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Analysis of PM2.5 concentrations in Heilongjiang Province associated with forest cover and other factors 被引量:6
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作者 Yu Zheng San Li +2 位作者 Chuanshan Zou Xiaojian Ma Guocai Zhang 《Journal of Forestry Research》 SCIE CAS CSCD 2019年第1期269-276,共8页
Atmospheric particulate matter(PM2.5) seriously influences air quality. It is considered one of the main environmental triggers for lung and heart diseases. Air pollutants can be adsorbed by forest. In this study we i... Atmospheric particulate matter(PM2.5) seriously influences air quality. It is considered one of the main environmental triggers for lung and heart diseases. Air pollutants can be adsorbed by forest. In this study we investigated the effect of forest cover on urban PM2.5 concentrations in 12 cities in Heilongjiang Province,China. The forest cover in each city was constant throughout the study period. The average daily concentration of PM2.5 in 12 cities was below 75 lg/m^3 during the non-heating period but exceeded this level during heating period. Furthermore, there were more moderate pollution days in six cities. This indicated that forests had the ability to reduce the concentration of PM2.5 but the main cause of air pollution was excessive human interference and artificial heating in winter. We classified the 12 cities according to the average PM2.5 concentrations. The relationship between PM2.5 concentrations and forest cover was obtained by integrating forest cover, land area,heated areas and number of vehicles in cities. Finally,considering the complexity of PM2.5 formation and based on the theory of random forestry, we selected six cities and analyzed their meteorological and air pollutant data. The main factors affecting PM2.5 concentrations were PM10,NO_2, CO and SO_2 in air pollutants while meteorological factors were secondary. 展开更多
关键词 FOREST COVER Heilongjiang PROVINCE influencing factor pm2.5 CONCENTRATIONS RANDOM FOREST
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The Relationship between Major Components of PM2.5 and Meteorological Factors in Urban Tokyo, Japan
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作者 Ping Li Hideo Hasegawa 《Journal of Environmental Science and Engineering(B)》 2017年第1期27-33,共7页
In this research, the main purpose is to estimate the variation of PM2.5 mass concentration and study the influence of meteorological characteristics on major components of PM2.5 concentrations in urban Tokyo, Japan. ... In this research, the main purpose is to estimate the variation of PM2.5 mass concentration and study the influence of meteorological characteristics on major components of PM2.5 concentrations in urban Tokyo, Japan. The results shown that the annual mean mass concentration of PM2.5 in urban Tokyo was higher than JEQS (Japanese Environmental Quality Standard) of the MOEJ (Ministry of the Environment Japan) (15 μg/m^3), and 41.1% of the daily PM2.5 mass concentration exceeded the annual JEQS concentration during observation period. The major components of PM2.5 including SO4^2-, NO3^-, NH4^+, OC and EC were tightly related to the meteorological conditions, the correlations results shown that the wind speed and relative humidity had significant correlations with major components of PM2.5 than the other meteorological factors. Higher relative humidity, windless and less rainfall conditions were favorable for elimination of PM2.5 concentration. Higher temperature was beneficial to the formation of SO42", but higher temperature and stronger sunshine duration were not conducive to the formation of NO3^-. 展开更多
