Policy-relevant Scenarios Research Articles

Flexible emulation of the climate warming cooling feedback to globally assess the maladaptation implications of future air conditioning use

Abstract Rising affluence and a warming climate mean that the demand for air conditioning (AC) is rising rapidly, as society adapts to climate extremes. Here we present findings from a new methodological framework to flexibly couple and emulate these growing demands into a global integrated assessment model (IAM), subsequently representing the positive feedbacks between rising temperatures, growth in cooling demand, and carbon emissions. In assessing global and regional climate change impacts on cooling energy demand, the emulator incorporates climate model uncertainties and can explore behavioural and adaptation-related assumptions on setpoint temperature and access to cooling. It is also agnostic to the emissions and climate warming trajectory, enabling the IAM to run new policy-relevant scenarios (Current Policies, 2 °C and 1.5 °C) with climate impacts that do not follow Representative Concentration Pathways. We find that climate model uncertainty has a significant effect, more than doubling the increase in electricity demand, when comparing the 95th percentile cases to the median of the climate model ensemble. Residential AC cooling energy demands are expected to increase by 150% by 2050 whilst providing universal access to AC would result in the order of a 400% increase. Depending on the region, under current policies and limited mitigation, climate change could bring in the order of 10%–20% higher cooling-related electricity demands by 2050, and approximately 50% by 2100. Set point temperature has an important moderating role—increasing internal set-point from 23 °C to 26 °C, approximately halves the growth in electricity demand, for the majority of scenarios and regions. This effect is so strong that the change in set point temperature to both residential and commercial sectors outweighs the growth in demand that would occur by providing universal access to AC by 2050 to the 40% of the global population who would otherwise not afford it.

Comparison of UKESM1 and CESM2 simulations using the same multi-target stratospheric aerosol injection strategy

Abstract. Solar climate intervention using stratospheric aerosol injection (SAI) has been proposed as a method which could offset some of the adverse effects of global warming. The Assessing Responses and Impacts of Solar climate intervention on the Earth system with Stratospheric Aerosol Injection (ARISE-SAI) set of simulations is based on a moderate-greenhouse-gas-emission scenario and employs injection of sulfur dioxide at four off-equatorial locations using a control algorithm which maintains the global-mean surface temperature at 1.5 K above pre-industrial conditions (ARISE-SAI-1.5), as well as the latitudinal gradient and inter-hemispheric difference in surface temperature. This is the first comparison between two models (CESM2 and UKESM1) applying the same multi-target SAI strategy. CESM2 is successful in reaching its temperature targets, but UKESM1 has considerable residual Arctic warming. This occurs because the pattern of temperature change in a climate with SAI is determined by both the structure of the climate forcing (mainly greenhouse gases and stratospheric aerosols) and the climate models' feedbacks, the latter of which favour a strong Arctic amplification of warming in UKESM1. Therefore, research constraining the level of future Arctic warming would also inform any hypothetical SAI deployment strategy which aims to maintain the inter-hemispheric and Equator-to-pole near-surface temperature differences. Furthermore, despite broad agreement in the precipitation response in the extratropics, precipitation changes over tropical land show important inter-model differences, even under greenhouse gas forcing only. In general, this ensemble comparison is the first step in comparing policy-relevant scenarios of SAI and will help in the design of an experimental protocol which both reduces some known negative side effects of SAI and is simple enough to encourage more climate models to participate.

Material Requirements, Circularity Potential and Embodied Emissions Associated with Wind Energy

