[PPT] - Vladimir Bogillo Department of Antarctic Geology and Geoecology PowerPoint Presentation

SLIDE 1

Transboundary Transport of Atmospheric Aerosols and POPs from Ukraine Aerosols and POPs from Ukraine, Adsorption Thermodynamics and Reaction Kinetics of VOCs on the Surface of the Kinetics of VOCs on the Surface of the Aerosol’ Components

Vladimir Bogillo

Department of Antarctic Geology and Geoecology Geoecology I nstitute of Geological Sciences National Academy of Sciences of National Academy of Sciences of Ukraine, Kiev e- mail: vbog@carrier. kiev. ua g

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Transboundary transport of aerosols from Ukraine after Chernobyl’ incident (137Cs)

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Content of first part

Transport of dust to Central Europe

(W. Birmili et al., Atmos. Chem. Phys., 8, 997–1016, 2008; Hl dil J B ll i f G i 83(2) 175 206 2008) Hladil, J., Bulletin of Geosciences 83(2), 175–206, 2008)

Transport of fine particles to Southern Finland

(J V Niemi et al Atmos Chem Phys 6 5049–5066 2006) (J. V. Niemi et al., Atmos. Chem. Phys., 6, 5049–5066, 2006)

Transport of combustion aerosols to Crete Island

(J. Sciare et al, Atmos. Chem. Phys. Discuss., 8, 6949–6982, y 2008)

Transport of industrial aerosols to Israel

(Y Erel et al Environ Sci Technol 41 5198 5203 2007) (Y. Erel et al, Environ. Sci. Technol.41, 5198-5203, 2007)

Transport of PM10 to Istanbul

(T. Kindap et al, Atmos. Environ. 40, 3536–3547, 2006) ( p , , , )

Transboundary transport of POPs in Europe

(EMEP Status Report 2/2007)

Influence of aerosols and air temperature on transboundary

transport of POPs

SLIDE 4

Hydromet’s network of air-quality monitoring stations in Ukraine

SLIDE 5

Air pollutions in Ukraine

Uk i h d l d i ll ti i it f i t ti l

Ukraine has declared air pollution a priority area for international

cooperation

Since the early 1990s, the long-term trend in air pollution in Ukraine

has been positive During 1995 2002 air emissions from stationary has been positive. During 1995–2002, air emissions from stationary sources decreased by a factor of 1.4

An inventory in 2002–2003 of the POPs stored on Ukrainian territory

revealed that 19,341 t of obsolete pesticides were stored at 4,983 storage revealed that 19,341 t of obsolete pesticides were stored at 4,983 storage sites and of these sites, only 499 are well maintained, 2,871 have satisfactory storage conditions, and the rest are not maintained properly

In 2004, air emissions from leading industrial sectors were distributed

as follows: 62% from manufacturing, 37% from mining and quarrying and 1% from construction materials

In 2005, air emission from industrial sources runs up to 4449300 t

(96 5% f h i d t d 3 5% f t t) (96.5% from heavy industry and 3.5% from transport)

Emissions from mining of metals, minerals and energy-producing

materials totaled 991400 t in 2004 Donetsk oblast alone acco nts for abo t 40% of total air emissions in

Donetsk oblast alone accounts for about 40% of total air emissions in

Ukraine, followed by Dnipropetrovsk (21%) and Zaporizhzhia (6%)

blasts. The city of Mariupol, in the Donetsk oblast, has accounted for

about 5% of total emissions in Ukraine %

The cities with the highest air pollution are located in the Donetsko-

Prydniprivskyy industrial area

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Emissions of SO2, NOx and dust from power plants and electricity production Industrial air emissions of main pollutants, 2000–2003

SLIDE 7

Soils degradation and contamination in Ukraine

Still, in 2004, DDT residues were found in Donetsk, Zaporizhzhia and Kherson oblasts. A still unsolved problem is the contamination risk from more than 19,000 tons of often improperly stored obsolete pesticides. A total of 5 million hectares are contaminated. 43 military sites are registered as potentially contaminated by toxic waste.

SLIDE 8

Hotspot fire maps (FIRMS data) for the year 2004

SLIDE 9

Main sources of aerosols in Ukraine

Wind-blown dust particles emitted from eroded dry soil

surfaces of farm lands (423000 km2) ( )

Combustion particles from biomass burning on the farm

lands and forest fires

Mixed particulates (mineral, carbonaceous, sulphate and
rganic, enriched by heavy metals (Pb, Cd, Hg, Zn, Fe, Sn,

Cr, Mn, Cu) from various industrial sources (mining, quarrying, power plants, coke, metallurgy, chemical, petrochemical construction materials asphalt petrochemical, construction materials, asphalt, woodworking industry, arms production and transport

Sea-salt particles emitted from Black Azov Seas and from

Sea-salt particles emitted from Black, Azov Seas and from numerous saline lakes in Southern Ukraine

Biogenic and secondary particles from Carpathian,

Biogenic and secondary particles from Carpathian, Polessya, Crimea

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Transport of dust to Central Europe Transport of dust to Central Europe

Wind-blown dust particles emitted from dry soil surfaces

contribute considerably to the global aerosol mass and

ptical thickness as well as to particle concentrations
ptical thickness, as well as to particle concentrations

near the surface

Current estimates of annual global emission of dust

ti l th t il bl f l t t particles that are available for long-range transport vary between 1000 and 2000 Tg (Zender et al., 2004)

Frequent transport of dust plumes from the Sahara, the

q p p , largest dust source worldwide, towards Europe can be

bserved frequently within the free troposphere
Other sources of mineral dust aerosol include the

Other sources of mineral dust aerosol include the Arabian Peninsula, the Gobi and Taklamakan deserts in Asia, and the Australian and South American deserts

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Human activities can modify dust emissions from soils by

h i th il bilit f fi ti l th h changing the availability of fine particles, e.g., through destruction of soil crusts and removal of vegetation in semi-arid regions. The total amount of soil dust emission g from such anthropogenic influence are currently estimated to contribute up to 20% of the total dust emissions (Solomon et al 2007) (Solomon et al., 2007)

The total area of the Ukraine is 603 700 km2, 70% of which

are used as farm lands. The Southern Ukraine has been characterized as a “steppe” zone. The human impact has almost completely removed the former native forests and steppe lands and created large scale agricultural units In steppe lands, and created large-scale agricultural units. In the wide “loess” plains the very fertile black earth (Chernozem) has formed, which belongs to the most fertile soils worldwide. Due to the intensive agricultural development, the soil has become prone to wind erosion and in fact wind has been found to have eroded Ukrainian and in fact, wind has been found to have eroded Ukrainian soils over an area of 220 000 km2

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A comparison of the climate of the past (ca. 100 years ago) ith th li t f t d h th t th t it f th with the climate of today shows that the territory of the Ukraine has become arid due to human activities. Consequently, wind erosion has become wide-spread even q y, p in areas formerly unaffected by wind erosion Meteorological statistics over the past 40 years indicated the frequency of dust storms was found to be 3–5 per year in the steppe zone, with an average duration of 8–17 h i i i i i Dust storms in the Ukraine are typically associated with wind speeds of 20 m s−1 and more with Chernozemic soils being the most susceptible to wind erosion being the most susceptible to wind erosion During dust storms, these soils can lose 70 t of soil per ha and hour

Dust transport from the Ukraine into Central Europe is an

unusual feature, and has not been documented in the literature

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Uncovered, active fields of eolian sand dunes with grass and limited shrub vegetation; surroundings of Velyki Kopani village, Kherson region

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Macroscopic appearance of the sediment (24 April, 2007) A -Nízké Tatry Mts (Slovak R.), B - Krkonoše Mts. (Czech R.), C - Krušné hory Mts. (Czech R.), D - Town of Púchov (Slovak R.), E -Town of Brno, F - Town of Blansko

SLIDE 15

Dust source activation on 23 March 11:00 UTC over the Southern Ukraine (SEVERI on board the MSG satellite)

SLIDE 16

The MODIS-Aqua composite image of Southern Ukraine

n 23 March 2007, 10:50 UTC

Kakhovskaya lake

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On 23 March, meteorological observations in the southern and eastern

area around the Kahkova Reservoir report average wind speeds up to area around the Kahkova Reservoir report average wind speeds up to 15 m s−1 and wind gusts up to 25 m s−1 and confirm “observations of atmospheric dust”

It is likely that these unusually high surface wind speeds in combination

It is likely that these unusually high surface wind speeds in combination with a preceding drought period of two weeks as well as the lack of vegetation in March led to the high dust emission rates

On 23 and 24 March 2007 the synoptic situation over Europe was
On 23 and 24 March 2007 the synoptic situation over Europe was

governed by a high-low dipole pattern due to a low pressure area over the Mediterranean Sea and a high pressure region built up by a permanent anticyclone located over Fennoscandinavia and an permanent anticyclone located over Fennoscandinavia and an anticyclone located over South Russia

The eastward moving Mediterranean depression on the one side and the

persistent high pressure area on the other side forced an increasing persistent high pressure area on the other side forced an increasing pressure gradient over the Black Sea and Southern Ukraine, generating a low-level jet into Central Europe

The low level jet effected the transport of a dry and subsiding air from
The low-level jet effected the transport of a dry and subsiding air from

the Black Sea area to Central Europe along a narrow corridor and reaches Germany on 24 March

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Geographic map with three particle trajectories originating at the same site (48°N, 33°E) from different heights

