Centro de Ciencias de la Atmosfera

Quantitative analysis of phenolic compounds from four apple varieties (Golden and Red Delicious, Granny Smith and Green Reineta) using high-performance liquid chromatography with diode-array detection was carried out. For each variety, both peel and pulp were analysed. The identification of phenolic compounds was made by comparing their retention times and UV spectra with those of standards. The results revealed differences between pulp and peel in all cases studied. The highest levels of phenolic compounds were found in the peel. High levels of catechins and flavonol glycosides, especially rutin, were found in apple peels. Chlorogenic acid was the major peak in the pulp for all apple varieties studied except for Granny Smith. Significant quantitative differences between the apple varieties were also found, the Golden Delicious variety showing the lowest content of phenolic compounds and Green Reineta variety the highest. The recovery of phenolic compounds from both peel and pulp was measured in all apple varieties. The values ranged between 95 and 105%, indicating close to quantitative recovery for the method used.

In this paper, the unfeasibility of producing "objective" probabilistic climate change scenarios is discussed. Realizing that the knowledge of "true" probabilities of the different scenarios and temperature changes is unachievable, the objective must be to find the probabilities that are the most consistent with what our state of knowledge and expert judgment are. Therefore, subjective information plays, and should play, a crucial role. A new methodology, based on the Principle of Maximum Entropy, is proposed for constructing probabilistic climate change scenarios when only partial information is available. The objective is to produce relevant information for decision-making according to different agents' judgment and subjective beliefs. These estimates have desirable properties such as: they are the least biased estimate possible on the available information; maximize the uncertainty (entropy) subject to the partial information that is given; The maximum entropy distribution assigns a positive probability to every event that is not excluded by the given information; no possibility is ignored. The probabilities obtained in this manner are the best predictions possible with the state of knowledge and subjective information that is available. This methodology allows distinguishing between reckless and cautious positions regarding the climate change threat.

This paper explores the relation between coffee production and climatic and economic variables in Veracruz in order to estimate the potential impacts of climate change. For this purpose, an econometric model is developed in terms of those variables. The model is validated by means of statistical analysis, and then used to project coffee production under different climatic conditions. Climate change scenarios are produced considering that the observed trends of climate variables will continue to prevail until the year 2020. An approach for constructing simple probability scenarios for future climate variability is presented and used to assess possible impacts of climate change beyond what is expected from changes in mean values. The model shows that temperature is the most relevant climatic factor for coffee production, since production responds significantly to seasonal temperature patterns. The results for the projected climate change conditions for year 2020 indicate that coffee production might not be economically viable for producers, since the model indicates a reduction of 34% of the current production. Although different economic variables (the state and international coffee prices, a producer price index for raw materials for coffee benefit, the national and the USA coffee stocks) were considered as potentially relevant, our model suggests that the state real minimum wage could be regarded as the most important economic variable. Real minimum wage is interpreted here as a proxy for the price of labor employed for coffee production. This activity in Mexico is very labor intensive representing up to 80% of coffee production costs. As expected, increments in the price of such an important production factor increase production costs and have strong negative effects on production. Different assumptions on how real minimum wage could evolve for the year 2020 are considered for developing future production scenarios.

In this paper, the unfeasibility of producing “objective” probabilistic climate change scenarios is discussed. Realizing that the knowledge of “true” probabilities of the different scenarios and temperature changes is unachievable, the objective must be to find the probabilities that are the most consistent with what our state of knowledge and expert judgment are. Therefore, subjective information plays, and should play, a crucial role. A new methodology, based on the Principle of Maximum Entropy, is proposed for constructing probabilistic climate change scenarios when only partial information is available. The objective is to produce relevant information for decision-making according to different agents’ judgment and subjective beliefs. These estimates have desirable properties such as: they are the least biased estimate possible on the available information; maximize the uncertainty (entropy) subject to the partial information that is given; The maximum entropy distribution assigns a positive probability to every event that is not excluded by the given information; no possibility is ignored. The probabilities obtained in this manner are the best predictions possible with the state of knowledge and subjective information that is available. This methodology allows distinguishing between reckless and cautious positions regarding the climate change threat.

