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Atmosphere, Volume 9, Issue 4 (April 2018)

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Cover Story (view full-size image) Indoor and outdoor PM2.5 at Colorado USA homes varies by season, being highest in the summer. The [...] Read more.
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Editorial

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Open AccessEditorial Announcing the Atmosphere 2018 Travel Award for Young Investigators
Atmosphere 2018, 9(4), 147; https://doi.org/10.3390/atmos9040147
Received: 16 April 2018 / Revised: 16 April 2018 / Accepted: 16 April 2018 / Published: 16 April 2018
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Research

Jump to: Editorial, Review, Other

Open AccessArticle Avoiding Extremes: Benefits of Staying below +1.5 °C Compared to +2.0 °C and +3.0 °C Global Warming
Atmosphere 2018, 9(4), 115; https://doi.org/10.3390/atmos9040115
Received: 17 January 2018 / Revised: 13 March 2018 / Accepted: 15 March 2018 / Published: 21 March 2018
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Abstract
The need to restrict global mean temperature to avoid irreversible climate change is supported by scientific evidence. The need became political practice at the Conference of the Parties in 2015, where the participants decided to limit global warming to not more than +2.0
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The need to restrict global mean temperature to avoid irreversible climate change is supported by scientific evidence. The need became political practice at the Conference of the Parties in 2015, where the participants decided to limit global warming to not more than +2.0 °C compared to pre-industrial times and to rather aim for a limit of +1.5 °C global warming. Nevertheless, a clear picture of what European climate would look like under +1.5 °C, +2.0 °C and +3.0 °C global warming level (GWL) is still missing. In this study, we will fill this gap by assessing selected climate indices related to temperature and precipitation extremes, based on state of the art regional climate information for Europe taken from the European branch of the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) ensemble. To assess the impact of these indices under climate change, we investigate the spatial extent of the area of the climate change signal in relation to the affected population. This allows us to demonstrate which climate extremes could be avoided when global warming is kept well below +2.0 °C or even +1.5 °C compared to higher GWLs. The European north–south gradient of tropical nights and hot days is projected to be intensified with an increasing global warming level. For precipitation-related indices, an overall increase in precipitation extremes is simulated, especially under +3.0 °C GWL, for mid- and northern Europe, whereas an increase in dry days is projected for many regions in southern Europe. The benefit of staying below +1.5 °C GWL compared to +2.0 °C GWL is the avoidance of an additional increase in tropical nights and hot days parallel to an increase in dry days in parts of southern Europe as well as an increase in heavy precipitation in parts of Scandinavia. Compared to +3.0 °C GWL, the benefit of staying at +1.5 °C GWL is to avoid a substantial increase (i.e., an increase of more than five dry days and ten tropical nights) in dry days and tropical nights in southern European regions, while, in several European regions and especially in northern Europe, a substantial increase (i.e., more than two heavy precipitation days) in heavy precipitation days could be avoided. This study shows that a statistically significant change in the investigated climate indices can be avoided under +1.5 °C GWL compared to the investigated higher GWLs +2.0 °C and +3.0 °C for the majority of the population in almost all regions. Future studies will investigate compound events where the severity of single extreme events is intensified. Full article
(This article belongs to the Section Climatology and Meteorology)
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Open AccessArticle Micro-Scale Properties of Different Bora Types
Atmosphere 2018, 9(4), 116; https://doi.org/10.3390/atmos9040116
Received: 24 January 2018 / Revised: 15 March 2018 / Accepted: 16 March 2018 / Published: 21 March 2018
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Abstract
In this paper we use 20 Hz wind measurements on three levels (2, 5, and 10 m) to investigate the differences in micro-scale properties of different bora types, i.e., deep and shallow bora with further subdivision to cyclonic and anticyclonic bora cases. Using
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In this paper we use 20 Hz wind measurements on three levels (2, 5, and 10 m) to investigate the differences in micro-scale properties of different bora types, i.e., deep and shallow bora with further subdivision to cyclonic and anticyclonic bora cases. Using Fourier spectral analysis, we investigate a suitable turbulence averaging scale and bora gust pulsations. The obtained data set is further used to test the Monin–Obukhov similarity theory, the surface layer stratification, the behavior of the terms in the prognostic turbulence kinetic energy equation, and the wind profiles. One of our main goals is to identify possible micro-scale differences between shallow and deep bora types because of the possible different mountain wave dynamics in those flows. We found that a turbulence averaging scale of 30 min is suitable for this location and is in agreement with previous bora studies. The wind speed power spectral densities of all selected bora episodes showed pulsations with periods of 2–8 min. This suggests that mountain wave breaking was present in all cases, regardless of flow depth and synoptic type. The stability parameter analysis confirmed the near-neutral thermal stratification of bora; a consequence of intensive mechanical mixing. No significant differences related to bora type were observed in other micro-scale parameters. Full article
(This article belongs to the Special Issue Atmospheric Processes over Complex Terrain)
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Open AccessArticle Estimating Hourly Beam and Diffuse Solar Radiation in an Alpine Valley: A Critical Assessment of Decomposition Models
Atmosphere 2018, 9(4), 117; https://doi.org/10.3390/atmos9040117
Received: 5 March 2018 / Revised: 19 March 2018 / Accepted: 20 March 2018 / Published: 21 March 2018
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Abstract
Accurate solar radiation estimates in Alpine areas represent a challenging task, because of the strong variability arising from orographic effects and mountain weather phenomena. These factors, together with the scarcity of observations in elevated areas, often cause large modelling uncertainties. In the present
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Accurate solar radiation estimates in Alpine areas represent a challenging task, because of the strong variability arising from orographic effects and mountain weather phenomena. These factors, together with the scarcity of observations in elevated areas, often cause large modelling uncertainties. In the present paper, estimates of hourly mean diffuse fraction values from global radiation data, provided by a number (13) of decomposition models (chosen among the most widely tested in the literature), are evaluated and compared with observations collected near the city of Bolzano, in the Adige Valley (Italian Alps). In addition, the physical factors influencing diffuse fraction values in such a complex orographic context are explored. The average accuracy of the models were found to be around 27% and 14% for diffuse and beam radiation respectively, the largest errors being observed under clear sky and partly cloudy conditions, respectively. The best performances were provided by the more complex models, i.e., those including a predictor specifically explaining the radiation components’ variability associated with scattered clouds. Yet, these models return non-negligible biases. In contrast, the local calibration of a single-equation logistical model with five predictors allows perfectly unbiased estimates, as accurate as those of the best-performing models (20% and 12% for diffuse and beam radiation, respectively), but at much smaller computational costs. Full article
(This article belongs to the Special Issue Atmospheric Processes over Complex Terrain)
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Open AccessArticle Wintertime Local Wind Dynamics from Scanning Doppler Lidar and Air Quality in the Arve River Valley
Atmosphere 2018, 9(4), 118; https://doi.org/10.3390/atmos9040118
Received: 25 January 2018 / Revised: 8 March 2018 / Accepted: 16 March 2018 / Published: 21 March 2018
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Abstract
Air quality issues are frequent in urbanized valleys, particularly in wintertime when a temperature inversion forms and the air within the valley is stably stratified over several days. In addition to pollutant sources, local winds can have a significant impact on the spatial
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Air quality issues are frequent in urbanized valleys, particularly in wintertime when a temperature inversion forms and the air within the valley is stably stratified over several days. In addition to pollutant sources, local winds can have a significant impact on the spatial distribution and temporal evolution of pollutant concentrations. They can be very complex and difficult to represent in numerical weather prediction models, particularly under stable conditions. Better knowledge of these local winds from observations is also a prerequisite to improving air quality prediction capability. This paper analyses local winds during the Passy-2015 field experiment that took place in a section of the Arve river valley, near Chamonix–Mont-Blanc. This location is one of the worst places in France regarding air quality. The wind analysis, which is mainly based on scanning Doppler lidar data sampling a persistent temperature inversion episode, reveals features consistent with the higher pollutant concentrations observed in this section of the valley as well as their spatial heterogeneities. In particular, an elevated down-valley jet is observed at night in the northern half of the valley, which, combined with a weak daytime up-valley wind, leads to very poor ventilation of the lowest layers. A northeast–southwest gradient in ventilation is observed on a daily-average, and is consistent with the PM10 heterogeneities observed within the valley. Full article
(This article belongs to the Special Issue Atmospheric Processes over Complex Terrain)
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Open AccessArticle Hazardous Source Estimation Using an Artificial Neural Network, Particle Swarm Optimization and a Simulated Annealing Algorithm
Atmosphere 2018, 9(4), 119; https://doi.org/10.3390/atmos9040119
Received: 9 January 2018 / Revised: 16 February 2018 / Accepted: 6 March 2018 / Published: 22 March 2018
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Abstract
Locating and quantifying the emission source plays a significant role in the emergency management of hazardous gas leak accidents. Due to the lack of a desirable atmospheric dispersion model, current source estimation algorithms cannot meet the requirements of both accuracy and efficiency. In
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Locating and quantifying the emission source plays a significant role in the emergency management of hazardous gas leak accidents. Due to the lack of a desirable atmospheric dispersion model, current source estimation algorithms cannot meet the requirements of both accuracy and efficiency. In addition, the original optimization algorithm can hardly estimate the source accurately, because of the difficulty in balancing the local searching with the global searching. To deal with these problems, in this paper, a source estimation method is proposed using an artificial neural network (ANN), particle swarm optimization (PSO), and a simulated annealing algorithm (SA). This novel method uses numerous pre-determined scenarios to train the ANN, so that the ANN can predict dispersion accurately and efficiently. Further, the SA is applied in the PSO to improve the global searching ability. The proposed method is firstly tested by a numerical case study based on process hazard analysis software (PHAST), with analysis of receptor configuration and measurement noise. Then, the Indianapolis field case study is applied to verify the effectiveness of the proposed method in practice. Results demonstrate that the hybrid SAPSO algorithm coupled with the ANN prediction model has better performances than conventional methods in both numerical and field cases. Full article
