Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6340465 | Atmospheric Environment | 2013 | 8 Pages |
Abstract
Although methane (CH4) fluxes from northern wetlands in Asia have been described in previous research at different temporal and spatial scales, integrated studies at the ecosystem scale were scarce. In this study, CH4 fluxes were measured using eddy covariance (EC) technique and the chamber method in a cool temperate marsh in northeast China during the growing season (May-September) of 2011. CH4 emissions were highly variable, both temporally and spatially during the measurement period. According to the EC observation data, CH4 fluxes showed a significant diurnal cycle during the mid-growing season with nighttime average flux about 67% of the average daytime values. Daily cumulative CH4 fluxes varied from 54 to 250 mg CH4 mâ2 dâ1 with an average flux of 136.2 mg CH4 mâ2 dâ1. The observations of chamber method showed that CH4 emissions differed markedly among the three main plant communities. Average flux at the Carex lasiocarpa site was about 4 times and 13.5 times of that at the Glyceria spiculosa site and Deyeuxia angustifolia site, respectively. The spatial variability of CH4 flux was mainly controlled by the varying water table level as well as the spatial distribution of different vascular plants, while the seasonal dynamic of CH4 emission could be best explained by the change of surface soil temperature and air pressure. A comparison was made between EC measurements and the upscaled chamber based model. The results from the model overestimated CH4 emission by 28% compared to the EC data. Considering the large variability of methane emission, it is necessary to conduct continuous observations on CH4 emission from northern wetlands at different temporal and spatial scales to comprehend the variability and also to predict responses to climate change.
Keywords
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Atmospheric Science
Authors
Li Sun, Changchun Song, Yuqing Miao, Tianhua Qiao, Chao Gong,