Influence of Sea Breeze_BC, PM2.5, PM10

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    Influence of sea breeze circulation and road traffic emissions on therelationship between particle number, black carbon, PM1, PM2.5 andPM2.510 concentrations in a coastal city

    Sergio Rodrguez a,b,*, Emilio Cuevas a, Yenny Gonzalez a, Ramon Ramos a,Pedro Miguel Romero a, Noem Perez c, Xavier Querol c, Andres Alastuey c

    a Izana Atmospheric Research Centre, AEMet, Associated Unit to CSIC Studies on Atmospheric Pollution, C/ La Marina, 20,

    6a Planta, E38001 Santa Cruz de Tenerife, Canary Islands, Spainb Department of Geology, University of Huelva, Associated Unit to CSIC on Air Pollution, Campus El Carmen, E21071 Huelva, Spainc Institute of Earth Science Jaume Almera, CSIC, Lluis Sole i Sabaris S/N, E08028 Barcelona, Spain

    a r t i c l e i n f o

    Article history:

    Received 19 February 2008

    Received in revised form 26 March 2008

    Accepted 2 April 2008

    Keywords:

    Ultrafine particles

    New particle formation

    Black carbonSoot

    Vehicle exhausts

    a b s t r a c t

    The physical characterisation of metrics representative of ambient air particle concentra-

    tion is becoming a topic of great interest for urban air quality monitoring and human ex-

    posure assessment. In this article, the influence of sea breeze circulation and primary road

    traffic emissions on the relationship between the urban aerosol number (N3, particles

    >3 nm), black carbon

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    aerodynamic diameter, respectively) with an increased risk

    to sufferers of respiratory and cardiovascular diseases

    (Dockery and Pope, 1996). As a result of this, PM10 and

    PM2.5 are currently used as urban air quality reference

    metrics. More recent research has highlighted the high

    potential toxicity of some PM components. For example, ul-

    trafine particles (

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    2. Methodology

    2.1. Study city

    This study was performed in Santa Cruz de Tenerife (Ca-

    nary Islands; 28280N, 16150W; Fig. 1). This is a 221,500

    inhabitant city (distributed over 150 km2) located at the

    bottom of the southern slope of the Anaga ridge and the

    eastern slope of the SW to NE ridge crossing the Island.

    This topographic setting protects the city from the Trade

    winds (NNE) that blow over the ocean (see details on the

    meteorology in Guerra et al., 2004). The main sources of an-

    thropogenic aerosols in the cityare: (1) road traffic (the two

    main city roads are highlighted in Fig.1A), (2) a crude oil re-

    finery (COR) located on the SE shore of the city (see COR in

    Fig. 1C), and (3) ship emissions in the harbour. Natural

    Saharan dust and sea salt may significantly contribute to

    the daily aerosol load (>100 mgPM10 m3 during dust

    events; Viana et al., 2002).

    2.2. Measurements

    Measurements of PM were performed simultaneously

    (mid-March to mid-April 2006) at three sites in the city

    of Santa Cruz de Tenerife (Fig. 1C): (1) Santa Cruz Observa-

    tory (SCO), (2) Tome Cano (TC) and (3) Gladiolos (GL).

    (A) Santa Cruz Observatory (SCO; Fig.1C) is a coastal urban

    background site located on the roof of an 8-floor build-

    ing at 52 m above sea level, at about 45 m above

    ground. Measurements of meteorological parameters

    (wind speed and direction, temperature, relative

    humidity, pressure and global radiation), trace gases

    (CO, SO2 and O3) and particles at SCO are performed

    by the staff of Izana GAW Observatory in the frame-

    work of the GURME (GAW) program. The site is on

    the NE edge of the city, close to the shore and on the

    western side of Anaga Avenue (a 4-lane road running

    along the shore). The main data set used in this study

    was collected at this site, where the following mea-

    surements were performed:B PMx mass concentrations. One-minute concentrations of

    PM1, PM2.5 and PM10 have been obtained at this site

    since 2002 by multiplying the aerosol volume concen-

    trations (monitored with an Optical Particle Counter

    OPC GRIMM) by experimentally determined vol-

    ume-to-mass conversion factors. These factors were

    determined by cross correlating the aerosol (PM10 and

    PM2.5) mass (determined by 24-h filter sampling with

    high volume samplers) versus the volume (

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    (B) Gladiolos and Tome Cano are city centre sites located to

    the NWof the industrial area of the city (crude oil refin-

    ery) and to the NW of the motorway (which links the

    city to the northern side of the island; Fig. 1C). At these

    sites measurements of PM10, PM2.5, gaseous pollut-

    ants (CO, NOx, SO2 and O3) and meteorology (wind

    speed and direction, temperature, relative humidity

    and pressure) are continuously performed by following

    standard procedures in air quality networks. Measure-

    ments of PM10 and PM2.5 were performed with beta

    and TEOM instruments, respectively. PM2.5 was not

    monitored at the Tome Cano site.