(This article belongs to the Section Air Quality)
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Open AccessArticle Modelling of Basin Wide Daily Evapotranspiration with a Partial Integration of Remote Sensing Data
Atmosphere 2018, 9(4), 120; https://doi.org/10.3390/atmos9040120
Received: 6 February 2018 / Revised: 17 March 2018 / Accepted: 20 March 2018 / Published: 22 March 2018
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Abstract
Evapotranspiration (ET) is the most significant water balance component and is also a very complex component to evaluate in spatio–temporal scales. Remotely-sensed data greatly increases the accuracy of basin wide ET estimation but only in periods with available satellite images. This paper describes
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Evapotranspiration (ET) is the most significant water balance component and is also a very complex component to evaluate in spatio–temporal scales. Remotely-sensed data greatly increases the accuracy of basin wide ET estimation but only in periods with available satellite images. This paper describes an attempt to estimate daily ET regardless of the availability of the satellite images. The method is based on application of the interpolated evaporative fraction (Λ) from “historical” satellite images to periods with no satellite data available. Basin wide daily ET is obtained by combining interpolated Λ and standard PET methods on meteorological stations. The reliability of such approach was evaluated by comparing the obtained daily ET to the SEBAL ET estimates through the analysis of residuals (Δ), standard deviations of residuals (σ) and the Nash–Sutcliffe coefficient (NSE) over the basin. The SEBAL ET estimates were validated with the data from two lysimeters. The discrepancy of obtained ET versus the SEBAL ET estimates (Δ = 0.13 mm day−1, σ = 0.64 mm day−1, NSE = 0.07) indicated that the proposed concept has relatively high accuracy, which is notably higher than the Penman–Monteith interpolated ET estimates (Δ = 1.94 mm day−1, σ = 1.03 mm day−1, NSE = −4.71). It was shown that a total of five images can provide a reliable estimate of interpolated Λ and thus represent specific characteristics of a basin. As the presented concept requires minimum remote sensing data and ground based inputs, it could be applied to estimate basin wide daily ET in data scarce regions and in periods with no satellite images available. Full article
(This article belongs to the Section Climatology and Meteorology)
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Open AccessArticle Precipitation Preventing a Deficit of Readily Available Soil Water in Arable Soils in Poland
Atmosphere 2018, 9(4), 121; https://doi.org/10.3390/atmos9040121
Received: 27 February 2018 / Revised: 19 March 2018 / Accepted: 21 March 2018 / Published: 23 March 2018
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Abstract
Plants grown in arable soils mainly use rainwater stored in the soil at matric potential between −10 kPa and −100 kPa, which corresponds to the readily available soil water (RASW). RASW in the 100-cm soil layer of Polish arable soils is relatively low
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Plants grown in arable soils mainly use rainwater stored in the soil at matric potential between −10 kPa and −100 kPa, which corresponds to the readily available soil water (RASW). RASW in the 100-cm soil layer of Polish arable soils is relatively low and ranges from about 12 mm in mountain clay soils up to 75 mm in black earths, which, at an average daily evapotranspiration of 3.8 mm·day−1 and spatio—temporal variability of precipitation, determines water scarcity of crop plants. The aim of the study is to estimate the values and the frequency of critical rainfall which ensures that soil water is kept in the range of readily available to plants and prevents water shortages for plants in arable soils. In order to meet this condition, the decade (10-day) sums of this precipitation, included in the ranges 16–27, 22–31, 26–35 and 33–39 mm, occur in 20.8, 13.4, 11.3 and 5.9%, respectively, of the decades of the vegetation period (April to September). Maps of critical rainfall spatial diversity in the background of the actual soil cover in Poland were generated. They may be useful for preliminary, estimated operational planning of irrigation needs. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Variability and Factors of Influence of Extreme Wet and Dry Events in Northern Mexico
Atmosphere 2018, 9(4), 122; https://doi.org/10.3390/atmos9040122
Received: 15 January 2018 / Revised: 15 March 2018 / Accepted: 16 March 2018 / Published: 23 March 2018
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Abstract
The goal of this study was to generate a method to examine seasonal variability by climatic classification and Pacific seasonal factors to identify extreme wet and dry events in northern Mexico for the period 1952–2013. Using the standardized precipitation and evapotranspiration index (SPEI)
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The goal of this study was to generate a method to examine seasonal variability by climatic classification and Pacific seasonal factors to identify extreme wet and dry events in northern Mexico for the period 1952–2013. Using the standardized precipitation and evapotranspiration index (SPEI) on scales of three months (SPEI-3) and 24 months (SPEI-24), the variability of extreme wet and dry events were measured. The SPEI-3 and SPEI-24 anomalies were divided by the standard deviation (standardized Z anomalies). A Pearson correlation for SPEI-3, SPEI-24, Pacific decadal oscillation (PDO) and the oceanic El Niño index (ONI) was applied. Wet extreme events were recorded in 1954, 1968, 1976–1977, 1981, 1984, 1986 and 2003, of which the greatest magnitude was recorded in 1984 for the Sinaloa-very dry region. Extreme dry events were recorded in 1952–1953, 1990, 1997, 2003 and 2011–2013. The Z anomalies of the wet extreme events observed coincide with +PDO phase anomalies. In this study, the El Niño southern oscillation (ENSO) has little influence on wet and dry extreme events in northern Mexico. The negative phase anomalies of sea surface temperature (−SST) in the equatorial and eastern Pacific are indicators of extreme wet events. This study shows for the first time the influence of the PDO and the ONI on seasonal variability of extreme wet and dry events by climatic classification through the SPEI index in northern Mexico. Full article
(This article belongs to the Section Climatology and Meteorology)
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Open AccessArticle Sensitivity of Numerical Weather Prediction to the Choice of Variable for Atmospheric Moisture Analysis into the Brazilian Global Model Data Assimilation System
Atmosphere 2018, 9(4), 123; https://doi.org/10.3390/atmos9040123
Received: 9 February 2018 / Revised: 12 March 2018 / Accepted: 13 March 2018 / Published: 23 March 2018
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Abstract
Due to the high spatial and temporal variability of atmospheric water vapor associated with the deficient methodologies used in its quantification and the imperfect physics parameterizations incorporated in the models, there are significant uncertainties in characterizing the moisture field. The process responsible for
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Due to the high spatial and temporal variability of atmospheric water vapor associated with the deficient methodologies used in its quantification and the imperfect physics parameterizations incorporated in the models, there are significant uncertainties in characterizing the moisture field. The process responsible for incorporating the information provided by observation into the numerical weather prediction is denominated data assimilation. The best result in atmospheric moisture depend on the correct choice of the moisture control variable. Normalized relative humidity and pseudo-relative humidity are the variables usually used by the main weather prediction centers. The objective of this study is to assess the sensibility of the Center for Weather Forecast and Climate Studies to choose moisture control variable in the data assimilation scheme. Experiments using these variables are carried out. The results show that the pseudo-relative humidity improves the variables that depend on temperature values but damage the moisture field. The opposite results show when the simulation used the normalized relative humidity. These experiments suggest that the pseudo-relative humidity should be used in the cyclical process of data assimilation and the normalized relative humidity should be used in non-cyclic process (e.g., nowcasting application in high resolution). Full article
(This article belongs to the Section Climatology and Meteorology)
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Open AccessArticle Variation of Indoor Particulate Matter Concentrations and Association with Indoor/Outdoor Temperature: A Case Study in Rural Limpopo, South Africa
Atmosphere 2018, 9(4), 124; https://doi.org/10.3390/atmos9040124
Received: 24 January 2018 / Revised: 20 February 2018 / Accepted: 23 February 2018 / Published: 23 March 2018
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Abstract
There is still a pressing concern regarding the causes of poor indoor air quality and the consequent effects on health, because people spend a considerable amount of time indoors. Information about seasonal variation and the determinants of particulate matter (PM) concentrations could guide
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There is still a pressing concern regarding the causes of poor indoor air quality and the consequent effects on health, because people spend a considerable amount of time indoors. Information about seasonal variation and the determinants of particulate matter (PM) concentrations could guide the design and implementation of intervention strategies. This study was conducted in Giyani, Limpopo province, South Africa. The main aim was to assess indoor air quality. Indoor PM and temperature were monitored to describe seasonal and diurnal patterns of indoor PM4 concentration and to estimate the association between PM concentrations and indoor as well as ambient conditions. Indoor PM4 was monitored hourly in kitchens for the duration of spring (September), summer (February) and winter (July). Indoor temperatures were monitored hourly in kitchens, living rooms and bedrooms. Outdoor temperature and outdoor relative humidity were also monitored for the same period. Indoor temperatures showed a large range in the three sampled seasons, with the maximum values raising the largest cause for concern. Maximum indoor temperatures in summer exceeded the threshold of 35 °C, which has been shown to have adverse health effects. Occupants of the sampled households were exposed to indoor PM4 concentrations that exceeded national and international guidelines. Hourly indoor temperature was statistically significantly correlated to PM4 concentrations in the summer and spring (r = 0.22 and 0.24 respectively, p < 0.001 for both) and negatively correlated to outdoor relative humidity (r = −0.27, p < 0.001). Diurnal PM4 variations showed pronounced patterns with morning and evening peaks. PM4 was consistently higher throughout the day in summer compared to spring and winter. Community-based intervention strategies should consider these seasonal differences in PM4 exposure and tailor awareness messages for exposure prevention accordingly. Full article
