Analysis of mass concentration of atmospheric particulate matter in a sandstorm course and its affecting factors in the Taklimakan Desert

During the course of a major sandstorm from April 17 to April 23, 2008 in the Taklimakan Desert, data pertaining to the mass concentrations of different-sized atmospheric particulate matter were observed continuously with Grimm 1.108, Thermo RP 1400a, TSP, and CAWS-600 instruments. The results showed that： （1） during the entire sandstorm process there were some dif- ferences between the daily mean particle concentration peaks and the hourly mean particle concentration peaks because the actual sandstorm lasted for only about 4 hr, whereas more particles were accumulated in the floating dust days before and after the actual sandstorm; （2） the intensity of the sandstorm was enhanced with the increase of wind speed, and this was related to the peak mass concentrations of atmospheric particulate matter; the wind speed directly affected the concentration of atmospheric particulate matter： the higher the wind speed, the higher the mass concentration （〉0.23 μm was 39,496.5 μg/m^3, and 〉20.0 μm was 5,390.7μg/m^3）; （3） the concentration changes of PM10 and TSP were also related to the course and intensity of the sandstorm; and （4） the mass concentration of atmospheric particulate matter had the following sequence during the dust weather： clear day 〈 floating dust 〈 floating and blowing dust 〈 sandstorm. Temperature, relative humidity, and barometric pressure are important factors affecting the strength of storms, which could also indirectly affect the concentration change of atmospheric particulate matter.

The Effect of Urban Agglomeration Expansion on PM_(2.5) Concentrations: Evidence from a Quasi-natural Experiment

This study constructs a quasi-natural experiment based on the expansion of the Yangtze River Delta urban agglomeration(YRDUA) of China in 2010 to investigate the impact and inner mechanism of urban agglomeration expansion on fine particulate matter(PM_(2.5)) concentrations through propensity scores in difference-in-differences models(PSM-DID) using panel data from 286 prefecturelevel cities in China from 2003 to 2016. The results show that 1) urban agglomeration expansion contributes to an overall decrease in PM_(2.5)concentration, which is mainly achieved from the original cities. For the new cities, on the other hand, the expansion significantly increases the local PM_(2.5)concentration. 2) In the long term, the significant influence of urban agglomeration expansion on PM_(2.5)concentration lasts for three years and gradually decreases. A series of robustness tests confirm the applicability of the PSM-DID model.3) Cities with weaker government regulation, a better educated population and higher per capita income present stronger PM_(2.5)reduction effects. 4) Urban agglomeration expansion affects the PM_(2.5)concentration mainly through industrial transfer and population migration, which cause a decrease in the PM_(2.5)concentration in the original cities and an increase in the PM_(2.5)concentration in the new cities.Corresponding policy suggestions are proposed based on the conclusions.

Particulate Matter Concentrations in the Vicinity of an Incinerator

Incineration is an effective way of health care waste management, but it is also a source of air pollution. Thermal decomposition of organic and inorganic waste during incineration releases a large concentration of air pollutants such as CO, SO2, NOx, CO2 and particulate matter (PM). A cross sectional-descriptive study was conducted to determine the short-term variations in PM concentrations across various areas in the vicinity of a local incinerator in Windhoek, Namibia. XRF Qualitative analysis method was used to determine the elemental composition of fallout dust concentration from six study areas/stations in the vicinity of a local incinerator. Single bucket fallout monitors were deployed following the American Society for Testing and Materials standard method for collection and analysis of dust fallout to determine the elemental composition of fallout dust. Real-time PM concentration trends were also recorded using a portable Micro dust Pro Real-time Dust Monitor for PM10 at a height of 2.2 m above the ground. High PM concentration peaks were observed in the morning and afternoon hours at varying points. The fallout dust rate ranged between highest 1839.3 mg/m2/day at sampling Point 4 and lowest 711 mg/m2/day at sampling Point 2. The XRF analysis revealed the presence of toxic elements and crustal elements in order of decreasing abundance: Mn > Zn > Cr > V > Zr > Sr > Pb > Ni and SI > K > Fe > Ti > Ca > Al > P respectively. Highest elemental composition concentrations were found at sampling location in the vicinity of the incinerator and in industrial area.