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Charts of sealevel pressure (hPa) and horizontal surface wind speeds in Beaufort (colour code) on 23 and 24 March 2007, 12:00 UTC respectively 12:00 UTC respectively

Superposition of back trajectories originating on 24 March 2007 at 20 receptor sites in Germany

Time series of PM10 mass concentrations at a number of selected air quality monitoring stations in Slovakia, the Czech Republic, Poland, and Germany

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Dust concentration and its altitude variation Dust concentration and its altitude variation

Hourly PM10 mass concentrations reached 1400 µg m−3 in Slovakia and

1200 µg m−3 in Poland. The maximum hourly value in Germany was 640 3 h l PM l l t i ll d 20

−3 A

640 µgm−3, where rural PM10 levels are typically around 20 µg m−3. As a result of the dust event the legal daily limit value of PM10 (EU First Air Quality Daughter Directive (1999/30/EC)) was exceeded over an area spanning several EU member states area spanning several EU member states

Total dust load is about 3 Tg and the Total dust load is about 3 Tg and the load based on PM10 – related mass is 60 Gg Gg

Vertical profile of the volume extinction coefficient of the aerosol Vertical profile of the volume extinction coefficient of the aerosol as retrieved from Lidar observations at 0.532 µm wavelength at Leipzig, on 24 March 2007, 12:33–13:44 UTC

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Mineralogical and Chemical Composition of the dust

Besides the preferentially entrained and delivered quartz, the sediment

contains also perthitic feldspar, chlorite and chloritoids, and notably low amounts of mica, clay minerals and carbonate amounts of mica, clay minerals and carbonate

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A plot of lead isotope ratios. Based on published data, an attempt was made to separate the North African Middle East trendline from the made to separate the North African–Middle East trendline from the Central–East European signatures

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The study revealed that the deposited sediment is characterized by

polydisperse and multimodal particle size distributions and consists polydisperse and multimodal particle-size distributions and consists predominantly of angular to subrounded quartz particles of silt size. Only a few percent of coarser and finer material are contained

Among the major element characteristics, the Na2O/K2O, CaO/MgO

and MgO/Fe2O3 ratios are very close to those obtained for the upper continental crust

In minor and trace elements, the Hf/Sc, Zr/Hf, Th/U ratios are only

slightly higher than those of the most common UCC or sedimentary materials materials

The Pb isotope signatures correspond to a considerably lithogenic

characteristic; only the Prague sample shows a certain overprint probably influenced by EU-type petrol combustion

The element content does not contradict the supposed source based on

meteorological observations, i.e., from surface argillaceous and sandy g , , g y soils east of Kherson, Ukraine

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Transport of fine particles to Southern Finland p p

The composition and mass concentrations of fine aerosol particles

(PM2.5) in clean background areas are strongly affected by long-range t t transport

During transport and aging, particles of different origin may change

their properties due to coagulation and cloud processes as well as due to reactions with gases via various heterogeneous pathways

Differences in sources and in meteorological conditions may strongly

affect composition, mixing state, concentration and size of different particle types observed

The clean background areas in Finland are especially favorable for

investigation of the properties of aged, long-range transported aerosols g p p g g g p with clearly different origin

The aerosol samples were collected at a rural background site in

Southern Finland in May 2004 during pollution episode (PM1 ~ 16 µg y g p p (

1

µg m−3, backward air mass trajectories from south-east), intermediate period (PM1 ~ 5 µg m−3, backtrajectories from north-east) and clean period (PM1 ~ 2 µg m−3, backtrajectories from northwest/north)

1

SLIDE 25

Backward air mass trajectories arriving at 250 m level to H ti l d i th i li i d i M 2004 Hyytiala during the six sampling periods in May 2004

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TEM images of different particle types from PM0.2−1 sample 7 collected during the pollution episode; (a) tar ball (b) soot and (c) Si-rich fly ash during the pollution episode; (a) tar ball, (b) soot and (c) Si-rich fly ash mixed with (ammonium)sulphates containing material. The rest of the particles were classified as “(ammonium) sulphates and their mixtures with C K soot with C, K, soot

SLIDE 27

Particle group

Elemental characteristics

Tar balls

Abundant C with minor S, often minor K Tar balls Abundant C with minor S, often minor K

Soot

Abundant C, often minor S, K and/or Si

(Ammonium)sulphates and
their mixtures with C K
their mixtures with C, K

and/or different inclusions S with variable amounts of C and/or (usually minor) K

Silicates

Abundant Si usually with Al variable

Silicates

Abundant Si, usually with Al, variable minor Fe, Ca, K, Mg, Na, Ti,and/or S

Metal oxides/hydroxides

Abundant Mn, Fe, Zn and/or Pb C /M b t l h t Ca/Mg carbonates, sulphates and/or nitrates Abundant Ca with C and/or S, sometimes with abundant Mg and/or minor Si

Sea salts

Abundant Na, variable Cl and S, minor Mg, K and Ca

Porous Na-rich particles

Abundant Na with S and K, noMg and Ca

Biological particles

Abundant C, usually minor K and/or P

C-rich fragments

Abundant C g

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The major particle types in PM0.2−1 samples were soot and

(ammonium)sulphates and their mixtures with variable amounts of C, K t d/ th i l i N b ti f th t K, soot and/or other inclusions. Number proportions of those two particle groups in PM0.2−1 samples were 0 – 12% and 83 – 97%, respectively D i h ll i i d h i f C i h i l

During the pollution episode, the proportion of Ca-rich particles was

very high (26 – 48%) in the PM1−3.3 and PM3.3−11 samples, while the PM0.2−1 and PM1−3.3 samples contained elevated proportions of silicates (22 33%) t l id /h d id (1 9%) d t b ll (1 4%) (22 – 33%), metal oxides/hydroxides (1 – 9%) and tar balls (1 – 4%). These aerosols originated mainly from polluted areas of Eastern Europe, and some open biomass burning smoke was also brought by long range transport long-range transport

During the clean period, when air masses arrived from the Arctic

Ocean, PM1−3.3 samples contained mainly sea salt particles (67 – 89%) ith i bl t f Cl b tit ti ( i l b NO ) with a variable rate of Cl- substitution (mainly by NO3

)
During the intermediate period, the PM1−3.3 sample contained porous

(sponge-like) Na-rich particles (35%) with abundant S, K and O. They i ht i i t f th b i f d l t f might originate from the burning of wood pulp wastes of paper

industry. The proportion of biological particles and C-rich fragments

(probably also biological origin) were highest in the PM3.3−11 samples (0 81% d 0 22% i l ) – 81% and 0 – 22%, respectively)

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Transport of combustion aerosols to Crete Island

Long-term (5-yr) measurements of carbonaceous (BC, OC) aerosols

were reported in the Mediterranean Basin (Crete Island)

Their seasonal trends demonstrate two peaks (early spring and

p ( y p g summer) corresponding to long-range transported biomass burning aerosols originating from apart to agriculture (post-harvest wheat residual) waste burning in the countries surrounding the Black Sea (i.e. at 1000 2000km upwind of Crete) at 1000–2000km upwind of Crete)

The contribution of biomass burning to the concentrations of BC and

OC have been shown to be rather small on a yearly basis (20 and 14%, respectively) but could be significant for some months (34 and 32% of respectively) but could be significant for some months (34 and 32% of BC and OC, respectively, for the month of August) and are expected to present a strong seasonal/interannual variability

Noteworthy, these biomass burning aerosols are expected to have an

y, g p even more important impact at the emission sources (mainly in Ukraine and surroundings countries) as observed from Aerosol Optical Depth measurements performed in Moldova A thi t h th l t i lt l d i E d th

As this country has the largest agriculture land area in Europe and the

highest European values for energy-crop potential, agriculture (wheat crop residual) waste burning in this region is likely to represent a non- negligible source of combustion aerosols in the near future over Europe negligible source of combustion aerosols in the near future over Europe

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Hotspot fire maps (FIRMS data) for the year 2004

SLIDE 31

Yearly-based wind direction occurrences for the 4 sectors (North West East and South) at Finokalia station in Crete (North, West, East, and South) at Finokalia station in Crete

Isl. M.O.Y stands for Month Of the Year

SLIDE 32

Seasonal variations of iron concentration in dust aerosols and light absorption measurements obtained from aethalometer (babs (AETHALO)) corrected and uncorrected from the light absorption due to dust aerosols (babs (Fe2O3))

Weighed seasonal variations of BC concentrations derived from two thermo-optical (IMPROVE and NIOSH) one optical (AETHALO) and one thermal (2-STEP) protocol. N lt t i ( K) t ti th f th fi d ( 1 5 ) Non-sea salt potassium (nss-K) concentrations are those from the fine mode (<1.5 µm)

SLIDE 33

Temporal variations of monthly mean BC, OC and nss-K concentrations in Crete Island concentrations in Crete Island

SLIDE 34

Transport of mineral particles to Israel

During the summer months aerosols collected in Israel are

highly polluted by metals (EFNi = 120, EFCu = 320, EFZn = g y p y (

Ni

,

Cu

,

Zn

30, EFPb = 540)

The fraction of European Pb of mostly industrial sources is

61% (21% in Jerusalem), and the fraction of European Cu, Zn, Ni, and aerosols should be on the same order

Whenever a steep pressure gradient is built between the

barometric trough originating from the Persian Gulf and the subtropical ridge along the African coast stronger the subtropical ridge along the African coast, stronger westerly winds and cooler temperatures (deep Persian Trough) prevail over the Middle East, and higher amounts g ) p , g

f European pollution are observed in the atmosphere

SLIDE 35

208Pb/206Pb and 206Pb/207Pb values of the sampled aerosols

The values of alkyl Pb emitted in Israel are from soil samples The values of alkyl-Pb emitted in Israel are from soil samples collected near major roads

SLIDE 36

All samples collected in the current study contain high concentrations

f Pb, Cu, Zn, and Ni, and the enrichment factors (EF )

(metal/Al)smp/(metal/Al)UC); UC ) upper continental crust) vary between 64 and 945, 44 and 555, 0.9 and 66, and 1.8 and 275, respectively

The current study demonstrates how changes in synoptic conditions are responsible for changes in sources of pollution and how the impact of emissions in one part of the World affects air quality in another part.

