• Energy Research

Abstract: In this study the Impact-Pathway Approach methodology was applied for monetary valuation of health impacts due to cadmium emitted to soil as a micro-pollutant present in phosphorus fertilizers. Due to the high persistency of cadmium in soil, and high soil-to-plant transfer rates, humans are exposed to cadmium through their diet causing potential adverse health impacts. Future scenarios for cadmium emissions to soil via agricultural applications of inorganic and organic fertilizers in Denmark were defined. A simplified fate and speciation model allowed the increase in soil cadmium concentration to be calculated for each scenario. Human exposure was determined based on soil-crop bioconcentration factors for cadmium and dietary intake rates of Danish food crops. Updated dose-response functions linking lifetime cadmium intake to the probability of developing cadmium-induced renal disease and osteoporosis were applied. These impacts were converted into monetary values by using the EU standard value of a life-year adjusted for quality of life experience. Annualized cost per unit of phosphorus and cadmium are presented, discounted and undiscounted, for comparison. Application of struvite (magnesium ammonium phosphate) and mineral fertilizer produced the lowest external health costs, followed by the fertilizer products wastewater sludge and pig manure. The external cost estimates produced in this study could be used to design economic policy instruments to encourage use of cleaner fertilizer products.

Abstract: In this study the Impact-Pathway Approach methodology was applied for monetary valuation of health impacts due to cadmium emitted to soil as a micro-pollutant present in phosphorus fertilizers. Due to the high persistency of cadmium in soil, and high soil-to-plant transfer rates, humans are exposed to cadmium through their diet causing potential adverse health impacts. Future scenarios for cadmium emissions to soil via agricultural applications of inorganic and organic fertilizers in Denmark were defined. A simplified fate and speciation model allowed the increase in soil cadmium concentration to be calculated for each scenario. Human exposure was determined based on soil-crop bioconcentration factors for cadmium and dietary intake rates of Danish food crops. Updated dose-response functions linking lifetime cadmium intake to the probability of developing cadmium-induced renal disease and osteoporosis were applied. These impacts were converted into monetary values by using the EU standard value of a life-year adjusted for quality of life experience. Annualized cost per unit of phosphorus and cadmium are presented, discounted and undiscounted, for comparison. Application of struvite (magnesium ammonium phosphate) and mineral fertilizer produced the lowest external health costs, followed by the fertilizer products wastewater sludge and pig manure. The external cost estimates produced in this study could be used to design economic policy instruments to encourage use of cleaner fertilizer products.

Bayesian networks (BNs) are widely implemented as graphical decision support tools which use probability inferences to generate “what if?” and “which is best?” analyses of potential management options for water resource management, under climate change and socio-economic stressors. This paper presents a systematic quantitative literature review of applications of BNs for decision support in water resource management. The review quantifies to what extent different types of data (quantitative and/or qualitative) are used, to what extent optimization-based and/or scenario-based approaches are adopted for decision support, and to what extent different categories of adaptation measures are evaluated. Most reviewed publications applied scenario-based approaches (68%) to evaluate the performance of management measures, whilst relatively few studies (18%) applied optimization-based approaches to optimize management measures. Institutional and social measures (62%) were mostly applied to the management of water-related concerns, followed by technological and engineered measures (47%), and ecosystem-based measures (37%). There was no significant difference in the use of quantitative and/or qualitative data across different decision support approaches (p = 0.54), or in the evaluation of different categories of management measures (p = 0.25). However, there was significant dependence (p = 0.076) between the types of management measure(s) evaluated, and the decision support approaches used for that evaluation. The potential and limitations of BN applications as decision support systems are discussed along with solutions and recommendations, thereby further facilitating the application of this promising decision support tool for future research priorities and challenges surrounding uncertain and complex water resource systems driven by multiple interactions amongst climatic and non-climatic changes.

Bayesian networks (BNs) are widely implemented as graphical decision support tools which use probability inferences to generate “what if?” and “which is best?” analyses of potential management options for water resource management, under climate change and socio-economic stressors. This paper presents a systematic quantitative literature review of applications of BNs for decision support in water resource management. The review quantifies to what extent different types of data (quantitative and/or qualitative) are used, to what extent optimization-based and/or scenario-based approaches are adopted for decision support, and to what extent different categories of adaptation measures are evaluated. Most reviewed publications applied scenario-based approaches (68%) to evaluate the performance of management measures, whilst relatively few studies (18%) applied optimization-based approaches to optimize management measures. Institutional and social measures (62%) were mostly applied to the management of water-related concerns, followed by technological and engineered measures (47%), and ecosystem-based measures (37%). There was no significant difference in the use of quantitative and/or qualitative data across different decision support approaches (p = 0.54), or in the evaluation of different categories of management measures (p = 0.25). However, there was significant dependence (p = 0.076) between the types of management measure(s) evaluated, and the decision support approaches used for that evaluation. The potential and limitations of BN applications as decision support systems are discussed along with solutions and recommendations, thereby further facilitating the application of this promising decision support tool for future research priorities and challenges surrounding uncertain and complex water resource systems driven by multiple interactions amongst climatic and non-climatic changes.

