Multiannual assessment of the desert dust impact on air quality in Italy combining PM10 data with physics-based and geostatistical models

Barnaba, Francesca; Romero, Nancy Alvan; Bolignano, Andrea; Basart, Sara; Renzi, Matteo; Stafoggia, Massimo

doi:10.1016/j.envint.2022.107204

Cited by 19 publications

(7 citation statements)

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“…The monthly and seasonal averages of dust-PM 10 (55–220 µg m −3 ) are more homogenous over the country with peak plumes south of GCMA and over Aswan, shown to be mainly influenced by the site type, with enhanced values in more urbanized locations. A similar PM 10 gradient but at lesser magnitudes has affected Italy by atmospheric transport of desert dust from the Northern Africa and the Middle East drylands (Barnaba et al 2022 ). Also, high Saharan-dust PM 10 background levels are recorded in Southern Spain (30 µg m −3 PM 10 as an annual mean for rural areas) and very similar values are recorded in industrial and urban areas (Rodriguez et al 2001 ).…”

Section: Resultsmentioning

confidence: 94%

Spatio-temporal patterns and trends of the air pollution integrating MERRA-2 and in situ air quality data over Egypt (2013–2021)

Masoud

2023

Air Qual Atmos Health

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For best-informed decision-making to improve climate change adaptation and reduce present and future air pollution health hazards, it is essential to identify major trends in spatiotemporal air quality patterns of common air contaminants. This study examined the patterns and trends of SO2, NO2, CO, O3, and particulate matter (PM) air pollutants over 91 monitoring stations in Egypt during 93 months in the August (2013)–April (2021) period. In situ data with their monthly, seasonal, and yearly spatial trends are defined and used to validate the counterpart satellite reanalysis MERRA-2 data. The Mann–Kendall test characterized the seasonal monotonic trends and their Sen’s slope, and annual change rate for both data series. Regression analysis of MERRA-2 against in situ concentrations of SO2 and PM10 revealed underestimation with RMSE values of 13.38 g m−3 and 69.46 g m−3, respectively. Local plumes with variable magnitudes characterized distinct industrial places clarified by patterns of in situ pollutants. As a result of the COVID-19 lockdown, the in situ air pollutants showed a considerable regional decline in the yearly average in 2020 compared to the years before. The in situ air pollutants showed annual trends far more significant than those seen in the MERRA-2 data. The shortcomings of the few and spatiotemporal discontinuities of the in situ contaminants are addressed by MERRA-2 air quality products. The in situ data made trends and magnitudes clear that were hidden in their MERRA-2 counterparts. The results clarified air pollution patterns, trends, and spatial variability over Egypt that are essential for climate risk management and for reducing environmental/health concerns.

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Section: Resultsmentioning

confidence: 94%

Spatio-temporal patterns and trends of the air pollution integrating MERRA-2 and in situ air quality data over Egypt (2013–2021)

Masoud

2023

Air Qual Atmos Health

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“…This field will be used to evaluate the ability of the reanalysis to reproduce dust concentration values at the ground (Barnaba et al, 2022a). Over Europe, the latter will be extracted from measured PM 10 values following a procedure similar to that described (Barnaba et al, 2022b). Furthermore, visibility data from 3D dustextinction coefficient fields have been used for aviation applications (Basart et al, 2021), while soiling index based on wet and dry dust deposition has been used to develop products for solar energy production (Rautio et al, 2022).…”

Section: Reanalysis Product Descriptionmentioning

confidence: 99%

The MONARCH high-resolution reanalysis of desert dust aerosol over Northern Africa, the Middle East and Europe (2007–2016)