SLIDE 37

Transport of PM10 to Turkey

Ground-based aerosol optical measurements were conducted within the

framework of the Aerosol Robotic Network (AERONET) program at the IMS-METU site at Erdemli (36°33′N, 34°15′E) along the Turkish coast ( ) g

f the northeastern Mediterranean from January 2000 to June 2001
Dust storms affecting the region primarily originate from the central

g g p y g Sahara in spring, the eastern Sahara in summer, and the Middle East/Arabian peninsula in autumn. Summer and autumn dust intrusions usually occurred at higher altitudes (above 700 hPa), whereas urban- usually occurred at higher altitudes (above 700 hPa), whereas urban industrial aerosols from the north over the Balkan region, Ukraine, and Anatolia were transported to the region at lower altitudes Si l t d I t b l PM10 t 50% h i th i

Simulated Istanbul PM10 response to 50% change in anthropogenic

emissions during 5–12 January 2002

SLIDE 38

Spatial distribution of calculated mean annual dust suspension flux of different particle size in 2005: (a) PM ; suspension flux of different particle size in 2005: (a) – PM2.5; (b) – PM10; (c) – PM20, µg/m2/s

a b c

EMEP, 2005

SLIDE 39

Spatial distribution of annual averages of specific l f E aerosol surface over Europe

SLIDE 40

Absolute contribution of European countries to lead transboundary transport in Europe in 2005 and relative fraction of national emissions in p p f f this contribution, t/y

400 500 f Pb, t/y 80 100 % 200 300 400 dary transport of 40 60 80 Pb emissions, Transboundary transport 100

khstan Greece Turkey Poland

rtugal

Spain Italy kistan mania eration kraine enegro ngdom France ulgaria elgium rmany

vakia

kistan FYR of govina rlands public nistan stonia elarus ungary yzstan lbania erland inland Latvia Croatia

venia

rbaijan weden Austria reland eorgia nmark huania Moldov

rway

Cyprus menia Malta mbourg celand

naco

Transbound 20 Fraction of Fraction of emissions

Kazak G T P Po Uzbek Rom Russian_Fede Uk Serbia&Monte United_Kin F Bu Be Ger Slo Taji The F Bosnia_Herzeg Nether Czech_Re Turkme Es Be Hu Kyrgy A Switze F C Slo Azer Sw A I Ge Den Lith Republic_of_M No C Arm Luxem Ic Mo

Absolute contribution of European countries to mercury transboundary transport in Europe in 2005 and relative fraction of national emissions in this contribution, t/y

16 20

f Hg, t/y

80 100

ns, %

4 8 12 16

y e y e

a

a a a a a a a a d a a a d

nsboundary transport o

20 40 60 80 Fraction of Hg emissio Transboundary transport Fraction of emissions

Turkey Poland Greece Kazakhstan RussianFederation Spain Italy France UnitedKingdom Ukraine Serbia&Montenegro Portugal Hungary CzechRepublic Romania Bulgaria Slovakia Germany Belgium BosniaHerzegovina The_FYR_of_Macedonia Cyprus Denmark Azerbaijan Switzerland Netherlands Austria Finland Sweden Croatia Malta Norway Slovenia Belarus Estonia Lithuania Ireland Luxembourg Georgia RepublicofMoldova Albania Armenia Iceland Monaco Latvia

Tran

SLIDE 41

SLIDE 42

Spatial distribution of emissions from Ukraine in 2005

Trends in mean concentrations of i i 2000 i /

3

particles since 2000. Units: µg/m3

SLIDE 43

Transboundary Fluxes in 2005 y

xidized sulphur deposition
xidized nitrogen deposition reduced nitrogen deposition
d ed su p u depos
d ed
ge

depos

educed
ge

depos

Main contributors to PM2.5 (left) and PMcoarse (right) concentrations in Ukraine

SLIDE 44

Importance of atmospheric aerosols aerosols

Solid and liquid aerosols affect on:

bi h i l l f C O N Cl B I S P

biogeochemical cycles of C, O, N, Cl, Br, I, S, P,

As, Cd, Pb, Fe, Cu, Co, Ca, etc.

human and ecosystem health
human and ecosystem health
chemical composition of atmosphere
visibility of atmosphere
visibility of atmosphere
radiative atmospheric budget
Earth’s climate
Earth s climate

They are also carriers for transport of moderate and low-volatile persistent toxic organic atmospheric pollutants (POPs) over a long distances from their industrial and agricultural sources

SLIDE 45

Main persistent organic pollutants

Chlorinated pesticides:

p p’-DDT p,p’-DDE γ-HCH p,p DDT HCB Heptachlor

P l hl i t d dib di i

HCB

Polychlorinated dibenzo-p-dioxins: Polychlorinated dibenzofurans:

1970

Polychlorinated dibenzofurans: Polychlorinated biphenyls:

970

Polycyclic aromatic hydrocarbons:

Benzo[a]pyrene

Polybrominated diphenyl ethers:

1980

SLIDE 46

Long-range transport potential, LA, and persistence, τA, for selected POPs in air as estimated by TaPL3 model

POPs LA, km τA, h Carbon tetrachloride 498960 1443 Hexachlorobenzene 200910 3516 Hexachlorobenzene 200910 3516 3,4-Benzopyrene 493 1507 Pentachlorophenol 2554 132 Chlordane 1357 428 γ-hexachlorocyclohexane 3021 755 Heptachlor 1636 5.7 α- hexachlorocyclohexane 4473 270

SLIDE 47

Distribution of a pollutant between gaseous and an aerosol form gas

↔

part K gas

C particle C

p

+

ti l particle

What happens when a semivolatile organic (POP) encounters a

particle?

SLIDE 48

Partitioning Modes Partitioning Modes

M d f POP ti l i t ti

log log log

) (

1

RT Q Q tsp s

v

Te a N p K

−

+

Mode of POP-particle interaction

depends on the particle – Adsorption Solid particle, no

rganic liquid layer (dust

1600 log log log

p L p

p K + − = 760 log log log

m

RT f p K +

rganic liquid layer (dust,

inorganic salts) – Absorption Particle either liquid, or has substantial liquid pL

(torr): vapor pressure of the pure compound

6

10 log log log ζ

m
m

L p

MW p K + − =

liquid, or has substantial liquid layer (combustion particles, secondary organic aerosol)

POPs such as PAHs, and alkanes

pL (torr): vapor pressure of the pure compound Ns (sites/cm2): surface conc. of sorption sites atsp (m2/g): particle surface area Q1, Qv (kJ/mol): enthalpy of vaporization

primarily partition to organic or carbonaceous aerosols rather than to mineral-based aerosols

R: gas constant T (K): temperature fom: weight fraction of TSP in organic matter (om) phase MWom: mean molecular weight of the om phase z: activity coefficient

SLIDE 49

Partition Coefficient Kp: Adsorption & Absorption

)/RT Q (Q

Langmuir adsorption:

L

)/RT Q (Q tsp s p

p 1600 Te a N K

v 1−

= pressure vapor area sites, # ∝

Absorption into a liquid film:

6

m

p

760RT f K =

Absorption into a liquid film:

ti it MW fraction

rganic

∝

6

L
m

p

10 p MW γ activity press, vapor , MW

phase

rg

SLIDE 50

log Kp = mrlog Po

L + br

g

p r g L r

mr = -1 mr

1

log K

PAHs, PAHs, alkanes alkanes chlorinated chlorinated

Kp

chlorinated chlorinated

rganics
rganics

log Po

(L)

log P (L)

If b br is constant…. is constant….

r r

SLIDE 51

If absorption is important, Koa may be a better predictor of Kp p p ,

a

y p

p

those previous equations used p as the descriptor variable. we could also use Koa :

a
ct
m
m
ct
ct
m

P

K MW MW f K

12

10 ⋅ ⋅ ⋅ ⋅ = ρ ζ ζ

Koa = n-octanol-air partition coefficient fom = fraction of organic matter MWom, MWoct = molecular wt of NOM or n-octanol

m,
ct

ξom , ξoct = activity coeff. of SOC in NOM or n-octanol roct = density of n-octanol

SLIDE 52

Distribution of PCDD/F content in the environment between main environmental media in 2004 (EMEP, 2007)

Vegetation 3% Ocean 1% Air 0.1% Soil 96%

SLIDE 53

Transport of POPs in Europe (EMEP estimates, 2005)

Calculations of pollution levels of polychlorinated dibenzo(p)dioxins and

dibenzofurans (PCDD/Fs) in the EMEP region were performed for total PCDD/F toxicity with use of physical-chemical properties of “indicator y p y p p congener” 2,3,4,7,8-PeCDF

