王占永,博士,副教授,硕士生导师,福建省引进高层次人才(C类)。2016年获得上海交通大学土木工程专业博士学位,之后先后受聘于中山大学智能工程学院、网投十大信誉排名品牌(中国)有限公司。现主讲《交通环境工程》、《多元统计与交通建模》等本科课程以及《交通环境智能监测与评估》、《多元统计分析》等研究生课程。2012年至今,一直致力于交通污染暴露统计学、交通减污降碳的绿地响应策略、基于无人机的大气污染智能监测技术等交通环境与健康交叉领域研究工作。创新成果主要集中在:(1)以无人机和微型传感器为载体,集成研发道路交通及施工大气污染的走航观测技术及智能评估系统平台;(2)以实测数据为驱动,探究城市、街区、道路等多尺度大气污染的三维分布规律;(3)利用非线性统计、机器学习、流体力学等理论方法,揭示交通环境污染的动力学机制,提出减少沿路出行和居住污染暴露的实用性策略(聚焦交通管控、设施优化、绿化配置等策略)。
主持(含结题)国家自然科学基金青年项目、福建省自然科学基金面上项目、广州市民生计划重点项目等国家省部级课题多项,发表学术论文50余篇,其中第一和通讯作者发表SCI论文近20篇,Google学术引用约1200次,个人H指数19,申请和授权专利及软著7项。担任世界交通运输大会交叉学部交通污染及GIS-T技术委员会委员、中国公路学会会员、中国人工智能学会智能交通专业委员会会员、中国地理学会会员、中国林学会会员及国际中国规划学会会员,多次受邀在美国TRB年会、交通运输研究(上海)论坛、国际中国规划学会年会、中国环境化学年会、中国地理学年会等国内外学术会议做口头报告;担任Journal of Cleaner Production、Science of the Total Environment、Sustainable Cities and Society、Journal of Environmental Management、Building and Environment、Transportation Research Part D、Environmental Pollution、Urban Climate、Cities、Atmospheric Environment、中国环境科学、中国环境监测等国内外主流学术期刊的审稿人,以及Frontiers in Public Health、Frontiers in Environmental Science等SCI期刊Guest/Review Editor。团队拥有中国航空器拥有者及驾驶员协会(AOPA-China)颁发的多旋翼无人机驾驶员执照。
Google Scholar: https://scholar.google.com/citations?user=pb10FFwAAAAJ&hl=zh-CN
ResearchGate: https://www.researchgate.net/profile/Zhanyong-Wang-3
Web of Science: https://www.webofscience.com/wos/author/record/583243
ORCID: http://orcid.org/0000-0003-4147-175X
Email: wangzy1026@fafu.edu.cn, wangzy1026@163.com
一、代表性论著(*通讯作者):
2023年:
[1] Wang, Z.#*, Cao, R.#, Li, B., et al., 2023. Characterizing the nighttime vertical profiles of atmospheric particulate matter and ozone in a megacity of South China using unmanned aerial vehicle measurements, Environmental Research, 116854. https://doi.org/10.1016/j.envres.2023.116854
[2] Chen, X., Wu, J., Yang, W., Wang, Z.*, et al., 2023. Measuring and modeling the effects of green barriers on the spatial distribution of fine particulate matter at roadside, Urban Climate, 52, 101727.
https://doi.org/10.1016/j.uclim.2023.101727
[3] Luo, B., Cao, R., Yang, W., Wang, Z.*, et al., 2023. Analysing and predicting the fine-scale distribution of traffic particulate matter in urban nonmotorized lanes by using wavelet transform and random forest methods, Stochastic Environmental Research and Risk Assessment, 37, 2657-2676.
https://doi.org/10.1007/s00477-023-02411-6
[4] Yang, W., Cao, R., Ma, F., Wang, Z.*, et al., 2023. High-resolution distributions of traffic particles and personal inhalation dose estimation at different pedestrian overpasses, Atmospheric Pollution Research, 14, 7, 101786. https://authors.elsevier.com/sd/article/S1309-1042(23)00140-X
[5] Cao, R., Luo, B., Liu, K., Wang, Z.*, et al., 2023. Identifying the spatiotemporal hotspots of atmospheric particulate matter and the influential factors in urban non-motorized lanes by mobile measurement and generalized additive model, Air Quality, Atmosphere & Health, 16, 1907-1929.
https://doi.org/10.1007/s11869-023-01382-5
[6] Cao, R., Xiao, Y.,…, Wang, Z.*, 2023. Using complex systems theory to comprehend the coordinated control effects of PM2.5 and O3 in Yangtze River Delta Industrial Base in China, Stochastic Environmental Research and Risk Assessment, under review.