This paper explores the relation between coffee production and climatic and economic variables in Veracruz in order to estimate the potential impacts of climate change. For this purpose, an econometric model is developed in terms of those variables. The model is validated by means of statistical analysis, and then used to project coffee production under different climatic conditions. Climate change scenarios are produced considering that the observed trends of climate variables will continue to prevail until the year 2020. An approach for constructing simple probability scenarios for future climate variability is presented and used to assess possible impacts of climate change beyond what is expected from changes in mean values. The model shows that temperature is the most relevant climatic factor for coffee production, since production responds significantly to seasonal temperature patterns. The results for the projected climate change conditions for year 2020 indicate that coffee production might not be economically viable for producers, since the model indicates a reduction of 34% of the current production. Although different economic variables (the state and international coffee prices, a producer price index for raw materials for coffee benefit, the national and the USA coffee stocks) were considered as potentially relevant, our model suggests that the state real minimum wage could be regarded as the most important economic variable. Real minimum wage is interpreted here as a proxy for the price of labor employed for coffee production. This activity in Mexico is very labor intensive representing up to 80% of coffee production costs. As expected, increments in the price of such an important production factor increase production costs and have strong negative effects on production. Different assumptions on how real minimum wage could evolve for the year 2020 are considered for developing future production scenarios.

To characterize observed global and hemispheric temperatures, previous studies have proposed two types of data-generating processes, namely, random walk and trend-stationary, offering contrasting views regarding how the climate system works. Here we present an analysis of the time series properties of global and hemispheric temperatures using modern econometric techniques. Results show that: The temperature series can be better described as trend-stationary processes with a one-time permanent shock which cannot be interpreted as part of the natural variability; climate change has affected the mean of the processes but not their variability; it has manifested in two stages in global and Northern Hemisphere temperatures during the last century, while a second stage is yet possible in the Southern Hemisphere; in terms of Article 2 of the Framework Convention on Climate Change it can be argued that significant (dangerous) anthropogenic interference with the climate system has already occurred.

From the climatologic data bases (SICLIM and CLICOM) built by the Servicio Meteorológico Nacional (SMN) of Mexico, we have defined two normals: one called Period I, from 1950 to 1975, and the other called Period II, from 1976 to 2000. The objective of the present work is to make an estimation of the annual volume of superficial available water in Periods I and II, and the changes between them, in two important hydrologic regions of Mexico, called Lerma-Santiago-Pacifico (HR-LSP) and Balsas (HR-B), whose population annually demands almost one-third of the water extracted in all the country. For this purpose, a non-linear thermo-hydrological model is used. It consists of two equations applied to the soil, i.e. the thermal energy and water balance equations, which are coupled through the soil temperature and soil moisture. The results show that the change from Period I to Period II was more significant in the HR-B than in the HR-LSP. In the HR-LSP, the conditions of aridity were favoured by a decrease of 3.4% in the precipitation, which affected almost the entire region. On the average, the HR-B experienced an increase of 7.0% in precipitation, and therefore, a considerable increase in the volume of available water from Period I to Period II. However, in the northern part of this region, the increase in temperature and the decrement in precipitation reduced water availability, while the opposite occurred in the south of the region, where the decrease of the temperature and the increase in the precipitation increased the available water and favoured conditions of humidity in Period II.

El Panel Intergubernamental de Cambio Climático (IPCC, por sus siglas en ingles)
publicado en el 2001 su tercer informe sobre cambio climático. Dentro de este
informe se hace referencia a la vulnerabilidad de México al cambio climático ; en
particular La Primera Comunicación Nacional ante la Convención Marco de las
Naciones Unidas sobre el Cambio Climático se basa en gran parte en los
resultados obtenidos en el Estudio de Pais: México, México ante el Cambio
Climático, coordinado por ej Instituto de Ecología bajo Ja dirección de Carlos Gay
(Fernandez et al 2001-2002), apoyado por investigadores de! mismo centro. Del
Estudio Pais se derivan los primeros estudios sobre el impacto de un posible
cambio climático en ta cosecha del maíz en 7 sitios en la parte central de México
realizados por Conde et al (1997). Estos estudios pioneros demuestran que e}
cambio climático puede tener un impacto importante en Ja producción del maíz,
teniéndose que tomar medidas de adaptaci6n para mitigar dicho impacto.
Posteriormente estos estudios fueron enfocados a! estado de Tlaxcala (Conde et
al,1999,2000)}.
El trabajo presentado en esta tesis retoma el caso de estudio de Tlaxcala y se
introduce un método para planificar la fecha de siembra del maíz en ciertos
municipios de este estado ante un posible cambio climático. Este método consiste
en calcular, en el periodo fenomenológico del maíz, un índice agro-climático
establecido por la FAO (FAO, 1980) tomando en cuenta la humedad del suelo
inicial, para establecer la mejor fecha de siembra y obtener una mas alta
producción en la cosecha.