关键词 pm2.5 major components meteorological factors.
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Analysis on Characteristics and Meteorological Influencing Factors of Air PM 2.5 Pollution in Chongqing,China
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作者 Xianshuang YANG Limei WU Chao JIN 《Meteorological and Environmental Research》 CAS 2020年第5期125-130,共6页
Based on the real-time data released by 17 atmospheric automatic stations in Chongqing,the pollution characteristics and variation trends of PM 2.5 and PM 10 and their correlations with meteorological factors from Jan... Based on the real-time data released by 17 atmospheric automatic stations in Chongqing,the pollution characteristics and variation trends of PM 2.5 and PM 10 and their correlations with meteorological factors from January 2014 to December 2018 were analyzed.The results show that the annual average mass concentration of PM 2.5 in Chongqing reduced from 65μg/m 3 in 2014 to 40μg/m 3 in 2018,and the annual average mass concentration of PM 10 decreased from 98μg/m 3 in 2014 to 64μg/m 3 in 2018.However,the annual average mass concentration of PM 2.5 in Chongqing from 2014 to 2018 and the annual average mass concentration of PM 10 from 2014 to 2016 exceeded the national level II standard,and the maximum exceeding standard rate was up to 0.86 and 0.40 times respectively.The monthly average mass concentration of PM 2.5 and PM 10 changed obviously,and the overall distribution was"U"-shaped.The ratio of PM 2.5 to PM 10 mass concentration ranged from 47.4%to 80.7%,with an average of 62.4%.The Pearson correlation coefficient between the mass concentration of PM 2.5 and PM 10 varied from 0.961 to 0.989,and there was a significant correlation at the confidence level of 0.01(bilateral).The mass concentration of PM 2.5 and PM 10 was extremely significantly correlated with average temperature,precipitation,and average air pressure,while there was no significant correlation between the mass concentrations of PM 2.5 and PM 10 and average relative humidity.The mass concentration of PM 2.5 and PM 10 was significantly correlated with sunshine duration. 展开更多
关键词 PM 2.5 PM 10 Meteorological factors CHONGQING
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Predictive Meteorological Factors for Elevated PM2.5 Levels at an Air Monitoring Station Near a Petrochemical Complex in Yunlin County, Taiwan
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作者 Yee-Hsin Kao Chih-Wen Lin Jui-Kun Chiang 《Open Journal of Air Pollution》 2019年第1期1-17,共17页
Since 1991, air pollution has gained special attention in Taiwan after a petrochemical complex was constructed in Mailiao Township, Yunlin County. We explored the association between the magnitude of PM2.5 and meteoro... Since 1991, air pollution has gained special attention in Taiwan after a petrochemical complex was constructed in Mailiao Township, Yunlin County. We explored the association between the magnitude of PM2.5 and meteorological factors during 2012-2016. Our findings revealed that 1) mean PM2.5 levels gradually decreased from 30.70 μg/m3 in 2013 to 25.36 μg/m3 in 2016;2) wind speed is the main determinant of air quality—air quality significantly improved when it was faster than 4 m/sec;and 3) wind direction is another determinant of air quality—when the wind direction was southerly, air quality improved. Elevated PM2.5 levels were defined as those hourly levels higher than