瞿明凯，男，博士，副研究员，硕士生导师，中国科学院青年创新促进会会员。2012年7月获华中农业大学资源环境信息工程专业博士学位；2012年7月 ~ 2014年6月在中国科学院南京土壤研究所做博士后；2014年7月留所；2018年10月 ~ 2019年10年在美国康涅狄格大学地理系做访问****。主要从事区域土壤环境信息、土壤污染时空预测模拟与来源解析研究。主持和参与了国家自然科学基金等十余项基金项目。构建了一套结合点/面状辅助信息，来进行高精度农田土壤与环境风险预测制图的方法体系；基于区域土壤属性空间变异性和空间相关性的特点，提出了针对区域土壤污染物来源解析的稳健局部受体模型（即稳健绝对主成分分数/地理加权回归模型）。目前已在Environ. Pollut.、Sci. Total Environ.、Soil Sci. Soc. Am. J.、Ecol. Indic.等杂志上发表论文50余篇，其中第一/通讯作者SCI文章22篇，EI文章3篇。现为20余份国内外学术期刊的审稿人。Tel: ; E-mail: qumingkai@issas.ac.cn。

研究领域与招生方向：n区域土壤环境信息；
n土壤污染时空预测模拟与来源解析。
真诚欢迎具有资源环境与遥感信息、土壤学、环境科学与工程等专业背景的同学们加入研究团队。我们共同探索，齐心努力！
获奖及荣誉：中国科学院青年创新促进会成员（2017年11月）
代表论著：
[1] Chen J., Qu M.K.*, Zhang J.L., Xie E.Z., Zhao Y.C., Huang B., 2021. Soil fertility quality assessment based on geographically weighted principal component analysis (GWPCA) in large-scale areas. Catena. 105197. https://doi.org/10.1016/j.catena.2021.105197.
[2] Qu M.K.*, Chen J., Huang B., Zhao Y.C., 2020. Resampling with in situ ？eld portable X-ray ？uorescence spectrometry (FPXRF) to reduce the uncertainty in delineating the remediation area of soil heavy metals. Environmental Pollution. 116310. https://doi.org/10.1016/j.envpol.2020.116310.
[3] Qu M.K.*, Chen J., Huang B., Zhao Y.C., 2020. Source apportionment of soil heavy metals using robust spatial receptor model with categorical land-use types and RGWR-corrected in-situ FPXRF data. Environmental Pollution. 116220. https://doi.org/10.1016/j.envpol.2020.116220.
[4] Chen J., Qu M.K.*, Zhang J.L., Xie E.Z., Zhao Y.C., Huang B., 2020. Improving the spatial prediction accuracy of soil available nitrogen using geographically weighted principal component analysis-geographically weighted regression kriging (GWPCA-GWRK). Soil Science Society of America Journal. https://doi.org/10.1002/saj2.20189.
[5] Zhang J.L., Wang Y., Qu M.K.*, Chen J., Yang L.F., Huang B., Zhao Y.C., 2020. Source apportionment of soil nitrogen and phosphorus based on robust residual kriging and auxiliary soil-type map in Jintan County, China. Ecological Indicators. 106820. https://doi.org/10.1016/j.ecolind.2020.106820.
[6] Qu M.K.*, Chen J., Huang B., Zhao Y.C., 2020. Enhancing apportionment of the point and diffuse sources of soil heavy metals using robust geostatistics and robust spatial receptor model with categorical soil-type data. Environmental Pollution. 114964. https://doi.org/10.1016/j.envpol.2020.114964.
[7] Qu M.K.*, Chen J., Huang B., Zhao Y.C., 2020. Exploring the spatially varying relationships between cadmium accumulations and the main influential factors in the rice-wheat rotation system in a large-scale area. Science of the Total Environment. 139565. https://doi.org/10.1016/j.scitotenv.2020.139565.
[8] Liu G., Liu B., Yang L., Hu W., Qu M.K.*, Lu F., Huang B. 2020. Using pXRF to assess the accumulation, sources, and potential ecological risk of potentially toxic elements in soil under two greenhouse vegetable production systems in North China. Environmental Science and Pollution Research. 27, 11105–11115. http://dx.doi.org/10.1007/s11356-020-07674-y.
[9] Qu M.K.*, Chen J., Li W.D., Zhang C.R., Wan M.X., Huang B., Zhao Y.C., 2019. Correction of in-situ portable X-ray fluorescence (PXRF) data of soil heavy metal for enhancing spatial prediction. Environmental Pollution. 112993. https://doi.org/10.1016/j.envpol.2019.112993.
[10]Qu M.K.*, Wang Y., Huang B.*, Zhao Y.C., 2018. Spatial uncertainty assessment of the environmental risk of soil copper using auxiliary portable X-ray ？uorescence spectrometry data and soil pH. Environmental Pollution. 240: 184-190. https://doi.org/10.1016/j.envpol.2018.04.118.
[11]Qu M.K.*, Wang Y., Huang B.*, Zhao Y.C., 2018. Source apportionment of soil heavy metals using robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR) receptor model. Science of the Total Environment. 626: 203-210. https://doi.org/10.1016/j.scitotenv.2018.01.070.
[12]Qu M.K., Li W.D., Zhang C.R., Huang B.*, Zhao Y.C., 2016. Spatial assessment of soil nitrogen availability and varying effects of related main soil factors on soil available nitrogen. Environmental Science: Processes & Impacts. 18(11): 1449-1457. https://doi.org/10.1039/c6em00407e.