(This article belongs to the Special Issue Indoor Air Pollution)
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Open AccessArticle Understanding Long-Term Variations in Surface Ozone in United States (U.S.) National Parks
Atmosphere 2018, 9(4), 125; https://doi.org/10.3390/atmos9040125
Received: 6 February 2018 / Revised: 13 March 2018 / Accepted: 17 March 2018 / Published: 25 March 2018
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Abstract
Long-term surface ozone observations at 25 National Park Service sites across the United States were analyzed for processes on varying time scales using a time scale decomposition technique, the Ensemble Empirical Mode Decomposition (EEMD). Time scales of interest include the seasonal cycle, large-scale
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Long-term surface ozone observations at 25 National Park Service sites across the United States were analyzed for processes on varying time scales using a time scale decomposition technique, the Ensemble Empirical Mode Decomposition (EEMD). Time scales of interest include the seasonal cycle, large-scale climate oscillations, and long-term (>10 years) trends. Emission reductions were found to have a greater impact on sites that are nearest major urban areas. Multidecadal trends in surface ozone were increasing at a rate of 0.07 to 0.37 ppbv year−1 before 2004 and decreasing at a rate of −0.08 to −0.60 ppbv year−1 after 2004 for sites in the East, Southern California, and Northwestern Washington. Sites in the Intermountain West did not experience a reversal of trends from positive to negative until the mid- to late 2000s. The magnitude of the annual amplitude (=annual maximum–minimum) decreased at eight sites, two in the West, two in the Intermountain West, and four in the East, by 5–20 ppbv and significantly increased at three sites; one in Alaska, one in the West, and one in the Intermountain West, by 3–4 ppbv. Stronger decreases in the annual amplitude occurred at a greater proportion of sites in the East (4/6 sites) than in the West/Intermountain West (4/19 sites). The date of annual maximums and/or minimums has changed at 12 sites, occurring 10–60 days earlier in the year. There appeared to be a link between the timing of the annual maximum and the decrease in the annual amplitude, which was hypothesized to be related to a decrease in ozone titration resulting from NOx emission reductions. Furthermore, it was found that a phase shift of the Pacific Decadal Oscillation (PDO), from positive to negative, in 1998–1999 resulted in increased occurrences of La Niña-like conditions. This shift had the effect of directing more polluted air masses from East Asia to higher latitudes over the North American continent. The change in the Pacific Decadal Oscillation (PDO)/El Niño Southern Oscillation (ENSO) regime influenced surface ozone at an Alaskan site over its nearly 30-year data record. Full article
(This article belongs to the Section Air Quality)
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Open AccessArticle A Robust Non-Gaussian Data Assimilation Method for Highly Non-Linear Models
Atmosphere 2018, 9(4), 126; https://doi.org/10.3390/atmos9040126
Received: 5 January 2018 / Revised: 14 March 2018 / Accepted: 20 March 2018 / Published: 26 March 2018
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Abstract
In this paper, we propose an efficient EnKF implementation for non-Gaussian data assimilation based on Gaussian Mixture Models and Markov-Chain-Monte-Carlo (MCMC) methods. The proposed method works as follows: based on an ensemble of model realizations, prior errors are estimated via a Gaussian Mixture
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In this paper, we propose an efficient EnKF implementation for non-Gaussian data assimilation based on Gaussian Mixture Models and Markov-Chain-Monte-Carlo (MCMC) methods. The proposed method works as follows: based on an ensemble of model realizations, prior errors are estimated via a Gaussian Mixture density whose parameters are approximated by means of an Expectation Maximization method. Then, by using an iterative method, observation operators are linearized about current solutions and posterior modes are estimated via a MCMC implementation. The acceptance/rejection criterion is similar to that of the Metropolis-Hastings rule. Experimental tests are performed on the Lorenz 96 model. The results show that the proposed method can decrease prior errors by several order of magnitudes in a root-mean-square-error sense for nearly sparse or dense observational networks. Full article
(This article belongs to the Special Issue Efficient Formulation and Implementation of Data Assimilation Methods)
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Open AccessArticle Challenges and Opportunities for Data Assimilation in Mountainous Environments
Atmosphere 2018, 9(4), 127; https://doi.org/10.3390/atmos9040127
Received: 15 February 2018 / Revised: 16 March 2018 / Accepted: 21 March 2018 / Published: 27 March 2018
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Abstract
This contribution aims to summarize the current state of data assimilation research as applied to land and atmosphere simulation and prediction in mountainous environments. It identifies and explains critical challenges, and offers opportunities for productive research based on both models and observations. Though
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This contribution aims to summarize the current state of data assimilation research as applied to land and atmosphere simulation and prediction in mountainous environments. It identifies and explains critical challenges, and offers opportunities for productive research based on both models and observations. Though many of the challenges to optimal data assimilation in the mountains are also challenges in flatter terrain, the complex land–atmosphere interactions and increased surface heterogeneity in the mountains violate key assumptions and methods in the data assimilation algorithms and the underlying models. The effects of model inadequacy are particularly acute in complex terrain. Recent research related to some of the key challenges suggest opportunities to make gains in both land and atmospheric data assimilation in the mountains. Research directions are suggested, focusing on model improvement in a data assimilation context, and design of field programs aimed at data assimilation. Full article
(This article belongs to the Special Issue Atmospheric Processes over Complex Terrain)
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Open AccessArticle Micrometeorological Measurements Reveal Large Nitrous Oxide Losses during Spring Thaw in Alberta
Atmosphere 2018, 9(4), 128; https://doi.org/10.3390/atmos9040128
Received: 10 February 2018 / Revised: 9 March 2018 / Accepted: 27 March 2018 / Published: 29 March 2018
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Abstract
Agricultural soils in Canada have been observed to emit a large pulse of nitrous oxide (N2O) gas during the spring thaw, representing a large percentage of the annual emissions. We report on three years of spring thaw N2O flux
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Agricultural soils in Canada have been observed to emit a large pulse of nitrous oxide (N2O) gas during the spring thaw, representing a large percentage of the annual emissions. We report on three years of spring thaw N2O flux measurements taken at three Alberta agricultural sites: a crop production site (Crop), cattle winter-feeding site (WF), and a cattle winter-grazing site (WG). Soil fluxes were calculated with a micrometeorological technique based on the vertical gradient in N2O concentration above each site measured with an open-path (line-averaging) FTIR gas detector. The Crop and WG sites showed a clear N2O emission pulse lasting 10 to 25 days after thawing began. During this pulse there was a strong diurnal cycle in emissions that paralleled the cycle in near-surface soil temperature. The emission pulse was less pronounced at the WF site. The average spring thaw losses (over 25 to 31 days) were 5.3 (Crop), 7.0 (WF), and 8.0 (WG) kg N2O-N ha−1, representing 1 to 3.5% of the annual nitrogen input to the sites. These large losses are higher than found in most previous western Canadian studies, and generally higher than the annual losses estimated from the Intergovernmental Panel on Climate Change and Canadian National Inventory Report calculations. The high N2O losses may be explained by high soil nitrate levels which promoted rapid denitrification during thawing. The application of a high resolution (temporal) micrometeorological technique was critical to revealing these losses. Full article
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Open AccessArticle Temperature Extremes: Estimation of Non-Stationary Return Levels and Associated Uncertainties
Atmosphere 2018, 9(4), 129; https://doi.org/10.3390/atmos9040129
Received: 1 December 2017 / Revised: 12 March 2018 / Accepted: 19 March 2018 / Published: 29 March 2018
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Abstract
Estimating temperature extremes (TEs) and associated uncertainties under the non-stationary (NS) assumption is a key research question in several domains, including the nuclear safety field. Methods for estimating TEs and associated confidence intervals (CIs) have often been used in the literature but in
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Estimating temperature extremes (TEs) and associated uncertainties under the non-stationary (NS) assumption is a key research question in several domains, including the nuclear safety field. Methods for estimating TEs and associated confidence intervals (CIs) have often been used in the literature but in a stationary context, separately and without detailed comparison. The extreme value theory is often used to assess risks in a context of climate change. It provides an accurate indication of distributions describing the frequency of occurrence of TEs. However, in an NS context, the notion of the return period is not easily interpretable. For instance, to predict a high return level (RL) in a future year, time-varying distributions must be used and compared. This study examines the performance of a new concept to predict RLs in an NS context and compares three methods for constructing the associated CIs (delta, profile likelihood, and parametric bootstrap). The present work takes up the concept of integrated return periods that define the T-year RL as the level for which the expected number of events in a T-year period is one and proposes a new method based on conditional predictions that is useful for predicting high RLs of extreme events in the near future (the 100-year RL in the year 2030, for instance). The daily maximum temperature (DMT) observed at the Orange Station in France was used as a case study. Several trend models were compared and a new likelihood-based method to detect breaks in TEs is proposed. The analyses were conducted assuming the time-varying Generalized Extreme Value (GEV) distribution. The concepts have been implemented in a software package (Non-Stationary Generalized Extreme Value (NSGEV)). The application demonstrates that the RL estimates for NS situations can be quite different from those corresponding to stationary conditions. Overall, the results suggest that the NS analysis can be helpful in making a more appropriate assessment of the risk for periodic safety reviews during the life of a nuclear power plant (NPP). Full article
(This article belongs to the Special Issue Temperature Extremes and Heat/Cold Waves)
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Open AccessArticle The Influence of Absolute Mass Loading of Secondary Organic Aerosols on Their Phase State
Atmosphere 2018, 9(4), 131; https://doi.org/10.3390/atmos9040131
Received: 19 December 2017 / Revised: 26 February 2018 / Accepted: 27 March 2018 / Published: 31 March 2018
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Abstract
Absolute secondary organic aerosol (SOA) mass loading (CSOA) is a key parameter in determining partitioning of semi- and intermediate volatility compounds to the particle phase. Its impact on the phase state of SOA, however, has remained largely unexplored. In this study,
