A methodology for the quantification of the net African dust load in air quality monitoring networks

Escudero, Miguel; Querol, Xavier; Pey, Jorge; Alastuey, Andrés; Pérez, Noemí; Ferreira, Francisco; Garcı́a-Alonso, Susana; Rodrı́guez, Sergio; Cuevas, E.

doi:10.1016/j.atmosenv.2007.04.047

Cited by 193 publications

(160 citation statements)

References 12 publications

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“…However, similar results achieved by the currently used method-ology (Escudero et al, 2007a(Escudero et al, , 2007b and HMMs suggest that further research is needed. It would be interesting to establish how both methodologies (and others) complement each other as HMMs may offer significant information once regimes are defined, namely: (i) net contributions due to different sources; (ii) contributions to the annual PM10 mean from every regime; and (iii) the probability of change among regimes.…”

Section: Study Of the Regimes Over Timesupporting

confidence: 54%

“…As can be appreciated, the estimation results are similar. Those authors use a methodology based on the assessment of PM10 concentration TS at background sites by means of the calculation of the monthly mobile 40th percentile (Escudero et al, 2007a;Querol et al, 2013aQuerol et al, , 2013b. This latter method is outlined in Section 3.4.…”

Section: Behaviour Of Regimes In the Iberian Peninsula And Archipelagosmentioning

confidence: 99%

“…The first group is considered to be based on basic numerical data treatment (Belis et al, 2013). It also includes simple time series (TS) modelling of data that may be used, for instance, to estimate natural PM10 contributions from deserts (Escudero et al, 2007a). The second one includes models to simulate aerosol emission formation, transport and deposition, although they are limited by the accuracy of emission inventories, when available.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Time series clustering for estimating particulate matter contributions and its use in quantifying impacts from deserts

Gómez-Losada

Pires

Pino‐Mejías

2015

Atmospheric Environment

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Source apportionment studies use prior exploratory methods that are not purpose-oriented and receptor modelling is based on chemical speciation, requiring costly, time-consuming analyses. Hidden Markov Models (HMMs) are proposed as a routine, exploratory tool to estimate PM10 source contributions. These models were used on annual time series (TS) data from 33 background sites in Spain and Portugal. HMMs enable the creation of groups of PM10 TS observations with similar concentration values, defining the pollutant's regimes of concentration. The results include estimations of source contributions from these regimes, the probability of change among them and their contribution to annual average PM10 concentrations. The annual average Saharan PM10 contribution in the Canary Islands was estimated and compared to other studies. A new procedure for quantifying the wind-blown desert contributions to daily average PM10 concentrations from monitoring sites is proposed. This new procedure seems to correct the net load estimation from deserts achieved with the most frequently used method.

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Section: Study Of the Regimes Over Timesupporting

confidence: 54%

Section: Behaviour Of Regimes In the Iberian Peninsula And Archipelagosmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Time series clustering for estimating particulate matter contributions and its use in quantifying impacts from deserts

Gómez-Losada

Pires

Pino‐Mejías

2015

Atmospheric Environment

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“…The 30-day moving averages of the previous and next 15 days of the regional background concentrations were calculated, excluding days with potential African dust transport. Averages corresponded to 40th percentiles in the case of Porto, Barcelona and Florence (Escudero et al, 2007). In Milan and Athens, a more conservative indicator, the 50th percentile, was selected since it was found to reproduce better PM background concentrations (SEC 2011/208).…”

Section: Quantification Of the Contribution Of Natural Sourcesmentioning

confidence: 99%

AIRUSE-LIFE +: estimation of natural source contributions to urban ambient air PM<sub>10</sub> and PM<sub>2. 5</sub> concentrations in southern Europe – implications to compliance with limit values

et al. 2017

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Abstract. The contribution of natural sources to ambient air particulate matter (PM) concentrations is often not considered; however, it may be significant for certain areas and during specific periods of the year. In the framework of the AIRUSE-LIFE+ project, state-of-the-art methods have been employed for assessing the contribution of major natural sources (African dust, sea salt and forest fires) to PM concentrations, in southern European urban areas. 24 h measurements of PM 10 and PM 2.5 mass and chemical composition were performed over the course of a year in five cities: Porto, Barcelona, Milan, Florence and Athens. Net African dust and sea-salt concentrations were calculated based on the methodologies proposed by the EC (SEC 2011/208). The contribution of uncontrolled forest fires was calculated through receptor modelling. Sensitivity analysis with respect to the calculation of African dust was also performed, in order to identify major parameters affecting the estimated net dust concentrations. African dust contribution to PM concentrations was more pronounced in the eastern Mediterranean, with the mean annual relative contribution to PM 10 decreasing from 21 % in Athens, to 5 % in Florence, and around 2 % in Milan, Barcelona and Porto. The respective contribution to PM 2.5 was calculated equal to 14 % in Athens and from 1.3 to 2.4 % in all other cities. High seasonal variability of contributions was observed, with dust transport events occurring at different periods in the western and eastern Mediterranean basin. Sea salt was mostly related to the coarse mode and also exhibited significant seasonal variability. Sea-salt concentrations were highest in Porto, with average relative contributions equal to 12.3 % for PM 10 . Contributions from uncontrolled forest fires were quantified only for Porto and were low on an annual basis (1.4 and 1.9 % to PM 10 and PM 2.5 , respectively); nevertheless, contributions were greatly increased during events, reaching 20 and 22 % of 24 h PM 10 and PM 2.5 concentrations, respectively.