Una de las causas mas importantes que han derivado en una reducción de la
Capacidad productiva del campo agrícola mexicano es sin duda a los efectos de
algunos eventos climáticos extremos como son: sequias, las cuales se
caracterizan por temperaturas por arriba de su valor climático y por precipitaci6n
por debajo de su valor climáticos y por eventos meteorológicos extremos como
son: heladas asociadas a los nortes en México (Pérez |. 1996) 0 a Ciclones
Tropicales (Pérez 1.1990), estos fenómenos se desarrollan en cuestión de días (5
días). y lluvias en exceso, las cuales pueden presentarse por ondas del este
intensas, frentes o huracanes.

En lo que respecta al régimen de precipitación, la falta de Lluvias en Abril y la
primera quincena de Mayo se traduce en rendimientos agrícolas bajos,
principalmente en la region centro de México, Puebla, Hidalgo, Guanajuato,

Querétaro y Tlaxcala.

De esta manera, al contar con un pronostico de Lluvias para la primavera es de
gran importancia, pues se pueden tomar medidas tales como adelantar o atrasar

la fecha de siembra y/o usar semillas de periodo mas corto (Mendoza A. S 2001).

Las heladas son fenómenos meteorológicos extremos que afectan alrededor del
70% del territorio mexicano, provocando graves daños a la_ agricultura,
estadísticamente es mas probable que se presente una helada cuando la
temperatura minima es menor a los 6°C,.

From the climatologic data bases (SICLIM and CLICOM) built by the Servicio Meteorológico Nacional (SMN) of Mexico, we have defined two normals: one called Period I, from 1950 to 1975, and the other called Period II, from 1976 to 2000. The objective of the present work is to make an estimation of the annual volume of superficial available water in Periods I and II, and the changes between them, in two important hydrologic regions of Mexico, called Lerma-Santiago-Pacifico (HR-LSP) and Balsas (HR-B), whose population annually demands almost one-third of the water extracted in all the country. For this purpose, a non-linear thermo-hydrological model is used. It consists of two equations applied to the soil, i.e. the thermal energy and water balance equations, which are coupled through the soil temperature and soil moisture. The results show that the change from Period I to Period II was more significant in the HR-B than in the HR-LSP. In the HR-LSP, the conditions of aridity were favoured by a decrease of 3.4% in the precipitation, which affected almost the entire region. On the average, the HR-B experienced an increase of 7.0% in precipitation, and therefore, a considerable increase in the volume of available water from Period I to Period II. However, in the northern part of this region, the increase in temperature and the decrement in precipitation reduced water availability, while the opposite occurred in the south of the region, where the decrease of the temperature and the increase in the precipitation increased the available water and favoured conditions of humidity in Period II.

The latest phase of the program to improve the air quality in the Valley of Mexico, also known, as Pro Aire is about to go into effect for the next 10 years. Pro Aire puts emphasis on agricultural wind erosion and associated dust emissions impacting downwind air quality. The main objective of this investigation was to use an empirical USEPA erosion model coupled to a meteorological/transport-dispersion prediction model, CALMET/CALPUFF, to estimate dust emissions and concentrations in the Mexico City Basin. The model simulations for particulate matter (PM 10 ) are validated against observations taken at the most recent research field study, the IMADA-AVER field campaign, conducted during the spring of 1997 to provide information about high ozone, particulate matter concentrations and visibility impairment. The spatial and temporal PM distribution in the region is presented for a specific wind blown dust event consisting of two IMADA days, in order to understand how soil dust emissions from agricultural fallow land affect downwind areas during the dry season. Results show good agreement with the main spatial features of the local wind circulation and wind blown dust concentrations. A correlation coefficient of nearly 0.8 between predictions and observations for a modeled day suggests that an important portion of the total measured concentration had geological origin. This work constitutes an essential advancement on the mesoscale air quality problem on the MCMA due to wind erosion. r