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Absolute secondary organic aerosol (SOA) mass loading (CSOA) is a key parameter in determining partitioning of semi- and intermediate volatility compounds to the particle phase. Its impact on the phase state of SOA, however, has remained largely unexplored. In this study, systematic laboratory chamber measurements were performed to elucidate the influence of CSOA, ranging from 0.2 to 160 µg m−3, on the phase state of SOA formed by ozonolysis of various precursors, including α-pinene, limonene, cis-3-hexenyl acetate (CHA) and cis-3-hexen-1-ol (HXL). A previously established method to estimate SOA bounce factor (BF, a surrogate for particle viscosity) was utilized to infer particle viscosity as a function of CSOA. Results show that under nominally identical conditions, the maximum BF decreases by approximately 30% at higher CSOA, suggesting a more liquid phase state. With the exception of HXL-SOA (which acted as the negative control), the phase state for all studied SOA precursors varied as a function of CSOA. Furthermore, the BF was found to be the maximum when SOA particle distributions reached a geometric mean particle diameter of 50–60 nm. Experimental results indicate that CSOA is an important parameter impacting the phase state of SOA, reinforcing recent findings that extrapolation of experiments not conducted at atmospherically relevant SOA levels may not yield results that are relevant to the natural environment. Full article
(This article belongs to the Special Issue Formation and Transformation of Organic Aerosol)
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Open AccessArticle Refinement of Modeled Aqueous-Phase Sulfate Production via the Fe- and Mn-Catalyzed Oxidation Pathway
Atmosphere 2018, 9(4), 132; https://doi.org/10.3390/atmos9040132
Received: 28 February 2018 / Revised: 29 March 2018 / Accepted: 31 March 2018 / Published: 1 April 2018
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Abstract
We refined the aqueous-phase sulfate (SO42−) production in the state-of-the-art Community Multiscale Air Quality (CMAQ) model during the Japanese model inter-comparison project, known as Japan’s Study for Reference Air Quality Modeling (J-STREAM). In Japan, SO42− is the major
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We refined the aqueous-phase sulfate (SO42−) production in the state-of-the-art Community Multiscale Air Quality (CMAQ) model during the Japanese model inter-comparison project, known as Japan’s Study for Reference Air Quality Modeling (J-STREAM). In Japan, SO42− is the major component of PM2.5, and CMAQ reproduces the observed seasonal variation of SO42− with the summer maxima and winter minima. However, CMAQ underestimates the concentration during winter over Japan. Based on a review of the current modeling system, we identified a possible reason as being the inadequate aqueous-phase SO42− production by Fe- and Mn-catalyzed O2 oxidation. This is because these trace metals are not properly included in the Asian emission inventories. Fe and Mn observations over Japan showed that the model concentrations based on the latest Japanese emission inventory were substantially underestimated. Thus, we conducted sensitivity simulations where the modeled Fe and Mn concentrations were adjusted to the observed levels, the Fe and Mn solubilities were increased, and the oxidation rate constant was revised. Adjusting the concentration increased the SO42− concentration during winter, as did increasing the solubilities and revising the rate constant to consider pH dependencies. Statistical analysis showed that these sensitivity simulations improved model performance. The approach adopted in this study can partly improve model performance in terms of the underestimation of SO42− concentration during winter. From our findings, we demonstrated the importance of developing and evaluating trace metal emission inventories in Asia. Full article
(This article belongs to the Special Issue Regional Scale Air Quality Modelling)
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Open AccessArticle Seasonal Variability of Airborne Particulate Matter and Bacterial Concentrations in Colorado Homes
Atmosphere 2018, 9(4), 133; https://doi.org/10.3390/atmos9040133
Received: 5 February 2018 / Revised: 25 March 2018 / Accepted: 27 March 2018 / Published: 2 April 2018
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Abstract
Aerosol measurements were collected at fifteen homes over the course of one year in Colorado (USA) to understand the temporal variability of indoor air particulate matter and bacterial concentrations and their relationship with home characteristics, inhabitant activities, and outdoor air particulate matter (PM).
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Aerosol measurements were collected at fifteen homes over the course of one year in Colorado (USA) to understand the temporal variability of indoor air particulate matter and bacterial concentrations and their relationship with home characteristics, inhabitant activities, and outdoor air particulate matter (PM). Indoor and outdoor PM2.5 concentrations averaged (±st. dev.) 8.1 ± 8.1 μg/m3 and 6.8 ± 4.5 μg/m3, respectively. Indoor PM2.5 was statistically significantly higher during summer compared to spring and winter; outdoor PM2.5 was significantly higher for summer compared to spring and fall. The PM2.5 I/O ratio was 1.6 ± 2.4 averaged across all homes and seasons and was not statistically significantly different across the seasons. Average indoor PM10 was 15.4 ± 18.3 μg/m3 and was significantly higher during summer compared to all other seasons. Total suspended particulate bacterial biomass, as determined by qPCR, revealed very little seasonal differences across and within the homes. The qPCR I/O ratio was statistically different across seasons, with the highest I/O ratio in the spring and lowest in the summer. Using one-minute indoor PM10 data and activity logs, it was observed that elevated particulate concentrations commonly occurred when inhabitants were cooking and during periods with elevated outdoor concentrations. Full article
(This article belongs to the Special Issue Indoor Air Pollution)
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Open AccessArticle Statistical Analysis of Spatiotemporal Heterogeneity of the Distribution of Air Quality and Dominant Air Pollutants and the Effect Factors in Qingdao Urban Zones
Atmosphere 2018, 9(4), 135; https://doi.org/10.3390/atmos9040135
Received: 2 March 2018 / Revised: 22 March 2018 / Accepted: 31 March 2018 / Published: 4 April 2018
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Abstract
Air pollution has impacted people’s lives in urban China, and the analysis of the distribution and driving factors behind air quality has become a current research focus. In this study, the temporal heterogeneity of air quality (AQ) and the dominant air pollutants across
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Air pollution has impacted people’s lives in urban China, and the analysis of the distribution and driving factors behind air quality has become a current research focus. In this study, the temporal heterogeneity of air quality (AQ) and the dominant air pollutants across the four seasons were analyzed based on the Kruskal-Wallis rank-sum test method. Then, the spatial heterogeneity of AQ and the dominant air pollutants across four sites were analyzed based on the Wilcoxon signed-rank test method. Finally, the copula model was introduced to analyze the effect of relative factors on dominant air pollutants. The results show that AQ and dominant air pollutants present significant spatiotemporal heterogeneity in the study area. AQ is worst in winter and best in summer. PM10, O3, and PM2.5 are the dominant air pollutants in spring, summer, and winter, respectively. The average concentration of dominant air pollutants presents significant and diverse daily peaks and troughs across the four sites. The main driving factors are pollutants such as SO2, NO2, and CO, so pollutant emission reduction is the key to improving air quality. Corresponding pollution control measures should account for this heterogeneity in terms of AQ and the dominant air pollutants among different urban zones. Full article
(This article belongs to the Section Air Quality)
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Open AccessArticle Enhanced Global Monsoon in Present Warm Period Due to Natural and Anthropogenic Forcings
Atmosphere 2018, 9(4), 136; https://doi.org/10.3390/atmos9040136
Received: 28 February 2018 / Revised: 25 March 2018 / Accepted: 3 April 2018 / Published: 4 April 2018
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Abstract
In this study, we investigate global monsoon precipitation (GMP) changes between the Present Warm Period (PWP, 1900–2000) and the Little Ice Age (LIA, 1250–1850) by performing millennium sensitivity simulations using the Community Earth System Model version 1.0 (CESM1). Three millennium simulations are carried
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In this study, we investigate global monsoon precipitation (GMP) changes between the Present Warm Period (PWP, 1900–2000) and the Little Ice Age (LIA, 1250–1850) by performing millennium sensitivity simulations using the Community Earth System Model version 1.0 (CESM1). Three millennium simulations are carried out under time-varying solar, volcanic and greenhouse gas (GHG) forcing, respectively, from 501 to 2000 AD. Compared to the global-mean surface temperature of the cold LIA, the global warming in the PWP caused by high GHG concentration is about 0.42 °C, by strong solar radiation is 0.14 °C, and by decreased volcanic activity is 0.07 °C. The GMP increases in these three types of global warming are comparable, being 0.12, 0.058, and 0.055 mm day−1, respectively. For one degree of global warming, the GMP increase induced by strong GHG forcing is 2.2% °C−1, by strong solar radiation is 2.8% °C−1, and by decreased volcanic forcing is 5.5% °C−1, which means that volcanic forcing is most effective in terms of changing the GMP among these three external forcing factors. Under volcanic inactivity-related global warming, both monsoon moisture and circulation are enhanced, and the enhanced circulation mainly occurs in the Northern Hemisphere (NH). The circulation, however, is weakened in the other two cases, and the GMP intensification is mainly caused by increased moisture. Due to large NH volcanic aerosol concentration in the LIA, the inter-hemispheric thermal contrast of PWP global warming tends to enhance NH monsoon circulation. Compared to the GHG forcing, solar radiation tends to warm low-latitude regions and cause a greater monsoon moisture increase, resulting in a stronger GMP increase. The finding in this study is important for predicting the GMP in future anthropogenic global warming when a change in natural solar or volcanic activity occurs. Full article
(This article belongs to the Section Climatology and Meteorology)
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Open AccessArticle Atmospheric Distribution of PAHs and Quinones in the Gas and PM1 Phases in the Guadalajara Metropolitan Area, Mexico: Sources and Health Risk
Atmosphere 2018, 9(4), 137; https://doi.org/10.3390/atmos9040137
Received: 27 January 2018 / Revised: 1 April 2018 / Accepted: 3 April 2018 / Published: 5 April 2018
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Abstract
Polycyclic aromatic hydrocarbons (PAHs) and quinones in the gas phase and as submicron particles raise concerns due to their potentially carcinogenic and mutagenic properties. The majority of existing studies have investigated the formation of quinones, but it is also important to consider both
