Demonstrating PM<Subscript>2.5</Subscript> and road-side dust pollution by heavy metals along Thika superhighway in Kenya,sub-Saharan Africa

This study assessed the level of heavy metal in roadside dust and PM_2.5 mass concentrations along Thika superhighway in Kenya. Thika superhighway is one of the busiest roads in Kenya, linking Thika town with Nairobi. Triplicate road dust samples collected from 12 locations were analysed for lead (Pb), chromium (Cr), cadmium (Cd), nickel (Ni), zinc (Zn), and copper (Cu) using atomic absorption spectrophotometry (AAS). PM_2.5 samples were collected on pre-weighed Teflon filters using a BGI personal sampler and the filters were then reweighed. The ranges of metal concentrations were 39–101 μg/g for Cu, 95–262 μg/g for Zn, 9–28 μg/g for Cd, 14–24 μg/g for Ni, 13–30 μg/g for Cr, and 20–80 μg/g for Pb. The concentrations of heavy metals were generally highly correlated, indicating a common anthropogenic source of the pollutants. The results showed that the majority of the measured heavy metals were above the background concentration, and in particular, Cd, Pb, and Zn levels indicated moderate to high contamination. Though not directly comparable due to different sampling timeframes (8 h in this study and 24 h for guideline values), PM_2.5 for all sites exceeds the daily WHO PM_2.5 guidelines of 25 μg/m³. This poses a health risk to people using and working close to Thika superhighway, for example, local residents, traffic police, street vendors, and people operating small businesses. PM_2.5 levels were higher for sites closer to Nairobi which could be attributed to increased vehicular traffic towards Nairobi from Thika. This study provides some evidence of the air pollution problem arising from vehicular traffic in developing parts of the world and gives an indication of the potential health impacts. It also highlights the need for source apportionment studies to determine contributions of anthropogenic emissions to air pollution, as well as long-term sampling studies that can be used to fully understand spatiotemporal patterns in air pollution within developing regions.     

Determination of road dust loadings and chemical characteristics using resuspension

The contribution of fugitive dust from traffic to air pollution can no longer be ignored in China. In order to obtain the road dust loadings and to understand the chemical characteristics of PM₁₀ and PM_2.5 from typical road dust, different paved roads in eight districts of Beijing were selected for dust collection during the four seasons of 2005. Ninety-eight samples from 28 roads were obtained. The samples were resuspended using equipment assembled to simulate the rising process of road dust caused by the wind or wheels in order to obtain the PM₁₀ and PM_2.5 filter samples. The average road dust loading was 3.82 g m^− 2, with the highest of 24.22 g m^− 2 being in Hutongs in the rural–urban continuum during winter. The road dust loadings on higher-grade roads were lower than those on lower-grade roads. Attention should be paid to the pollution in the rural–urban continuum areas. The sums of element abundances measured were 16.17% and 18.50% for PM₁₀ and PM_2.5 in road dust. The average abundances of OC and EC in PM₁₀ and PM_2.5 in road dust were 11.52%, 2.01% and 12.50%, 2.06%, respectively. The abundance of elements, water-soluble ions, and OC, EC in PM₁₀ and PM_2.5 resuspended from road dust did not change greatly with seasons and road types. The soil dust, construction dust, dust emitted from burning coal, vehicle exhaust, and deposition of particles in the air were the main sources of road dust in Beijing. Affected by the application of snow-melting agents in Beijing during winter, the amount of Cl⁻ and Na⁺ was much higher during that time than in the other seasons. This will have a certain influence on roads, bridges, vegetations, and groundwater.     

