Air pollutant concentrations near three Texas roadways,Part I: Ultrafine particles

Vehicular emitted air pollutant concentrations were studied near three types of roadways in Austin, Texas: (1) State Highway 71 (SH-71), a heavily traveled arterial highway dominated by passenger vehicles; (2) Interstate 35 (I-35), a limited access highway north of Austin in Georgetown; and (3) Farm to Market Road 973 (FM-973), a heavily traveled surface roadway dominated by truck traffic. Air pollutants examined include carbon monoxide (CO), oxides of nitrogen (NO_x), and carbonyl species in the gas-phase. In the particle phase, ultrafine particle (UFP) concentrations (diameter < 100 nm), fine particulate matter (PM_2.5, diameter < 2.5 μm) mass and carbon content and several particle-bound organics were examined. All roadways had an upwind stationary sampling location, one or two fixed downwind sample locations and a mobile monitoring platform that characterized pollutant concentrations fall-off with increased distance from the roadways. Data reported in this paper focus on UFP while other pollutants and near-roadway chemical processes are examined in a companion paper. Traffic volume, especially heavy-duty traffic, wind speed, and proximity to the road were found to be the most important factors determining UFP concentrations near the roadways. Since wind directions were not consistent during the sampling periods, distances along wind trajectories from the roadway to the sampling points were used to study the decay characteristics of UFPs. Under perpendicular wind conditions, for all studied roadway types, particle number concentrations increased dramatically moving from the upwind side to the downwind side. The elevated particle number concentrations decay exponentially with increasing distances from the roadway with sharp concentration gradients observed within 100–150 m, similar to previously reported studies. A single exponential decay curve was found to fit the data collected from all three roadways very well under perpendicular wind conditions. No consistent pattern was observed for UFPs under parallel wind conditions. However, regardless of wind conditions, particle concentrations returned to background levels within a few hundred meters of the roadway. Within measured UFP size ranges, smaller particles (6–25 nm) decayed faster than larger ones (100–300 nm). Similar decay rates were observed among UFP number, surface, and volume.     

Economic assessment of managing processionary moth in pine forests: a case-study in Portugal

This paper assesses the private and social profitability of current strategies for managing processionary moth (Thaumetopoea pityocampa) in Portuguese pine forests, looking at economic and environmental costs and benefits. Costs include the expenses for forest treatment and the social costs of threats to human health (dermatitis amongst others); benefits are assessed in terms of both revenue and social benefits such as carbon fixation and recreation. The evaluation was done using Cost Benefit Analysis (CBA) as an analytical framework. While this tool is currently applied to forest and environmental assessment and specific applications to pest management strategies are to be found in agricultural economics, rather few attempts have been made in the field of forest pest management. In order to assess and compare with--without options, a case-study was analysed for the Setúbal Peninsula, south of Lisbon, an area where extensive stands of maritime pine (Pinus pinaster) grow. The exercise has shown that CBA can be a valuable tool for assessing the economic and social profitability of pest management. The results demonstrate that the loss of revenues in the no-management option is not sufficient to make pest management profitable for private forest owners in the short-term. Conversely, a social profit is gained as pest management minimizes health risks for humans and avoids possible recreational losses.     

The influence of use-related,environmental, and managerial factors on soil loss from recreational trails

Recreational uses of unsurfaced trails inevitably result in their degradation, with the type and extent of resource impact influenced by factors such as soil texture, topography, climate, trail design and maintenance, and type and amount of use. Of particular concern, the loss of soil through erosion is generally considered a significant and irreversible form of trail impact. This research investigated the influence of several use-related, environmental, and managerial factors on soil loss on recreational trails and roads at Big South Fork National River and Recreation Area, a unit of the U.S. National Park Service. Regression modeling revealed that trail position, trail slope alignment angle, grade, water drainage, and type of use are significant determinants of soil loss. The introduction of individual and groups of variables into a series of regression models provides improved understanding and insights regarding the relative influence of these variables, informing the selection of more effective trail management actions. Study results suggest that trail erosion can be minimized by avoiding “fall-line” alignments, steep grades, and valley-bottom alignments near streams, installing and maintaining adequate densities of tread drainage features, applying gravel to harden treads, and reducing horse and all-terrain vehicle use or restricting them to more resistant routes.     

