Atmósfera (Journal)
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Regional growth curves and extreme precipitation events estimation in the steppe area of northwestern Algeria
Get PDFA regional statistical analysis has been established for an improved estimate of extreme frequency precipitation in the steppe area of northwestern Algeria. This analysis made it possible to determine three homogeneous regions by using methods based on statistical procedures, such as the analysis of the ascendant hierarchical classification and the L-moments method. The regions thus defined accurately reflect the climatological differences and specific characters influencing precipitation patterns in the study area. The generalized extreme value (GEV) distribution has been identified as the most appropriate distribution for modeling annual maximum daily rainfall quantiles according to the L-moments ratio plot and fit-quality tests. Rainfall indices combined with the regional growth curves can evaluate in a reasonable way the maximum rainfall quantiles at the stations by using the mean maximum precipitations of the observation series. The regional approach has considerably reduced the differences caused by the disparity of the values taken by the shape parameter of the GEV distribution as a function of the observation sites, and the estimation of high quantiles becomes more spatially consistent in a region. Different forms of growth curves are characteristic for the three regions. The error reflected by the bias and root mean square error (RMSE) are below 16 and 25%, respectively, for a 100-year return period. The study provides an assessment of the maximum daily rainfalls that can be useful in the study of floods and the design of hydrotechnical works
Verification of traffic emission factors using measurements in a short tunnel in the Czech Republic
Get PDFRoad transportation activities are major contributors of nitrogen oxides emissions to the air. The impact on the growth of NOx emission levels is found to be strongly correlated with the traffic intensities on highways. Various types of emission models performing emission assessment of traffic-related pollutants have been developed, but few of them were developed by using real-world measurements of NOx concentrations in ambient air. The most convenient sites to perform measurements in real-world conditions are road tunnels. This paper presents a comparison of HBEFA model NOx emission calculations and NOx emission measured in a short tunnel in the Czech Republic. Simultaneously, measured time-resolved NOx concentration and traffic activity counting were performed in the Zeleny most tunnel in the Czech Republic. The experimental work yielded reliable results of the mutual correlation of NOx level and traffic intensity in the tunnel section with statistical evidence. Emission factors from HBEFA emission model for road transport were applied and compared with the results from several measurement campaigns in the Czech Republic. It was found that calculated NOx emissions differed from measured NOx emissions due to the overestimation of light vehicles emissions and underestimation of high-duty vehicles emissions
Black carbon radiative forcing in south Mexico City, 2015
Get PDFBlack carbon (BC) is a strong radiative forcer. Because of its multiple effects on climate change, BC has been located as the second important impact factor of climate change only after carbon dioxide. Sources of BC include mainly diesel vehicles and biomass burning. Mexico’s pledges before the Paris Agreement are, between others, the reduction of BC emissions to up to 51% by 2030 compared with those in 2000. In order to know the exact contribution of BC to the emission inventory of Mexico it is necessary to estimate several BC properties, such as its radiative forcing and its effects on the radiative heating of the atmosphere, among others. In this work, a technique based on the available remote-sensing and ground-based data along with the Optical Properties of Aerosols and Clouds (OPAC) and the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) algorithms were used to estimate black carbon radiative forcing in the south of Mexico City during 2015. Land-based measurements were taken from a recently created monitoring network, the Aerosol Robotic Network (AERONET), and satellite measurements were obtained from the Moderate Resolution Imaging Spectroradiometer) (MODIS). Black carbon monthly concentrations along 2015 were between 1.9 and 4.1 μg/m3. Results show that monthly average radiative forcing on the top of the atmosphere over south Mexico City during 2015 was +30.2 ± 6.2 W/m2. November, December and January presented the highest radiative forcing values (+34.9, +46.9, +34.0, respectively). In addition, estimates of atmospheric heating show an average annual value of 0.85 ± 0.22 W/m2. Values of Ångström > 1, as obtained in this work, indicate that aerosols are of the urban type and freshly emitted. Also, low single scattering albedo values in increasing wavelengths show that aerosols are mainly from urban-industrial aerosols
