Developing a participatory impact assessment approach and action research culture within a communication for social change organisation in Nepal

Developing an effective impact evaluation framework, managing and conducting rigorous impact evaluations, and developing a strong research and evaluation culture within development communication organisations presents many challenges. This is especially so when both the community and organisational context is continually changing and the outcomes of programs are complex and difficult to clearly identify.----- This paper presents a case study from a research project being conducted from 2007-2010 that aims to address these challenges and issues, entitled Assessing Communication for Social Change: A New Agenda in Impact Assessment. Building on previous development communication projects which used ethnographic action research, this project is developing, trailing and rigorously evaluating a participatory impact assessment methodology for assessing the social change impacts of community radio programs in Nepal. This project is a collaboration between Equal Access – Nepal (EAN), Equal Access – International, local stakeholders and listeners, a network of trained community researchers, and a research team from two Australian universities. A key element of the project is the establishment of an organisational culture within EAN that values and supports the impact assessment process being developed, which is based on continuous action learning and improvement. The paper describes the situation related to monitoring and evaluation (M&E) and impact assessment before the project began, in which EAN was often reliant on time-bound studies and ‘success stories’ derived from listener letters and feedback. We then outline the various strategies used in an effort to develop stronger and more effective impact assessment and M&E systems, and the gradual changes that have occurred to date. These changes include a greater understanding of the value of adopting a participatory, holistic, evidence-based approach to impact assessment. We also critically review the many challenges experienced in this process, including:----- • Tension between the pressure from donors to ‘prove’ impacts and the adoption of a bottom-up, participatory approach based on ‘improving’ programs in ways that meet community needs and aspirations.----- • Resistance from the content teams to changing their existing M&E practices and to the perceived complexity of the approach.----- • Lack of meaningful connection between the M&E and content teams.----- • Human resource problems and lack of capacity in analysing qualitative data and reporting results.----- • The contextual challenges, including extreme poverty, wide cultural and linguistic diversity, poor transport and communications infrastructure, and political instability.----- • A general lack of acceptance of the importance of evaluation within Nepal due to accepting everything as fate or ‘natural’ rather than requiring investigation into a problem.

Environmental health risk assessment of dioxin exposure through foods in a Dioxin hot spot—Bien Hoa City, Vietnam

This study used the Australian Environmental Health Risk Assessment Framework to assess the human health risk of dioxin exposure through foods for local residents in two wards of Bien Hoa City, Vietnam. These wards are known hot-spots for dioxin and a range of stakeholders from central government to local levels were involved in this process. Publications on dioxin characteristics and toxicity were reviewed and dioxin concentrations in local soil, mud, foods, milk and blood samples were used as data for this risk assessment. A food frequency survey of 400 randomly selected households in these wards was conducted to provide data for exposure assessment. Results showed that local residents who had consumed locally cultivated foods, especially fresh water fish and bottom-feeding fish, free-ranging chicken, duck, and beef were at a very high risk, with their daily dioxin intake far exceeding the tolerable daily intake recommended by the WHO. Based on the results of this assessment, a multifaceted risk management program was developed and has been recognized as the first public health program ever to have been implemented in Vietnam to reduce the risks of dioxin exposure at dioxin hot-spots.

Making a case for social impact assessment in urban development : social impacts and legal disputes in Queensland, Australia

Urban land use planning and policy decisions are often contested, with the multiple stakeholders (business, developers, residents, policymakers and the wider community) frequently holding opposing viewpoints about the issues and best solution. In recent years, however, the participatory process of social impact assessment (SIA) has received significant attention as a way to mitigate conflict, facilitating negotiation and conflict resolution. This paper examines how social impacts have informed development appeals in Australia, focussing on ten cases from the Queensland Planning and Environment Court (QPEC). Half are appeals from community members (typically neighbours) wanting to oppose approvals and half from organisations appealing against City Councils’ decisions to deny their development applications. While legal challenges do not necessarily reflect attitudes and practices, they provide a means to begin to assess how social impacts (although not often explicitly defined as such) inform development related disputes. Based on the nature and outcomes of 10 QPEC cases, we argue that many legal cases could have been avoided if SIA had been undertaken appropriately. First, the issues in each case are clearly social, incorporating impacts on amenity, the character of an area, the needs of different social groups, perceptions of risk and a range of other social issues. Second, the outcomes and recommendations from each case, such as negotiating agreements, modifying plans and accommodating community concerns would have been equally served thorough SIA. Our argument is that engagement at an early stage, utilising SIA, could have likely achieved the same result in a less adversarial and much less expensive and time-consuming environment than a legal case.

Regulatory Impact Assessment of Potential Duplication of Governance and Reporting Standards for Charities

On 25 January 2013, the Council of Australian Governments (COAG) released a Regulatory Impact Assessment (RIA) for consultation on ways to reduce regulatory duplication between the proposed Commonwealth governance and reporting standards and existing state and territory requirements.

