A comparative study of US EPA 1996 and 1999 emission inventories in the west Gulf of Mexico coast region, USA

Emission inventory is one of the required inputs to air quality models. To assist in the urban and regional modeling efforts, United States Environmental Protection Agency (EPA) has compiled a National Emission Inventory (NEI) for criterion pollutants, and the precursors of ozone and particulate matter (PM). In December 2002, EPA released the 1999 NEI estimates (NEI99), which represent the most recent national emission data. However, the data sets are not in model-ready format for air quality simulations. This present work converts the NEI99 Final Version 2 data sets into Inventory Data Analyzer (IDA) format and processes the data using the Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system to generate a gridded emission inventory in a domain covering the west Gulf Coast Region, USA. The spatial and diurnal emission characteristics of the gridded emission inventories are then assessed and compared with those of the National Emission Trend 1996 (NET96). The NEI99 database contains more complete emission records in both area and point sources. It is also found that NEI99 data exhibit greater emissions with respect to point and mobile sources but smaller emissions with respect to area sources when compared to the corresponding gridded NET96 data in the same study domain. The most distinct differences between the NEI99 and NET96 databases are CO emission of mobile sources, SO2 emissions of point sources, and VOC/PM/NH3/NOx emissions of area and non-road sources. The gridded NEI99 data show low VOC/NOx ratios (<2-5) in the urban areas of the study domain.     

“We cannot let this happen again”: reversing UK flood policy in response to the Somerset Levels floods, 2014

The Multiple Streams Framework offers a theoretical account of how policy proposals move from latent possibilities to becoming favored for implementation. We apply this framework in the context of the policy response to the 2013–2014 flooding of the Somerset Levels and Moors. Stakeholder interviews and analysis of news media coverage evidence the way in which a specific policy option that had fallen out of favor with the national Environment Agency – dredging – came to the fore and was eventually adopted during the period in which the conjunction of problem, policy, and political pressures came to a head. Local political activists mobilized a wider campaign with the help of social media and capitalized on national political sensitivities to successfully promote dredging. What is less clear is the longevity of the policy reversal, given funding constraints.     

Trait‐based prediction of extinction risk of small‐bodied freshwater fishes

Small body size is generally correlated with r‐selected life‐history traits, including early maturation, short‐generation times, and rapid growth rates, that result in high population turnover and a reduced risk of extinction. Unlike other classes of vertebrates, however, small freshwater fishes appear to have an equal or greater risk of extinction than large fishes. We explored whether particular traits explain the International Union for Conservation of Nature (IUCN) Red List conservation status of small‐bodied freshwater fishes from 4 temperate river basins: Murray‐Darling, Australia; Danube, Europe; Mississippi‐Missouri, North America; and the Rio Grande, North America. Twenty‐three ecological and life‐history traits were collated for all 171 freshwater fishes of ≤120 mm total length. We used generalized linear mixed‐effects models to assess which combination of the 23 traits best explained whether a species was threatened or not threatened. We used the best models to predict the probability of 29 unclassified species being listed as threatened. With and without controlling for phylogeny at the family level, small body size—among small‐bodied species—was the most influential trait correlated with threatened species listings. The k‐folds cross‐validation demonstrated that body size and a random effect structure that included family predicted the threat status with an accuracy of 78% (SE 0.5). We identified 10 species likely to be threatened that are not listed as such on the IUCN Red List. Small body size is not a trait that provides universal resistance to extinction, particularly for vertebrates inhabiting environments affected by extreme habitat loss and fragmentation. We hypothesize that this is because small‐bodied species have smaller home ranges, lower dispersal capabilities, and heightened ecological specialization relative to larger vertebrates. Trait data and further model development are needed to predict the IUCN conservation status of the over 11,000 unclassified freshwater fishes, especially those under threat from proposed dam construction in the world's most biodiverse river basins.     

Beyond ‘just’ flood risk management: the potential for—and limits to—alleviating flood disadvantage

Regional Environmental Change - The threat of flooding poses a considerable challenge for justice. Not only are more citizens becoming exposed to risk, but they are expected to play increasingly...     

Cautioning against overemphasis of normative constructs in conservation decision making

Questions around how to conserve nature are increasingly leading to dissonance in conservation planning and action. While science can assist in unraveling the nature of conservation challenges, conservation responses rely heavily on normative positions and constructs to order actions, aid interpretations, and provide motivation. However, problems can arise when norms are mistaken for science or when they stymy scientific rigor. To highlight these potential pitfalls, we used the ethics-based tool of argument analysis to assess a controversial conservation intervention, the Pelorus Island Goat Control Program. The program proponents' argument for restorative justice was unsound because it relied on weak logical construction overly entrenched in normative assumptions. Overreliance on normative constructs, particularly the invocation of tragedy, creates a sense of urgency that can subvert scientific and ethical integrity, obscure values and assumptions, and increase the propensity for flawed logic. This example demonstrates how the same constructs that drive biodiversity conservation can also drive poor decision making, spur public backlash, and justify poor animal welfare outcomes. To provide clarity, a decision-making flowchart we devised demonstrates how values, norms, and ethics influence one another. We recommend practitioners follow 3 key points to improve decision making: be aware of values, as well as normative constructs and ethical theories that those values inform; be mindful of overreliance on either normative constructs or ethics when deciding action is justified; and be logically sound and transparent when building justifications. We also recommend 5 key attributes that practitioners should be attentive to when making conservation decisions: clarity, transparency, scientific integrity, adaptiveness, and compassion. Greater attention to the role of norms in decision making will improve conservation outcomes and garner greater public support for actions.     

