Arts as a vehicle for community building and post‐disaster development

Use of the arts in international aid is common in an ad hoc form, but it has not been systematically theorised or evaluated. The arts have the potential to be a culturally contextualised and sustainable intervention for adults and children in the aftermath of war or disaster. On the micro level, the arts are a method to enable the retrieval and reprocessing of traumatic memories that are often encoded in images rather than in words. On a macro level, they can help to reconstruct a group narrative of a disaster as well as mobilise people back into control of their lives. This paper researches a long‐term project using arts in Sri Lanka following the civil war and tsunami. A central finding is the need to understand arts within their cultural context, and their usefulness in strengthening the voices and problem‐solving capacities of the victims of the disaster.     

Evaluation of a population mobility,mortality, and birth surveillance system in South Kivu,Democratic Republic of the Congo

Prospective, community-based surveillance systems for measuring birth, death, and population movement rates may have advantages over the ‘gold-standard’ retrospective household survey in humanitarian contexts. A community-based, monthly surveillance system was established in South Kivu, Democratic Republic of the Congo, in partnership with a local implementing partner and the national ministry of health. Data were collected on the occurrence of births, deaths, arrivals, and departures over the course of one year, and a retrospective survey was conducted at the end of the period to validate the information. Discrepancies between the two approaches were resolved by a third visit to the households with discordant records. The study found that the surveillance system was superior in terms of its specificity and sensitivity in measuring crude mortality and birth rates as compared to the survey, demonstrating the method's potential to measure accurately important population-level health metrics in an insecure setting in a timely, community-acceptable manner.     

Integrated Risk Framework for Onsite Wastewater Treatment Systems

Onsite wastewater treatment systems (OWTS) are becoming increasingly important for the treatment and dispersal of effluent in new urbanised developments that are not serviced by centralised wastewater collection and treatment systems. However, the current standards and guidelines adopted by many local authorities for assessing suitable site and soil conditions for OWTS are increasingly coming under scrutiny due to the public health and environmental impacts caused by poorly performing systems, in particular septic tank-soil adsorption systems. In order to achieve sustainable onsite wastewater treatment with minimal impacts on the environment and public health, more appropriate means of assessment are required. This paper highlights an integrated risk based approach for assessing the inherent hazards associated with OWTS in order to manage and mitigate the environmental and public health risks inherent with onsite wastewater treatment. In developing a sound and cohesive integrated risk framework for OWTS, several key issues must be recognised. These include the inclusion of relevant stakeholders throughout framework development, the integration of scientific knowledge, data and analysis with risk assessment and management ideals, and identification of the appropriate performance goals for successful management and mitigation of associated risks. These issues were addressed in the development of the risk framework to provide a generic approach to assessing risk from OWTS. The utilisation of the developed risk framework for achieving more appropriate assessment and management techniques for OWTS is presented in a case study for the Gold Coast region, Queensland State, Australia.     

Modeling traffic air pollution in street canyons in New York City for intra-urban exposure assessment in the US Multi-Ethnic Study of atherosclerosis and air pollution

We evaluated the Danish AirGIS air quality and exposure model system using air quality measurement data from New York City in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Measurements were used from three US EPA Air Quality System (AQS) monitoring stations and a comprehensive MESA Air measurement campaign including about 150 different locations and about 650 samples of about 2 week measurements of NO_x, NO₂ and PM_2.5. AirGIS is a deterministic exposure model system based on the dispersion models Operational Street Pollution Model (OSPM) and the Urban Background Model (UBM). The UBM model reproduced the annual levels within 1–26% depending on station and pollutant at the three urban background EPA monitor stations, and generally reproduced well the seasonal and diurnal variation. The full model with OSPM and UBM reproduced the MESA Air measurements with a correlation coefficient of r² = 0.51 for NO_x, r² = 0.28 for NO₂ and r² = 0.73 for PM_2.5.     

Research priorities for managing the impacts and dependencies of business upon food,energy, water and the environment

Delivering access to sufficient food, energy and water resources to ensure human wellbeing is a major concern for governments worldwide. However, it is crucial to account for the ‘nexus’ of interactions between these natural resources and the consequent implications for human wellbeing. The private sector has a critical role in driving positive change towards more sustainable nexus management and could reap considerable benefits from collaboration with researchers to devise solutions to some of the foremost sustainability challenges of today. Yet opportunities are missed because the private sector is rarely involved in the formulation of deliverable research priorities. We convened senior research scientists and influential business leaders to collaboratively identify the top forty questions that, if answered, would best help companies understand and manage their food-energy-water-environment nexus dependencies and impacts. Codification of the top order nexus themes highlighted research priorities around development of pragmatic yet credible tools that allow businesses to incorporate nexus interactions into their decision-making; demonstration of the business case for more sustainable nexus management; identification of the most effective levers for behaviour change; and understanding incentives or circumstances that allow individuals and businesses to take a leadership stance. Greater investment in the complex but productive relations between the private sector and research community will create deeper and more meaningful collaboration and cooperation.     