长沙市冬季人行道PM2.5污染特征及影响因素

了解不同气象条件下城市人行道细颗粒物(PM_2.5)时空分布特征对于指导城市环境评价及街道空间规划布局具有重要意义。选取长沙市车流量及人流量较大的4条道路旁0、5、10 m处的人行道,在冬季晴天、阴天和大风天开展PM_2.5质量浓度、风速、温度及相对湿度监测,探讨PM_2.5分布特征与气象因子的关系。结果表明:冬季晴天、阴天及大风天的人行道PM_2.5质量浓度变化呈现双峰双谷特征,峰值均出现在06:00—08:00,其次为18:00—20:00,谷值出现在14:00—16:00及22:00—24:00;距离机动车道10m处的人行道PM_2.5含量低于机动车道旁(即距离机动车道0 m)的人行道PM_2.5含量,这种差异在大风天气下更为显著;人行道PM_2.5质量浓度与温度、风速呈显著负相关关系,与空气湿度呈显著正相关关系,低温不利于PM_2.5扩散,但在大风天温度对PM_2.5的影响极小,风对PM_2.5含量的变化影响极大,在远离机动车道的人行道更为显著,而高湿度天气有利于PM_2.5的凝结。低温、高湿天气下06:00—08:00、18:00—20:00人行道PM_2.5质量浓度较高,大风对PM_2.5质量浓度具有一定削减作用,早晚高峰减少人行道洒水以降低空气湿度,有利于PM_2.5质量浓度的降低,减少PM_2.5积累。     

Computational Fluid Dynamics Modelling of the Pollution Dispersion and Comparison with Measurements in a Street Canyon in Helsinki

A measuring campaign was conducted in a street canyon (Runeberg St.) in Helsinki in 2003–2004. The concentrations of NO _x , NO₂, PM₁₀ and PM_2.5 were measured at street level and at roof level at an urban background location. This study utilises the data measured from 1 Jan to 30 April, 2004, when wind speed and direction measurements were also conducted on-site at the roof level. The computational fluid dynamics model ADREA-HF was used to compute the street concentrations, and the results were compared with the measurements. The predictions for the selected cases agreed fairly well (within < 25 % for 15 min average values) with the measured data, except for two cases: a windward flow in case of a low wind speed, and a moderate southerly flow parallel to the street canyon. The main reasons for the differences of predictions and measurements are the negligence of traffic-induced turbulence in the modelling and an under-prediction of ventilation of urban background air from a crossing street. Numerical results are presented for various example cases; these illustrate the formation of the vortices in the canyon in terms of the wind direction and speed and the influence of the characteristics of the flow fields on the concentration distributions.     

道路绿化带影响大气颗粒物分布实测研究

以福州市西三环快速路某路段为实验靶区,利用微型环境检测仪采集路边细颗粒物(PM_2.5)、亚微米颗粒物(PM_1.0)和黑碳(BC)的空间分布样本,解析其在道路绿化带前后(绿化带前是指干道和辅道外边缘线位置,其他位置均视为绿化带后)的变化特征及原因。结果表明：(1)颗粒物浓度随着采样点远离干道而整体趋于递减,呈现BC>PM_2.5>PM_1.0的衰减率变化特征,且植被稠密的路边环境对应更大的颗粒物浓度降幅。(2)夏季绿化带后的颗粒物浓度降幅高于冬季,冬季绿化带后部分采样点的PM_1.0和PM_2.5浓度甚至有所抬升。在植被茂密的路边环境下,风自干道吹向绿化带情景的路边空气质量介于风自绿化带吹向干道情景和风平行于干道情景之间。(3)BC对交通变化的敏感性高于PM_2.5和PM_1.0,植被茂密的绿化带后的颗粒物浓度降幅会因交通强度的上升而增大。风自干道吹向绿化带时,绿化带对颗粒物的调节作用会随交通源强和季节的变化而不同...     

Influence of Building Density and Roof Shape on the Wind and Dispersion Characteristics in an Urban Area: A Numerical Study

The Computational Fluid Dynamics code CFX-TASCflow is used for simulating the wind flow and pollutant concentration patterns in two-dimensional wind-tunnel models of an urban area. Several two-dimensional multiple street canyon configurations are studied corresponding to different areal densities and roof shapes. A line source of a tracer gas is placed at the bottom of one street canyon for modelling street-level traffic emissions. The flow fields resulting from the simulations correspond to the patterns observed in street canyons. In particular and in good agreement with observations, a dual vortex system is predicted for a deep flat-roof street canyon configuration, while an even more complex vortex system is evidenced in the case of slanted-roof square street canyons. In agreement with measurement data, high pollutant concentration levels are predicted either on the leeward or the windward side of the street canyon, depending on the geometrical details of the surrounding buildings.     

