Article(id=1317089717213057590, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1317089654613070048, articleNumber=null, orderNo=null, doi=10.3981/j.issn.1000-7857.2025.10.00030, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1760025600000, receivedDateStr=2025-10-10, revisedDate=1788364800000, revisedDateStr=2026-09-03, acceptedDate=null, acceptedDateStr=null, onlineDate=1791948258927, onlineDateStr=2026-10-14, pubDate=1789228800000, pubDateStr=2026-09-13, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791948258927, onlineIssueDateStr=2026-10-14, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791948258927, creator=13701087609, updateTime=1791948258927, updator=13701087609, issue=Issue{id=1317089654613070048, tenantId=1146029695717560320, journalId=1146031591421210625, year='2026', volume='44', issue='17', pageStart='1', pageEnd='140', issueExtLink='null', onlineDate='null', pubDate='1789228800000', pubDateStr='2026-09-13', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1791948244002, creator='13701087609', updateTime=1791948304422, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1317089908171322237, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1317089654613070048, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1317089908171322238, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1317089654613070048, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=65, endPage=74, ext={EN=ArticleExt(id=1317089717418578487, articleId=1317089717213057590, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Research progress on monitoring technologies for light pollution prevention and control, columnId=1150494642224591153, journalTitle=Science & Technology Review, columnName=Exclusive, runingTitle=null, highlight=null, articleAbstract=

With the widespread application of artificial nighttime lighting in urban areas, light pollution has become a global environmental issue, posing serious threats to human physical and mental health, the living rhythms of flora and fauna, and the stability and balance of entire ecosystems. Scientific, precise, and efficient light environment monitoring plays a crucial supporting role in source prevention and control, governance improvement, and long−term management. A review of frontier advances in technical innovation and monitoring network construction, both domestically and internationally, indicates that space−air−ground integrated monitoring is becoming the mainstream approach, and the application of emerging intelligent technologies will enhance the accuracy of light environment identification and classification. Future light environment measurement technologies are evolving towards greater precision, standardization, coordination, and intelligence. In view of the current state of light pollution monitoring in China, it is necessary to further refine policies and standards, promote the application of monitoring technologies, and accelerate the construction of a “space−air−ground” integrated monitoring network, thereby providing Chinese technical solutions for the modernization of light pollution governance.

, authors=Ying HAO1, 2, Xiaopeng WANG1, Weilong PENG1, Feng XUE1, Dagong JIA1, 3, authorsList=Ying HAO, Xiaopeng WANG, Weilong PENG, Feng XUE, Dagong JIA, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=All rights reserved. Unauthorized reproduction is prohibited., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1317089717917700664, articleId=1317089717213057590, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=面向光污染防治的监测技术研究进展, columnId=1150494642375586098, journalTitle=科技导报, columnName=特色专题, runingTitle=null, highlight=null, articleAbstract=

随着城市夜间人工照明的广泛应用,光污染已成为全球性环境问题,对人类身心健康、动植物生存节律乃至整个生态系统的稳定与平衡构成严重威胁。科学、精准、高效的光污染监测,是光污染源头防控、治理改善与长效管理的重要支撑。系统梳理了国内外光污染监测在技术创新、监测网络建设等方面的前沿进展。结果表明,“天空地”一体化监测将成为光污染监测的主流,新兴智能技术的应用将显著提升光污染识别与分类的准确性。未来,光污染监测技术将朝着精确化、标准化、协同化、智能化方向发展。立足中国光污染监测现状,应进一步完善政策标准,推动监测技术应用,加快构建“天空地”一体化监测网络,为光污染治理现代化提供中国技术方案。

, authors=郝影1, 2, 王晓鹏1, 彭炜龙1, 薛峰1, 贾大功1, 3, authorsList=郝影, 王晓鹏, 彭炜龙, 薛峰, 贾大功, authorCompany=null, correspAuthors=null, authorNote=

郝影,高级工程师,研究方向为噪声、振动、光污染治理,评估与监测,电子信箱:

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类型地面监测
监测指标方法/设备监测指标方法/设备
天空辉光上射光通比实验室计算配光曲线,根据光强确定
上射光通比
天空亮度二维影像亮度计/天空质量计
受光区域水平/垂直照度照度计区域亮度点式亮度计/二维影像亮度计
阈值增量亮度计、眩光仪眩光指数眩光仪
光源亮度亮度计色温色温仪
发光强度照度计/亮度计频闪频闪仪
), ArticleFig(id=1317089724725056106, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1317089717213057590, language=CN, label=表1, caption=