Wind energy, which is often posited as a key decarbonisation option, represents one of the fastest-growing energy sources globally in recent years. Research on the material requirements for transitioning to a low-carbon electricity system at national levels, as well as research exploring the potential of the electricity system to serve as a source of secondary materials remains underexplored. We address these gaps in the knowledge by analysing the stocks and flows in a wind power system towards 2050 using Sweden as a case study, including the demands for bulk (concrete and steel) and critical materials (neodymium and dysprosium), through a dynamic material flow analysis based on policy-relevant scenarios. We demonstrate that some of the investigated scenarios generate substantial increases in the stocks and flows of bulk and critical materials. We show that, after 2045, the year by which Sweden has committed to reducing greenhouse gas emissions to net-zero, the inflows show a decreasing trend while the outflows show an increasing trend, suggesting the beginning of the closing of the material loops, provided untapped circularity potentials transform into actual capacities. For wind power to comply with emissions targets, the steel and concrete production processes will need to be decarbonised at a rate in line with the climate targets. We show that the adoption of mitigation measures to decarbonise the concrete and steel industries aligned with Sweden's climate change mitigation agenda, has the potential to reduce embodied carbon emissions for wind power infrastructure in 2045 from corresponding to around 4 % of current total national emissions in the absence of measures to practically negligible levels. National policies need to focus on promoting the implementation of circularity strategies and decarbonising the entire value chain of the involved materials.

Hydrogen and the decarbonization of the energy system in europe in 2050: A detailed model-based analysis

The paper aims to address the potential of low-carbon and renewable hydrogen in decarbonizing the European energy system; specifically, reducing emissions by 55% in 2030 compared to 1990, and targeting net-zero emissions by 2050. The methodology relies on a cost-optimization modelling approach using three models complementarily: a detailed European TIMES-type model (MIRET-EU); an aggregated model for the European energy system, allowing endogenous cost reductions based on technology deployment in a dynamic programming formulation for investment strategies (Integrate Europe); and a dedicated model for assessing hydrogen import options for Europe (HyPE). Two policy-relevant scenarios have been developed: Technology Diversification (TD) and Renewable Push (RP). Both lead to climate neutrality in Europe in 2050 but the RP scenario differs by setting new reinforced targets for renewable technologies in Europe. Results show that hydrogen production would increase sharply in the coming decades, exceeding 30 million tons (Mt) by 2030 and more than 100 Mt by 2050 in both scenarios. Polyvalence of hydrogen in decarbonizing the European energy system for certain hard-to-abate energy uses in transport and industry is also observed. European hydrogen production relies on a diverse mix including both renewable and low-carbon technologies. It is complemented by hydrogen imports from neighboring regions, that represent between 10 and 15% of total demand in 2050. Access to existing cross-border pipelines is a critical advantage compared to maritime transport. Notably, there are considerable cost reductions due to technology deployment for solar power and hydrogen production by electrolyzers.

Reactor ageing and phase-out policies: global and regional prospects for nuclear power generation

Nuclear is considered as a valuable option for the decarbonization of power generation, as it is a no-carbon, yet commercially consolidated technology. However, its real prospects are uncertain, especially in the OECD countries. The main aim of this work is to explore the techno-economic implications of policy-relevant scenarios for nuclear power, designed on the actual prospects in the world regions and developed with the Integrated Assessment Model WITCH.The analysis shows that nuclear generation constantly grows over the century, even if in general the nuclear share in the global electricity mix does not significantly change over time. If constraints are applied to nuclear deployment, the contribution of this technology is compensated by renewables (mainly wind and solar PV) and, to a lower extent, by CCS.The policy costs related to nuclear phase-out are moderate, as they are almost completely compensated by innovation and technology benefits in renewables and energy efficiency. Phase-out policies applied only to the OECD regions do not entail any additional policy costs in these regions, while non-OECD regions marginally benefit from lower uranium prices.

Integrated Modeling to Evaluate Climate Change Impacts on Coupled Social-Ecological Systems in Alaska