Air quality effects of traffic in a canyon-like street (Falmouth,U.K.)

It has been suggested that in relation to air quality impacts, roads with low (<20 000 vpd) traffic flow need not be consideredas significant. This study examines this suggestion more closelyby comparing real-time monitoring of traffic related pollutants (NO₂, PM₁₀ and PAH) at two sites (including a `canyon-street') in Falmouth, Cornwall in relation to traffic flow. For comparison, real-time monitoring data for NO₂ and PM₁₀ is also taken from a well ventilated site in Camelford, Cornwall. The data obtained suggest that roads with traffic flow considerably lower than 20 000 vpd can give rise topollutant levels which have implications for human health. The application of simple linear regression techniques to the datasuggests that under certain conditions simple estimates can be made in relation to likely traffic-related air quality effects in canyon-like streets.     

An Integrated Approach to Street Canyon Pollution Modelling

An integrated method for the prediction of the spatial pollution distribution within a street canyon directly from a microscopic traffic simulation model is outlined. The traffic simulation package Paramics is used to model the flow of vehicles in realistic traffic conditions on a real road network. This produces details of the amount of pollutant produced by each vehicle at any given time. The authors calculate the dispersion of the pollutant using a particle tracking diffusion method which is superimposed on a known velocity and turbulence field. This paper shows how these individual components may be integrated to provide a practical street canyon pollution model. The resulting street canyon pollution model provides isoconcentrations of pollutant within the road topography.     

Relationships of relative humidity with PM<Subscript>2.5</Subscript> and PM<Subscript>10</Subscript> in the Yangtze River Delta,China

Severe particulate matter (PM, including PM_2.5 and PM₁₀) pollution frequently impacts many cities in the Yangtze River Delta (YRD) in China, which has aroused growing concern. In this study, we examined the associations between relative humidity (RH) and PM pollution using the equal step-size statistical method. Our results revealed that RH had an inverted U-shaped relationship with PM_2.5 concentrations (peaking at RH = 45–70%), and an inverted V-shaped relationship (peaking at RH = 40 ± 5%) with PM₁₀, SO₂, and NO₂. The trends of polluted-day number significantly changed at RH = 70%. The very-dry (RH < 45%), dry (RH = 45–60%) and low-humidity (RH = 60–70%) conditions positively affected PM_2.5 and exerted an accumulation effect, while the mid-humidity (RH = 70–80%), high-humidity (RH = 80–90%), and extreme-humidity (RH = 90–100%) conditions played a significant role in reducing particle concentrations. For PM₁₀, the accumulation and reduction effects of RH were split at RH = 45%. Moreover, an upward slope in the PM_2.5/PM₁₀ ratio indicated that the accumulation effects from increasing RH were more intense on PM_2.5 than on PM₁₀, while the opposite was noticed for the reduction effects. Secondary transformations from SO₂ and NO₂ to sulfate and nitrate were mainly responsible for PM_2.5 pollution, and thus, controlling these precursors is effective in mitigating the PM pollution in the YRD, especially during winter. The conclusions in this study will be helpful for regional air-quality management.     

