层次分析法在环境风险评价中的应用

调查化工区周围敏感目标及突发性污染事故类型，根据层次分析法原理，建立层次结构模型，构造两两比较判断矩阵，计算矩阵的最大特征值及对应的特征向量，做出层次排序及一致性检验，判断污染事故类型的重要性。     

草地畜牧业雪灾脆弱性评价 --以内蒙古牧区为例

从综合减灾和区域可持续发展的角度，建立了雪灾脆弱性评价指标体系及评价模型，并从雪灾区域孕灾环境敏感性以及区域畜牧业承灾体对雪灾的适应性两方面，对内蒙古雪灾脆弱性进行了评价。研究结果表明：内蒙古牧区雪灾脆弱性存在若明显的地域差异，中西部牧区比东部牧区脆弱性大，北部牧区比南部牧区脆弱性大，并且近10年来脆弱性提高的旗县明显增多，草地季节性干旱、北方干旱化以及草场超载过牧、退化加剧是畜牧业雪灾脆弱性呈增加趋势的直接原因。     

The role of the rural settlements in the Brazilian savanna deforesting process

Although the drivers of deforestation in Brazil are relatively well known, there is still limited understanding of the role of family farm-based rural settlements in land cover changes, particularly in the Brazilian savanna. This research aims to identify land use patterns within rural settlements and examine how they are influenced by regional dynamics. The study is based on GIS techniques and satellite image classification (Landsat 5-TM and RapidEye imagery), combined with geo-referenced fieldwork data in three different regions of the State of Goiás. The results reveal that the deforestation arrangement within the studied rural settlements is very similar to the deforestation found in the surrounding regions. As a positive outcome, the rural settlements have a higher share of remnant vegetation when compared to the surrounding areas, but this is still concentrated within legal reserves. We conclude that the changing patterns of rural settlement land cover are highly influenced by regional dynamics.     

Source attribution and quantification of benzene event emissions in a Houston ship channel community based on real-time mobile monitoring of ambient air

A mobile laboratory equipped with a proton transfer reaction mass spectrometer (PTR-MS) operated in Galena Park, Texas, near the Houston Ship Channel during the Benzene and other Toxics Exposure Study (BEE-TEX). The mobile laboratory measured transient peaks of benzene of up to 37 ppb_v in the afternoon and evening of February 19, 2015. Plume reconstruction and source attribution were performed using the four-dimensional (4D) variational data assimilation technique and a three-dimensional (3D) micro-scale forward and adjoint air quality model based on mobile PTR-MS data and nearby stationary wind measurements at the Galena Park Continuous Air Monitoring Station (CAMS). The results of inverse modeling indicate that significant pipeline emissions of benzene may at least partly explain the ambient concentration peaks observed in Galena Park during BEE-TEX. Total pipeline emissions of benzene inferred within the 16-km² model domain exceeded point source emissions by roughly a factor of 2 during the observational episode. Besides pipeline leaks, the model also inferred significant benzene emissions from marine, railcar, and tank truck loading/unloading facilities, consistent with the presence of a tanker and barges in the Kinder Morgan port terminal during the afternoon and evening of February 19. Total domain emissions of benzene exceeded corresponding 2011 National Emissions Inventory (NEI) estimates by a factor of 2–6.

Implications:?Port operations involving petrochemicals may significantly increase emissions of air toxics from the transfer and storage of materials. Pipeline leaks, in particular, can lead to sporadic emissions greater than in emission inventories, resulting in higher ambient concentrations than are sampled by the existing monitoring network. The use of updated methods for ambient monitoring and source attribution in real time should be encouraged as an alternative to expanding the conventional monitoring network.     

Considering the needs of indigenous and local populations in conservation programs

Local rural and indigenous communities have assumed increasing responsibility for conservation within and between areas buffering the impacts of agricultural or resource‐extraction zones and protected areas. Empowering local communities as central partners in conservation and climate‐change mitigation has allowed many people to gain access to land and citizenship rights but has provided limited improvements in access to social services and economic opportunities even as expectation about their role as environmental stewards grows. These expectations, however, are inconsistent with reality. We conducted multiple field studies in Brazil since the mid‐1980s to illustrate the discrepancies between conservation programs and local conditions and expectations. We suggest that public policies and conservation programs should not delegate responsibility for managing protected areas to local and indigenous communities without considering local needs and expectations and locals’ attitudes toward conservation. In other words, behavior that maintains or improves the environment should not be treated as traditional based on the expectations of outsiders. Framing local populations as traditional environmentalists creates contradictions and frustrations for local populations and for conservation professionals and policy makers.     

Guarana improves behavior and inflammatory alterations triggered by methylmercury exposure: an in vivo fruit fly and in vitro neural cells study

Environmental Science and Pollution Research - Methylmercury (MeHg) is a well-known environmental pollutant associated with neurological and developmental deficits in animals and humans. However,...     

Modeling a spatially restricted distribution in the Neotropics: How the size of calibration area affects the performance of five presence-only methods

We here examine species distribution models for a Neotropical anuran restricted to ombrophilous areas in the Brazilian Atlantic Forest hotspot. We extend the known occurrence for the treefrog Hypsiboas bischoffi (Anura: Hylidae) through GPS field surveys and use five modeling methods (BIOCLIM, DOMAIN, OM-GARP, SVM, and MAXENT) and selected bioclimatic and topographic variables to model the species distribution. Models were first trained using two calibration areas: the Brazilian Atlantic Forest (BAF) and the whole of South America (SA). All modeling methods showed good levels of predictive power and accuracy with mean AUC ranging from 0.77 (BIOCLIM/BAF) to 0.99 (MAXENT/SA). MAXENT and SVM were the most accurate presence-only methods among those tested here. All but the SVM models calibrated with SA predicted larger distribution areas when compared to models calibrated in BAF. OM-GARP dramatically overpredicted the species distribution for the model calibrated in SA, with a predicted area around 10⁶ km² larger than predicted by other SDMs. With increased calibration area (and environmental space), OM-GARP predictions followed changes in the environmental space associated with the increased calibration area, while MAXENT models were more consistent across calibration areas. MAXENT was the only method that retrieved consistent predictions across calibration areas, while allowing for some overprediction, a result that may be relevant for modeling the distribution of other spatially restricted organisms.