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Atmosphere, Volume 5, Issue 4 (December 2014) , Pages 699-1041

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Open AccessArticle
Can Agrometeorological Indices of Adverse Weather Conditions Help to Improve Yield Prediction by Crop Models?
Atmosphere 2014, 5(4), 1020-1041; https://doi.org/10.3390/atmos5041020
Received: 11 September 2014 / Revised: 17 November 2014 / Accepted: 17 November 2014 / Published: 15 December 2014
Cited by 6 | Viewed by 2522 | PDF Full-text (788 KB) | HTML Full-text | XML Full-text
Abstract
The impact of adverse weather conditions (AWCs) on crop production is random in both time and space and depends on factors such as severity, previous agrometeorological conditions, and plant vulnerability at a specific crop development stage. Any exclusion or improper treatment of any [...] Read more.
The impact of adverse weather conditions (AWCs) on crop production is random in both time and space and depends on factors such as severity, previous agrometeorological conditions, and plant vulnerability at a specific crop development stage. Any exclusion or improper treatment of any of these factors can cause crop models to produce significant under- or overestimates of yield. The analysis presented in this paper focuses on a range of agrometeorological indices (AMI) related to AWCs that might affect real yield as well as simulated yield. For this purpose, the analysis addressed four indicators of extreme temperatures and three indicators of dry conditions during the growth period of maize and winter wheat in Austria, Croatia, Serbia, Slovakia, and Sweden. It is shown that increases in the number and intensity of AWCs cannot be unambiguously associated with increased deviations in simulated yields. The identified correlations indicate an increase in modeling uncertainty. This finding represents important information for the crop modeling community. Additionally, it opens a window of opportunity for a statistical (“event scenario”) approach based on correlations between agrometeorological indices of AWCs and crop yield data series. This approach can provide scenarios for certain locations, crop types, and AWC patterns and, therefore, improve yield forecasting in the presence of AWCs. Full article
Open AccessArticle
Estimation of Black Carbon Emissions from Dry Dipterocarp Forest Fires in Thailand
Atmosphere 2014, 5(4), 1002-1019; https://doi.org/10.3390/atmos5041002
Received: 31 July 2014 / Revised: 10 October 2014 / Accepted: 23 October 2014 / Published: 5 December 2014
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Abstract
This study focused on the estimation of black carbon emissions from dry dipterocarp forest fires in Thailand. Field experiments were set up at the natural forest, Mae Nam Phachi wildlife sanctuary, Ratchaburi Province, Thailand. The dead leaves were the main component consumed of [...] Read more.
This study focused on the estimation of black carbon emissions from dry dipterocarp forest fires in Thailand. Field experiments were set up at the natural forest, Mae Nam Phachi wildlife sanctuary, Ratchaburi Province, Thailand. The dead leaves were the main component consumed of the surface biomass with coverage higher than 90% in volume and mass. The dead leaves load was 342 ± 190 g∙m−2 and followed by a little mass load of twig, 100 g∙m−2. The chemical analysis of the dead leaves showed that the carbon content in the experimental biomass fuel was 45.81 ± 0.04%. From the field experiments, it was found that 88.38 ± 2.02% of the carbon input was converted to carbon released to the atmosphere, while less than 10% were left in the form of residues, and returned to soil. The quantity of dead leaves consumed to produce each gram of carbon released was 2.40 ± 0.02 gdry biomass burned. From the study, the emissions factor of carbon dioxide, carbon monoxide, particulate matter (PM2.5) and black carbon amounted 1329, 90, 26.19 and 2.83 g∙kg−1dry biomass burned, respectively. In Thailand, the amount of black carbon emissions from dry dipterocarp forest fires amounted 17.43 tonnes∙y−1. Full article
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Open AccessArticle
Meteorological Influences on Trace Gas Transport along the North Atlantic Coast during ICARTT 2004
Atmosphere 2014, 5(4), 973-1001; https://doi.org/10.3390/atmos5040973
Received: 27 February 2014 / Revised: 7 October 2014 / Accepted: 30 October 2014 / Published: 4 December 2014
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Abstract
An analysis of coastal meteorological mechanisms facilitating the transit pollution plumes emitted from sources in the Northeastern U.S. was based on observations from the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) 2004 field campaign. Particular attention was given to the [...] Read more.