Water management alternatives to reservoirs with a high rate of evaporation in Nuevo León, Mexico
Get PDFA research was conducted for evaluating an alternative management under evaporation stress of the reservoir El Cuchillo, which supplies water to the Metropolitan Area of Monterrey (AMM, Spanish acronym) located in the state of Nuevo León, Mexico. The surface sources of water supplies for the AMM come from three reservoirs: La Boca, El Cuchillo and Cerro Prieto, which are integrated in a single system and exchange water with two reservoirs, Marte R. Gómez and Las Blancas. Due to high temperatures during the whole year, especially in the summer, as well as the big surface area of the pool, El Cuchillo is a big source of water loss by evaporation. This research conducted an analysis to achieve alternative scenarios for water management in reservoirs facing this problem, by applying the model HEC-ResSim. This model, created by the US Army Corps of Engineers, has a multi reservoir simulator and can simulate water resource systems from many sources. The present study used monthly observed data from 1994 to 2014 of reservoir volume, inflow and diversion; in addition, hydraulic data from the reservoirs were used to develop the numerical model. The results show that it is possible to increase the reservoir diversion and obtain 50 % more water for the scenario 1 and 70 % more for the scenario 2 during a period of 20 years from 1994 to 2014, if these cycles of evaporation are taking in consideration
Ammonia emissions and dry deposition in the vicinity of dairy farms
Get PDFWe conducted the first research in the Czech Republic to measure ventilation and ammonia (NH3) emission rates in a naturally ventilated animal building (dairy farm) during a five-day measurement period in June, combined with a three-month (May-July) monitoring of NH3 concentration and dry deposition at 12 locations along horizontal gradients from the dairy farm up to the distance of 400 m. Passive diffusion-tube samplers were used to measure monthly NH3 concentrations. Moisture (H2O) balance was used to determine ventilation rates of the dairy farm. Continuous measurements of gas concentrations (NH3), temperature and relative humidity inside and outside the building were performed. The air exchange rate was 4.8 h–1 and the emission rate was 43.2 NH3 g cow–1 d–1 for building. The emission rate was 126% of what was obtained using emission factors from the Czech national inventory (34.2 g cow–1 d–1). NH3 concentrations and dry deposition fluxes decreased exponentially with distance from the dairy farm. Between May and July, mean predicted dry deposition fluxes ranged from 0.28 to 0.03 µg NH3 m–2 s–1 at a distance of 50 and 400 m from the source, respectively. Dry NH3 deposition over the nearest 400 m from the source accounted for 11.5% of daily emissions. The results confirm the short-range dispersion of NH3 emitted from a point source found in other studies, but it may not be the same in other situations, since dispersion of NH3 is dependent on the surrounding land-cover and on the number of animals in a barn
Analysis of a new spatial interpolation weighting method to estimate missing data applied to rainfall records
Get PDFIn the present work, two new generalized weighted methods of imputation of missing data are developed and tested using a daily rainfall series. The proposed methodology allows to fully rebuild the time series while preserving its statistical properties. Rainfall records in the state of Tabasco, Mexico, during the period 1980-2012 were used to test and evaluate the proposed methodology. The imputation of missing data in a given weather station is performed by using daily data from neighboring stations with a similar rainfall behavior. The choice of optimal parameters for the proposed formulae is based on minimizing the mean absolute error (MAE) via an evolutionary strategy (CMA-ES). The K-means method was used with the Euclidean distance in order to select the adequate neighboring weather stations. Five different methods were applied to estimate the optimal number of clusters: the elbow method, gap statistics, TraceW, Hartigan and Krzanowski-Lai indices. In addition, the structural stability of the chosen clusters was evaluated in order to demonstrate that these represent the correct data structure and are not the result of an artificial internal procedure of the grouping algorithm. Results from two different statistical tests, Friedman and Nemenyi post hoc, showed that our two new methods produce significantly and statistically better estimation when compared to existing methods in the literature.
