Statistical models for surface-atmosphere energy balance components (net radiation, sensible heat, and soil-stored heat) as functions of global radiation are proposed. This study was carried out during three seasons (winter, spring, and summer) in Mexicali, an arid city of northwest México, by means of representative measurement campaigns of three types of land use in the study zone: urban, rural (desert), and farmed suburban. The hysteresis pattern in the proposed models between the global radiation and net radiation was found during summer at suburban and urban sites, which seems to be originated by atmospheric moisture introduced by artificial irrigation and the thermal inertia of land cover. The coefficient of determination (R2) and the mean square error are used as indicators of the quality of models.

  Atmósfera 29(1), 35-60 (2016)This work focuses on evaluating the climate change projected by the end of the 21st century under the SRES A2 emission scenario over southern South America using the regional model MM5. The model projects: (i) an increase of precipitation over central Argentina, Uruguay and southern Brazil during summer and fall; (ii) a decrease in precipitation over most of the study domain during winter and spring; (iii) an important decrease in precipitation over central and southern Chile, through the year. In general, the projected temperature increase depends on the season and the examined area; particularly, it is highest over tropical and subtropical latitudes in spring and over high latitudes in summer. The MM5 model projects: (i) an increase of the interannual precipitation variability of precipitation over central Argentina and Uruguay regardless the season; (ii) a slight decrease in interannual temperature variability over large extents of Argentina for summer and winter; (iii) a slight increase in interannual temperature variability at transition seasons; with highest values over central Chile in autumn and over north central Argentina in spring. From the reliability assessment of regional climate projections, it can be concluded that signal-to-noise ratio is high for temperature and low for precipitation. Therefore, the MM5 model is a useful tool in the generation of regional climate change scenarios of high resolution over southern South America, particularly for temperature, and is a starting point to perform studies related to impacts of climate change.

Spatial and temporal variations in aerosol particulate matter (PM) were investigated for distribution over the four seasons of chemical constituents and particle size fractions in Faisalabad, Pakistan from June 2012 to April 2013. At nine sampling sites, four PM mass size fractions (total suspended particulates [TSP], PM10, PM4 and PM2.5) were monitored; simultaneously, TSP mass samples were collected on glass fiber filters using a high volume air sampler. TSP samples (144) were subjected to quantitative chemical analyses for determining trace elements (Pb, Cd, Ni, Zn, Cu, Fe) using atomic absorption spectroscopy, and water-soluble cations (Ca2+, Mg2+, Na+, K+, NH4+) and anions (Cl–, SO42– and NO3–) by ion chromatography. The highest PM mass concentrations were observed at industrial sites, while they were somewhat lower in major road intersections and lowest in the remote background site. It was also observed that PM mass concentrations were about two to 20 times higher than the standard limits of the World Health Organization and the US Environmental Protection Agency. Coarse particles (TSP, PM10 and PM4) were found to be highest during the summer, while relatively fine particles (PM2.5) were higher during the winter period. Concentrations of all size fractions were lowest during the monsoon sampling period at all sites. Concentrations of different elements and water-soluble ions also followed the similar temporal pattern as PM mass concentrations. The crustal elements Ca, Fe, Mg and Na were the largest contributors to TSP mass while elements of anthropogenic origin (Pb, Cd, Ni, Cu and Zn) had relatively lower concentrations and also showed a high spatial variation. Among the anions, sulfate (SO42–) was the predominant species contributing to 50-60% of the total anion concentration. It was found that rainfall, wind speed and relative humidity were the most important meteorological factors affecting PM concentrations. The evaluation of data presented in this paper will serve as a basis for future regional modeling and source apportionment. 

We analyze trends of high values of tropospheric ozone over Mexico City based on data corresponding to the years 2001-2014. The data consists of monthly maxima ozone concentrations based on 29 monitoring stations. Due to the large presence of missing data, we consider the monthly maxima based on five well identified geographical zones. We assess time trends based on a statistical model that assumes that these observations follow an extreme value distribution, where the location parameter changes in time accordingly to a regression model. In addition, we use Bayesian methods to estimate simultaneously a zonal and an overall time-trend parameter along with the shape and scale parameters of the Generalized Extreme Value distribution. We compare our results to a model that is based on a normal distribution. Our analyses show some evidence of decaying ozone levels for the monthly maxima during the period of study.

