Ethyl acetate fraction of Sargassum pallidum extract attenuates particulate matter-induced oxidative stress and inflammation in keratinocytes and zebrafish

Objective:To evaluate the effect of the ethyl acetate fraction derived from Sargassum pallidum extract against particulate matter(PM)-induced oxidative stress and inflammation in HaCaT cells and zebrafish.Methods:HaCaT cells and zebrafish were used to evaluate the protective effects of the ethyl acetate fraction of Sargassum pallidum extract against PM-induced oxidative stress and inflammation.The production of nitric oxide(NO),intracellular ROS,prostaglandin E_(2)(PGE_(2)),and pro-inflammatory cytokines,and the expression levels of COX-2,iNOS,and NF-κB were evaluated in PM-induced HaCaT cells.Furthermore,the levels of ROS,NO,and lipid peroxidation were assessed in the PM-exposed zebrafish model.Results:The ethyl acetate fraction of Sargassum pallidum extract significantly decreased the production of NO,intracellular ROS,and PGE_(2) in PM-induced HaCaT cells.In addition,the fraction markedly suppressed the levels of pro-inflammatory cytokines and inhibited the expression levels of COX-2,iNOS,and NF-κB.Furthermore,it displayed remarkable protective effects against PM-induced inflammatory response and oxidative stress,represented by the reduction of NO,ROS,and lipid peroxidation in zebrafish.Conclusions:The ethyl acetate fraction of Sargassum pallidum extract exhibits a protective effect against PM-induced oxidative stress and inflammation both in vitro and in vivo and has the potential as a candidate for the development of pharmaceutical and cosmeceutical products.

Modeling and Characterization of Fine Particulate Matter Dynamics in Bujumbura Using Low-Cost Sensors

Air pollution is a result of multiple sources including both natural and anthropogenic activities. The rapid urbanization of the cities such as Bujumbura, economic capital of Burundi, is one of these factors. The very first characterization of the spatio-temporal variability of PM2.5 in Bujumbura and the forecasting of PM2.5 concentration have been conducted in this paper using data collected during a year, from August 2022 to August 2023, by low-cost sensors installed in Bujumbura city. For each commune, an hourly, daily and seasonal analysis was carried out and the results showed that the mass concentrations of PM2.5 in the three municipalities differ from one commune to another. The average hourly and annual PM2.5 concentrations exceed the World Health Organization standards. The range is between 28.3 and 35.0 μg/m3. In order to make a prediction of PM2.5 concentration, an investigation of Recurrent Neural Networks with Long Short-Term Memory has been undertaken.

Spatial Analysis of Fine Particulate Matter (PM2.5) in South St. Boniface and Mission Industrial Area, Winnipeg, Manitoba, Canada

Particulate matter smaller than 2.5 microns (PM2.5) stays airborne for long periods and can enter the lungs, increasing respiratory and cardiovascular risks. Metal shredders are known sources of PM2.5, lead and other heavy metals. Winnipeg residents of South Saint Boniface (SSB) in Manitoba, Canada, live downwind of the Mission Industrial Area (MIA), which includes a metal shredder, train tracks and other industries. Residents are concerned about the MIA air and noise pollution and wanted ambient air quality monitoring in their mixed land-use area to understand its impact on their health. We measured and mapped the daytime PM2.5, from the MIA and South St. Boniface (SSB) neighborhoods using the Dylos DC 1700 PM over seven months. The Dylos air quality data for PM2.5 was validated by the two federal reference monitors in the city, finding a moderate to very strong correlation (r = 0.52 to 0.83;p-value 0.001), confirming good accuracy. A spatial analysis of the emission data showed that the highest pollution concentration was downwind of the scrap metal shredder in MIA. One-way ANOVA and Pearson correlation analysis revealed significantly higher levels of PM2.5 at MIA and SSB than at the reference sites, which are away from pollution sources. The PM2.5 Canadian Ambient Air Quality Standard (CAAQS) of 27 μg/m3 was exceeded downwind of the property line of the scrap metal shredder in the MIA for five of the 35 monitoring days averaging between 28.9 μg/m3 to 38.1 μg/m3 over eight hours. The standard was not exceeded in the residential area, although PM2.5 levels higher than background levels increased SSB residents exposure levels. This exceedance of regulatory standards requires action to reduce emissions.