the third quartile (36 μg/m3). The significantly negative predictive factors for elevated PM2.5 levels were the summer or autumn seasons, rainfall, increased wind speed, and wind direction from 150&#176 to 230&#176 from the north. The significantly positive predictive factors for elevated PM2.5 levels were working hours from 6 a.m. to 2 p.m., a temperature between 11&#176C and 25&#176C, relative humidity between 40% and 68%, and wind direction (e.g., northerly wind, northeasterly wind, and easterly wind). The predictive formula is attached in the Appendix. Therefore, people should protect themselves on these high-risk days. 展开更多
关键词 Fine PARTICULATE Matter (pm2.5) PETROCHEMICAL Complex METEOROLOGICAL factors
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2015年上海崇明岛PM2.5和 PM10浓度变化特征及气象因素影响分析 被引量:19
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作者 吴健 齐晓宝 +4 位作者 苏敬华 李佳凤 沙晨燕 熊丽君 王敏 《气象与环境科学》 2019年第3期1-8,共8页
通过对2015年1-12月上海崇明岛崇南地区颗粒物(PM2.5、PM10)浓度的连续监测,研究了PM2.5、PM10在不同季节的动态变化特征及与其他因子(SO2、NO2、O3)的相关性,分析了风向风速和降雨对颗粒物浓度的影响。结果表明:崇明岛PM2.5和PM10浓度... 通过对2015年1-12月上海崇明岛崇南地区颗粒物(PM2.5、PM10)浓度的连续监测,研究了PM2.5、PM10在不同季节的动态变化特征及与其他因子(SO2、NO2、O3)的相关性,分析了风向风速和降雨对颗粒物浓度的影响。结果表明:崇明岛PM2.5和PM10浓度的季节变化明显,呈现冬季的>春季的>秋季的>夏季的的特征,冬季PM2.5和PM10小时浓度均值分别为0.058mg/m^3和0.085mg/m^3,夏季PM2.5和PM10均值分别为0.034mg/m^3和0.054mg/m^3。PM2.5和PM10浓度分别与SO2浓度和NO2浓度显著正相关,与O3显著负相关。全年来看,在西南风向时PM2.5和PM10浓度较高,这主要受该方向上游吴淞工业区、宝钢、石洞口电厂、罗店工业区等工业排放影响;从高浓度颗粒物(PM2.5质量浓度≥0.115mg/m^3)来向看,北和西北风向时出现高浓度颗粒物的频率最高,这主要是受到我国北方采暖季大气颗粒物输送过程对崇明岛区域的脉冲式污染影响所致;PM2.5、PM10实时浓度与相应的风速呈显著负相关。降雨量大于5mm或持续3h及以上的连续降雨对大气颗粒物起到显著的湿清除作用,降雨后PM2.5和PM10质量浓度分别降低了68.0%和66.9%,降雨时和雨后PM2.5浓度为0.025~0.033mg/m^3,均低于我国环境空气PM2.5的一级浓度限值。 展开更多
关键词 pm2.5 PM10 变化特征 气象因素
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基于CEEMDAN的多时间尺度的北京市PM_(2.5)浓度影响因素研究
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作者 叶紫涵 刘婵 +2 位作者 谭章禄 胡翰 彭胜男 《中国环境管理》 CSSCI 2024年第3期131-142,共12页
研究PM_(2.5)浓度的主要影响因素,对提升北京市空气质量具有重要意义。与以往仅限于原始时间尺度的研究不同,本文基于CEEMDAN方法考察了多时间尺度下年平均风速、城市绿化、人口密度、产业结构和能源强度对北京市PM_(2.5)浓度波动的影响... 研究PM_(2.5)浓度的主要影响因素,对提升北京市空气质量具有重要意义。与以往仅限于原始时间尺度的研究不同,本文基于CEEMDAN方法考察了多时间尺度下年平均风速、城市绿化、人口密度、产业结构和能源强度对北京市PM_(2.5)浓度波动的影响,并与原始时间尺度的主导因素进行对比。研究发现:原始尺度的北京市PM_(2.5)浓度影响因素是不同时间尺度内影响因素合力作用结果,不同时间尺度下影响因素不同。城市绿化、人口密度、产业结构和能源强度在多时间尺度中起到短期增强波动的作用,城市绿化和产业结构是贯穿于各个时间尺度的具有趋势性,决定北京市PM_(2.5)浓度基本走势的影响因素。 展开更多
关键词 PM_(2.5) 多时间尺度 影响因素 CEEMDAN 空气质量
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基于机器学习的汾渭平原PM_(2.5)和O_(3)变化特征及影响因素
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作者 李焕 苏慧 +2 位作者 张婷 赵竹子 王璐瑶 《环境化学》 CAS CSCD 北大核心 2024年第5期1585-1598,共14页
本文以2017—2021年汾渭平原典型城市西安大气PM_(2.5)和O_(3)浓度数据为基础,运用机器学习方法分析了PM_(2.5)和O_(3)的变化特征和趋势,讨论了污染气体(NO_(2)、SO_(2)、CO和HCHO)与气象因素(温度、相对湿度、风速、大气压力、边界层... 本文以2017—2021年汾渭平原典型城市西安大气PM_(2.5)和O_(3)浓度数据为基础,运用机器学习方法分析了PM_(2.5)和O_(3)的变化特征和趋势,讨论了污染气体(NO_(2)、SO_(2)、CO和HCHO)与气象因素(温度、相对湿度、风速、大气压力、边界层高度和太阳辐射)对PM_(2.5)和O_(3)浓度变化的交互影响.Theil-Sen趋势分析发现2017—2021年西安市PM_(2.5)和O_(3)分别以每年6.03%和2.06%的速度下降.单因素广义加性模型(GAM)中,NO_(2)、SO_(2)和CO对PM_(2.5)浓度变化影响的模型解释率较高,温度、太阳辐射和大气压对O_(3)浓度变化影响的模型解释率较高.多因素GAM模型中,PM_(2.5)和O_(3)均呈现非线性变化,模型的解释方差分别为84.9%和75.0%,拟合程度较高.通过等高线图分析了多个气象因素和多种污染气体两两交互作用分别对PM_(2.5)和O_(3)浓度的影响,其中温度和污染气体(NO_(2)、SO_(2)、CO和O_(3))对PM_(2.5)浓度的影响更大;温度和太阳辐射对O_(3)的影响更大.NO_(2)和CO分别与气象条件两两相互作用时,PM_(2.5)浓度随NO_(2)和CO的增高而增高,O_(3)浓度则与NO_(2)和CO的变化趋势相反.结合本地污染物源清单,建议加强控制工业源和移动源排放,有助于降低PM_(2.5)和O_(3)的浓度. 展开更多
关键词 pm2.5 O_(3) 机器学习 变化趋势 影响因素
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邢台市影响PM_(2.5)和O_(3)浓度多时间尺度演变的重要因素
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作者 兰童 韩力慧 +2 位作者 田健 齐超楠 肖茜 《中国环境科学》 EI CAS CSCD 北大核心 2024年第9期4786-4795,共10页