Experimental Study on the Effect of Humidification on the Pollution Characteristics of Particulate Matter in the Office

Indoor air quality has a direct impact on human health. Indoor air quality has aroused great concern. This experimental study compares the effects of different water humidification on the indoor particulate pollution characteristics, and analyzes the mass concentration and the particulate number concentration distribution of different sizes of particulates with time under each condition of the purified water humidification, the tap water humidification and the cold boiled water humidification in the office. The results show that under the three kinds of wetting conditions, the concentration of the fine particulates is higher. More minerals are contained in the tap water and the cold boiled water, so the two kinds of humidification have more significant impact on indoor particulate matter. But the purified water humidification has nearly no significant effect on it. The calcium and magnesium ionic compounds are partly removed after the water boiled, so the cold boiled water humidification has less impact on the indoor particulate matter than the tap water humidification. The mass concentration and particulate number concentration of the particle may also be affected due to the frequency of ultrasonic vibration.

Comparative Study of Conocarpus erectus and Phoenix dactylifera as Plant Biomonitors of Particulate Matter Pollution in Kuwait over Three Land Use Classes

Magnetic plant biomonitoring has been proven to be an effective tool in the assessment of air quality. Kuwait presents a unique environment due to its dry desert climatic conditions and prevailing dry deposition patterns that may affect accumulation rates of magnetic mineral particles. This study evaluated two widely distributed ornamental species, buttonwood (Conocarpus erectus) and palm (Phoenix dactylifera) for their effectiveness as biomagnetic monitors over three different land use classes (urban, suburban and industrial land classes). The differences between land use classes were classified by their proximity to major pollution sources as well as population density. Leaf sampling was conducted over various heights and distances from the nearest road. Total leaf saturated isothermal magnetization (SIRM), hard isothermal magnetization (HIRM), hard isothermal magnetization percentage (HIRM%) and s-ratio have been measured. Scanning electron microscopy (SEM) was used to analyze leaf surface micromorphology. It was determined that NRM values are similar for all land use classes and species, ranging from 0.3 to 0.5 μA. Palm leaf overall magnetic concentration was identified to be higher at the industrial land use class than at the urban land use class, indicating high coercivity minerals to magnetically dominate the land use classes. Additionally, total leaf SIRM was determined to be higher at short distances of 0 - 5 meters from the vicinity of the road. The surface rugosity of palm has deep ridges and furrows with ununiform wax projections across the leaf surface, while buttonwood has a smooth wax film with low relief. Differences in leaf micromorphology in addition to plant physiology, justify species magnetic parametric variances. Palm leaf had an average SIRM value that is 120% higher than buttonwood. It has been highlighted that through the application of the magnetic parameter results to spatial distribution maps that there is an association between particulate matter (PM) and the locality of main roads and local services that may experience higher intensities of traffic.

Valuations of Elemental Concentrations of Particle Matter in Ulaanbaatar, Mongolia

This study focused on the contents of the air particulate matter pollution in two districts of Ulaanbaatar and determined the chemical composition of air borne samples and the source of those particles. Samples of fine and coarse fractions of PM were collected using a “Gent” stacked filter unit in two fractions of 0 - 2.2 μm and 2.2 - 10 μm sizes in two semi-residential areas from September 2012 to August 2013. This paper points out that fine and coarse concentration varied seasonally with meteorological changes. In sampling site 3, Zuun Ail (Figure 1) combustion generators generate the majority of pollution around 50.6% of household waste furnace to create high-temperature combustion of 21.6%. However, this net contributes to soil contamination near the lower value (5%) that arises around the vacuum environment in substantial amounts (14%), where is open around the buildings and residential areas, and the soil is considered to be due to the construction. But the data point to the highway in the distance, where is 9% of contamination of all vehicles’ smoke, and exhaust is similar to the data collected in Ulaanbaatar. According to analysis of samples of Nuclear Research Center (NRC) sampling site 2, it shows burning source of Particulate Matter 2.5 pollution in the air is around 25.5% of household waste furnace to create high-temperature product of combustion. But here the very high net contribution to the pollution of soil, is 31.6%. Today’s emerging dust is around 15.2%, showing that motor vehicle pollution causes 19.7%. Since the analysis was done on a sample-by-sample basis, it is possible to estimate the daily contributions of pollution sources and provide useful information based on a limited number of samples in order to address air quality management issues in Ulaanbaatar.