Spatial and Temporal Variation of Particulate Matter (PM10 and PM2.5) and Its Health Effects during the Haze Event in Malaysia

This study aims to assess and compare levels of particulate matter(PM10 and PM2.5)in urban and industrial areas in Malaysia during haze episodes,which typically occur in the south west monsoon season.The high concentrations of atmospheric particles are mainly due to pollution from neighbouring countries.Daily PM concentrations were analysed for urban and industrial areas including Alor Setar,Tasek,Shah Alam,Klang,Bandaraya Melaka,Larkin,Balok Baru,and Kuala Terengganu in 2018 and 2019.The analysis employed spatiotemporal to examine how PM levels were distributed.The data summary revealed that PM levels in all study areas were right-skewed,indicating the occurrence of high particulate events.Significant peaks in PM concentrations during haze events were consistently observed between June and October,encompassing the south west monsoon and inter-monsoon periods.The study on acute respiratory illnesses primarily focused on Selangor.Analysis revealed that Klang had the highest mean number of inpatient cases for acute exacerbation of bronchial asthma(AEBA)and acute exacerbation of chronic obstructive pulmonary disease(AECOPD)with values of 260.500 and 185.170,respectively.Similarly,for outpatient cases of AEBA and AECOPD,Klang had the highest average values of 41.67 and 14.00,respectively.Shah Alam and Sungai Buloh did not show a significant increase in cases during periods of biomass burning.The statistical analysis concluded that higher concentrations of PM were associated with increased hospital admissions,particularly from June to September,as shown in the bar diagram.Haze episodes were associated with more healthcare utilization due to haze-related respiratory illnesses,seen in higher inpatient and outpatient visits(p<0.05).However,seasonal variability had minimal impact on healthcare utilization.These findings offer a comprehensive assessment of PM levels during historic haze episodes,providing valuable insights for authorities to develop policies and guidelines for effective monitoring and mitigation of the negative impacts of haze events.

基于遗传-模式搜索算法的微尺度管控区域大气污染物PM2.5溯源

针对微尺度管控区域可能发生的大气污染提出有效的靶向诊断方法-结合高斯烟羽模型和遗传-模式搜索算法的大气污染物分布式溯源方法.将污染源反算模型得到的污染物理论质量浓度与传感器网络观测值的数据对应关系作为目标函数,使用模式搜索算法嵌入遗传算法加快反算模型的搜索过程,反算得到污染源强度和位置.依托杭州市亚运板球场馆大气感知器网络进行实验验证,监测2021年10月PM2.5质量浓度、气象数据,对所提出的混合式大气污染溯源方法进行实验验证.实验结果表明:改进遗传-模式搜索算法对于多维变量的搜索效果较好,能快速精准地反算污染源的位置和强度,可以为微尺度管控区域突发性气体污染防治提供应急决策参考.

2022年南京市大气PM_(2.5)中多环芳烃污染特征及健康风险

目的了解南京市大气细颗粒物(PM_(2.5))中多环芳烃(polycyclic aromatic hydrocarbons,PAHs)污染特征,评估其健康风险。方法于2022年每月10—16日分别在江北新区和江宁区2个监测点开展PM_(2.5)和PAHs采样,分别采用称重法和高效液相色谱法测定PM_(2.5)和PAHs含量,利用健康风险评价模型评价PAHs的致癌风险。结果不同季节PM_(2.5)、PAHs和B[a]P的浓度存在差异(P<0.01),其中PM_(2.5)、PAHs浓度均是冬、春季高于夏、秋季,B[a]P浓度春季高于夏、秋季。两个监测点PAHs、B[a]P年均浓度、春季、夏季浓度的比较,差异均具有统计学意义(P<0.05),且江北新区均高于江宁区。两个监测点含量最高的多环芳烃是5环、其次是4环和6环。两个监测点3环、4环、5环、6环PAHs年均浓度均不同(P均<0.05),江北新区高于江宁区。PAHs年浓度中位数值对两个监测点人群的终生超额致癌风险均大于1.0×10^(-6)。PAHs年浓度95分位数对人群的年龄段超额致癌风险除江宁区0~2岁年龄段人群外,对其他年龄段人群的超额致癌风险均大于1×10^(-6)。结论南京市两个监测点大气PM_(2.5)中PAHs分布存在季节和地区差异,具有潜在的超额致癌风险。