为了揭示邢台市大气PM_(2.5)-O_(3)复合污染的演变特征及其影响因素,基于在线监测平台提供的气象要素及污染物浓度数据,使用KZ滤波法分解邢台市PM_(2.5)和O_(3)的原始浓度序列,之后将多元逐步回归法与KZ滤波法结合定量识别污染物的长期... 为了揭示邢台市大气PM_(2.5)-O_(3)复合污染的演变特征及其影响因素,基于在线监测平台提供的气象要素及污染物浓度数据,使用KZ滤波法分解邢台市PM_(2.5)和O_(3)的原始浓度序列,之后将多元逐步回归法与KZ滤波法结合定量识别污染物的长期分量中源排放及气象因素对污染物浓度的贡献.同时使用随机森林方法,定性探究具体的源排放和气象因子对于邢台市PM_(2.5)和O_(3)原始序列浓度的影响.结果表明:邢台市PM_(2.5)浓度的长期分量呈现显著的下降趋势,短期分量是PM_(2.5)浓度的主要贡献者.O_(3)浓度长期分量呈现增加的趋势,季节分量是O_(3)浓度的主要贡献者.源排放和气象因素对PM_(2.5)长期分量浓度变化的贡献占比约为5:1,两者对于O_(3)长期分量浓度变化贡献占比接近3.5:1,源排放过程是邢台市长期大气PM_(2.5)-O_(3)复合污染的主因.相对湿度(RH)对邢台市PM_(2.5)原始序列浓度的影响最大,其次为工业源排放和机动车尾气排放;影响O_(3)原始序列最大的的3个因子分别是气象因素中的短波辐射强度(SR)、温度(T)以及机动车尾气排放. 展开更多
关键词 邢台 PM_(2.5) O_(3) KZ滤波 随机森林 影响因素
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Characteristics and fate behavior of environmentally persistent free radicals in atmospheric particulate matter
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作者 WANG Xueying CUI Long +2 位作者 XUE Yonggang HO Kinfai HUANG Yu 《地球环境学报》 CSCD 2024年第4期596-611,共16页
Background,aim,and scope Environmentally persistent free radicals(EPFRs)have received significant attention due to their longer lifetime and stable existence in various environments.The strong environmental migration ... Background,aim,and scope Environmentally persistent free radicals(EPFRs)have received significant attention due to their longer lifetime and stable existence in various environments.The strong environmental migration ability of particulate matter allows EPFRs to migrate over long-distance transport,thereby impacting the quality of the local atmospheric environment.Additionally,EPFRs can also adhere to atmospheric particles and interact with typical gaseous pollutants to affect atmospheric chemical reactions.EPFRs can produce some reactive organic species,promoting oxidative stress in the human body,damaging biological macromolecules and ultimately affecting the organism health.EPFRs are considered as a novel type of pollutant that affects human health.Despite their significance,there are few literatures available on the characteristics and fate behaviors of EPFRs up to date.Therefore,supplemental reviews are crucial for providing comprehensive understanding of EPFRs.Materials and methods This review summarizes the characteristics of EPFRs in particulate matter,outlines the generation mechanism and influencing factors of EPFRs,and the impacts of EPFRs on environmental quality and organism health.Results The content of EPFRs in particulate matter ranges from 1017 to 1020 spins∙g−1.Due to the strong mobility of atmospheric particulate matter,the long-term exposure to high levels of EPFRs may aggravate the impact of particulate matter on human health.The interaction between EPFRs and typical gaseous pollutants can alter their fate and influence atmospheric chemical reactions.EPFRs are mainly produced by transition metal elements and substituted aromatic hydrocarbons through electron transfer.Additionally,the chemical bond rupture of organic substances through heat treatment or ultraviolet radiation can also produce EPFRs,and heterogeneous reactions are capable producing them as well.The production of EPFRs is not only influenced by transition metal elements and precursors,but also by various environmental factors such as oxygen,temperature,light radiation,and relative humidity.Discussion EPFRs in atmospheric particulates matters are usually rich in fine particulates with obvious seasonal and regional variations.They can easily enter the human respiratory tract and lungs with