Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

The border city of Mexicali has some of the worst air pollution in México, mainly due to the high levels of fine particulate matter (PM) and O3 registered. This also impacts the air quality of communities across the border in California’s Imperial Valley. A field campaign was conducted in April of 2005 to obtain ambient concentrations of volatile organic compounds (VOC), and thus obtain insight on the levels and sources of these O3 and fine PM precursors. Six-liter stainless steel canisters were deployed at a site located in the downtown area of the city to obtain ambient air samples that were then analyzed for 54 selected target species. Samples were collected on a daily basis at three different sampling times: 6-9, 13-16, and 20-23 h LT. Average total non-methane organic compounds (TNMOC) concentration was 560 ppbC, with the morning samples having the highest reported average concentration (795) and the afternoon the lowest (257 ppbC). Aromatics contributed around 24% to the TNMOC concentration. Correlation between different species indicates strong influence of local anthropogenic sources (e.g., xylenes-benzene ratio of 2.1). In addition, high correlations between typical products from internal combustion engines (e.g., acetylene-ethene R2 = 0.90, ethene-propylene R2 = 0.94, benzene-ethene R2 = 0.75) across all samples and a consistent contribution of more than 15% of these species (ethene, acetylene, propylene and benzene) indicate major contribution from mobile sources. This is supported by receptor modeling results obtained through the application of the Chemical Mass Balance model to the ambient data. Source apportionment estimates indicate a 56% contribution of gasoline-related mobile source emissions to the VOC that were measured, 18 contribution from LPG emissions, 6 from diesel exhaust, and 5 from consumer products.

A study was undertaken to establish the spatio-temporal behavior of the extreme daily values of atmospheric pressure at ground level in a zone comprising the central part of the Iberian Peninsula (Spanish Central Plateau). The study involves the time period between 1961 and 2003. From the data series of minimum values of daily pressure, measured at 14 weather observatories in the zone over the time period considered, the series of anomalies in daily pressure (differences with respect to the mean) were constructed for each of the observatories and for the Spanish Central Plateau and for each of the zones into which this latter can be subdivided. The extreme values of these anomalies were established considering as threshold values those of the P05 percentile, for the lowest values, and of the P95 percentile for the highest one. The series of extreme, annual and seasonal anomaly frequencies were constructed and, finally, the trend of those frequencies was analyzed, both for each individual weather observatory and for the regions considered. In all cases, the results proved to be in agreement. Analysis of the trend of the annual series of extreme anomaly frequencies over the Spanish Central Plateau revealed that the lowest values of minimum daily pressure at ground level follow a decreasing trend while for the highest ones the trend is increasing. That is, between 1961 and 2003 the number of days per year with higher of minimum atmospheric pressure values at ground level increased whereas the number of days per year with lower values decreased. Additionally, an analysis was made of the trend of seasonal series; from the results, it is concluded that only the winter is determinant as regards the behaviour of the annual series.

This paper analyzes some summer rainfall characteristics in Buenos Aires and developes a seasonal prediction scheme. Buenos Aires is located along the coast of the Río de la Plata in Argentina. The outstanding rainfall feature is the presence of an annual cycle with maximum precipitation in summer. The analysis of the annual rainfall evolution since 1908 showed a positive trend of 2.1 mm/year and 1.8 mm/year for the period between December and February, representative of the summer season. The Observatorio Central Buenos Aires/station, located in the downtown, registered a mean annual accumulated rainfall of 1070 mm with a standard deviation of 239 mm, during the period 1908-2007. The mean accumulated precipitation during January, February and March was 305 mm with a standard deviation of 125 mm. The wet and dry periods were identified and the dry periods tended to be longer during 1908-1957 meanwhile wet periods resulted longer and more intense in 1958-2007. Accumulated rainfall between December and February was related to some mean meteorological variables between September and November, with the aim to develop a statistical prediction scheme. Careful selection of predictors, based largely on physical reasoning, was done and they were used in a regression model, following a forward stepwise methodology. The analysis shows that the most important source of predictability comes from the cyclonic activity in the Atlantic Ocean and the flow from Brazilian forest. The observed and forecast rainfall series were significantly correlated (0.59) and nearly the 35% of summer rainfall variance was predicted by the proposed method. A semi-quantitative validation was done by using terciles of the observed and forecast distributions. The skill of the forecast got a good result although there is still an important portion of the variance that cannot be explained by this model and therefore, the method might be improved in future research.

