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Atmosphere, Volume 6, Issue 7 (July 2015) – 6 articles , Pages 863-959

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4538 KiB  
Article
Case Study of Particle Number Fluxes and Size Distributions during Nucleation Events in Southeastern Italy in the Summer
by Marianna Conte, Antonio Donateo, Adelaide Dinoi, Franco Belosi and Daniele Contini
Atmosphere 2015, 6(7), 942-959; https://doi.org/10.3390/atmos6070942 - 14 Jul 2015
Cited by 13 | Viewed by 5332
Abstract
Concentrations, size distributions and particle number vertical turbulent fluxes were measured by the eddy-covariance method at an urban background site in southeastern Italy during the summer. CO2/H2O concentrations and fluxes were also determined together with meteorological parameters. Time series show that particles could [...] Read more.
Concentrations, size distributions and particle number vertical turbulent fluxes were measured by the eddy-covariance method at an urban background site in southeastern Italy during the summer. CO2/H2O concentrations and fluxes were also determined together with meteorological parameters. Time series show that particles could be divided into two size classes with negatively-correlated temporal trends in diurnal hours: nanoparticles (diameter Dp < 50 nm) and larger particles (Dp > 50 nm). Larger particles include part of the Aitken mode and the accumulation mode. Nanoparticles peaked in diurnal hours due to the presence of several days with nucleation events when particles Dp > 50 nm were at minimum concentrations. Nucleation increased diurnal total particle concentration by a factor of 2.5, reducing mean and median diameters from Dmean = 62.3 ± 1.2 nm and Dmedian = 29.1 ± 1.3 nm on non-event days to Dmean = 35.4 ± 0.6 nm and Dmedian = 15.5 ± 0.3 nm on event days. During nucleation events, particle deposition increased markedly (i.e., downward fluxes), but no significant changes in CO2 concentrations and fluxes were observed. This is compatible with new particle formation above the measurement height and a consequent net transport towards the surface. Correlation with meteorology shows that the formation of new particles is correlated with solar radiation and favored at high wind velocity. Full article
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2203 KiB  
Article
Measurement of Ozone Concentration on the Elevation Gradient of a Low Hill by a Semiconductor-Based Portable Monitor
by Isao Kanda
Atmosphere 2015, 6(7), 928-941; https://doi.org/10.3390/atmos6070928 - 14 Jul 2015
Cited by 3 | Viewed by 4440
Abstract
Ozone concentration has a complex distribution in mountain areas, but the low spatial density of high elevation monitoring stations has limited our understanding of ozone behavior. To achieve high spatial density, mobile measurement was carried out using a portable ozone monitor based on [...] Read more.
Ozone concentration has a complex distribution in mountain areas, but the low spatial density of high elevation monitoring stations has limited our understanding of ozone behavior. To achieve high spatial density, mobile measurement was carried out using a portable ozone monitor based on a semiconductor sensor. On the elevation gradient of a relatively low hill (273 m above seal level) in Matsuyama, Japan, 66 walking measurements were conducted in the pre-dawn hours of the winter in 2012 and 2013. The ozone concentration at the top of the hill was positively correlated with the daily maximum concentration on the plain on the previous day. The difference in ozone concentration between the top and bottom of the hill was found to increase with increasing vertical temperature difference. The measurement method established in this study provides a low-cost alternative to grasp the distribution of ozone in mountain areas. Full article
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3548 KiB  
Article
Synthesis Analysis of One Severe Convection Precipitation Event in Jiangsu Using Ground-Based GPS Technology
by Hao Wang, Jianxin He, Ming Wei and Zhendong Zhang
Atmosphere 2015, 6(7), 908-927; https://doi.org/10.3390/atmos6070908 - 10 Jul 2015
Cited by 23 | Viewed by 7832
Abstract
Global positioning system (GPS) detection technology has several advantageous characteristics (i.e., all-weather applications, high accuracy, high spatial and temporal resolution, and low cost), and GPS tracking and monitoring techniques for water vapor have developed rapidly in recent years. The GPS-precipitable water [...] Read more.
Global positioning system (GPS) detection technology has several advantageous characteristics (i.e., all-weather applications, high accuracy, high spatial and temporal resolution, and low cost), and GPS tracking and monitoring techniques for water vapor have developed rapidly in recent years. The GPS-precipitable water vapor (GPS-PWV), obtained through inversion using this technology can reflect the water vapor inflow and outflow in a vertical air column above a certain area in nearly real-time, which is especially important for areas of severe water vapor variation. In this paper, we studied the relationship between GPS-PWV variation and actual precipitation. The specific aim was to identify the underlying physical mechanisms driving the variation and to further strengthen the utility of GPS-PWV in forecasts and warnings of severe convection weather. We concluded that (1) rapid rise in the GPS-PWV in the long-term low-level data predicted the arrival of precipitation and was therefore useful in weather forecasts; (2) the GPS-PWV variation was closely related with the movement of the water vapor transfer belt; (3) the atmosphere showed an unstable energy structure before the GPS-PWV increase; and (4) local motion was strongly related with the development and maintenance of precipitation. Full article
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758 KiB  
Article
Forecasting Urban Air Quality via a Back-Propagation Neural Network and a Selection Sample Rule
by Yonghong Liu, Qianru Zhu, Dawen Yao and Weijia Xu
Atmosphere 2015, 6(7), 891-907; https://doi.org/10.3390/atmos6070891 - 09 Jul 2015
Cited by 18 | Viewed by 4730
Abstract
In this paper, based on a sample selection rule and a Back Propagation (BP) neural network, a new model of forecasting daily SO2, NO2, and PM10 concentration in seven sites of Guangzhou was developed using data from January [...] Read more.