某典型交通路口大气颗粒物(PM10和PM2.5)中多氯联苯季节变化特征

应用同位素稀释高分辨率气相色谱-高分辨质谱 (HRGC-HRMS) 联用技术对北京市北四环典型交通路口大气颗粒物PM₁₀和PM_2.5中多氯联苯(PCBs)进行了监测,分析了PCBs浓度水平、单体组成特征、粒径分布规律和季节变化趋势。结果表明:大气颗粒物PM₁₀和PM_2.5样品中19种PCBs浓度和毒性浓度(TEQ,以世界卫生组织毒性当量因子WHO-TEF计)分别为1.05～13.83 pg/m³(平均值为6.66 pg/m³)和1.24～15.18 fg/m³ (平均值为6.84 fg/m³)、0.80～8.51 pg/m³(平均值为4.32 pg/m³)和0.88～13.40 fg/m³ (平均值为5.90 fg/m³),PM₁₀和PM_2.5中PCBs的单体分布模式相似,浓度丰度最大的是PCB-28和PCB-209,而对毒性当量贡献最大的是PCB-126。PCBs浓度季节变化明显,冬、春季明显高于夏、秋季。 PCBs浓度季节变化特征表明,不同季节采样点PCBs来源不同,除历史使用外,采暖季节可能主要来自机动车排放和化石燃料的燃烧,而非采暖季节主要来自机动车排放。粒径分布表现为PCBs倾向于富集在PM_2.5中,占PM₁₀总浓度的61%～87%(平均值为72%)。     

Diurnal concentrations variations,size distributions for ambient air particles and metallic pollutants (Cr,Mn, Ni,Cd, Pb) during summer season at a traffic area

This study characterized and discussed particulate ambient air particulate concentrations and seasonal variations for PM₁₈, PM₁₀, PM_2.5, and PM₁ during June 2013–July 2013 at this traffic sampling site. In addition, this study also characterized the ambient air particulates size distributions by using MOUDI-100S4 sampler to collect 1-day the ambient suspended particles (PM₁₈, PM₁₀, PM_2.5, and PM₁) at this sampling site. In addition, the study also showed that the main pollutants contributions were from traffic and residual areas. As for the pollutants seasonal concentrations variations, the results indicated that the average particle concentrations orders were all displayed as daytime?>?nighttime for PM₁₈, PM₁₀, PM_2.5 and PM₁ at this characteristic sampling site. The results further indicated that the mean highest of metal concentrations in this study indicated that the average metal concentration were all displayed as Mn?>?Cr?>?Ni?>?Pb?>?Cd for PM₁₈, PM₁₀, PM_2.5 and PM₁ on daytime and nighttime at this characteristic sampling site.     

Simulation of Urban-Scale Air Pollution Patterns in Luxembourg: Contributing Sources and Emission Scenarios

The aim of this study is to investigate the air pollution situation in an urban area in southwestern Luxembourg and to simulate annual NO₂ and PM₁₀ concentrations in response to changes in meteorological conditions and emissions using a Gaussian dispersion model. Simulations are carried out for the years 1998–2006. Emission scenarios related to road transport and nonindustrial combustion are performed in order to predict changes of air pollution levels. Road transport is by far the most important local emission source in the study area. Scenarios with more stringent emission standards for vehicles, less traffic, and fewer heavy-duty vehicles lead to reductions of NO_x and primary PM₁₀ emissions. As a result, the annual NO₂ concentrations are decreasing in most parts of the study area and are below the European annual limit value of 40 μg?m^?3. In contrast, a scenario with increased use of wood pellets for domestic heating shows an increase in urban PM₁₀ concentration. The year-to-year variability of meteorological conditions accounts for the same magnitude of absolute NO₂ and PM₁₀ concentration changes as the emission scenarios. The comparison with measurements located in the study area shows that the model is able to predict urban-scale annual average air pollution. The proposed application results show that the model can be appropriate for policy-driven air quality management and planning queries.     

Seasonal Variations of PM10 and TSP in Residential and Industrial Sites in an Urban Area of Kolkata, India

The objective of the study is to investigate seasonal and spatial variations of PM₁₀ (particulate matter with aerodynamic diameter less than or equal to 10 μm) and TSP (total suspended particulate matter) of an Indian Metropolis with high pollution and population density from November 2003 to November 2004. Ambient concentration measurements of PM₁₀ and TSP were carried out at two monitoring sites of an urban region of Kolkata. Monitoring sites have been selected based on the dominant activities of the area. Meteorological parameters such as wind speed, wind direction, rainfall, temperature and relative humidity were also collected simultaneously during the sampling period from Indian Meteorological Department, Kolkata. The 24 h average concentrations of PM₁₀ and TSP were found in the range 68.2–280.6 μg/m³ and 139.3–580.3 μg/m³ for residential (Kasba) area, while 62.4–401.2 μg/m³ and 125.7–732.1 μg/m³ for industrial (Cossipore) area, respectively. Winter concentrations of particulate pollutants were higher than other seasons, irrespective of the monitoring sites. It indicates a longer residence time of particulates in the atmosphere during winter due to low winds and low mixing height. Spread of air pollution sources and non-uniform mixing conditions in an urban area often result in spatial variation of pollutant concentrations. The higher particulate pollution at industrial area may be attributed due to resuspension of road dust, soil dust, automobile traffic and nearby industrial emissions. Particle size analysis result shows that PM₁₀ is about 52% of TSP at residential area and 54% at industrial area.     