Review of Agri-Environment Indexes and Stewardship Payments

Agri-environment programs aim to secure environmental and social stewardship services through payments to farmers. A critical component of many agri-environment programs is an agri-environment index (AEI) used to quantify benefits and target investments. An AEI will typically comprise multiple indicators, which are weighted and combined using a utility function, to measure the benefit of investment options (e.g., projects, farms, regions). This article presents a review of AEIs with 11 case studies from agri-environment programs in the United States, Australia, and the United Kingdom. We identify a generic procedure used to define AEIs and explore the implications of alternative methodological approaches. We conclude that AEIs have become an extremely important policy instrument and make suggestions for their improvement.     

Conflicts between stakeholder groups affecting the ecology and economy of the Segara Anakan region

This study analyses how the conflict potential between different stakeholder groups is affecting the ecology and economy of the Segara Anakan region, a mangrove-fringed lagoon in central Java, Indonesia. The lagoon’s increasing sedimentation/silting up and the area’s expanding population has led to various interest groups conflicting with one another over how the resources of the lagoon and its surrounding area are to be utilized. Conflicts arise between occupational and ethnic groups in the lagoon’s bordering villages in the context of a transformation from fisheries to wetland agriculture. Land and mangrove use is therefore a cause for conflict between multiple groups, including Javanese fishermen, Sundanese farmers from Central and West Java and external shrimp farm owners. A result of the “Segara Anakan Development Project”—an 8-year undertaking that began in 1996—is that the lagoon was frequently dredged. Due to the dredging and resulting contamination of the land, a regional clash was triggered between Sundanese farmers and Javanese fishers. Our study reveals that the conflict potential between the various interest groups in the Segara Anakan Lagoon area could be reduced if the scarcity of natural resources were alleviated. Religious aspects also play a large role in marine resource utilization. Recognizing that the human utilization of natural resources is strongly symbolic and thereby culturally defined, we unravel the resource conflicts in our study area and offer some strategic approaches towards more sustainable outcomes.     

A fuzzy multi-attribute model for risk evaluation in workplaces

Risk assessment constitutes a critical phase of the safety management process. It basically consists of evaluating the risks involved in the execution of working activities, so as to provide the managers with information suitable to address intervention measures. The most important activity in risk assessment is the risk evaluation task but, despite its importance, national and international regulations have never formalized a standard methodology for addressing it, leaving companies complete freedom to adopt the approach they consider appropriate. As a consequence, companies generally settle on the use of simple methodologies which frequently are not able to emphasize all the main aspects affecting risk in the workplace and to produce a precise ranking of hazardous activities. In this paper, a new methodology for risk evaluation is then proposed with the aim to overcome limitations of the classical approaches. In particular, new factors are introduced to take into account effects of human behavior and environment on risk level, other than the classical injury magnitude and occurrence probability of an accident. The proposed methodology also integrates an estimative approach based on the fuzzy logic theory, which permits more coherence in the evaluation process, producing a very suitable final rank of hazardous activities. Finally, an actual case study is reported to show the capabilities of the new risk evaluation model.     

When experts disagree: the need to rethink indicator selection for assessing sustainability of agriculture

Sustainability indicators are well recognized for their potential to assess and monitor sustainable development of agricultural systems. A large number of indicators are proposed in various sustainability assessment frameworks, which raises concerns regarding the validity of approaches, usefulness and trust in such frameworks. Selecting indicators requires transparent and well-defined procedures to ensure the relevance and validity of sustainability assessments. The objective of this study, therefore, was to determine whether experts agree on which criteria are most important in the selection of indicators and indicator sets for robust sustainability assessments. Two groups of experts (Temperate Agriculture Research Network and New Zealand Sustainability Dashboard) were asked to rank the relative importance of eleven criteria for selecting individual indicators and of nine criteria for balancing a collective set of indicators. Both ranking surveys reveal a startling lack of consensus amongst experts about how best to measure agricultural sustainability and call for a radical rethink about how complementary approaches to sustainability assessments are used alongside each other to ensure a plurality of views and maximum collaboration and trust amongst stakeholders. To improve the transparency, relevance and robustness of sustainable assessments, the context of the sustainability assessment, including prioritizations of selection criteria for indicator selection, must be accounted for. A collaborative design process will enhance the acceptance of diverse values and prioritizations embedded in sustainability assessments. The process by which indicators and sustainability frameworks are established may be a much more important determinant of their success than the final shape of the assessment tools. Such an emphasis on process would make assessments more transparent, transformative and enduring.     

