Aerosol Science - Science topic

Hey there Mika Mika,

Absolutely, integrating multiple air quality map images into a single image to depict the average is a great approach for your research. Here's a method using Python and a library called Matplotlib:

1. **Data Preparation**: First, you'll Mika Mika need to download the images from the Sentinel-5 website and organize them properly.

2. **Python Script**: Write a Python script to read all the images, calculate the average, and create a new image.

```python

import numpy as np

import matplotlib.pyplot as plt

from PIL import Image

# Function to read an image and convert it to numpy array

def read_image(image_path):

img = Image.open(image_path)

return np.array(img)

# Function to calculate the average of images

def average_images(image_paths):

total_images = len(image_paths)

first_image = read_image(image_paths[0])

sum_image = first_image.astype(np.float64)

# Summing up all images

for path in image_paths[1:]:

img = read_image(path)

sum_image += img.astype(np.float64)

# Calculating the average

average_image = (sum_image / total_images).astype(np.uint8)

return average_image

# List of paths to your daily images

daily_images_paths = ["path_to_your_images/image1.png", "path_to_your_images/image2.png", ...]

# Call the function to get the average image

average_img = average_images(daily_images_paths)

# Save the average image

plt.imsave("average_image.png", average_img)

```

3. **Visualization**: You Mika Mika can also visualize the average image using Matplotlib.

```python

plt.imshow(average_img)

plt.axis('off')

plt.show()

```

This script will generate an average image from all the daily images you Mika Mika have. It's important to ensure that the images are aligned and have the same dimensions. You Mika Mika can adjust the script accordingly if your images have different sizes.

Some interesting articles to read are:

Feel free to reach out if you Mika Mika need further assistance!

Utilizar muestreadores de Partículas Suspendidas totales en el Aire, puede resultar muy apropiado.

I agree with Michel M. Verstraete about MISR data. In addition, you may also consider looking at POLDER aerosol products. As polarized reflectance from snow surface can be small enough, which is an advantage for retrieving aerosols over snow. This is one article about this:

Also, CALIOP lidar may provide aerosol retrievals over snow as well, although with limited spatial coverage.

@Marie - another approach that has worked for us was polyurethane (PUF) foam, followed by a filter. This may decrease the loading on the filter. You can still extract most of the organic compounds.

Hi Fabrice Kapiamba,

If I'm understanding your question correctly, you are trying to convert a concentration in units of counts/L to dN/dlogDp for a specific Dp range, say Dp1 to Dp2.

If that is the case, I believe you would do the following:

E.g. if the range of the Dp size bin is 0.3 μm to 0.4 μm, you would divide the resulting concentration from Step 1 by [log(0.4) - log(0.3)].

This should give you a value that is comparable to the dN/dlogDp value from your other instrument.

Let me know if I've misinterpreted anything or something is unclear.

Best,

Joe

Dear @Sujan Prasad Gautam

Thank you very much.

Thanks Dr. Nick Jordan

The Hygroscopicity is morphology dependent. For further discussion please kindly consider Laskina et al. (2014): Size Matters in the Water Uptake and Hygroscopic Growth of Atmospherically Relevant Multicomponent Aerosol Particles

ABSTRACT: Understanding the interactions of water with atmospheric aerosols is crucial for determining the size, physical state, reactivity, and climate impacts of this important component of the Earth’s atmosphere. Here we show that water uptake and hygroscopic growth of multicomponent, atmospherically relevant particles can be size dependent when comparing 100 nm versus ca. 6 μm sized particles. It was determined that particles composed of ammonium sulfate with succinic acid and of a mixture of chlorides typical of the marine environment show size-dependent hygroscopic behavior. Microscopic analysis of the distribution of components within the aerosol particles show that the size dependence is due to differences in the mixing state, that is, whether particles are homogeneously mixed or phase separated, for different sized particles. This morphology-dependent hygroscopicity has consequences for heterogeneous atmospheric chemistry as well as aerosol interactions with electromagnetic radiation and clouds.

Single Scattering Albedo parameter retrieval requires accurate information about the aerosol refractive index (or chemical composition). In AERONET, the volume size distribution parameters (mode radii and width) are retrieved along with the refractive index (wavelength dependent) information. You can use this information in a Mie Scattering code to derive the single scattering albedo and scattering phase function (or asymmetry parameter) along with aerosol extinction or optical depth at a particular wavelength. This may not be the best solution but you can give a try!

Omar Z. Sharaf : If one is free in the choice of an integration algorithm for the ordinary differential equations of particle transport in the fluid, than I would choose a 4th order Runge-Kutta method with automatic adaptive timestep control, so that it can be achieved, that a certain prescribed error threshold is maintained all the time.

: I tend to disagree on that. If a particle size distribution is selected for a certain injection, than the solver tries to realize this distribution function by injecting particles of different sizes with the appropriate probability, which realizes finally the size distribution function.

