Study of atmospheric particulate matter in Buenos Aires city

Bogo, Horacio; Otero, Marcelo; Castro, Pablo; Ozafrán, M. J.; Kreiner, Andrés J.; Calvo, Ernesto J.; Negri, R. Martı́n

doi:10.1016/s1352-2310(02)00977-9

Cited by 92 publications

(46 citation statements)

References 14 publications

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“…South American cities Rio de Janeiro, Buenos Aires and Sao Paulo were present in the former cluster and showed negative slopes. This is in agreement with issues associated with SO 2 ( additionally CO for Sao Paulo) and PM2.5 levels caused by vehicular and industrial emissions as identified previously (Toledo et al [53], Mage et al [5], Bogo et al [54]). The second cluster shows that cities like Tokyo and London have similar offsets (∼25) as Kolkata and Beijing.…”

Section: Global Trend Of Rsupporting

confidence: 93%

Novel Decomposition Scheme for Characterizing Urban Air Quality with MODIS

2017

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Urban air pollution is one of the most widespread global sustainability problems. Previous research has studied growth or fall of particulate matter (PM) levels using on-ground monitoring stations in urban regions. However, studying this worldwide is difficult because most cities do not have sufficient infrastructure to monitor air quality. Thus, satellite data is increasingly being employed to solve this limitation. In this paper, we use 16 years (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) of aerosol optical depth (AOD) and Angstrom exponent (α) datasets, retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) sensors on the National Aeronautics and Space Administration's (NASA) Terra satellite to study air quality over 60 locations globally. We propose a novel technique, called AirRGB decomposition, to characterize urban air quality by decomposing AOD and α retrievals into 'components' of three distinct scenarios. In the AirRGB decomposition method, using AOD and α dataset three scenarios were investigated: 'R'-high α and high AOD, 'G'-high α and low AOD, and 'B'-low α and low AOD values. These scenarios were mapped and quantified over a triangular red, green and blue color scale. This visualization easily segregates regions having a high concentration of industrial aerosol from only natural aerosols. Our analysis indicates that a sharp divide exists between North American and European cities and Asian cities in terms of baseline pollution and slopes of R and G trends. We found that while pollution in cities in China has started to decrease (e.g., since 2011 for Beijing), it continues to increase in South Asia and Southeast Asia. e.g., R offset of Beijing and New Delhi was 54.98 and 50.43 respectively but R slope was −0.04 and 0.08 respectively. High offset (≥45) and slope (≥0.025) of B for New York, Tokyo, Sydney and Sao Paolo shows that they have clean air, which is still getting better.

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Section: Global Trend Of Rsupporting

confidence: 93%

Novel Decomposition Scheme for Characterizing Urban Air Quality with MODIS

2017

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“…Ion composition in the two daytime samples were similar with those in the rush periods. Because of the their hygroscopic nature, water-soluble components of atmospheric aerosols can change size, composition, number and the lifetime of particles, and increase the solubility of toxic organic compounds (Bogo et al, 2003;Tsitouridou et al, 2003;Castillo et al, 2005;Fang et al, 2006).…”

Section: Pahs Levelsmentioning

confidence: 99%

Characteristics of Traffic-related Emissions: A Case Study in Roadside Ambient Air over Xi’an, China

Shen

Han

Cao

et al. 2010

Aerosol Air Qual. Res.

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Traffic-related emissions were measured at a heavy-traffic roadside in Xi'an at the end of April, 2008 to survey the exposure levels of freshly emitted carbon monoxide (CO), mass and chemical composition (OC, EC, inorganic ions, and PAHs) of PM 10 , and ozone (O 3 ). In general, high levels of mass concentration and chemical species in PM 10 were observed during daily heavy traffic periods (morning, noon, and evening traffic rush hours), especially in the morning traffic rush hour. OC and EC accounted for 9.3% and 3.0% of PM 10 mass, respectively, and the ratios of OC/EC were constant during the heavy traffic periods (with a mean value of 3.2). Water-soluble ions constituted 14.0% of PM 10 and the dominant ionic species were Ca 2+ , SO 4 2-, and NO 3 -in the roadside samples. Re-suspended road dust constituted a large fraction of PM 10 , causing the PM 10 samples to become more alkaline. The concentrations of 12 prior-controlled PAHs revealed the potential high health risk of this roadside area in Xi'an. The diurnal variation in CO and O 3 exhibited a different trend, which indicated that CO level was largely influenced by the instantaneous emission of vehicles while O 3 was closely associated with the overall traffic conditions and meteorological status.

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“…These research studies are focused on topics such as impact assessment of specific sources, characterization of multi-elemental aerosol composition, and source identification through receiver models [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Atmospheric Particulate Matter Variability during 2014 at Buenos Aires City (Argentina) Comparing Ground-Based Measurements and Satellite Data

Ceca

Micheletti

Piacentini

2017

Proceedings of the 2nd International Electronic Conference on Atmospheric Sciences

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Air pollution is a major environmental risk to health. In particular, exposure to high concentrations of small particulates (PM10 and PM2.5) is related to increased mortality and morbidity. In Argentina, only at Buenos Aires city (34.4° S 58.3° W), which together with the surrounding districts accounts for the 30% of the total country population, continuous measurements of air quality are carried out. Though ground-based stations provide very accurate PM concentration values, they have very limited spatial coverage and may not be sufficient to assess the level of population exposure. Satellite-based is a valid alternative to fill these observational gaps. In this work, the MODIS 3 km × 3 km AOD retrievals for 2014, for both Terra and Aqua, were employed to evaluate the spatio-temporal variation of atmospheric aerosols over Buenos Aires and its metropolitan area in a year period. The MODIS AOD dataset is validated using the AOD dataset reported by the CEILAP_BA AERONET station (34.5° S 58.5° W). Satellite data show some areas with higher AOD values throughout the year-period in which no PM monitoring is not actually being carried out. These areas correspond mainly to a west zone within Buenos Aires territory and two other areas, at west and south Buenos Aires districts. Buenos Aires local government and the surrounding districts should make an effort to expand the monitoring network in order to make it representative of the actual exposure to particulate matter of the whole population.

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Study of atmospheric particulate matter in Buenos Aires city

Cited by 92 publications

References 14 publications

Novel Decomposition Scheme for Characterizing Urban Air Quality with MODIS

Novel Decomposition Scheme for Characterizing Urban Air Quality with MODIS

Characteristics of Traffic-related Emissions: A Case Study in Roadside Ambient Air over Xi’an, China

Atmospheric Particulate Matter Variability during 2014 at Buenos Aires City (Argentina) Comparing Ground-Based Measurements and Satellite Data

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