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Polycyclic aromatic hydrocarbons (PAHs) and quinones in the gas phase and as submicron particles raise concerns due to their potentially carcinogenic and mutagenic properties. The majority of existing studies have investigated the formation of quinones, but it is also important to consider both the primary and secondary sources to estimate their contributions. The objectives of this study were to characterize PAHs and quinones in the gas and particulate matter (PM1) phases in order to identify phase distributions, sources, and cancer risk at two urban monitoring sites in the Guadalajara Metropolitan Area (GMA) in Mexico. The simultaneous gas and PM1 phases samples were analyzed using a gas chromatography–mass spectrometer. The lifetime lung cancer risk (LCR) due to PAH exposure was calculated to be 1.7 × 10−3, higher than the recommended risk value of 10−6, indicating a potential health hazard. Correlations between parent PAHs, criteria pollutants, and meteorological parameters suggest that primary sources are the main contributors to the Σ8 Quinones concentrations in PM1, while the secondary formation of 5,12-naphthacenequinone and 9,10-anthraquinone may contribute less to the observed concentration of quinones. Additionally, naphthalene, acenaphthene, fluorene, phenanthrene, and anthracene in PM1, suggest photochemical degradation into unidentified species. Further research is needed to determine how these compounds are formed. Full article
(This article belongs to the Special Issue Urban Particulate Matters: Composition, Sources, and Exposure)
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Open AccessArticle The Global Precipitation Climatology Project (GPCP) Monthly Analysis (New Version 2.3) and a Review of 2017 Global Precipitation
Atmosphere 2018, 9(4), 138; https://doi.org/10.3390/atmos9040138
Received: 15 March 2018 / Revised: 2 April 2018 / Accepted: 4 April 2018 / Published: 7 April 2018
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Abstract
The new Version 2.3 of the Global Precipitation Climatology Project (GPCP) Monthly analysis is described in terms of changes made to improve the homogeneity of the product, especially after 2002. These changes include corrections to cross-calibration of satellite data inputs and updates to
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The new Version 2.3 of the Global Precipitation Climatology Project (GPCP) Monthly analysis is described in terms of changes made to improve the homogeneity of the product, especially after 2002. These changes include corrections to cross-calibration of satellite data inputs and updates to the gauge analysis. Over-ocean changes starting in 2003 resulted in an overall precipitation increase of 1.8% after 2009. Updating the gauge analysis to its final, high-quality version increases the global land total by 1.8% for the post-2002 period. These changes correct a small, incorrect dip in the estimated global precipitation over the last decade given by the earlier Version 2.2. The GPCP analysis is also used to describe global precipitation in 2017. The general La Niña pattern for 2017 is noted and the evolution from the early 2016 El Niño pattern is described. The 2017 global value is one of the highest for the 1979–2017 period, exceeded only by 2016 and 1998 (both El Niño years), and reinforces the small positive trend. Results for 2017 also reinforce significant trends in precipitation intensity (on a monthly scale) in the tropics. These results for 2017 indicate the value of the GPCP analysis, in addition to research, for climate monitoring. Full article
(This article belongs to the Section Climatology and Meteorology)
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Open AccessCommunication A Technique for Estimating Greenhouse Gas Exchange Adjacent Cattle Feedlots
Atmosphere 2018, 9(4), 139; https://doi.org/10.3390/atmos9040139
Received: 28 February 2018 / Revised: 6 April 2018 / Accepted: 6 April 2018 / Published: 9 April 2018
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Abstract
Concentrated animal feeding operations (CAFO) such as open-air beef cattle feedlots are known ‘hot spots’ of emissions of numerous gases including the major greenhouse gases methane, nitrous oxide, and carbon dioxide. Some work has documented CAFOs to derive typical emission factors, but few
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Concentrated animal feeding operations (CAFO) such as open-air beef cattle feedlots are known ‘hot spots’ of emissions of numerous gases including the major greenhouse gases methane, nitrous oxide, and carbon dioxide. Some work has documented CAFOs to derive typical emission factors, but few studies have looked beyond the CAFO to the local landscape to derive the net off-farm emissions. To address the net emissions, the exchange of gases downwind of CAFOs is required, determined in part by the air quality of the gas plume from the CAFO and the characteristics of the underlying surface. Our study measured these downwind fluxes at an open-air beef cattle feedlot using an open-path Fourier Transform Infrared detector and a flux-gradient method. The results showed the dynamic response of fluxes to gas concentration (fresh air or feedlot air) and surface condition (actively growing crop and tilled stubble). These results shed light on the pathways of greenhouse gas flow near a CAFO source, and showed that solely measuring source emissions from a CAFO would lead to errors when developing emission factors. Full article
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Open AccessArticle Freezing on a Chip—A New Approach to Determine Heterogeneous Ice Nucleation of Micrometer-Sized Water Droplets
Atmosphere 2018, 9(4), 140; https://doi.org/10.3390/atmos9040140
Received: 23 February 2018 / Revised: 20 March 2018 / Accepted: 7 April 2018 / Published: 10 April 2018
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Abstract
We are presenting a new approach to analyze the freezing behavior of aqueous droplets containing ice nucleating particles. The freezing chip consists of an etched and sputtered (15 × 15 × 1) mm gold-plated silicon or pure gold chip, enabling the formation of
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We are presenting a new approach to analyze the freezing behavior of aqueous droplets containing ice nucleating particles. The freezing chip consists of an etched and sputtered (15 × 15 × 1) mm gold-plated silicon or pure gold chip, enabling the formation of droplets with defined diameters between 20 and 80 µm. Several applications like an automated process control and an automated image evaluation were implemented to improve the quality of heterogeneous freezing experiments. To show the functionality of the setup, we compared freezing temperatures of aqueous droplets containing ice nucleating particles (i.e., microcline, birch pollen washing water, juniper pollen, and Snomax® solution) measured with our setup, with literature data. The ice nucleation active surface/mass site density (ns/m) of microcline, juniper pollen, and birch pollen washing water are shown to be in good agreement with literature data. Minor variations can be explained by slight differences in composition and droplet generation technique. The nm values of Snomax® differ by up to one order of magnitude at higher subzero temperatures when compared with fresh samples but are in agreement when compared with reported data of aged Snomax® samples. Full article
(This article belongs to the Special Issue Ice Nucleation in the Atmosphere)
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Open AccessArticle Regional Forecasting of Wind Speeds during Typhoon Landfall in Taiwan: A Case Study of Westward-Moving Typhoons
Atmosphere 2018, 9(4), 141; https://doi.org/10.3390/atmos9040141
Received: 6 February 2018 / Revised: 6 April 2018 / Accepted: 8 April 2018 / Published: 10 April 2018
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Abstract
Taiwan is located on a route where typhoons often strike. Each year, the strong winds accompanying typhoons are a substantial threat and cause significant damage. However, because the terrains of high mountains in Taiwan vary greatly, when a typhoon passes the Central Mountain
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Taiwan is located on a route where typhoons often strike. Each year, the strong winds accompanying typhoons are a substantial threat and cause significant damage. However, because the terrains of high mountains in Taiwan vary greatly, when a typhoon passes the Central Mountain Range (CMR), the wind speed of typhoons becomes difficult to predict. This research had two primary objectives: (1) to develop data-driven techniques and a powerful artificial neural network (ANN) model to predict the highly complex nonlinear wind systems in western Taiwan; and, (2) to investigate the accuracy of wind speed predictions at various locations and for various durations in western Taiwan when the track of westward typhoons is affected by the complex geographical shelters and disturbances of the CMR. This study developed a typhoon wind speed prediction model that evaluated various typhoon tracks (covering Type 2, Type 3, and Type 4 tracks, as defined by the Central Weather Bureau), and evaluated the prediction accuracy at Hsinchu, Wuqi, and Kaohsiung Stations in western Taiwan. Back propagation neural networks (BPNNs) were employed to establish wind speed prediction models, and a linear regression model was adopted as the benchmark to evaluate the strengths and weaknesses of the BPNNs. The results were as follows: (1) The BPNNs generally had favorable performance in predicting wind speeds and their performances were superior to linear regressions; (2) when absolute errors were adopted to evaluate the prediction performances, the predictions at Hsinchu Station were the most accurate, whereas those at Wuqi Station were the least accurate; however, when relative errors were adopted, the predictions at Hsinchu Station were again the most accurate, whereas those at Kaohsiung were the least accurate; and, (3) regarding the relative error rates for the maximum wind speed of Types 2, 3, and 4 typhoons, Wuqi, Kaohsiung, and Wuqi had the most accurate performance, respectively; as for maximum wind time error (ETM) for Types 2, 3, and 4 typhoons, Kaohsiung, Wuqi, and Wuqi correspondingly performed the most favorably. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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Open AccessArticle Oasis Irrigation-Induced Hydro-Climatic Effects: A Case Study in the Hyper-Arid Region of Northwest China
Atmosphere 2018, 9(4), 142; https://doi.org/10.3390/atmos9040142
Received: 7 February 2018 / Revised: 29 March 2018 / Accepted: 3 April 2018 / Published: 10 April 2018
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Abstract
The response of potential evapotranspiration (ET0) to widespread irrigation is important to fully understand future regional climate changes and to infer adaptive management of agricultural water resources. The quantitative impact of irrigation on ET0 from 1960 to 2013 was evaluated using historical time
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The response of potential evapotranspiration (ET0) to widespread irrigation is important to fully understand future regional climate changes and to infer adaptive management of agricultural water resources. The quantitative impact of irrigation on ET0 from 1960 to 2013 was evaluated using historical time series data of daily meteorological observations in the hyper-arid region of northwest China. The decreasing trends in ET0 were accelerated for meteorological stations in regions with oasis agriculture, especially in the summer and during the growing season. Irrigation led to a cooling effect on temperature, increased relative humidity and precipitation. All of these changes contributed to a larger decrease of ET0 trend. The findings of this study advance our insight into the effects of irrigation on dynamics in ET0 and meteorological factors. Further investigations to understand how ET0 responds to climate change and agricultural irrigation could provide guidance for determining effective measures of water resources for adapting to global change. Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land - Atmosphere Interactions)
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Open AccessArticle Observed Correlation between Aerosol and Cloud Base Height for Low Clouds at Baltimore and New York, United States
Atmosphere 2018, 9(4), 143; https://doi.org/10.3390/atmos9040143