地面监测指标及监测设备

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类型地面监测
监测指标方法/设备监测指标方法/设备
天空辉光上射光通比实验室计算配光曲线,根据光强确定
上射光通比
天空亮度二维影像亮度计/天空质量计
受光区域水平/垂直照度照度计区域亮度点式亮度计/二维影像亮度计
阈值增量亮度计、眩光仪眩光指数眩光仪
光源亮度亮度计色温色温仪
发光强度照度计/亮度计频闪频闪仪
), ArticleFig(id=1317089724792164971, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1317089717213057590, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
指标类别核心指标标准依据/应用场景
光学物理指标垂直照度、上射光通比、色温GB/T 38439−2019(道路/建筑立面)[60]
生态影响指标SQM值、受威胁物种分布自然保护区暗夜评估[4,60]
社会经济指标区域照明能耗密度、人口密度城市光环境规划(深圳地方标准)[63]
), ArticleFig(id=1317089724859273836, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1317089717213057590, language=CN, label=表2, caption=

中国光污染监测指标

, figureFileSmall=null, figureFileBig=null, tableContent=
指标类别核心指标标准依据/应用场景
光学物理指标垂直照度、上射光通比、色温GB/T 38439−2019(道路/建筑立面)[60]
生态影响指标SQM值、受威胁物种分布自然保护区暗夜评估[4,60]
社会经济指标区域照明能耗密度、人口密度城市光环境规划(深圳地方标准)[63]
), ArticleFig(id=1317089724934771309, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1317089717213057590, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
监测技术主要技术方法研究特点
天基监测 DMSP−OLS卫星夜间灯光记录;目视观测星等变化;基础照度计测量;天文台系统性记录
 VIIRS−DNB高分辨率卫星遥感;国际空间站高分辨率成像。建立DMSP数据标准化处理流程;光污染物理传输模型;稳定灯光提取算法
 优点:区域覆盖面积广、时效性高
 缺点:数据精度不足,主要用于定性描述,观测方法主观性强、缺乏科学测量标准,受气象影响较大,时空间分辨率不足、灵活性差
低空监测无人机多光谱遥感技术;无人机载监测技术 优点:区域覆盖面积较大,测量精度显著提高;空间分布特征精细化分析能力较强
 缺点:数据精度不足,受气象影响较大
地面监测SQM天空质量测量仪系列化;区域性SQM监测网络
数字单反相机全天空成像,CCD技术光谱分析
 优点:自动化和便携性增强;光源解析能力强;初步网络化监测尝试
 缺点:空间广域观测范围有限
“天空地一体化”监测网络人工智能数据分析;多平台数据融合技术 空间分辨率和空间广域观测范围大幅提升;区域性和国家性网络建立;多尺度监测体系形成;智能化分析技术应用;公众参与科学项目
), ArticleFig(id=1317089724993491566, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1317089717213057590, language=CN, label=表3, caption=

光污染监测技术的发展现状

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监测技术主要技术方法研究特点
天基监测 DMSP−OLS卫星夜间灯光记录;目视观测星等变化;基础照度计测量;天文台系统性记录
 VIIRS−DNB高分辨率卫星遥感;国际空间站高分辨率成像。建立DMSP数据标准化处理流程;光污染物理传输模型;稳定灯光提取算法
 优点:区域覆盖面积广、时效性高
 缺点:数据精度不足,主要用于定性描述,观测方法主观性强、缺乏科学测量标准,受气象影响较大,时空间分辨率不足、灵活性差
低空监测无人机多光谱遥感技术;无人机载监测技术 优点:区域覆盖面积较大,测量精度显著提高;空间分布特征精细化分析能力较强
 缺点:数据精度不足,受气象影响较大
地面监测SQM天空质量测量仪系列化;区域性SQM监测网络
数字单反相机全天空成像,CCD技术光谱分析
 优点:自动化和便携性增强;光源解析能力强;初步网络化监测尝试
 缺点:空间广域观测范围有限
“天空地一体化”监测网络人工智能数据分析;多平台数据融合技术 空间分辨率和空间广域观测范围大幅提升;区域性和国家性网络建立;多尺度监测体系形成;智能化分析技术应用;公众参与科学项目
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面向光污染防治的监测技术研究进展
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郝影 1, 2 , 王晓鹏 1 , 彭炜龙 1 , 薛峰 1 , 贾大功 1, 3
科技导报 | 特色专题 2026,44(17): 65-74
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科技导报 |特色专题 2026 , 44 (17) : 65 -74
面向光污染防治的监测技术研究进展
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郝影1, 2 , 王晓鹏1, 彭炜龙1, 薛峰1, 贾大功1, 3
作者信息
  • 1天津大学精密仪器与光电子工程学院,天津 300072
  • 2天津市生态环境监测中心,天津 300191
  • 3天津大学卫生应急学院,天津 300072
作者简介:

郝影,高级工程师,研究方向为噪声、振动、光污染治理,评估与监测,电子信箱:

Research progress on monitoring technologies for light pollution prevention and control
Ying HAO1, 2 , Xiaopeng WANG1, Weilong PENG1, Feng XUE1, Dagong JIA1, 3
Affiliations
  • 1School of Accuracy Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
  • 2Tianjin Eco−Environmental Monitoring Center, Tianjin 300191, China
  • 3School of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China
出版时间: 2026-09-13 doi: 10.3981/j.issn.1000-7857.2025.10.00030
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随着城市夜间人工照明的广泛应用,光污染已成为全球性环境问题,对人类身心健康、动植物生存节律乃至整个生态系统的稳定与平衡构成严重威胁。科学、精准、高效的光污染监测,是光污染源头防控、治理改善与长效管理的重要支撑。系统梳理了国内外光污染监测在技术创新、监测网络建设等方面的前沿进展。结果表明,“天空地”一体化监测将成为光污染监测的主流,新兴智能技术的应用将显著提升光污染识别与分类的准确性。未来,光污染监测技术将朝着精确化、标准化、协同化、智能化方向发展。立足中国光污染监测现状,应进一步完善政策标准,推动监测技术应用,加快构建“天空地”一体化监测网络,为光污染治理现代化提供中国技术方案。

光污染  /  监测技术  /  防治  /  环境  /  监测指标

With the widespread application of artificial nighttime lighting in urban areas, light pollution has become a global environmental issue, posing serious threats to human physical and mental health, the living rhythms of flora and fauna, and the stability and balance of entire ecosystems. Scientific, precise, and efficient light environment monitoring plays a crucial supporting role in source prevention and control, governance improvement, and long−term management. A review of frontier advances in technical innovation and monitoring network construction, both domestically and internationally, indicates that space−air−ground integrated monitoring is becoming the mainstream approach, and the application of emerging intelligent technologies will enhance the accuracy of light environment identification and classification. Future light environment measurement technologies are evolving towards greater precision, standardization, coordination, and intelligence. In view of the current state of light pollution monitoring in China, it is necessary to further refine policies and standards, promote the application of monitoring technologies, and accelerate the construction of a “space−air−ground” integrated monitoring network, thereby providing Chinese technical solutions for the modernization of light pollution governance.