If the injection conditions get more complicated, e.g. by two overset distribution functions for particle size and particle velocity, i.e. a particle with a certain size should be injected with a certain velocity by itself again following a certain distribution function, than this cannot be realized within the ANSYS Fluent GUI. In this case you need to write a piece of C programe which realizes this overset of particle injection conditions and creates the particle injection conditions in an particle input data file in accordance to Fluent syntax. Than this particle injection file can be used for the initial particle injection conditions instead of the build-in injection creation tools.

Regards,

Dr. Th. Frank.

Artur Braun Thank you for your comment! Frankly, I'm not familiar with this technology, and from a quick glance it seems like this isn't exactly what I was looking for, but very interesting nonetheless. From what I can understand, the soot was analyzed in a chamber (i.e. "experimental hutch") using the SAXS method, while I was looking for something that could potentially take measurements of morphology "in-line" with the flow of the SP2. Either way, thanks for sharing the interesting experiment and your thoughts!

Hi Ehsan,

As for Influenza type A, it is important to consider that the air exhaled by the healthy person also contains influenza virus particles. In studies of particles exhaled by healthy subjects during tidal breathing, researchers reported concentrations from 1 to over 1 × 104 particles per liter, with the majority of the particles being less than 0.3 μm in diameter. One of the studies also reported that 55% of the population studied exhaled >98% of the particles in the air volume investigated and concluded that these subjects, classified as high producers, could, over time, exhale more particles during normal tidal breathing than during relatively infrequent coughing or sneezing events. Concentrations in exhaled breath samples ranged from <48 to 300 influenza virus RNA copies per filter in the positive samples, corresponding to exhaled breath generation rates ranging from <3.2 to 20 influenza virus RNA copies per minute. Total particle concentrations ranged from 67 to 8.5 × 103 particles per liter of air.

To determine the concentration of virus particles in the air, the RT-PCR method is often used. However, RT-PCR analysis provides information on the total number of viral particles, but not on the number of infectious particles. Influenza virus genomic segments are chosen and packaged at random, whereby only parts of the virions are infectious.

Best wishes,

Ilya

You may have some inspiration from the above papers

Additionaly, FTP site of MODIS L2 atmosphere data is following,

Giovanni, providing L3 data, is another nice DB ! 

Are you running it with monotonic and positive definite namelist options? That may help.

The problem of radiative transfer in the atmosphere is still far from being solved. We can provide, however, some rough estimates. According to Koschmieder law, the visibility range X_v could be estimated as:

X_v=3.912/B_ext

where B_ext is the extinction coefficient (for derivation you can consult entry Visibility in the English edition of the Wikipedia)

B_ext for particles in the sub-micron range of sizes (such as we can expect to be suspended in air over the dessert areas) we have

B_ext=0.37 x 10^{-4} [m^{-1}]

(This estimate is based on Willeke and Brockmann (1977), Atm. Env. Vol. 11, pp 995-999)

The visibility range is thus around 105 km. Considering that the value of B_ext could be slightly larger after including some of the particles from mode 1 (see eq. (10) in Willeke and Brockmann (1977)) the value X_v =75.75 km mentioned in your question looks very reasonable.

I hope that this is helpful.

See the book by Cooper and Alley, Air Pollution Control. A design Approach 2nd Ed (1994), Chapter 12, You need to know the solute and the isotherm on coal. But you will find a generailsed isotherm on activated coal in the book. If you need to calculate time between regenaration cycles, see McCabe et al, Unit Operations in Chem Eng, the Chapter on Adsorption. McGraw Hill 1993.You will find there a couple of good examples.

Regards

I used a 6 stage Marple Impactor  a long time ago and analysed the samples with PIXE. This required having the minimum mass possible in the substrate. In order to use your samples in a microscope you need an as plane as possible surface. Not to have rebounce, you need it to be sticky. Try getting a smooth surface (a glass or a polymer material) and get it covered with a very thin layer of grease (eg. you may dissolve 5% paraffin in benzene and deposit a thin film of the solution over your collecting surface, after the benzene evaporates you get a very thin greasy surface, micrometers thick. Take into account that you should handle benzene in a proper laboratory, not on the desk of you office!). Notice that the thin greasy film must be invisible to the naked eye, otherwise it is too thick. As to glass fibre or quartz fibre filters, they will be too rough for a good work with the microscope.

@Robert

Over continents there are other hygroscopic components in aerosol: sulfuric acid, ammonium sulphate and nitrate as well as soluble organic compounds

Dear all,

Here is the author's reply as attached.  

He mentioned that "our grouping (i.e., 370 nm group vs 880 nm group) should be accepted in a relative way to stress two cases, (i) samples having components that absorb relatively more light at short wavelength and (ii) samples having components that absorb relatively more light at longer wavelength."

Well, I didn't think of any other components that will absorb more long-wavelength (880nm) light  than Black carbon.  In my opinion, if the sample is pure BC, EBC(370) will be equal to EBC (880) (see attached pic), but once there is organics that absorb UV-light, EBC(370) will be greater than EBC (880).