Received: 12 February 2018 / Revised: 19 March 2018 / Accepted: 4 April 2018 / Published: 11 April 2018
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Abstract
The correlation between aerosol particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) and cloud base height (CBH) of low clouds (CBH lower than 1.5 km a.g.l.) at Baltimore and New York, United States, for an 8 year period (2007–2014) was
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The correlation between aerosol particulate matter with aerodynamic diameter ≤2.5 μ m (PM2.5) and cloud base height (CBH) of low clouds (CBH lower than 1.5 km a.g.l.) at Baltimore and New York, United States, for an 8 year period (2007–2014) was investigated using information from the Automated Surface Observing System (ASOS) observations and collocated U.S. Environmental Protection Agency (EPA) observations. The lifting condensation level (LCL) heights were calculated and compared with the CBH. The monthly average observations show that PM2.5 decreases from 2007 to 2014 while there is no significant trend found for CBH and LCL. The variability of the LCL height agrees well with CBH but LCL height is systematically lower than CBH (~180 m lower). There was a significant negative correlation found between CBH–LCL and PM2.5. All of the cloud cases were separated into polluted and clean conditions based on the distribution of PM2.5 values. The distributions of CBH–LCL in the two groups show more cloud cases with smaller CBH–LCL in polluted conditions than in clean conditions. Full article
(This article belongs to the Special Issue Atmospheric Aerosol Composition and its Impact on Clouds)
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Open AccessArticle Hazard Quotients, Hazard Indexes, and Cancer Risks of Toxic Metals in PM10 during Firework Displays
Atmosphere 2018, 9(4), 144; https://doi.org/10.3390/atmos9040144
Received: 19 March 2018 / Revised: 5 April 2018 / Accepted: 6 April 2018 / Published: 12 April 2018
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Abstract
Bonfire night is a worldwide phenomenon given to numerous annual celebrations characterised by bonfires and fireworks. Since Thailand has no national ambient air quality standards for metal particulates, it is important to investigate the impacts of particulate injections on elevations of air pollutants
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Bonfire night is a worldwide phenomenon given to numerous annual celebrations characterised by bonfires and fireworks. Since Thailand has no national ambient air quality standards for metal particulates, it is important to investigate the impacts of particulate injections on elevations of air pollutants and the ecological health impacts resulting from firework displays. In this investigation, Pb and Ba were considered potential firework tracers because their concentrations were significantly higher during the episode, and lower than/comparable with minimum detection limits during other periods, indicating that their elevated concentrations were principally due to pyrotechnic displays. Pb/Ca, Pb/Al, Pb/Mg, and Pb/Cu can be used to pin-point emissions from firework displays. Air mass backward trajectories (72 h) from the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model indicated that areas east and north-east of the study site were the main sources of the airborne particles. Although the combined risk associated with levels of Pb, Cr, Co., Ni, Zn, As, Cd, V, and Mn was far below the standards mentioned in international guidelines, the lifetime cancer risks associated with As and Cr levels exceeded US-EPA guidelines, and may expose inhabitants of surrounding areas of Bangkok to an elevated cancer risk. Full article
(This article belongs to the Special Issue Urban Particulate Matters: Composition, Sources, and Exposure)
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Open AccessArticle Air-Pollutant Emissions from Agricultural Burning in Mae Chaem Basin, Chiang Mai Province, Thailand
Atmosphere 2018, 9(4), 145; https://doi.org/10.3390/atmos9040145
Received: 20 February 2018 / Revised: 2 April 2018 / Accepted: 10 April 2018 / Published: 13 April 2018
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Abstract
Particulate pollution is a continual problem which is usually caused by the burning of crop residues in highland agricultural systems. The objectives of this study are to investigate crop-residue management and estimate the amount of pollutant emissions from burning crop residues for each
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Particulate pollution is a continual problem which is usually caused by the burning of crop residues in highland agricultural systems. The objectives of this study are to investigate crop-residue management and estimate the amount of pollutant emissions from burning crop residues for each land-use pattern (grain maize, seed maize and integrated farming), and to estimate the chemical compositions of PM2.5 emissions from agricultural burning in Mae Chaem basin, Chiang Mai Province, Thailand. The purposive sampling method was used for sample selection. A door-to-door questionnaire survey was used to obtain responses from 149 respondents. Greenhouse gas (GHG) emissions from the open burning of crop residues were estimated, using specific emission factors obtained from several literature reviews and from the field by the questionnaire survey. Results revealed that the majority of farmers burned maize residues during April and May and mostly in the afternoon. These burning behaviors are in line with the supportive weather conditions that reflect high values of temperature and wind speed, and less rainfall and relative humidity result in maize residues being burned easily and quickly. The integrated farming system generated the lowest GHG emissions and amount of chemical composition of PM2.5 emissions, followed by the grain maize and seed maize patterns, respectively. This study strongly supports the implementation of the integrated farming system in Mae Chaem basin. Proactive and reactive measures should be taken in a well-organized and systematic fashion and should engage all related parties. More importantly, there is an urgent need for policy makers to include PM2.5 concentrations to upgrade Thailand’s air-quality index (PM2.5 AQI). Full article
(This article belongs to the Special Issue Fire and the Atmosphere)
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Open AccessArticle Accounting for Field-Scale Dry Deposition in Backward Lagrangian Stochastic Dispersion Modelling of NH3 Emissions
Atmosphere 2018, 9(4), 146; https://doi.org/10.3390/atmos9040146
Received: 27 February 2018 / Revised: 26 March 2018 / Accepted: 4 April 2018 / Published: 14 April 2018
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Abstract
A controlled ammonia (NH3) release experiment was performed at a grassland site. The aim was to quantify the effect of dry deposition between the source and the receptors (NH3 measurement locations) on emission rate estimates by means of inverse dispersion
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A controlled ammonia (NH3) release experiment was performed at a grassland site. The aim was to quantify the effect of dry deposition between the source and the receptors (NH3 measurement locations) on emission rate estimates by means of inverse dispersion modelling. NH3 was released for three hours at a constant rate of Q = 6.29 mg s−1 from a grid of 36 orifices spread over an area of 250 m2. The increase in line-integrated NH3 concentration was measured with open-path optical miniDOAS devices at different locations downwind of the artificial source. Using a backward Lagrangian stochastic (bLS) dispersion model (bLSmodelR), the fraction of the modelled release rate to the emitted NH3 ( Q bLS / Q ) was calculated from the measurements of the individual instruments. Q bLS / Q was found to be systematically lower than 1, on average between 0.69 and 0.91, depending on the location of the receptor. We hypothesized that NH3 dry deposition to grass and soil surfaces was the main factor responsible for the observed depletion of NH3 between source and receptor. A dry deposition algorithm based on a deposition velocity approach was included in the bLS modelling. Model deposition velocities were evaluated from a ‘big-leaf’ canopy resistance analogy. Canopy resistances (generally termed R c ) that provided Q bLS / Q = 1 ranged from 75 to 290 s m−1, showing that surface removal of NH3 by dry deposition can plausibly explain the original underestimation of Q bLS / Q . The inclusion of a dry deposition process in dispersion modelling is crucial for emission estimates, which are based on concentration measurements of depositing tracers downwind of homogeneous area sources or heterogeneously-distributed hot spots, such as, e.g., urine patches on pastures in the case of NH3. Full article
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Open AccessArticle The Impacts of Vegetation and Meteorological Factors on Aerodynamic Roughness Length at Different Time Scales
Atmosphere 2018, 9(4), 149; https://doi.org/10.3390/atmos9040149
Received: 27 February 2018 / Revised: 26 March 2018 / Accepted: 10 April 2018 / Published: 16 April 2018
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Abstract
The aerodynamic roughness length (z0m) is a crucial parameter for reliably simulating turbulent exchanges between the land surface and the atmosphere. Due to the large number of input variables related to vegetation growth and aerodynamic conditions near the surface, estimating z
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The aerodynamic roughness length (z0m) is a crucial parameter for reliably simulating turbulent exchanges between the land surface and the atmosphere. Due to the large number of input variables related to vegetation growth and aerodynamic conditions near the surface, estimating z0m precisely is difficult and, to date, no universal model has been established. Understanding the z0m changes in time series data and the relative contributions of vegetation indices and meteorological factors is important to providing a basis for modelling z0m. In this paper, the main meteorological factors that influence z0m in different seasons are presented based on data from three automatic weather stations (AWSs) that represent various land surface patterns in the Heihe river basin. A correlation analysis identified the dominant factors that influence z0m changes at half-hour and daily scales; then, a factor analysis was performed to identify the different contributions of vegetation indices and meteorological factors to z0m at different time scales. The results show that meteorological factors (wind speed, wind direction and atmospheric stability) are the main driving factors for z0m at the Arou and Guantan sites, which are situated in grassland and forest mountain areas, respectively, and that the vegetation indices have no impact on the z0m variations in these areas. In contrast, for the Daman site, situated in flat farmland, the vegetation indices are the primary driving factors, while meteorological factors such as wind speed and atmospheric stability are secondary factors, and wind direction has no significant influence. Finally, a detailed analysis was conducted to detect the relationships between half-hourly z0m measurements and three dominant meteorological factors. Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land - Atmosphere Interactions)
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Open AccessArticle An Uncertainty Investigation of RCM Downscaling Ratios in Nonstationary Extreme Rainfall IDF Curves
Atmosphere 2018, 9(4), 151; https://doi.org/10.3390/atmos9040151
Received: 16 March 2018 / Revised: 6 April 2018 / Accepted: 16 April 2018 / Published: 18 April 2018
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Abstract
Designed for rainstorms and flooding, hydrosystems are largely based on local rainfall Intensity–Duration–Frequency (IDF) curves which include nonstationary components accounting for climate variability. IDF curves are commonly calculated using downscaling outputs from General Circulation Models (GCMs) or Regional Circulation Models (RCMs). However, the
