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To derive the comprehensive aerosol in situ characteristics at a rural background area in Saudi Arabia, an aerosol measurements station was established to Hada Al Sham, 60 km east from the Red Sea and the city of Jeddah. The present sturdy describes the observational data from February 2013 to February 2015 of scattering and absorption coefficients, Angstrom exponents and single scattering albedo over the measurement period. The average scattering and absorption coefficients at wavelength 525 nm were 109 ± 71 Mm − 1 (mean ± SD, at STP conditions) and 15 ± 17 Mm − 1 (at STP conditions), respectively. As expected, the scattering coefficient was dominated by large desert dust particles with low Angstrom scattering exponent, 0.49 ± 0.62. Especially from February to June the Angstrom scattering exponent was clearly lower (0.23) and scattering coefficients higher (124 Mm − 1 ) than total averages because of the dust outbreak season. Aerosol optical properties had clear diurnal cycle. The lowest scattering and absorption coefficients and aerosol optical depths were observed around noon. The observed diurnal variation is caused by wind direction and speed, during night time very calm easterly winds are dominating whereas during daytime the stronger westerly winds are dominating (sea breeze). Positive Matrix Factorization mathematical tool was applied to the scattering and absorption coefficients and PM 2.5 and coarse mode (PM 10 –PM 2.5 ) mass concentrations to identify source characteristics. Three different factors with clearly different properties were found; anthropogenic, BC source and desert dust. Mass absorption efficiencies for BC source and desert dust factors were, 6.0 m 2 g − 1 and 0.4 m 2 g − 1 , respectively, and mass scattering efficiencies for anthropogenic (sulphate) and desert dust, 2.5 m 2 g − 1 and 0.8 m 2 g − 1 , respectively.

An air pollutant proxy is a mathematical model that estimates an unobserved air pollutant using other measured variables. The proxy is advantageous to fill missing data in a research campaign or to substitute a real measurement for minimising the cost as well as the operators involved (i.e., virtual sensor). In this paper, we present a generic concept of pollutant proxy development based on an optimised data-driven approach. We propose a mutual information concept to determine the interdependence of different variables and thus select the most correlated inputs. The most relevant variables are selected to be the best proxy inputs, where several metrics and data loss are also involved for guidance. The input selection method determines the used data for training pollutant proxies based on a probabilistic machine learning method. In particular, we use a Bayesian neural network that naturally prevents overfitting and provides confidence intervals around its output prediction. In this way, the prediction uncertainty could be assessed and evaluated. In order to demonstrate the effectiveness of our approach, we test it on an extensive air pollution database to estimate ozone concentration. An air pollutant proxy is a mathematical model that estimates an unobserved air pollutant using other measured variables. The proxy is advantageous to fill missing data in a research campaign or to substitute a real measurement for minimising the cost as well as the operators involved (i.e., virtual sensor). In this paper, we present a generic concept of pollutant proxy development based on an optimised data-driven approach. We propose a mutual information concept to determine the interdependence of different variables and thus select the most correlated inputs. The most relevant variables are selected to be the best proxy inputs, where several metrics and data loss are also involved for guidance. The input selection method determines the used data for training pollutant proxies based on a probabilistic machine learning method. In particular, we use a Bayesian neural network that naturally prevents overfitting and provides confidence intervals around its output prediction. In this way, the prediction uncertainty could be assessed and evaluated. In order to demonstrate the effectiveness of our approach, we test it on an extensive air pollution database to estimate ozone concentration.