inhalable particulates,thereby increasing the risk of exposure.Additionally,EPFRs in atmospheric particulates can interact with some typical gaseous pollutants,impacting the life and fate of EPFRs in the atmosphere,and alter atmospheric chemical reactions.Traditionally,EPFRs are generated by transition metal elements and substituted aromatic hydrocarbons undergoing electron transfer in the post-flame and cool-zone regions of combustion systems and other thermal processes to remove HCl,H_(2)O or CO groups,ultimately produce semiquinones,phenoxyls,and cyclopentadienyls.Recent studies have indicated that EPFRs can also be generated under the conditions of without transition metal elemental.Organics can also produce EPFRs through chemical bond rupture during heat treatment or light radiation conditions,as well as through some heterogeneous reactions and photochemical secondary generation of EPFRs.The presence or absence of oxygen has different effects on the type and yield of EPFRs.The concentration,type,and crystal type of transition metal elements will affect the type,content,and atmospheric lifetime of EPFRs.It is generally believed that the impact of transition metal element types on EPFRs is related to the oxidation-reduction potential.The combustion temperature or heat treatment process significantly affects the type and amount of EPFRs.Factors such as precursor loading content,pH conditions,light radiation and relative humidity also influence the generation of EPFRs.EPFRs can interact with pollutants in the environment during their migration and transformation process in environmental medium.This process accelerates the degradation of pollutants and plays a crucial role in the migration and transformation of organic pollutants in environmental media.The reaction process of EPFRs may lead to the production of reactive oxygen species(ROS)such as∙OH,which can induce oxidative stress,inflammation and immune response to biological lung cells and tissues,leading to chronic respiratory and cardiopulmonary dysfunction,cardiovascular damage and neurotoxic effects,ultimately impacting the health of organisms.Conclusions The interaction mechanism between EPFRs in particulate matter and gaseous pollutants remains unclear.Furthermore,research on the generation mechanism of EPFRs without the participation of transition metals is not comprehensive,and the detection of EPFRs is limited to simple qualitative categories and lack accurate qualitative analysis.Recommendations and perspectives Further research should be conducted on the generation mechanism,measurement techniques,migration pathways,and transformation process of EPFRs.It is also important to explore the interaction between EPFRs in atmospheric particulate matter and typical gaseous pollutants. 展开更多
关键词 particulate matter(PM) environmentally persistent free radicals(EPFRs) formation mechanism influencing factors
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基于小波变换的湖南省PM_(2.5)污染特征分析
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作者 徐赞超 穆述鑫 +1 位作者 耿星莉 刘迎云 《环境科学与技术》 CAS CSCD 北大核心 2024年第3期80-92,共13页