light pollution  /  monitoring technology  /  prevention and control  /  light environment  /  monitoring index
郝影, 王晓鹏, 彭炜龙, 薛峰, 贾大功. 面向光污染防治的监测技术研究进展. 科技导报, 2026 , 44 (17) : 65 -74 . DOI: 10.3981/j.issn.1000-7857.2025.10.00030
Ying HAO, Xiaopeng WANG, Weilong PENG, Feng XUE, Dagong JIA. Research progress on monitoring technologies for light pollution prevention and control[J]. Science & Technology Review, 2026 , 44 (17) : 65 -74 . DOI: 10.3981/j.issn.1000-7857.2025.10.00030
光作为地球生命赖以生存的环境要素,不仅为生命运转提供动力源泉,更具有调控生物节律等生态过程的重要作用[1−3]。然而,随着全球经济发展,过度和不合理的人工照明导致光污染问题显著增长[4−6],引发了公众的担忧[7]。2023年全球光污染地图显示,83%的人类居住区夜空亮度超出自然阈值3倍以上,40%的陆地生态系统面临夜间光干扰威胁,直接引发鸟类迁徙路线偏移等生态危机[8−10]。
光环境的剧烈改变严重威胁适应能力较弱的动植物,对人类的影响也不容忽视[11]。在生态环境方面,光污染会引发水稻减产、病害增加,甚至造成城市局部生态系统崩坏[12−13]。有学者指出,光污染会对地球气候产生影响,是引起全球生态危害的重要因素之一[14]。在人体健康方面,光污染可导致人体免疫系统功能异常,诱发癌症等[15]。
中国作为全球最大的照明产品生产与消费国,夜间光环境持续恶化,同样面临着严峻的光污染防治挑战。研究显示,2012—2020年,京津冀城市群夜间灯光总量逐年递增,整体增长超过130%[16],华北地区照明碳排放年均增速达6.7%[17],光污染投诉量的逐年增长,促使深圳、上海等超大城市将光污染防治纳入地方环境立法[18],中国首批建立的国家公园(熊猫、东北虎豹、海南热带雨林、三江源和武夷山等)光污染指数均呈显著上升趋势,夜间照明总指数增长了52.2倍,在青藏高原、三江源等生态脆弱区的天然光环境正遭受人类活动的冲击,严重影响了当地生态平衡[19]。
为了更好地保护人居环境和野外自然光环境,中国亟须系统性地开展光污染防治[20]。本文聚焦光污染防治工作中重要的环境监测环节,按照天基监测、低空无人机载监测和地面监测3类,从监测技术和监测指标2个层面阐述国内外发展现状,系统梳理国内外光污染监测在技术创新、监测网络建设等方面的前沿进展。立足中国光污染防治现状,深入剖析中国光污染监测领域的关键制约因素,并提出相应的针对性策略,力求为构建“天空地”一体化监测网络,完善光污染“监测—评估—治理”闭环管理,提供坚实的理论支撑与明确的实践路径。
随着工业化发展和城市化进程推进,光污染问题逐渐凸显,已成为社会普遍关注的环境问题[21]。国际社会很早就关注光污染问题,并制定多个标准以减少人造光源的干扰。1980年,国际照明委员会(International Commission on Illumination,CIE)就关注到天空光对天文观测的影响,并与国际天文联合会(International Astronomical Union,IAU)联合发表了减少靠近天文台城市的天空光的相关文章,呼吁靠近天文台的城市减少天空光污染[22]。目前,CIE已经发布了包括《室外照明装置干扰光影响的限制指南》(CIE 150)在内的10余个关于夜景照明和干扰光防治的技术文件[23−24],促进光污染的治理,推动照明设计朝着更环保、节能和对天文观测友好的方向发展。
光污染监测技术的发展经历了从简单观测到多设备、多平台协同精密监测、评估的演进过程,其监测技术发展与环境保护意识的觉醒、航天技术的发展以及精密仪器制造能力的提升密切相关。早期光污染监测研究主要依托天文观测需求驱动,监测技术主要依靠目视观测和基础光度测量设备,技术手段相对单一,数据的时空精度也不足,主要用于光污染定性描述而非定量分析,但为后续发展奠定了基础。天文学家通过肉眼观测星空的变化评估不同地区的光污染程度,使用简单的照度计测量地面光强,但测量方法缺乏标准化,数据可比性差[6]。20世纪60年代,美国国防气象卫星计划(Defense Meteorological Satellite Program,DMSP)无意中记录到夜间城市灯光数据,但当时这些数据主要用于军事目的[25]。1972年,DMSP数据解密后,科研人员开始意识到卫星夜间灯光数据在光污染研究中的巨大潜力,这是卫星遥感技术在光污染监测中应用的起点。DMSP−OLS(Operational Linescan System)卫星最初用于云层检测和气象观测,但其夜间模式意外捕获了城市灯光信息,成为第一个系统性记录全球夜间灯光的光学系统,其空间分辨率约为2.7 km,为后续的光污染研究奠定了数据基础[26]。