[7] 吴杰,曹如晖,林鑫源,陈舒婷,杨文彬,王占永*,胡喜生,徐锦强,张兰怡,2023. 慢行道大气颗粒物分布特征及慢行者暴露估算, 环境科学学报, 43(8): 273-290. DOI: 10.13671/j.hjkxxb.2023.0059
[8] 陈舒婷,陈昕,罗斌儒,马范,胡喜生,王占永*,2023. 道路绿化带影响大气颗粒物分布实测研究, 中国环境监测, 39(1): 105-116. DOI: 10.19316/j.issn.1002-6002.2023.01.12
[9] 马范,罗斌儒,杨文彬,陈舒婷,胡喜生,徐锦强,王占永*,2023. 公交站交通颗粒物污染的时空分布, 环境污染与防治, 45(03): 338-345&351. DOI: 10.15985/j.cnki.1001-3865.2023.03.011
2022年及之前:
[1] Cao., R., Li, B., Wang, Z.*, et al., 2020. Using a distributed air sensor network to investigate the spatiotemporal patterns of PM2.5 concentrations, Environmental Pollution, 264, 114549. https://doi.org/10.1016/j.envpol.2020.114549
[2] Cai, M., Huang, Y., Wang, Z.*, 2020. Dynamic three-dimensional distribution of traffic pollutant at urban viaduct with the governance strategy, Atmospheric Pollution Research, 11, 1418-1428. https://doi.org/10.1016/j.apr.2020.05.002
[3] Wang, D., Wang, Z.*, Peng, Z.R., et al., 2020. Using unmanned aerial vehicle to investigate the vertical distribution of fine particulate matter, International Journal of Environmental Science and Technology, 17(1), 219-230. https://doi.org/10.1007/s13762-019-02449-6
[4] Cai, M., Li, J., Wang, Z.*, et al., 2020. Evaluation of external costs in road transport under the openness of a gated community, Frontiers of Earth Science, 14: 140-151. https://doi.org/10.1007/s11707-019-0762-z
[5] Li, C., Wang, Z.*, Li, B., et al., 2019. Investigating the relationship between air pollution variation and urban form, Building and Environment, 147, 559-568. https://doi.org/10.1016/j.buildenv.2018.06.038
[6] Gao, Y., Wang, Z.*, Liu C., et al., 2019. Assessing neighborhood air pollution exposure and its relationship with the urban form, Building and Environment, 155, 15-24. https://doi.org/10.1016/j.buildenv.2018.12.044
[7] Lu, S., Wang, D., Wang, Z.*, et al., 2019. Investigating the role of meteorological factors in the vertical variation in PM2.5 by unmanned aerial vehicle measurement, Aerosol and Air Quality Research, 19(7): 1493-1507. https://doi.org/10.4209/aaqr.2018.07.0266
[8] Li, B., Cao, R., Wang, Z.*, et al., 2019. Use of multi-rotor unmanned aerial vehicles for fine-grained roadside air quality monitoring, Transportation Research Record, 2673(7): 169-180.
https://doi.org/10.1177%2F0361198119847991
[9] Li, B., Zhu, Y., Wang, Z.*, et al., 2018. Use of multi-rotor unmanned aerial vehicles for radioactive source search, Remote Sensing, 10(5), 728. https://doi.org/10.3390/rs10050728
[10] Wang, Z.*, Zhong, S., He, H.D., et al., 2018. Fine-scale variations in PM2.5 and black carbon concentrations and corresponding influential factors at an urban road intersection, Building and Environment, 141, 215-225. https://doi.org/10.1016/j.buildenv.2018.04.042
[11] Wang, Z., Wang, D., Peng, Z.R.*, et al., 2018. Performance assessment of a portable nephelometer for outdoor particle mass measurement, Environmental Science: Processes & Impacts, 20, 370-383.
https://doi.org/10.1039/C7EM00336F
[12] Wang, Z., Lu, Q.C., He, H.D., et al., 2017. Investigation of the spatiotemporal variation and influencing factors on fine particulate matter and carbon monoxide concentrations near a road intersection, Frontiers of Earth Science, 11(1), 63-75. https://doi.org/10.1007/s11707-016-0564-5
[13] Wang, Z., Lu, F., He, H.D., et al., 2015. Fine-scale estimation of carbon monoxide and fine particulate matter concentrations in proximity to a road intersection by using wavelet neural network with genetic algorithm, Atmospheric Environment, 104, 264-272. https://doi.org/10.1016/j.atmosenv.2014.12.058
[14] Wang, Z., He, H.D., Lu, F., et al., 2015. Hybrid model for prediction of carbon monoxide and fine particulate matter concentrations near road intersection, Transportation Research Record, 2503, 29-38.
https://doi.org/10.3141/2503-04
[15] 王占永,陈昕,胡喜生,何红弟,蔡铭,彭仲仁*,2022. 植物屏障影响路边大气颗粒物分布机理及研究方法的进展, 生态环境学报, 31(5): 1047-1058. https://doi.org/10.16258/j.cnki.1674-5906.2022.05.020
[16] 罗斌儒,曹如晖,陈昕,胡喜生,王占永*,2022. 城市慢行道路中交通颗粒物的时空分布研究, 上海大学学报(自然科学版), 28(4): 582-593. https://doi.org/10.12066/j.issn.1007-2861.2351
[17] 王占永,蔡铭*,彭仲仁,高雅,2017. 基于移动观测的路边PM2.5和CO浓度的时空分布, 中国环境科学, 37(12), 4428-4434. http://www.zghjkx.com.cn/CN/Y2017/V37/I12/4428
[18] 彭仲仁,王占永,李超,高雅,路庆昌,黄蓉,2017. 城市交通与灰霾治理, 中国城市发展报告, 166-184.