    Finally, measurements of road traffic intensity (number

    of vehicles h1) were also performed in several parts of the

    city by city council staff. In this article we will only show the

    road traffic intensity at the coastal Anaga Avenue (where

    the SCO site is located).

    3. Results and discussion

    During the intensive field measurement campaign,

    mean concentrations of 24 mg m3 of PM10, 14 mg m3 of

    PM2.5, 9 mg m3 of PM1, 1.9 mg m3 of BC and 26305

    cm3 of N3 were recorded at the urban background SCO

    site (Santa Cruz Observatory), 46 mg m3 of PM10 at TC

    (Tome Cano) and 43 mg m3 of PM10 and 13 mg m3 of

    PM2.5 at GL (Gladiolos) were recorded at the city centre

    sites. These mean PMx concentrations are slightly lower

    than the annual mean PMx concentrations typically

    recorded in this city because Saharan dust events (the

    main cause of high PMx concentrations in this city; Viana

    et al., 2002) did not occur during our campaign. Thesemean PMx concentrations are within the range of those

    typically observed in mid European cities (Harrison and

    Jones, 2005; Puustinen et al., 2007; Rodrguez et al.,

    2007; Ruuskanen et al., 2001).

    3.1. Mean daily evolution of aerosols

    The urban scale transport of air pollutants in Santa Cruz

    de Tenerife is mainly driven by breeze circulation (Fig. 1B

    and C). This breeze is characterised by inland (westward)

    airflows during daylight (34 m s1) and a slight seaward

    (eastward) airflowat night (w1 m s1). Inland breeze blow-

    ing started at 08:00 and was characterised by an abrupt

    shift in wind direction. Fig. 2 displays the regular daily evo-

    lution of the road traffic intensity and the particle and some

    gaseous pollutant concentrations at the SCO coastal

    (Fig. 2AF), TC and GL city centre (Fig. 2GI) sites.

    At the SCO coastal site, particle (PMx, BC and N3)and CO

    concentrations exhibited a maximum during the morning

    rush hours of working days, and a subsequent decrease

    (09:0019:00) associated with the easterly entry of marine

    air (Fig. 2AF). At night, a smooth increase in the PMx con-

    centrations, associated with slight westerly winds bringing

    air masses from the city centre, was observed at SCO.

    At the TC and GL city centre sites, after the maximum in

    the NO and PMx concentrations recorded during the

    morning rush hours, a decrease in the PMx concentrations

    such as that described above at SCO (09:0019:00) was not

    observed (Fig. 2GI). However, PM10 and PM2.5 at TC and

    GL showed an increasing trend until 21:00 (local time).

    This contrasting behaviour between the PMx concentra-

    tions at the coastal (SCO) and city centre (TC and GL) sites

    is a consequence of the easterly inland breeze blowing dur-

    ing daylight, which prompts the entry of clean marine air

    masses along the coast and favours the inland transport of

    the pollutants (emitted in the eastern part of the city) to the

    city centre. This is one of the reasons because PM10 con-

    centrations are much lower at SCO coastal than at TC and

    GL city centre sites. In fact, this daylight breeze results in

    the inland transport of the (refinery) SO2 plumes, giving

    rise to higher SO2 concentrations during daylight than at

    night at the TC and GL city centre sites (Fig. 2GI).

    At the SCO coastal site, N3 and BC concentrations also

    exhibited well defined daily cycles (Fig. 2AC). During

    working days, N3 and BC presented a maximum during

    the morning rush hours. The morning maximum in the

    vehicles h1/wind speed ratio indicates that the morning

    maximum in the particle concentration is favoured by the

    coupled effects of an increase in the road traffic intensity

    and low wind speed in the morning (owing to the fact

    that the inland breeze has not yet started blowing). Observe

    that the daily evolution of N3 and BC during weekdays is

    different from that recorded at weekends because of the

    change in road traffic patterns. This daily evolution in num-

    ber concentration is similar to that typically observed in

    other cities (e.g.Wehner and Wiedensohler, 2003; Charron

    and Harrison, 2003; Rodrguez et al., 2007). In Helsinki and

    Liepzig, a similar daily evolution in the black carbon mass

    and soot number concentrations has been observed,

    respectively (Pakkanen et al., 2000; Rose et al., 2006).

    3.2. Processes af fecting urban coastal aerosol concentrations

    The relationship between road traffic intensity,

    meteorology and particle concentration at SCO (coastal

    urban background site) was examined using Principal

    Component Analysis (PCA) followed by a varimax rota-

    tion. This analysis was performed at several times of

    the day: morning (07:0009:00), central daylight

    (11:0017:00) and night (00:0005:00). Three principal

    components, accounting for 81, 66 and 72% of the total

    variance for the three daytime periods selected, were

    found (Table 1):

    B principal component 1 is positively correlated with PMx

    and BC and negatively correlated with wind speed.

    The fact that this component does not exhibit a signifi-

    cant correlation with road traffic intensity (number of

    vehicles h1) indicates that fresh road traffic emissions

    do not exhibit a major influence on PMx variance. The

    significant negative factor loading of wind speed indi-

    cates that this component accounts for the influence

    on the aerosol mass (BC and PMx), of the dilution and

    the air mass renovation prompted by wind blowing

    over the study city. The negative association of the N3/

    BC ratio in this component will be discussed later.