A neural network (NN) model is developed to predict the seasonal number of tropical cyclones (TCs) formed over the north Indian Ocean during the post-monsoon season (October, November, December). The frequency of TCs and the large scale climate variables derived from the NCEP/NCAR reanalysis dataset of resolution 2.5º • 2.5o have been analyzed for the period 1971-2013. Data for the years 1971-2002 have been used for the development of the model, which is tested with independent sample data for the years 2003-2013. Applying correlation analysis, five large-scale climate variables, namely geopotential height at 500 hPa, relative humidity at 500 hPa, sea level pressure, and zonal wind at 700 hPa and 200 hPa for the antecedent month September are selected as predictors. Based on some performance parameter statistics, the performance of the NN model is evaluated and the results are compared with the multiple linear regression (MLR) model. From the results it is inferred that the predicted tropical cyclone count by both models is very close to the actual counts for both periods. However, the NN model is found to be superior to the MLR model. This tropical cyclone prediction technique may be useful for operational prediction purposes.

The purpose of this paper is to represent the exact solutions of the barotropic vorticity equations (BVE) on the rotating unit sphere S2 as a manifold, which are zonal flows, Rossby-Haurwitz waves and generalized solutions named modons. Modern methods of the function theory are connected to the sphere defined as a compact differentiable manifold. When the differentiable manifold S2 is well understood, the abstract notion of local chart, change of chart, and atlases becomes evident. One of the aims of this paper is to better understand the solution of the barotropic vorticity equation on the manifold S2 and its usefulness to identify the properties of the solutions on the Riemannian manifold (S2, g). Therefore, a more general type of space will be available, which can also contain substantial geometric and analytic information about solutions for the barotropic vorticity equation.

Dust emission is a main source of aerosol in the atmosphere and is highly sensitive to wind velocity. Surface feature characteristics, soil properties and meteorological parameters also influence dust emission. Thus far, no study has referred to dust flux over the Indian subcontinent; therefore, we estimated dust flux using empirical equations and land cover data for seven locations in the northwest and the Indo-Gangetic Plains (IGP) having different soil types. Our study indicates differences in dust flux among locations. In the northwest, dust emission was initiated at a friction velocity of 0.23 to 0.27 m s–1 and dust flux was lesser than the IGP. In the IGP, dust emission was initiated at a friction velocity ranging from 0.22 to 0. 35 m s–1. Dust flux ranged from 0.073 to 0.084 kg m–1 s–1 at a given friction velocity (0.6 m s–1). It was observed that at low friction velocity, dust flux was low at locations with high clay content (> 20%) and sandy soils, compared to sandy loam and silt loam soil types. A reverse trend was observed at a higher friction velocity. Our study clearly indicates the effect of soil texture in dust emission.

Mesoscale atmospheric circulations play an important role in the transport of air pollution and local air quality issues. The planetary boundary layer (PBL), the thermo-dynamical structure and the flow field play an important role in air pollution dispersion. Hence, the PBL parameters over Nagpur, India are simulated using the ARW v. 3.6.1 mesoscale model. High-resolution simulations are conducted with triple nested domains having a horizontal resolution of 27, 9 and 3 km, as well as 27 vertical levels by using the 1 . 1º NCEP Final Analysis meteorological fields for initial and boundary conditions. Eight fair-weather days in winter and summer (January and April 2009) with no significant synoptic activity were chosen for the study. Sensitivity experiments of the ARW model were conducted with two non-local (Yonsei University [YSU], and Asymmetric Convective Model v. 2 [ACM2]) and three local turbulence kinetic energy (TKE) closure (Mellor-Yamada Nakanishi and Niino Level 2.5 PBL [MYNN2], Mellor-Yamada-Janjic [MYJ], and quasi-normal scale elimination [QNSE]) turbulence diffusion parameterizations, to study the evolution of PBL parameters and the thermodynamical structure during the study period. After validation of the simulated parameters with the available in-situ data, it was revealed that the non-local PBL scheme YSU, followed by local scheme MYNN2, could able to capture the characteristic variations of surface meteorological variables and the thermodynamical structure of the atmosphere. The present results suggest that the PBL schemes, namely YSU and MYNN2, performed better in representing the boundary-layer parameters and are useful for air pollution dispersion studies.