Morphology,Nanostructure,and Oxidation Reactivity of Particulate Matter Emitted by Diesel Blending with Various Aromatics

This study aims to analyze the influence of the polycyclic aromatic hydrocarbon(PAH)content in diesel on the physical and chemical properties of diesel soot particles.Four diesel fuels with different PAH content were tested on a 11.6 L direct-injection diesel engine.The raw particulate matter(PM)before the after-treatment devices was collected using the thermophoresis sampling system and the filter sampling system.A transmission electron microscope and Raman spectrometer are used to analyze the physical properties of the soot particles,including morphology,primary particle size distribution,and graphitization degree.A Fourier transform infrared spectrometer and thermogravimetric analyzer are used to characterize the surface chemical composition and oxidation reactivity of soot particles,respectively.The results show that as the PAH content in the fuel decreases,the size of the primary soot particles decreases from 29.58 to 26.70 nm.The graphitization degree of soot particles first increases and then decreases,and the relative content of the aliphatic hydrocarbon functional groups of soot particles first decreases and then increases.The T_(10),T_(50),and T_(90) of soot from high-PAH fuel are 505.3,589.3,and 623.5℃,while those from low-PAH fuel are 480.1,557.5,and 599.2℃,respectively.This indicates that exhaust PM generated by the low-PAH fuel has poor oxidation reactivity.However,as the PAH content in fuel is further decreased,the excessively high cetane number may cause uneven mixing and incomplete combustion,leading to enhanced oxidation reactivity.

我国城市地区PM_(2.5)和O_(3)污染相关性:2017~2022年时空演变特征与协同防控启示

基于2017~2022年全国地级及以上城市空气质量监测数据及各省(自治区、直辖市)污染排放数据,计算PM_(2.5)日均浓度(DA PM_(2.5))和O_(3)日最大8h滑动平均值(MDA8_O_(3))间的皮尔逊相关系数(R_(p)),分区域分时段研究了二者相关性的时空变化特征,从污染排放等方面分析其原因.结果表明:从时空变化上看,全国范围内DA PM_(2.5)和MDA8_O_(3)第一、四季度在统计上无显著相关性(R_(p)=-0.11~0.03),仅西南、华南地区为正相关(R_(p)=0.11~0.32).全国范围内DA PM_(2.5)和MDA8O_(3)在第二季度(R_(p)=0.26~0.36)、第三季度(R_(p)=0.46~0.55)呈正相关,汾渭平原及西北地区在部分年份不相关.污染排放是影响PM_(2.5)和O_(3)污染相关性的主要因素.从时间变化上看,全国和各区域一次PM_(2.5)、二氧化硫排放特征值(ECV_(PM_(2.5))、ECV_(SO_(2)))下降而氮氧化物、挥发性有机物排放特征值(ECVNOx和ECVVOCs)上升,这与大部分省(自治区、直辖市)R_(p)平均值上升的趋势一致.从空间分布上看,在ECVPM_(2.5)和ECVSO2低而ECV_(NOx)和ECV_(VOCs)高的地区,PM_(2.5)与O_(3)污染正相关性较强.提出全国不同区域差异化的污染防控启示.京津冀及周边、长三角、东北和西南地区(第二、三季度)以及华南地区(全年),需关注NO_(x)和VOCs排放控制.京津冀及周边、长三角、东北和西南地区(第一、四季度)以及汾渭平原和西北地区(全年),需加强一次PM_(2.5)污染减排.

Ambient Fine Particulate Matter Exposure and Blood Pressure:Evidence from a Large Chinese Multiple Follow-Up Study