Best,

Guoliang

Hi friends,

Anyone could help inMatlab code to plot SMPS data for number concentrations and particle diameter vs. time 

The simple answer to this question of whether single particle is "better" than ensemble (bulk) particle analysis is... one needs to be specific about what they are looking to learn.

Single particle chemical analysis of aerosols is complementary to ensemble or bulk analysis of aerosol: each gives you a different kind of information.  

Single particle methods excel at describing the mixing state of the aerosol (do chemicals reside in the same or separate particles?) and can do a nice job in determinations of aerosol source contributions to an air mass, but tend to struggle with mass-based quantitation.  Single particle mass spectrometers produce large datasets in relatively short time frames, requiring data clustering methods (ART-2a, K-means, etc) to reduce the data to something more analytically manageable.  Microscopic single-particle techniques (when operated without computer automation) can have the opposite problem, where they can sometimes struggle to provide statistically-robust data due to high analytical costs per particle, but provide high resolution spatial information and now some even provide spatially-resolved spectroscopic information.  

Ensemble aerosol techniques provide strong mass-based quantitation of the aerosol population, which is valuable for many types of studies in which mass closure is important.  Since aerosol mass increases as the cube of the particle size, these measurements tend to emphasize the influence of larger particles on the sample, unless the technique explicitly size-segregates the sample.  Ensemble aerosol sampling, when performed at sufficiently high temporal resolution (e.g., real-time mass spectrometry), can be used to understand aerosol sources using a source-receptor data analysis tool -- Positive Matrix Factorization has been widely applied for this purpose in many studies for over a decade.  Bulk/ensemble analytical methods fail to describe the mixing state of the particle population, and sometimes can struggle with accounting for changes in number concentration of small particles, which do not constitute a large influence on the total aerosol mass, but can be important for cloud properties, for instance.  

Both types of information are valuable, but which one you require depends very heavily on the type of scientific question you plan to ask.  If you're looking for a study where both are used, I'd recommend the attached companion papers by Dall'Osto et al. and Decesari et al. where they use both techniques to characterize aerosol in the marine boundary layer.  There are a lot of examples of studies where it is stressed that one of the two approaches is more appropriate for a certain application, but without knowledge of your scientific question, this would be difficult to help you assess which would be more appropriate.

 I think you can use CAMx or CMAQ, which are very well-known air quality model. Each of them has specific modules for source apportionment analysis hence they could possibly be utilized for your study. The link below would show you some example studies regarding on the source apportionment using the CAMx and CMAQ model. I'm not sure whether you want to conduct a model based study or measurement based one, but hopefully these are helpful for your study. 

This means the value given is applicable provided the range of AOD values are between those. If not, you need to go for other methods .

Validation exersizes show that different instruments perform different in different regions and no instrument performs best everywhere. Therefore I would suggest a combination of MODIS, MISR, SeaWiFS and ATSR-2/AATRS, all of which are no readily available. CALIOP when you need height info and speciation. Examples can be found in the literature

Gulab:

You may estimate the carbon by difference: then you must know the concentration of the major anions.

Actually this is the way I did this myself 20 years ago with cascade-impactor samples. At that time we did not even know there was so much carbon in PM. Carbon was not analysed and there were only 2 persons in Europe who had done that for a few sampes 10 YEARS earlier

prof Puxbaum and dr Cachier

Alexandra

I do not understand what you mean with

"Carbon particulates that are OXIDISED up to about 600ºC were classified as organic carbon":

at this temperature all carbon is combusted:

did you mean HEATED up to 600 C without OXYGEN?

Gouliang

Protocols: the IMPROVE protocol is just one; there is also the NIOSH DRI and EUSAAR protocol in which the heating rates are different and thus also the various fractions OC1 OC2 etc

Dear Sandra, the topic is interesting. I wish these documents may support you.

Moreover, I suppose you will have to consider also the effect of humidity on particle (size for instance..).

Cheers, Valerio 

 http://www.ecn.nl/docs/library/report/2000/c00061.pdf

Short answer: there's been claimed correlations and some theoretical work, but no experimental verification.

Long answer with citations:

A correlation between cosmic ray flux and clouds in Earth’s atmosphere has been described (see, for instance, Marsh and Svensmark, 2000). However, this correlation has been called into question by Sloan and Wolfendale (2008) and Erlykin and Wolfendale (2011). Further, the claim of a correlation between climate change and spiral arm crossings (used to support the cosmic ray–cloud connection) by Shaviv (2002) has been effectively ruled out based on updated knowledge of Galactic dynamics (Overholt et al., 2009). The physical mechanism itself, involving enhanced formation of aerosols and nucleation sites (Tinsley, 2000; Svensmark et al., 2009), while plausible, is not established (Wagner et al., 2001; Pierce and Adams, 2009). The CLOUD experiment at CERN has sought to establish such a mechanism, with inconclusive results (Duplissy et al., 2010, Kirkby et al., 2011).

Marsh, N. and Svensmark, H. (2000) Cosmic rays, clouds, and climate. Space Sci Rev 94:215–230.