Uptake and Engagement of Activities to Promote Native Species in Private Gardens

Environmental Management - Activities undertaken by householders in their gardens have huge potential to enhance city-wide biodiversity, but programs aimed at activating householders require an...     

Hazard property classification of waste according to the recent propositions of the EC using different methods

Hazard classification of waste is a necessity, but the hazard properties (named “H” and soon “HP”) are still not all defined in a practical and operational manner at EU level. Following discussion of subsequent draft proposals from the Commission there is still no final decision. Methods to implement the proposals have recently been proposed: tests methods for physical risks, test batteries for aquatic and terrestrial ecotoxicity, an analytical package for exhaustive determination of organic substances and mineral elements, surrogate methods for the speciation of mineral elements in mineral substances in waste, and calculation methods for human toxicity and ecotoxicity with M factors.In this paper the different proposed methods have been applied to a large assortment of solid and liquid wastes (>1 0 0).Data for 45 wastes – documented with extensive chemical analysis and flammability test – were assessed in terms of the different HP criteria and results were compared to LoW for lack of an independent classification. For most waste streams the classification matches with the designation provided in the LoW. This indicates that the criteria used by LoW are similar to the HP limit values.This data set showed HP 14 ‘Ecotoxic chronic’ is the most discriminating HP. All wastes classified as acute ecotoxic are also chronic ecotoxic and the assessment of acute ecotoxicity separately is therefore not needed. The high number of HP 14 classified wastes is due to the very low limit values when stringent M factors are applied to total concentrations (worst case method). With M factor set to 1 the classification method is not sufficiently discriminating between hazardous and non-hazardous materials. The second most frequent hazard is HP 7 ‘Carcinogenic’. The third most frequent hazard is HP 10 ‘Toxic for reproduction’ and the fourth most frequent hazard is HP 4 “Irritant – skin irritation and eye damage”. In a stepwise approach, it seems relevant to assess HP 14 first, then, if the waste is not classified as hazardous, to assess subsequently HP 7, HP 10 and HP 4, and then if still not classified as hazardous, to assess the remaining properties.The elements triggering the HP 14 classification in order of importance are Zn, Cu, Pb, Cr, Cd and Hg. Progress in the speciation of Zn and Cu is essential for HP 14. Organics were quantified by the proposed method (AFNOR XP X30-489) and need no speciation. Organics can contribute significantly to intrinsic toxicity in many waste materials, but they are only of minor importance for the assessment of HP 14 as the metal concentrations are the main HP 14 classifiers. Organic compounds are however responsible for other toxicological characteristics (hormone disturbance, genotoxicity, reprotoxicity…) and shall be taken into account when the waste is not HP 14 classified.     

Removal of hexavalent chromium upon interaction with biochar under acidic conditions: mechanistic insights and application

Environmental Science and Pollution Research - Chromium pollution of soil and water is a serious environmental concern due to potential carcinogenicity of hexavalent chromium [Cr(VI)] when...     

A hierarchical Bayesian model for forecasting state-level corn yield

Historically, the National Agricultural Statistics Service crop forecasts and estimates have been determined by a group of commodity experts called the Agricultural Statistics Board (ASB). The corn yield forecasts for the “speculative region,” ten states that account for approximately 85 % of corn production, are based on two sets of monthly surveys, a farmer interview survey and a field measurement survey. The members of the ASB subjectively determine a forecast on the basis of a discussion of the survey data and auxiliary information about weather, average planting dates, and crop maturity. The ASB uses an iterative procedure, where initial state estimates are adjusted so that the weighted sum of the final state estimates is equal to a previously-determined estimate for the speculative region. Deficiencies of the highly subjective ASB process are lack of reproducibility and a measure of uncertainty. This paper describes the use of Bayesian methods to model the ASB process in a way that leads to objective forecasts and estimates of the corn yield. First, we use small area estimation techniques to obtain state-level forecasts. Second, we describe a way to adjust the state forecasts so that the weighted sum of the state forecasts is equal to a previously-determined regional forecast. We use several diagnostic techniques to assess the goodness of fit of various models and their competitors. We use Markov chain Monte Carlo methods to fit the models to both historic and current data from the two monthly surveys. Our results show that our methodology can provide reasonable and objective forecasts of corn yields for states in the speculative region.