A review of the distribution of particulate trace elements in urban terrestrial environments and its application to considerations of risk

We review the evolution, state of the art and future lines of research on the sources, transport pathways, and sinks of particulate trace elements in urban terrestrial environments to include the atmosphere, soils, and street and indoor dusts. Such studies reveal reductions in the emissions of some elements of historical concern such as Pb, with interest consequently focusing on other toxic trace elements such as As, Cd, Hg, Zn, and Cu. While establishment of levels of these elements is important in assessing the potential impacts of human society on the urban environment, it is also necessary to apply this knowledge in conjunction with information on the toxicity of those trace elements and the degree of exposure of human receptors to an assessment of whether such contamination represents a real risk to the city’s inhabitants and therefore how this risk can be addressed.     

Electrochemical degradation of chlorophenoxy and chlorobenzoic herbicides in acidic aqueous medium by the peroxi-coagulation method

The degradation of 4-chlorophenoxyacetic acid (4-CPA), 4-chloro-2-methylphenoxyacetic acid (MCPA), 2,4-dichlorophenoxyacetic acid (2,4-D) and 2,4,5-trichlorophenoxyacetic acid (2,4,5-T) as chlorophenoxy herbicides, as well as of 3,6-dichloro-2-methoxybenzoic acid (dicamba) as chlorobenzoic herbicide, has been studied by peroxi-coagulation. This electrochemical method yields a very effective depollution of all compounds in acidic aqueous medium of pH 3.0 working under pH regulation, since they are oxidized with hydroxyl radicals produced from Fenton's reaction between Fe(2+) and H(2)O(2) generated by the corresponding Fe anode and O(2)-diffusion cathode. Their products can then be removed by mineralization or coagulation with the Fe(OH)(3) precipitate formed. Both degradative paths compete at low currents, but coagulation predominates at high currents. The peroxi-coagulation process of dicamba at I>or=300 mA leads to more than 90% of coagulation, being much more efficient than its comparative electro-Fenton treatment with a Pt anode and 1 mM Fe(2+), where only mineralization takes place. For the chlorophenoxy compounds, electro-Fenton gives a slightly lower depollution than peroxi-coagulation, because more easily oxidable products are produced. Oxidation of chlorinated products during peroxi-coagulation is accompanied by the release of chloride ion to the solution. The efficiency of this method decreases with increasing electrolysis time and current. The decay of all herbicides follows a pseudo-first-order reaction, with a similar constant rate for 4-CPA, MCPA, 2,4-D and 2,4,5-T, and a higher value for dicamba.     

Integrating intraseasonal grassland dynamics in cross-scale distribution modeling to support waterbird recovery plans

Despite much discussion about the utility of remote sensing for effective conservation, the inclusion of these technologies in species recovery plans remains largely anecdotal. We developed a modeling approach for the integration of local, spatially measured ecosystem functional dynamics into a species distribution modeling (SDM) framework in which other ecologically relevant factors are modeled separately at broad scales. To illustrate the approach, we incorporated intraseasonal water-vegetation dynamics into a cross-scale SDM for the Common Snipe (Gallinago gallinago), which is highly dependent on water and vegetation dynamics. The Common Snipe is an Iberian grassland waterbird characteristic of European agricultural meadows and a member of one of the most threatened bird guilds. The intraseasonal dynamics of water content of vegetation were measured using the standard deviation of the normalized difference water index time series computed from bimonthly images of the Sentinel-2 satellite. The recovery plan for the Common Snipe in Galicia (northwestern Iberian Peninsula) provided an opportunity to apply our modeling framework. Model accuracy in predicting the species’ distribution at a regional scale (resulting from integration of downscaled climate projections with regional habitat–topographic suitability models) was very high (area under the curve [AUC] of 0.981 and Boyce's index of 0.971). Local water-vegetation dynamic models, based exclusively on Sentinel-2 imagery, were good predictors (AUC of 0.849 and Boyce's index of 0.976). The predictive power improved (AUC of 0.92 and Boyce's index of 0.98) when local model predictions were restricted to areas identified by the continental and regional models as priorities for conservation. Our models also performed well (AUC of 0.90 and Boyce's index of 0.93) when projected to updated water-vegetation conditions. Our modeling framework enabled incorporation of key ecosystem processes closely related to water and carbon cycles while accounting for other factors ecologically relevant to endangered grassland waterbirds across different scales, allowed identification of priority areas for conservation, and provided an opportunity for cost-effective recovery planning by monitoring management effectiveness from space.     

