Monitoring and analyses of various air pollutants like particulate matter (PM10), sulphur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO) and ammonia (NH3), as well as meteorological parameters (temperature, humidity, wind speed and direction) have been performed for the period between April and May, 2014 at three different sites (an area with high vehicular density, a residential area and an industrial area) of an urban area in eastern India. The hourly average concentration of surface ozone is found maximum at the industrial site (70.085 µg/m3) followed by the residential site (39.067 µg/m3) and the site with high vehicular density (25.936 µg/m3). The site with high vehicular density shows the maximum 24 h average concentration of NO2 (86.112 µg/m3) and NH3 (109.673 µg/m3). Maximum daily (24 h) average concentration of PM10 (392.127 µg/m3) and SO2 (174.069 µg/m3), and highest hourly average of CO (3.846 mg/m3) at the industrial site can be attributed to emissions from the surrounding industries. Computation of air quality indices (AQI) show that both site I (a traffic congested area with AQI = 53.85) and site III (an industrial area with AQI = 71.68) fall under a moderately polluted category whereas site II (a residential area with AQI = 22.69) is found to be clean. This detailed study reveals that variations in the concentration of different air pollutants manifest the combined effect of emission sources and patterns, planetary boundary layer height and meteorology.

Paleoclimatology data includes measures of the amount of carbon dioxide in the atmosphere and level and temperature of the oceans, among others. Recent records of climate change data were done at equidistant times; the different variables were typically measured at the same time to allow for association studies among them. However, there are no registered records of climate change data for thousands or millions of years ago. Scientists have had to device alternative ways of measuring these quantities. These methods are usually a result of indirect measurements, such as ice coring, where both the variable of interest and the time have to be estimated. As a result, paleoclimate data are a collection of time series where observations are unequally spaced. Here we review a Bayesian statistical method to produce equally spaced series and apply it to three paleoclimatology datasets that span from 300 million years ago to the present.

Dust 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.

Due to the lack of models to predict the ozone layer even after an ample range of total column ozone (TCO) measurements around the globe, a direct relationship between solar activity by means of sunspot number observations and total ozone satellite data for a tropical Andes mountains region at Bogotá-Colombia, is presented. Sunspot number data and 37 years of TCO records from satellite missions Nimbus 7, Meteor 3, Earth Probe and AURA from January 1979 through August 2016, are analyzed. Ozone annual cyclic behavior, which strongly depends on the annual cyclic Sun-Earth distance variation, as well as the dynamics of the solar activity cycles allow to derive a physical-mathematical adaptive model for predicting and reconstructing daily stratospheric ozone over the city of Bogotá, very close to the equator. Results suggest that the ozone layer as a natural indicator of solar activity.

Mexican islands are one of the most diverse territories in the world and consequently their conservation should be a national and international priority. Three main threats to islands’ diversity have been detected: invasive species, land use change and climate change. Most studies have been focused on invasive species and land use change. Actually, as far as we know, this work is the first approach to evaluate climate change impacts on the biodiversity of islands in Mexico. We had two main goals: to list the vertebrate species that have been registered in Mexican islands and to model the possible impacts of climate change in the distribution of islands’ vertebrates. To evaluate climate change impacts, we used the ecological niche modeling that relates geographic occurrences with environmental variables to create a bioclimatic profile that can be projected in other time and other geographic areas. In our results we obtained a list of species registered in Mexican islands that increased in more than twice the number of species acknowledged by the Mexican government and the ecological niche modeling of 54 vertebrate species. We found that the species list effort was very important, because knowing which species exist is the first step to preserve them. In terms of ecological niche modeling, we modeled mammals, reptiles and amphibians. From these three groups, reptiles were the group with greatest losses and more species in the top-ten vulnerable list. If we considered a no dispersion scenario, all evaluated species presented losses regarding their current potential distribution area. If the full dispersion scenario was taken into account, the net change value resulted positive for the majority of the species evaluated, consequently if no barriers exist and the dispersion ability is good enough, changes in climatic conditions might not be an important threat. However, this is not the case for most species evaluated. Areas with a higher number of species (richest areas) do show changes in the future with shifts to the east and north of the country. Finally, we could find significant differences between times and scenarios in terms of suitable area losses. Greatest losses can be found in the long term RCP 8.5 Wm–2 in comparison to the long term RCP 4.5 Wm–2, meaning that the direction that humanity takes in terms of climate change will have consequences on island biodiversity. In this work, we did not take into account the sea level rise, which is expected to have important impacts on islands species.