Air concentrations of PCDD/Fs

Deposition fluxes p

SLIDE 54

Depositions of PCDD/Fs to the own territory and to the rest EMEP t it d t ti l i i f E t i territory due to national emissions of European countries

700 800 900 g TEQ/y To the country Outside the country 200 300 400 500 600 700 s of PCDD/Fs, g 100 200 Ukraine Turkey eration Poland

rtugal

Italy Bulgaria France Republic ingdom enegro cedonia Spain

mania

Hungary Greece lovakia Croatia ermany erbaijan Belgium Georgia egovina Austria Belarus Armenia akhstan Albania Sweden erlands Finland Norway Ireland enmark Latvia zerland thuania lovenia Moldova Estonia Monaco Cyprus mbourg Iceland Depositions U Russian Fed P B Czech R United K rbia_and_Mont The FYR of Mac Ro H G S C Ge Aze B G Bosnia&Herze B A Kaza A S The Nethe F N De Switz Lit S Republic of M E M Luxem Ser T

SLIDE 55

Calculated air concentrations, soil concentrations and total depositions of PCDD/Fs in European countries in 2004 in comparison with emission densities

Country

CA, fg/m3 CS, TEQ/g TD, pg/m2/day ED, pg/m2/day

B l

2 5 241 8 2 6 0 5

Belarus

2.5 241.8 2.6 0.5

France

4.4 522.9 5.3 1.5

Germany

6.5 806.4 6.1 2.0

Germany

6.5 806.4 6.1 2.0

Hungary

6.6 380.4 5.5 2.2

Italy

5.0 331.2 4.9 2.9

y Poland

6.2 495.9 5.7 4.2

Moldova

4.0 226.2 2.8 0.4

Romania

4.2 248.6 3.7 1.2

Russia

1.4 106.1 1.4 0.5

Slovakia

6.7 566.0 6.0 3.7

Turkey

5.1 115.6 3.8 3.5

Uk i

6 0 277 2 4 9 4 7

Ukraine

6.0 277.2 4.9 4.7

United Kingdom

3.4 299.4 2.1 3.2

SLIDE 56

Average PCDD/F air concentrations in European countries in 2004

(red line indicates the average air concentrations over all European countries) ( g p )

12 15 g TEQ/m

3

26 3 6 9

ncentrations, fg

3

zerland edonia

rtugal

epublic elgium mbourg ulgaria ntenegr

vakia

ungary ermany Poland Ukraine Croatia rlands Greece Albania

venia

Turkey Italy govina Austria France rmenia Monaco mania rbaijan

ldova

Cyprus Georgia nmark ngdom elarus Spain huania Malta Latvia Estonia eration khstan reland weden Norway Finland celand

Air co

Switz Mace Po CzechRe Be Luxem Bu Serbia&Mon Sl Hu Ge P U C Nethe G A Sl T BosniaHerze A F Ar M Ro Aze RepublicofM C G De UnitedKin B Lith E RussianFede Kaza I Sw N F Ic

T d f PCDD/F i il i d i i i Uk i f 2005 2020 Trends of PCDD/F air, soil concentrations and emissions in Ukraine from 2005 to 2020

3 4 5 TEQ/m

2/day

6 8 10 fg TEQ/m

3

3 4 5 g TEQ/m

2/day

60 80 100 ., fg TEQ/g 1 2 2005 2007 2009 2011 2013 2015 2017 2019 Emissions, pg 2 4 Air conc., 1 2 2005 2007 2009 2011 2013 2015 2017 2019 Emissions, pg 20 40 Soil conc.

Emission of PCDD/Fs in Ukraine will be increased by about 4% and only minor reduction of air concentrations (about 4%) takes place from 2005 to 2020

SLIDE 57

Calculated air concentrations, ng/m3 (a) and deposition fluxes g/km2/y (b) of B[a]P in 2005 in comparison with fluxes, g/km2/y (b) of B[a]P in 2005 in comparison with emissions, g/km2/y (c)

a. b. c.

a. b. c.

Depositions of B[a]P to the own territory due to national emissions of European countries, t/y

50 /y Export To the country 10 20 30 40 Depositions of B[a]P, t/ Ukraine Poland Germany Spain Turkey Italy Russian Federation Romania Latvia Belarus Czech Republic Portugal Hungary erbia_and_Montenegro France Sweden Slovakia Bulgaria Belgium Finland Lithuania Estonia The Netherlands Greece Bosnia&Herzegovina Ireland Denmark United Kingdom Austria Georgia Azerbaijan Croatia Slovenia Norway Kazakhstan Albania Armenia The FYR of Macedonia Republic of Moldova Cyprus Luxembourg Switzerland Iceland Monaco S T

SLIDE 58

Spatial distribution of POPs annual emissions, g/km2/y (a), annual mean air concentrations, pg/m3 (b), and total depositions, g/km2/y (c) for 2005

PCB 28 PCB-28 a. b. c. γ-HCH HCB

SLIDE 59

Effect of bounding with aerosols and temperature on transboundary transport of POPs transboundary transport of POPs

Calculation of KP values at different temperatures

U f “i ilib i ” d d

Use of “iso-equilibrium” dependence:

∆Hij = ∆Gij(Tis) + Tis∆Sij; -2.3RTlog Kij = a∆Hij + b

j j j j j

∆HOA = -38.9±8.4 - (4.89±0.96)log KOA (N = 6, r = - 0.931) ∆HOW = -36.9±15.7 + (3.4±2.6)log KOW (N = 6, r = 0.540)

OW

( ) g

OW (

) log KIA(15 oC) = 0.635log L16 + 5.11Σβ2

H + 3.60Σα2 H – 8.4

1

70 80 90 100

RIM), kJ mole

1

⎞ ⎜ ⎛ ∆

ij

H 1 1

40 50 60 70

∆HAW(EXPER

⎟ ⎠ ⎜ ⎜ ⎝ − − =

ref ij ref ij ij

T T R T K T K 1 1 ) ( ln ) ( ln

40 50 60 70 80 90 100 40

∆HAW (ESTIMATED), kJ mole

1

SLIDE 60

Main modes for transport of POPs in range from 25o to 0 oC can be distinguished from dependences of their can be distinguished from dependences of their log KAW versus log KOA quantities:

multiple hoppers

3
2

mers

multiple hoppers single hoppers

PCB15 PCB194

HCB

PCB180

PCB153

PCB101 PCB52 PCB28 PCB8

log KAW

5
4

3

swimm

PBDE47

γ-HCH α-HCH

OCDD TCDD DDT

l 7 8 9 10 11 12 13

6

CHL

log K log KOA

The DDTs, heavy PCBs, PCDDs and PBDE congeners are “single hoppers” and they have potential to easily irreversible deposition to environmental f h HCB HCH d li ht PCB “ lti l surfaces, whereas HCB, HCHs and light PCBs congeners are “multiple hoppers” and they would be readily exchanged between air and underlying surfaces in response to the temperature changes

SLIDE 61

SORPTION TO ATMOSPHERIC PARTICULATES Th t h i ti l b d f ti f th POP Φ

The atmospheric particle-bound fractions of the POPs, ΦP:

P P

K ' 1 ' = Φ

OA t t Q OM P

K v f K ) / ( ' ρ ρ =

P P

K' 1+

OA

ct

part Q OM P

K v f K ) / ( ρ ρ

vQ is the volume fraction of particles in the atmosphere, fOM is the volume fraction of organic matter in the particle, fOM is the volume fraction of organic matter in the particle, ρpart and ρoct are the densities of the particles and n-octanol

0,8 1,0

DDT, TCDD ΦP

0,4 0,6 0,8

γ-HCH

PCB-31 PCB-180 CHL

40
20

20 0,0 0,2

HCB

α-HCH T,

C

The heavy PCBs congeners (starting with penta-CB), TCDDs, TCDFs and their more heavy congeners, and DDT would be entirely particle-bounded at typical winter

temperatures. These POPs, called “single hoppers”, are usually deposited irreversibly

to the Earth’ surface. The rest of the POPs are referred to “multiple hoppers” and they readily undergo air – underlying surface exchange

SLIDE 62

SCAVENGING BY SNOW FROM AIR

The snow - gas-phase scavenging ratio (Wgas,snow) being given by:

W K SA Wgas-snow = KIASAsρw

KIA: the water/air interface – air partition coefficient SA : the snow specific surface area SAs: the snow specific surface area ρw: the density of water

25000000 30000000

α-HCH

HCH

WSA 10000000 15000000 20000000

γ-HCH

TCDD DDT PCB 180

40
30
20
10

5000000

PCB-180 HCB, PCB-31

40
30
20
10

T,

C

The snow scavenging at low air temperatures would be very effective way for removal of the POPs from atmosphere with the exception of HCB and light for removal of the POPs from atmosphere, with the exception of HCB and light PCBs congeners

SLIDE 63

ATMOSPHERIC PERSISTENCE

The drop of temperature strongly influences on atmospheric half-live
f the POPs (τ1/2)
Reaction of gaseous POPs with OH radical in atmosphere is the major

loss process

Lowering the temperature leads to deceleration of the reaction due to
Lowering the temperature leads to deceleration of the reaction due to

reduction both of the rate coefficient and the atmospheric concentration of OH radical

Second effect of the temperature lowering is the increase of non-

reactive particle-bound fraction for the OCs. Sorption of the OCs on atmospheric particulates can lead to growth of their gas phase half- p p g g p lives