Climate modeling and prediction is important in water resources management, especially in arid and semi-arid regions that frequently suffer further from water shortages. The Maharlu-Bakhtegan basin, with an area of 31 000 km2 is a semi-arid and arid region located in southwestern Iran. Therefore, precipitation and water shortage in this area have many problems. This study presents a drought index modeling approach based on large-scale climate indices by using the adaptive neuro-fuzzy inference system (ANFIS), the M5P model tree and the multilayer perceptron (MLP). First, most of the climate signals were determined from 25 climate signals using factor analysis, and subsequently, the standardized precipitation index (SPI) was predicted one to 12 months in advance with ANFIS, the M5P model tree and MLP. The evaluation of the models performance by error parameters and Taylor diagrams demonstrated that performance of the MLP is better than the other models. The results also revealed that the accuracy of prediction increased considerably by using climate indices of the previous month (t – 1) (RMSE = 0.802, ME = –0.002 and PBIAS = –0.47).

The emissions of greenhouse gases (GHGs) in an oil palm plantation associated with land use change have been evaluated on a site-specific basis. Nitrous oxide (N₂O) emissions from the application of nitrogen fertilizers during the growth stages of the palm oil were analyzed for palms of different ages within the plantation. The N₂O release ranges between 19.11-22.17 kg of N2O-N/ha, resulting in the emission of 1052.26-1209.51 kg of CO2-eq/ha. However, there is no clear relationship between the emissions of N2O or CO2-eq and the age of the oil palms. On the other hand, the impact from land use change for the development of the site was also evaluated by assessing the emissions from carbon stock changes within the plantation. The transformation of a rubber estate into an oil palm plantation loses the soil carbon content (i.e., release of carbon emissions). However, this phenomenon has been anticipated in literature. Overall, fertilizer-related emissions and fuel emissions during the growth stages contribute to about 79 and 21%, respectively, of the total GHG emissions from the plantation. Therefore, it is likely that the application of nitrogen fertilizer may increase the existing carbon emission from the conversion of rubber to oil palm plantation, but the values are within the estimated for a Malaysian oil palm plantation.

  Atmósfera 29(1), 23-34 (2016)Fluid dynamics has the purpose of understanding the movement of liquids and gases by functions that describe the distribution of velocities. Some natural phenomena that present these functions are hurricanes, generated by pressure differences; cyclones, developed by the horizontal temperature gradient; and eddies, associated with a hydrostatic pressure gradient. In the particular case of eddies, they generate the so-called secondary velocities, which are flows formed by the presence of unequal forces between a hydrostatic pressure gradient and centrifugal forces, or by shear stresses at the joining of two flows. In addition, this phenomenon is observed in tornados, where the centrifugal force is greater in the upper layer and decreases towards the bottom, whereas the pressure gradient moves from a high to a low pressure; while in rivers it is detected particularly in bends or joins. Understanding the development of secondary currents is important for the reason that flow behavior is a function of the magnitude of these currents; hence their characterization is fundamental. The objective of this study was to obtain the secondaryvelocities developed as an effect of the union of two water currents, based on data acquired from Doppler acoustic recorders. A second objective was to draw the secondary velocities and to show the rotation flow effect, a kind of results that are difficult to obtain in any other way. The flow mechanisms are related with erosion and sedimentation processes; therefore, understanding them might help to evaluate and predict morphological changes in rivers.

This study was conducted to investigate the compositional characteristics of particulate matter (PM) collected both at an urban background site (Elms Road observational site, EROS) and a roadside site (Bristol Road observational site, BROS). PM samples were collected at the receptor sites between March 28 and April 11, 2012. Observed parameters included water-soluble ions (Cl–, NO–3, SO42–, Na+, NH4+, K+, Mg2+, Ca2+) and trace metals (V, Al, Cr, Mn, Fe, Zn, Cu, Sb, Ba, Pb). Results showed higher concentrations of NO–3, NH4+, Al and Fe at BROS than EROS regarding PM2.5; and Cl–, NO–3, Na+, K+ and Fe regarding PM2.5-10, indicating roadside increments. The ionic and metal components of PM2.5 at EROS constituted 44 and 7% of the total measured PM mass, respectively. The proportions of these species were 46 and 8% at BROS. For PM2.5-10, water-soluble ions and trace metal components represented 42 and 12% at EROS, and 56 and 11% at BROS.