Tropical cyclone Mitch, which occurred in October 1998 on the Caribbean Sea, is studied. Mitch affected countries in Central America, where it caused great economic and human losses, and the authors believe that the scientific community has not paid enough attention to this phenomenon. Two NE-SE oriented dipole patterns associated with their convergence-divergence zones contributed significantly to its formation and intensification, which are analyzed from the observational synoptic point of view. The most remarkable characteristics of this phenomenon in the mean field occurred between October 18 and November 4, 1998 when another NW-SE dipolar pattern was formed, consisting of a high-level anticyclone from North America (HLA) and a high-level anticyclone from South America (HLC). To discern these patterns, two data sources were used: the NCAR-ds627.0 (ERA-Interim) reanalysis and the NCEP/NCAR reanalysis. The simplest idealization of the NW-SE dipolar vortex is a tropical modon, which is an exact solution of the barotropic vorticity equation (BVE) on a rotating sphere. The role of the HLA and the HLC in the excitation of tropical waves is explored using a numerical spectral method for sutdying the normal mode stability of exact solutions of the BVE. The initiation of the tropical wave at low levels could be associated with disturbances at high levels of the most unstable normal mode.

Climate change is considered a serious threat to food security worldwide. In this study, yields of maize, beans, wheat, soybean, sorghum, barley and potato were modeled with 28 future climate change scenarios. Our results reduce the information gap that is frequently reported for Mexico and will contribute to better knowledge on spatial impact of climate change. We applied FAO AquaCrop model for 22 case studies located in 14 states of Mexico. Climate change scenarios were: CNRM, GFDL, HADGEM, MPI and Ensemble REA, with two radiative forcing concentrations (4.5 and 8.5 W m–2) and three time horizons (2015-2039, 2045-2069, and 2075-2099). The results show decreases in yields of most of the case studies as a consequence of a decrease in the amount and distribution of precipitation. Maize yield in warm dry climates could decrease up to 84% in the most severe scenarios. Beans could decrease from 10 to 40% in the north of the country, while in the northwest a 15% decrease in wheat yield is predicted. Soybeans could benefit, with increases from 15 to 40%. Sorghum and potatoes are expected to decrease for all the case studies, while barley would have increases and decreases. The results suggest differentiated impacts according to crops and regions studied. We concluded that agriculture requires better focused strategies and policies (attention on crop and spatial distribution).

Arid and semi-arid lands in Mexico dominate 60% of the national territory. They harbor many endemic species, as well as a large proportion of the population, and offer diverse ecosystem services. These regions are subjected to anthropogenic impacts derived from agriculture and livestock farming, which have caused land degradation and desertification. In addition, these ecosystems are highly sensitive to climate variability and projected global environmental change. However, information about how land use/land cover change and climate variability processes overlap and synergize each other in these ecoregions is scattered in different publications, and it is desirable to integrate it to provides more complete information for decision making. In this study we describe both land cover and land use changes in the five arid and semi-arid ecoregions in Mexico (Sonoran, Chihuahuan, Tamaulipan, Mexican High Plateau and Tehuacán-Cuicatlán valley) between 2002 and 2011, and their current exposure to droughts, low temperatures, floods and tropical cyclones. These results are discussed in terms of regional climate trends documented in the literature. We found that land use and land cover change differ between ecoregions, with the Sonoran and Chihuahuan ecoregions being the least affected. The overall exposure to extreme climate events is high in all ecoregions except for the Tehuacán-Cuicatlán valley, although each region has different exposure profiles. Observed trends for all ecoregions generally point towards an increase in both maximum and minimum temperatures, while trends for precipitation are less clear. Our results can serve as a guideline for identifying areas where anthropogenic processes of land use and land cover changes and extremes climatic events synergize, to better guide management under a changing environment

Environmental problems are typically produced by the interactions of complex natural and human systems and can entail far-reaching and sometimes irreversible consequences. Their study is characterized by the existence of incomplete knowledge and high levels of uncertainty and, in some cases, ambiguousness in the definition of the problem itself and its boundaries. These so-called wicked problems openly challenge the traditional disciplinary approach commonly used in natural and social sciences and call for the development of interdisciplinary, integrated research, as well as for innovative methods and frameworks.

Recent IPCC reports suggest that the world is getting warmer. Consequently, the concentration of atmospheric water vapor, which determines the water for precipitation, is substantially increasing in accordance with the Clausius-Clapeyron (CC) relationship, which establishes that water vapor in the atmosphere increases at a rate of 7% per ºC of warming. In this study, we explored the relationship between extreme precipitable water events and temperature over the whole globe, its two hemispheres, and the 5º latitudinal bands by using NCEP/NCAR and MERRA-2 reanalysis data for 1980-2017. Our results indicate that extreme precipitable water events linked to temperature basically follow the CC relationship at temperatures roughly below 5 ºC and the sub-CC relationship for temperatures above ~5 ºC, globally and in both hemispheres. The relationship between extreme precipitable water events and temperature over latitudinal regions is not uniform and varies regionally. Our results further indicate that the increasing rate of extreme precipitable water events is higher in the tropics and mid-latitudes of the southern hemisphere than in the northern hemisphere. This study shows the usefulness of the principle of Clausius-Clapeyron relationship to explain extreme precipitable water events linked to temperature.