Characterization and Identification of the Sources of Chromium, Zinc, Lead, Cadmium, Nickel, Manganese and Iron in Pm10 Particulates at the Two Sites of Kolkata, India

Monitoring of ambient PM₁₀ (particulate matter which passes through a size selective impactor inlet with a 50% efficiency cut-off at 10 μm aerodynamic diameter) has been done at residential (Kasba) and industrial (Cossipore) sites of an urban region of Kolkata during November 2003 to November 2004. These sites were selected depending on the dominant anthropogenic activities. Metal constituents of atmospheric PM₁₀ deposited on glass fibre filter paper were estimated using Inductively Coupled Plasma Atomic Emission Spectrometer (ICP-AES). Chromium (Cr), zinc (Zn), lead (Pb), cadmium (Cd), nickel (Ni), manganese (Mn) and iron (Fe) are the seven toxic trace metals quantified from the measured PM₁₀ concentrations. The 24 h average concentrations of Cr, Zn, Pb, Cd, Ni, Mn and Fe from ninety PM₁₀ particulate samples of Kolkata were found to be 6.9, 506.1, 79.1, 3.3, 7.4, 2.4 and 103.6 ng/m³, respectively. The 24 h average PM₁₀ concentration exceeded national ambient air quality standard (NAAQS) as specified by central pollution control board, India at both residential (Kasba) and industrial (Cossipore) areas with mean concentration of 140.1 and 196.6 μg/m³, respectively. A simultaneous meteorology study was performed to assess the influence of air masses by wind speed, wind direction, rainfall, relative humidity and temperature. The measured toxic trace metals generally showed inverse relationship with wind speed, relative humidity and temperature. Factor analysis, a receptor modeling technique has been used for identification of the possible sources contributing to the PM₁₀. Varimax rotated factor analysis identified four possible sources of measured trace metals comprising solid waste dumping, vehicular traffic with the influence of road dust, road dust and soil dust at residential site (Kasba), while vehicular traffic with the influence of soil dust, road dust, galvanizing and electroplating industry, and tanning industry at industrial site (Cossipore).     

Comparison of Numerical and Experimental Results for the Evaluation of the Depollution Effectiveness of Photocatalytic Coverings in Street Canyons

Towards the aim of improving the air quality in the urban environment via the application of innovative TiO₂ based photocatalytic coverings, a field campaign took place within the frame of the EU PICADA project () to asses the expected depollution efficiency of such materials under realistic conditions. Furthermore, extensive numerical modeling was performed via the application of the RANS CFD code for microscale applications MIMO, in an effort to asses the sensitivity of the developing flow field and the corresponding dispersion mechanism and hence of the depollution efficiency of the PICADA products on a wide range of factors, with most notably the length of the street canyon, the thermal exchange between the heated street canyon walls and the air and the approaching wind direction. For the needs of the PICADA project a new, simple module had to be implemented into MIMO to be able to model the removal of NO_x from a street canyon whose walls have been treated with a photocatalytic product. The model simulations results presented in this paper, show that MIMO is indeed capable of predicting the effectiveness of the photocatalytic products in question. At the same time, they reveal a strong dependence of the developing flow and concentration fields inside the field site street canyon configuration on most of the aforementioned factors with most notably the direction of the approaching wind.