Effect of Meteorological Data Assimilation on Regional Air Quality Forecasts over the Korean Peninsula

The Weather Research and Forecasting model coupled with Chemistry(WRF-Chem),a type of online coupled chemistry-meteorology model(CCMM),considers the interaction between air quality and meteorology to improve air quality forecasting.Meteorological data assimilation(DA)can be used to reduce uncertainty in meteorological field,which is one factor causing prediction uncertainty in the CCMM.In this study,WRF-Chem and three-dimensional variational DA were used to examine the impact of meteorological DA on air quality and meteorological forecasts over the Korean Peninsula.The nesting model domains were configured over East Asia(outer domain)and the Korean Peninsula(inner domain).Three experiments were conducted by using different DA domains to determine the optimal model domain for the meteorological DA.When the meteorological DA was performed in the outer domain or both the outer and inner domains,the root-mean-square error(RMSE),bias of the predicted particulate matter(PM)concentrations,and the RMSE of predicted meteorological variables against the observations were smaller than those in the experiment where the meteorological DA was performed only in the inner domain.This indicates that the improvement of the synoptic meteorological fields by DA in the outer domain enhanced the meteorological initial and boundary conditions for the inner domain,subsequently improving air quality and meteorological predictions.Compared to the experiment without meteorological DA,the RMSE and bias of the meteorological and PM variables were smaller in the experiments with DA.The effect of meteorological DA on the improvement of PM predictions lasted for approximately 58-66 h,depending on the case.Therefore,the uncertainty reduction in the meteorological initial condition by the meteorological DA contributed to a reduction of the forecast errors of both meteorology and air quality.

我国6个典型城市大气能见度及其影响因素研究

采用线性相关性分析、分类变量分析等统计学方法,分析了巴彦淖尔、石家庄、廊坊、郑州、武汉、广州六市2019—2020年的PM_(2.5)与气象观测数据,研究了PM_(2.5)浓度与大气相对湿度对大气能见度的影响。结果表明:六市大气能见度年变化规律虽存在较大差异,但最低值均出现于每年12月—次年2月,且年变化规律基本一致;气象条件、相对湿度、PM_(2.5)浓度对能见度的影响明显,其中相对湿度通过改变PM_(2.5)物化性质间接影响能见度,与能见度相关程度相对较弱。PM_(2.5)浓度与能见度的线性相关性良好,以幂函数为主;整体上,相对湿度与PM_(2.5)浓度对大气能见度影响呈协同作用,相对湿度越大的城市对PM_(2.5)的控制要求越高。此外,PM_(2.5)浓度高于平台点时,大气能见度基本不随PM_(2.5)浓度增加而继续降低,只有PM_(2.5)浓度低于突变点时,大气能见度才会随PM_(2.5)浓度降低而显著提升,各市能见度突变点与平台期点所对应PM_(2.5)浓度差异较大。

莫高窟文物保存环境的大气颗粒物背景浓度及化学组成

大气颗粒物是潜在威胁遗址与文物的一种大气污染物,颗粒物沉降或吸附后覆盖文物表面细节,降低其审美价值,并带来进一步的物理或化学侵蚀。通过分析莫高窟开放洞窟(16窟、257窟)、非开放洞窟(320洞窟)和窟外大气中各粒径颗粒物(总悬浮颗粒物TSP、粗颗粒物PM_(10)和细颗粒物PM_(2.5))背景和典型沙尘天气质量浓度及其碳组分和水溶性无机离子组分含量,获得文物保存环境中大气颗粒物的质量浓度及化学组成。各观测季节内,非沙尘天气窟内TSP质量浓度介于48.4~60.0μg/m^(3),PM_(10)质量浓度介于13.3~61.3μg/m~3,PM_(2.5)质量浓度介于9.9~59.2μg/m^(3)。洞窟是否向公众开放对窟内颗粒物浓度水平和组成的影响不显著,开放和非开放洞窟颗粒物质量浓度的I/O比值多小于1,显示窟内颗粒物主要源于室外。窟内颗粒物化学组成中,地壳源矿物尘多占据主导地位,在沙尘频发的春季占比介于53.0%至80.7%之间,冬季占比介于17.1%~44.0%。其他化学组分中,细颗粒PM_(2.5)中碳组分和总水溶性无机离子含量占比明显高于TSP和PM_(10)。冬季窟内PM_(2.5)质量浓度低于春季,但碳组分和无机离子浓度值和含量占比均高于春季(除去春季16洞窟),冬季碳组分和无机离子含量占比高达60%,其中酸性组分含量占比和可达30%。对莫高窟大气颗粒物的控制不能忽视细颗粒浓度及其化学组成的潜在危害。