Studies from throughout much of the world have shown a general increase in extreme precipitation events over the past few decades, although most of these studies have focused on mid-to-high latitude land-based locations, particularly in the Northern Hemisphere. Many tropical and subtropical areas have not been analyzed due in part to non-existent or non-continuous data required for assessments of longer-term trends in extreme events. However, in this investigation, we assembled daily precipitation records for 142 stations in southern México over the period 1960-2004 and calculated 23 different annual indicators of extreme precipitation events that have been widely used in the professional literature. Ultimately using 44 of these stations with the most complete records, we used various univariate and multivariate statistical procedures to uncover the underlying significant upward trend in the occurrence of extreme events. Furthermore, we found that the variations in extreme events were significantly related to El Niño-Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO), with extreme events tending to occur more frequently during La Niña periods and during the positive phase of the PDO.

In México, there is a network of 12 meteorological radars to monitor intense convective systems. Data from Cerro de la Catedral Doppler radar, 40 km northwest of México City, have been used to obtain precipitation rates estimates during intense precipitation events. Results show that although estimates are close to the observed precipitation in surface stations, a new configuration of the radar system is necessary to better capture the characteristics of intense storms, particularly at the foothills of the western mountains. The comparison between the estimate from the radar and a dense network of rain gauges shows that such deficiency may be related to systematic errors due to blockage (radar), but also to sampling problems (radar and rain gauge). The calibration by itself may not be enough since there is significant blockage with the radar at the peak of a high elevation but relatively distant mountain. Such location limits the scan capacity from making a good vertical coverage. The present characteristics of the elevation of the radar beam prevent the radar from estimating the amount of precipitation in the lowest part of the clouds, near the cloud base. A new configuration of the radar system for México City is proposed taking into account spatial coverage and propagation effects upon a standard atmosphere in a horizontally constant reflectivity field.

Spatial variability in the climate of México City was studied using multivariate methods to analyze 30 years of meteorological data from 37 stations (from the Servicio Meteorológico Nacional) located within the city. Although it covers relatively small area, México City encompasses considerable climatic heterogeneity, due mainly to the contrasts in elevation and land use within its territory. Multivariate methods were used in this study to reduce the dimensionality of the variables reported by the weather stations, to define climate indexes for representing the main features of México City’s climate more compactly, as well as to identify geographic zones with similar climatic characteristics. The results of the study contribute additional evidence of the important influence of orography and urbanization on climates in cities. Two large regions and four subregions with similar climatic characteristics were identified in this study: low altitude suburban, low altitude highly urbanized, urbanized mountain base, and higher elevation with forests. Three climate indices were also defined. The three indexes are related to temperature and precipitation, to days with fog and with electrical storms, and to days with hail and low temperatures. The results of this study suggest that multivariate analysis can be a useful tool for urban planning and for tracking the impact of anthropogenic factors on microclimate.  

This study is the second part of a series where NH3 and NOx emission inventories for Galicia (NW Spain), a region with a great risk of eutrophication, have been developed. The principal sources of NOx emissions in Galicia and their associated uncertainty have been calculated in this paper. The results prove that industrial and mobile sources produce 90% of the emissions, principally due to road transport, power and cogeneration plants. Use of fertilizers or fuels for residential purposes, burning of agricultural waste, soils, fires and lightning are minor sources of emissions. In the case of fires, in regions specially affected like Galicia, attention must be paid to variations in number and type of burnt areas from one year to another, because it can significantly change total NOx emissions. The emissions produced by agricultural, fishery and forest vehicles and machines as well as by maritime and railway traffic are the main focus of uncertainty due to the lack of specific data for Galicia like type, age and power of the machines. Other important focuses of uncertainties are the emissions from soils and fires owing to the absence of a more specific methodology.