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    B principal component 2 is positively correlated with road

    traffic intensity, BC and N3. This component represents

    the influence of fresh vehicle exhaust emissions on the

    particle concentration.

    B principal component 3 is present during daylight (i.e.

    morning rush hours 07:0009:00 and central daylight

    period 11:0017:00). The positive correlation of the

    N3/BC ratio and solar radiation intensity suggests that

    nucleation of photo-oxidized vapours contributes to in-

    creasing the above ratio by enhancing new particle for-

    mation in ambient air. Further details are provided

    below.

    3.3. Influence of wind speed

    The results of the PCA shown above indicate that wind

    speed exerts: (1) a major influence on PMx, (2) a moderate

    influence on BC and (3) a relatively low influence on N3. In

    fact, wind speed exhibited Pearsons correlation coefficients

    (r) of0.50, 0.44, 0.41, 0.33 and 0.0 with PM2.510,

    PM2.5, PM1, BC and N3, respectively (values calculated using

    3092 10-min observations). These results are corroborated

    when analysing the particle concentration versus wind

    speed plots shown in Fig. 3. The fact that high N3 concentra-

    tions (>45103 cm3) may still be recorded under high

    wind speed conditions (>5 m s1) may be accounted for by

    new particle formation processes. At a roadside site in Lon-

    don, Charron and Harrison (2003) found that increases in

    wind speed produced much higher decreases in the concen-

    tration of accumulation mode particles (0.11 mm) than in

    the concentration of nucleation mode particles (

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    This behaviour is not observed for PM2.5 and PM1 (Fig. 4C1

    and D1). During the morning, the PM2.510 concentrations

    also tend to increase when road traffic intensity increases,

    this being most probably due to road dust re-suspension

    (Fig. 4E1).

    The much lower direct influence of the road traffic

    emissions in PM2.5 and PM1 (Fig. 4C1 and D1) than in N3

    and BC (Fig. 4A1 and B1) may be accounted for by the com-

    ing into force of the European Standards EURO 14 (pro-

    gressively since 1992) for vehicle exhaust emissions.

    Because these standards are established in terms of parti-

    cle mass (g km1), they have decreased the emissions of

    accumulation (0.11 mm) and coarse (>1 mm) mode parti-

    cles, which are the main contributors to PMx. In contrast,

    N3 and BC tend to increase when the road traffic intensity

    increases. This is due to the fact that vehicle exhaust mostly

    emits ultrafine and soot particles and these are the main

    contributors to N3 and BC (Burtscher, 2005; Harris and

    Maricq, 2001; Rose et al., 2006).

    Although BC concentrations tend to increase when road

    traffic intensity increases, different BC concentrations are

    observed for a given number of vehicles h1 bin at different

    times of the day (Fig. 4A1). For example, a road traffic inten-

    sity within the range of 11001200 vehicles h1 is associ-

    ated with 3.7 mgBC m3 during the 07:0009:00 period

    and with 1.5 mgBC m3 during the 11:0017:00 period.

    The lower BC concentrations during the 11:0017:00 pe-

    riod are a consequence of the higher wind speeds during

    that period of daylight (because of the inland breeze blow-

    ing). For this reason we have normalized the road traffic in-

    tensity data by dividing them by wind speed (Fig. 4A3).

    Observe how BC concentrations tend to increase in

    a more regular way (monotonic growth) when increasing

    the vehicles h1/wind speed ratio than when increasing

    the vehicles h1 ratio (Fig. 4A1 and A3). The results show

    how increases in 200 vehicles h1 m1 s1 are associated

    with BC increases of about 0.50 0.29 mgBC m3 (on aver-

    age) at any time of the day.

    This analysis of particle concentration versus vehi-

    cles h1/windspeed was also applied tothe PMx andN3con-

    centrations (Fig. 4A3F3). The most important results are:

    (1) N3 also exhibits an increasing trend with the vehi-

    cles h1/wind speed ratio of about 3250 2395 cm3

    every 200 vehicles h1 m.s1 during the 07:0009:00

    period and of about 65231437 cm3 every 200 vehi-

    cles h1 m.s1 in the 11:0017:00 period. These higher

    values in the 11:0017:00 period in comparison with

    the 07:0009:00 period suggest an enhancement in

    the particle formation processes at noon and during

    the afternoon. This interpretation is supported by the

    results shown in the following section.

    (2) PM2.5 and PM1 do not exhibit a strong association with

    the vehicles h1/wind speed ratio (as that described for

    BC and N3).

    (3) PM2.510 exhibits a clearly increasing trend of about

    1.20 0.90 mgPM2.510 m3 every 200 vehicles h1

    m.s1 during the morning rush hours (07:0009:00),

    most probably due to road dust re-suspension. The

    weaker association observed during the 11:0017:00

    period (Fig. 4E3) is probably due to the influence of

    sea salt transported inland during daylight.