In this paper, based on a sample selection rule and a Back Propagation (BP) neural network, a new model of forecasting daily SO2, NO2, and PM10 concentration in seven sites of Guangzhou was developed using data from January 2006 to April 2012. A meteorological similarity principle was applied in the development of the sample selection rule. The key meteorological factors influencing SO2, NO2, and PM10 daily concentrations as well as weight matrices and threshold matrices were determined. A basic model was then developed based on the improved BP neural network. Improving the basic model, identification of the factor variation consistency was added in the rule, and seven sets of sensitivity experiments in one of the seven sites were conducted to obtain the selected model. A comparison of the basic model from May 2011 to April 2012 in one site showed that the selected model for PM10 displayed better forecasting performance, with Mean Absolute Percentage Error (MAPE) values decreasing by 4% and R2 values increasing from 0.53 to 0.68. Evaluations conducted at the six other sites revealed a similar performance. On the whole, the analysis showed that the models presented here could provide local authorities with reliable and precise predictions and alarms about air quality if used at an operational scale. Full article
(This article belongs to the Special Issue Air Quality and Source Apportionment)
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3435 KiB  
Article
Insights into Indoor/Outdoor PM Concentration Ratios due to Dust Storms in an Arid Region
by Helena Krasnov, Itzhak Katra and Michael D. Friger
Atmosphere 2015, 6(7), 879-890; https://doi.org/10.3390/atmos6070879 - 25 Jun 2015
Cited by 6 | Viewed by 5044
Abstract
Dust storms have impacts on both human and physical environments, associated with an increase in atmospheric particulate matter (PM) concentrations. Most studies on exposure to PM have focused on the outdoor air, while information on indoor pollution, is still lacking. The aim of [...] Read more.
Dust storms have impacts on both human and physical environments, associated with an increase in atmospheric particulate matter (PM) concentrations. Most studies on exposure to PM have focused on the outdoor air, while information on indoor pollution, is still lacking. The aim of this study was to examine the impact of desert dust events on PM concentrations in indoor environments. A total of over 200 real time measurements of PM were conducted in houses in the Negev Desert during dust storms. Indoor and outdoor PM concentrations were characterized, as well as the relationships between the two datasets. The findings indicated that atmospheric PM10 concentrations can increase from 20–120 μg·m−3 on non-dust days to more than 1500 μg·m−3 during dust events. Indoor concentrations can reach as high as 1000 μg·m−3. The calculated indoor/outdoor (I/O) PM ratio ranged from 0.79 for low-level storms to 0.58 during stronger events. Indoor PM concentrations were found to be dependent on the dust storm intensity (low, medium, high) and duration with a time lag. The information obtained in this study is critical for assessment of policy interventions to reduce exposure risk and health effects due dust storms. Full article
(This article belongs to the Special Issue Indoor and Outdoor Air Quality)
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1643 KiB  
Article
Towards Optimal Aerosol Information for the Retrieval of Solar Surface Radiation Using Heliosat
by Richard Mueller, Uwe Pfeifroth and Christine Traeger-Chatterjee
Atmosphere 2015, 6(7), 863-878; https://doi.org/10.3390/atmos6070863 - 24 Jun 2015
Cited by 20 | Viewed by 4768
Abstract
High quality data of surface radiation is a prerequisite for climate monitoring (Earth radiation budget) and solar energy applications. A very common method to derive solar surface irradiance is the Heliosat method, a one channel approach for the retrieval of the effective cloud [...] Read more.
High quality data of surface radiation is a prerequisite for climate monitoring (Earth radiation budget) and solar energy applications. A very common method to derive solar surface irradiance is the Heliosat method, a one channel approach for the retrieval of the effective cloud albedo (CAL). This information is then used to derive the solar surface irradiance by application of a clear sky model. The results of this study are based on radiative transfer modelling, visual inspection of satellite images and evaluation of satellite based solar surface radiation with ground measurements. The respective results provide evidence that variations in Aerosol Optical depth induced by desert storms and biomass burning events lead to a significant increase of the effective cloud albedo, thus, that certain aerosol events are interpreted as clouds by the method. For the estimation of the solar surface radiation aerosol information is needed as input for the clear sky model. As the aerosol effect is partly considered by CAL, there is a need to modify external aerosol information for the use within the clear sky model, e.g., by truncation of high aerosol loads. Indeed, it has been shown that a modified version of the Monitoring Atmospheric Composition and Climate (MACC) aerosol information leads to better accuracy of the retrieved solar surface radiation than the original MACC data for the investigated 9 sites and time period (2006–2009). Further, the assumption of a constant aerosol optical depth of 0.18 provides also better accuracies of the estimated solar surface radiation than the original MACC data for the investigated sites and period. It is concluded that this is partly due to the consideration of scattering aerosols by the effective cloud albedo. Full article
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