Objective This study aimed to investigate the association of ambient PM_(2.5)exposure with blood pressure(BP)at the population level in China.Methods A total of 14,080 participants who had at least two valid blood pressure records were selected from the China Health and Retirement Longitudinal Survey during 2011–2015.Their long-term PM_(2.5)exposure was assessed at the geographical level,on the basis of a regular 0.1°×0.1°grid over China.A mixed-effects regression model was used to assess associations.Results Each decrease of 10μg/m^(3)in the 1 year-mean PM_(2.5)concentration(FPM1Y)was associated with a decrease of 1.24[95%confidence interval(CI):0.84–1.64]mmHg systolic BP(SBP)and 0.50(95%CI:0.25–0.75)mmHg diastolic BP(DBP),respectively.A robust association was observed between the long-term decrease in PM_(2.5)and decreased BP in the middle-aged and older population.Using a generalized additive mixed model,we further found that SBP increased nonlinearly overall with FPM1Y but in an approximately linear range when the FPM1Y concentration was<70μg/m^(3);In contrast,DBP increased approximately linearly without a clear threshold.Conclusion Efficient control of PM_(2.5)air pollution may promote vascular health in China.Our study provides robust scientific support for making the related air pollution control policies.

Impact of Urban 3D Morphology on Particulate Matter 2.5(PM2.5) Concentrations:Case Study of Beijing, China

Urban particulate matter 2.5(PM2.5)pollution and public health are closely related,and concerns regarding PM2.5 are widespread.Of the underlying factors,the urban morphology is the most manageable.Therefore,investigations of the impact of urban three-dimensional(3D)morphology on PM2.5 concentration have important scientific significance.In this paper,39 PM2.5 monitoring sites of Beijing in China were selected with PM2.5 automatic monitoring data that were collected in 2013.This data set was used to analyze the impacts of the meteorological condition and public transportation on PM2.5 concentrations.Based on the elimination of the meteorological conditions and public transportation factors,the relationships between urban 3D morphology and PM2.5 concentrations are highlighted.Ten urban 3D morphology indices were established to explore the spatial-temporal correlations between the indices and PM2.5 concentrations and analyze the impact of urban 3D morphology on the PM2.5 concentrations.Results demonstrated that road length density(RLD),road area density(RAD),construction area density(CAD),construction height density(CHD),construction volume density(CVD),construction otherness(CO),and vegetation area density(VAD)have positive impacts on the PM2.5 concentrations,whereas water area density(WAD),water fragmentation(WF),and vegetation fragmentation(VF)(except for the 500 m buffer)have negative impacts on the PM2.5 concentrations.Moreover,the correlations between the morphology indices and PM2.5 concentrations varied with the buffer scale.The findings could lay a foundation for the high-precision spatial-temporal modelling of PM2.5 concentrations and the scientific planning of urban 3D spaces by authorities responsible for controlling PM2.5 concentrations.

同位素结合PMF模型解析珠三角PM_(2.5)来源研究

二次气溶胶是大气细颗粒物(PM_(2.5))中最多的组分,客观识别其来源是PM_(2.5)源解析的难点,也是精确控制PM_(2.5)污染来源的关键。本研究在广东省鹤山超级大气监测站采集了76个PM_(2.5)样品,分析了其碳质组分(元素碳和有机碳)、水溶性离子(SO_(4)^(2-)、NH4^(+)、K^(+)、Ca^(2+)、Cl^(-)、Na^(+)、Mg^(2+)、NO_(2)^(-)和NO_(3)^(-))和金属元素(Fe、Cr、Cu、Mn、Ni、Pb、V、Zn、Cd、As)共20种化学组分,测定了7个PM_(2.5)代表样品的总碳(TC)放射性碳(^(14)C)。基于PM_(2.5)化学组分的PMF模型结果显示,生物质燃烧、海盐、土壤扬尘、轮船排放、工业过程、燃煤源和二次气溶胶分别贡献PM_(2.5)的18.98%、4.32%、13.85%、7.61%、14.08%、12.72%和30.03%。基于已发表的δ^(15)N(NO_(3)^(-))、δ^(18)O(NO_(3)^(-))结果,利用贝叶斯模型定量解析了NO_(3)^(-)的来源,并应用线型回归将PMF模型解析的二次气溶胶源再分配给一次颗粒源,结果显示,燃煤源(36.50%)、生物燃料源(29.35%)、土壤扬尘+海盐源(21.00%)和移动源(13.15%)是珠三角PM_(2.5)的主要来源。二次分配后PMF模型结果中TC的非化石源贡献与基于^(14)C结果的相对误差小于9%,说明PMF模型能很好地捕获PM_(2.5)主要贡献源,并且较准确地源解析珠三角的PM_(2.5),研究结果可为区域污染防治政策措施的制定提供科学依据。