[1] 福建省自然科学基金面上项目(编号:2021J01105),乡村振兴背景下城郊道路大气颗粒物三维扩散的无人机观测研究,2021/11–2024/11,在研,主持。
[2] 国家自然科学基金青年项目(编号:41701552),基于旋翼无人机监测的城市高架路边交通污染物的三维分布研究,2018/01–2020/12,已结题,主持。
[3] 广州市民生科技攻关计划项目(编号:201803030032),利用无人机观测技术研究城市细颗粒物的垂直分布特征,2018/04–2022/10,已结题,主持。
[4] 公司青年教师科研启动基金(编号:712018R0307),防护林对高架路交通污染物三维分布的影响研究,2020/04–2023/04,在研,主持。
[5] 国家自然科学基金委员会联合基金中心重大项目(编号:U1811463)子课题三,交通环境耦合建模与决策优化,2019/04–2022/03,在研,参与。
[6] 国家社科基金重大项目(编号:16ZDA048),城市交通政策和设施建设对大气环境影响的评价研究,2017/01–2020/12,已结题,参与。
[7] 上海市环保局重大专项(编号:2014–8),基于系留气球和无人机技术的区域输送对上海典型空气污染过程影响研究,2015/01–2016/05,已结题,参与。
三、专利及软著:
[1] 交通污染智能感知平台V1.0, 2023.05, 授权计算机软件著作权: 2023SR1047915
[2] 基于地空一体化的空气污染智能监测方法及平台, 2022.06, 申请发明专利: ZL 202210734211.2
[3] 基于无人机的空气污染监测位置及指标参数确定方法, 2023.10, 申请发明专利: ZL202311411805.0
[4] 基于实时和历史数据的无人机监测大气数据丢失补偿方法, 2023.10, 申请发明专利: ZL202311411824.3
[5] 一种基于无人机的大气污染物监测传感器的布局方法, 2018.12, 授权发明专利: ZL201811612946.8
[6] 一种无人机搭载的大气污染在线监测系统, 2018.12, 授权实用新型专利: ZL201822117898.7
[7] 基于无人机的工业园区大气污染数据采集方法, 2016.05, 授权发明专利: ZL201510292812.2
1. 硕士生
[1] 2019级,陈昕,已毕业
[2] 2020级,罗斌儒、马范、陈舒婷,已毕业
[3] 2021级,曹如晖、吴杰、杨文彬,研三在读
[4] 2022级,林鑫源、刘凯煊,研二在读
[5] 2023级,徐嘉敏、肖亚熙、董阳斌,研一在读
2. 奖励及荣誉
[2] 校优秀硕士学位论文基金,城市慢行道交通颗粒物时空热点识别及智能预报,罗斌儒,2021
[3] 校大员工创新训练项目,高架路旁交通污染的垂直分布特征研究,安兴等,2023
[4] 校大员工创新训练项目,道路交通污染的无人机智能监测技术,林晗宇等,2022
[5] 校本科生优秀毕业论文,绿地分隔带影响慢行道交通污染的实测研究,郑祥龙,2022
[6] 院本科生优秀毕业论文,城市慢行道交通颗粒物空间分布预测,黎吉强,2023
[7] 院本科生优秀毕业论文,道路大气颗粒物扩散的绿地响应模拟,魏霖,2022
[8] 院本科生优秀毕业论文,利用移动背包识别非机动车道颗粒物分布热点,曹如晖,2021
[9] 院本科生优秀毕业论文,行道树对高架路交通颗粒物分布的影响研究,王云路,2021
[10] 第九届全国大员工统计建模大赛研究生组省级二等奖,曹如晖,杨文彬,吴杰,2023
[11] 全国大员工测绘学科创新创业智能大赛测绘技能竞赛省级二等奖,崔佳辉,2023
3. 学术交流
[1] 2023世界交通运输大会交叉学部口头报告,杨文彬(优秀报告人)、吴杰、林鑫源,3人次,2023
[2] 2022世界交通运输大会交叉学部口头报告,罗斌儒、马范,2人次,2022
[3] 第16届全国环境博士生学术会议口头报告,罗斌儒、曹如晖,2人次,2022
[4] 2021中国地理学大会口头报告,陈昕,2021
[5] 院“第一届研究生学术论坛”口头报告,陈昕,一等奖,2021
[6] 院“第二届研究生学术论坛”口头报告,陈舒婷,一等奖,2022