Assessment of RegCM4 simulated inter-annual variability and daily-scale statistics of temperature and precipitation over Mexico

The skill of a regional climate model (RegCM4) in capturing the mean patterns, interannual variability and extreme statistics of daily-scale temperature and precipitation events over Mexico is assessed through a comparison of observations and a 27-year long simulation driven by reanalyses of observations covering the Central America CORDEX domain. The analysis also includes the simulation of tropical cyclones. It is found that RegCM4 reproduces adequately the mean spatial patterns of seasonal precipitation and temperature, along with the associated interannual variability characteristics. The main model bias is an overestimation of precipitation in mountainous regions. The 5 and 95 percentiles of daily temperature, as well as the maximum dry spell length are realistically simulated. The simulated distribution of precipitation events as well as the 95 percentile of precipitation shows a wet bias in topographically complex regions. Based on a simple detection method, the model produces realistic tropical cyclone distributions even at its relatively coarse resolution (dx = 50 km), although the number of cyclone days is underestimated over the Pacific and somewhat overestimated over the Atlantic and Caribbean basins. Overall, it is assessed that the performance of RegCM4 over Mexico is of sufficient quality to study not only mean precipitation and temperature patterns, but also higher order climate statistics.     

The Water Framework Directive: Can more information be extracted from groundwater data? A case study of Seewinkel,Burgenland, eastern Austria

Water protection is one of the most important goals in environmental protection. The Clean Water Act in the USA and the Water Framework Directive (WFD) in Europe are the legal frameworks to facilitate the achievement of this goal. The question is raised of whether more information can be extracted from WFD-related groundwater data. To answer it, a methodology has been developed that is easy to use and could be implemented into official practice. A case study is presented in which the groundwater data of a sodic area in Austria (Seewinkel) is assessed. Eighteen parameters in groundwater sampled from 23 wells (1991–2011) were analyzed. With basic statistics, trend-, cluster-, Wilks’ λ and spatial sampling density analysis, local phosphorus and boron phenomena were described, along with the determining role of sulphate, groundwater flow, and the oxygen gradient in the area. As a final step, the spatial sampling density was determined. Regarding the current set of parameters, all the sampling sites are necessary and only in the case of certain parameters (Ca²⁺, Mg²⁺, K⁺, NO₃ ^?, pH) could one sampling site be abandoned. The methodology applied brings a new perspective to exploring groundwater data collected according to the requirements of the WFD.     

Geophysical exploration on the subsurface geology of La Garrotxa monogenetic volcanic field (NE Iberian Peninsula)

We applied self-potential (SP) and electrical resistivity tomography (ERT) to the exploration of the uppermost part of the substrate geology and shallow structure of La Garrotxa monogenetic volcanic field, part of the European Neogene–Quaternary volcanic province. The aim of the study was to improve knowledge of the shallowest part of the feeding system of these monogenetic volcanoes and of its relationship with the subsurface geology. This study complements previous geophysical studies carried out at a less detailed scale and aimed at identifying deeper structures, and together will constitute the basis to establish volcanic susceptibility in La Garrotxa. SP study complemented previous smaller-scale studies and targeted key areas where ERT could be conducted. The main new results include the generation of resistivity models identifying dykes and faults associated with several monogenetic cones. The combined results confirm that shallow tectonics controlling the distribution of the foci of eruptive activity in this volcanic zone mainly correspond to NNW–SSE and accessorily by NNE–SSW Neogene extensional fissures and faults and concretely show the associated magmatic intrusions. These structures coincide with the deeper ones identified in previous studies, and show that previous Alpine tectonic structures played no apparent role in controlling the loci of this volcanism. Moreover, the results obtained show that the changes in eruption dynamics occurring at different vents located at relatively short distances in this volcanic area are controlled by shallow stratigraphical, structural and hydrogeological differences underneath these monogenetic volcanoes.     

Relationship between Hypoxia and Macrobenthic Production in Chesapeake Bay

Human development has degraded Chesapeake Bay's health, resulting in an increase in the extent and severity of hypoxia (≤2 mg O₂ l^-1). The Bay's hypoxic zones have an adverse effect on both community structure and secondary production of macrobenthos. From 1996 to 2004, the effect of hypoxia on macrobenthic production was assessed in Chesapeake Bay and its three main tributaries (Potomac, Rappahannock, and York Rivers). Each year, in the summer (late July???early September), 25 random samples of the benthic macrofauna were collected from each system, and macrobenthic production in the polyhaline and mesohaline regions was estimated using Edgar's allometric equation. Fluctuations in macrobenthic production were significantly correlated with dissolved oxygen. Macrobenthic production was 90 % lower during hypoxia relative to normoxia. As a result, there was a biomass loss of ~7,320–13,200 metric tons C over an area of 7,720 km², which is estimated to equate to a 20 % to 35 % displacement of the Bay's macrobenthic productivity during the summer. While higher consumers may benefit from easy access to stressed prey in some areas, the large spatial and temporal extent of seasonal hypoxia limits higher trophic level transfer, via the inhibition of macrobenthic production. Such a massive loss of macrobenthic production would be detrimental to the overall health of the Bay, as it comes at a time when epibenthic and demersal predators have high-energy demands.     