The purpose of this study is to select a number of stations from the existing Sistema de Monitoreo Atmosférico (Atmospheric Monitoring System, SIMAT) of Mexico City to serve as an equivalent to the Photochemical Assessment Monitoring Stations according to the US-EPA criteria, in order to improve the study of urban ozone occurrence. The results indicate that four existing SIMAT stations meet the criteria to form such network. The relevance of this study is to present an ozone precursors monitoring network with continuous measurements for future trustful studies on air quality for ozone, considering the atmospheric chemistry and photochemical modeling for the design control strategies appropriate for the particular conditions of Mexico City.

Air pollution is a threat to cultural heritage because it accelerates the natural deterioration of monuments, palaces, churches, and archaeological ruins, which have an irreplaceable value. In the Mexico City Metropolitan Area (MCMA), there are 19 968 buildings registered as archaeological, historic, or artistic monuments. Some are built with calcareous rocks (limestone and marble) but many of them are made with andesite, tezontle and tuff stone. This paper reports for the first time the spatial distribution of the potential risk of deterioration on calcareous rocks in terms of surface recession with regard to Mexican cultural heritage in the MCMA for the base year 2007. The risk estimate was performed using Lipfert’s damage function, only applicable to carbonate stones of medium and low porosity. These include mainly medium/high density limestone and marble. Carrara white marble has a density of 2.69 g cm–3 and a porosity of 0.37%, and limestone has a density of 2.2-2.6 g cm–3 and a porosity of 5-20%. For high porosity (low density) limestone the function would be applicable with a potential under-estimation. In this function, annual recession rate is a function of annual averages of precipitation, pH, and dry deposition of SO2 and HNO3. Data from several meteorological monitoring networks, the MCMA air quality and acid deposition monitoring networks, and a 3D air quality model (MCCM) were interpolated in a GIS in order to obtain map layers for these variables. These overlaid maps were used to apply the Lipfert functions at the specific coordinates of a small sample of relevant historic or artistic monuments. The complexity of climate gradients, wind patterns, and emissions distribution within the Mexico Megacity leads to gradients as large as 50% in estimated recession rates using the Lipfert function at nearby sites made of the same type of building materials. The Comisión Ambiental de la Megalópolis (Environmental Commission of the Megacity) divides the MCMA into five sectors. Differences in recession rates between them were, in 1990, as large as those between estimated values for Oviedo, Paris, and Prague in Europe for the period 1980-2000. Recession rates decreased by about 50% from 1990 to 2007, the base year for this report, due to the success of air pollution control actions focused on the protection of public health. Nevertheless, strong recession gradients are still expected for carbonate stone within the MCMA. The recession values reported in this work must be taken as conservative estimates due to the not yet optimal performance of 3D air quality models in urban meteorology and the high degree of uncertainty in modeling emissions inventories. Most notable is the SO2 emissions inventory. These maps call for a program of experimental determination of recession rates for building materials that comprise a very large part of Mexico’s unique cultural heritage. These maps should also be added to the critical level maps obtained for human exposure, crops, and ecosystems in order to properly estimate the actual cost of air pollution in the MCMA and the area under its influence.

The design flow is the basis for planning and designing different hydraulic works. The precision in estimated flows is important when analyzing the feasibility of such structures because the value directly influences the evaluation of the failure effects. However, due to flow variability, the precision of the estimate is drastically reduced when small samples are used in a conventional flood frequency analysis (FFA). This paper proposes a new approach based on a combined simulation of the annual peak and mean flows. The method was evaluated by considering 10-, 20-, 30-, 40- and 50-yr subsamples obtained from 13 gauging stations located in the Susquehanna River basin. The results were compared with those obtained by FFA and the regional station-year method. This new approach can reduce the uncertainty in estimating the design flow when few data are available.