20世纪90年代后期,光污染研究开始系统化,理论基础逐步建立。2001年,基于DMSP卫星数据制作的首个“世界人工夜空亮度图集”发布,标志着全球尺度光污染评估技术的建立。该成果不仅展示了全球光污染的空间分布格局,更是建立了从卫星观测数据推算地面光污染水平的技术方法体系。研究人员开发了光污染的物理传输模型,通过卫星观测得到的逃逸光量反推地面光污染水平。这些模型考虑了大气散射、地表反射等物理过程,为后续的精确测量奠定了理论基础[27]。同时,建立了DMSP夜间灯光数据的标准化处理流程,包括辐射定标、几何校正、年际间定标等技术方法,发展了稳定光源亮度提取算法,去除船只、火灾等临时光源的干扰。基于图集的地面光源亮度评估工作也开始标准化,包括卫星测量设备选择、观测条件要求、数据记录格式等技术标准的建立[24]。天文观测台开始系统性记录夜空亮度变化,为长期趋势分析提供基础数据。这一时期光污染研究开始从天文学扩展到环境科学、城市规划等多个领域,推动了监测技术的多样化发展。
2010年后,随着人工智能的迅速发展,光污染监测技术也随之向着智能化发展。2011年发射的VIIRS(visible infrared imaging radiometer)传感器的昼夜波段(day/night band,DNB)代表了卫星夜间监测技术的重大进步[6],相比DMSP−OLS,VIIRS−DNB(visible infrared imaging radiometer suite day/night band)具有更高的空间分辨率、更好的辐射定标精度和更宽的动态范围[28]。VIIRS提供月度无云合成数据,支持更精细的时间变化分析,显著提升了卫星遥感在光污染监测中的应用效果。国际空间站(International Space Station,ISS)搭载的高分辨率相机也开始用于光污染监测,能够提供米级别分辨率的夜间城市灯光图像,为城市尺度的光污染精细化分析提供了新的技术手段。
随着电荷耦合器件(charge−coupled device,CCD)技术的进步,光谱仪开始应用于光污染源的识别和分析。研究人员能够通过光谱特征识别不同类型的光源(如高压钠灯、金属卤化物灯、荧光灯等),为光污染源头控制提供科学依据。在卫星遥感监测技术方面,DMSP的数据处理技术得到完善,发展了更加精确的数据处理算法,包括饱和像元处理、跨传感器定标、长时间序列分析等技术[27],提高了监测的精度和效率,建立了全球夜间灯光数据库,支持大尺度光污染时空变化分析。
鉴于卫星实现光污染监测存在空间精度低、数据单一的问题,无人机遥感技术快速兴起,成为光污染监测技术体系的重要组成部分。2016年,英国诺丁汉特伦特大学首创无人机载SQM(sky quality meter)系统监测夜空光环境,绘制光污染地图,解决了卫星监测数据空间分辨率不足问题[29]。2022年,意大利团队利用无人机上的数码相机检测夜间地面亮度,并验证RGB影像亮度指数与地面实测亮度的强相关性(R2=0.88),确立无人机影像替代地面测量的可行性[30]。2024年,波兰格但斯克工业大学设计了一款专用于光污染监测的无人机平台,同时搭载数码相机(Sony Alpha 6000)、天空质量计(Unihedron SQM−LU−DL)、多光谱相机(MicaSense Dual RedEdge−MX)与光谱仪(UPRtek MK350D)。通过100 m高度的水平航飞,该平台实现了路灯光谱特征与亮度的精细识别;通过200 m高度的垂直剖面飞行,验证了SQM读数在10 m 离地高度以上趋于稳定的规律,为移动式天空质量测量确立了最佳作业高度[31]。基于无人机载平台的光污染监测,解决了基于卫星平台光污染监测存在的空间分辨率不足、灵活性差和地面观测站光污染监测区域受限的问题,能够针对特定区域进行详细的光污染特征分析,但是复杂大气条件对成像的干扰和夜间飞行安全、续航限制等问题也为光污染低空无人机载监测技术带来了挑战。
卫星与无人机遥感通过自上而下观测地面向上光辐射,能够直观获得区域光污染的区域分布;地面监测虽监测覆盖范围小,但指标维度丰富,具有不可替代的优势。各国研究者利用SQM、数码相机、亮度计、照度计、眩光仪等设备,获取城市街区尺度的精细光污染数据[24, 28],其涵盖指标包括天空辉光亮度、光源光度参数(亮度、发光强度、色温、频闪)及受光面光环境参数(亮度、照度、眩光、阈值增量)(表1)。
在天空亮度方面,21世纪初,加拿大Unihedron公司推出了首款商业化天空质量测量仪SQM,使普通公众和研究者都能便捷量化夜空亮度,是光污染监测技术发展的重要里程碑[28]。SQM具有自动化测量、数据记录、便携性强等特点,成为全球光污染监测的标准设备。随着SQM技术不断改进,还发展出多种型号以满足不同监测需求,例如SQM−L、SQM−LU和SQM−LE等。2011年Kyba使用SQM观察了德国柏林的夜空亮度,并分析了云量对城市光污染的影响[32]。地面监测网络在这一阶段得到了系统化发展,形成了多个具有代表性的区域性和国家性监测网络。如奥地利州政府运营着欧洲最密集的SQM监测网络,该网络包含多个长期监测站点,覆盖城市地区、人口中等密度地区和农村地区[33]。西班牙光污染研究协作网络(Red Espan̈ola de Estudios sobre la Contaminación Lumínica,REECL)建立了全国性的SQM监测系统,特别关注保护区的光污染监测,结合大气传输模型分析不同光源的贡献[34]。荷兰国家公共卫生与环境研究所(Rijksinstituut voor Volksgezondheid en Milieu,RIVM)建立了由9台SQM−LE组成的国家级夜空亮度监测网络,用于跟踪荷兰光污染的长期变化趋势[35]。格罗宁根大学卡普坦天文研究所亦在荷兰北部建立了区域SQM网络(Was het donker),2020—2023年数据显示最暗区域光污染正以每年2.78%~6.68%的速度增长[36]。