Sloan, T. and Wolfendale, A.W. (2008) Testing the proposed causal link between cosmic rays and cloud cover. Environ Res Lett 3, doi:10.1088/1748-9326/3/2/024001.

Erlykin, A.D. and Wolfendale, A.W. (2011) Cosmic ray effects on cloud cover and their relevance to climate change. Journal of Atmospheric and Solar-Terrestrial Physics 73:1681–1686.

Shaviv, N.J. (2002) Cosmic ray diffusion from the galactic spiral arms, iron meteorites, and a possible climatic connection. Phys Rev Lett 89, doi:10.1103/PhysRevLett.89.051102.

Overholt, A.C., Melott, A.L., and Pohl, M. (2009) Testing the link between terrestrial climate change and galactic spiral arm transit. Astrophys J 705, doi:10.1088/0004-637X/705/2/L101.

Tinsley, B.A. (2000) Influence of solar wind on the global electric circuit, and inferred effects on cloud microphysics, temperature, and dynamics in the troposphere. Space Sci Rev 94:231–258.

Svensmark, H., Bondo, T. and Svensmark, J. (2009) Cosmic ray decreases affect atmospheric aerosols and clouds. Geophys Res Lett 36, doi:10.1029/2009GL038429.

Wagner, G., Livingstone, D.M., Masarik, J., Muscheler, R., and Beer, J. (2001) Some results relevant to the discussion of a possible link between cosmic rays and Earth’s climate. J Geophys Res 106:3381–3387.

Pierce, J.R. and Adams, P.J. (2009) Can cosmic rays affect cloud condensation nuclei by altering new particle formation rates? Geophys Res Lett 36, doi:10.1029/2009GL037946.

Duplissy, J., et al. (2010) Results from the CERN pilot CLOUD experiment. Atmos Chem Phys 10:1635–1647.

Kirkby, J., et al. (2011) Role of sulphuric acid, ammonia and galactic cosmic rays in atmospheric aerosol nucleation. Nature 476:429–433.

Aerosols play an important role in the global climate, the radiative forcing of climate, and the Earth’s radiative balance.  They act by modifying the local and planetary albed and by absorbing the upward terrestrial thermal radiation. Aerosols influence the radiation balance through two key processes: directly, by scattering and absorbing solar radiation, and indirectly, by acting as cloud condensation nuclei and thus dramatically affecting the optical properties of clouds.

see attached file as well to more detail about it.

Regards

Today's NAAPS Dust Cloud image

There are some Forecasting "Rules of Thumb" here which may help: http://weatherfaqs.org.uk/book/export/html/164

If you are not going to study condensation and rain droplet formation processes in detail  there is no need to know anything about aerosol for calculating rainfall  rates or the amount of precipitation. You simply assume that there always  are enough condensation nuclei present. In fact this is the case. So you only have to calculate the amount of water which has to fall out to reduce the supersaturation during an ascent of an airmass so that a relative humidity of 100 % is not exceeded. Of course you also have to take into account the amount of evaporation of the droplets if they are falling through layers of dry air.

doi does not work, but you can find this paper on ResearchGate

A.I. Chulichkov, M.S. Andreev, A.S. Emilenko, V.A. Ivanov, A.P. Medvedev, O.V. Postylyakov. Method of estimation of cloud base height using ground-based digital stereophotography. Proc. SPIE, Vol 9680, 96804N,

Hello Mohit,

You measure Da with Elpi and TSI 3076 manual is speaking about mobility Diameter.  You can calculate your aerodynamic diameter, NaCl density is ~2.2 .

Salt concentration might be too high.

I would extend the explanation to include high EA conditions when you are burning bituminous and sub-bituminous coal.

I tried some Virginia coals (3) in a bottom-lit downdraft (BLDD) stove and had significant tar formation which was not in the form of balls, but a general gluing together of all the coal. Loose coal was put in, it got hot under adequate air conditions, it all glued itself together into a single mass. The glue was flowing high melting temperature tar, which later burned away leaving individual pieces of coke. If the Time Temperature Turbulence combination was inadequate, the consequence would be condensed tar PM.

I attributed this to the tars which have melting temperatures high enough to resist instant vaporisation. I expect that during incomplete combustion of that material, you will get spherical PM with a similar composition.

If you can get an XRF and XRD analysis, send it to Prof Lodoysamba in Mongolia and ask him if it is recognisable. He has done a lot of nuclear analysis of PM in Ulaanbaatar.

From his lessons, you can develop the capacity to use those two tests to track particles back to their origins (source apportionment).  He was able to differentiate between carbonaceous particles that came from high and low temperature combustion.(i.e. power stations and domestic stoves).

Papori --

Thanks for your interest in MISR.  I agree with previous notes by Felix and Michel.  The Level 2 data are generally better for determining aerosol type than the Level 3, because sensitivity to aerosol type varies greatly with retrieval conditions, much more than optical depth sensitivity, so the aggregation process that generates Level 3 data tends to combine results of considerably varying uncertainty.  