    3.5. The numbertoblack carbon ratios

    The relationship between N3 and BC concentrations at

    the SCO site has been used to identify periods of enhance-

    ment in the new particle formation rates, which would lead

    to an increase in the N3/BC ratio. At SCO, N3 and BC

    exhibited a significant correlation because of the vehicle

    exhaust emissions: r0.70 during the whole measure-

    ments campaign (based on 3092 10-min averages data).

    When plotting the N3 versus BC data, it can clearly be ob-

    served that all points are comprised between two well

    defined borders with slopes (S) Smin 4.8 106 parti-

    cles ngBC1 and Smax 47106 particles ngBC1, repre-

    senting the minimum and maximum N3/BC ratios

    observed in ambient air at the SCO site, respectively

    (Fig. 5). The fact that the N3 versus BC data are comprised

    between these two slopes is observed at any time of the

    day. For the periods 00:0005:00, 07:0009:00 and

    11:0017:00, Smin and Smax exhibit values of 4.5, 4.9 and

    8.1106 particles ngBC1 and 48, 43 and 57 parti-

    cles ngBC1, respectively (plots not shown for the sake of

    brevity). The fact that the slope Smin is much higher during

    the central part of daylight, indicates that: (1) the slope Sminis strongly related to the minimum contribution of the ve-

    hicle exhaust emissions to the particle number

    Table 1

    Factor loading of the Principal Components Analysis performed with data from selected periods

    Morning rush hours (07:0 009:0 0) Central daylight (11:0 017:0 0) Night (0 0:0 005:0 0)

    PC 1 PC 2 PC 3 PC 1 PC 2 PC 3 PC 1 PC 2

    Vehicles h1 0.11 0.89 0.14 0.29 0.51 0.04 0.01 0.85

    BC 0.56 0.70 0.33 0.39 0.82 0.22 0.75 0.59

    N3 0.17 0.90 0.07 0.32 0.81 0.28 0.30 0.80

    N3/BC 0.50 0.05 0.61 0.23 0.18 0.77 0.77 0.04

    PM1 0.95 0.06 0.07 0.86 0.27 0.08 0.86 0.36PM2.5 0.96 0.04 0.08 0.89 0.21 0.05 0.86 0.37

    PM2.510 0.88 0.16 0.08 0.52 0.16 0.55 0.85 0.46

    Wind speed 0.42 0.15 0.81 0.63 0.07 0.12 0.49 0.09

    Radiation 0.24 0.03 0.73 0.08 0.20 0.72

    Explained variance 38% 24% 19% 29% 20% 17% 46% 26%

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    concentration (minimum amount of particles emitted and

    formed during the dilution and cooling of exhaust per

    nanogram of BC emitted by the vehicle exhaust), and (2)

    there is an enhancement in the new particle formation

    rates during daylight resulting in a higher N3/BC ratio

    (4.9106 particles ngBC1 during the 07:0009:00 period

    and 8.1106 particles ngBC1 during the 11:0017:00 pe-

    riod on average; Fig. 6). Observe in Fig. 6 how the N3/BC

    ratio exhibits a daily evolution with a maximum during

    daylight. Previous studies have shown that enhancements

    in the new particle formation rates during the dilution

    and cooling of the vehicle exhaust are favoured by low am-

    bient air temperature (e.g. Olivares et al., 2007) and/or low

    wind speed leading to less dilution (Casati et al., 2007).

    However, these two reasons are not plausible at SCO, where

    the highest N3/BC ratios are observed during the period of

    highest temperature and wind speed 11:0017:00 (Fig. 6).

    At SCO the N3/BC ratio reaches the highest values during

    the noon and afternoon period when:

    (1) solar radiation intensity reaches the highest values. In

    fact, in the PCA discussed above, it was shown how

    Principal Component 3 is correlated with the N3/BC ra-

    tio and the solar radiation (PC 3 in Table 1),

    (2) PM1 and PM2.5 concentrations (where most of the

    aerosol surface area is comprised) are minima (Figs. 2

    and 6). The fact that the N3/BC ratio exhibited a much

    higher anti-correlation with PM1 and PM2.5 than

    with PM2.510 during the 11:0017:00 period (plot

    not shown), suggests a more active role of the accumu-

    lation mode particles (which typically accounts for

    most of the aerosol surface area) as condensation sink

    for the aerosol gaseous precursors,

    (3) it is positively correlated with wind speed for wind

    speed values between 0 and 4 m s1 (Figs. 3E and 4F3).

    These features suggest that, in additionto thenew particle

    formation during the dilution and cooling of the vehicle ex-

    haust, there is a non-negligible contribution to N3 concentra-

    tions due to new particle formation in ambient air. In fact, the

    features described above fit very well with those of the new

    particle formation in ambient air described by Boy and Kul-

    mala (2002), Rodrguez et al. (2005) and Hamed et al.