Social-ecological system resonance: a theoretical framework for brokering sustainable solutions

Sustainability science is a solution-oriented discipline. Yet, there are few theory-rich discussions about how this orientation structures the efforts of sustainability science. We argue that Niklas Luhmann’s social system theory, which explains how societies communicate problems, conceptualize solutions, and identify pathways towards implementation of solutions, is valuable in explaining the general structure of sustainability science. From Luhmann, we focus on two key concepts. First, his notion of resonance offers us a way to account for how sustainability science has attended and responded to environmental risks. As a product of resonance, we reveal solution-oriented research as the strategic coordination of capacities, resources, and information. Second, Luhmann’s interests in self-organizing processes explain how sustainability science can simultaneously advance multiple innovations. The value logic that supports this multiplicity of self-organizing activities as a recognition that human and natural systems are complex coupled and mutually influencing. To give form to this theoretical framework, we offer case evidence of renewable energy policy formation in Texas. Although the state’s wealth is rooted in a fossil-fuel heritage, Texas generates more electricity from wind than any US state. It is politically antagonistic towards climate-change policy, yet the state’s reception of wind energy technology illustrates how social and environmental systems can be strategically aligned to generate solutions that address diverse needs simultaneously. This case demonstrates that isolating climate change—as politicians do as a separate and discrete problem—is incapable of achieving sustainable solutions, and resonance offers researchers a framework for conceptualizing, designing, and communicating meaningfully integrated actions.     

A stochastic Lagrangian micromixing model for the dispersion of reactive scalars in turbulent flows: role of concentration fluctuations and improvements to the conserved scalar theory under non-homogeneous conditions

Several reaction schemes, based on the conserved scalar theory, are implemented within a stochastic Lagrangian micromixing model to simulate the dispersion of reactive scalars in turbulent flows. In particular, the formulation of the reaction-dominated limit (RDL) reaction scheme is here extended to improve the model performance under non-homogeneous conditions (NHRDL scheme). The validation of the stochastic model is obtained by comparison with the available measurements of reactive pollutant concentrations in a grid-generated turbulent flow. This test case describes the dispersion of two atmospheric reactant species (NO and O₃) and their reaction product (NO₂) in an unbounded turbulent flow. Model inter-comparisons are also assessed, by considering the results of state-of-the-art models for pollutant dispersion. The present validation shows that RDL reaction scheme provides a systematic overestimation (relative error of ca. 85% around the centreline) in computing the local reactant consumption/production rate, whereas the NHRDL scheme drastically reduces this gap (relative error lower than 5% around the centreline). In terms of NO₂ production (or reactant consumption), neglecting concentration fluctuations determines overestimations of the product mean of around 100% and a NO₂ local production of one order of magnitude higher than the reference simulation. In terms of standard deviations, the concentration fluctuations of both the passive and reactive scalars are generally of the same order of magnitude or up to 1 or 2 orders of magnitudes higher than the corresponding ensemble mean values, except for the background reactant close to the plume edges. The study highlights the importance of modelling pollutant reactions depending on the instantaneous instead of the mean concentrations of the reactants, thus quantifying the role of the turbulent fluctuations of concentration, in terms of scalar statistics (mean, standard deviation, intensity of fluctuations, skewness and kurtosis of concentration, segregation coefficient, simulated reaction rate). This stochastic particle method represents an efficient numerical technique to solve the convection–diffusion equation for reactive scalars and involves several application fields: micro-scale air quality (urban and street-canyon scales), accidental releases, impact of odours, water quality and fluid flow industrial processes (e.g. combustion).     

Effect of ferrate on green algae removal

Green algae Cladophora aegagropila, present in cooling water of thermal power plants, causes many problems and complications, especially during summer. However, algae and its metabolites are rarely eliminated by common removal methods. In this work, the elimination efficiency of electrochemically prepared potassium ferrate(VI) on algae from cooling water was investigated. The influence of experimental parameters, such as Fe(VI) dosage, application time, pH of the system, temperature and hydrodynamics of the solution on removal efficiency, was optimized. This study demonstrates that algae C. aegagropila can be effectively removed from cooling water by ferrate. Application of ferrate(VI) at the optimized dosage and under the suitable conditions (temperature, pH) leads to 100% removal of green algae Cladophora from the system. Environmentally friendly reduction products (Fe(III)) and coagulation properties favour the application of ferrate for the treatment of water contaminated with studied microorganisms compared to other methods such as chlorination and use of permanganate, where harmful products are produced.