Tomaso

Escribano

Basart

et al. 2022

Earth Syst. Sci. Data

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Abstract. One of the challenges in studying desert dust aerosol along with its numerous interactions and impacts is the paucity of direct in situ measurements, particularly in the areas most affected by dust storms. Satellites typically provide column-integrated aerosol measurements, but observationally constrained continuous 3D dust fields are needed to assess dust variability, climate effects and impacts upon a variety of socio-economic sectors. Here, we present a high-resolution regional reanalysis data set of desert dust aerosols that covers Northern Africa, the Middle East and Europe along with the Mediterranean Sea and parts of central Asia and the Atlantic and Indian oceans between 2007 and 2016. The horizontal resolution is 0.1∘ latitude × 0.1∘ longitude in a rotated grid, and the temporal resolution is 3 h. The reanalysis was produced using local ensemble transform Kalman filter (LETKF) data assimilation in the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH) developed at the Barcelona Supercomputing Center (BSC). The assimilated data are coarse-mode dust optical depth retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue Level 2 products. The reanalysis data set consists of upper-air variables (dust mass concentrations and the extinction coefficient), surface variables (dust deposition and solar irradiance fields among them) and total column variables (e.g. dust optical depth and load). Some dust variables, such as concentrations and wet and dry deposition, are expressed for a binned size distribution that ranges from 0.2 to 20 µm in particle diameter. Both analysis and first-guess (analysis-initialized simulation) fields are available for the variables that are diagnosed from the state vector. A set of ensemble statistics is archived for each output variable, namely the ensemble mean, standard deviation, maximum and median. The spatial and temporal distribution of the dust fields follows well-known dust cycle features controlled by seasonal changes in meteorology and vegetation cover. The analysis is statistically closer to the assimilated retrievals than the first guess, which proves the consistency of the data assimilation method. Independent evaluation using Aerosol Robotic Network (AERONET) dust-filtered optical depth retrievals indicates that the reanalysis data set is highly accurate (mean bias = −0.05, RMSE = 0.12 and r = 0.81 when compared to retrievals from the spectral de-convolution algorithm on a 3-hourly basis). Verification statistics are broadly homogeneous in space and time with regional differences that can be partly attributed to model limitations (e.g. poor representation of small-scale emission processes), the presence of aerosols other than dust in the observations used in the evaluation and differences in the number of observations among seasons. Such a reliable high-resolution historical record of atmospheric desert dust will allow a better quantification of dust impacts upon key sectors of society and economy, including health, solar energy production and transportation. The reanalysis data set (Di Tomaso et al., 2021) is distributed via Thematic Real-time Environmental Distributed Data Services (THREDDS) at BSC and is freely available at http://hdl.handle.net/21.12146/c6d4a608-5de3-47f6-a004-67cb1d498d98 (last access: 10 June 2022).

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“…Particulate matter less than 10 micrometres in diameter are called PM 10 . Some researchers have examined the characteristics, dispersion, and modelling of air pollutants, PM 10 and SO 2 , in recent years [19][20][21][22][23][24][25]. Climatological parameters are in interact both with air pollutants and with each other in the atmospheric environment [26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

İklimsel Değişkenlerin Partikül Madde ve Kükürt Dioksit Üzerindeki Etkisi

ZATEROGLU

2023

Çukurova Üniversitesi Mühendislik Fakültesi Dergisi

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Hava kirleticilerin tahmin edilmesi, insan sağlığı üzerindeki etkilerinin artması ve çevre sorunları nedeniyle önemli bir konu haline gelmiştir. Bu makale, Çoklu Doğrusal Regresyon yöntemine dayalı istatistiksel yaklaşım yoluyla hava kirletici konsantrasyonlarını tahmin etmek için bir tahmin modeli oluşturmayı amaçlamaktadır. Analiz, Kırıkkale'de bulunan izleme istasyonunda hava kirleticilerin günlük konsantrasyon değerlerini ve bulutluluk, rüzgar hızı, yağış, bağıl nem ve hava sıcaklığı gibi iklimsel değişkenleri içermektedir. İklim elemanlarının hava kirleticileri üzerindeki etkisi, regresyon analizi yöntemi kullanılarak istatistiksel açıdan önemli olarak tanımlanmıştır (%5’ten küçük önem düzeyi). Değerlendirilen iklimsel değişkenler arasında, partikül madde için adımsal regresyon modellerinde en sık seçilen değişkenler bulutluluk, yağış ve bağıl nem olurken, kükürt dioksit için en çok bağıl nem ve minimum hava sıcaklığı seçilmiştir.

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Multiannual assessment of the desert dust impact on air quality in Italy combining PM10 data with physics-based and geostatistical models

Cited by 19 publications

References 50 publications

Spatio-temporal patterns and trends of the air pollution integrating MERRA-2 and in situ air quality data over Egypt (2013–2021)

Spatio-temporal patterns and trends of the air pollution integrating MERRA-2 and in situ air quality data over Egypt (2013–2021)

The MONARCH high-resolution reanalysis of desert dust aerosol over Northern Africa, the Middle East and Europe (2007–2016)

İklimsel Değişkenlerin Partikül Madde ve Kükürt Dioksit Üzerindeki Etkisi

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