2002年,美国YANKEE公司推出结合数字相机的新型半球天空成像仪(hemispheric sky imager,HSI)。由此,基于数字相机的全天空成像技术开始应用于光污染监测。该技术使用鱼眼镜头覆盖整个天空半球,通过图像处理算法分析不同方向的光污染强度[28]。相比单点测量的SQM,全天空成像能够提供完整的夜空亮度分布图,揭示环境光的空间分布特征和主要来源方向。2015年,Dobler等[37]使用数码相机在美国曼哈顿同一地点拍摄了22个夜晚的照片,并分析了该地区光景的变化。2019年,Jechow等[38]利用鱼眼镜头相机拍摄的全天空图像测量夜空亮度,并分析了云和雪对天光的影响。美国国家公园管理局(National Park Service,NPS)在近100个国家公园开展夜空质量监测,开发了专门的便携式CCD相机系统,能够快速获取高分辨率的全天空亮度马赛克图像,精确测量天空亮度和眩光分布[39]。地面监测指标及相关监测设备可见表1。
“天空地一体化”生态系统监测是综合运用卫星遥感监测、航空遥感监测和地面站点监测等环境监测手段,基于数据挖掘、数据融合、数据协同和数据同化等关键技术,获得更加准确数据支持的立体生态监测感知体系。为了应对天基监测、低空无人机载、地面监测3种不同监测技术的光污染监测存在的技术瓶颈问题,多种监测技术协同融合成为主要趋势。天空地一体化监测,或天地联动监测等技术被广泛应用于科学研究领域。2016年,俄罗斯科学院利用卫星遥感技术和地面观测站点,监测和研究俄罗斯境内光污染状况,并分析了光污染对天文观测和天文学研究的影响[6]。2020年开始,欧盟“LIGHT4CITIES”项目通过卫星遥感与地面监测结合,量化分析光污染对城市绿地昆虫多样性的影响,发现LED路灯改造可使甲虫类生物量恢复15%[40]。2019年,瑞典斯德哥尔摩大学的研究团队通过卫星遥感、无人机和实地监测相结合的方法,研究了光污染对瑞典野生动物栖息地、迁徙和行为的影响,为保护当地野生动物多样性和生态系统平衡提供了科学依据和决策支持[41]。
与此同时,数据智能化分析方法和技术在此阶段得到快速发展,研究人员开发了卫星遥感与地面监测数据的融合方法,通过将VIIRS卫星数据与地面SQM网络数据相匹配,可以显著提高天空亮度预测的准确性[42],这种融合方法能够更好地降低大气散射效应,提高监测数据信噪比。人工智能和机器学习技术开始广泛应用于光污染数据分析,这些技术能够处理大规模的多源数据,识别光污染模式,预测未来趋势。特别是深度学习算法用于卫星图像的光源识别和分类管理,显著提高了识别精度[43]。Globe at Night等公众科学项目利用智能手机应用和简化的观测方法,动员全球公众参与光污染监测,这些项目不仅扩大了监测网络的覆盖范围,还提高了公众对光污染问题的认识[44]。
综上,光污染监测技术经历了从早期的直接观测,到地面监测技术的大发展与广泛应用,随着卫星天基监测与低空无人机监测技术的显著进步,最终促进了“天空地”一体化监测网络的构建。
光污染监测是环境保护和生态评估的前提条件,也是对光污染防治需求的响应。通过卫星、无人机和地面监测实现光污染监测,每种监测技术都伴随着特定监测方法和测量手段,所获得的光污染指标在精度、范围和应用领域方面各有特色,共同构成了多层次、多维度的光污染评价体系。
卫星遥感作为大尺度光污染监测的主要手段,目前主要依托VIIRS DNB和DMSP等监测系统平台获取全球夜间灯光数据[25,45]。卫星观测的核心指标包括夜间灯光亮度,以数字量化值(digital number,DN值)表示地表人工光源的辐射强度,以及天空亮度(通常以天文等级每平方角秒(mag/arcsec2)为单位测量夜空的整体亮度水平[46])。此外,上射光通量作为从地表向大气层辐射的人工光通量测量值,是评估光污染源强度的核心指标[47]。
在综合评估方面,卫星遥感还能提供总夜间灯光指数(total nighttime light,TNL)来反映特定区域内光污染的累积效应,以平均夜间灯光强度(average nighttime light,ANL)表征区域内的整体光污染水平,以及夜间灯光标准差(standard deviation of night light,SDNL)来反映光污染空间分布的均匀性[48]。这些指标能够支持大尺度的光污染时空变化分析,为宏观环境政策制定提供科学依据。然而,受限于卫星传感器的空间分辨率、光谱分辨率和动态时序性,卫星遥感在获取局部精细光污染特征方面,如地面色温和人群感知存在一定局限性。
无人机遥感平台因其灵活性和较高分辨率特点,能够弥补卫星遥感的不足,获得比卫星更为丰富和精细的光污染参数。无人机搭载的传感器可以实现地面分辨率0.12 m级别的高分辨率亮度分布测量[49],使得对单个光源和小范围区域的光污染特征分析成为可能。在光学指标方面,无人机除了能获取传统的亮度和照度信息外,还能测量对比亮度,即目标与背景之间的亮度差异,此为评估视觉质量的重要指标。
无人机平台在光谱分析方面具有显著优势,能够获取400~700 nm波长范围内的详细光谱功率分布(spectral power distribution,SPD),为光源类型识别和光污染成分分析提供重要数据[50]。相关色温(correlated color temperature,CCT)作为以开尔文(K)为单位的光源颜色特征参数,通常在3000~7500 K范围内变化,无人机能够精确测量并分析不同区域光源的色温分布特征[51]。此外,无人机还能够进行动态时序监测,不同功能区域的夜间光强变化模式存在差异,为理解城市光污染的动态特征提供了新的视角。
