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气候变化下黑龙江寒地稻田甲烷通量的时空动态特征。

Characterizing Spatiotemporal Dynamics of CH₄ Fluxes from Rice Paddies of Cold Region in Heilongjiang Province under Climate Change.

机构信息

School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin 150030, China.

Key Laboratory of Agricultural Water Resource Use, Ministry of Agriculture, Harbin 150030, China.

出版信息

Int J Environ Res Public Health. 2019 Feb 26;16(5):692. doi: 10.3390/ijerph16050692.

DOI:10.3390/ijerph16050692
PMID:30813633
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6427409/
Abstract

Paddy fields have become a major global anthropogenic CH₄ emission source, and climate change affects CH₄ emissions from paddy ecosystems by changing crop growth and the soil environment. It has been recognized that Heilongjiang Province has become an important source of CH₄ emission due to its dramatically increased rice planting area, while less attention has been paid to characterize the effects of climate change on the spatiotemporal dynamics of CH₄ fluxes. In this study, we used the calibrated and validated Long Ashton Research Station Weather Generator (LARS-WG) model and DeNitrification-DeComposition (DNDC) model to simulate historical and future CH₄ fluxes under RCP 4.5 and RCP 8.5 of four global climate models (GCMs) in Heilongjiang Province. During 1960⁻2015, the average CH₄ fluxes and climatic tendencies were 145.56 kg C/ha and 11.88 kg C/ha/(10a), respectively. Spatially, the CH₄ fluxes showed a decreasing trend from west to east, and the climatic tendencies in the northern and western parts were higher. During 2021⁻2080, the annual average CH₄ fluxes under RCP 4.5 and RCP 8.5 were predicted to be 213.46 kg C/ha and 252.19 kg C/ha, respectively, and their spatial distributions were similar to the historical distribution. The average climatic tendencies were 13.40 kg C/ha/(10a) and 29.86 kg C/ha/(10a), respectively, which decreased from west to east. The simulation scenario analysis showed that atmospheric CO₂ concentration and temperature affected CH₄ fluxes by changing soil organic carbon (SOC) content and plant biomass. This study indicated that a paddy ecosystem in a cold region is an important part of China's greenhouse gas emission inventory in future scenarios.

摘要

稻田已成为全球人为 CH₄排放的主要来源，气候变化通过改变作物生长和土壤环境来影响稻田生态系统中的 CH₄排放。人们已经认识到，由于黑龙江省水稻种植面积的大幅增加，该省已成为 CH₄排放的重要来源，而对气候变化对 CH₄通量时空动态的影响的关注较少。在本研究中，我们使用经过校准和验证的 Long Ashton Research Station Weather Generator（LARS-WG）模型和 DeNitrification-DeComposition（DNDC）模型，模拟了黑龙江省四个全球气候模型（GCMs）在 RCP4.5 和 RCP8.5 下的历史和未来 CH₄通量。在 1960 年至 2015 年期间，平均 CH₄通量和气候趋势分别为 145.56 kg C/ha 和 11.88 kg C/ha/（10a）。空间上，CH₄通量从西向东呈减少趋势，北部和西部的气候趋势较高。在 2021 年至 2080 年期间，预计 RCP4.5 和 RCP8.5 下的年平均 CH₄通量分别为 213.46 kg C/ha 和 252.19 kg C/ha，其空间分布与历史分布相似。平均气候趋势分别为 13.40 kg C/ha/（10a）和 29.86 kg C/ha/（10a），从西向东递减。模拟情景分析表明，大气 CO₂浓度和温度通过改变土壤有机碳（SOC）含量和植物生物量来影响 CH₄通量。本研究表明，寒冷地区的稻田生态系统是未来情景下中国温室气体排放清单的重要组成部分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/733b4e0fb64c/ijerph-16-00692-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/c16514a49c18/ijerph-16-00692-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/10b43e1cc602/ijerph-16-00692-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/405c8d9f7882/ijerph-16-00692-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/5066a1a3afa9/ijerph-16-00692-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/9aef3360ba2c/ijerph-16-00692-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/7169e90cf54a/ijerph-16-00692-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/0d36e8468551/ijerph-16-00692-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/b976e12399e0/ijerph-16-00692-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/e17675702ef6/ijerph-16-00692-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/7321f173d592/ijerph-16-00692-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/d2a1f93b62a9/ijerph-16-00692-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/5531d25bded2/ijerph-16-00692-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/733b4e0fb64c/ijerph-16-00692-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/c16514a49c18/ijerph-16-00692-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/10b43e1cc602/ijerph-16-00692-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/405c8d9f7882/ijerph-16-00692-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/5066a1a3afa9/ijerph-16-00692-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/9aef3360ba2c/ijerph-16-00692-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/7169e90cf54a/ijerph-16-00692-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/0d36e8468551/ijerph-16-00692-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/b976e12399e0/ijerph-16-00692-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/e17675702ef6/ijerph-16-00692-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/7321f173d592/ijerph-16-00692-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/d2a1f93b62a9/ijerph-16-00692-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/5531d25bded2/ijerph-16-00692-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/589e/6427409/733b4e0fb64c/ijerph-16-00692-g013.jpg

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