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Characteristics of Airborne Nanoparticles during Summertime in Kuwait
Abstract
Airborne nanoparticles have prompted a strong research interest in the scientific community due to their adverse effects on human health and the environment. However, there is a notable lack of studies focusing on extreme summertime conditions, where ambient temperatures can reach ~48 °C, relative humidity falls to its minimum values, and dust events are frequently encountered. The overall aims of this research are to understand the behaviour and sources of airborne nanoparticles in hot and arid environmental conditions, develop a statistical prediction model for nanoparticles that uses routinely-monitored air pollutants, and investigate the mitigation measures (i.e., vegetation barriers) used to limit the penetration of on-road nanoparticles to the surrounding vicinity.
Size-resolved measurements of particle number distribution (PNDs) and concentrations (PNCs) were carried out continuously for one month at a roadside location in the State of Kuwait using a fast-response differential mobility spectrometer (DMS500) to assess the influence of summertime meteorological conditions on nanoparticles. Further data of trace pollutants (NOx, O3, CO, SO2 and PM10) and meteorological variables (wind speed, wind direction, temperature, relative humidity, and solar radiation), were obtained from the Kuwait Environment Public Authority (KEPA). The collected data was analysed to assess the behaviour of nanoparticles during summertime and to understand any unusual behaviour of PNDs and PNCs during (i) the afternoon, when temperature reaches it maximum and relative humidity to its minimum, and (ii) during the occurrence of Arabian dust events. The collected PNDs data were used to apportion the major sources and their contribution to total PNCs using a positive matrix factorisation (PMF) model. Further, a preliminary attempt to predict nanoparticles in three size ranges (nucleation mode: 5–30 nm, Aitken mode: 30–100 nm, and accumulation mode: 100–300 nm) using artificial neural network (ANN), was made. For the prediction purpose, seven scenarios were considered using different combinations of the routinely-measured meteorological and trace pollutant data as covariates. In addition, intermittent monitoring of PNDs and the associated PNCs were performed using DMS50 at a kerbside location in the United Kingdom (UK) to investigate the effect of vegetation barriers on traffic-generated nanoparticles, as well as pedestrian exposure. PND data was collected at four sampling locations pseudo-simultaneously using a multi-probe switching system. These locations encompassed the vegetation barrier and allowed us to make novel comparisons.
Despite high traffic volumes during noon hours, there was a substantial decrease in PNCs with a corresponding increase in geometric mean diameters (GMDs) due to high ambient temperature (∼48 °C) and wind speed (∼15 m s–1). The high wind speed has a dispersive effect (i.e., dilution), and saltation causes the suspension of particles and enhances the coagulation process. Based on the PMF modelling, traffic emissions were found to be a major contributor (73%) to the total apportioned PNCs, whereas Arabian dust transport was found to be the lowest contributor (3%). ANN succeeded in capturing the general trend between observed and predicted PNCs with R2 up to 0.79. The deviations between the observed and predicted PNCs were not substantial, as evidenced by the fact that predicted PNCs were within a factor of two of the observed PNCs.
Vegetation barriers were found to reduce not only PNCs by ~37%, but also the associated particle respiratory deposited doses in the human respiratory tract (RDD) by ~36%. The implication of vegetation barrier results are of high importance in the reduction of PNCs and the associated RDD. Besides policy makers and environmental authorities, the findings of this work are important for the modelling community to treat major nanoparticle sources in dispersion modelling and health impact assessments in the region.
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Atmospheric particle number size distributions of airborne particles (diameter range 10–500 nm) were measured over ten weeks at three sites in the vicinity of the A100 urban motorway in Berlin, Germany. The A100 carries about 180 000 vehicles on a weekday, and roadside particle size distributions showed a number maximum between 20 and 60 nm clearly related to the motorway emissions. The average total number concentration at roadside was 28 000 cm−3 with a total range between 1200 and 168 000 cm−3. At distances of 80 and 400 m from the motorway the concentrations decreased to mean levels of 11 000 and 9 000 cm−3, respectively. An obstacle-resolving dispersion model was applied to simulate the 3-D flow field and traffic tracer transport in the urban environment around the motorway. By inverse modelling, vehicle emission factors were derived, representative of a relative share of 6% lorry-like vehicles, and a driving speed of about 80 km h−1. Three different calculation approaches were compared, which differ in the choice of the experimental winds driving the flow simulation. The average emission factor per vehicle was 2.1(±0.2) · 1014 km−1 for particle number and 0.077(±0.01) · 1014 cm3 km−1 for particle volume. Regression analysis suggested that lorry-like vehicles emit 116 (± 21) times more particulate number than passenger car-like vehicles, and that lorry-like vehicles account for about 91% of particulate number emissions on weekdays. Our work highlights the increasing applicability of 3-D flow models in urban microscale environments and their usefulness in determining traffic emission factors.