] [ } ) / ( 1 { 2 ln

) ( 2 / 1

O k v K f

Q OA

ct

part OM P A

ρ ρ τ + = ] [

) , ( 2 / 1

OH kOH

P A

kOH is the bimolecular rate coefficient for reaction of a chemical with OH radical and [OH] is the concentration of OH radical in air

SLIDE 64

ATMOSPHERIC PERSISTENCE

80000

t1/2(A), days DDT DDT + part

60000

DDT + part PCB-180 PCB-180 + part

γ-HCH

20000 40000

γ HCH

γ-HCH + part HCB HCB + part

20

20

p
20

20

t,

C

The gas-particle partitioning at low temperature greatly increases the gas phase h lf li f h POP Thi ff i d f h PCB PCDD half-lives for the POPs. This effect is more pronounced for heavy PCBs, PCDDs and PCDFs congeners and for DDTs family. The loss of the POPs by degradation in cold tropospheric atmosphere is insignificant way of their removal and such sinks f th POP th d l i f th i i bi l d iti i th for the POPs on the underlying surfaces as their microbial decomposition in the soils, lake and river sediments would be more considerable

SLIDE 65

Intermediate conclusions

Now, the dust particles, combustion and industrial aerosols from Ukraine

are observed in several parts of Central, Northern and Southern Europe

These particulates can affect on radiative atmospheric budget, visibility

p p g , y

f atmosphere, its chemical composition, climate and on the human and

ecosystem health in Europe

They are also carriers for transport of POPs over a long distances to

E f th i i d t i l d i lt l i Uk i Europe from their industrial and agricultural sources in Ukraine

It was found that heavy PCB congeners (starting from penta-CB),

TCDDs, TCDFs and their more heavy congeners, and DDTs would be entirely particle bounded at low tropospheric temperatures entirely particle-bounded at low tropospheric temperatures

The snow scavenging at low temperatures would be very effective way for

removal of the POPs from atmosphere, with the exception of HCB and light PCB congeners light PCB congeners

The gas-particle partitioning at low temperature greatly increases the gas

phase half-lives of the POPs. This effect is more pronounced for heavy PCBs, PCDDs and PCDFs congeners, and for DDTs family , g , y

International cooperation with Europian countries and national funding

are need to develop the modern aerosol observational network, the detailed study of the aerosol’ composition and the modeling the aerosol’ d i i Uk i Thi i ti l ti l bl t th dynamics in Ukraine. This is an exceptional national problem together with such main problems as monitoring of greenhouse gases and ozone level in Ukraine

SLIDE 66

Most of heterogeneous transformations on the aerosols f b i t t f i k f i i (HCl surface can be an important way of sink for inorganic (HCl, HBr, HI, HNO3, NO2, N2O5, SO2, COS, CS2, O3) organic impurities (VOCs, CFCs, HCFCs, PAHs, POPs) and radicals impurities (VOCs, CFCs, HCFCs, PAHs, POPs) and radicals (HO, HO2, NO3, RO, RO2) in air They are comparable on the rate with such

homogeneous ways of their sink, as their photolysis or their interaction with НOx and NO3 radicals The considerable sink of these impurities from troposphere via the heterogeneous mechanism is bound to be substantially in their photochemical cycles, and in the content of O3, HOx, NOx, SO2 and halogen oxides in troposphere, especially at night time

SLIDE 67

Volatile organic compounds (VOCs) used as
Volatile organic compounds (VOCs) used as

solvents and refrigerants are important priority toxic pollutants because exposure to the dangerous VOCs p p g can be injurious to human health and ecosystems

VOCs participate in much heterogeneous industrial

d t l h d l i f and natural processes, such as developing of stratospheric ozone hole over Antarctica and decreasing the tropospheric oxidation potential g p p p

Knowledge of VOCs adsorption from gas phase to

such interfaces as water, snow, plants, rocks, soils d di t i b d i l and sediments, organic, carbonaceous and mineral aerosols is important for assessing the partitioning and transport of the organics in our environment and transport of the organics in our environment

SLIDE 68

The following problems in description of VOCs interaction with surface of atmospheric aerosols: p

Current air/particle partition models ignored the effect of

different surface chemistry of the particles and non- y p additivity of the VOCs/surface interaction on the partitioning Q tit ti “ t t ti it ” l ti hi t

Quantitative “structure-activity” relationships are not

developed for uptake kinetics of VOCs by aerosol surfaces

Also these models ignored the effect of significant surface

Also, these models ignored the effect of significant surface heterogeneity of the solid aerosols on the partition thermodynamics and on the reaction surface kinetics of VOC VOCs

Development of QSARs for VOCs interaction (adsorption

equlibrium chemisorption kinetics) equlibrium, chemisorption kinetics)

Description of adsorption thermodynamics of VOCs, their

chemisorption, desorption and bimolecular reaction kinetics

n the heterogeneous surface of the solid aerosol components

SLIDE 69

Building Blocks of the Partitioning Model Model

ADSORPTION =

Nonspecific

+

Specific

INTERACTION

Contribution Contribution

Dispersion Acid-Base Dispersion Interaction (Hydrogen Bonding) and Charge-Transfer Polarisability Interaction Average Polarisability

f molecule

Acid and Base Parameters Average Polarisability

f Surface Sites

Acid and Base Parameters for Molecule

Average Acid and Base Average Acid and Base Parameters for Surface Sites

SLIDE 70

Non-specific interaction

sp nsp

H H H ∆ ∆ ∆

sp A nsp A A

H H H ∆ + ∆ = ∆ ∆ ∆ ∆ G G G

A A nsp A sp

= +

6 2 , 1 2 2 1 2 1 2 1

) 1 ( ) 4 ( ) ( 2 3 r N v v v v h w

A e e d

πε α α + − =

G e G nsp A

K G ζ α + × = ∆ −

nsp

K H ζ ∆

2 / 1 2 / 1

) ( ) 058 . 6 . 52 ( 0397 .

D S G

T K γ − = T K K

is H e H nsp A

K H ζ α + × = ∆ − T T K K

is is G H

− = Specific interaction

H H

K G β β Σ Σ ∆

G H G S H G S e G A

K G ς α β β α α + Σ × + Σ × + × = ∆ −

2 ) ( 2 ) ( H H H S H H S e H A

K H ς α β β α α + Σ × + Σ × + × = ∆ −

2 ) ( 2 ) ( H H sp

K K K K H Σ Σ ∆ 3 5 6 2 2 3 β

A B H A H B sp A

K K K K H × − × + Σ × × + Σ × × = ∆ − 3 . 5 . 6 . 2 2 . 3

2 2

β α

A B H A H B sp A

K K K K H × − × + Σ × × + Σ × × = ∆ − 3 . 04 . 6 . 2 1 . 1

* 2 2 *

β α T T T

is is G S H S

− =

) ( ) (

α α T T T

is is G S H S

− =

) ( ) (

β β

SLIDE 71

Compensation effect at adsorption of VOCs on solid materials

∆G = a∆H + b; ∆H = ∆G (T ) + T ∆S ;

1

∆GA = a∆HA + b; ∆HA = ∆GA(Tis) + Tis∆SA ; a = 1 – T/Tis ; b = ∆GA(Tis) T/Tis

Carbopack Carbosil

22 24 26 28

3.15 K), kJ mol

1

22 24 26 28

(433 K), kJ mol

1

Carbopack Carbosil

12 14 16 18 20

∆GA(373

14 16 18 20

∆GA(
10

10 20 30 40 50 60 70 10 12

∆HA, kJ mol
1

40 45 50 55 60 65 70 75 80 85 10 12

∆HA, kJ mol
1

32

1

28

Silica Gel Titania and titania/alumina/silica

26 28 30

A(413 K), kJ mol

20 22 24 26 28

SiO2/Al2O3/TiO2 TiO

∆GA, kJ mol
1

Silica Gel Titania and titania/alumina/silica

18 20 22 24

∆GA

10 12 14 16 18

TiO2

20 30 40 50 60 70 16

∆HA, kJ mol
1

35 40 45 50 55 60 65 70 8 10

∆HA, kJ mol
1

SLIDE 72

Estimation of acid-base descriptors for VOCs

[basicity] ~ [proton affinity, (PA)] ~ [maximum negative charge on an atom in molecule, (q-

max)] ~

[basicity in an standard equilibrium] [basicity in an standard equilibrium] [acidity] ~ [XR-H dissociation energy, (ER-H)] ~ [maximum positive charge on an H atom in molecule (q+ )] ~ [maximum positive charge on an H atom in molecule, (q max)] [acidity in an standard equilibrium, (pKHB)] Σα2

H = -0.11±0.03 + (2.7±0.3)×q+ max; N = 52; r = 0.820

Σβ2

H = -0.04±0.04 + (1.5±0.2)×q- max; N = 52; r = 0.827

Σα2

H = 0.135‘H+ max – 0.01; N = 32; r = 0.780

Σα2 0.135 H max 0.01; N 32; r 0.780 Σβ2

H = 0.00334‘PA – 0.444; N = 15; r = 0.834

Σβ2

H = 0.0071‘νOH + 0.08; N = 5; r = 0.994

SLIDE 73

QSARs for air/particle partitioning of POPs with their t h i l d i t quantum chemical descriptors

