Spatio-temporal assessing of natural vegetation regulation on SO2 absorption coupling ecosystem process model and OMI satellite data
文献类型：期刊论文
| 作者 | Zhao,Fen3,4; Yang,Peng4; Li,Renqiang3; Shang,Hua2; Xia,Lang4; Hu,Mengmeng4; Xu,Ming1,3 |
| 刊名 | Environmental Research Letters
 |
| 出版日期 | 2022-03-01 |
| 卷号 | 17期号:3 |
| 关键词 | regulating service SO2 absorption improved Biome-BGC model OMI/SO2 Qinghai province |
| DOI | 10.1088/1748-9326/ac5691 |
| 通讯作者 | Xu,Ming() |
| 英文摘要 | Abstract Quantifying the contribution of natural ecosystems on air quality regulation can help to lay the foundation for ecological construction, and to promote the sustainable development of natural ecosystems. To identify the spatio-temporal dynamic changes of natural vegetation regulation on SO2 absorption and the underlying mechanism of these changes in Qinghai Province, an important ecological barrier and the unique natural ecosystems, the Biome-BGC model was improved to simulate the canopy conductance to SO2 and leaf area index (LAI) on the daily scale, and then the SO2 absorption by vegetation was estimated coupling SO2 concentration from satellite data. Our results showed that the annual average SO2 absorption of the natural ecosystems in Qinghai Province was 4.74 × 104 tons yr?1 from 2005 to 2018, accounting for about 40% of the total emissions. Spatially, the ecosystem service of SO2 absorption gradually decreased from southeast to northwest, and varied from 0 in Haixi state to 14.37 kg SO2 ha?1 yr?1 in Haibei state. The annual average SO2 absorption in unit area was 0.68 kg SO2 ha?1 yr?1, and significantly higher SO2 absorption was observed in summer with 0.45 kg SO2 ha?1 quarterly. The canopy conductance and LAI controlled by climate variables would be the dominant driving factors for the variation of SO2 absorption for natural ecosystems. The sensitivity analysis showed that SO2 concentration contributed more to the uncertainties of SO2 absorption than the conductance in this study. Our results could provide powerful supports for realistic eco-environmental policy and decision making. |
| 语种 | 英语 |
| WOS记录号 | IOP:ERL_17_3_034044 |
| 出版者 | IOP Publishing |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/166803]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Xu,Ming |
| 作者单位 | 1.Jiangmen Laboratory of Carbon Science and Technology, Hong Kong University of Science and Technology, Jiangmen, Guangdong 529199, People’s Republic of China 2.Department of Ecology, Evolution and Natural Resources, Rutgers University, New Brunswick, NJ 08901, United States of America 3.Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China 4.Key Laboratory of Agricultural Remote Sensing (AGRIRS), Ministry of Agriculture and Rural Affairs/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, People’s Republic of China |
| 推荐引用方式 GB/T 7714 | Zhao,Fen,Yang,Peng,Li,Renqiang,et al. Spatio-temporal assessing of natural vegetation regulation on SO2 absorption coupling ecosystem process model and OMI satellite data[J]. Environmental Research Letters,2022,17(3). |
| APA | Zhao,Fen.,Yang,Peng.,Li,Renqiang.,Shang,Hua.,Xia,Lang.,...&Xu,Ming.(2022).Spatio-temporal assessing of natural vegetation regulation on SO2 absorption coupling ecosystem process model and OMI satellite data.Environmental Research Letters,17(3). |
| MLA | Zhao,Fen,et al."Spatio-temporal assessing of natural vegetation regulation on SO2 absorption coupling ecosystem process model and OMI satellite data".Environmental Research Letters 17.3(2022). |
入库方式： OAI收割
来源：地理科学与资源研究所
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