海洋悬浮物浓度的长期演变特征及机制

受气候变化和人类活动的影响,21世纪以来全球海洋的悬浮物浓度发生了显著变化。悬浮物浓度的剧烈变化不可避免地对海洋生态环境、地貌演化和生物地球化学循环产生重大影响。随着气候变化对人类活动的环境影响研究的深入,以及卫星遥感数据的不断积累,悬浮物浓度的长期变化趋势及其机制已成为地球科学研究的热点。本文概括性地总结了海洋悬浮物浓度长期变化的国内外研究进展,指出了中国近海相关研究的不足之处,并对未来发展方向作出了展望。

沿海港口疏浚工程悬浮物浓度遥感反演研究

为对沿海港口疏浚工程产生的悬浮物浓度进行有效的高时空分辨率动态监测,利用静止轨道卫星GOCIⅡ高时空分辨率的优势,根据实测水质样本悬浮物浓度数据和卫星遥感影像预处理后的遥感反射率,采用参数相关分析方法选取反演波段,建立基于单波段和波段比值的指数、线性、对数、多项式等反演模型,比选出最优模型并进行验证。应用该模型对某港区某日航道维护性疏浚作业水域以及倾倒水域的悬浮物浓度变化情况进行监测,结果表明其高时空分辨率的优势能更好地适应范围小、水质变化迅速的疏浚作业区和倾倒区特点,可追踪监测工程区域及周围海域悬浮物浓度的连续变化,为绿色疏浚提供参考。

武汉城市森林空气环境效应研究——以九峰国家森林公园为例

为探究城市森林空气环境的变化规律,以九峰国家森林公园为研究对象,以空气负离子浓度为主要监测指标,同步监测空气温、湿度,空气颗粒物浓度等,阐明其季节性变化规律,探索影响空气负离子浓度的主要因素。结果表明:森林环境可以显著改善空气温度、湿度,春季和秋季各林分的林内环境均达到“体感舒适”等级;与对照相比,各林分类型对PM_(1.0)、PM_(2.5)和PM_(10)有明显净化效果,其中秋季林分净化率高于夏季,春季最低,针叶+常绿阔叶林的颗粒物净化率相对较高;空气负离子浓度总体表现为夏季>春季>秋季,春季和秋季各林分空气负离子浓度的峰值出现时间主要集中在16∶00,夏季则是在10∶00;影响空气负离子浓度的主要因素在不同季节存在差异,各类型颗粒物浓度、天空开阔度在各季节均与负离子浓度呈极显著或显著负相关关系;空气负离子浓度在春季与空气湿度呈显著正相关,在夏季与树高呈显著正相关,在秋季则与空气温度、叶面积指数和树高表现出显著正相关关系。

我国城市群环境空气颗粒物浓度分布特征研究

利用2015—2022年颗粒物(PM_(2.5)和PM_(10))监测数据,从浓度水平和统计学分布2个角度,采用日均浓度、年均浓度、概率论角度达标情况和达标所需浓度降低量4个维度分析我国10个城市群(169个城市)的颗粒物浓度分布特征及异同。结果表明,我国城市群内部颗粒物浓度污染水平趋于平稳,城市群之间颗粒物浓度差异较大。我国城市群颗粒物浓度存在分层现象,根据颗粒物浓度水平将10个城市群分为高浓度、中浓度、低浓度城市群3类。从统计学分布角度也分为3类,但关中平原城市群被划分到高浓度城市群,其余城市群分类则不变。我国城市群之间颗粒物达标(GB 3095—2012《环境空气质量标准》二级标准)所需浓度降低量差异显著。海峡西岸城市群的PM_(2.5)和PM_(10)以及珠三角城市群的PM_(10)已经达标,而中原、关中平原、京津冀和山东半岛城市群如果要达标,PM_(2.5)和PM_(10)浓度分别需降低50%和27%以上。建议科学制定符合我国国情的颗粒物区域阶段目标值,推动城市群结合自身情况加快分阶段达标。