Marginal abatement cost curve for nitrogen oxides incorporating controls,renewable electricity,energy efficiency,and fuel switching

A marginal abatement cost curve (MACC) traces out the relationship between the quantity of pollution abated and the marginal cost of abating each additional unit. In the context of air quality management, MACCs are typically developed by sorting control technologies by their relative cost-effectiveness. Other potentially important abatement measures such as renewable electricity, energy efficiency, and fuel switching (RE/EE/FS) are often not incorporated into MACCs, as it is difficult to quantify their costs and abatement potential. In this paper, a U.S. energy system model is used to develop a MACC for nitrogen oxides (NO_x) that incorporates both traditional controls and these additional measures. The MACC is decomposed by sector, and the relative cost-effectiveness of RE/EE/FS and traditional controls are compared. RE/EE/FS are shown to have the potential to increase emission reductions beyond what is possible when applying traditional controls alone. Furthermore, a portion of RE/EE/FS appear to be cost-competitive with traditional controls.

Implications: Renewable electricity, energy efficiency, and fuel switching can be cost-competitive with traditional air pollutant controls for abating air pollutant emissions. The application of renewable electricity, energy efficiency, and fuel switching is also shown to have the potential to increase emission reductions beyond what is possible when applying traditional controls alone.     

Integrating Environmental and Socio-Economic Indicators of a Linked Catchment–Coastal System Using Variable Environmental Intensity

Can we develop land use policy that balances the conflicting views of stakeholders in a catchment while moving toward long term sustainability? Adaptive management provides a strategy for this whereby measures of catchment performance are compared against performance goals in order to progressively improve policy. However, the feedback loop of adaptive management is often slow and irreversible impacts may result before policy has been adapted. In contrast, integrated modelling of future land use policy provides rapid feedback and potentially improves the chance of avoiding unwanted collapse events. Replacing measures of catchment performance with modelled catchment performance has usually required the dynamic linking of many models, both biophysical and socio-economic—and this requires much effort in software development. As an alternative, we propose the use of variable environmental intensity (defined as the ratio of environmental impact over economic output) in a loose coupling of models to provide a sufficient level of integration while avoiding significant effort required for software development. This model construct was applied to the Motueka Catchment of New Zealand where several biophysical (riverine water quantity, sediment, E. coli faecal bacteria, trout numbers, nitrogen transport, marine productivity) models, a socio-economic (gross output, gross margin, job numbers) model, and an agent-based model were linked. An extreme set of land use scenarios (historic, present, and intensive) were applied to this modelling framework. Results suggest that the catchment is presently in a near optimal land use configuration that is unlikely to benefit from further intensification. This would quickly put stress on water quantity (at low flow) and water quality (E. coli). To date, this model evaluation is based on a theoretical test that explores the logical implications of intensification at an unlikely extreme in order to assess the implications of likely growth trajectories from present use. While this has largely been a desktop exercise, it would also be possible to use this framework to model and explore the biophysical and economic impacts of individual or collective catchment visions. We are currently investigating the use of the model in this type of application.     

Comparing universal kriging and land-use regression for predicting concentrations of gaseous oxides of nitrogen (NOx) for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

BACKGROUND: Epidemiological studies that assess the health effects of long-term exposure to ambient air pollution are used to inform public policy. These studies rely on exposure models that use data collected from pollution monitoring sites to predict exposures at subject locations. Land use regression (LUR) and universal kriging (UK) have been suggested as potential prediction methods. We evaluate these approaches on a dataset including measurements from three seasons in Los Angeles, CA. METHODS: The measurements of gaseous oxides of nitrogen (NOx) used in this study are from a "snapshot" sampling campaign that is part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). The measurements in Los Angeles were collected during three two-week periods in the summer, autumn, and winter, each with about 150 sites. The design included clusters of monitors on either side of busy roads to capture near-field gradients of traffic-related pollution. LUR and UK prediction models were created using geographic information system (GIS)-based covariates. Selection of covariates was based on 10-fold cross-validated (CV) R(2) and root mean square error (RMSE). Since UK requires specialized software, a computationally simpler two-step procedure was also employed to approximate fitting the UK model using readily available regression and GIS software. RESULTS: UK models consistently performed as well as or better than the analogous LUR models. The best CV R(2) values for season-specific UK models predicting log(NOx) were 0.75, 0.72, and 0.74 (CV RMSE 0.20, 0.17, and 0.15) for summer, autumn, and winter, respectively. The best CV R(2) values for season-specific LUR models predicting log(NOx) were 0.74, 0.60, and 0.67 (CV RMSE 0.20, 0.20, and 0.17). The two-stage approximation to UK also performed better than LUR and nearly as well as the full UK model with CV R(2) values 0.75, 0.70, and 0.70 (CV RMSE 0.20, 0.17, and 0.17) for summer, autumn, and winter, respectively. CONCLUSION: High quality LUR and UK prediction models for NOx in Los Angeles were developed for the three seasons based on data collected for MESA Air. In our study, UK consistently outperformed LUR. Similarly, the 2-step approach was more effective than the LUR models, with performance equal to or slightly worse than UK.     

Zoning and the Tasmanian commercial rock lobster fishery

In this paper, the island of Tasmania is considered as a government jurisdiction. Management at this scale can conflict with sustainability in local environments. The case used to make this argument is the Tasmanian commercial rock lobster fishery. Within this fishery, Tasmania-wide management paradoxically intensifies differences at the same time as it effaces them. These differences contrast with Tasmania-wide management claims regarding sustainability. Actor-network theory is used to help approach these tensions. Zoning the fishery is put forward as a way to take into account differences to produce sustainable local outcomes.