Developing a sustainability impact assessment framework for local urban planning

In order to meet the land use and infrastructure needs of the community with the additional challenges posed by climate change and a global recession, it is essential that Queensland local governments test their proposed integrated land use and infrastructure plans to ensure the maximum achievement of triple-bottom line sus-tainability goals. Extensive regulatory impact assessment systems are in place at the Australian and state government levels to substantiate and test policy and legislative proposals, however no such requirement has been extended to the local government level. This paper contends that with the devolution of responsibility to local government and growing impacts of local government planning and development assessment activities, impact assessment of regulatory planning instruments is appropriate and overdue. This is particularly so in the Queensland context where local governments manage metropolitan and regional scale responsibilities and their planning schemes under the Sustainable Planning Act 2009 integrate land use and infrastructure planning to direct development rights, the spatial allocation of land, and infrastructure investment. It is critical that urban planners have access to fit-for-purpose impact assessment frameworks which support this challenging task and address the important relationship between local planning and sustainable urban development. This paper uses two examples of sustainability impact assessment and a case study from the Queensland local urban planning context to build an argument and potential starting point for impact assessment in local planning processes.

Environmental health risk assessment of dioxin in foods and the sustainability of public health interventions at severe dioxin hot spots in Vietnam

This study assessed environmental health risk from dioxin in foods and sustainability of risk reduction programs at two heavily contaminated former military sites in Vietnam. The study involved 1000 household surveys, analysis of food samples and in-depth discussions with residents and officials. The findings indicate that more than 40 years after the war, local residents still experience high exposure to dioxin if they consume local high risk foods. Public health intervention programs were rated moderately to well sustained. Internal migration, and lack of clear, official guidance and sensitivity regarding dioxin issues were the main challenges for sustainability of prevention programs.

Environmental health risk assessment of dioxin in foods at the two most severe dioxin hot spots in Vietnam

Background Bien Hoa and Da Nang airbases were bulk storages for Agent Orange during the Vietnam War and currently are the two most severe dioxin hot spots. Objectives This study assesses the health risk of exposure to dioxin through foods for local residents living in seven wards surrounding these airbases. Methods This study follows the Australian Environmental Health Risk Assessment Framework to assess the health risk of exposure to dioxin in foods. Forty-six pooled samples of commonly consumed local foods were collected and analyzed for dioxin/furans. A food frequency and Knowledge–Attitude–Practice survey was also undertaken at 1000 local households, various stakeholders were involved and related publications were reviewed. Results Total dioxin/furan concentrations in samples of local “high-risk” foods (e.g. free range chicken meat and eggs, ducks, freshwater fish, snail and beef) ranged from 3.8 pg TEQ/g to 95 pg TEQ/g, while in “low-risk” foods (e.g. caged chicken meat and eggs, seafoods, pork, leafy vegetables, fruits, and rice) concentrations ranged from 0.03 pg TEQ/g to 6.1 pg TEQ/g. Estimated daily intake of dioxin if people who did not consume local high risk foods ranged from 3.2 pg TEQ/kg bw/day to 6.2 pg TEQ/kg bw/day (Bien Hoa) and from 1.2 pg TEQ/kg bw/day to 4.3 pg TEQ/kg bw/day (Da Nang). Consumption of local high risk foods resulted in extremely high dioxin daily intakes (60.4–102.8 pg TEQ/kg bw/day in Bien Hoa; 27.0–148.0 pg TEQ/kg bw/day in Da Nang). Conclusions Consumption of local “high-risk” foods increases dioxin daily intakes far above the WHO recommended TDI (1–4 pg TEQ/kg bw/day). Practicing appropriate preventive measures is necessary to significantly reduce exposure and health risk.

An economic approach towards estimating health impacts of major transport investments and transport policies: A case study of transport emission abatement policy

The PhD thesis developed an economic model as an integral part of the current Health Impact Assessment (HIA) framework. Based on a Health Production Function approach, the model showed how to estimate economic benefits of positive health gains generated by transport investment programs and transport policies. Using Australian mortality and morbidity statistics and applying econometric analysis, the case study quantified health benefits induced by transport emission abatement policies in dollar terms for the Australian households. Finally, the thesis demonstrated transferability of the economic model through two example case studies, establishing a wider application capacity of the model.