−

× + × + =

max

) log( q c b a K

e P

α

log (KP) = -3.6±1.6 + (0.05±0.02)αe + (6.1±8.6)q-

max, R2= 0.899

5 PAHs on urban aerosols (Athens, Greece)

log (KP) = -4.7±1.4 + (0.20±0.04) αe + (23.1±4.3) q-

max, R2=0.776

8 PCBs and PCDD/Fs on urban aerosols (Auxburg, Germany)

log (KP) = -16.5±1.7 + (0.52±0.05)αe + (7.6±3.2)q-

max, R2= 0.941

16 PCDD/Fs on urban aerosols (Tokyo, Japan)

log (KP) = -14.4±0.9 + (0.54±0.02)αe + (0.3±1.6)q-

max, R2= 0.983

16 PCDD/Fs on background aerosols (Alert, Canadian Artic)

log (KP) = -9.2±6.0 + (0.30±0.03)αe + (13±32)q-

max, R2= 0.937

8 PAHs on model secondary organic aerosols at RH = 10%

log (KP) = 0.9±0.5 + (0.27±0.02)αe + (9.7±1.8)q-

max, R2= 0.908

24 PCBs on sandy soils near Beirut, Libyan

SLIDE 74

Comparison of coefficients in the QSARs for different solid and liquid surfaces

i. Parent and modified carbonaceous solids

for microporous solids:

3

2 1 ) ( ⎠ ⎞ ⎜ ⎝ ⎛ − = d K K

G G 3

2 1 ) ( ⎠ ⎞ ⎜ ⎝ ⎛ − = d K K

H H

2 ⎠ ⎝ a

G G

2 ⎠ ⎝ a

H H

ii. Parent and modified inorganic solids

2 / 1

540 A K

n 2 / 1

540 .

H G

A K =

AH = -6.2±2.8 + (9.1±1.5)n0; N = 23, r = 0.789

∑

=

n i i G i app G

K K

1 ) ( ) (

θ

20 25

Hx10 20, J 2 4 2.8

F O

G, mol kJ

1

10 15 20

AH

1.6 2.0 2.4

Fe2O3 TiO2 Al2O3 SnO2 SiO

KG

1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 5

5 10 15 20 25 1.2

CaO MgO SiO2

n0

εk

SLIDE 75

Diagrams for normalized parameters of surface sites of carbonized (1), inorganic (2), organic (3) materials and water, snow and soils (4)

1.0

t

AC GF 40 CB es polarizability acidity basicity

1.0

Zeolite 5A

lite 13X

tes polarizability acidity basicity

(1) (2)

0.6 0.8

Wet soo Oxidized CF F enriched AC HFPE-modified CB Oxidized CB Graphitized eters of surface site

0.6 0.8

Cu2

IIFe II(CN)6

Na2NiFe

II(CN)6

CaCO3 TiO2 Zeo α-Al2O3 SiO2 eters of surface sit

0.2 0.4

Untreated C N- H O Normalized parame

0.2 0.4

Normalized param

0.0

N

0.0

drate polarizability acidity basicity

1 0

H=90%) H=70%) H=50%) RH=90%) RH=70%) (RH=50%) Water

(3) (4)

0 6 0.8 1.0

α-Lactose monohyd icular matrix

se paper
lyethylene oxide
f surface sites

basicity

0,6 0,8 1,0

Soil Euro1 (RH Soil Euro1 (RH Soil Euro1 (RH Soil EPA9 (R Soil EPA9 (R Soil EPA9 Snow rs of surface sites

0.2 0.4 0.6

α Cuti Callulo P malized parameters

0,2 0,4

rmalized paramete

0.0

Norm

0,0

No polarizability acidity basicity

SLIDE 76

Surface of solid aerosols

Homogeneous Heterogeneous

Induction heterogeneity: Lateral interaction, reconstruction

Geometrical heterogeneity: g y amorphous, random or patchwise topography of the active sites Structural heterogeneity: Micropores, mesopores Chemical heterogeneity: lattice defects, different types of the active sites (Lewis, Bronsted acid-base sites, etc.)

SLIDE 77

Description of adsorption energy distribution using several numerical procedures using several numerical procedures

CA: condensation approximation RP: regularization procedure da/dQ = f(Q): 1st derivative on isosteric adsorption heat

1.0

CA kJ

1

da/dQ = f(Q): 1st derivative on isosteric adsorption heat

0.8

da/dQst=f(Qst) EA), mole k

0.6

st

(

st)

RP alized ρ(E

0.4

RP Norma

0.0 0.2 10 20 30 40

EA, kJ mole

1

SLIDE 78

Distributions of surrogates for solid aerosols on adsorption energies

f atmospheric impurities

0.00015 0.00020

Al2O3(dehydr) ρ(EA), mole J

1

n-C5H12 (C2H5)2O CH CN

0.0005 0.0006 0.0007

Al2O3(hydr) ρ(EA), mole J

1

n-C5H12 (C2H5)2O CH3CN CHCl3

0.00010

CH3CN CHCl3 (C2H5)3N

0.0002 0.0003 0.0004

3

(C2H5)3N

10000 20000 30000 40000 50000 60000 70000 80000 90000 0.00000 0.00005

E J l

1

10000 20000 30000 40000 50000 60000 70000 80000 90000 0.0000 0.0001

E J l

1

EA, J mole

1

EA, J mole

1

0.00010 0.00012

(C2H )3N ρ(EA), mole J

1

Al2O3(hydr) 63% Al2O3 in SiO2(hydr)

1 2 1.4 1.6

(C2H5)2O

4, mole J

1

Trimethylsilylated SiO2 Hydroxylated SiO2

0.00004 0.00006 0.00008

(C2H5)3N ρ

0.6 0.8 1.0 1.2

ρ(EA)10

4

Hydroxylated SiO2 Methoxylated SiO2

10000 20000 30000 40000 50000 60000 70000 80000 90000 0.00000 0.00002

E J l

1

10 20 30 40 50 60 0.0 0.2 0.4

E kJ l

1

EA, J mole

1

EA, kJ mole

1

SLIDE 79

Distributions of surrogates for solid aerosols on adsorption energies

f atmospheric impurities

0.00035 0.00040

EA), mole J

1

SiO2

0.00035 0.00040

, mole J

1

SiO2 TiO2 20% TiO2 in SiO2

0.00015 0.00020 0.00025 0.00030

ρ(E

2

Al2O3 1%(w/w) Al2O3 in SiO2 23%(w/w) Al2O3 in SiO2

0 00015 0.00020 0.00025 0.00030

ρ(EA) 50% TiO2 and 22% Al2O3 in SiO2

3000 6000 9000 12000 15000 18000 0.00000 0.00005 0.00010 3000 6000 9000 12000 15000 18000 0.00000 0.00005 0.00010 0.00015

EA, J mole

1

3000 6000 9000 12000 15000 18000

EA, J mole

1

0.00035 0.00040

, mole J

1

40 45

ж моль

1

0.00015 0.00020 0.00025 0.00030

ρ(EA), SiO2 Al2O3 TiO2

30 35

QA(изостер), кДж

3000 6000 9000 12000 15000 18000 0.00000 0.00005 0.00010

Vaporization Heat of N2

0 0 0 2 0 4 0 6 0 8 1 0 1 2 20 25

QA(изостер)= 22.82+25.64exp(-a/0.27); R = 0.999 EA, J mole

1

0.0 0.2 0.4 0.6 0.8 1.0 1.2

а, мкмоль м

2

SLIDE 80

Adsorption of atmospheric impurities on surrogates of solid aerosols as revealed by IGC method at finite concentrations y

350 400

h Al O /SiO

)

0.12

n-hexane - Al2O3/SiO2 406 K

erage

200 250 300 350

n-hexane - Al2O3/SiO2

sure, Torr (STP)

0.06 0.08 0.10

443 K 423 K

Surface cove

50 100 150

f(P)=dΘ/dP Air

Partial press

0.02 0.04 20 40 60 80 100 120 140

τ, s

50 100 150 200 250 0.00

Pressure, Torr (STP)

SLIDE 81

Effect of surface heterogeneity of surrogates for solid aerosols on adsorption energies of halocarbons

0.00035 0.00040

Carbopack S

n C H Br 1,2-C2H4Cl2 mole J

1

50 55

CH3I on Carbosil J mole

1

aerosols on adsorption energies of halocarbons

0 00015 0.00020 0.00025 0.00030

n-C4H9Br ρ(EA),

40 45 50

EA(iso)= 32.9 +30.2*exp(-a/0.1) EA(iso), kJ

0.00000 0.00005 0.00010 0.00015

CH2Cl2

30 35 40 20000 30000 40000 50000 60000

EA, J mole

1

0.000035

J

1

0.000040

Silica Gel

J

1

0.0 0.1 0.2 0.3 0.4 0.5 0.6

a, µmole m

2

0.000020 0.000025 0.000030

Carbosil

1,2-C2H4Cl2 CH2Cl2 ρ(EA), mole

0.000025 0.000030 0.000035

Silica Gel

n-C4H9Br 1,2-C2H4Cl2 CH2Cl2 ρ(EA), mole J

0 000005 0.000010 0.000015

n-C4H9Br

0.000010 0.000015 0.000020 30000 40000 50000 60000 70000 0.000000 0.000005

EA, J mole

1

30000 40000 50000 60000 70000 0.000000 0.000005

EA, J mole

1

SLIDE 82

QSARs for adsorption of 23 VOCs on surface of surrogates for solid aerosols at finite concentrations