2,4-dichlorophenoxyacetic acid (2,4-D) micropollutant herbicide removing from water using granular and powdered activated carbons: a comparison applied for water treatment and health safety

Abstract

Activated carbons are well-known porous materials as an effective adsorbent used for the removal of emerging contaminants, such as herbicides, which are increasingly present in water bodies. Most water treatment plants, specially in Brazil, are unable to completely remove such contaminants by the conventional process and advanced treatment using activated carbons is required. The aim of this paper was to verify the influence of the activated carbons granulometry and specific surface area on the 2,4-dichlorophenoxyacetic acid (2,4-D) herbicide removal efficiency using distilled-deionized water and filtered water collected from a conventional Water Treatment Plant. Commercial activated carbons samples used in this work were obtained from two different manufacturers. Activated carbons were analyzed by the specific surface area, pore size and volume distribution, nuclear magnetic resonance, infrared and x-ray spectroscopy, moisture, volatile matter and ash contents. Batch adsorption isotherms experiments were used and performed by Langmuir and Freundlich models. Granular and powdered activated carbons removed over 99% of 2,4-D in distilled water and near to 99% using filtered water. The activated carbons evaluated in this work presented high performance and played a key role in water treatment by removing 2,4-D herbicide, ensuring the protection of human health and the ecosystem.     

Bioelectrochemical anaerobic sewage treatment technology for Arctic communities

This study describes a novel wastewater treatment technology suitable for small remote northern communities. The technology is based on an enhanced biodegradation of organic carbon through a combination of anaerobic methanogenic and microbial electrochemical (bioelectrochemical) degradation processes leading to biomethane production. The microbial electrochemical degradation is achieved in a membraneless flow-through bioanode–biocathode setup operating at an applied voltage below the water electrolysis threshold. Laboratory wastewater treatment tests conducted through a broad range of mesophilic and psychrophilic temperatures (5–23 °C) using synthetic wastewater showed a biochemical oxygen demand (BOD₅) removal efficiency of 90–97% and an effluent BOD₅ concentration as low as 7 mg L^?1. An electricity consumption of 0.6 kWh kg^?1 of chemical oxygen demand (COD) removed was observed. Low energy consumption coupled with enhanced methane production led to a net positive energy balance in the bioelectrochemical treatment system.     

Addressing social attitudes toward lethal control of wildlife in national parks

The extraordinary population growth of certain ungulate species is increasingly a concern in agroforestry areas because overabundance may negatively affect natural environments and human livelihoods. However, society may have negative perceptions of killing wildlife to reduce their numbers and mitigate damage. We used an online survey that included a choice experiment to determine Spanish citizens’ (n = 190) preferences toward wildlife population control measures related to negative effects of ungulate overabundance (negative impacts on vegetation and other wildlife species and disease transmission to livestock) in 2 agroforestry national parks in Spain. We used latent-class and willingness-to-pay in space models to analyze survey results. Two percent of respondents thought a national park should have no human intervention even if lack of management may cause environmental degradation, whereas 95% of respondents favored efforts to reduce damage caused by overabundant ungulate species. We estimated human well-being losses of survey respondents when sustainable effects of deer overabundance on the environment became unsustainable effects and well-being gains when sustainable effects transitioned to no visible effects. We found that the type of wildlife-control program was a very relevant issue for the respondents; indirect control in which killing was avoided was the preferred action. Sixty-six percent of respondents agreed with the option of hunters paying for culling animals to reduce ungulate impacts rather than management cost coming out of taxes, whereas 19% of respondents were against this option and willing to pay for other solutions in national parks. Our results suggest that killing wildlife in national parks could be a socially acceptable tool to manage overabundance problems in certain contexts, but it could also generate social conflicts.     

Accounting for multiple testing in the analysis of spatio-temporal environmental data

The statistical analysis of environmental data from remote sensing and Earth system simulations often entails the analysis of gridded spatio-temporal data, with a hypothesis test being performed for each grid cell. When the whole image or a set of grid cells are analyzed for a global effect, the problem of multiple testing arises. When no global effect is present, we expect $$ \alpha $$% of all grid cells to be false positives, and spatially autocorrelated data can give rise to clustered spurious rejections that can be misleading in an analysis of spatial patterns. In this work, we review standard solutions for the multiple testing problem and apply them to spatio-temporal environmental data. These solutions are independent of the test statistic, and any test statistic can be used (e.g., tests for trends or change points in time series). Additionally, we introduce permutation methods and show that they have more statistical power. Real-world data are used to provide examples of the analysis, and the performance of each method is assessed in a simulation study. Unlike other simulation studies, our study compares the statistical power of the presented methods in a comprehensive simulation study. In conclusion, we present several statistically rigorous methods for analyzing spatio-temporal environmental data and controlling the false positives. These methods allow the use of any test statistic in a wide range of applications in environmental sciences and remote sensing.     

墨西哥为实现2025年温室气体减排目标在电力生产中使用可再生能源

本研究介绍了到2025年时墨西哥电力生产的4种设想前景.第一种设想前景的关键是使用石油产品特别是燃料油,这代表了墨西哥过去能源政策的足迹.第二种设想前景是优先使用天然气,这反映了由于能源领域改革而于20世纪90年代中期形成的能源消费型.第三种设想前景认为,从技术的和经济的角度看来,大量使用可再生能源是可行的.第四种设想前景认为,目前和相当一段时间内要使用能源改革中形成的天然气技术,而在2007年以后,才开始大量使用可再生能源.这4种设想前景都依据温室气体(GHG)和酸雨前身气体(ARPG)推算到2025年.