The EPA PMF (Environmental Protection Agency positive matrix
factorization)
version 5.0 and the underlying multilinear engine-executable ME-2 contain
three methods for estimating uncertainty in factor analytic models: classical
bootstrap (BS), displacement of factor elements (DISP), and bootstrap
enhanced by displacement of factor elements (BS-DISP). The goal of these
methods is to capture the uncertainty of PMF analyses due to random errors
and rotational ambiguity. It is shown that the three methods complement each
other: depending on characteristics of the data set, one method may provide
better results than the other two. Results are presented using synthetic data
sets, including interpretation of diagnostics, and recommendations are given
for parameters to report when documenting uncertainty estimates from EPA PMF
or ME-2 applications.
A multidisciplinary group of researchers and policy-makers met to discuss the state-of-the-science regarding the potential of roadside vegetation to mitigate near-road air quality impacts in April 2010. Scientists discussed several studies that have measured and modeled the impacts of vegetative barriers on near-road air quality. Workshop participants agreed that further exploration of the use of vegetative barriers to mitigate adverse air quality is worth pursuing; however, care must be taken in both communicating the potential benefits of such a program and implementing this approach as a mitigation strategy. Participants also agreed that planting vegetation as a mitigation strategy may be most useful along existing roadways. Workshop participants identified a broad range of research needs and activities to further assess the role of vegetation in mitigating air quality impacts from traffic emissions.
A theoretical framework was constructed by which one can estimate the relative role of different processes in thedynamics of atmospheric nucleation mode particles. The framework relies on 14 timescales that describe (1) changes inthe total nuclei number concentration, (2) changes in the mean diameter of the nucleation mode and (3) concentrationsof low-volatile vapours responsible for the growth of nuclei. The magnitude of the derived timescales can be calculatedrelatively easily from the available measurement or modelling data. Application to the lower-troposphere revealed thatunder most conditions removal of nuclei is dominated by their coagulation with larger background particles and thatthis process competes very strongly with growth of nuclei to sizes relevant to atmospheric chemistry and physics.Withsome exceptions, self-coagulation of nuclei was shown to be of marginal importance compared with their growth bycondensation and their removal by coagulation. Finally, by comparing predictions based on relevant timescales withthose obtained from detailed numerical simulations, quantitative criteria were derived concerning (1) when one mayneglect self-coagulation of nuclei when looking at nucleation mode dynamics and (2) when the whole nucleation modecan be neglected because of its eventual removal. These criteria are extremely useful for atmospheric modellers whoneed to simplify their models as much as possible. From the modelling point of view, other processes requiring furtherattention are the introduction of new nuclei into the system and decrease in nuclei number concentration due to dilutionof the air. DOI: 10.1111/j.1600-0889.2004.00095.x
Frequent occurrence of Total Suspended Particulate (TSP), especially in summer, is one of the serious environmental issue in Kuwait. Increase in the frequency and concentration of TSP in the air is an indication of the degradation of the surrounding land. The TSP in air causes significant respiratory health problems. It is important to know the details of statistical parameters of TSP in the air for planning of activities which is influenced by the Particulate and also for assessing respiratory problems of the people whose nature of work warrants exposure to dusty climate. For this study the TSP is collected at five different locations using High Volume Sampler in Kuwait, viz. Manageesh, Jahra, Reqqa, Shuwaikh and Kuwait city for different range of periods. The TSP collected everyday is weighed and recorded in μg/m 3. Analysis on statistical parameters including probability density and probability of exceedence is carried out. From the analysis, it is found that the mean value of daily TSP vary from 197 to 330 μg/m 3, median varies from 123 to 167 μg/m 3 and mode from 75 to 163 μg/m 3. It is found that Jahra experience 9 days/year with daily TSP of more than 2000 μg/m 3, whereas for other locations it is from 1 to 3 times in a year. It is also found from the study that 15% of the measured TSP data exceeds 225 μg/m 3 for Kuwait city, 300 μg/m 3 for Shuwaikh and Manageesh, 375 μg/m 3 for Reqqa and 425 μg/m 3 for Jahra. Also based on recent measurements of TSP and Visibility for every five minutes, correlation between these two parameters were obtained. This paper provides a comprehensive details of the statistical analysis, probability density and probability of exceedence of TSP in Kuwait.
Covering an area of over 130 million km2 spanning the equator and tropics, the African continent features a spectacular geographic diversity. Consequently, it is characterised by extremely variable climatic, edaphic and ecological conditions, associated with a wide range of natural vegetation and wildlife, as well as human population density, crops and livestock. In this book, Henry Le Houérou presents his bioclimatic and biogeographic classification of Africa. The extensive data provide the basis for comparisons between various African regions, and with regions on other continents such as Latin America or the Indian subcontinent. The results constitute a rational basis for national, regional and sub-regional rural development planning, and for agricultural research dealing with aspects such as plant and animal introductions, the extrapolation or interpolation of experimental or developmental findings, and ecosystems dynamics. Possible problems of applications are also examined. © 2009 Springer-Verlag Berlin Heidelberg. All rights are reserved.