An analysis of coastal meteorological mechanisms facilitating the transit pollution plumes emitted from sources in the Northeastern U.S. was based on observations from the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) 2004 field campaign. Particular attention was given to the relation of these plumes to coastal transport patterns in lower tropospheric layers throughout the Gulf of Maine (GOM), and their contribution to large-scale pollution outflow from the North American continent. Using measurements obtained during a series of flights of the National Oceanic & Atmospheric Administration (NOAA) WP-3D and the National Aeronautics and Space Administration (NASA) DC-8, a unique quasi-Lagrangian case study was conducted for a freshly emitted plume emanating from the New York City source region in late July 2004. The development of this plume stemmed from the accumulation of boundary layer pollutants within a coastal residual layer, where weak synoptic conditions allowed for its advection into the marine troposphere and transport by a mean southwesterly flow. Upon entering the GOM, analysis showed that the plume layer vertical structure evolved into an internal boundary layer form, with signatures of steep vertical gradients in temperature, moisture and wind speed often resulting in periodic turbulence. This structure remained well-defined during the plume study, allowing for the detachment of the plume layer from the surface and minimal plume-sea surface exchange. In contrast, shear driven turbulence within the plume layer facilitated lateral mixing with other low-level plumes during its transit. This turbulence was periodic and further contributed to the high spatial variability in trace gas mixing ratios. Further influences of the turbulent mixing were observed in the impact of the plume inland as observed by the Atmospheric Investigation, Regional Modeling, Analysis and Prediction (AIRMAP) air quality network. This impact was seen as extreme elevations of surface ozone and CO levels, equaling the highest observed that summer. Full article
(This article belongs to the Special Issue Air Quality and Climate)
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Open AccessArticle
Brief Accuracy Assessment of Aerosol Climatologies for the Retrieval of Solar Surface Radiation
Atmosphere 2014, 5(4), 959-972; https://doi.org/10.3390/atmos5040959
Received: 8 August 2014 / Revised: 5 November 2014 / Accepted: 12 November 2014 / Published: 3 December 2014
Cited by 9 | Viewed by 2270 | PDF Full-text (333 KB) | HTML Full-text | XML Full-text
Abstract
Solar surface irradiance is an important variable in many different fields, e.g., climate monitoring and solar energy. Remote sensing data are nowadays well established and the only observational data source in many regions of the world. Aerosols significantly affect the clear sky radiation [...] Read more.
Solar surface irradiance is an important variable in many different fields, e.g., climate monitoring and solar energy. Remote sensing data are nowadays well established and the only observational data source in many regions of the world. Aerosols significantly affect the clear sky radiation and hence also the all sky radiation. In order to achieve the optimal accuracy for surface radiation, information of aerosols with low uncertainty is needed. In this study, the effect of four different aerosol climatologies on the solar surface radiation have been evaluated for the period 2006–2009 at nine BSRN stations. The use of the aerosol climatology from the European Center of Medium Weather Forecast (MACC) leads to the highest accuracy of solar radiation. The mean absolute bias is 6.8 Watt per square meter for global irradiance and 11.3 for direct irradiance. With the Max-Planck climatology (MAC-v1) 9.4 and 14.8 Watt per square meter and with GADS/OPAC (Global Aerosol Data Set/Optical Properties of Aerosols and Clouds) 10.0 and 14.6 Watt per square meter have been achieved, respectively. The improvement in the accuracy of solar radiation by using the MACC climatology is relatively large. Also remarkable is that the new MAC-v1 climatology and the older GADS/OPAC climatology performs on the same level with respect to the achieved accuracy in radiation. The effect of interannual variations of Aerosol Optical Depth (AOD) on the global irradiance is rather low for the investigated sites and period. Full article
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Open AccessArticle
Importance of Ship Emissions to Local Summertime Ozone Production in the Mediterranean Marine Boundary Layer: A Modeling Study
Atmosphere 2014, 5(4), 937-958; https://doi.org/10.3390/atmos5040937
Received: 22 September 2014 / Revised: 24 October 2014 / Accepted: 11 November 2014 / Published: 2 December 2014
Cited by 5 | Viewed by 2513 | PDF Full-text (10847 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Ozone concentrations in the Mediterranean area regularly exceed the maximum levels set by the EU Air Quality Directive, 2008/50/CE, a maximum 8-h mean of 120 μg·m-3, in the summer, with consequences for both human health and agriculture. There are a number [...] Read more.