The Alaska CLimate Integrated Modeling (ACLIM) project represents a comprehensive, multi-year, interdisciplinary effort to characterize and project climate-driven changes to the Eastern Bering Sea ecosystem, from physics to fishing communities. Results from the ACLIM project are being used to understand how different regional fisheries management approaches can help promote adaptation to climate-driven changes to sustain fish and shellfish populations and to inform managers and fishery dependent communities of the risks associated with different future climate scenarios. The project relies on iterative communications and outreach with managers and fishery dependent communities that has informed the selection of fishing scenarios. This iterative approach ensures that the research team focuses on policy relevant scenarios that explore realistic adaptation options for managers and communities. Within each iterative cycle, the interdisciplinary research team continues to improve: methods for downscaling climate models, climate-enhanced biological models, socio-economic modeling, and management strategy evaluation within a common analytical framework. The evolving nature of the ACLIM framework ensures improved understanding of system responses and feedbacks are considered within the projections and that the fishing scenarios continue to reflect the management objectives of the regional fisheries management bodies. The multi-model approach used for projection of biological responses facilitates the quantification the relative contributions of climate forcing scenario, fishing scenario, parameter, and structural uncertainty with and between models. Ensemble means and variance within and between models informs risk assessments under different future scenarios. The first phase of projections of climate conditions to the end of 21st century are complete, and projections of catch for core species under baseline (status quo) fishing conditions and two alternative fishing scenarios. The ACLIM modeling framework serves as a guide for multidisciplinary integrated climate impact and adaptation decision making in other large marine ecosystems.

Increasing capacity to produce scenarios and models for biodiversity and ecosystem services

Abstract: Extensive anthropogenic activities driven by the demand for agriculture and forestry products have led to dramatic reductions in biodiversity worldwide and significant changes in the provisioning of ecosystem services. These trends are expected to continue in the future as the world continues to develop without much consideration of the role that nature plays in sustaining human livelihoods. Scenarios and models can be important tools to help policy- and decision-makers foresee the impact of their decisions; thus, increasing capacity in creating such models and scenarios is of utmost importance. However, postgraduate training schools that focus on this topic are still rare. Here we present and reflect on the experience of the São Paulo School of Advanced Science on Scenarios and Modelling on Biodiversity and Ecosystem Services to Support Human Well-Being (SPSAS Scenarios). In addition, we introduce the Special Issue of Biota Neotropica that resulted from the activities taking place during the SPSAS Scenarios. In total, nine case studies emerged from the activities carried out during SPSAS Scenarios. These focused on a variety of ecosystems, their current drivers of change and expected trends, as well as on the development of alternative positive scenarios applying the recently developed Nature Futures Framework. We emphasize the need to increase capacity in scenario and modelling skills in order to address some of the existing gaps in producing policy-relevant scenarios and models for biodiversity and ecosystem services.

Quantifying\xa0economic resilience from input\u2013output susceptibility to\xa0improve predictions of economic growth and recovery

Modern macroeconomic theories were unable to foresee the last Great Recession and could neither predict its prolonged duration nor the recovery rate. They are based on supply−demand equilibria that do not exist during recessionary shocks. Here we focus on resilience as a nonequilibrium property of networked production systems and develop a linear response theory for input−output economics. By calibrating the framework to data from 56 industrial sectors in 43 countries between 2000 and 2014, we find that the susceptibility of individual industrial sectors to economic shocks varies greatly across countries, sectors, and time. We show that susceptibility-based growth predictions that take sector- and country-specific recovery into account, outperform—by far—standard econometric models. Our results are analytically rigorous, empirically testable, and flexible enough to address policy-relevant scenarios. We illustrate the latter by estimating the impact of recently imposed tariffs on US imports (steel and aluminum) on specific sectors across European countries.

Power system expansion planning under global and local emission mitigation policies

This work analyzes the impacts on the power system expansion planning of implementing CO2 and local pollutant emission taxes under five different policy-relevant scenarios. To do this, we have formulated and implemented an optimization model based on a mixed-integer linear program, which determines the optimal expansion plan considering the installation of both large-scale power plants and renewable-based distributed generation. An important characteristic of the proposed model is that it includes a detailed formulation of the power system. Moreover, differently than existing literature, special attention is given to the analysis of the spatial-temporal distributive effects of pollutant taxes, considering both global and local pollutant emissions. The method is applied to the main Chilean power system. Our results indicate that global and local pollutant taxes significantly impact both planning and operational decisions in the power system. In particular, pollutant taxes may have significant spatial distributive effects, as shown in the analysis of 13 regions of Chile, leading to damages in some specific regions while relatively benefiting others. Our results also show that the availability of renewable energy capacity may improve the effectiveness of pollutant taxes. Particularly, adding 1.5 GW of hydro capacity to the Chilean system allows avoiding around 32 GWh of fossil fuel generation per year, saving more than 1.5 billion US$ in the 10-year horizon considered. The proposed method and qualitative results are sufficiently generic to apply to any other jurisdiction.