In this study, the sensitivity of trajectory paths to anomalous soil moisture was analyzed during three different synoptic episodes in June 2006. The MM5 and Noah land surface models were used to simulate the response of the planetary boundary layer. The HYSPLIT model was used for trajectory analysis. It was found that the response in horizontal lower-level wind field was larger at regions where vertical wind velocity changes were also large. In addition, the sensitivity to soil moisture changes was significant and localized where convective activity was well developed and synoptic effects did not dominate. A nonlocal effect was felt over the rest of the domain where convection was not present since the model atmosphere reacted as a whole to compensate for induced changes in vertical velocity. This finding was supported by the fact that domain averaged vertical velocities changes were of the order of 0.2 cm s À1 or less at about 650 hPa and about 200 times smaller than modeled local vertical velocity changes. The largest change in horizontal wind field near the surface was found for weak synoptic events on June 11-12 and June 22-23 while the stronger synoptic event of June 17-18 showed smaller differences. These changes in wind field conditions impacted the transport and dispersion of pollutants. To quantify the sensitivity of air quality estimates to soil moisture uncertainty, we have used three well known measures of trajectory differences: the absolute horizontal transport deviation (AHTD), the relative horizontal transport deviation (RHTD) and the absolute vertical transport deviation (AVTD) for an ensemble of 98 trajectories departing from a region well within the computational domain. For the June 11-12 event it was found that for wet and dry soil moisture experiments, AHTD, RHTD, and AVGTD can reach values in the range 60-100 km, 10-20% and 500-900 m at 24 h run time, respectively. For the June 17-18 and June 22-23 events these values of trajectory differences were reduced more than half. These differences in behavior between time periods are largely attributed to the combined effects of synoptic forcing and the sensitivity of planetary boundary layer to soil moisture changes during well developed convection. The implication for air quality studies is that the soil moisture anomaly and related uncertainty in planetary boundary layer response needs to be incorporated in order to construct an ensemble of the most probable scenarios in which pollutants are released and transported throughout a given target region.

Keywords: land use induced land cover change vegetation fraction MM5 planetary boundary layer surface energy balance Changes in land use land cover (LULCC), vegetation fraction (FV), and soil moisture affects land surface atmosphere interactions, characteristics of planetary boundary layer (PBL), and near surface atmospheric moisture content. Previous studies have investigated impacts of LULC, FV, and soil moisture changes on atmosphere separately. The present study investigates the combined impacts of changes in LULC, FV, and soil moisture, on PBL atmosphere and near surface atmospheric moisture content. The study is set in western region of Kentucky, USA. We have used the Noah land surface scheme and MM5 model for this purpose. The study used two nested domains. The current land use land cover of the inner domain was changed to grass, forest, and bare soil to represent historical changes and potential near future modifications. Subsequently, FV and soil moisture were systematically changed for each of the land uses. The simulations have found that changes of current land use to grass within the inner domain increases latent heat flux, dew point temperature, relative humidity, and equivalent potential temperature. It was found that height of the PBL was reduced and development of circulation cells was visible along land use land cover discontinuity. Changes in horizontal and vertical wind field were also reported. FV changes for grass further magnified these impacts. For example, decrease or increase in FV has decreased or increased latent heat flux. Similar response of other PBL parameters could be found for changes in FV along with LULC. It was also found that if we replaced forest with lower FV by grass with higher FV, the impacts could cancel each other. Changes to forest and bare soil land use types and lower FV for forest also produced generally similar types of responses. Soil moisture changes, particularly drying, further impacted these responses. This study finds that increase in FV counteracts impacts of soil moisture reduction up to a level. Overall, grass produced moister PBL and lowered the height of PBL and LCL. It is interesting to note that during nighttime the impacts of LULC, FV and soil moisture changes were diminished. These changes not only modified meso-scale wind fields but also potential for convective development. It was concluded that similar experiments needed to be undertaken for convectively conducive environments to better understand the combined impacts of changes in LULC, FV and soil moisture.