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“…In their study, dust concentrations are assumed equal to the sum of fine soil and coarse particles using an operational definition adopted from Malm et al (1994Malm et al ( , 2000a. Escudero et al (2007) proposed a method to quantify the daily African dust load by subtracting the daily regional background level from the PM 10 concentration value. Ganor et al (2009) developed and tested an automated dust identification algorithm for monitoring location in Israel.…”

Section: Q Tong Et Al: Long-term Dust Climatology In the Western Usmentioning

confidence: 99%

Long-term dust climatology in the western United States reconstructed from routine aerosol ground monitoring

Tong

Wang

et al. 2012

Atmos. Chem. Phys.

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Abstract. This study introduces an observation-based dust identification approach and applies it to reconstruct longterm dust climatology in the western United States. Longterm dust climatology is important for quantifying the effects of atmospheric aerosols on regional and global climate. Although many routine aerosol monitoring networks exist, it is often difficult to obtain dust records from these networks, because these monitors are either deployed far away from dust active regions (most likely collocated with dense population) or contaminated by anthropogenic sources and other natural sources, such as wildfires and vegetation detritus. Here we propose an approach to identify local dust events relying solely on aerosol mass and composition from general-purpose aerosol measurements. Through analyzing the chemical and physical characteristics of aerosol observations during satellite-detected dust episodes, we select five indicators to be used to identify local dust records: (1) high PM 10 concentrations; (2) low PM 2.5 /PM 10 ratio; (3) higher concentrations and percentage of crustal elements; (4) lower percentage of anthropogenic pollutants; and (5) low enrichment factors of anthropogenic elements. After establishing these identification criteria, we conduct hierarchical cluster analysis for all validated aerosol measurement data over 68 IMPROVE sites in the western United States. A total of 182 local dust events were identified over 30 of the 68 locations from 2000 to 2007. These locations are either close to the four US Deserts, namely the Great Basin Desert, the Mojave Desert, the Sonoran Desert, and the Chihuahuan Desert, or in the high wind power region (Colorado). During the eight-year study period, the total number of dust events displays an interesting four-year activity cycle (one in 2000- The monthly frequency of dust events shows a peak from March to July and a second peak in autumn from September to November. The large quantity of dust events occurring in summertime also suggests the prevailing impact of windblown dust across the year. This seasonal variation is consistent with previous model simulations over the United States.

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A methodology for the quantification of the net African dust load in air quality monitoring networks

Cited by 193 publications

References 12 publications

Time series clustering for estimating particulate matter contributions and its use in quantifying impacts from deserts

Time series clustering for estimating particulate matter contributions and its use in quantifying impacts from deserts

AIRUSE-LIFE +: estimation of natural source contributions to urban ambient air PM<sub>10</sub> and PM<sub>2. 5</sub> concentrations in southern Europe – implications to compliance with limit values

Long-term dust climatology in the western United States reconstructed from routine aerosol ground monitoring

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A methodology for the quantification of the net African dust load in air quality monitoring networks

Cited by 193 publications

References 12 publications

Time series clustering for estimating particulate matter contributions and its use in quantifying impacts from deserts

Time series clustering for estimating particulate matter contributions and its use in quantifying impacts from deserts

AIRUSE-LIFE +: estimation of natural source contributions to urban ambient air PM&lt;sub&gt;10&lt;/sub&gt; and PM&lt;sub&gt;2. 5&lt;/sub&gt; concentrations in southern Europe – implications to compliance with limit values

Long-term dust climatology in the western United States reconstructed from routine aerosol ground monitoring

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AIRUSE-LIFE +: estimation of natural source contributions to urban ambient air PM<sub>10</sub> and PM<sub>2. 5</sub> concentrations in southern Europe – implications to compliance with limit values