Ozone concentrations in the Mediterranean area regularly exceed the maximum levels set by the EU Air Quality Directive, 2008/50/CE, a maximum 8-h mean of 120 μg·m-3, in the summer, with consequences for both human health and agriculture. There are a number of reasons for this: the particular geographical and meteorological conditions in the Mediterranean play a part, as do anthropogenic ozone precursor emissions from around the Mediterranean and continental Europe. Ozone concentrations measured on-board the Italian Research Council’s R. V. Urania during summer oceanographic campaigns between 2000 and 2010 regularly exceeded 60 ppb, even at night. The WRF/Chem (Weather Research and Forecasting (WRF) model coupled with Chemistry) model has been used to simulate tropospheric chemistry during the periods of the measurement campaigns, and then, the same simulations were repeated, excluding the contribution of maritime traffic in the Mediterranean to the anthropogenic emissions inventory. The differences in the model output suggest that, in large parts of the coastal zone of the Mediterranean, ship emissions contribute to 3 and 12 ppb to ground level daily average ozone concentrations. Near busy shipping lanes, up to 40 ppb differences in the hourly average ozone concentrations were found. It seems that ship emissions could be a significant factor in the exceedance of the EU directive on air quality in large areas of the Mediterranean Basin. Full article
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Open AccessArticle
Genetic Programming for the Downscaling of Extreme Rainfall Events on the East Coast of Peninsular Malaysia
Atmosphere 2014, 5(4), 914-936; https://doi.org/10.3390/atmos5040914
Received: 4 September 2014 / Revised: 18 November 2014 / Accepted: 20 November 2014 / Published: 27 November 2014
Cited by 37 | Viewed by 3912 | PDF Full-text (2190 KB) | HTML Full-text | XML Full-text
Abstract
A genetic programming (GP)-based logistic regression method is proposed in the present study for the downscaling of extreme rainfall indices on the east coast of Peninsular Malaysia, which is considered one of the zones in Malaysia most vulnerable to climate change. A National [...] Read more.
A genetic programming (GP)-based logistic regression method is proposed in the present study for the downscaling of extreme rainfall indices on the east coast of Peninsular Malaysia, which is considered one of the zones in Malaysia most vulnerable to climate change. A National Centre for Environmental Prediction reanalysis dataset at 42 grid points surrounding the study area was used to select the predictors. GP models were developed for the downscaling of three extreme rainfall indices: days with larger than or equal to the 90th percentile of rainfall during the north-east monsoon; consecutive wet days; and consecutive dry days in a year. Daily rainfall data for the time periods 1961–1990 and 1991–2000 were used for the calibration and validation of models, respectively. The results are compared with those obtained using the multilayer perceptron neural network (ANN) and linear regression-based statistical downscaling model (SDSM). It was found that models derived using GP can predict both annual and seasonal extreme rainfall indices more accurately compared to ANN and SDSM. Full article
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Open AccessArticle
The Synoptic Patterns Associated with Spring Widespread Dusty Days in Central and Eastern Saudi Arabia
Atmosphere 2014, 5(4), 889-913; https://doi.org/10.3390/atmos5040889
Received: 8 October 2014 / Revised: 26 October 2014 / Accepted: 13 November 2014 / Published: 27 November 2014
Cited by 6 | Viewed by 2442 | PDF Full-text (14168 KB) | HTML Full-text | XML Full-text
Abstract
Four synoptic regimes were identified as accompanying the widespread dust in central and eastern Saudi Arabia. The widespread cases of dust were classified based on the value and spread of the aerosol index data from the TOMS aerosol index (TOMS AI) satellite over [...] Read more.