Reactor Ageing and Phase-out Policies: Global and European Prospects for Nuclear Power Generation

Nuclear is considered as a valuable option for the decarbonization of the power generation, as it is a no-carbon, yet commercially consolidated technology. However, its real prospects are uncertain: if some countries, especially in the non-OECD area, have been extensively investing in nuclear, many OECD countries, which host the vast majority of operational reactors worldwide, feature old fleets which will not be replaced, as phase-out policies are being implemented. Research scenarios often consider polarized conditions based on either a global unconstrained nuclear development or a generalized phase-out. The main aim of this work is instead to explore the techno-economic implications of policy-relevant scenarios, designed on the actual nuclear prospects in the world regions, i.e. mainly differentiating policy constraints between the OECD and the non-OECD regions. The analysis, conducted via the Integrated Assessment Model WITCH, shows that nuclear generation constantly grows over the century, even if in general the nuclear share in the electricity mix does not significantly change over time, both at a global and at a European level. Over time, and especially if constraints are applied to nuclear deployment, the nuclear contribution is compensated by renewables (mainly wind and solar PV) and, to a lower extent, by CCS (only marginally in the EU). The policy costs related to the nuclear phase-out are not particularly high (0.4% additional global GDP loss with respect to the unconstrained policy scenario), as they are almost completely compensated by innovation and technology benefits in renewables and energy efficiency. Phase-out policies applied only to the OECD regions do not entail any additional policy costs, while non-OECD regions marginally benefit from lower uranium prices. A sudden shutdown of nuclear reactors in the OECD regions results in a doubling of these losses and gains.

Including robustness considerations in the search phase of Many-Objective Robust Decision Making

Many-Objective Robust Decision Making (MORDM) is a prominent model-based approach for dealing with deep uncertainty. MORDM has four phases: a systems analytical problem formulation, a search phase to generate candidate solutions, a trade-off analysis where different strategies are compared across many objectives, and a scenario discovery phase to identify the vulnerabilities. In its original inception, the search phase identifies optimal strategies for a single reference scenario for deep uncertainties, which may result in missing locally near-optimal, but globally more robust strategies. Recent work has addressed this issue by generating candidate strategies for multiple policy-relevant scenarios. In this paper, we incorporate a systematic scenario selection procedure in the search phase to consider both policy relevance and scenario diversity. The results demonstrate an increased tradeoff variety besides higher robustness, compared to the solutions found for a reference scenario. Future research can routinize multi-scenario search in MORDM with the aid of software packages.

Operationalising a social\u2013ecological system perspective on the Arctic Ocean

We propose a framework to support management that builds on a social–ecological system perspective on the Arctic Ocean. We illustrate the framework’s application for two policy-relevant scenarios of climate-driven change, picturing a shift in zooplankton composition and alternatively a crab invasion. We analyse archetypical system dynamics between the socio-economic, the natural, and the governance systems in these scenarios. Our holistic approach can help managers identify looming problems arising from complex system interactions and prioritise among problems and solutions, even when available data are limited.

From shared socio-economic pathways (SSPs) to oceanic system pathways (OSPs): Building policy-relevant scenarios for global oceanic ecosystems and fisheries