该文基于湖南省2017-2021年PM_(2.5)与其他5种大气污染物浓度监测数据以及气象资料,分析了PM_(2.5)浓度时空分布特征,利用连续小波变换和小波相干谱分别研究了PM_(2.5)浓度周期、PM_(2.5)与其他大气污染物及气象因子的相关性,确定了PM_(... 该文基于湖南省2017-2021年PM_(2.5)与其他5种大气污染物浓度监测数据以及气象资料,分析了PM_(2.5)浓度时空分布特征,利用连续小波变换和小波相干谱分别研究了PM_(2.5)浓度周期、PM_(2.5)与其他大气污染物及气象因子的相关性,确定了PM_(2.5)浓度的主要影响因子,结果表明:(1)湖南省PM_(2.5)浓度年平均值总体呈下降趋势,年均下降率达4.88%,PM_(2.5)浓度月平均值呈“U”型分布,2017年1月月均值浓度最高(91.9μg/m^(3)),2020年6月月均值浓度最低(15.8μg/m^(3));PM_(2.5)浓度年平均值的空间分布则呈现东北至西南高、西北及东南低的特点,PM_(2.5)浓度季平均值呈现冬季>秋季>春季>夏季的特征。(2)14个市(州)PM_(2.5)浓度都存在显著周期性变化,主要包括272 d左右的长周期和36 d左右的短周期。(3)PM_(2.5)浓度与其他大气污染物的相关性在不同时频尺度上存在差异。PM_(2.5)浓度与PM_(10)浓度在所有时频尺度上均存在显著的正相关。在小时频尺度(0~64 d)上,PM_(2.5)浓度与O_(3)、CO、NO_(2)和SO_(2)浓度都存在正相关性;在中时频尺度(64~256 d)上,PM_(2.5)浓度与O_(3)浓度的相关性不明显,与CO、NO_(2)和SO_(2)浓度存在正相关;在大时频尺度(256~512 d)上,PM_(2.5)浓度与O_(3)浓度呈现负相关,与NO_(2)和SO_(2)浓度呈现正相关,PM_(2.5)浓度与CO浓度在长沙和衡阳呈现正相关,在怀化呈现负相关。(4)PM_(2.5)浓度与气象因子的相关性在不同时频尺度上也存在差异。在小时频尺度上,PM_(2.5)与降水量、相对湿度和气压存在负相关,与温度和日照时数存在正相关,与风速存在正相关也存在负相关;在中时频尺度上,PM_(2.5)与各气象因子的相关性均不明显;在大时频尺度上,PM_(2.5)与降水、温度和日照时数呈现负相关,PM_(2.5)与气压呈现正相关,PM_(2.5)与相对湿度和风速的相关性不明显。 展开更多
关键词 PM_(2.5)浓度 污染特征 小波变换 影响因素 湖南省
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冬季地铁PM_(2.5)和PM_(10)动态分布特性与影响因素分析
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作者 王新如 裴斐 常利 《建筑节能(中英文)》 CAS 2024年第11期116-120,140,共6页
近年来,可吸入颗粒物(PM_(2.5)和PM_(10))污染引起了学界越来越多的关注。地铁作为城市发展的重要交通枢纽,其站内PM_(2.5)和PM_(10)的污染情况也受到广泛关注。目前对于地铁车站内可吸入颗粒物的研究主要集中在静态研究,缺乏对其动态... 近年来,可吸入颗粒物(PM_(2.5)和PM_(10))污染引起了学界越来越多的关注。地铁作为城市发展的重要交通枢纽,其站内PM_(2.5)和PM_(10)的污染情况也受到广泛关注。目前对于地铁车站内可吸入颗粒物的研究主要集中在静态研究,缺乏对其动态变化以及其变化影响因素的研究。针对某车站的站台、站厅和车厢内的PM_(2.5)和PM_(10)进行连续性测试,对于不同位置的PM_(2.5)和PM_(10)的动态变化和其影响因素进行分析。结果显示,当站外PM_(2.5)浓度值低于200μg/m^(3)时,车站内的PM_(2.5)和PM_(10)的浓度值比站外高,但当站外PM_(2.5)浓度值超过200μg/m^(3)时,车站内的PM_(2.5)和PM_(10)的浓度值比站外低。站厅和站台的PM_(2.5)和PM_(10)的浓度值呈现周期性波动,周期时间为列车的频次时间即7 min。由于车站构造的原因,站厅的波动比站台幅度小,且时间上要迟缓3 min。经过相关性分析,站外环境对站内的PM_(2.5)和PM_(10)的浓度变化有显著性影响(R^(2)=0.897)。但站内的温湿度以及客流量对其没有显著性影响(R^(2)=0.245和R^(2)=0.138)。该研究为将来研究地铁内PM_(2.5)和PM_(10)的控制提供数据支撑。 展开更多
关键词 地铁车站 PM_(2.5) PM_(10) 动态变化 影响因素
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长三角地区城市O3和PM2.5污染特征及影响因素分析 被引量:44
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作者 孙丹丹 杨书运 +2 位作者 王体健 束蕾 曲雅微 《气象科学》 北大核心 2019年第2期164-177,共14页
O3和PM2.5是影响长三角地区空气质量的主要污染物。利用2016年33个城市大气环境监测站6项污染物的小时浓度及4个省会城市的气象数据进行统计分析,研究了该地区O3和PM2.5浓度的时空分布特征及其影响因素。结果表明:长三角地区O3年平均浓... O3和PM2.5是影响长三角地区空气质量的主要污染物。利用2016年33个城市大气环境监测站6项污染物的小时浓度及4个省会城市的气象数据进行统计分析,研究了该地区O3和PM2.5浓度的时空分布特征及其影响因素。结果表明:长三角地区O3年平均浓度为50~73μg·m-3,平均为61μg·m^-3;除芜湖和宣城外,其余31城市均存在不同程度的超标状况,超标率为0.34%~18.86%,平均为5.68%。O3在5月和9月达到浓度高值;四季O3日变化均呈单峰型,峰值出现在15∶00,夏季O3峰值浓度最高值为157μg·m^-3。O3浓度沿海城市整体高于内陆城市;夏季宿迁—淮安—滁州片区O3污染较重。O3与NO2、CO显著负相关,且与NO2相关性较强;O3与气温、日照时数显著正相关,与相对湿度、降水呈负相关。PM2.5年平均浓度在25~62μg·m-3范围内,平均为49μg·m^-3;各城市均出现PM2.5超标,滁州PM2.5超标率最大,为23.91%。PM2.5在3月和12、1月达到浓度峰值;其日变化呈双峰型,09∶00—10∶00和22∶00—23∶00达到峰值。冬季徐州PM2.5浓度最高,为102μg·m^-3。PM2.5与NO2、CO、SO2、PM10显著正相关,与气温、风速、降水负相关。 展开更多
关键词 O3 pm2.5 污染特征 影响因素 拟合
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PM_(2.5)和O_(3)污染特征和时空变化相关性分析——以南充市为例
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作者 刘骏 夏杰 杜鑫 《绿色科技》 2024年第18期155-162,共8页
当前,细颗粒物(PM_(2.5))和臭氧(O_(3))已成为我国的两大主要空气污染物,特别是在人口密集的区域。PM_(2.5)和O_(3)污染程度强烈依赖于天气过程和人为排放,二者不仅影响社会经济健康发展,而且影响人体健康。为了探索PM_(2.5)和O_(3)的... 当前,细颗粒物(PM_(2.5))和臭氧(O_(3))已成为我国的两大主要空气污染物,特别是在人口密集的区域。PM_(2.5)和O_(3)污染程度强烈依赖于天气过程和人为排放,二者不仅影响社会经济健康发展,而且影响人体健康。为了探索PM_(2.5)和O_(3)的协同控制方法,分析两者相关性,掌握其主要影响因素,选取南充市主城区(顺庆区、高坪区、嘉陵区)为研究对象,以四川省空气质量监测网络管理系统中自动监测数据为基础,利用Origin、Excel、SPSS等软件,分析了该市环境空气中PM_(2.5)和O_(3)的污染现状、时空变化趋势以及影响因素,并探讨了二者的相关性。结果表明:①2018~2022年南充市主城区环境空气中PM_(2.5)、O_(3)年际变化整体呈下降趋势,近5年O_(3)浓度均达标,但2022年O_(3)出现反弹。②PM_(2.5)、O_(3)均表现出明显季节变化趋势,其中PM_(2.5)呈现冬春高、夏秋低的“河谷型”变化趋势,而O_(3)截然相反。③O_(3)峰值主要出现在15:00-17:00,PM_(2.5)多在23:00开始上升。④O_(3)和PM_(2.5)空间变化趋势与各自地理位置具有一定联系。 展开更多
关键词 PM_(2.5) O_(3) 变化趋势 影响因素
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基于地理探测器的广州市大气PM2.5浓度驱动因素分析 被引量:21
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作者 周敏丹 匡耀求 云国梁 《环境科学研究》 EI CAS CSCD 北大核心 2020年第2期271-279,共9页