Relationship between dust deposition rate and soil characteristics in an arid region of Iran
Get PDFDust formation is one of the most seriously damaging environmental issues in arid and semiarid areas. In this study, the decision tree-based Chi-square Automatic Interaction Detector (CHAID) algorithm was used to determine the non-linear relationships of soil physical and chemical properties with seasonal and annual dust deposition rate (DDR) in Gavkhouni swamp sub-basin, Central Iran. The results were compared with those obtained by the multiple linear regression (MLR) method. A set of 124 atmospheric dust samples was seasonally taken from 31 sites. A set of 96 surface soil samples was also collected. DDR and dust particle size distribution, as well as the physical and chemical properties of soil samples were investigated. The results showed that the highest and lowest DDR belonged to summer and autumn, respectively. Based on the CHAID algorithm results, the most important soil properties affecting DDR in autumn, winter, spring and summer, as well as annual DDR were soil organic matter content (importance coefficient [IC] = 0.34), gypsum (IC = 0.42), sand (IC = 0.39), silt (IC = 0.31), and sand (IC = 0.23), respectively. Based on the CHAID algorithm results, it appears that particle size distribution of surface soil, especially sand content is a determinant factor affecting seasonal and annual DDR in the study area. In this study, the MLR model had unacceptable accuracy as compared with the non-linear CHAID algorithm method. Therefore, it seems that in areas with high ecological complexity and complex nonlinear relationships among input and output data, the nonlinear methods such as CHAID are superior to linear methods such as MLR
Climatology of surface baroclinic zones in the coast of Brazil
Get PDFThis study presents the main differences between classical cold fronts, subtropical fronts and baroclinic troughs, as well as a climatology of these systems along the coast of Brazil. Regarding the seasonality of these systems, classical cold fronts are more frequent in winter followed by spring, subtropical fronts in spring, and baroclinic troughs in spring and summer. In southeastern Brazil, these three kinds of systems are responsible for about 40% (60%) of the total precipitation during the rainy (dry) season
PM2.5 concentrations in the greenbelt near the Lin’an toll station of the Hang Rui expressway and related influencing factors
Get PDFExpressways in China are developing rapidly, as is traffic pollution, which is one of the major sources of urban pollution. In this study, we chose the greenbelt in the idle zone near the Lin’an toll station along the Hang Rui expressway as our sampling area. Five points in the sampling area along Qianjin road were marked vertically at distances of 0, 15, 30, 45 and 60 m to monitor concentrations of PM2.5 and learn the varying patterns of these concentrations and influencing factors. The results showed that in spring (March, April and May), the average PM2.5 concentrations in the greenbelt were 32.56 ± 22.51, 77.71 ± 32.11 and 64.15 ± 29.00 μg m–3, respectively. The ranking of concentrations at different monitoring points in the same period was 0 > 15 > 60 > 30 > 45 m. The average concentrations in winter (November and December 2017, and February 2018) were 33.56 ± 9.34, 60.78 ± 17.67 and 124.71 ± 43.19 μg m–3, respectively. However, the ranking of concentrations at different monitoring points in the same period revealed some differences. Except at 0 m, the concentrations of PM2.5 in the other four positions were higher in winter than in spring. The reduction rate at 45 m reached its maximum in both spring and winter. PM2.5 concentrations were significantly correlated with meteorological factors, the structure of the plant community and traffic flow. PM2.5 concentrations were negatively correlated with temperature, positively correlated with relative humidity and was not significantly correlated with wind speed. The correlations of PM2.5 concentrations with the canopy density and degree of porosity differed greatly due to different seasons, and concentrations were significantly correlated with the amount of traffic flow, especially when there were large trucks.
Spatial analysis of wet spell probability over India (1971-2005) towards agricultural planning
Get PDFThe spatial analysis of the wet spell probability over the Indian region has been carried out using daily gridded (0.5º × 0.5º) rainfall data of 1971-2005 during the summer monsoon period, i.e. June-September. A threshold was applied to the weekly cumulative rainfall to convert the rainfall data into wet spell information. A Markov chain model was employed to estimate the initial and conditional probabilities of the wet spell for each grid and the spatio-temporal distribution of the wet spells probabilities was analyzed. The probability maps were able to capture the summer monsoon scenario over the Indian region, representing the onset, progression and withdrawal of monsoon rainfall. Higher wet spell probability was observed over the west coast and northeastern parts of India, i.e., the initial probability was maximum over these regions. However, lower probability values were observed in West Rajasthan, Gujarat and southern India. A threshold of 80% of the maximum initial probability was used to standardize the spatially-variable probability information, and a week with more than the threshold values was considered as a probable wet week. The duration of the longest probable wet spell was highest along the west coast and in northeastern India, whereas it was lowest in western and southern India. The start and duration of the longest spell of the probable wet week can be used for rainfed-agricultural planning, i.e., the start of sowing/planting, selection of crops and varieties based on their length of growing period, optimum harvesting period to avoid wet spell, etc.