地面观测技术作为最传统也是最精确的监测方式,使用的设备类型最为多样,获得的光污染指标也最为全面和深入。在基础光度学指标方面,地面观测能够精确测量地面水平照度、垂直照度及表面亮度。天空质量测量仪(sky quality meter,SQM)作为标准化设备,能够获得天顶方向的天空亮度,测量精度较高,为夜空质量评估提供了可比较的定量数据[52]。亮度均匀度作为评估照明分布均匀性的重要指标,对于城市照明规划和光污染控制具有重要意义。
地面观测在光谱分析方面具有最高的精度和最宽的光谱范围,能够获取从250 nm紫外波段至近红外波段的完整光谱特征[53]。亮度、光强作为光源发光强度的重要监测参数,CCT和显色指数(color rendering index,CRI)作为光源色彩质量评估的核心参数,在地面观测中能够得到最精确的测量。眩光指数,包括统一眩光评级(unified glare rating,UGR)等指标,是评估人工照明光对视觉舒适度影响的重要参数[54]。阈值增量作为评估光污染对视觉功能影响的定量指标,能够直接反映环境光对人眼视觉能力的损害程度,照度作为光对人居环境影响的重要考量指标被广泛应用。
这些监测技术和指标的综合应用,为光污染的科学评估、环境影响研究和治理策略制定提供了坚实的技术支撑。随着监测技术的不断进步和标准化程度的提高,光污染监测将为光污染防治发挥越来越重要的作用。
随着国内城市化水平的提高,城市规模不断扩张,人造光源应用的广度和深度不断扩大,同样对城市和野外的生态系统带来不良影响。当前,中国北京、上海、重庆、深圳、哈尔滨、杭州等地均存在不同程度的光污染超标现象,其中广告屏光污染最为严重,已经对驾驶安全和行人健康构成潜在危险,成为一种社会公害[55]。
面对光污染带来的社会公害,国家和地方政府、行业管理部门纷纷制定了管控标准,如GB/T 34973—2017《LED显示屏干扰光现场测量方法》[56]、GB/T 35626—2017《室外照明干扰光限制规范》[57]、GB/T 12454—2017《光环境评价方法》[58]、GB/T 36101—2018《LED显示屏干扰光评价要求》[59]、GB/T 38439—2019《室外照明干扰光测量规范》[60]、CJJ45—2015《城市道路照明设计标准》[61]、DB/T 29—71—2021《天津市城市夜景照明工程技术标准》[62]、DB4403/T 333—2023《夜间光环境区域限值》[63],以及DB23/T 3306—2022《城市户外LED广告屏干扰光条件限制规范》[64]等。这些标准涉及环境光亮度的分类、干扰光影响和来源、干扰光的评价、光污染测量方法等方面,为抑制和防治光污染提供依据。
中国《“十四五”生态环境监测规划》提出实施天地一体智慧监测预警重大工程,并明确要求“探索开展光污染监测和光环境质量评价研究”;雄安新区容东片区部署的逾7000根多功能信息杆柱集成空气质量、气象、噪声等环境传感模块,其“一杆多能”的建设模式为未来光污染一体化监测网络的布设提供了基础设施借鉴。2022年《上海市环境保护条例》首次将光污染纳入地方立法,规定建筑物照明需符合生态保护要求。深圳市西涌国际暗夜社区作为中国首个获国际暗夜协会认证的暗夜社区,依托深圳市气象局牵头编制的《西涌国际暗夜社区天文观测及户外照明设置指引》及《暗夜社区光环境规范》地方标准,通过在天文台布设天光监测设备并建立天文观测信号照明联动机制,初步实现了光污染动态管控。2026年8月15日起施行的《中华人民共和国生态环境法典》在污染防治编中专章规定光污染防治,首次在国家法律层面确立了光污染定义、监管体制与法律责任体系,为中国开展光污染防治提供了系统的法律依据。
相比国外发达国家,中国对光污染的认识和管理起步晚一些,对应的光污染监测技术与发达国家相比仍存在一定差距,特别是在标准化和系统化方面[65]。尽管如此,中国的光污染监测技术正处于快速发展阶段,在中国“双碳”目标与生物多样性保护战略指引下[17−18],已尝试将卫星夜光遥感纳入综合监测体系。2018年,武汉大学“珞珈一号”科学实验卫星01星在酒泉卫星发射中心成功发射,这是中国首颗专业夜光遥感卫星[66],被用于天空光照的监测,Li等[67]通过珞珈1−01夜间光影像数据绘制了南京市上空光照环境的空间格局。珞珈一号卫星具备高分辨率夜光成像能力,空间分辨率达到130 m,相比VIIRS−DNB的分辨率有显著提升。“可持续发展科学卫星1号”(SDGSAT−1)卫星以10 m(全色)和40 m(彩色)分辨率的微光成像能力,实现了对白色LED、红色LED、高压钠灯等照明类型的精细识别,并在城市光污染空间异质性刻画中展现出突出潜力。然而,在监测网络上,与国外成熟的SQM监测网络相比,中国地面光污染监测网络建设相对滞后。目前主要依托天文观测台站和科研院所开展零散的观测活动,缺乏系统性的国家级监测网络。