PM2.5变化的驱动因素是大气PM2.5研究的重要内容.为了揭示PM2.5污染的特点及其驱动影响因子,以广州市为例,采用地理探测器方法探测自然因素(包括平均降水量、平均温度、平均气压、平均相对湿度、平均风速、植被指数)与社会经济因素(包... PM2.5变化的驱动因素是大气PM2.5研究的重要内容.为了揭示PM2.5污染的特点及其驱动影响因子,以广州市为例,采用地理探测器方法探测自然因素(包括平均降水量、平均温度、平均气压、平均相对湿度、平均风速、植被指数)与社会经济因素(包括人口密度、国内生产总值、工业总产值、人均公园绿地面积、公交车辆数、电力消费量)对2015年广州市ρ(PM2.5)变化的影响机制与差异.结果表明:①基于因子探测分析发现,对ρ(PM2.5)变化影响最大的前三位驱动因素分别为植被指数、公交车辆数与电力消费量,对应的因子影响程度指标值分别为0.51、0.46、0.40.②基于生态探测分析发现,植被指数与其他自然因素(如平均温度、平均降水量、平均气压等)对ρ(PM2.5)空间分布的影响均存在显著差异,与所有社会经济因素对ρ(PM2.5)空间分布的影响均不存在显著差异;除植被指数外,公交车辆数与其他自然因素及社会经济因素对ρ(PM2.5)空间分布的影响均存在显著差异.③基于交互探测分析发现,所有影响因素(包括自然因素与社会经济因素)对ρ(PM2.5)变化的交互作用均大于单一影响因素的独自作用,其中平均降水量与平均气压交互作用后对ρ(PM2.5)变化的影响最大.研究显示,自然因素(尤其是植被指数、平均降水量)及自然因素与人为活动(如交通出行、电力消费等)交互效应对广州市ρ(PM2.5)的变化起决定性作用. 展开更多
关键词 pm2.5 影响因素 地理探测器 广州市
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徐州市区PM2.5浓度与气象因素的相关性研究 被引量:3
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作者 宋海啸 于守超 +3 位作者 翟付顺 逄润卿 董月 张雪梅 《长春师范大学学报》 2020年第4期112-116,142,共6页
为了探讨徐州市区PM2.5浓度与气象因素之间的相关性及气象因素对其浓度变化的影响,为改善城市空气环境质量提供技术支持,利用2018年徐州市区的PM2.5浓度监测数据和气象观测数据,进行PM2.5浓度与气象因素的相关性分析。结果表明:徐州市区... 为了探讨徐州市区PM2.5浓度与气象因素之间的相关性及气象因素对其浓度变化的影响,为改善城市空气环境质量提供技术支持,利用2018年徐州市区的PM2.5浓度监测数据和气象观测数据,进行PM2.5浓度与气象因素的相关性分析。结果表明:徐州市区2018年PM2.5浓度年均值为62.7μg·m^-3,超过国家年均准则值(35μg·m^-3)近两倍,空气污染情况严重。徐州市区大气颗粒物浓度水平具有明显的季节特征,冬季大气颗粒物污染最严重,夏季最轻。PM 2.5与气温、风速、气压的相关性显著,与湿度的相关性不显著。通过构建气象因素与PM 2.5浓度之间的关系式,为今后徐州市做好空气质量预报及制定合理有效的污染控制策略提供科学依据。 展开更多
关键词 徐州市 PM 2.5 气象因素
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Quantitative relationship between visibility and mass concentration of PM2.5 in Beijing 被引量:31
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作者 WANG Jing-li ZHANG Yuan-hang +4 位作者 SHAO Min LIU Xu-lin ZENG Li-min CHENG Cong-lan XU Xiao-feng 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2006年第3期475-481,共7页
The pollution of particulate matter less than 2.5μm (PM2.5) is a serious environmental problem in Beijing. The annual average concentration of PM2.5 in 2001 from seasonal monitor results was more than 6 times that ... The pollution of particulate matter less than 2.5μm (PM2.5) is a serious environmental problem in Beijing. The annual average concentration of PM2.5 in 2001 from seasonal monitor results was more than 6 times that of the U,S, national ambient air quality standards proposed by U.S. EPA. The major contributors to mass of PM2.5 were organics, crustal elements and sulfate. The chemical composition of PM2.5 varied largely with season, but was similar at different monitor stations in the same season. The fine particles (PM2.5) cause atmospheric visibility deterioration through light extinction, The mass concentrations of PM2.5 were anti-correlated to the visibility, the best fits between atmospheric visibility and the mass concentrations of PM2.5 were somehow different: power in spring, exponential in summer, logarithmic in autumn, power or exponential in winter. As in each season the meteorological parameters such as air temperature and relative humidity change from day to day, probably the reason of above correlations between PM2.5 and visibility obtained at different seasons come from the differences in chemical compositions of PM2.5. 展开更多
关键词 pm2.5 atmospheric urban aerosol air pollution meteorological factor VISIBILITY
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Evaluation of correlation between PM2.5 and radon-progeny equilibrium factor in radon chamber 被引量:4
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作者 Li-Fan Li Rui Chen +1 位作者 Shu-Min Zhou Bin Tang 《Nuclear Science and Techniques》 SCIE CAS CSCD 2018年第10期261-267,共7页