    (2007). The behaviour observed at the SCO site indicates

    that the decrease in PM1 and PM2.5 concentrations, promp-

    ted by the increase in wind speed (due to the inland breeze

    blowing), resultsin a decrease in theaerosol surface areacon-

    centrations. This would favour nucleation, rather than con-

    densation onto pre-existing particles, for those aerosol

    gaseous precursors formed by photo-oxidation processes.

    Observe in Fig. 6 how the daily variation of the N3/BC ratio

    is much better modulated by the daily evolution of the in-

    verse of PM1 (which typically comprises most of the aerosol

    surface) thanby the daily evolution of PM2.5101. Anexam-

    ple of one of these events (8th April 2006) is shown in Fig. 7:

    observe the correlated increases in the N3/BC ratio and in so-

    lar radiation intensity from 10:00 to 16:00. This contribution

    to N3 due to nucleationin ambient airduring thecentral part

    of the daylight accounts for: (1) the faster decrease in the BC

    than in the N3 concentrations after the morning rush hours

    (Fig. 2 A), and (2) the higher increase in N3 concentrations

    for every 200 vehicles h1 m.s1 bin during the 11:00

    17:00 period than during the 07:0009:00 period (described

    above; 3250 cm3 during the 07:0009:00 and about

    6523 cm3 during the 11:0017:00 periods).

    0

    40

    20

    6 8

    N3/BC,106,

    /ng

    0

    6

    0

    20

    10

    PM2.5-10,g/m3

    0

    40

    20

    PM2.5,g/m3

    0

    90

    45

    N

    3103,cm-3

    y = 1.87x-0.38

    R2 = 0.120

    y = 14.9x-0.21

    R2

    = 0.323

    y = 5.68x-0.59

    R2 = 0.524

    20 4 10

    wind speed, m/s

    12

    BC,g/m3

    A

    B

    C

    D

    E

    Fig. 3. Concentration of particles (AD) and N3/BC ratio (E) versus wind

    speed at the SCO site. Red dots and line in plots D and E represent the

    mean N3 and N3/BC values for each 1 m s1 bin.

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    3.6. Day-to-day particle events

    Fig. 8 shows the hourly BC, N3 and PMx concentrations

    at the SCO site and the road traffic intensity during a period

    of the measurement campaign. Fig. 9 shows the median of

    the BC, N3 and PMx concentrations for each wind direction

    for the 07:0009:00,11:0017:00 and 00:0005:00 periods

    during all the measurement campaigns. These data (Figs. 8

    and 9) clearly illustrate how N3, BC and PMx are influenced

    in different ways by breeze circulation, vehicle exhaust

    emissions and ageing processes given that:

    1. high BC and N3 concentrations are recorded during the

    morning rush hours due to fresh vehicle exhaust emis-

    sions (07:0009:00; Figs. 8A,B and 9A,B), the highest be-

    ing BC and N3 concentrations registered when wind

    blows from the city centre (Southwest; Fig. 9A1) or

    from the coastal Anaga Avenue (East; Fig. 8A1);

    2. high N3 concentrations (associated with high N3/BC ra-

    tios) during the central part of daylight (11:0017:00)

    are associated with easterly winds (inland breeze;

    Fig. 9B2) due to the above described new particle forma-

    tion in ambient air (Figs. 6 and 9A2,B2). Examples of

    wind speed, m/svehiclesh-1 vehiclesh-1/ wind speed, s/m

    4

    8

    0

    BC,g/m3

    2400

    2000

    0

    10

    5

    0

    20

    PM2.5-10,g/m3

    10

    15

    0

    PM2.5,g/m3

    PM1,g/m3

    0-5h

    7-9h

    11-17h

    C2 C3C1

    N3/BC,

    106/ng

    0

    10

    20

    F2 F3F1

    A2 A3A1

    D2 D3D1

    0

    30

    60

    103N3,m-3

    B2 B3B1

    1200

    1600

    0

    4 6 800 4

    00

    800

    1200

    1600

    2000

    2400

    E2 E3E1

    10

    800

    20

    Fig. 4. Particle concentration and N3/BC ratio averaged for each 100 vehicles h1 bin (A1F1), for each 1 ms1 bin (A2F2) and for each 200 vehicles h1

    bin (A3F3).

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    these events occurred during the periods 2224 and 28

    31 March 2006, when N3/BC ratios of 1525 106 parti-

    cles ngBC1 and 3 nm) and PMx (PM1, PM2.5 and PM2.510) concen-

    trations. BC and N3 concentrations are greatly influenced

    by fresh vehicle exhaust emissions and exhibit an increas-

    ing trend when the road traffic intensity (vehicles h1)/

    wind speed ratio increases. In contrast, PMx (specially

    PM1 and PM2.5) reaches the highest values at night due

    to the seaward transport of aged particulate pollutants to

    the shore, and the lowest values during daylight due to

    the inland entry of clean marine air. Although N3 and BC

    concentrations exhibit a significant correlation throughout

    0

    20

    500

    1000

    10

    30

    4 8 12 16 200

    globalradiation,w

    /m2

    time of day

    0

    N3 / BC, 106/ng

    50PM2.5-10-1, m3/g

    wind speed, m/s

    125PM1-1, m3/g

    Fig. 6. Daily mean cycle (hourly averaged values) of the global radiation,

    wind speed, the N3/BC ratio, and the inverse of the PM1 (PM1

    1

    ) andPM2.510 (PM2.5101) concentrations.