某铅锌浮选厂颗粒物浓度分布及其影响研究

铅锌浮选厂在生产过程中产生大量颗粒物,污染工作环境。以某铅锌浮选厂为研究对象,对厂房内、外颗粒物浓度分布情况进行测试分析,并对其污染状态及健康影响进行深入研究。结果表明:粒径小于10μm颗粒物其厂房内数量浓度高于厂房外,且数量浓度随粒径变小而增加,厂房内、外颗粒物的数量浓度比平均值大多大于1。PM_(10)、PM_(2.5)和PM1的厂房内质量浓度显著高于厂房外,厂房内PM_(10)、PM_(2.5)分别超过一级标准5.333倍和6.313倍,超过二级标准2.614倍和2.134倍。厂房内对厂房外颗粒物浓度有较大影响,颗粒物的分布和浓度也有所不同,环境因素对粉尘污染有较大影响。研究结果可为矿山环境颗粒物的有效控制提供数据参考价值。

大气颗粒物重金属污染排放浓度及环保检测技术研究

为降低大气颗粒物中重金属污染检测的检测误差,针对大气颗粒物重金属污染排放浓度及环保检测技术进行研究。利用光纤激光器对向污染的气体中发射一定波长的光束,等待污染分子完成光纤吸收后,获得红外吸收光谱,再分析分子运动状态,提取光谱中包含的特征。获取大气中声波传输信号,并结合声传播波动方程,计算出重金属污染排放浓度。最后,依托于稳态工况法和标准污染物排放限值,得出环保检测结果。实验结果表明:所提技术的检测结果的相对误差保持在3%以下,可以准确反映大气重金属污染情况。

宜昌市颗粒物污染浓度特征及气象条件影响分析

通过气象观测手段,监测分析宜昌市颗粒物污染浓度特征及气象影响因素,为研究三峡水利枢纽对局地气候的影响以及水库气候效应分析提供数据支撑和资料基础,具有重要意义。目前针对宜昌市的颗粒物尤其是黑碳(black carbon,BC)气溶胶颗粒物的相关研究很少。本文利用宜昌国家基本气象站2014年4月—2022年12月的大气颗粒物PM_(2.5)、PM_(10)和黑碳气溶胶连续观测资料,结合同期气象要素资料进行数理分析,研究PM_(2.5)、PM_(10)和黑碳质量浓度的变化特征及其气象影响条件。结果显示:(1)宜昌市PM_(2.5)和PM_(10)质量浓度总体呈逐年下降趋势,黑碳气溶胶质量浓度在2018年前总体下降,后呈较缓波动趋势,春季和冬季浓度较高,夏季、秋季较低,日变化呈双峰态势;(2)颗粒物质量浓度高低值分布与主导风向高度吻合,与风速、降水量呈显著负相关;(3)黑碳气溶胶质量浓度与PM_(2.5)、PM_(10)颗粒物质量浓度变化趋势高度相似,呈显著性正相关,相关系数分别为0.845和0.747,表明宜昌城市大气中颗粒物具有很强的同源性。总体来看,经济社会发展对生态环境变化产生一定的主导作用,新型有效的经济环保政策实施对于长江经济带的生态环境建设意义重大。