This is the first time to clearly derive the comprehensive physical properties of aerosols at a rural background area in Saudi Arabia. Aerosol measurements station was established at a rural background area in the Western Saudi Arabia to study the aerosol properties. This study gives overview of the aerosol physical properties (PM10, PM2.5, black carbon and total number concentration) over the measurement period from November 2012 to February 2015. The average PM10 and PM2.5 concentrations were 95 ± 78 μg m-3 (mean ± STD, at ambient conditions) and 33 ± 68 μg m-3 (at ambient conditions), respectively. As expected PM10 concentration was dominated by coarse mode particles (PM10-PM2.5), most probably desert dust. Especially from February to June the coarse mode concentrations were high because of dust storm season. Aerosol mass concentrations had clear diurnal cycle. Lower values were observed around noon. This behavior is caused by wind direction and speed, during night time very calm easterly winds are dominating whereas during daytime the stronger westerly winds are dominating (sea breeze). During the day time the boundary layer is evolving, causing enhanced mixing and dilution leading to lower concentration. PM10 and PM2.5 concentrations were comparable to values measured at close by city of Jeddah. Black carbon concentration was about 2% and 6% of PM10 and PM2.5 mass, respectively. Total number concentration was dominated by frequent new particle formation and particle growth events. The typical diurnal cycle in particle total number concentration was clearly different from PM10 and PM2.5.

We investigated the temporal variation of PM and aerosol particle number concentration (TC, D_p 0.25-32 µm) during year 2012 in Jeddah city. We focused on the daily patterns, wind sector analysis, and the effect of ambient conditions. The daily median values of the PM_(10) rarely exceeded 200 µg/m^3. The PM_(2.5) and PM_1 concentrations showed similar temporal variation with fraction of 39.5% and 19.3% of the PM_(10), respectively. The daily median values of the TC were generally below 500 cm^(-3) but showed three distinguished peaks (as high as 950 cm^(-3)) occurred during late September-early November, which was during the time of the Hajj season. These peaks were also observable in the PM_(2.5) and PM_1. The PM_(10) daily pattern on workdays and Thursdays were similar with a pronounced peak as high as 90 µg/m^3 during the morning time. The PM_(2.5) and PM_1 daily patterns were also similar to those of the PM_(10), especially on Thursdays and workdays, but with lower concentrations. The TC daily pattern was almost the same on all days showing high concentrations (between 150 and 200 cm^(-3)) during the first half of the day. The daily patterns of the TC were similar to those of the PM_1, especially on Workdays and Fridays. The emissions from the industrial city (located in the south of Jeddah) are the main source of PM in Jeddah. During the sea breeze that occurred in the afternoon accompanied low concentrations of PM and TC concentrations. The PM concentrations showed the famous U-shape with respect to the wind speed, whereas the TC was around 150 cm^(-3) when the wind speed was over 3 m/s. In general, the TC had a different behaviour with respect to the other ambient conditions than that of the PM concentrations, especially PM_(10).

Atmospheric aerosols have significant effects on human health and the climate. A large fraction of these aerosols originates from secondary new particle formation (NPF), where atmospheric vapors form small particles that subsequently grow into larger sizes. In this study, we characterize NPF events observed at a rural background site of Hada Al Sham (21.802∘ N, 39.729∘ E), located in western Saudi Arabia, during the years 2013–2015. Our analysis shows that NPF events occur very frequently at the site, as 73 % of all the 454 classified days were NPF days. The high NPF frequency is likely explained by the typically prevailing conditions of clear skies and high solar radiation, in combination with sufficient amounts of precursor vapors for particle formation and growth. Several factors suggest that in Hada Al Sham these precursor vapors are related to the transport of anthropogenic emissions from the coastal urban and industrial areas. The median particle formation and growth rates for the NPF days were 8.7 cm−3 s−1 (J7 nm) and 7.4 nm h−1 (GR7−12 nm), respectively, both showing highest values during late summer. Interestingly, the formation and growth rates increase as a function of the condensation sink, likely reflecting the common anthropogenic sources of NPF precursor vapors and primary particles affecting the condensation sink. A total of 76 % of the NPF days showed an unusual progression, where the observed diameter of the newly formed particle mode started to decrease after the growth phase. In comparison to most long-term measurements, the NPF events in Hada Al Sham are exceptionally frequent and strong both in terms of formation and growth rates. In addition, the frequency of the decreasing mode diameter events is higher than anywhere else in the world.