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The Influence Of Atmospheric Aerosol’s Direct Radiation Effect On Winter Wheat GPP In North China

Posted on:2022-10-28Degree:MasterType:Thesis
Country:ChinaCandidate:Y Y DuFull Text:PDF
GTID:2493306326987719Subject:Master of Agriculture
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North China is one of the largest farmland ecosystems in my country.The sown area of winter wheat accounts for about 43%of the country.The food production problem in this region has always been concerned.It is also the most severely polluted area of atmospheric aerosols in my country.It is to study the impact of atmospheric aerosols on crops.Typical area.At present,the research on the impact of atmospheric aerosols on vegetation is mostly focused on the response of forest ecosystem carbon cycle to aerosols.For crops,they only focus on yield and not refined to GPP.Most studies are based on flux observation sites,which are not representative.After the outbreak of COVID-19,my country has adopted strict control measures.The drastic reduction of human behavior may affect changes in atmospheric aerosol concentration,which will affect crop productivity.Based on multi-source remote sensing data,this study designed an automatic extraction algorithm for winter wheat in North China,and extracted the spatial distribution information of winter wheat from 2001 to 2020.The mask extracted AOD,PAR,and GPP in the areas where winter wheat has been grown in North China for 20 years.Based on the spatial and temporal distribution characteristics and related relationships of participants,the response relationship of winter wheat GPP to AOD under the background of COVID-19 is studied.The main findings are as follows:(1)The average values of AOD,PAR,and GPP in North China from 2001 to 2020 were 0.46,90.3W·m-2 and 16.0 g C·m-2·d-1,respectively.AOD in North China showed an upward trend from 2001 to2010.2020 shows a weakening trend.The monthly distribution trends of AOD,PAR,and GPP are consistent,showing a convex curve,and they all reach their peaks in summer.The results of the MK trend test show that AOD and scattered PAR both have a decreasing trend,decreasing by-0.0041 and-0.126W·m-2 each year.GPP,direct PAR,and total PAR are increasing trends,each increasing by 0.221 g C·m-2·d-1,0.273 W·m-2 and 0.109 W·m-2,respectively..(2)There was a significant negative correlation between AOD and winter wheat GPP in North China(r=-0.36),and the degree of correlation was different in different regions and different growth periods.The effect of atmospheric aerosol absorption and scattering PAR is obvious.AOD has a strong negative correlation with direct PAR and total PAR,with correlation coefficients of-0.93 and-0.95,respectively,and a strong positive correlation with scattered PAR,with a correlation coefficient of 0.84.Winter wheat GPP in Henan Province is sensitive to AOD response(r=-0.32),followed by Beijing-Tianjin-Hebei(r=-0.13),and Shandong Province is the weakest(r=-0.09).Winter wheat GPP was negatively correlated with AOD at the green-joining stage,the correlation coefficient was 0.13,the correlation between the two at heading stage was very weak,and the maturity stage was positively correlated,with a correlation coefficient of 0.38.(3)Compared with the same period in the past five years,during COVID-19,the AOD over winter wheat in North China dropped by 23%,and the aerosol extinction effect was weakened,resulting in a year-on-year increase of 11.1%and 4.8%in direct PAR and total PAR.At the same time,the rainfall was much higher than the 5-year average,and the surface temperature was basically the same.In the end,GPP increased by 30.1%.The driving force of meteorological factors on winter wheat GPP is photosynthetically active radiation(0.495)>rainfall(0.399)>atmospheric aerosol optical thickness(0.239)>surface temperature(0.092).During COVID-19,changes in photosynthetically active radiation caused by atmospheric aerosols were the main driving factor for winter wheat GPP in North China,and rainfall was the secondary driving factor.
Keywords/Search Tags:Atmospheric aerosol, Winter wheat GPP, Photosynthetically active radiation, Spatial and temporal distribution, COVID-19
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