Four synoptic regimes were identified as accompanying the widespread dust in central and eastern Saudi Arabia. The widespread cases of dust were classified based on the value and spread of the aerosol index data from the TOMS aerosol index (TOMS AI) satellite over the area of interest. The synoptic regimes of these dust cases were recognized using the Empirical Orthogonal Function (EOF) analysis of their mean sea level pressure (SLP), which was obtained from the National Centers for Environmental Prediction and the National Center for Atmospheric Research (NCEP/NCAR) Reanalysis Project dataset. The variations of the analyzed SLP of these four regimes appeared as meridional distributions for the first two regimes and zonal distributions for the second two regimes. A surface synoptic study of the first two regimes showed that the most significant features were either a strong low-pressure system over the eastern region or a strong high-pressure system over the western region. The synoptic features for the less significant regimes (the second two regimes) were characterized by the interaction between the northern high-pressure belt, which shifted northward because of the significant regime decrease, and the southern low-pressure belt. In addition, the upper synoptic study showed that the upper synoptic systems support the surface systems. Moreover, the study showed that the surface northerly wind over the eastern Arabian Peninsula is the dominant wind during strong dust activity, whereas the surface southerly wind is dominant during weak dust activity. Full article
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Open AccessArticle
Mapping Global Atmospheric CO2 Concentration at High Spatiotemporal Resolution
Atmosphere 2014, 5(4), 870-888; https://doi.org/10.3390/atmos5040870
Received: 26 August 2014 / Revised: 17 October 2014 / Accepted: 21 October 2014 / Published: 26 November 2014
Cited by 8 | Viewed by 2949 | PDF Full-text (3006 KB) | HTML Full-text | XML Full-text
Abstract
Satellite measurements of the spatiotemporal distributions of atmospheric CO2 concentrations are a key component for better understanding global carbon cycle characteristics. Currently, several satellite instruments such as the Greenhouse gases Observing SATellite (GOSAT), SCanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY), and [...] Read more.
Satellite measurements of the spatiotemporal distributions of atmospheric CO2 concentrations are a key component for better understanding global carbon cycle characteristics. Currently, several satellite instruments such as the Greenhouse gases Observing SATellite (GOSAT), SCanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY), and Orbiting Carbon Observatory-2 can be used to measure CO2 column-averaged dry air mole fractions. However, because of cloud effects, a single satellite can only provide limited CO2 data, resulting in significant uncertainty in the characterization of the spatiotemporal distribution of atmospheric CO2 concentrations. In this study, a new physical data fusion technique is proposed to combine the GOSAT and SCIAMACHY measurements. On the basis of the fused dataset, a gap-filling method developed by modeling the spatial correlation structures of CO2 concentrations is presented with the goal of generating global land CO2 distribution maps with high spatiotemporal resolution. The results show that, compared with the single satellite dataset (i.e., GOSAT or SCIAMACHY), the global spatial coverage of the fused dataset is significantly increased (reaching up to approximately 20%), and the temporal resolution is improved by two or three times. The spatial coverage and monthly variations of the generated global CO2 distributions are also investigated. Comparisons with ground-based Total Carbon Column Observing Network (TCCON) measurements reveal that CO2 distributions based on the gap-filling method show good agreement with TCCON records despite some biases. These results demonstrate that the fused dataset as well as the gap-filling method are rather effective to generate global CO2 distribution with high accuracies and high spatiotemporal resolution. Full article
(This article belongs to the Special Issue Air Quality and Climate)
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Open AccessArticle
The Copula Function-Based Probability Characteristics Analysis on Seasonal Drought & Flood Combination Events on the North China Plain
Atmosphere 2014, 5(4), 847-869; https://doi.org/10.3390/atmos5040847
Received: 11 September 2014 / Revised: 30 October 2014 / Accepted: 4 November 2014 / Published: 18 November 2014
Cited by 8 | Viewed by 2591 | PDF Full-text (6252 KB) | HTML Full-text | XML Full-text
Abstract
Drought & flood events, especially the drought & flood combination events (DFCEs) on the North China Plain (NCP), known as an important grain production region in China, constitute a serious threat to China’s food security. Studies on DFCEs in this region are of [...] Read more.