45 50 55

ntal), kJ mole

1

Carbopack Carbosil Silica Gel

120 140 160 180

ntal), kJ

2mole

2

Carbopack Carbosil Silica Gel

30 35 40

EA(av)(experime

40 60 80 100

σ

2 EA(experimen

20 25 30 35 40 45 50 55 20 25

EA(av)(calculated), kJ mole

1

20 40 60 80 100 120 140 160 180 20

σ

2 EA(calculated), kJ 2mole

2

(max) A

E

) / e p(

1

RT E K P

−

×

∫

= Θ

(max) (min)

) ( ) , ( ) , (

A A

E A A dE

E T P T P ρ θ ) / exp( 1 ) / exp( ) , (

1 1

RT E K P RT E K P T P

A A −

× + × = θ ⎪ ⎨ ⎧ ≤ ≤

(max) (min)

1 ) (

A A A

E E E E E E ⎪ ⎩ ⎪ ⎨ > < − =

(max) (min) (max) (min) (min) (max)

; ) (

A A A A A A A A A A

E E E E E E E ρ

(min) (max) A A

E E E K + = =

2 3 (min) 3 (max) 2 A A

K E E K − σ 2

) (av A I

E K = =

(min) (max)

) ( 3

I A A Ea II

K E E K − − = = σ Carbopack :

H e av A

E

2 ) (

2 . 29 1 . 3 8 . 9 α α Σ × + × + =

e E

α σ × − = 7 . 15 182

2

Carbosil:

H H

E 6 11 30 1 4 24 β α α Σ × + Σ × + × + =

H 2

89 8 2 126 α α σ Σ × + × + = Carbosil:

e av A

E

2 2 ) (

6 . 11 30 . 1 4 . 24 β α α Σ × + Σ × + × + =

e E 2

89 8 . 2 126 α α σ Σ × + × + = Silica Gel:

H H e av A

E

2 2 ) (

3 . 25 4 . 19 66 . 1 . 21 β α α Σ × + Σ × + × + =

H E 2 2

84 84 β σ Σ × + =

SLIDE 83

Compensation behavior in adsorption of halocarbons

n heterogeneous surface of surrogates for solid aerosols

16 0 16.5

g st)

1

30

n-C4H9Br on Carbopack S

1
n heterogeneous surface of surrogates for solid aerosols

14.5 15.0 15.5 16.0

CH3I on Carbosil ln K0 (mm Hg

20 25

ln K0 = -3.042 + 0.384*Ec K0(Θ) (mm Hg st)

12.5

13.0 13.5 14.0

ln K0 = ln K0(iso) + EA/RTiso ln K0(iso) = 7.06; Tiso = 698 K; R = 0.9998

10 15

ln K

30 35 40 45 50 55

EA, kJ mole

1

20 30 40 50 60 70 80 90 5

EC(Θ), kJ mole

1

14 15

Hg st)

1

11

CH Cl

1

12 13 14

Adsorption of CH3I on Silica Gel ln K0(iso), (mm

8 9 10

CH2Cl2 CH3Cl

0(iso), (mm Hg st)

10

11 12

ln K0(iso)= 10.375 + 5.406exp(-a/0.342); R = 0.996

5 6 7

CCl4 ln K0

0.0 0.2 0.4 0.6 0.8 1.0 1.2

a, µmole m

2

300 350 400 450 500 550 3 4

4

CHCl3 Tiso, K

SLIDE 84

Dependencies of partition coefficients for CH3I from air to surface of aerosol’ surrogates on the relative surface coverage surface of aerosol surrogates on the relative surface coverage and temperature

1: Carbopack (253 K)

4 5

mm.Hg.st)

1

1: Carbopack (253 K) 2: Silica Gel (253 K) 3: Carbosil (253 K) 4: Carbopack (293 K)

3

coefficient, (m 3

4: Carbopack (293 K) 5: Silica Gel (293 K) 6: Carbosil (293 K)

2

Partition 6 2 1

0.0 0.2 0.4 1

5 4

0.0 0.2 0.4

Relative surface coverage

The partition coefficients vastly depend on the aerosol’ surface chemistry. They drop exponentially as the surface coverage rises even at small θ They drop exponentially as the surface coverage rises even at small θ. Reduction of the temperature results in substantial increase of the coefficients.

SLIDE 85

Influence of non-uniformity of aerosol surface on kinetics of the heterogeneous atmospheric sink for the VOCs the heterogeneous atmospheric sink for the VOCs

The rate of reaction of gas-phase A with the homogeneous

aerosol surface sites S with formation of the chemisorbed aerosol surface sites S with formation of the chemisorbed product AS: A + S → AS A d ] [ A + S → AS

t A t t

A m S c A dt A d ] [ 4 ] [ ] [ γ γϖ = = −

[A] th h t ti f A t t [A]t – the gas phase concentration of A at t, γ – the uptake coefficient, ω – the collision rate of A with the particle surface,

mean gas phase velocity of A toward the particle,

SA – specific adsorption area of the particles, m – weight of the particles per air volume

c

g p p

( )

t k A A t ' exp ] [ ] [ − = m S c k

A

4 ' γ γϖ = =

SLIDE 86

The rate equation for heterogeneous aerosol surface is:

∫

− =

' max

' ) ' ( ) ' exp( ] [ ] [

k i t

dk k t k A A ρ

∫

' min

k

[A]0 – the gas phase concentration of A at t = 0, (k’) th f diff ti l di t ib ti f ti k’ ffi i t ρ(k’) – the surface differential distribution function on k’ coefficient k’min and k’max – the minimal and maximal coefficients k’ For Γ- distribution on coefficient k’:

a

b t k k ⎞ ⎜ ⎛ − = ) ' exp( ) ' ( ρ

For Γ- distribution on coefficient k :

t b t k k ⎠ ⎜ ⎝ − − = ) exp( ) (

min

ρ

0 9 1.0

[A]t/[A]0

50

min

0.6 0.7 0.8 0.9 30 40

ρ(k), m

a = 1.5; b = 100 мин a = 1.5; b = 50 мин

0.2 0.3 0.4 0.5

k1=0.05 мин

1

k0=0.05 мин

1; a = 1.5; b = 100 мин

k0=0.05 мин

1; a = 1.5; b = 50 мин

10 20 5 10 15 20 0.0 0.1

Время, мин

0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12

k, мин

1

SLIDE 87

Kinetics on heterogeneous surface with its power distribution

n coefficient k’

2.0

, мин

1

Однородная поверхность (k = 2 мин

1)

Неоднородная поверхность с ν=0.5 и η=5

1.5

сть реакции

Неоднородная поверхность с ν 0.5 и η 5 Неоднородная поверхность с ν=1.0 и η=5 Неоднородная поверхность с ν=1.5 и η=5

1.0

ьная скорос

0.5

Относитель

0.0 0.2 0.4 0.6 0.8 1.0 0.0

[A]t/[A]0

' ln

/ 1

k

ν

⎞ ⎜ ⎜ ⎛ ' ln ) ' (ln k k ν η ρ ⎠ ⎜ ⎜ ⎝ =

; η = ln k’max – ln k’min

SLIDE 88

Diffusion correction to rate equation on the aerosol surface Diffusion correction to rate equation on the aerosol surface

Coefficient k’ depends on the dimension of the aerosol particles:

⎞ ⎛ 4 '

A

mS c k γ ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ × =

n n n

K K K K f 283 75 ) 1 ( ) ( + + =

n

R D K λ λ = = 2 ) ( 1

n

K f γ +

n

K 283 . 75 . +

P P

R D

∫

max

) ( 4 ] [

2

P

R t

dR dn R F R A d

Kn - the Knudsen number, λ – the gas phase mean free path DP – the diameter of the particle

∫

= =

min

) ( 4 ] [

2

P

R P P P P t A

dR dR dn R F R dt v π

P

p RP – the radius of the particle

[ ]

n n P e t A P

K K f R A A D R F ) , ( 1 ) ] [ ] ([ ) ( γ + − =

0.8 1.0

Kn=0,1 Kn=0,05 Kn=0,01 генного стока

γ γ 3 ) 1 ( 4 1 71 , 333 , 1 ) , (

1 1

− + + =

− − n n

K K K f

0 2 0.4 0.6

Kn=1,0 Kn=0,5 льная скорость гетерог

γ 3 1

1

+

n

K

0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2

Kn=5,0 Относител Вероятность протекания реакции

SLIDE 89

Dependence of rate of Langmuir-Hinshelwood and catalytic reactions on homogeneous and heterogeneous aerosol reactions on homogeneous and heterogeneous aerosol surfaces on the partial pressure of the gas-phase reactant

i i C i i Langmuir-Hinshelwood Catalytic reaction reaction

1 6

ν = 1,67

12

α = 0,6

ии

1 0 1.2 1.4 1.6

Однородная поверхность

ость реакции

8 10

, корость реакци

0.4 0.6 0.8 1.0

ν = 2,5

Однородная поверхность

Скоро

4 6

α = 0,4

0 2

Однородная поверхность

С

20 40 60 80 100 0.0 0.2

ν = 5,0

Парциальное давление

20 40 60 80 100 2

α = 0,2

Парциальное давление

) 1 ( 1

A A A chem A A A

P K k P K v Θ − + =

2 1 2 1

k P k P k k v

A A A

+ =

η / 1 A F S

P K = Θ

α A A

P k v ' =

SLIDE 90

Use of model for discrete heterogeneous surface to describe the uptake kinetics on atmospheric aerosols p p For discrete heterogeneous surface:

