An Observational Study on the Local Climate Effect of the Shangyi Wind Farm in Hebei Province

Zhangjiakou is an important wind power base in Hebei Province,China.The impact of its wind farms on the local climate is controversial.Based on long-term meteorological data from 1981 to 2018,we investigated the effects of the Shangyi Wind Farm(SWF)in Zhangjiakou on air temperature,wind speed,relative humidity,and precipitation using the anomaly or ratio method between the impacted weather station and the non-impacted background weather station.The influence of the SWF on land surface temperature(LST)and evapotranspiration(ET)using MODIS satellite data from 2003 to 2018 was also explored.The results showed that the SWF had an atmospheric warming effect at night especially in summer and autumn(up to 0.95℃).The daytime air temperature changes were marginal,and their signs were varying depending on the season.The annual mean wind speed decreased by 6%,mainly noted in spring and winter(up to 14%).The precipitation and relative humidity were not affected by the SWF.There was no increase in LST in the SWF perhaps due to the increased vegetation coverage unrelated to the wind farms,which canceled out the wind farm-induced land surface warming and also resulted in an increase in ET.The results showed that the impact of wind farms on the local climate was significant,while their impact on the regional climate was slight.

Research on temperature distribution characteristics of oilimmersed power transformers based on fluid network decoupling

Due to the complex structure and large size of large-capacity oil-immersed power transformers,it is difficult to predict the winding temperature distribution directly by numerical analysis.A 180 MVA,220 kV oil-immersed self-cooling power transformer is used as the research object.The authors decouple the internal fluid domain of the power transformer into four regions:high voltage windings,medium voltage windings,low voltage windings,and radiators through fluid networks and establish the 3D fluidtemperature field numerical analysis model of the four regions,respectively.The results of the fluid network model are used as the inlet boundary conditions for the 3D fluidtemperature numerical analysis model.In turn,the fluid resistance of the fluid network model is corrected according to the results of the 3D fluid-temperature field numerical analysis model.The prediction of the temperature distribution of windings is realised by the coupling calculation between the fluid network model and the 3D fluid-temperature field numerical analysis model.Based on this,the effect of the loading method of the heat source is also investigated using the proposed method.The hotspot temperatures of the high-voltage,medium-voltage,and low-voltage windings are 89.43,86.33,and 80.96°C,respectively.Finally,an experimental platform is built to verify the results.The maximum relative error between calculated and measured values is 4.42%,which meets the engineering accuracy requirement.

Estimation of Terrestrial Net Primary Productivity in China from Fengyun-3D Satellite Data

Currently,the satellite data used to estimate terrestrial net primary productivity(NPP)in China are predominantly from foreign satellites,and very few studies have based their estimates on data from China’s Fengyun satellites.Moreover,despite their importance,the influence of land cover types and the normalized difference vegetation index(NDVI)on NPP estimation has not been clarified.This study employs the Carnegie–Ames–Stanford approach(CASA)model to compute the fraction of absorbed photosynthetically active radiation and the maximum light use efficiency suitable for the main vegetation types in China in accordance with the finer resolution observation and monitoring-global land cover(FROM-GLC)classification product.Then,the NPP is estimated from the Fengyun-3D(FY-3D)data and compared with the Moderate Resolution Imaging Spectroradiometer(MODIS)NPP product.The FY-3D NPP is also validated with existing research results and historical field-measured NPP data.In addition,the effects of land cover types and the NDVI on NPP estimation are analyzed.The results show that the CASA model and the FY-3D satellite data estimate an average NPP of 441.2 g C m^(−2) yr^(−1) in 2019 for China’s terrestrial vegetation,while the total NPP is 3.19 Pg C yr^(−1).Compared with the MODIS NPP,the FY-3D NPP is overestimated in areas of low vegetation productivity and is underestimated in high-productivity areas.These discrepancies are largely due to the differences between the FY-3D NDVI and MODIS NDVI.Compared with historical field-measured data,the FY-3D NPP estimation results outperformed the MODIS NPP results,although the deviation between the FY-3D NPP estimate and the in-situ measurement was large and may exceed 20%at the pixel scale.The land cover types and the NDVI significantly affected the spatial distribution of NPP and accounted for NPP deviations of 17.0%and 18.1%,respectively.Additionally,the total deviation resulting from the two factors reached 29.5%.These results show that accurate NDVI products and land cover types are important prerequisites for NPP estimation.

Impacts of the Urban Spatial Landscape in Beijing on Surface and Canopy Urban Heat Islands

How does the urban spatial landscape(USL)pattern affect the land surface urban heat islands(SUHIs)and canopy urban heat islands(CUHIs)?Based on satellite and meteorological observations,this case study compares the impacts of the USL pattern on SUHI and CUHI in the central urban area(CUA)of Beijing using the satellite land-surface-temperature product and hourly temperature data from automatic meteorological stations from 2009 to 2018.Eleven USL metrics—building height(BH),building density(BD),standard deviation of building height(BSD),floor area ratio(FAR),frontal area index(FAI),roughness length(RL),sky view factor(SVF),urban fractal dimension(FD),vegetation coverage(VC),impervious coverage(IC),and albedo(AB)—with a 500-m spatial resolution in the CUA are extracted for comparative analysis.The results show that SUHI is higher than CUHI at night,and SUHI is only consistent with CUHI at spatial-temporal scales at night,particularly in winter.Spatially,all 11 metrics are strongly correlated with both the SUHI and CUHI at night,with stronger correlation between most metrics and SUHI.VC,AB,and SVF have the greatest impact on both the SUHI and CUHI.High SUHI and CUHI values tend to appear in areas with BD≥0.26,VC≤0.09,AB≤0.09,and SVF≤0.67.In summer,most metrics have a greater impact on the SUHI than CUHI;the opposite is observed in winter.SUHI variation is affected primarily by VC in summer and by VC and AB in winter,which is different for the CUHI variation.The collective contribution of all 11metrics to SUHI spatial variation in summer(61.8%)is higher than that to CUHI;however,the opposite holds in winter and for the entire year,where the cumulative contribution of the factors accounts for 66.6%and 49.6%,respectively,of the SUHI variation.

Catalytic Amidation of 5-Hydroxymethylfurfural to 2,5-Furandicarboxamide over Alkali Manganese Oxides

2,5-Furandicarboxamide was firstly synthesized in yield of 85% via catalytic oxidative amidation of 5-hydroxy- methylfurfural with aqueous NH3 over alkali manganese oxides of a-MnO2/NaxMnO〉 The intermediates of 5-hydroxymethyl-furonitrile, 2,5-dicyanofuran, and 5-cyano-2-furancarboxamide were verified and their reactivities were further examined. The kinetic analysis results showed that the transformation of intermediate product of 5-cyano-2-furancarboxamide to 2,5-furan-dicarboxamide is a slower step, which is closely relative to the reaction temperature and basicity of catalyst.