AbstractThere is an increasing need for long-term monitoring of ecosystems and their services to inform on-ground management and policy direction. The supply of many ecosystem services relies on connections that span multiple ecosystems. Monitoring the underlying condition of interconnected ecosystems, using established indicators, is therefore required to track effectiveness of past interventions and, ideally, identify impending change. Here we conduct performance testing of ecological indicators for a catchment-to-coast system with the aim of identifying the time-scales over which they respond to change. We chose a case-study of a coastal fishery in Northern Australia that exhibits strong catchment-to-coast connectivity, has long-term available data and is under threat from water resource development. We developed a novel approach to performance testing. Our model drew on state-space modelling to capture ecological dynamics, and structural equation modelling to capture covariation in indictors timeseries. We first quantified covariation among three established ecological indicators: pasture biomass, vegetation greenness and barramundi catch per unit effort. Covariation in the indicators was driven by river flow, with higher values of all indicators occurring in years with greater river flow. We then defined reference bounds for each indicator that accounted for natural variation in river flow. We predicted the emergence times for each indicator, as the time taken for each indicator to emerge from the background of natural variation. Emergence times quantified at 80% and higher confidence levels were >10 years in all cases. Past trends and current status of ecosystem service flows are often used by decision makers to directly inform near-term actions, particularly provisioning services (such as barramundi catch) due to their important contribution to regional economies. We found that the ecological indicators should be used to assess historical performance over decadal timespans, but not as short-term indicators of recent change. More generally, we offer an approach to performance testing of indicators. This approach could be useful for quantifying time-scales of ecosystem response in other systems where cross-ecosystem connections are important.

AbstractThere is an increasing need for long-term monitoring of ecosystems and their services to inform on-ground management and policy direction. The supply of many ecosystem services relies on connections that span multiple ecosystems. Monitoring the underlying condition of interconnected ecosystems, using established indicators, is therefore required to track effectiveness of past interventions and, ideally, identify impending change. Here we conduct performance testing of ecological indicators for a catchment-to-coast system with the aim of identifying the time-scales over which they respond to change. We chose a case-study of a coastal fishery in Northern Australia that exhibits strong catchment-to-coast connectivity, has long-term available data and is under threat from water resource development. We developed a novel approach to performance testing. Our model drew on state-space modelling to capture ecological dynamics, and structural equation modelling to capture covariation in indictors timeseries. We first quantified covariation among three established ecological indicators: pasture biomass, vegetation greenness and barramundi catch per unit effort. Covariation in the indicators was driven by river flow, with higher values of all indicators occurring in years with greater river flow. We then defined reference bounds for each indicator that accounted for natural variation in river flow. We predicted the emergence times for each indicator, as the time taken for each indicator to emerge from the background of natural variation. Emergence times quantified at 80% and higher confidence levels were >10 years in all cases. Past trends and current status of ecosystem service flows are often used by decision makers to directly inform near-term actions, particularly provisioning services (such as barramundi catch) due to their important contribution to regional economies. We found that the ecological indicators should be used to assess historical performance over decadal timespans, but not as short-term indicators of recent change. More generally, we offer an approach to performance testing of indicators. This approach could be useful for quantifying time-scales of ecosystem response in other systems where cross-ecosystem connections are important.

Globally, solar photovoltaic (PV) is rapidly becoming a key source of energy, incentivised through the use of feed-in tariffs (FiTs). Solar PV is enjoying a similarly swift adoption in Australia, encouraged through FiTs. This review builds on earlier work, compiling and comparing FiTs in Australia across its states and territories for residential small scale photovoltaic installations. The purpose of this review is three-fold: (1) to synthesise a set of data on FiT policy which can be used to inform future Australia-wide policy analysis; (2) to understand the coevolution of: policies to subsidise solar panel installation; installation costs; and installation numbers; and (3) to employ this set of data on FiT policy to examine whether FiT policy corresponds with unintended adverse energy justice outcomes (i.e. electricity disconnections from the grid). The analysis presented in this review indicates that FiT policies correspond to a greater number of electricity disconnections from the grid. These findings are discussed in the context of broader debates.