakbin P, Hudda N, Cheung KL, Moore KF, Sioutas C (2010) Spatial and temporal variability of coarse (PM10 − 2.5) particulate matter concentrations in the Los Angeles area. Aerosol Sci Technol 44:514–525CrossRefGoogle Scholar
  30. Pant P, Harrison RM (2013) Estimation of the contribution of road traffic emissions to particulate matter concentrations from field measurements: a review. Atmos Environ 77:78–97CrossRefGoogle Scholar
  31. Pascal M, Falq G, Wagner V, Chatignoux E, Corso M, Blanchard M, Host S, Pascal L, Larrieu S (2014) Short-term impacts of particulate matter (pm10, pm10–2.5, pm2.5) on mortality in nine French cities. Atmos Environ 95:175–184CrossRefGoogle Scholar
  32. Pope CA III, Burnett RT, Krewski D, Jerrett M, Shi Y, Calle EE, Thun MJ (2009) Cardiovascular mortality and exposure to airborne fine particulate matter and cigarette smoke: shape of the exposure-response relationship. Circulation 120:941–948CrossRefGoogle Scholar
  33. Setälä H, Viippola V, Rantalainen AL, Pennanen A, Ylipelkonen V (2012) Does urban vegetation mitigate air pollution in northern conditions? Environ Pollut 183:104–112CrossRefGoogle Scholar
  34. Shi W, Sing WM, Wang J, Zhao Y (2012) Analysis of airborne particulate matter (pm2.5) over Hong Kong using remote sensing and GIS. Sensors (Basel) 12:6825–6836CrossRefGoogle Scholar
  35. Sun CY (2011) A street thermal environment study in summer by the mobile transect technique. Theor Appl Climatol 106:433–442CrossRefGoogle Scholar
  36. Sun CY, Brazel AJ, Chow WTL, Hedquist BC, Prashad L (2009) Desert heat island study in winter by mobile transect and remote sensing techniques. Theor Appl Climatol 98:323–335CrossRefGoogle Scholar
  37. Tai APK, Mickley LJ, Jacob DJ (2010) Correlations between fine particulate matter (pm2.5) and meteorological variables in the United States: implications for the sensitivity of pm2.5 to climate change. Atmos Environ 44:3976–3984CrossRefGoogle Scholar
  38. Tallis M, Taylor G, Sinnett D, FreerSmith P (2011) Estimating the removal of atmospheric particulate pollution by the urban tree canopy of London, under current and future environments. Landsc Urban Plan 103:129–138CrossRefGoogle Scholar
  39. Tecer LH, Süren P, Alagha O, Karaca F, Tuncel G (2008) Effect of meteorological parameters on fine and coarse particulate matter mass concentration in a coalmining area in Zonguldak, Turkey. J Air Waste Manage Assoc 58:543–552CrossRefGoogle Scholar
  40. Tong Z, Whitlow TH, Macrae PF, Landers AJ, Yoshiki H (2015) Quantifying the effect of vegetation on near-road air quality using brief campaigns. Environ Pollut 201:141–149CrossRefGoogle Scholar
  41. Tong Z, Baldauf RW, Isakov V, Deshmukh P, Zhang MK (2016) Roadside vegetation barrier designs to mitigate near-road air pollution impacts. Sci Total Environ 541:920–927CrossRefGoogle Scholar
  42. Wang ZH, Fan C, Myint SW, Wang C (2016) Size matters: what are the characteristic source areas for urban planning strategies? PLoS One 11:e0165726CrossRefGoogle Scholar
  43. Wania A, Bruse M, Blond N, Weber C (2012) Analysing the influence of different street vegetation on traffic-induced particle dispersion using microscale simulations. J Environ Manag 94:91–101CrossRefGoogle Scholar
  44. Weber N, Haase D, Franck U (2014) Assessing modelled outdoor traffic-induced noise and air pollution around urban structures using the concept of landscape metrics. Landsc Urban Plan. 125:105–116CrossRefGoogle Scholar
  45. Wu J, Xie W, Li W, Li J (2015) Effects of urban landscape pattern on pm2.5pollution—a Beijing case study. PLoS One 10:e0142449CrossRefGoogle Scholar
  46. Yan S, Cao H, Chen Y, Wu C, Hong T, Fan H (2016) Spatial and temporal characteristics of air quality and air pollutants in 2013 in Beijing. Environ Sci Pollut Res Int 23:13996–14007CrossRefGoogle Scholar
  47. Yang J, Mcbride J, Zhou J, Sun Z (2005) The urban forest in Beijing and its role in air pollution reduction. Urban For Urban Green 3:65–78CrossRefGoogle Scholar
  48. Yang L, Ye WU, Li J, Song S, Zheng X, Hao J (2015) Mass concentrations and temporal profiles of pm10, pm2.5 and pm1 near major urban roads in Beijing. Front Environ Sci Eng 9:675–684CrossRefGoogle Scholar
  49. Yin S, Shen Z, Zhou P, Zou X, Che S, Wang W (2011) Quantifying air pollution attenuation within urban parks: an experimental approach in Shanghai, China. Environ Pollut 159:2155–2163CrossRefGoogle Scholar
  50. Zhang JJY, Sun L, Barrett O, Bertazzon S, Underwood FE, Johnson M (2015) Development of land-use regression models for metals associated with airborne particulate matter in a North American city. Atmos Environ 106:165–167CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Landscape Architecture, Beijing Laboratory of Urban and Rural Ecological Environment, National Engineering Research Center for FloricultureBeijing Forestry UniversityBeijingChina

Personalised recommendations