Within the MISR Level 2 Aerosol product, the parameter RegBestEstimateSpectralOptDepthFraction contains five sub-fields: Fraction optical depth "small," "medium," and "large," and fraction optical depth spherical and non-spherical (DPS, Rev. S, p.164). The cutoff between "small" and "medium" is 0.35 microns, and between "medium" and "large" is 0.70 microns (MISR Aerosol ATBD, Rev. G, Section 3.5.10.2, p. 67). 

 We recently published an analysis of MISR Standard Product aerosol-type data quality:

Kahn, R. A., and B. J. Gaitley, 2015. An analysis of global aerosol type as retrieved by MISR. J. Geophys. Res. Atmos. 120, doi:10.1002/2015JD023322.

The paper can be downloaded from:

Note especially the discussion in Sections 3.2 and 3.5, and the related Supplemental Material.  Another paper that might be of interest here is:

Dey, S., and L. Di Girolamo (2010), A climatology of aerosol optical and microphysical properties over the Indian subcontinent from 9 years (2000–2008) of Multiangle Imaging Spectroradiometer (MISR) data, J. Geophys. Res., 115, D15204, doi:10.1029/2009JD013395.

Be well.  Ralph

Check my publications. There is one in IEEE in 2010 that my be of help

the only study I could find that measured Ventilation during walking (study with only 1 subject!) gives the following values: walking at 3 mph: 1.3 m3/h and walking at 5 mph: 1.6 m3/h.

Seems that only a very small number of studies measured ventilation in a direct way while walking, but that the results are comparable.

Bas de Geus

Normally, when we have concentration and need to express it as flux, we have to multiply with speed.  You have to do the contrary process which all preceded answers just clearly suggested.

kind thanks for the answers to both of you. 

Hi Ritanjali,

If I am getting you correctly, you want some MATLAB code which can download MOD04_L2 product (granule) from web or ftp (as per choice) according to your region of interest. If it is so, I can give you my matlab code modified for your purpose. We don't have any information about lat/lon from the file name (MOD04_L2) but L2 file name contain information about UTC time, which is more or less same for a particular location (10-15 min difference depending on location, check it out !! I am not sure !!) So you have to sort out this UTC problem for your particular use.........

Hope it solves your problem !!! :)

Let me know if you face any problem with the code.

Thanks

Amit

Hi Waqar,

The uncertainties for each PAH species should be determined as part of your analytical method. Presumably you have quantified your PAHs using some GC/MS variant so there will be plenty of literature out there about how different groups have calculated uncertainty. The USEPA would also likely have a guide for quantifying uncertainty for the analysis of PAHs because there is a standard method. Your analytical method should also produce MDLs which can be used to calculate uncertainties for those samples below the MDL. I would highly recommend reading: 

which should give you an idea how to treat your data. To answer your other question, depending on how your uncertainty is calculated, you may have one value for each PAH, or you may have a different value for each PAH in each sample.

A few things appear a bit problematic with your wider study. First, 52 samples is quite low for a source apportionment study. Typically you would want more than 100 samples. Obviously sampling for longer may not be possible all the time, but the small number of samples could cause problems. More concerning for me is your attempt to apportion PAHs. I know in the literature this is widely reported, but care should be taken before you embark on this. I recommend reading: 

Galarneau, E. 2008. Review: source specificity and atmospheric processing of airborne PAHs: implications for source apportionment. Atmospheric Environment, 42: 8139-8149.

This paper highlights a number of problems with trying to apportion PAHs, most notable of which is that PAHs do not satisfy the most basic "rules" of receptor modelling. The arguments against trying to apportion PAHs are well-presented in the paper and may convince you to try using your data another way.

I hope this information helps and good luck with your work.

Travis

If you want to use the spatial-temporal model with observations from 30 monitoring stations to predict the concentration of pollutants at other location and at present or future time, then a state-space model based on Kalman filtering method can be useful. There are a number of packages in R or Matlab to do this.

EXTINCTION = SCATTERING + ABSORPTION

what you write is the SINLE SCATTERING ALBEDO (SSA)

Second of all the AOD is the logarithm of the ratio of transmitted light intensity versus initial intensity

and the AOD is a sum of scattering and absorption by aerosol AND by the air molecules (RAYLEIGH-scattering); the RAYLEIGH scattering is subtracted

And at certain wavelengths there is additional attenuation of light by absorption by trace-gases like NO2 and ozone and even water vapour

Please consult a textbook such as Iqbal

Probably, there are many works related to your question in the JQSRT, some of them by M. Mischenko et al. (http://www.giss.nasa.gov/staff/mmishchenko/mishchenko.html). Also, the Amsterdam database is a database of the scattering matrices and optical properties of aerosol and hydrosol particles cited in several articles (http://www.iaa.es/scattering/amsterdam/index.html).

Dear Sascha,

please have a look at:

Rate Coefficients for the Gas-Phase Reaction of OH Radicals with Selected Dihydroxybenzenes and Benzoquinones

Olariu, R. I., Barnes, I., Becker, K. H. and Klotz, B.

Int. J. Chem. Kinet. 32 (2000) 696-702

Also SOA formation has been studied by Cecile Coeur-Tourneur, however, I have to search for her publication.