    0

    35103

    10BC,ng/m3

    70103

    N3,cm-3

    500

    0

    35103

    70103

    1000

    0

    Radiation,w/m2

    0

    15

    30 N3/BC,106/ng

    6 12 18

    time of day

    0

    A

    B

    Fig. 7. 10-min averaged values of the solar radiation, N3/BC ratio, black car-

    bon (BC) and number N3 concentrations at the SCO site during 8th April

    2006.

    120

    50103

    0

    100103

    BC, g/m3

    N3,cm-3

    Smin

    Smax

    6

    Fig. 5. Hourly averaged values of the particle number N3 versus particle

    black carbon (BC) concentrations at the SCO site.

    S. Rodrguez et al. / Atmospheric Environment 42 (2008) 65236534 6531

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    the whole day, the N3/BC ratio experiences a daily evolu-

    tion correlated with that of the solar irradiance and wind

    speed, in such a way that high N3 concentrations associated

    with high N3/BC ratios and high solar irradiance conditions

    are recorded during the daylight inland breeze period

    due to an enhancement of some new particle formation

    processes. The analysis performed indicates that this en-

    hancement in the new particle formation processes is

    strongly related to the nucleation of photo-oxidized va-pours under the relatively low PMx (and consequently

    low aerosol surface area) concentrations prompted by the

    inland entry of clean marine air due to the daylight breeze

    blowing. The statistical tools used in this study corroborate

    the association between BC and N3 with road traffic inten-

    sity (fresh emissions), PMx and wind speed1 and N3/

    BC ratio and solar radiation (enhancement in the new par-

    ticle formation due to photo-oxidation processes).

    Although it is known that new particle formation due to

    photo-oxidation of aerosol gaseous precursors may occur

    in the urban atmosphere (e.g. Wehner and Wiedensohler,

    2003; Kulmala et al., 2004; Qian et al., 2007), most studieson urban ultrafine particles are currently focused mainly

    on primary vehicleexhaust emissions. The resultsobtained

    here indicate that this contribution due to photo-chemically

    22 23 24 25 26 27 121 328 229 3130

    AprilMarch

    1000

    vehicles/h

    0

    2000 B

    0

    80103

    40103

    N3,cm-3

    SCO

    0

    60

    30

    2000

    0

    1000

    C

    g/m3

    PM2.5

    PM2.5-10

    PM10

    PM1

    1000

    0

    2000 A

    0

    10

    5

    BC,g/m3

    Fig. 8. Hourly mean values of road traffic intensity at the coastal Anaga Avenue (vehicles h1) and of the particle BC, N3 and PMx concentrations at the SCO site

    from March 21st to April 3rd 2006.

    BC

    6

    12

    6

    12

    0-5h

    7-9h

    11-17hcentral

    daylight

    night

    morning

    N PM2.5 PM2.5-10

    10

    20

    PM1

    10

    20

    20

    40

    10

    20

    20

    40

    20

    40

    10

    20

    10

    20

    10

    20

    6

    12

    N3 x103

    35

    70

    35

    70

    35

    70B2

    B3

    B1

    D2

    D3

    D1

    C2

    C3

    C1

    E2

    E3

    E1

    A2

    A3

    A1

    Fig. 9. Hourly mean concentrations of the particle BC, N3 and PMx for each wind direction at several times of the day at the SCO site.

    S. Rodrguez et al. / Atmospheric Environment 42 (2008) 652365346532

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    induced nucleation may significantly contribute to the urban

    ultrafine particle concentration.

    The results of this study show how the strong changes in

    daylight to night meteorological conditions (which in-

    cludes inland entries of clean air during daylight) exert

    a great/major influence on the complex relationship be-

    tween the number concentration and other aerosol con-

    centration metrics. This, and other processes, not yet well

    characterised, may contribute to the large spatial variability

    in the particle number concentration as described by Hoek

    et al. (2008).

    According to Kulmala et al. (2004), new particle forma-

    tion rates in a coastal environment as high as those in indus-

    trial plumes are frequently recorded. This could, in part, be

    due tothefactthat someof the factors which may favournu-

    cleation are present in the coastal environment: (i) enough

    high relative humidity to favour binary H2OH2SO4 nucle-

    ation (Easter and Peter, 1994; Olivares et al., 2007), (ii) rela-

    tively clean air conditions (low aerosol surface area

    concentration) due to the marine air entries) and (iii) the

    mixingof twoair parcels with differenttemperature anddif-

    ferent relative humidities (Nilsson and Kulmala, 1998).