Drought & flood events, especially the drought & flood combination events (DFCEs) on the North China Plain (NCP), known as an important grain production region in China, constitute a serious threat to China’s food security. Studies on DFCEs in this region are of great significance for the rational allocation of water resources and the formulation of integrated response strategy for droughts and floods. In this study, L-moments theory and bivariate copula method were used to evaluate the probability characteristics of seasonal DFCEs (continuous drought, continuous flood, and alternation between drought and flood) on the NCP, based on the daily precipitation data (1960–2012) at 19 meteorological stations. Results indicate the following: (1) On the NCP, the precipitation in summer accounts for 56.45%–72.02% of mean annual precipitation, and the precipitation in autumn and spring come second. The winter precipitation is the smallest (less than 4%); (2) The best-fit distribution for precipitation anomaly percentages in spring, summer and autumn are Generalized Normal (GNO), Generalized Logistic (GLO) and Pearson III (P-III) in sub-region I, respectively. While in sub-region II, they are respectively the P-III, P-III and Generalized Extreme-Value (GEV); (3) Compared with the Gumbel copula and Clayton copula, Frank copula is more suitable for spring-summer and summer-autumn precipitation anomaly percentage sequences on the NCP; (4) On the time scale, continuous drought respectively dominate in spring-summer DFCEs and in summer-autumn DFCEs on the NCP. Summer-autumn DFCEs prevail in sub-region I with the average probability value 0.34, while spring-summer DFCEs dominate in sub-region II, of which average probability value is 0.42; (5) On the spatial scale, most areas where the probability of continuous drought in spring-summer and spring drought & summer flood is relatively high are located in the northwest, northeast, and coastal parts of sub-region II; all the events with high probability of continuous drought in summer-autumn and summer flood & autumn drought occurred at the central part in the northwest of sub-region II. Full article
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Open AccessArticle
Analysis on Effectiveness of SO2 Emission Reduction in Shanxi, China by Satellite Remote Sensing
Atmosphere 2014, 5(4), 830-846; https://doi.org/10.3390/atmos5040830
Received: 5 August 2014 / Revised: 18 September 2014 / Accepted: 23 October 2014 / Published: 10 November 2014
Cited by 5 | Viewed by 2662 | PDF Full-text (12239 KB) | HTML Full-text | XML Full-text
Abstract
The SO2 emissions from coal-fired power plants in China have been regulated since 2005 by a mandatory installation of flue gas desulfurization (FGD) devices. In order to verify the effectiveness of FGD systems applied in power plants, Shanxi (a province well-known for [...] Read more.