降水过程对大气颗粒物的清除作用研究——以山西省晋中市榆次区为例

为明确晋中市榆次区降水过程对大气颗粒物的清除效果,基于2021年1月至2022年12月榆次区的大气颗粒物(PM_(2.5)、PM_(10))浓度和气象观测数据,利用数理统计、相关性分析等方法分别从降水总量、降水持续时间、降水前颗粒物浓度和小时最大降水量4个指标研究降水过程对PM_(2.5)、PM_(10)的清除效果。结果表明:降水总量的增加有利于促进对PM_(2.5)、PM_(10)的清除效果,随着降水总量增加,PM_(2.5)、PM_(10)的平均清除率提高,正清除比例增加;连续降水可增强对大气颗粒物的清除效果,当连续降水达到12 h可有效降低PM_(2.5)、PM_(10)的浓度;降水对颗粒物的清除效果和颗粒物初始浓度有较好的正相关性,当降水过程开始3 h前颗粒物浓度较高时,降水对PM_(2.5)、PM_(10)有较好的清除效果,但PM_(2.5)初始浓度≤35μg/m^(3),PM_(10)初始浓度≤50μg/m^(3)时,易出现负清除作用;小时最大降水量>1.5 mm时,降水过程对大气颗粒物有比较明显的清除效果。

基于无人机垂直观测的连云港地区一次污染天气分析

2020年12月11—13日连云港地区出现了一次大范围重污染天气过程,利用搭载在无人机上的粒子计数器和气溶胶采样装置对连云港地区近地面大气颗粒物进行垂直探测,结合风廓线雷达、地基微波辐射计以及地面气象观测和再分析资料,分析了大气颗粒物浓度廓线和气象要素垂直分布特征,并通过后向轨迹追踪模式分析了污染物来源及扩散情况,探究了此次污染天气的成因。结果表明:风廓线雷达观测的高空风场和微波辐射计测量的温湿变化特征与颗粒物垂直特征具有较好的对应关系,从污染物的垂直分布看,污染严重时段,污染物主要集中在200 m以下高度,污染层浅薄,呈现明显的双峰结构,在污染扩散阶段,随着逆温层减弱抬升,污染物向上扩散,地面污染物浓度明显下降,污染层较为深厚。污染物外源输送和污染物在连云港地区有利气象条件下的吸湿增长是本轮污染天气的主要原因。其中上游污染物传输主要来源于徐州和山东半岛中部地区,污染物离开连云港后主要沿东南到东方向向海上扩散,风向的转变可能是预报污染开始消散的关键气象条件,而风速的大小则是污染物消散快慢的关键。

西安第十四届全国运动会及残特奥会前后PM_(2.5)溯源研究

基于2021年9月~11月西安市环境空气质量监测数据,分析十四运会及残特奥会前中后期西安市区域PM_(2.5)的污染特征,利用HYSPLIT模型、潜在源贡献因子法(PSCF)和权重浓度轨迹法(CWT)确定气团输送路径、潜在源区及其对PM_(2.5)质量浓度的贡献.结果表明:研究期间西安市以东南风为主导,PM_(2.5)浓度在十四运会期间最低,残特奥会结束后最高.PM_(2.5)的气团输送路径以陕南附近的本地输送、偏东和偏南方向的近距离输送以及西北方向的远距离输送为主.PM_(2.5)的潜在源区主要分布在河南湖北、贵州四川重庆、新疆内蒙地区以及陕南各城市及周边省份交界处.

校园绿地秋季不同活动空间保健因子变化特征及综合评价

为了给华南地区校园师生及城市居民游憩出行场所与时间以及校园绿色空间设计提供科学依据,研究于2022年9—10月,同步观测华南农业大学内5种活动空间(林荫型、临水型、草坪型、行道树型以及广场型)的保健因子。结果表明,5种空间内的小气候日变化均呈倒“V”形,除广场型处于Ⅲ级不舒适水平外,其他4种空间均达到Ⅱ级舒适水平;空气负离子质量浓度日变化呈“双峰型”,林荫型空间空气负离子质量浓度达Ⅳ级保健浓度,其他4种空间均处于Ⅴ级允许浓度;空气颗粒物(PM_(2.5)和PM_(10))质量浓度日变化呈“U”型,林荫型空间达到环境空气质量Ⅰ级标准。不同空间综合保健功能排序为林荫型>临水型>行道树型>草坪型>广场型,此外林荫型空间保健功能在上午10:00时和下午16:00—18:00时空间综合保健指数达到峰值,因此建议校园师生此时段前往郁闭度较高的林荫型空间健身游憩。