Climate change impact assessment: Uncertainty modeling with imprecise probability

Hydrologic impacts of climate change are usually assessed by downscaling the General Circulation Model (GCM) output of large-scale climate variables to local-scale hydrologic variables. Such an assessment is characterized by uncertainty resulting from the ensembles of projections generated with multiple GCMs, which is known as intermodel or GCM uncertainty. Ensemble averaging with the assignment of weights to GCMs based on model evaluation is one of the methods to address such uncertainty and is used in the present study for regional-scale impact assessment. GCM outputs of large-scale climate variables are downscaled to subdivisional-scale monsoon rainfall. Weights are assigned to the GCMs on the basis of model performance and model convergence, which are evaluated with the Cumulative Distribution Functions (CDFs) generated from the downscaled GCM output (for both 20th Century [20C3M] and future scenarios) and observed data. Ensemble averaging approach, with the assignment of weights to GCMs, is characterized by the uncertainty caused by partial ignorance, which stems from nonavailability of the outputs of some of the GCMs for a few scenarios (in Intergovernmental Panel on Climate Change [IPCC] data distribution center for Assessment Report 4 [AR4]). This uncertainty is modeled with imprecise probability, i.e., the probability being represented as an interval gray number. Furthermore, the CDF generated with one GCM is entirely different from that with another and therefore the use of multiple GCMs results in a band of CDFs. Representing this band of CDFs with a single valued weighted mean CDF may be misleading. Such a band of CDFs can only be represented with an envelope that contains all the CDFs generated with a number of GCMs. Imprecise CDF represents such an envelope, which not only contains the CDFs generated with all the available GCMs but also to an extent accounts for the uncertainty resulting from the missing GCM output. This concept of imprecise probability is also validated in the present study. The imprecise CDFs of monsoon rainfall are derived for three 30-year time slices, 2020s, 2050s and 2080s, with A1B, A2 and B1 scenarios. The model is demonstrated with the prediction of monsoon rainfall in Orissa meteorological subdivision, which shows a possible decreasing trend in the future.

Human health risk assessment of heavy metals in urban stormwater

Toxic chemical pollutants such as heavy metals (HMs) are commonly present in urban stormwater. These pollutants can pose a significant risk to human health and hence a significant barrier for urban stormwater reuse. The primary aim of this study was to develop an approach for quantitatively assessing the risk to human health due to the presence of HMs in stormwater. This approach will lead to informed decision making in relation to risk management of urban stormwater reuse, enabling efficient implementation of appropriate treatment strategies. In this study, risks to human health from heavy metals were assessed as hazard index (HI) and quantified as a function of traffic and land use related parameters. Traffic and land use are the primary factors influencing heavy metal loads in the urban environment. The risks posed by heavy metals associated with total solids and fine solids (<150µm) were considered to represent the maximum and minimum risk levels, respectively. The study outcomes confirmed that Cr, Mn and Pb pose the highest risks, although these elements are generally present in low concentrations. The study also found that even though the presence of a single heavy metal does not pose a significant risk, the presence of multiple heavy metals could be detrimental to human health. These findings suggest that stormwater guidelines should consider the combined risk from multiple heavy metals rather than the threshold concentration of an individual species. Furthermore, it was found that risk to human health from heavy metals in stormwater is significantly influenced by traffic volume and the risk associated with stormwater from industrial areas is generally higher than that from commercial and residential areas.

Mahanadi streamflow: climate change impact assessment and adaptive strategies

Impacts of climate change on hydrology are assessed by downscaling large scale general circulation model (GCM) outputs of climate variables to local scale hydrologic variables. This modelling approach is characterized by uncertainties resulting from the use of different models, different scenarios, etc. Modelling uncertainty in climate change impact assessment includes assigning weights to GCMs and scenarios, based on their performances, and providing weighted mean projection for the future. This projection is further used for water resources planning and adaptation to combat the adverse impacts of climate change. The present article summarizes the recent published work of the authors on uncertainty modelling and development of adaptation strategies to climate change for the Mahanadi river in India.

Correction for Bias in Downscaling GCM Simulations for Hydrologic Impact Assessment

In a statistical downscaling model, it is important to remove the bias of General Circulations Model (GCM) outputs resulting from various assumptions about the geophysical processes. One conventional method for correcting such bias is standardisation, which is used prior to statistical downscaling to reduce systematic bias in the mean and variances of GCM predictors relative to the observations or National Centre for Environmental Prediction/ National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data. A major drawback of standardisation is that it may reduce the bias in the mean and variance of the predictor variable but it is much harder to accommodate the bias in large-scale patterns of atmospheric circulation in GCMs (e.g. shifts in the dominant storm track relative to observed data) or unrealistic inter-variable relationships. While predicting hydrologic scenarios, such uncorrected bias should be taken care of; otherwise it will propagate in the computations for subsequent years. A statistical method based on equi-probability transformation is applied in this study after downscaling, to remove the bias from the predicted hydrologic variable relative to the observed hydrologic variable for a baseline period. The model is applied in prediction of monsoon stream flow of Mahanadi River in India, from GCM generated large scale climatological data.