在传感器研发方面,国内光电传感器芯片虽然自给率不高,但随着传感器市场需求量的激增,国家出台了多项政策扶持集成电路(integrated circuit,IC)企业的发展,企业也越来越重视光电传感器的研究[68]。此外,厦门大学、中国科学院上海技术物理研究所、天津大学也对光电检测理论及光电传感器投入了大量资金进行研究。卢杭全[69]采用标准互补金属氧化物半导体(complementary metal oxide semiconductor,CMOS)工艺,开发了集成环境光感测与接近感测功能的二合一传感器芯片。通过跨阻放大器(trans-impedance amplifier,TIA)与逐次逼近型模数转换器(analog to digital converter,ADC)的协同工作,成功将光强信号转换为数字输出,实现了高达10 kLx的环境光动态检测范围。陈志辉[70]提出了一种创新的自适应分辨率调节方法,通过动态调整ADC分辨率来模拟人眼对光强的对数响应特性:在强光污染下采用较低的ADC有效分辨率,而在弱光条件下提升ADC分辨率,成功将环境光传感器的检测范围拓展至0.1 Lx~10 kLx的宽广区间。赵晨等[71]针对长波红外焦平面探测器的噪声抑制问题,开发了基于两步背景抑制算法的创新结构,通过有效滤除光敏单元固有的暗电流噪声,显著改善了红外焦平面读出电路在强背景光干扰环境下的信噪比表现,为高精度红外探测应用提供了重要技术支撑。
目前,中国采用的光污染监测指标更多参照国际上通用指标实现光污染监测。随着国内开展侧重人居环境和生态影响的光污染防治,光环境监测指标将逐步本土化。中国光污染监测指标见表2。
光污染监测技术正朝着精确化、标准化、协同化和智能化的方向发展(表3),技术发展将更加注重多学科交叉融合,从单纯的技术研发向应用导向转变。同时,光污染测量技术将更加注重与环境保护政策的结合,为照明管理、城市规划和生态保护提供科学支撑。随着全球对光污染问题认识的深入和环境保护要求的提高,光污染测量技术将在推动全球范围内的光污染防控工作中发挥越来越重要的作用。
中国开展的光污染监测多为科研机构获取有限的监测结果,即科研监测范围和时间常常是有限的,其数据获取的空间和时间维度都具有一定的局限性,还不足以支撑时空维度光污染保护和光污染防治工作,城市光污染的评估还过多依赖于推演算法。
中国光污染监测技术发展面临多重技术瓶颈,主要表现为核心传感器件对外依存度较高,高精度光谱仪、环境光传感器等关键器件主要依赖进口,技术自主可控能力不足;现有监测点位多为科研院所和天文台站分散布设,缺乏统一规划的国家级监测网络,难以形成区域性光污染态势感知能力;多源数据融合技术有待完善,不同技术手段获取的数据在空间分辨率、时间同步性和光谱响应特性方面存在差异。同时,标准化体系建设滞后,现有标准主要聚焦于照明设备技术规范,而监测方法、数据质量控制、评价指标体系等相对缺乏,不同地区和部门的监测标准存在差异,导致数据可比性不强。
法律法规体系有待健全,多部门管理体制下职责边界不够清晰,协调机制有待完善,针对不同类型光污染源的分类管理标准和执法依据需要进一步细化。产业化应用推广面临困难,光污染监测设备成本相对较高,特别是高精度、多参数监测设备,限制了大规模推广应用;监测数据与环境管理决策结合度不够紧密,数据价值挖掘和应用转化能力有限;社会公众对光污染危害认知程度不高,市场需求驱动力不足,影响了相关技术和产品的产业化发展。
随着中国光污染治理的不断深化,特别是《生态环境法典》设立光污染防治专章,不仅为治理工作提供了最高法律依据,更奠定了精细化管理的基础,而科学、合理的监测技术是实现这一目标的前提。未来,中国光污染监测技术将朝着智能化、网络化、精准化方向发展。在监测网络层面,将针对不同区域特性,构建覆盖城市群、生态敏感区、天文观测区等关键区域的“天空地”一体化网络,逐步实现多尺度、多维度的综合监测。在核心技术方面,传感器技术将逐步打破高端产品对外依赖,基于CMOS工艺的光电传感器将实现更高集成度与更低功耗。人工智能技术与传统监测技术的深度融合,利用机器学习算法显著提升光污染源识别、评估及预测能力;同时,作为天基监测基础的卫星遥感技术将持续发挥关键作用,随着低空在轨卫星的密集部署,中国夜光遥感监测的时空分辨率和覆盖能力将得到进一步提升。
基于环境保护的光污染监测是实现生态文明建设的关键技术支撑。中国光污染监测在政策、技术和应用方面取得了一定的进展,具备了一定的基础,但仍面临标准滞后、技术应用滞后等挑战。未来需以技术创新为核心,结合中国光污染监测现状,加快构建符合国情的光污染监测标准体系,填补监测方法与评价规范的空白;大力推进天空地一体化监测网络的工程化落地,实现对重点区域的全覆盖动态监控;深化人工智能等技术在数据分析和源头溯源中的应用,提升监测数据的决策支撑能力;建立健全跨部门数据共享与协同治理机制,从而为光污染的精准防控提供科学依据,全面提升中国光污染治理的现代化水平。

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doi: 10.3981/j.issn.1000-7857.2025.10.00030
  • 接收时间:2025-10-10
  • 首发时间:2026-10-14
  • 出版时间:2026-09-13
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  • 收稿日期:2025-10-10
  • 修回日期:2026-09-03
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    1天津大学精密仪器与光电子工程学院,天津 300072
    2天津市生态环境监测中心,天津 300191
    3天津大学卫生应急学院,天津 300072
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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