[13]Qu M.K.*, Li W.D., Zhang C.R., Huang B., Zhao Y.C., 2015. Assessing the pollution risk of soil Chromium based on loading capacity of paddy soil at a regional scale. Scientific Reports. 5: 18451. https://doi.org/10.1038/srep18451.
[14]Qu M.K., Huang B.*, Li W.D., Zhang C.R., Zhao Y.C., 2015. Spatial uncertainty of joint health risk of multiple trace metals in rice grain in Jiaxing city, China. Environmental Science: Processes & Impacts. 17(1): 120-130. https://doi.org/10.1039/c4em00513a.
[15]Qu M.K., Li W.D., Zhang C.R., Huang B.*, Zhao Y.C., 2014. Spatially nonstationary relationships between copper accumulation in rice grain and some related soil properties in paddy fields at a regional scale. Soil Science Society of America Journal. 78(5): 1765–1774. https://doi.org/10.2136/sssaj2014.02.0067.
[16]Qu M.K., Li W.D., Zhang C.R., Zhao Y.C.*, Huang B., Sun W.X., Hu W.Y., 2013. Comparison of Three Methods for Soil Fertility Quality Spatial Simulation with Uncertainty Assessment. Soil Science Society of America Journal. 77(6): 2182-2191. https://doi.org/10.2136/sssaj2013.05.0177.
[17]Qu M.K., Li W.D.*, Zhang C.R., 2014. Spatial distribution and uncertainty assessment of potential ecological risks of soil heavy metals using sequential Gaussian simulation. Human and Ecological Risk Assessment: An International Journal. 20(3): 764-778. https://doi.org/10.1080/**.2013.770352.
[18]Qu M.K., Li W.D., Zhang C.R., Huang B.*, Zhao Y.C., 2014. Estimating the pollution risk of cadmium in soil using a composite soil environmental quality standard. Scientific World Journal. 750879. http://dx.doi.org/10.1155/2014/750879.
[19]Qu M.K.*, Li W.D., Zhang C.R., Wang S.Q., Yang Y., He L.Y., 2013. Source apportionment of heavy metals in soils using multivariate statistics and geostatistics. Pedosphere. 23(4): 437-444. http://dx.doi.org/10.1016/S1002-0160(13)60036-3.
[20]Qu M.K., Li W.D.*, Zhang C.R., 2013. Assessing the spatial uncertainty in soil nitrogen mapping through stochastic simulations with categorical land use information. Ecological Informatics. 16: 1-9. http://dx.doi.org/10.1016/j.ecoinf.2013.04.001.
[21]Qu M.K., Li W.D.*, Zhang C.R., 2013. Assessing the risk costs in delineating soil nickel contamination using sequential Gaussian simulation and transfer functions. Ecological Informatics. 13: 99-105. http://dx.doi.org/10.1016/j.ecoinf.2012.06.005.
[22]Qu M.K., Li W.D.*, Zhang C.R., Wang S.Q.*, 2012. Effect of Land Use Types on the Spatial Prediction of Soil Nitrogen. GIScicence & Remote Sensing. 49(3): 397-411. http://dx.doi.org/10.2747/1548-1603.49.3.397.
[23]Qu M.K., Li W.D.*, Zhang C.R., Zhao Y.C., Huang B., 2014. County-Scale Spatial Variability of Macronutrient Availability Ratios in Paddy Soils. Applied and Environmental Soil Science. 689482. http://dx.doi.org/10.1155/2014/689482.
[24]瞿明凯*，李卫东，张传荣，黄标，胡文友，2013．基于受体模型和地统计学相结合的土壤镉污染源解析．中国环境科学．33(5): 854-860.
[25]瞿明凯，李卫东*，张传荣，黄标，2014．地理加权回归及其在土壤和环境科学上的应用前景．土壤．46(1): 15-22.
[26]李锦芬，瞿明凯*，黄标，刘刚，赵永存，孙维侠，胡文友．2017．区域土壤CEC与相关控制因子的空间非平稳关系评估．土壤学报．54(3): 638-646. http://dx.doi.org/10.11766/trxb5.
[27]李锦芬，瞿明凯*，刘刚，黄标．2018．县域尺度土壤铜的有效性及相关影响因素评估．环境科学．39(1): 363-370．http://dx.doi.org/10.13227/j.hjkx..
[28]王燕，瞿明凯*，陈剑，杨兰芳，黄标，赵永存．2019．基于GWRK的土壤有效磷空间预测及其超标风险评估．中国环境科学．39: 245-256. http://dx.doi.org/10.19674/j.cnki.issn1000-6923.2019.0031.
[29]陈剑，瞿明凯*，王燕，万梦雪，黄标，赵永存．2019．长三角平原区县域土壤磷素流失风险及其空间不确定性的快速评估．生态学报．39(24): 9131-9142．http://dx.doi.org/10.5846/stxb6.
[30]刘宏波，瞿明凯*，张健琳，康俊锋，赵永存，黄标．2021．土壤污染物源解析技术研究进展．环境监控与预警．http://dx.doi.org/.10.3969/j.issn.1674-6732.2021.01.001
承担科研项目情况：承担10余项科研项目：中国博士后科学基金一等资助、中国博士后科学基金特别资助、江苏省自然科学基金青年基金、国家自然科学基金青年基金、国家科技支撑计划子课题、科技基础性工作专项子课题、中科院“一三五”计划和领域前沿项目、国家自然科学基金面上基金、中科院青年创新促进会人才项目、重点研发计划子课题等。