    Acknowledgements

    This study was financed by the Ministry for the Environ-

    ment of Spain (Direccion General de Calidad Ambiental;

    Project B026/2007/3-10.1: Evaluacion integral del impacto

    de las emisiones de partculas de los automoviles en la cal-

    idad del aire urbano). The Council of Santa Cruz de Tener-

    ife and the Departments of Environmental Health and of

    the Environment of the Canary Islands Government also

    contributed to this study. Measurements at SCO are per-

    formed within the framework of the GURME (GAW) pro-gram. Part of this study was performed into the

    framework of the project- GRACCIE (CONSOLIDER

    INGENIO; Ministry of Education and Culture of Spain).

    References

    Boy, M., Kulmala, M., 2002. Nucleation events in the continental boundarylayer: influence of physical and meteorological parameters. Atmo-spheric Chemistry and Physics 2, 116.

    Burtscher, H., 2005. Physical characterization of particulate emissionsfrom diesel engines: a review. Journal of Aerosol Science 36, 896932.

    Cabada, J.C., Rees, S., Takahama, S., Khlystov, S.A., Pandis, S.N., Davidson, C.I., Robinson, A.L., 2004. Mass size distributions and size resolvedchemical composition of fine particulate matter at the Pittsburgh

    supersite. Atmospheric Environment 38, 31273141.

    Casati, R., Scheer, V., Vogt, R., Benter, T., 2007. Measurement of nucleationand soot mode particle emission from a diesel passenger car in realworld and laboratory in situ dilution. Atmospheric Environment 41,21252135.

    Charron, A., Harrison, R.M., 2003. Primary particle formation from vehicleemissions during exhaust dilution in the roadside atmosphere. Atmo-spheric Environment 37, 41094119.

    Dockery, D., Pope, A., 1996. Epidemiology of acute health effects: sum-mary of time-series studies. In: Wilson, R., Spengler, J.D. (Eds.), Parti-cles in Our Air: Concentration and Health Effects. Harvard University

    Press, Cambridge, MA, USA, pp. 123147.Easter, R.C., Peters, L.K., 1994. Binary homogeneous nucleation: tempera-

    ture and relative humidity fluctuations, nonlinearity and aspects ofnew particle production in the atmosphere. Journal of AppliedMeteorology 33, 775784.

    Guerra, J.C., Rodrguez, S., Arencibia, M.T., Garca, M.D., 2004. Study on theformation and transport of ozone in relation to the air quality man-agement and vegetation protection in Tenerife (Canary Islands). Che-mosphere 56, 11571167.

    Hamed, A., Joutsensaari, J., Mikkonen, S., Sogacheva, L., Dal Maso, M.,Kulmala, M., Cavalli, F., Fuzzi, S., Facchini, M.C., Decesari, S.,Mircea, M., Lehtinen, K.E.J., Laaksonen, A., 2007. Nucleation andgrowth of new particles in Po Valley, Italy. Atmospheric ChemistryPhysics 7, 355376.

    Harris, J.S., Maricq, M.M., 2001. Signature size distributions for diesel andgasoline engine exhaust particulate matter. Journal of Aerosol Science32, 749764.

    Harrison, R.M., Jones, A.M., 2005. Multisite study of particle number con-centrations in urban air. Environmental Science and Technology 39,60636070.

    Highwood, E.J., Kinnersley, R.P., 2006. When smoke gets in your eyes:the multiple impact of atmospheric black carbon on climate, airquality and health. Environment International 32, 560566. Reviewarticle.

    Hoek, G., Kos, G., Harrison, R., de Hartog, J., Meliefste, K., ten Brink, H.,Katsouyanni, K., Karakatsani, A., Lianou, M., Kotronarou, A.,Kavouras, I., Pekkanen, J., Vallius, M., Kulmala, M., Puustinen, A.,Thomas, S., Meddings, C., Ayres, J., van Wijnen, J., Hameri, K., 2008. In-dooroutdoor relationships of particle number and mass in four Eu-ropean cities. Atmospheric Environment 42, 156169.

    Ketzel, M., WhlinKristensson, A., Swietlicki, E., Berkowicz, R., Nielsen,O.J., Palmgren, F., 2004. Particle size distribution and particle massmeasurements at urban, near-city and rural level in the Copenhagenarea and Southern Sweden. Atmospheric Chemistry and Physics 4,

    281292.Kulmala, M., Petaja, T., Monkkonen, P., Koponen, I.K., Dal Maso, M.,

    Aalto, P.P., Lehtinen, K.E.J., Kerminen, V.M., 2005. On the growth ofnucleation mode particles: source rates of condensable vapor in pol-luted and clean environments. Atmospheric Chemistry and Physics 5,409416.

    Kulmala, M., Vehkamaki, H., Petaja, T., Dal Maso, M., Lauria, A.,Kerminen, V.M., Birmili, W., McMurry, P.H., 2004. Formation andgrowth rates of ultrafine atmospheric particles: a review of observa-tions. Journal of Aerosol Science 35, 143176.

    Monkkonen, P., Umac, R., Srinivasan, D., Koponen, I.K., Lehtinen, K.E.J.,Hameri, K., Suresh, R., Sharma, V.P., Kulmala, M., 2004. Relationshipand variations of aerosol number and PM10 mass concentrations ina highly polluted urban environmentdNew Delhi, India. AtmosphericEnvironment 38, 425433.