Particulate Matters Pollution Characteristic and the Correlation between PM (PM_2.5, PM₁₀) and Meteorological Factors during the Summer in Shijiazhuang

In recent years, the haze occurs frequently and air pollution is getting worse in Beijing-Tianjin-Hebei Region, China. The particulate matter pollution characteristic researches are playing a sig-nificant role especially in the districts where have higher concentration PM and air pollution. In this study, we collected daily particulate matter (PM10, PM2.5) mass concentration data from 7 air pollution monitoring stations in Shijiazhuang City, Hebei, China over a 3-month period from June to August to investigate particulate matter pollution characteristic and the relationship with me-teorological conditions. Statistical results show that PM10 is the major pollutant in Shijiazhuang City;the average daily concentrations of PM2.5 and PM10 are 94.45 μg/m3 and 219.15 μg/m3, respectively. The daily average of PM10 and PM2.5 level over the period exceeded the first grade of the daily average limit of the ambient air quality standards (GB3095-2012). And there is a significantly positive correlation between atmospheric pressure and particulate matter pollution, but there is a significantly negative correlation between atmospheric temperature and PM concentrations. Precipitation has a clear role mainly in the coarse particles;however, there has little effect on fine particulate matter. Relative humidity and wind speed have a poor correlation with atmospheric pollutant concentrations (not remarkably high).

HC-PM COUPLING MODEL FOR PARTICULATE MATTER EMISSION OF DIESEL ENGINES

A rapid, phenomenological model that predicts paniculate matter (PM) emissionof diesel engines is developed and formulated. The model is a chemical equilibrium compositionmodel, and is based on the formation mechanisms of PM and unburned hydrocarbon (HC) emissions ofdiesel engines. It can evaluate the emission concentration of PM via the emission concentration ofHC. To validate the model, experiments are carried out in two research diesel engines. Comparisonsof the model results with the experimental data show good agreement. The model can be used toevaluate the concentration of PM emission of diesel engines under lack of PM measuring instruments.In addition, the model is useful for computer simulations of diesel engines, as well as electroniccontrol unit (ECU) designs for electronically controlled diesel engines.

Human Health Risks from Exposure to Heavy Metals of Suspended Particulate Matter around the Tongon Gold Mine, Côte d’Ivoire

The Tongon mine, the largest gold mine in C?te d’Ivoire, has been in operation since April 2010. However, to our knowledge to date, no study has been conducted on metallic contamination in suspended particulate matter (PM10 and PM2.5) where there is a lack of information on the carcinogenic and non-carcinogenic risk to human health associated with the exposure of populations in the Tongon area to these pollutants. The general objective of this study is to evaluate the level of contamination of PM10;PM2.5 by heavy metals and their impact on the health of populations exposed to these pollutants in the Tongon gold mine area. The sampling and measurement of suspended particulate matter (PM10 and PM2.5) were done using a MiniVol TAS passive air sampler. Heavy metal concentrations were determined by inductively coupled plasma mass spectroscopy (Nex ION 2000 ICP-MS, USA). The results indicate that the average concentrations of suspended particles (PM2.5 and PM10) obtained are all above the recommended exposure limits. In addition, among the heavy metals contained in the suspended particles, the concentrations of arsenic and nickel are high and all above the standard limit values. The assessment of the health risks related to the inhalation of PM10 particles reveals that their inhalation over a long period could cause a carcinogenic risk.

基于机器学习的郑州市大气PM_(2.5)与O_(3)浓度预测方法及气象因子的影响分析

近年来,我国面临着细颗粒物(PM_(2.5))污染形势依然严峻以及臭氧(O_(3))污染日益凸显的双重压力.为进一步准确预测郑州市大气PM_(2.5)与O_(3)浓度并探明气象因子的影响,本研究使用2018−2022年郑州市大气污染物和气象因子逐时数据,结合统计学单因素分析和机器学习LightGBM模型多因素分析,建立了一种基于长时间序列数据的PM_(2.5)与O_(3)浓度预测及气象因子影响分析的综合分析方法.结果表明:①训练后的LightGBM模型能够较好地预测PM_(2.5)污染,准确率达80.8%;对O_(3)污染预测的准确率为52.5%.②郑州市大气PM_(2.5)浓度与气压呈正相关,与比湿和环境温度均呈负相关;大气O_(3)8 h滑动平均浓度(O_(3)-8 h浓度)与比湿和太阳辐射均呈正相关,与气压呈负相关.③有利的气象条件可能是2021年PM_(2.5)年均浓度得到显著改善的重要因素;同时,不利的气象条件也促使2021年和2022年6月O_(3)月评价值(O_(3)日最大8 h滑动平均90百分位浓度)有所上升.研究显示,这种基于长时间序列的综合分析方法适用于大气PM_(2.5)与O_(3)浓度的气象因子影响分析,也能有效预测PM_(2.5)与O_(3)的浓度.