Cheers,

Peter

Hello Candace

Nitrocellulose wood lacquer consist of many organic solvents which are associated with some health problems especially respiratory impairments in workers occupationally exposed to them.

You can surf the web searching for health effects of organic solvents that are ingredients of your lacquer of interest. For instance. formaldehyde.

Dear Maria,

Band 1 of the Landsat 8 Operational Land Imager (OLI) instrument is labeled "Coastal aerosol", but that does not mean that this channel, on its own, provides any information on aerosols: it is just a measurement in the "deep blue" spectral region that can be used, in conjunction with other channels, to retrieve information on aerosols. The band label is very poorly chosen, though scattering of solar radiation by aerosols in the atmosphere does indeed increase significantly when the wavelength of the radiation shortens.

You should consult books and articles on the characterization of atmospheric aerosols based on the inversion of radiation transfer models against multispectral measurements for input on how to perform this task and retrieve information on aerosols.

For an introduction to these concepts and techniques, consult

Jacqueline Lenoble (Editor) (1986) Radiative Transfer in Scattering and Absorbing Atmospheres.

Jacqueline Lenoble (1993) Atmospheric Radiative Transfer, Deepak Publisher.

Thomas and Stamnes (2002) Radiative Transfer in the Atmosphere and Ocean, Cambridge University Press.

K. N. Liou (2002) An Introduction to Atmospheric Radiation, Volume 84, Second Edition, Academic Press.

A somewhat simpler approach to aerosol characterization is to estimate the Ångström exponent from two spectral bands, and then relate that value to the aerosol type. See, for instance,

Alternatively, you should collaborate with a research group that can retrieve this information for you and provide you directly with aerosol products (rather than just radiance measurements at the entrance of satellite instruments).

Cheers, Michel.

Much to my surprise (and yours?) there is only a bit of accesible information on this item. You can start with this document, as far as you haven't discovered it yourself: http://www.advancetecllc.com/pdf/ATEC-WP-Air-Shower-Effectiveness-D1005-001.pdf

And another one: http://cleanroom-construction.net/whitepapers/effectiveness-of-air-showers/

The first report refers a.o. to Liberty Industries. On their site they sell a set of test reports: http://catalog.liberty-ind.com/item/air-showers/air-shower-test-reports/astr-1?

There is more information on cleanroom testing according to ISO 14644 series from ISO/TC 209, referring to cleanroom classification. This technical committee might be another starting point: http://www.iest.org/Portals/36/docs/Journal/TechTalk/Ensor_ISO_TechTalk.pdf

Well, it's just a start I guess, hopefully you'll find more.

For a basic understanding of the influence of the atmospheric aerosol on the thermal forcing at the aerosol level, one can treat aerosols as clouds of particulate matter (hereafter aerosol-clouds). However, aerosol-clouds have very different optical properties vis-a-vis the water-clouds. Hence, radiative forcing of the aerosol-clouds is quite different from those of water-clouds. In fact, aerosol-clouds absorb a lot more solar as compared to water-clouds; therefore vertical placement of aerosol clouds makes a huge impact on the air temperature and short wave transmitted through the cloud. One finds that sometimes aerosols in the atmosphere can absorb enough solar radiation as to burn off the surrounding or mixed in clouds. If one can get aerosol-optical properties, computing radiative effects of aerosol-clouds is a straight forward calculation.  As stated in prior responses, the aerosol-cloud interaction effect can vary significantly based on the state of the atmosphere, its water vapor content, its clouds, and the surface of the earth beneath. The specific outcome in a specific situation must be obtained by calculations in which aerosols are present at different heights of interest together with realistic aerosol optical properties.

@Rosaline

After your last entry I understand much better what you are after. However, the area of heterogeneous conversion of NOx is a very tricky one. My main experience is the interaction with walls of smog chambers. It appears that the presence of a surface water layer is essential. However, I think that up till today there is not a good kinetic description for the interconversions taking place in such a rather well-defined environment. A amin issue is the formation of nitrous acid. This is a key compound for starting the photochemical cycle. Of course this is of more importance at sites where photochemistry occurs

 There is also the interaction of nitric (and sulfuric) acid with seasalt, but this reaction is fast and occurs already in the aerosol in the air.

By the way did you have a look at the literature on the heterogeneous / surface reactions of the compounds?

ISORROPIA only provides equilibria but the question for you obviously is how fast?

Dear Manish, I recommend you to read to my colleague Gustavo Delgado I give you the link http://www.lamjol.info/index.php/UNIVERSITAS  the suggest use the Maple 13 programm.