There is an urgent need for developing policy-relevant future scenarios of biodiversity and ecosystem services. This paper is a milestone toward this aim focusing on open ocean fisheries. We develop five contrasting Oceanic System Pathways (OSPs), based on the existing five archetypal worlds of Shared Socioeconomic Pathways (SSPs) developed for climate change research (e.g., Nakicenovic et al., 2014 and Riahi et al., 2016). First, we specify the boundaries of the oceanic social-ecological system under focus. Second, the two major driving forces of oceanic social-ecological systems are identified in each of three domains, viz., economy, management and governance. For each OSP (OSP1 “sustainability first”, OSP2 “conventional trends”, OSP3 “dislocation”, OSP4 “global elite and inequality”, OSP5 “high tech and market”), a storyline is outlined describing the evolution of the driving forces with the corresponding SSP. Finally, we compare the different pathways of oceanic social-ecological systems by projecting them in the two-dimensional spaces defined by the driving forces, in each of the economy, management and governance domains. We expect that the OSPs will serve as a common basis for future model-based scenario studies in the context of the Intergovernmental Panel on Climate Change (IPCC) and the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES).

Projecting demands for renal replacement therapy in the Northern Territory: a stochastic Markov model.

Objective The aim of the present study was to evaluate the potential effects of different health intervention strategies on demand for renal replacement therapy (RRT) services in the Northern Territory (NT). Methods A Markov chain simulation model was developed to estimate demand for haemodialysis (HD) and kidney transplantation (Tx) over the next 10 years, based on RRT registry data between 2002 and 2013. Four policy-relevant scenarios were evaluated: (1) increased Tx; (2) increased self-care dialysis; (3) reduced incidence of end-stage kidney disease (ESKD); and (4) reduced mortality. Results There were 957 new cases of ESKD during the study period, with most patients being Indigenous people (85%). The median age was 50 years at onset and 57 years at death, 12 and 13 years younger respectively than Australian medians. The prevalence of RRT increased 5.6% annually, 20% higher than the national rate (4.7%). If current trends continue (baseline scenario), the demand for facility-based HD (FHD) would approach 100000 treatments (95% confidence interval 75000-121000) in 2023, a 5% annual increase. Increasing Tx (0.3%), increasing self-care (5%) and reducing incidence (5%) each attenuate demand for FHD to ~70000 annually by 2023. Conclusions The present study demonstrates the effects of changing service patterns to increase Tx, self-care and prevention, all of which will substantially attenuate the growth in FHD requirements in the NT. What is known about the topic? The burden of ESKD is projected to increase in the NT, with demand for FHD doubling every 15 years. Little is known about the potential effect of changes in health policy and clinical practice on demand. What does this paper add? This study assessed the usefulness of a stochastic Markov model to evaluate the effects of potential policy changes on FHD demand. What are the implications for practitioners? The scenarios simulated by the stochastic Markov models suggest that changes in current ESKD management practices would have a large effect on future demand for FHD.

Choosing small sets of policy-relevant scenarios by combining vulnerability and diversity approaches

Computer simulation models can generate large numbers of scenarios, far more than can be effectively utilized in most decision support applications. How can one best select a small number of scenarios to consider? One approach calls for choosing scenarios that illuminate vulnerabilities of proposed policies. Another calls for choosing scenarios that span a diverse range of futures. This paper joins these two approaches for the first time, proposing an optimization-based method for choosing a small number of relevant scenarios that combine both vulnerability and diversity. The paper applies the method to a real case involving climate resilient infrastructure for three African river basins (Volta, Orange and Zambezi). Introducing selection criteria in a stepwise manner helps examine how different criteria influence the choice of scenarios. The results suggest that combining vulnerability- and diversity-based criteria can provide a systematic and transparent method for scenario selection.

A Sectoral Micro-Economic Approach to Scenario Selection and Development: The Case of the Greek Power Sector

Generating policy-relevant scenarios is instrumental for understanding and developing policy measures. These are especially relevant to the power sector. Practitioners have been working on policy-relevant scenarios for the ex-ante assessment of policy measures in a meaningful way for end-users related to climate change mitigation and adaptation strategies. This paper presents a method for generating such policy relevant scenarios by focusing on the actor-contingent elements of the scenarios, i.e., the developments that are within the control of system actors to change or bring about. Several scenario techniques focusing on systematic-formalized or quantitative approaches have been published on this front over the past few years. Here, we introduce a methodology that is best suited for the assessment of the expected effect of different policy measures on the involved stakeholders’ behavior as well as for the analysis of the interactions between different policy measures as reflected on their impact on the strength and direction of the provided incentives. The applicability of our methodology is demonstrated for the case of the Greek power market. It was further evaluated in view of the challenges related to the issues of generation capacity adequacy and increased fiscal deficit. The strategic implications of the proposed approach concern the demonstration of the benefits from adopting a policy assessment methodology that focus on stakeholder expectations and interactions.