The dosage of environmental radon progeny is typically estimated according to the environmental radon exposure and the recommended radon-progeny equilibrium factor, F. To investigate the relationship between PM2.5 and... The dosage of environmental radon progeny is typically estimated according to the environmental radon exposure and the recommended radon-progeny equilibrium factor, F. To investigate the relationship between PM2.5 and the radon-progeny equilibrium factor, cigarettes are used to simulate the haze–fog in a multi-functional radon chamber to achieve a stable radon concentration environment. A radon detector and a portable laser aerosol spectrometer are used to obtain the values for C_(mean) PM2.5,C_(Rn), and C_p. The results show that the mean values of F conform with the typical value recommended by the United Nations Scientific Committee on the Effects of Atomic Radiation and are within the reasonable range of0.1–0.9. In this study, a positive correlation is observed between the F values and PM2.5 concentrations. 展开更多
关键词 pm2.5 RADON CHAMBER EQUILIBRIUM FACTOR Linear regression
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大气PM2.5对大鼠心肌细胞的毒性作用 被引量:8
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作者 焦周光 胡凌飞 +3 位作者 李娜 张柯 温占波 李劲松 《环境科学研究》 EI CAS CSCD 北大核心 2018年第9期1636-1644,共9页
为评估大气PM_(2.5)及其不同组分对心肌细胞H9C2的毒性作用,探讨PM_(2.5)对心血管系统产生毒性作用的关键组分,将前期采集并制备的PM_(2.5)完全颗粒物、PM_(2.5)水溶性组分、PM_(2.5)脂溶性组分和PM_(2.5)单纯颗粒物以不同质量浓度对H9C... 为评估大气PM_(2.5)及其不同组分对心肌细胞H9C2的毒性作用,探讨PM_(2.5)对心血管系统产生毒性作用的关键组分,将前期采集并制备的PM_(2.5)完全颗粒物、PM_(2.5)水溶性组分、PM_(2.5)脂溶性组分和PM_(2.5)单纯颗粒物以不同质量浓度对H9C2细胞染毒.用MTS法在染毒6、10、24、48、72 h后测定细胞活力;根据细胞活力测定结果,选用较低染毒浓度(10μg/m L),用相关试剂盒测定染毒24 h后胞内和上清液中LDH(乳酸脱氢酶)和SOD(超氧化物歧化酶)活力,ELISA及RT-q PCR法测定炎性因子IL-6和TNF-α表达量,AP位点计数法测定细胞DNA损伤情况.结果表明:颗粒物成分(PM_(2.5)完全颗粒物和PM_(2.5)单纯颗粒物)对H9C2细胞表现出强烈的生长抑制作用,50μg/m L及以上染毒浓度组在染毒时间≥24 h时细胞可能已经全部死亡,而可溶性成分(PM_(2.5)水溶性组分和PM_(2.5)脂溶性组分)对H9C2细胞生长表现为极弱或无生长抑制作用,仅400μg/m L的PM_(2.5)脂溶性组分始终对细胞生长表现出抑制作用;各组分样本都在一定程度上造成了H9C2细胞损伤,降低了胞内LDH和SOD活性;PM_(2.5)完全颗粒物和PM_(2.5)脂溶性组分在造成炎性损伤方面的作用较为明显.研究显示,颗粒物组分对H9C2细胞致死作用显著,相对而言,PM_(2.5)完全颗粒物表现出的毒性作用最强且最全面. 展开更多
关键词 pm2.5 心肌细胞 细胞活力 炎性因子
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气象因素对常州市区PM2.5浓度影响 被引量:15
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作者 王振 杨卫芬 +4 位作者 叶香 李艳萍 夏京 李春玉 何涛 《气象与环境学报》 2020年第3期26-32,共7页
利用2016—2018年常州市区环境空气细颗粒物数据,结合同期地面气象资料,分析了常州市区PM 2.5以及气象因素的变化特征,并统计分析气象因素对PM 2.5浓度的影响。结果表明:常州市区PM 2.5、降水量、相对湿度和气温等具有明显季节性,呈夏... 利用2016—2018年常州市区环境空气细颗粒物数据,结合同期地面气象资料,分析了常州市区PM 2.5以及气象因素的变化特征,并统计分析气象因素对PM 2.5浓度的影响。结果表明:常州市区PM 2.5、降水量、相对湿度和气温等具有明显季节性,呈夏季较高冬季较低,而气压夏季较低冬季较高的特征。相对湿度与PM 2.5呈正相关,即随着相对湿度的增加PM 2.5超标率和平均浓度均增加;降水对PM 2.5具有一定的清除作用,清除率与降水前PM 2.5浓度、降水量、降水强度有关,降水量、降水强度越大,则降水清除效果越好,而降水前PM 2.5浓度较小,则清除率不明显;常州市区偏西风时PM 2.5的超标率和平均浓度较其他风向较高;风速对常州市区PM 2.5的影响呈负相关,即风速越大PM 2.5超标率和平均浓度均减小;常州市区地面天气形势可以分为两种类型,第一种类型表现为气压较低气温较高,PM 2.5超标率以及平均浓度相对较低,而第二种类型表现为气压较高气温较低,PM 2.5超标率以及平均浓度相对较高。 展开更多
关键词 气象因素 PM 2.5超标率 清除率 天气形势
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乌鲁木齐市PM2.5浓度的预测 被引量:1
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作者 谢心庆 郑薇 《伊犁师范学院学报(自然科学版)》 2015年第4期48-53,共6页
近年来,乌鲁木齐市雾霾现象频繁出现.而PM 2.5浓度的高低是出现雾霾的首要因素,为了提前预测PM 2.5浓度值并及时通过人工降水法降低其浓度,对乌鲁木齐市空气质量监测站收集到6个月的观测数据进行分析,得到与乌鲁木齐市PM 2.5浓度强相关... 近年来,乌鲁木齐市雾霾现象频繁出现.而PM 2.5浓度的高低是出现雾霾的首要因素,为了提前预测PM 2.5浓度值并及时通过人工降水法降低其浓度,对乌鲁木齐市空气质量监测站收集到6个月的观测数据进行分析,得到与乌鲁木齐市PM 2.5浓度强相关的因素,为综合考虑天气、温度、风力风向对PM 2.5浓度观测值的影响,以添加虚拟变量及因子分析提取因子的方法,将强相关因素、提取的天气、温度、风力风向因子与PM 2.5浓度观测值进行回归预测,通过模型检验得到模型的预测效果较好. 展开更多
关键词 PM 2.5 虚拟变量 因子分析 多元回归
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