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Ecological benefits of roadside greening vegetation in Shanxi Province.

WANG Hui1, REN Jian-zhong2, GUO Jin-ping1**, ZHANG Yun-xiang1   

  1. (1 College of Forestry, Shanxi Agricultural University, Taigu 030801, Shanxi, China; 2Forestry Department of Shanxi Province, Taiyuan 030002, China)
  • Online:2014-09-10 Published:2014-09-10

Abstract:

To investigate the ecological services and economic benefits of roadside treebelts in Shanxi Province, sampling points were set up in typical roadside treebelts with varied stand structures and different distances from roads to record dispersion patterns of SO2, NO2 and dust, noise attenuation and daily temperature variation. The recorded data were then analyzed according to major stand characteristics, such as species composition, stand density, canopy density, degree of porosity and LAI to construct estimation models for ecological services of roadside treebelt. Moreover, reduction of SO2, NO2, dust and noise, carbon fixation and oxygen release of roadside greening vegetation in Shanxi Province were estimated based on the models. The economic benefits of roadside treebelt in terms of their ecological services were also calculated. The results showed that the effective green coverage of main highway landscaping projects in Shanxi Province was 29194.29 hm2 by 2011 with carbon storage of 887343.6 t in total. The calculated economic losses avoided by the roadside greening vegetation were about 543000, 487000, 4421000, 987000 and 214000 RMB per year in terms of SO2 reduction, NO2 reduction, dust reduction, noise reduction and temperature reduction, respectively. Furthermore, the calculated economic benefits generated by these roadside greening vegetations were about 262713000 and 77441000 RMB per year in terms of carbon fixation and oxygen release. In total, the economic benefit provided by roadside greening vegetation in Shanxi Province was about 0.347 billion RMB annually.
 

Key words: stable hydrogen isotope, tree dieback, sap flow, Populus simonii, water source