南充市大气PM10与PM2.5排放清单及特征

以四川省南充市为研究区域,通过实地调研、现场测试及结合统计年鉴等获得数据,采用排放因子法计算南充市2014年大气PM_(10)、PM_(2.5)排放量并建立排放清单。结果表明,南充市2014年扬尘源、移动源、生物质燃烧源、化石燃料固定燃烧源、工艺过程源排放总量PM_(10)分别为85 187、1 777、9 175、2 417、3 519 t,PM_(2.5)分别为16 093、1 619、7 322、914、1 585 t,PM_(10)贡献率分别为83.5%、1.7%、9.0%、2.4%、3.4%,PM_(2.5)贡献率分别为58.4%、5.9%、26.6%、3.3%、5.8%。城市区域扬尘源、生物质燃烧源、移动源、化石燃料固定燃烧源、工艺过程源对PM_(10)贡献分别为60.0%、12.5%、6.3%、8.6%、12.5%,对PM_(2.5)贡献分别为41.8%、21.6%、14.4%、8.1%、14.1%。南充市2014年大气PM_(10)、PM_(2.5)排放源总量和贡献率以及区域空间分布特征均存在差异。     

省级高空间分辨率扬尘源排放清单研究

通过对浙江省统一开展部署和行动,现场调查收集全省7 507个施工工地、3 923个堆场以及不同等级公路和城市道路的真实活动水平数据,并基于点源地理信息和路网信息图层,采用排放系数法和ArcGIS工具构建了浙江省2015年3 km×3 km高空间分辨率扬尘源排放清单。结果表明,2015年浙江省扬尘源PM₁₀和PM_2.5的排放量分别为24.26×10⁴ t和6.00×10⁴ t,其中PM₁₀和PM_2.5排放贡献均主要为施工扬尘和道路扬尘,施工扬尘分别贡献37.7%和39.3%,道路扬尘分别贡献36.5%和39.1%。从城市空间分布来看,杭州市、宁波市、温州市、绍兴市扬尘排放总量居于全省前四,舟山市最低,而城市主城区排放量显著高于郊区。     

大数据解析技术在大气环境监测中的应用研究

针对近年来新兴的大数据及挖掘、分析技术,对大数据解析技术在环境科学研究中的应用进行了分析和探析。以城市局部地区大气细颗粒污染物PM2.5浓度计算为例,筛选了PM2.5浓度历史数据、气象条件、交通状况、人群活动情况、网格道路状况等数据为影响特征量,分析了用神经网络法进行大数据解析和推演的原理和数学过程,是用数学、计算机、统计等方法研究解决多元、非线性复杂环境问题的一种新的探索。     

Measurements and Modelling of Air Pollution in a Street Canyon in Helsinki

A measuring campaign was conducted in the street canyon 'Runeberg street' in Helsinki in 1997. Hourly concentrations of carbon monoxide (CO), nitrogen oxides (NO_X), nitrogen dioxide (NO₂) and ozone (O₃) were measured at the street and roof levels, and the relevant hourly meteorological parameters were measured at the roof level. The hourly street level measurements and on-site electronic traffic counts were conducted during the whole year 1997, and roof level measurements were conducted during approximately two months, from 3 March to 30 April in 1997. The Operational Street Pollution Model (OSPM) was used to calculate the street concentrations and the results were compared with the measurements. The overall agreement between measured and predicted concentrations was good for CO and NO_x, but the model slightly overestimated the measured concentrations of NO₂. The database, which contains all measured and predicted data, is available for a further testing of other street canyon dispersion models.     

石家庄市大气颗粒物元素组分特征分析

为研究石家庄市大气颗粒物的污染特征及其来源,于2013年4—5月在主城6区分别采集TSP、PM10和PM2.5颗粒物样品,利用ICP-MS分析其中的22种元素浓度。结果表明,石家庄市城区Ca、Fe元素在各粒径颗粒物中含量都较高,PM2.5中的S、K含量较高,PM10和TSP中Mg、Al的浓度相对较高。颗粒物的主要来源为燃煤尘、道路尘和建筑尘,TSP、PM10和PM2.5具有较好的统计相关性和同源性。