∑

=

n i i i S ef 1 ) ( γ

α γ

γef – the effective uptake coefficient for whole surface γef p γi – the uptake coefficient by surface compartment i αS(i) – the part of the i-th compartment in the whole surface HNO3 uptake Gobi desert: γ0 = 5,210-5 (48% Si, 22% Ca, 10% Fe, 10% Al, 2% Mg) Sahara desert: γ0 = 2,010-5 (80% Si, 1% Ca, 7% Fe, 8% Al,1% Mg) SiO2 : γ0 = 2,910-5 α-Al2O3: γ0 = 9,710-5 α-Fe2O3: γ0 = 5,310-5 (Underwood G.M. et al, 2001) CaO: γ0 = 6,110-3 M O 3 710 4 MgO: γ0 = 3,710-4 O3 decomposition: γ0(exp( = 6,010-5 , γ0(est) = 7,210-5 (Michel A.E. et al, 2003)

n dust from Sahara
n dust from Sahara

The validity of the approach is confirmed by coincidence of the experimental and estimated uptake coefficients for interaction of O3 with α-Al2O3 surfaces, preliminary t t d b SO HNO d ith SiO f li i difi d b 7 t 1 l treated by SO2, HNO3 and with SiO2 surfaces, preliminary modified by 7-oct-1-enyl and 1-octyl groups, and with the parent oxide surfaces

SLIDE 91

Kinetic isotherms for chemisorption of organosilicon compounds on surface of surrogates for solid aerosols

1.0

CHEMISORPTION ISOTHERMS ON HOMOGENEOUS AND HETEROGENEOUS SURFACES

[A]t/[A]0 Homogeneous Surface; k = 0.05 min

1

Uniform Distribution on Activation Energy;

1.0

CHEMISORPTION ISOTHERMS OF ORGANOSILOXANE ON Al2O3 SURFACE

verage

compounds on surface of surrogates for solid aerosols

0.6 0.8

gy (T = 293 K; k0= 0.05 min

1; ∆EA= 32 kJ mole
1)

0.6 0.8

ction Surface Co 293 K 323 K

0.2 0.4 0.2 0.4

HMCTS + Al2O3 Reac 323 K 373 K 423 K

20 40 60 80 100 0.0

Time, min

5 10 15 20 25 30 0.0

Reaction Time, min

1.0

SiCl4 rage

1.0

SiO2 T = 673 K (CH3)3SiCN

0.6 0.8

SiO2 Tp = 673 K Tr = 548 K CH3SiCl3 (CH ) SiCl n Surface Cover

0.6 0.8

Tp = 673 K Tr = 573 K rface Coverage

0.2 0.4

(CH3)2SiCl2 (CH3)3SiCl Reaction

0.2 0.4

(CH3)3SiNCS (CH3)3SiN3 Reaction Su

50 100 150 200 250 300 0.0

Reaction Time, min

20 40 60 80 100 120 0.0

(CH3)3SiNCO Reaction Time, min

SLIDE 92

Chemisorption kinetics on amorphous surface

1.0

1 - Θ

1.0

1 - Θ

0.6 0.8

kav= 1.0

σk= 0.00001 σr= 0.001 A

0.6 0.8

r = 6 0 A rav= 3.7 A

σk= 2.0

1 - Θ

0.2 0.4

rav= 6.0 A rav= 4.5 A rav= 4.0 A rav= 3.7 A

0.2 0.4

rav= 6.0 A

σk= 2.0

rav= 6.0 A

σk= 0.00001

rav= 3.7 A

σk= 0.00001

1 2 3 4 0.0

kτ

1 2 3 4 0.0

kτ

6 7

kav= 1.0

σk= 0.00001

kav(app), σ

2 k(app) 20 25

kav(app), σ

2 k(app) 3 4 5

k

σr= 0.01 A

kav(app)

10 15

kav= 1.0

σk= 0.00001

rav= 4 A

σ

2 k(app)

4 5 6 7 8 1 2

σ

2 k(app)

r A

0.0 0.1 0.2 0.3 0.4 5

kav(app)

k

A rav, A

σr, A

SLIDE 93

QSARs for chemisorption kinetics on metal oxide surfaces p

Transition state

nergy

Reagents

Potential en

H-complex (P) DA-complex (P) DA-complex (R) H-complex (R)

Reaction coordinate

120 130

Eact, kJ mol

1

120 140

(CH3)3Si-O-Si(CH3)3

SiO2

Eact, kJ mol

1

90 100 110 120 60 80 100

TiO2/SiO2 Al2O3/SiO2 TiO

60 70 80 20 40

Al2O3 TiO2

8.0 8.5 9.0 9.5 10.0 10.5 11.0

100/(IP~M-OH- EARSiX), eV

1

0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5

20

KD(av)

SLIDE 94

TPD kinetics of water from silica surface

Simulated TPD spectra of water

0.24 0.20

Single crystal surface r = 0.5 nm r = 0.7 nm

I, a.u.

0.06 0.05 Simulated TPD spectra of water from disordered lattice at different initial coverages

β = 20 K s

1

ED(0) = 387kJ mol

1

18 1

0 89 1.0

I, a.u. 0.16 0.12 0.08

Amorphous surface (r = 0.3 nm) r = 0.3 nm 0.04 0.03 0.02 AD= 10

18s

1

rOH= 3 nm 0.26 0.49 0.68 0.80 0.89

0.04

1100 900 700 500

T, K

0.01 500 1000 900 800 700 600

T, K

β = 20 K s

1

E (0) = 387 kJ mol

1

Without surface diffusion 0 16

I, a.u.

Simulated and experimental TPD spectra of water from aerosilagel sample at β = 0.097 K s

1

0.24

I, a.u.

ED(0) 387 kJ mol AD= 10

18s

1

rOH= 0.5 nm

ΘOH= 1.0

0.16 0.12 0.08 g p

β

0.20 0.16 0.12 Surface diffusion 8 0.04 0.08 0.04 900 800 700 600 500 400

T, K

1200 1100 1000 900 800

T, K

900 800 700 600 500 400

SLIDE 95

Determination of mesopores size distribution and desorption energy distribution from data of i h i i l i f lid quasi-thermogravimetric analysis of solids

0.0

Tb n-butanol/silica gel

dm/dτ, mg min

1

0.10

Cumulative pore-size distribution

f silica gel surface

Vmeso, cm

3

1.5
1.0
0.5

2: Area of heterogeneous surface 1: Area of mesopores

0.06 0.08

2.5
2.0

5

2 1

0.02 0.04 20 40 60 80 100 120 140 160 180

3.0

1 T,

C

2 4 6 8 10 0.00

Rmeso, nm

1

0.25

1

3 4 5

Differential pore-size distribution

f silica gel surface

meso10 2, cm 3 nm

0.20

Distribution of silica gel surface

n n-butanol desorption energy

ρ(ED), mol kJ

1

2

dVmeso/dRm

0.10 0.15 2 4 6 8 10

Rmeso, nm

88 90 92 94 96 0.05

ED, kJ mol

1

SLIDE 96

Kinetics of bimolecular photoreaction ili f (P * DMA)

n silica surface (Py* + DMA)

Distributions of silica surface on apparent rate constants for ρ(kapp)10

7, s 3.5

Dependence of average apparent rate constant on DMA/Py ratio

kapp(av)10

7, s
1

6 8

apparent rate constants for Py

* fluorescence quenching by DMA

at dufferent DMA/Py ratio Q 10

2.0 2.5 3.0 2 4

10 20 100 200 300

0.5 1.0 1.5 0.0 0.2 0.4 0.6 0.8 1.0 1.2

kapp10

6,s
1

50 100 150 200 250 300 0.0

DMA/Py

Distribution of surface

α (k

k )

1

ρ(kapp) ρ(kapp) 10

7, s

1

Distribution of surface

n apparent rate constant

in accordance with model (1 - α )(k - k )

1

αQ(k2- k1)

app 0.08 0.10 0.12

Distribition of silica surface on apparent rate constants for Py

* fluorescence quenching by DMA

at DMA/Py = 200 (293 K) (1 αQ)(k5 k6)

0.02 0.04 0.06

Regularization Model

k6 k5 k4 k3 k2 k1 kapp

20 40 60 80 0.00

kapp10

7, s
1

SLIDE 97

Conclusions

Parameters of compensation dependence are calculated for adsorption
f VOCs series on the surface of 34 solids and liquids
One-type QSARs for the gas/interface partitioning and its temperature

dependencies are proposed and relations between the QSAR’s coefficients and the surface characteristics determined by IGC are coefficients and the surface characteristics determined by IGC are derived

Coefficients in the QSAR’s for 300 different surface components of

atmospheric aerosols are calculated

The relationships between experimental and theoretical acid-base

descriptors of VOCs were established p

Proposed QSARs were extended to describe the VOCs gas/interface

partitioning in region of finite surface concentrations for three solids M d l f h i i d i d bi l l i

Models for chemisorption, desorption and bimolecular reaction

kinetics on heterogeneous aerosol surface are developed

QSARs for chemisorption of organosilanes and organosiloxanes on the

Q p g g silica and other oxide surfaces are derived

SLIDE 98

My acknowledgments: My acknowledgments:

Center for Atmospheric Sciences,

Cambridge University, UK g y,

Robert Scott Polar Institute, Cambridge