Oliver,

Thanks for the comment and the reference  - we will look at it. We are using the M100/110R Rotating MOUDI Impactor - it is the old rotating MOUDI impactor. The study we are conducting focuses on the analysis of mine dust and investigation of the percent of quartz for each size fraction. We are using coated substrates 

Depends on what you are interested in. Do you want to distinguish differences in effects of compounds on a biological system and determine relative toxicity. If so I would use a solvent that extracts most of the compounds and that would be a mixture of Acetone/Hexane 1:1 ratio which extracts polar and nonpolar compounds. This is also used to determine responses of cells to exposure of compounds adsorbed to PM. However, if you know something about your extract and would like to do something more specific you could do a serial extraction first with hexane alone and then Acetone. Then you can evaluate what ever response or even further fractionation with HPLC (or other methods). There are a couple of other strategies but again it depends on the question you ask. 

Thanks for your answer, Avi!

I managed to get the instrument run. The problem was that there were some air bubbles in the butanol line which prevented a proper function. I removed them by gently pressing the silicon tubing which runs from the butanol bottle to the instrument. Now everything's working perfectly.

Cheers,

Martin

"Based on a combination of global aerosol models and observation-based methods, the best radiative effect estimate of the aerosol–radiation interaction in Assessment Report 5 (AR5) is –0.35 (–0.85 to +0.15) W.m–2 (global annual mean between 1750 and 2011 http://www.climatechange2013.org/images/report/WG1AR5_Chapter08_FINAL.pdf page 24). As far as I understand, this is an estimate for all 7 aerosols conisdered in AR5 without distinction between natural and anthropogenic.

For the major natural global aerosol, Mineral Dust, the global mean radiative forcing in AR5 is -0.10 (-0.30 +0.10) W.m-2. The RE of other natural aerosols such as sea-salt was not provided as such in AR5 as far as I know.

You can also obtain more information on the aerosol optical characteristics at SGP from the direst sun and inversion products of the AERONET site there, referred to as Cart_site:

I agree with Deborah. The attached reading is excellent. I will also like to add that contemporary focus on the trait theory of leadership has substantially declined in today's complex world. The stress is rather more on transformational leadership and situational leadership.

It is indeed a difficult question with no universal answer. Over urban areas the mixing layer (typically 0.5 to 2 km high) might force convection so that the aerosol concentration is relatively constant over height in that layer. But these processes are very dynamic, and typically change rapidly over short distances and  time periods, even during a single day.

I guess you would have to run a chemical transport model, such as WRF-Chem, to obtain a precise time-dependent answer for your location, but it is obviously not an easy task...

Hi - yes that's basically what I meant, although I'd use all pairs of data with a mile between, rather than splitting the data up into "whole mile" chunks. For instance, a mile has passed between 0 and 10 min, as you say, but a mile has also passed between 1 and 13 min (taking 12 min), etc. I can't speak for how the standard is defined as I'm not familiar with it, but that's how I'd do it.

Dear Dr. Hubert, this is an excellent research paper link which you have provided by Vanhellemont & Ruddick. Precisely what I have been looking for. I have started following your updates. I see that you have also done some work in 'ocean color remote sensing'. Are you still associated with the coastal water study in Hanoi? Thank you so much for your pertinent answer. 

Dear Dr. Mauricio, you have a very keen sense of observation. This is a brilliant idea. Thank you for this first-rate research paper. Those guys in Scripps have been doing some great quality research. I am deeply thankful for your efforts in putting together these significant research papers related to S.California bight and Chile's river plumes. Have you also been doing your research in Chile area?

These are some of the finest answers I've received so far for my question. Since I am just a budding researcher my motivation has always come from being able to observe things by 'standing on the shoulders of giants' like you. Therefore I will be indebted if you have any advice, suggestions or recommendations in order for me to do some quality research which would be beneficial for humans and mother nature alike. Right now I'm at the stage of collecting and examining closely relevant research papers related to remote sensing of coastal regions, all the possible threats which might range from small-scale sand erosion to mighty coastal hazards and the prospect of planning mitigation measures along with analyzing pre and post disaster scenarios for coastal resilience. Conservation of biodiversity in these regions is another area of concern for me.

Please have a look to the attached paper.

Best regards

Uwe

Hi,

your question is too general to get a detailed answer. which instrument are you using? why do you prefer choosing only one supersaturation point and what exactly are you trying to study from it. I hope that with these details I will be able to give you a helpful answer.

Avi.

High AOD conditions are not just caused by pollution. You must also include dust storms and smoke from biomass burning. In many cases, these sources act together. This is typical of many areas in Asia, for instance. In other words, you need more than just AOD to determine the signature of pollution.

From simple considerations TSPM: Stands for Total Suspended Particulate Matter and would essentially be the concentration one would get when a high-volume bulk sampling is done on a filter substrate.

RSPM is that fraction of TSPM which is readily inhaled by humans through their respiratory system and in general, considered as particulate matter with their diameter (aerodynamic) less than 2.5 micrometers. Larger particles would be filtered in the nasal duct.

PM10 is a subset of TSPM and stands for particulate matter with aerodynamic diameter less than 10 micrometer.

However, these are all some rules for convenience; in practice, most of the air-borne particles are non-spherical and it is difficult to assign a diameter. Further aerodynamic diameter is also a mathematical concept (an imaginary sphere having unit bulk-density and the same settling speed as that of the actual particle) and hence is related through the density (mass per unit volume) of the particle.