    Nilsson, E.D., Kulmala, M., 1998. The potential for atmospheric mixingprocesses to enhance the binary nucleation rate. Journal of Geophys-

    ical Research 103, 13811389.

    50

    0

    100

    20 400

    C PM10

    20

    0

    40

    500 100

    A PM2.5

    g/m3

    PMx SCO, g/m3

    25

    0

    50

    DPM2.5-10

    y=0.78x + 21.3

    r2= 0.54

    500 100

    TC vs. SCOGL vs. SCO GL vs. SCO

    50

    0

    100GL vs. SCO

    B PM10

    250 50

    y=1.2x + 17.7

    r2= 0.89

    y=0.9x + 20.7

    r2= 0.82

    y=1.0x + 1.0

    r2= 0.88

    Fig. 10. Daily mean concentrations of PM2.5, PM2.510 and PM10 at city centre sites (GL and TC) versus at SCO coastal urban background.

    S. Rodrguez et al. / Atmospheric Environment 42 (2008) 65236534 6533

  • 7/29/2019 Influence of Sea Breeze_BC, PM2.5, PM10

    12/12

    Olivares, G., Johansson, C., Strom, J., Hansson, H.C., 2007. The role of am-bient temperature for particle number concentrations in a street can-yon. Atmospheric Environment 41, 21452155.

    Pakkanen, T.A., Kerminen, V.M., Ojanen, C.H., Hillamo, R.E., Aarnio, P.,Koskentalo, T., 2000. Atmospheric black carbon in Helsinki. Atmo-spheric Environment 34, 14971506.

    Peters, A., Wichmann, H.E., Tuch, T., Heinrich, J., Heyder, J., 1997. Respira-tory effects are associated with the number of ultrafine particles.American Journal of Respiratory and Critical Care Medicine 155,13761383.

    Puustinen, A., Hameri, K., Pekkanen, J., Kulmala, M., de Hartog, J.,Meliefste, K., ten Brink, H., Kos, G., Katsouyanni, K., Karakatsani, A.,Kotronarou, A., Kavouras, I., Meddings, G., Thomas, S., Harrison, R.,Ayres, J.G., van der Zee, S., Hoek, G., 2007. Spatial variation of particlenumber and mass over four European cities. Atmospheric Environ-ment 41, 66226636.

    Qian, S., Sakurai, H., McMurry, P.H., 2007. Characteristics of regional nu-cleation events in Urban East St. Louis. Atmospheric Environment41, 41194127.

    Rodrguez, S., Van Dingenen, R., Putaud, J.P., Martins-Dos Santos, S.,Roselli, D., 2005. Nucleation and growth of new particles in the ruralatmosphere of Northern ItalydRelationship to air quality monitoring.Atmospheric Environment 39, 67346746.

    Rodrguez, S., Van Dingenen, R., Putaud, J.P., DellAcqua, A., Pey, J.,Querol, X., Alastuey, A., Chenery, S., Kin-Fai, H., Harrison, R.M.,Tardivo, R., Scarnato, B., Gianelle, V., 2007. A study on the relationship

    between mass concentrations, chemistry and number size distribu-tion of urban fine aerosols in Milan, Barcelona & London. AtmosphericChemistry and Physics 7, 22172232.

    Rose, D., Wehner, B., Ketzel, M., Engler, C., Voigtlander, J., Tuch, T.,Wiedensohler, A., 2006. Atmospheric number size distributions ofsoot particles and estimation of emission factors. Atmospheric Chem-istry and Physics 6, 10211031.

    Ruuskanen, R., Tuch, Th., Ten Brink, H., Peters, A., Khlystov, A., Mirme, A.,Kos, G.P.A., Brunekreef, B., Wichmann, H.E., Buzorius, G., Vallius, M.,Kreyling, W.G., Pekkanem, J., 2001. Concentrations of ultrafine, fine

    and PM2.5 particles in three European cities. Atmospheric Environ-ment 35, 37293738.

    Second Position Paper on Particulate Matter, 2004. CAFE working groupon particulate matter (accessed 20.12.04).

    Viana, M., Querol, X., Alastuey, A., Cuevas, E., Rodrguez, S., 2002. Influ-ence of African dust on the levels of atmospheric particulates in theCanary Islands air quality network. Atmospheric Environment 36,58615875.

    Viana, M., Perez, C., Querol, X., Alastuey, A., Nickovic, S., Baldasano, J.M.,2005. Spatial and temporal variability of PM levels and compositionin a complex summer atmospheric scenario in Barcelona (NE Spain).Atmospheric Environment 39, 53435361.

    Wehner, B., Wiedensohler, A., 2003. Long term measurements of submi-crometer urban aerosols: statistical analysis for correlations with me-teorological conditions and trace gases. Atmospheric Chemistry andPhysics 3, 867879.

    S. Rodrguez et al. / Atmospheric Environment 42 (2008) 652365346534