Effect of the injection of pure oxygen into a membrane bioreactor on the elimination of bisphenol A

The effect of the injection of pure oxygen instead of air in a membrane bioreactor for the elimination of bisphenol A is investigated. A dynamic experiment was developed in a pilot plant where the aerobic reactor was continuously spiked with 1 mg L^?1 of bisphenol A. Air was injected for 10 days and then pure oxygen was injected for another 10 days. The bisphenol A concentration was determined in aqueous phases and activated sludge using simple and sensitive analytical methods based on different extraction procedures and liquid chromatography tandem mass spectrometry analysis. Enzymatic activity was also determined and toxicity tests were performed to discard that the spiked bisphenol A concentration could negatively affect the microorganisms in the bioreactor and, thus, the membrane bioreactor performance. The effluent bisphenol A concentration increased up to 0.26 mg L^?1 after 4 days in the air injection treatment, and up to 0.48 mg L^?1 after only 12 h in the oxygen injection treatment. In both cases, this was followed by a decrease in concentration despite the continuous spiking of bisphenol A into the bioreactor. In presence of pure oxygen, bisphenol A concentration reached background levels (below the limit of quantification) after 5 days. In contrast, when using air a total of 10 days were required to reach background levels. The injection of pure oxygen instead of air is an important innovation in wastewater treatment, allowing permanent elimination of organic contaminants, avoiding their return to the environment and ensuring the safety of water.     

A geochemical and 3D-geometry geophysical survey to assess artificial groundwater recharge potential in the Pacific coast of Baja California,Mexico

A geophysical and geochemical study was carried out in the Maneadero aquifer, Baja California, Mexico, with the aim of identifying potential recharge locations for reclaimed water (RW). This coastal aquifer shows a significant decline in water quality, both as a result of salinization and the pollution by nitrates. Total dissolved solids (TDS) in an extreme case increased from 4 g l^?1 in 2000 to 27 g l^?1 in 2011. Nitrate as N–NO₃, reaches 46 mg l^?1. Based on their geochemistry and location, four water-quality zones are identified: (a) fresh water with TDS ≈ 1 g l^?1 in the upper creeks, (b) mixture between seawater and freshwater in the coast-proximal sections, (c) water significantly enriched in nitrate below and adjacent to the town of Maneadero, and (d) brackish water with no signs of current interaction with freshwater. The 3D geophysics identifies the influence of modern recharge areas and also buried flow-paths down to at least 30 m depth. The locations best suitable for aquifer recharge are those with equal or higher TDS concentrations (>2.5 g l^?1) than RW, which are located at the brackish water zone and/or at the coastal limits of the mixing zones.     

More accurate,calibrated bootstrap confidence intervals for estimating the correlation between two time series

Estimation of Pearson’s correlation coefficient between two time series, in the evaluation of the influences of one time-dependent variable on another, is an often used statistical method in climate sciences. Data properties common to climate time series, namely non-normal distributional shape, serial correlation, and small data sizes, call for advanced, robust methods to estimate accurate confidence intervals to support the correlation point estimate. Bootstrap confidence intervals are estimated in the Fortran 90 program PearsonT (Mudelsee, Math Geol 35(6):651–665, 2003), where the main intention is to obtain accurate confidence intervals for correlation coefficients between two time series by taking the serial dependence of the data-generating process into account. However, Monte Carlo experiments show that the coverage accuracy of the confidence intervals for smaller data sizes can be substantially improved. In the present paper, the existing program is adapted into a new version, called PearsonT3, by calibrating the confidence interval to increase the coverage accuracy. Calibration is a bootstrap resampling technique that performs a second bootstrap loop (it resamples from the bootstrap resamples). It offers, like the non-calibrated bootstrap confidence intervals, robustness against the data distribution. Pairwise moving block bootstrap resampling is used to preserve the serial dependence of both time series. The calibration is applied to standard error-based bootstrap Student’s $t$ confidence intervals. The performance of the calibrated confidence interval is examined with Monte Carlo simulations and compared with the performance of confidence intervals without calibration. The coverage accuracy is evidently better for the calibrated confidence intervals where the coverage error is acceptably small already (i.e., within a few percentage points) for data sizes as small as 20.     

The state of the environment in Mexico

The present work evaluates the state of the environment in Mexico based on indicators of the present status of the country’s natural resource management, social and economical conditions and anthropogenic modifications. The Mexican environment is interpreted as a spatially open system having a historical character that is essentially determined by the continual interaction between nature, society and economy. The landscape approach is followed, considering as units of territorial analysis each one of the 145 biophysical environmental units included in the national physiographic regionalization. The assessment of 16 indicators for each biophysical environmental unit was made considering their regional environmental integrity problems, the degree of disarticulation of their structure and function, and the alteration of their territorial structure, all of which determine whether or not they accomplish their environmental functions and achieve environmental stability. The classification of the state of the environment included 5 categories in 8 combinations represented in the map of the state of the environment in Mexico for the year 2008. The map shows that nearly 47.10% of the country’s surface has an environmental status ranging between unstable and critical, the problematic areas being mostly concentrated in the southeast and center of the national territory.     

Dispersion modeling of air pollutants in the atmosphere: a review

Modeling of dispersion of air pollutants in the atmosphere is one of the most important and challenging scientific problems. There are several natural and anthropogenic events where passive or chemically active compounds are emitted into the atmosphere. The effect of these chemical species can have serious impacts on our environment and human health. Modeling the dispersion of air pollutants can predict this effect. Therefore, development of various model strategies is a key element for the governmental and scientific communities. We provide here a brief review on the mathematical modeling of the dispersion of air pollutants in the atmosphere. We discuss the advantages and drawbacks of several model tools and strategies, namely Gaussian, Lagrangian, Eulerian and CFD models. We especially focus on several recent advances in this multidisciplinary research field, like parallel computing using graphical processing units, or adaptive mesh refinement.