Hi,

you may and probably should use PSL spheres as a core material . You will need to generate aerosols as people usually do (atomizer-->diffusion drier-->neutralizer) and then size select the PSL's (to get rid of small particles that are always found for some reason between 0-100nm). A simple way for coating PSL is passing the mono-dispersed aerosol flow through vapors of your organic compound. you generate the vapors by heating up the organic compound in a 3 neck Erlenmeyer, one neck is inlet, the second is useful for temperature measurement, the third one is the outlet of course. careful control on the temperature and aerosol flow is required in order to get repeatability, but it is completely feasible.

People used to prepare core/shell aerosols in my group not long time ago so if you need further help or wish to discuss about it feel free and send me an email. your FAPA-MS is very interesting , good luck with it.

Avi.

The determination of optical parameters (absorption coefficient, scattering coefficient, extinction coeffitient, SSA) as a function of wavelength has been used as a way to distinguish between various aerosol types. To investigate this wavelength dependence, it is calculated the Angstrom exponent, which is defined as the negative slope of the logarithm of the optical paramenter as a function of wavelength

The scattering and absorption Angstrom exponents are used as qualitative indicators of particle size and chemical composition. Smaller scattering Angstrom exponents are associated with larger particles and higher scattering Angstrom exponents are associated with smaller particles. Also, specific values of the absorption Angstrom exponents are characteristic of the chemical specie. For example, 1 for urban aerosol, higer than 1 for carbonaceous particles resulting from coal combustion, etc...

The wavelength dependence of SSA is also influenced by various aerosol species. For example, for urban-industrial aerosols and biomass burning, SSA decreases with increasing wavelength, whereas for desert dust, SSA increases with increasing wavelength. Some dust particles are strong absorbers, and the increase of absorption together with the decrease of scattering can also contribute to the change of the slope of SSA from positive to negative.

You can see, for example:

Mogo, S., Cachorro, V. E., Lopez, J. F., Montilla, E., Torres, B., Rodríguez, E., Bennouna, Y., and de Frutos, A. M.: In situ measurements of aerosol optical properties and number size distributions in a coastal region of Norway during the summer of 2008, Atmos. Chem. Phys., 12, 5841-5857, doi:10.5194/acp-12-5841-2012, 2012.

Virkkula, A., Backman, J., Aalto, P. P., Hulkkonen, M., Riuttanen, L., Nieminen, T., dal Maso, M., Sogacheva, L., de Leeuw, G., and Kulmala, M.: Seasonal cycle, size dependencies, and source analyses of aerosol optical properties at the SMEAR II measurement station in Hyytiälä, Finland, Atmos. Chem. Phys., 11, 4445-4468, doi:10.5194/acp-11-4445-2011, 2011.

Dubovik, O., Holben, B., Eck, T., Smirnov, A., Kaufman, Y., King, M., Tanré, D., and Slutsker, I.: Variability of absorption and optical properties of key aerosol types observed in worldwide locations, J. Atmos. Sci., 59, 590–608, 2002.

Hello Luis, I believe we have met once. I think this is a very good question. EPA has been considering this for many years now. I am uncertain about the direction they will go. The strongest evidence for a health effect appears to come from the toxicology literature. However, EPA makes its decisions based on a wider range of evidence, including the epidemiological literature. We know that such epidemiological data is challenging to collect for ultrafines since their concentrations are much more variable in time and space than fine particulates (PM2.5). Such monitoring networks for ultrafines are simply not well established in the United States, which means that the epidemiological studies necessary to support an ultrafine PM standard are quite limited and would need to come from other parts of the world, particularly the UK or other countries in continental Europe. Another fact that is hard to dismiss is the recent review of the evidence of health effects of ultrafine particles from the Health Effects Institute. This came to a fairly weak conclusion and argued that more evidence on ultrafine particles is needed. It emphasized the need for epidemiological evidence, as I have highlighted here. You might consider reading through the HEI review if you have not already. This is available on their website at http://pubs.healtheffects.org/view.php?id=394. I hope this answer is helpful to you.

Added to what Oliver has raised, the sizes can vary depending on the ambient conditions like relative humidity which in turn is dependent on chemical composition.

Thank you for such a detailed explanation!

Let me know if u need help

There are a number of labs or companies that offer such tests as a service, e.g. IBR Inc. in Grass Lake, MI (USA) or their subsidiary IBR (UK) Ltd., fiatec GmbH in Mainleus (Germany), Labor Ilgen - Service für Filtration und Separation in Krostitz (Germany), Karpov Institute of Physical Chemistry - ISTC in Moscow (Russia) and others. Unfortunately all of these are quite far from India and I am personally not familiar with others that are nearer where you are.

There are several commercially available air ion counters, most based on the Gerdien tube. Do you have a calibrated air ion counter? Are you planning on making your own? The expected number of ion pairs can be calculated from the definition of the Roentgen. To measure the Roentgen you will need a free air ionization chamber. A practical size of a free air ionization chamber is limited to gamma energies less than 1 MeV.