An analysis of the weekend air pollution episode of April 14-15, 2007 is presented using air quality modeling techniques. It is shown that the emissions of Toluca Metropolitan Area west of México City influencing the air quality of the city is a better explanation of the air pollution event on that weekend than the existence of a “weekend effect”. It is also shown that the enforcement of traffic rules curbing car circulation during that weekend would not have resulted in ozone concentration reductions over México City. The improvement in air quality in México City requires the implementation of comprehensive measurements at the regional scale.  

This work identifies some of the climate-hydrological variables that best express the vulnerability of hydrological resources at watershed level (Sinú-Caribbean Basin, Colombia). The analysis utilizes the outputs of some general circulation models runs under different scenarios of greenhouse gas emissions (A2 and B2). The IPCC has produced diverse scenarios of greenhouse gas emissions, reported in the Special Report on Emissions Scenarios (SPES) (IPCC, 2001). Statistical downscaling models (SDSM) are used that allow the observation of climate change at local level; the Water Evaluation and Planning System (WEAP), an integrated approach to simulate water systems and orient management policies, is applied as well as certain mathematical analyses and statistical methods. Thus, the study visualizes and analyzes the incidence of potential climate change on the hydroelectric sector, finding the degree of vulnerability for this or any other sector that relies on water as a source, and offers tools, strategies and criteria for the planning and orientation of projections in the different productive sectors. The results predict increases in maximum, mean and minimum temperatures, for example, the maximum temperature before the end of the century could rise from 1.3° to 2.5°C in scenario A2 and from 0.9° to 1.7°C in B2; an increase in precipitation is estimated up to approximately 30.4% in A2 and 27.9% in B2. The number of extreme events forecast is found over previously determined thresholds; an estimation is made of the water balance and the relation of the above variables to the Sinú River inflow to the Urrá 1 dam and the generation of hydroelectric energy. Changes in the generation of hydroelectric energy vary from 0.6 to -35.2% for the period 2010 to 2039, reduction in the Sinú River inflow to the dam in a range of -2.3 to -34.9% and a drop in the stored volume in the dam of -0.9 to -29.4 percent in relation to the maximum storage capacity (MSC), according to the analyzed scenario.  

The Penman-method (PM) to estimate the reference evapotranspiration (ETo) needs four meteorological parameters: air temperature, relative humidity, wind velocity, and net radiation, which may not be everywhere available and is the most reliable method and recommended by the FAO as the standard to verify other empirical methods. However, the Thornthwaite (TM) and Hargreaves (HM) models are frequently used because they are based on measurements of air temperature, commonly recorded in many meteorological stations throughout the world, becoming an option for estimating ETo. Nevertheless, in order to obtain appropriate results, the equations need to be locally calibrated. In the present study, the original coefficients of the TM and HM were modified for regional calibration in semi-arid and tropical subhumid in the state of Yucatán, México, using as a standard the Penman- equations of FAO. Meteorological data from two stations in the state of Yucatán, México were used, corresponding to a coastal, semi-arid climate (Progreso) and an inland, tropical subhumid climate (Mérida). In the comparison, the indices of concordance (D), confidence (C), correlation (R) and regression (R2) were analyzed, together with the mean bias error (MBE), root mean square error (RMSE), relative error (RE) indicators and the ratio between both average estimations of ETo (r). Using the HM without adjustment, we obtained good estimations of ETo, both in Mérida and in Progreso, with C values of 0.825 and 0.816, respectively. The use of TM without adjustment is not recommended in neither of the studied meteorological stations. However, in both stations, TM without adjustment is the best model for the estimation of ETo during the rainy months (from June to October). In both inland and coastal meteorological stations, better annual estimations of ETo are obtained by the use of the HM with adjustment (C values of 0.906 and 0.917 respectively).