In Havana, transport is blamed as a likely source of pollution issues, which is usually supported on arguments referring to a vehicle fleet mainly made of old cars (i.e., most models are American from the 1950s or Russian from the 1980s) with poor technical conditions. Most of the existing studies are based on measurements from passive samplers collected for 24 h, which may not be representative of conditions where pollutant concentrations (particles or gases) fluctuate or are not homogeneous, such as transport-related pollution. The goal of this paper is to explore the transport-generated pollution by examining short-time correlations between traffic flows, pollutant concentrations and meteorological parameters. To do that, statistical relationships among all variables were analyzed, which revealed that PM10, NO2 and SO2 concentration levels are influenced by vehicular traffic, mainly with low-speed winds blowing perpendicular to the street axis. Furthermore, southeast and northeast winds force drag pollutionfrom sources other than traffic. These conclusions depend on the specific conditions of the summer season at the measurement area. A more complete analysis could be conducted when more data becomes available for each season.

The accurate estimation of the amount of global solar radiation potential on the earth’s surface is one of the most important parameters for solar energy investments and long-term climate studies. The most accurate solar radiation data are generally available in some ground stations where they are obtained by using direct measurement. However, the estimation of global solar radiation data can be conducted by some estimation methods in the areas that do not have this information. This study compares and discusses some approaches to identify the most accurate method for daily global solar radiation reaching on a horizontal surface. The comparisons are carried out between some selected conventional empirical methods taken from the related literature, the satellite-based HELIOSAT method and the coupled (hybrid) method which uses both ground data and satellite images. These selected methods have been tested previously and declared most accurate by many researchers for Turkey. The performance results were compared with ground-measured data and all methods were analyzed by using statistical errors in the selected site. According to the last six years of data results, the coupled method is better than the others (except the Angstrom method), with daily difference values (91%) and daily absolute difference values lower than 2.5 MJ m–2 day.

The activities taking place along the coast of the Gulf of Mexico are of great economic importance; however, these activities are potential sources of acid rain precursors. Potentially sensitive receptors to acid deposition in the coastal region of the Gulf of Mexico are lakes, rivers, forests, soils and monuments of cultural heritage. The aim of this study was to evaluate the chemical composition, enrichment factors and trends of wet atmospheric deposition at La Mancha, Veracruz, from 2003 to 2014. The major ions, pH and conductivity were analyzed daily during rainy and dry seasons. The following value ranges of the annual volume weighted mean (VWM) were: pH: 4.78-5.40; SO42–: 16-32 μeq L–1; NO3–: 4-15 μeq L–1, among others. The principal findings were found: (1) acid rain has been present for more than a decade along the coast of the Gulf of Mexico; (2) the non-marine ions in decreasing order were: NO3–, NH4+, Ca+ and SO42–; (3) all of the ions were present in major concentrations during the dry season due to minimal precipitation; (4) in several cases, the value of the pH events was low during the rainy season due to the low presence of chemical species that could favor neutralization; (5) the VWM pH in wet deposition was in the range of 4.78 to 5.40 during the study period (2003-2014), and (6) a significant increasing trend for pH was observed during the entire study period, while an increasing trend occurred from 2003 to 2008 for SO42–, NO3–, K+ and Ca2+, which decreased until 2011 and then increased until 2014.

A 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.

Atmospheric pollution has emerged as a disaster in developing countries like Pakistan. The aim of this study was to observe and analyze the air quality status of the twin cities of Pakistan, Rawalpindi and Islamabad, with a combined population of 15 million. The concentration of criteria pollutants along with CO2 was measured at five different locations within these cities. Sampling was done for 24 h at each location using a mobile air quality monitoring lab. The overall concentrations of SO2, NOX and O3 were found to be within the permissible limits of the US-EPA standards and the National Environmental Quality Standards of Pakistan, with higher PM10 and CO2 concentrations at most locations. The highest concentrations of PM10 were observed at Saddar, Rawalpindi (184 µg m–3), while minimum values were observed at the Blue Area of Islamabad (121 µg m–3). The concentration of CO2 during the study period was found to be high in almost all locations, with Saddar, Rawalpindi, indicating the highest value (409 ppm). The concentrations of CO2 at the Blue Area and the National University of Science and Technology of Islamabad were observed to be as high as 385.3 and 246 ppm, respectively. The behavior of pollutants with different meteorological parameters was also studied. For source identification, backward air trajectories were also generated using the HYSPLIT model.