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Designed for rainstorms and flooding, hydrosystems are largely based on local rainfall Intensity–Duration–Frequency (IDF) curves which include nonstationary components accounting for climate variability. IDF curves are commonly calculated using downscaling outputs from General Circulation Models (GCMs) or Regional Circulation Models (RCMs). However, the downscaling procedures used in most studies are based on one specific time scale (e.g., 1 h) and generally ignore scale-driven uncertainty. This study analyzes the uncertainties in IDF curves stemming from RCM downscaling ratios for four representative weather stations in the United Kingdom. We constructed a series of IDF curves using distribution-based scaling bias-correction technology and a statistical downscaling method to explore the scale-driven uncertainty of IDF curves. The results revealed considerable scale-induced uncertainty of IDF curves for short durations and long return periods; however, there was no clear correlation with the mean storm intensity of the IDF curves of different RCM ensemble members for each duration and return period. The scale-driven uncertainty of IDF curves, which may be propagated or enhanced through hydrometeorological applications, is critical and cannot be ignored in the hydrosystem design process; therefore, a multi-scale method to derive IDF curves must be developed. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Atmospheric Emissions from Oil and Gas Extraction and Production in Greece
Atmosphere 2018, 9(4), 152; https://doi.org/10.3390/atmos9040152
Received: 25 November 2017 / Revised: 6 April 2018 / Accepted: 12 April 2018 / Published: 18 April 2018
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Abstract
This paper addresses the atmospheric emissions of CO2, SO2, H2S, NOx, and volatile organic compounds (VOCs) from oil and gas extraction and production in the Gulf of Kavala. This is currently the only location of oil and
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This paper addresses the atmospheric emissions of CO2, SO2, H2S, NOx, and volatile organic compounds (VOCs) from oil and gas extraction and production in the Gulf of Kavala. This is currently the only location of oil and gas production in Greece. Facilities are located both offshore (Kappa and Delta platforms) and onshore (Sigma plant), producing sweet gas, sour gas, and sour crude oil. This study presents the characteristics of atmospheric emissions, including emission measurements, emission inventories, and concentration measurements, from a central monitoring station and twelve total sulfation stations, the latter aiming to assess the effects of atmospheric emissions to air quality. During the development of the monitoring system, special attention was placed to sulfur compounds, since the existence of sour gas and sour crude oil was expected to lead to increased amounts of H2S and SO2. One of the main findings of the present study is that if the prevailing wind direction is considered (i.e., from N–NE), then the central monitoring station is not located downwind of the onshore and offshore facilities; therefore, its position should be re-examined. The emission inventories showed that flaring at the offshore facilities is the main source of SO2 emissions, while SO2 emissions and ambient concentrations were well below the relevant standards. Furthermore, CO2 emissions were lower by 67.73% as compared to 2008, when emissions reached a maximum. This was attributed to more energy demanding activities during that period, and mainly to the operation of turbines between 2007 and 2009. Since it is expected that the exploitation of hydrocarbons as well as oil and gas extraction and production will increase in the future in Greece, appropriate measures should be taken to ensure environmental protection, such as the use of up-to-date emission control technologies and a flare gas recovery system. Full article
(This article belongs to the Special Issue Advances in Atmospheric Physics: Selected Papers from CEST2017)
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Open AccessArticle Cloud Longwave Scattering Effect and Its Impact on Climate Simulation
Atmosphere 2018, 9(4), 153; https://doi.org/10.3390/atmos9040153
Received: 29 January 2018 / Revised: 4 April 2018 / Accepted: 11 April 2018 / Published: 18 April 2018
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Abstract
The cloud longwave (LW) scattering effect has been ignored in most current climate models. To investigate its climate impact, we apply an eight-stream DIScrete Ordinates Radiative Transfer (DISORT) scheme to include the cloud LW scattering in the General circulation model version of the
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The cloud longwave (LW) scattering effect has been ignored in most current climate models. To investigate its climate impact, we apply an eight-stream DIScrete Ordinates Radiative Transfer (DISORT) scheme to include the cloud LW scattering in the General circulation model version of the LongWave Rapid Radiative Transfer Model (RRTMG_LW) and the Community Atmospheric Model Version 5 (CAM5). Results from the standalone RRTMG_LW and from diagnostic runs of CAM5 (no climate feedback) show that the cloud LW scattering reduces the upward flux at the top of the atmosphere and leads to an extra warming effect in the atmosphere. In the interactive runs with climate feedback included in CAM5, the cloud LW scattering effect is amplified by the water vapor-temperature feedback in a warmer atmosphere and has substantial influences on cloud fraction and specific humidity. The thermodynamic feedbacks are more significant in the northern hemisphere and the resulting meridional temperature gradient is different between the two hemispheres, which strengthens the southern branch of Hadley circulation, and modulates the westerly jet near 50° S and the upper part of Walker circulation. Our study concludes that the cloud LW scattering effect could have complex impacts on the global energy budget and shall be properly treated in future climate models. Full article
(This article belongs to the Special Issue Cloud Radiative Processes and Effect)
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Open AccessArticle Combined Effects of Synoptic-Scale Teleconnection Patterns on Summer Precipitation in Southern China
Atmosphere 2018, 9(4), 154; https://doi.org/10.3390/atmos9040154
Received: 2 March 2018 / Revised: 8 April 2018 / Accepted: 16 April 2018 / Published: 19 April 2018
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Abstract
Using ERA-Interim daily reanalysis and precipitation data, the combined effects of East Asia-Pacific (EAP) and Silk Road (SR) teleconnection patterns on summer precipitation in Southern China were investigated on synoptic to sub-monthly timescales. Combined EAP and SR patterns lead to more persistent and
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Using ERA-Interim daily reanalysis and precipitation data, the combined effects of East Asia-Pacific (EAP) and Silk Road (SR) teleconnection patterns on summer precipitation in Southern China were investigated on synoptic to sub-monthly timescales. Combined EAP and SR patterns lead to more persistent and extreme precipitation in the Yangtze River Valley (YRV) and exhibit an obvious zonal advance between the South Asia High (SAH) and Western Pacific Subtropical High (WPSH) prior to its onset. During typical combined events, an overlap between the SAH and WPSH remains in a favorable position for Persistent Extreme Precipitation (PEP). Furthermore, SR-induced acceleration of the westerly jet stream and extra positive vorticity advection provide persistent upper-level divergence for YRV precipitation. An anomalous EAP-related cyclone/anticyclone pair over East Asia induces enhanced low-level southwesterlies to the northern anticyclone flank and northerlies from the mid-latitudes, advecting anomalously abundant moisture toward the YRV, resulting in clear moisture convergence. Moreover, the strong ascent of warmer/moister air along a quasi-stationary front may be crucial for PEP. During decay, the SAH and WPSH diverge from each other and retreat to their normal positions, and the strong ascent of warmer/moister air rapidly weakens to dissipation, terminating PEP in the YRV. Full article
(This article belongs to the Special Issue Weather and Climate Extremes: Current Developments)
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Open AccessArticle Long-Term Rainfall Trends over the Tanzania Coast
Atmosphere 2018, 9(4), 155; https://doi.org/10.3390/atmos9040155
Received: 28 February 2018 / Revised: 30 March 2018 / Accepted: 4 April 2018 / Published: 20 April 2018
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Abstract
Spatial and temporal rainfall trends over the Tanzanian coast are analysed and trends for over 50 years are investigated. This type of study is crucial at this time because the area under study is now one of the world’s economic hotspots, as major
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Spatial and temporal rainfall trends over the Tanzanian coast are analysed and trends for over 50 years are investigated. This type of study is crucial at this time because the area under study is now one of the world’s economic hotspots, as major gas fields have been discovered and the area also has high potential for oil field discoveries. Methods applied in this study include the Mann-Kendall test for rainfall data to detect the long-term trends, while Sen’s slope estimator test was used for finding the magnitude of change over time. The results exhibited rainfall trend patterns with substantial variations between the stations. The Z value of the Mann-Kendall test showed various months with negative trend at a significance level ≥95%. The few months that showed a positive trend were not statistically significant. Generally, rainfall trends varied in different months for different stations. However, the most outstanding observation on individual months is July, which showed a highly statistically significant (99.9%) reduction in rainfall for the whole coastal area, including the regions of Mtwara, Dar es Salaam and Tanga. The last part of this paper describes the relationship between July rainfall and the horizontal winds from the National Centre for Environmental Prediction/National Centre for Atmospheric Research (NCEP/NCAR) re-analysis. It is observed that the strength of the anticyclonic flow over the southwest Indian Ocean, which is associated with the westward fluxes of moisture, is responsible for rainfall over the whole coastal area of Tanzania during July. Full article
(This article belongs to the Special Issue Precipitation Variability and Change in Africa)
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Open AccessArticle Spatial Factor Analysis for Aerosol Optical Depth in Metropolises in China with Regard to Spatial Heterogeneity
Atmosphere 2018, 9(4), 156; https://doi.org/10.3390/atmos9040156
Received: 4 March 2018 / Revised: 12 April 2018 / Accepted: 18 April 2018 / Published: 20 April 2018
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Abstract
A substantial number of studies have analyzed how driving factors impact aerosols, but they have been little concerned with the spatial heterogeneity of aerosols and the factors that impact aerosols. The spatial distributions of the aerosol optical depth (AOD) retrieved by Moderate Resolution