Spatiotemporal assessment of particulate matter(PM_(10) and PM_(2.5)) and ozone in a Caribbean urban coastal city

Air pollution has become a critical issue in urban areas,so a broad understanding of its spatiotemporal characteristics is important to develop public policies.This study analyzes the spatiotemporal variation of atmospheric particulate matter(PM_(10) and PM_(2.5))and ozone(O_(3))in Barranquilla,Colombia from March 2018 to June 2019 in three monitoring stations.The average concentrations observed for the Móvil,Policía,and Tres Avemarías stations,respectively,for PM_(10):46.4,51.4,and 39.7μg/m^(3);for PM_(2.5):16.1,18.1,and 15.1μg/m^(3) and for O_(3):35.0,26.6,and 33.6μg/m^(3).The results indicated spatial and temporal variations between the stations and the pollutants evaluated.The highest PM concentrations were observed in the southern part of the city,while for ozone,higher concentrations were observed in the north.These variations are mainly associated with the influence of local sources in the environment of each site evaluated as well as the meteorological conditions and transport patterns of the study area.This study also verified the existence of differences in the concentrations of the studied pollutants between the dry and rainy seasons and the contribution of local sources as biomass burnings from the Isla Salamanca Natural Park and long-range transport of dust particles from the Sahara Desert.This study provides a scientific baseline for understanding air quality in the city,which enables policy makers to adopt efficient measures that jointly prevent and control pollution.

基于双重差分法的宁夏大气PM_(2.5)长期暴露对呼吸系统疾病死亡影响的研究

目的了解宁夏2010—2015年呼吸系统疾病死亡情况和PM_(2.5)的分布状况,探讨宁夏大气PM_(2.5)长期暴露对居民呼吸系统疾病死亡的影响。方法收集2010—2015年宁夏居民死亡监测数据,各街道、乡镇大气PM_(2.5)年均浓度以及气象、人口、地理信息等相关资料。采用改良的双重差分设计(广义非线性模型拟合),分析大气PM_(2.5)长期暴露对呼吸系统疾病死亡的影响。结果在呼吸系统疾病死亡人群中,男性占比55.36%,女性比占44.63%;64岁及以下组占比14.21%,65岁及以上组占比85.79%;大气PM_(2.5)浓度每升高1μg/m 3,对呼吸系统疾病和下呼吸道疾病死亡的OR值及95%置信区间(CI)分别为1.03(1.02~1.04)、1.03(1.02~1.05)。分层分析结果显示,大气PM_(2.5)浓度每升高1μg/m 3,对男性和女性呼吸系统疾病死亡的OR及95%CI分别为1.03(1.02~1.04)和1.03(1.02~1.05);对年龄≤64岁及年龄≥65岁组呼吸系统疾病死亡的OR及95%CI分别为1.02(0.99~1.05)和1.03(1.02~1.04)。结论宁夏地区大气PM_(2.5)长期暴露增加人群呼吸系统疾病、下呼吸道疾病死亡的风险,男性和女性均为敏感人群,年龄≥65岁组人群更加敏感。

Risk of Cardiovascular Disease Associated with the Exposure of Particulate Matter (PM_2.5): Review

Association of particulate matter (PM2.5) increases the risk of cardiovascular disease. Experimental and clinical evidences suggested that PM2.5 is directly linked with cardiovascular disease. PM2.5 also plays an important role in the biological mechanisms influencing in the cardiovascular system. Here in this review, we tried to discuss that PM2.5 is associated with the increase risk of cardiovascular disease in which PM2.5 air pollutants enter through the alveolar of the lungs through the systemic circulation inducing cardiovascular disease. More studies need to be done for further understanding to clarify the interactions of PM2.5 components associated with cardiovascular disease.

