Study On The Effect Of Aerosol On Grassland Vegetation Net Primary Productivity Based On Environmental Remote Sensing Technology

The atmospheric aerosol owe to its characteristics of complex composition and wide range of distribution affected the solar radiation,cloud weather and other meteorological conditions,has become the main ambient pollutant affecting the air quality in China.The change of climate and environment condition will affect the growth and yield of vegetation,however,there is scarce research on the impact of the aerosol on vegetation growth.In this paper,taking the grassland area in northern China-Xilingol League as the research object,in order to effectively and timely grasp the extent of the atmospheric environment pollution and its ecological effect in this region and to provide a reference for the grassland ecological construction,the trend and distribution of the aerosol and the grassland vegetation productivity were studied,and the influence of aerosol on grassland were analyzed.The study is based on MODIS L1 B data,using 6S model and dense dark vegetation method to retrieval the aerosol optical depth(AOD)in the research region from 2008 to2016.The MOD04L2 product,the ground monitoring station data and the measured particle concentration were used to verify the accuracy of the retrieval results.The influence of meteorological factors on AOD was analyzed by using correlation coefficient method,and then analyzed the temporal and spatial distribution characteristics of AOD during ten-day,month,year and 9 years.Besides,the net primary productivity(NPP)of vegetation in the research region was estimated by CASA model,and the estimated NPP was verified by the measured biomass and MOD17A3 product data.Then,the paper analyzed the distribution characteristics of NPP in month,season and year.Finally,the relationship between AOD and NPP is determined by calculating the spatial correlation coefficient and the correlation coefficient of pixels.The main contents and results are as follows:(1)Verification the accuracy of retrieval AOD.The results showed that the regional AOD was positively correlated with the MOD04L2(aerosol product)(0.509 **,P< 0.01),indicated that the dark vegetation method is suitable for the retrieval of AOD in the research region.There was a significant positive correlation between the monitoring station data and the measured particle concentration with the retrieval AOD data.(2)Temporal and spatial distribution of AOD from 2008 to 2016.Temporal distribution characteristics of AOD are as follows: From 2008 to 2016,there was no uniform change trend of AOD in January,April and July.But the change trend of the AOD in October was obvious that was ascending by ten days during the month.The average value of AOD was declining in January from 2008 to 2016,and there was no significant change in the months.Took the monthly value of AOD in January,April,July and October to synthesis the yearly value of AOD,and the results showed that the highest value is in2013,the lowest in 2015.The characteristic of the spatial distribution of the annual AOD is consistent.The distribution of the low value is in the west and the high value is in the east.In general,the AOD value in research region is low,it demonstrate that the air in the region is clean.(3)The analysis of spatial correlation coefficient between regional AOD and meteorological factors.The results showed that the AOD value was negatively correlated with the average temperature,sunshine duration and solar radiation in January,April,July and October.The AOD value was positively correlated with the relative humidity,and the correlation coefficient was the highest in July.There was a significant positive correlation between AOD and precipitation in July,while precipitation in January,April and October had a sedimentation effect on aerosol particles,and the correlation coefficient was low.The average wind speed was negatively correlated with AOD.The effect of air pressure on AOD is small.In July and October,the impact of the seven meteorological factors on AOD is more obvious.(4)The verification accuracy,estimation and distribution of regional NPP.The correlation coefficient between the estimated NPP and the measured plant biomass is 0.477,and the correlation coefficient with MOD17A3 product is 0.843,which indicated that the CASA model can be used to simulate the vegetation productivity in the research region.The NPP reached its maximum in July or August from 2008 to 2016.The trend of seasonal NPP is summer > autumn > spring.The regional NPP annual average has a slow upward trend.The spatial distribution characteristics of vegetation NPP were consistent monthly,seasonally and annually,and gradually increased from the west to the East.(5)The regional correlation analysis of AOD and NPP.The spatial correlation coefficient of monthly or annually AOD and NPP were positive in the Xilingol League area,but there was a large difference in the distribution region of the correlation coefficients.The results demonstrated that the positive correlation coefficient was from 52.35% to 86%in the research region.The positive correlation coefficient between AOD and NPP in April and October was low,and the effect of AOD on NPP was obvious only in July.Under the influence of regional precipitation,humidity,radiation and other meteorological impact factors,the annual AOD and vegetation NPP showed the similar spatial distribution characteristics,and the correlation coefficient is positive.All in all,the relationship between AOD and NPP is influenced by meteorological environmental factors,the value of AOD is small and the air is clean in the research region.Therefore,the AOD is not the dominant factor affect the distribution of NPP.