The SO2 emissions from coal-fired power plants in China have been regulated since 2005 by a mandatory installation of flue gas desulfurization (FGD) devices. In order to verify the effectiveness of FGD systems applied in power plants, Shanxi (a province well-known for the largest coal reserves in China) was selected, and the characteristic and evolution of SO2 densities over 22 regions with large coal-fired power plants during 2005–2012 were investigated by using the satellite remote sensing data from the Ozone Monitoring Instrument (OMI). A unit-based inventory was also employed to study the trend of SO2 emissions from coal-fired power plants in Shanxi. The results show that the operation of FGD systems was successful in reducing SO2 emissions from power plants during 2005–2010: the mean SO2 densities satellite-observed over those regions with power plants operated before 2005 showed a notable decrease of approximate 0.4 DU; the mean SO2 densities over other regions with power plants newly built behind 2006 did not show a statistical increasing trend overall; the mean SO2 density over the whole Shanxi also showed a moderate decline from 2008 to 2010. However, the polluted conditions over Shanxi during 2011–2012 rebounded and the declining trend in mean SO2 density over the whole Shanxi disappeared again. In comparison of unit-based emission inventory, the emissions calculated show a similar trend with SO2 densities satellite-observed during 2005–2010 and still maintain at a lower volume during 2011–2012. By investigating the developments of other emission sources in Shanxi during 2005–2012, it is considered that the rapid expansion of industries with high coal-consumption has played an important role for the increment rise of SO2 emissions. Lack of an independent air quality monitoring network and the purposeful reduced operation rate of FGD systems occurring in some coal-fired power plants have reduced the effectiveness of SO2 emission reduction policy applied in Shanxi. In view that the SO2 pollution in Shanxi has not been well ameliorated, more reasonable and mandatory policies, such as a national-wide independent monitoring network and installation of FGD systems in other large emission sources, should be pushed out in the near future. Full article
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Open AccessArticle
Analysis of Criteria Air Pollutant Trends in Three Mexican Metropolitan Areas
Atmosphere 2014, 5(4), 806-829; https://doi.org/10.3390/atmos5040806
Received: 11 August 2014 / Revised: 10 October 2014 / Accepted: 21 October 2014 / Published: 5 November 2014
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Abstract
Data from the annual, seasonal, and hourly behavior of the criteria air pollutants CO, NO2, SO2, O3, and PM10 in three Mexican metropolitan areas (the Mexico City Metropolitan Area (MCMA), Guadalajara Metropolitan Area (GMA), and Monterrey [...] Read more.
Data from the annual, seasonal, and hourly behavior of the criteria air pollutants CO, NO2, SO2, O3, and PM10 in three Mexican metropolitan areas (the Mexico City Metropolitan Area (MCMA), Guadalajara Metropolitan Area (GMA), and Monterrey Metropolitan Area (MMA)) over the period 2000–2011 were analyzed; and compliance with Mexican air quality standards was evaluated, highlighting causes of specific episodes of high and low concentrations. Data analyzed were collected from automatic air-monitoring networks located in the MCMA (32 stations), GMA (8 stations), and MMA (5 stations). In the MCMA and MMA, correlations between wind direction and concentrations of SO2 suggest that there was a considerable contribution of trans-boundary transport from outside of these areas. Analysis of annual trends revealed large reductions of CO in the MCMA, and SO2 in the three metropolitan areas. However, the annual mean concentration of O3 increased by 47% and 42% in the GMA and MMA, respectively, from 2000 to 2011, but decreased by 13% in the MCMA from 2005 to 2010. The annual mean concentration of PM10 in the MMA was about 58% and 76% higher than that in the MCMA and GMA, respectively, from 2001 to 2010. Full article
(This article belongs to the Special Issue Air Quality and Climate)
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Open AccessArticle
Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment
Atmosphere 2014, 5(4), 788-805; https://doi.org/10.3390/atmos5040788
Received: 23 September 2014 / Accepted: 8 October 2014 / Published: 3 November 2014
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Abstract
We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM), and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the [...] Read more.
We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM), and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro) and NFIS-WPM (Ave) are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy. Full article
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Open AccessArticle
Characteristics and Sources of Metals in TSP and PM2.5 in an Urban Forest Park at Guangzhou
Atmosphere 2014, 5(4), 775-787; https://doi.org/10.3390/atmos5040775
Received: 3 September 2014 / Revised: 16 October 2014 / Accepted: 21 October 2014 / Published: 28 October 2014
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Abstract
Urban forest parks play important roles in improving environments, protecting biodiversity and even public welfare. Aerosols, including total suspended particles (TSP) and particulate matter with aerodynamic diameter less than 2.5 µm (PM2.5), were simultaneously collected in an urban forest park [...] Read more.