2016—2022年珠三角地区PM_(2.5)中多环芳烃污染特征及健康风险

目的评价多环芳烃暴露的人群健康风险,了解珠三角地区大气PM_(2.5)及其中16种多环芳烃的污染特征和来源。方法2016—2022年在广东省珠三角地区的广州、深圳、佛山及珠海市选10个区设置10个监测点,每月10—16日采集环境空气样品,测定PM_(2.5)及其中16种多环芳烃含量,分析多环芳烃污染来源,使用BaP毒性当量法评价多环芳烃呼吸暴露途径的人群健康风险。结果2016—2022年珠三角地区PM_(2.5)逐年平均浓度(x±s)分别为(57.45±29.66)、(51.26±35.69)、(43.86±33.17)、(40.53±24.70)、(29.26±34.27)、(31.57±24.91)、(30.17±21.06)μg/m^(3),呈下降趋势(Z=-29.83,P<0.01),PM_(2.5)中多环芳烃平均浓度(x±s)分别为(6.23±6.29)、(5.17±6.95)、(4.00±4.46)、(3.34±3.93)、(2.52±2.92)、(3.05±4.30)、(2.65±2.60)ng/m^(3),浓度虽然降低近60%,但下降趋势无统计学意义,多环芳烃16种成分除萘(NAP)外均呈下降趋势(P<0.05),2018—2022年PM_(2.5)中多环芳烃致癌效应健康风险CR值M(P_(25),P_(75))为5.35×10^(-7)(2.54×10^(-7),1.21×10^(-6)),自第69百分位数开始大于1×10^(-6),第99百分位数为9.19×10^(-6),均小于1×10^(-4)。结论珠三角地区四城市大气PM_(2.5)污染整体呈不断改善趋势,四城市中临海的深圳和珠海市优于佛山和广州市,PM_(2.5)与多环芳烃成分含量呈显著正相关,逐月变化趋势基本一致。多环芳烃污染主要是本地源排放所致,存在石化燃料燃烧、机动车尾气排放、石油挥发和有机物质燃烧等多重来源,不同城市多环芳烃污染构成和来源并不完全一致,且高温燃煤对多环芳烃浓度变化有重要影响。珠三角地区大气PM_(2.5)中多环芳烃具有潜在致癌风险,宜引起关注。

PM_(2.5)有机提取物经由铁死亡诱导人支气管上皮细胞损伤的研究

目的探讨细颗粒物(PM_(2.5))有机提取物能否诱导人支气管上皮细胞铁死亡。方法通过索氏提取法提取PM_(2.5)中有机物作为受试物,使用BEAS-2B细胞,以0.1%DMSO溶液作为溶剂对照,染毒于不同剂量(2.5、5、10和20μg/mL)的PM_(2.5)有机提取物构建细胞染毒模型;使用铁死亡抑制剂(Ferrostatin-1,Fer-1)构建铁死亡干预模型。通过吸光度法检测PM_(2.5)有机提取物染毒后BEAS-2B细胞存活率、丙二醛(malondialdehyde,MDA)和谷胱甘肽(glutathione,GSH)浓度;通过荧光法检测细胞内Fe2+含量、活性氧(reactive oxygen species,ROS)含量和脂质过氧化物(lipid peroxidation,LPO)含量;通过qRT-PCR方法检测铁死亡相关基因(如GPX4、SLC7A11、ACSL4、FTL和TFRC等)表达。结果与对照组相比,PM_(2.5)有机提取物染毒24 h后,当染毒剂量为10μg/mL时,细胞内Fe2+含量、ROS含量、LPO含量和MDA浓度均出现显著上升;而GSH浓度出现显著下降;qRT-PCR结果显示,细胞暴露于20μg/mL PM_(2.5)有机提取物时,细胞内铁死亡相关基因GPX4显著下调,SLC7A11、ACSL4、FTL和TFRC出现显著性上调。干预实验中,使用铁死亡特异性抑制剂Fer-1干预后上述变化得到明显改善。结论PM_(2.5)有机提取物可能通过诱导细胞铁死亡导致呼吸系统细胞损伤,进而对肺组织产生潜在健康影响。