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A substantial number of studies have analyzed how driving factors impact aerosols, but they have been little concerned with the spatial heterogeneity of aerosols and the factors that impact aerosols. The spatial distributions of the aerosol optical depth (AOD) retrieved by Moderate Resolution Imaging Spectrometer (MODIS) data at 550-nm and 3-km resolution for three highly developed metropolises, the Beijing-Tianjin-Hebei (BTH) region, the Yangtze River Delta (YRD), and the Pearl River Delta (PRD), in China during 2015 were analyzed. Different degrees of spatial heterogeneity of the AOD were found, which were indexed by Moran’s I index giving values of 0.940, 0.715, and 0.680 in BTH, YRD, and PRD, respectively. For the spatial heterogeneity, geographically weighted regression (GWR) was employed to carry out a spatial factor analysis, where terrain, climate condition, urban development, and vegetation coverage were taken as the potential driving factors. The results of the GWR imply varying relationships between the AOD and the factors. The results were generally consistent with existing studies, but the results suggest the following: (1) Elevation increase would more likely lead to a strong negative impact on aerosols (with most of the coefficients ranging from −1.5~0 in the BTH, −1.5~0 in the YRD, and −1~0 in the PRD) in the places with greater elevations where the R-squared values are always larger than 0.5. However, the variation of elevations cannot explain the variation of aerosols in the places with relatively low elevations (with R-squared values approximately 0.1, ranging from 0 to 0.3, and approximately 0.1 in the BTH, YRD, and PRD), such as urban areas in the BTH and YRD. (2) The density of the built-up areas made a strong and positive impact on aerosols in the urban areas of the BTH (R-squared larger than 0.5), while the R-squared dropped to 0.1 in the places far away from the urban areas. (3) The vegetation coverage led to a stronger relief on the AOD in parts of the YRD and PRD (with coefficients less than −0.6 and ranging from −0.4~−0.6, respectively) where there is greater vegetation coverage, and led to a weaker relief on the AOD in the urban area of the PRD with a coefficient of approximately −0.2~−0.4. Full article
(This article belongs to the Special Issue Aerosol Optical Properties: Models, Methods & Measurements)
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Open AccessArticle PM2.5 Characteristics and Regional Transport Contribution in Five Cities in Southern North China Plain, During 2013–2015
Atmosphere 2018, 9(4), 157; https://doi.org/10.3390/atmos9040157
Received: 4 March 2018 / Revised: 3 April 2018 / Accepted: 12 April 2018 / Published: 21 April 2018
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Abstract
PM2.5 data from major cities in the southern North China Plain during 2013–2015 were comprehensively analyzed relative to variation features, meteorology effects, and regional transport contributions. The annual average ranged from 87 to 123 μg m−3, with the highest in
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PM2.5 data from major cities in the southern North China Plain during 2013–2015 were comprehensively analyzed relative to variation features, meteorology effects, and regional transport contributions. The annual average ranged from 87 to 123 μg m−3, with the highest in Baoding and Shijiazhuang, the moderate in Handan and Hengshui, and the lowest in Cangzhou, which revealed an evident concentration gradient with distance from the mountains. PM2.5 pollution indicated significantly regional characteristics and high correlations in daily PM2.5 changes and similar seasonal and diurnal variations in five cities. The highest concentrations mainly occurred in the winter, then autumn, spring, and summer, and the diurnal variations were bimodal with peaks during the morning rush hours and at night, which were mostly dominated by the differences in source emissions and the boundary layer. The PM2.5 concentrations were significantly positively correlated with relative humidity, especially during winter. The highest PM2.5 concentrations in all cities were associated with the south, southeast, and southwest pathways, while the short northwest pathway in the winter for Baoding and Shijiazhuang experienced the highest concentration. Regional contributions ranged from 19.6 to 33.7% annually, with the largest in Baoding and Shijiazhuang. These results provide a scientific basis for pollution forecasting and control in these heavily polluted cities. Full article
(This article belongs to the Special Issue Air Quality in China: Past, Present and Future)
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Open AccessReview A Review of Paleo El Niño-Southern Oscillation
Atmosphere 2018, 9(4), 130; https://doi.org/10.3390/atmos9040130
Received: 16 February 2018 / Revised: 26 March 2018 / Accepted: 27 March 2018 / Published: 30 March 2018
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Abstract
The Earth has seen El Niño-Southern Oscillation (ENSO)—the leading mode of interannual climate variability—for at least millennia and likely over millions of years. This paper reviews previous studies from perspectives of both paleoclimate proxy data (from traditional sediment records to the latest high-resolution
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The Earth has seen El Niño-Southern Oscillation (ENSO)—the leading mode of interannual climate variability—for at least millennia and likely over millions of years. This paper reviews previous studies from perspectives of both paleoclimate proxy data (from traditional sediment records to the latest high-resolution oxygen isotope records) and model simulations (including earlier intermediate models to the latest isotope-enabled coupled models). It summarizes current understanding of ENSO’s past evolution during both interglacial and glacial periods and its response to external climatic forcings such as volcanic, orbital, ice-sheet and greenhouse gas forcings. Due to the intrinsic irregularity of ENSO and its complicated relationship with other climate phenomena, reconstructions and model simulations of ENSO variability are subject to inherent difficulties in interpretations and biases. Resolving these challenges through new data syntheses, new statistical methods, more complex climate model simulations as well as direct model-data comparisons can potentially better constrain uncertainty regarding ENSO’s response to future global warming. Full article
(This article belongs to the Special Issue El Niño Southern Oscillation (ENSO))
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Open AccessReview Land-Use Regression Modelling of Intra-Urban Air Pollution Variation in China: Current Status and Future Needs
Atmosphere 2018, 9(4), 134; https://doi.org/10.3390/atmos9040134
Received: 1 March 2018 / Revised: 30 March 2018 / Accepted: 1 April 2018 / Published: 3 April 2018
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Abstract
Rapid urbanization in China is leading to substantial adverse air quality issues, particularly for NO2 and particulate matter (PM). Land-use regression (LUR) models are now being applied to simulate pollutant concentrations with high spatial resolution in Chinese urban areas. However, Chinese urban
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Rapid urbanization in China is leading to substantial adverse air quality issues, particularly for NO2 and particulate matter (PM). Land-use regression (LUR) models are now being applied to simulate pollutant concentrations with high spatial resolution in Chinese urban areas. However, Chinese urban areas differ from those in Europe and North America, for example in respect of population density, urban morphology and pollutant emissions densities, so it is timely to assess current LUR studies in China to highlight current challenges and identify future needs. Details of twenty-four recent LUR models for NO2 and PM2.5/PM10 (particles with aerodynamic diameters <2.5 µm and <10 µm) are tabulated and reviewed as the basis for discussion in this paper. We highlight that LUR modelling in China is currently constrained by a scarcity of input data, especially air pollution monitoring data. There is an urgent need for accessible archives of quality-assured measurement data and for higher spatial resolution proxy data for urban emissions, particularly in respect of traffic-related variables. The rapidly evolving nature of the Chinese urban landscape makes maintaining up-to-date land-use and urban morphology datasets a challenge. We also highlight the importance for Chinese LUR models to be subject to appropriate validation statistics. Integration of LUR with portable monitor data, remote sensing, and dispersion modelling has the potential to enhance derivation of urban pollution maps. Full article
(This article belongs to the Section Air Quality)
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Open AccessReview A Review of Airborne Particulate Matter Effects on Young Children’s Respiratory Symptoms and Diseases
Atmosphere 2018, 9(4), 150; https://doi.org/10.3390/atmos9040150
Received: 12 March 2018 / Revised: 11 April 2018 / Accepted: 13 April 2018 / Published: 16 April 2018
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Abstract
Exposure to airborne fine particulate matter (PM2.5) carries substantial health risks, particularly for younger children (0–10 years). Epidemiological evidence indicates that children are more susceptible to PM health effects than adults. We conducted a literature review to obtain an overview of
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Exposure to airborne fine particulate matter (PM2.5) carries substantial health risks, particularly for younger children (0–10 years). Epidemiological evidence indicates that children are more susceptible to PM health effects than adults. We conducted a literature review to obtain an overview of existing knowledge regarding the correlation of exposure to short- and long-term PM concentrations with respiratory symptoms and disease in children. A collection of scientific papers and topical reviews were selected in cooperation with two experienced paediatricians. The literature review was performed using the keywords “air pollution”, “particulate matter”, “children’s health” and “respiratory” from 1950 to 2016, searching the databases of Scopus, Google Scholar, Web of Science, and PubMed. The search provided 45,191 studies for consideration. Following the application of eligibility criteria and experts’ best judgment to titles and abstracts, 28 independent studies were deemed relevant for further detailed review and knowledge extraction. The results showed that most studies focused mainly on the effect of short-term exposure in children, and the reported associations were relatively homogeneous amongst the studies. Most of the respiratory diseases observed in outdoor studies were related to changes in lung function and exacerbation of asthma symptoms. Allergic reactions were frequently reported in indoor studies. Asthma exacerbation, severe respiratory symptoms and moderate airway obstruction on spirometry were also observed in children due to various sources of indoor pollution in households and schools. Mixed indoor and outdoor studies indicate frequent occurrence of wheezing and deterioration of lung function. There is good evidence of the adverse effect of short-term exposure to PM on children’s respiratory health. In terms of long-term exposure, fine particles (PM0.1–PM2.5) represent a higher risk factor than coarse particles (PM2.5–PM10). Additional research is required to better understand the heterogeneous sources and the association of PM and adverse children’s health outcomes. We recommend long-term cooperation between air quality specialists, paediatricians, epidemiologists, and parents in order to improve the knowledge of PM effects on young children’s respiratory health. Full article
(This article belongs to the Special Issue Impacts of Air Pollution on Human Health)
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Other

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Open AccessCorrection Correction: Koutsouris et al. Utilization of Global Precipitation Datasets in Data Limited Regions: A Case Study of Kilombero Valley, Tanzania. Atmosphere, 2017, 8, 246
Atmosphere 2018, 9(4), 148; https://doi.org/10.3390/atmos9040148
Received: 3 April 2018 / Revised: 3 April 2018 / Accepted: 3 April 2018 / Published: 16 April 2018
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Abstract
The authors would like to correct the published article [1], following the detection of editorial mistakes by the main author, as explained below[...] Full article
(This article belongs to the Special Issue Precipitation Variability and Change in Africa)
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