Urban forest parks play important roles in improving environments, protecting biodiversity and even public welfare. Aerosols, including total suspended particles (TSP) and particulate matter with aerodynamic diameter less than 2.5 µm (PM2.5), were simultaneously collected in an urban forest park (Dafushan) at Guangzhou, southern China, from January 2012 to December 2013. The concentrations of 12 metals (Al, Cd, Co, Cr, Cu, Hg, Mn, Mo, Ni, Pb, Se, and Zn) in both TSP and PM2.5 were quantified using an inductively coupled plasma-mass spectrometer. The origins and possible sources of the studied metals in the PM2.5 and TSP were evaluated using the crustal enrichment factors and the principal component analysis, respectively. The results showed that Dafushan urban forest park was polluted by PM2.5 rather than by TSP. The PM2.5 and TSP in the forest park exhibited seasonal patterns with significantly higher contents in the dry season compared with the rainy season. The metals Al, Zn, Pb were the most abundant, while Hg was the lowest metals in the aerosols. The ratios of PM2.5/TSP ratio indicated that the metals were predominant in the finer particles (PM2.5). The crustal enrichment factors indicated that Cd, Cu, Mo, Pb, Se and Zn in the aerosols originated from anthropogenic sources, while Al and Mn were mainly of crustal origin. The principal component analysis implied that industrial activities, traffic-related emissions, and soil dust were the main possible sources of the metals in both PM2.5 and TSP in Dafushan forest park. Full article
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Open AccessArticle
Local Climate Classification and Dublin’s Urban Heat Island
Atmosphere 2014, 5(4), 755-774; https://doi.org/10.3390/atmos5040755
Received: 20 May 2014 / Revised: 10 September 2014 / Accepted: 19 September 2014 / Published: 21 October 2014
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Abstract
A recent re-evaluation of urban heat island (UHI) studies has suggested that the urban effect may be expressed more meaningfully as a difference between Local Climate Zones (LCZ), defined as areas with characteristic dimensions of between one and several kilometers that have distinct [...] Read more.
A recent re-evaluation of urban heat island (UHI) studies has suggested that the urban effect may be expressed more meaningfully as a difference between Local Climate Zones (LCZ), defined as areas with characteristic dimensions of between one and several kilometers that have distinct effects on climate at both micro-and local-scales (city streets to neighborhoods), rather than adopting the traditional method of comparing urban and rural air temperatures. This paper reports on a UHI study in Dublin (Ireland) which maps the urban area into LCZ and uses these as a basis for carrying out a UHI study. The LCZ map for Dublin is derived using a widely available land use/cover map as a basis. A small network of in-situ stations is deployed into different LCZ across Dublin and additional mobile temperature traverses carried out to examine the thermal characteristics of LCZ following mixed weather during a 1 week period in August 2010. The results show LCZ with high impervious/building coverage were on average >4 °C warmer at night than LCZ with high pervious/vegetated coverage during conditions conducive to strong UHI development. The distinction in mean LCZ nocturnal temperature allows for the generation of a heat map across the entire urban area. Full article
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Open AccessArticle
Spatial and Decadal Variations in Potential Evapotranspiration of China Based on Reanalysis Datasets during 1982–2010
Atmosphere 2014, 5(4), 737-754; https://doi.org/10.3390/atmos5040737
Received: 20 May 2014 / Revised: 17 September 2014 / Accepted: 19 September 2014 / Published: 17 October 2014
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Abstract
Potential evapotranspiration (PET) is an important indicator of atmospheric evaporation demand and has been widely used to characterize hydrological change. However, sparse observations of pan evaporation (EP) prohibit the accurate characterization of the spatial and temporal patterns of PET over large spatial scales. [...] Read more.
Potential evapotranspiration (PET) is an important indicator of atmospheric evaporation demand and has been widely used to characterize hydrological change. However, sparse observations of pan evaporation (EP) prohibit the accurate characterization of the spatial and temporal patterns of PET over large spatial scales. In this study, we have estimated PET of China using the Penman-Monteith (PM) method driven by gridded reanalysis datasets to analyze the spatial and decadal variations of PET in China during 1982–2010. The results show that the estimated PET has decreased on average by 3.3 mm per year (p < 0.05) over China during 1982–1993, while PET began to increase since 1994 by 3.4 mm per year (p < 0.05). The spatial pattern of the linear trend in PET of China illustrates that a widely significant increasing trend in PET appears during 1982–2010 in Northwest China, Central China, Northeast China and South China while there are no obvious variations of PET in other regions. Our findings illustrate that incident solar radiation (Rs) is the largest contributor to the variation of PET in China, followed by vapor pressure deficit (VPD), air temperature (Tair) and wind speed (WS). However, WS is the primary factor controlling inter-annual variation of PET over Northwest China. Full article
Open AccessArticle
Use of a Simple GIS-Based Model in Mapping the Atmospheric Concentration of γ-HCH in Europe
Atmosphere 2014, 5(4), 720-736; https://doi.org/10.3390/atmos5040720
Received: 20 March 2014 / Revised: 22 July 2014 / Accepted: 19 August 2014 / Published: 15 October 2014
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Abstract
The state-of-the-art of atmospheric contaminant transport modeling provides accurate estimation of chemical concentrations. However, existing complex models, sophisticated in terms of process description and potentially highly accurate, may entail expensive setups and require very detailed input data. In contexts where detailed predictions are [...] Read more.
The state-of-the-art of atmospheric contaminant transport modeling provides accurate estimation of chemical concentrations. However, existing complex models, sophisticated in terms of process description and potentially highly accurate, may entail expensive setups and require very detailed input data. In contexts where detailed predictions are not needed (e.g., for regulatory risk assessment or life cycle impact assessment of chemicals), simple models allowing quick evaluation of contaminants may be preferable. The goal of this paper is to illustrate and critically discuss the use of a simple equation proposed by Pistocchi and Galmarini (2010), which can be implemented through basic GIS functions, to predict atmospheric concentrations of lindane (γ-HCH) in Europe from both local and remote sources. Concentrations were computed for 1995 and 2005 assuming different modes of use of lindane and consequently different spatial patterns of emissions. Results were compared with those from the well-established MSCE-POP model (2005) developed within EMEP (European Monitoring and Evaluation Programme), and with available monitoring data, showing acceptable correspondence in terms of the orders of magnitude and spatial distribution of concentrations, especially when the background effect of emissions from extracontinental sources, estimated using the same equation, is added to European emissions. Full article
Open AccessArticle
Aerosol Optical Properties of a Haze Episode in Wuhan Based on Ground-Based and Satellite Observations
Atmosphere 2014, 5(4), 699-719; https://doi.org/10.3390/atmos5040699
Received: 7 May 2014 / Revised: 9 September 2014 / Accepted: 24 September 2014 / Published: 15 October 2014
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Abstract
A severe haze episode that occurred in Wuhan, central China, from 6–14 June 2012 was investigated using ground-based and satellite-derived observations, from which the optical properties and vertical distribution of the aerosols were obtained. The mass concentrations of PM2.5 and black carbon [...] Read more.
A severe haze episode that occurred in Wuhan, central China, from 6–14 June 2012 was investigated using ground-based and satellite-derived observations, from which the optical properties and vertical distribution of the aerosols were obtained. The mass concentrations of PM2.5 and black carbon (BC) were 9.9 (332.79 versus 33.66 μg∙m3) and 3.2 times (9.67 versus 2.99 μg∙m3) greater, respectively, on haze days than during normal weather. The large aerosol loading contributed to the high values of the scattering (2.32 km−1) and absorption coefficients (0.086 km−1). Particle size became larger, consistent with the reduced scattering Ångström exponent. The high asymmetry parameter (0.65) and single scattering albedo (SSA) (0.97) observed in the haze, which coincided with the relatively low backscatter ratio (0.11) and up-scatter fraction (0.23), were related to the increased particle size, and could have had a heating effect on the atmosphere. Aerosols accumulated primarily below 3 km and according to CALIPSO, were regular in their shapes. At the surface, the aerosol extinction coefficient detected by satellite remained at ~1 km−1, very close to the ground-based observations. Aerosol optical properties measured at this downtown site could help further the understanding of the effects of aerosols on the air quality, city environment, and radiation balance. Full article
(This article belongs to the Special Issue Air Quality and Climate)
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