An open source framework for many-objective robust decision making

This study introduces a new open source software framework to support bottom-up environmental systems planning under deep uncertainty with a focus on many-objective robust decision making (MORDM), called OpenMORDM. OpenMORDM contains two complementary components: (1) a software application programming interface (API) for connecting planning models to computational exploration tools for many-objective optimization and sensitivity-based discovery of critical deeply uncertain factors; and (2) a web-based visualization toolkit for exploring high-dimensional datasets to better understand system trade-offs, vulnerabilities, and dependencies. We demonstrate the OpenMORDM framework on a challenging environmental management test case termed the “lake problem”. The lake problem has been used extensively in the prior environmental decision science literature and, in this study, captures the challenges posed by conflicting economic and environmental objectives, a water quality “tipping point” beyond which the lake may become irreversibly polluted, and multiple deeply uncertain factors that may undermine the robustness of pollution management policies. The OpenMORDM software framework enables decision makers to identify policy-relevant scenarios, quantify the trade-offs between alternative strategies in different scenarios, flexibly explore alternative definitions of robustness, and identify key system factors that should be monitored as triggers for future actions or additional planning. The web-based OpenMORDM visualization toolkit allows decision makers to easily share and visualize their datasets, with the option for analysts to extend the framework with customized scripts in the R programming language. OpenMORDM provides a platform for constructive decision support, allowing analysts and decision makers to interactively discover promising alternatives and potential vulnerabilities while balancing conflicting objectives.

Quantifying The Burden Of Disease From Ambient Air Pollution And Its Major Sources: GBD 2013 And GBD Maps

Background Ambient air pollution (AAP) threatens global health. The Global Burden of Disease (GBD) 2010 study estimated that exposure to ambient fine particulate air pollution, PM2.5, contributed to 3 million premature deaths and 74 million lost years of healthy life in 2010, with two-thirds occurring in low- and middle income countries (LMIC) in Asia. Major sources in Asia include coal-burning for power generation and other uses, household burning of solid fuels, and road transport. Estimating the burden of disease attributable to AAP from major sources is critical to support the control of both air pollution and climate-forcing emissions. Methods GBD 2013 extends methods and datasets used in GBD 2010 to estimate the burden of disease attributable to AAP for 1990-2013 in 188 countries and at sub-national levels for China, the UK and Mexico. GBD MAPS will estimate the burden of disease attributable to PM2.5 from major sources of air pollution in China, India and Eastern Europe, using emissions data to estimate source-specific PM2.5 levels. Results We will present estimates of global exposure to AAP, and its burden of disease, and preliminary results of GBD MAPS in China, including the contribution of coal combustion to PM2.5 exposure and current and predicted disease burden under future (ca. 2030) policy-relevant scenarios. Discussion We expect to confirm the importance of AAP as a global risk factor, particularly in LMIC, and to observe divergent trends in both exposure and burden between high-income countries and LMIC. The burden attributable to coal-burning in China will likely be substantial, with large health benefits possible from reducing coal burning.

Residual load, renewable surplus generation and storage requirements in Germany

I examine the effects of increasing amounts of fluctuating renewable energy on residual load, which is defined as the difference between actual power demand and the feed-in of non-dispatchable and inflexible generators. I draw on policy-relevant scenarios for Germany and make use of extensive sensitivity analyses. Whereas yearly renewable surplus energy is low in most scenarios analyzed, peak surplus power can become very high. Decreasing thermal must-run requirements and increasing biomass flexibility substantially reduce surpluses. I use an optimization model to determine the storage capacities required for taking up renewable surpluses. Allowing curtailment of 1% of the yearly feed-in of non-dispatchable renewables would render storage investments largely obsolete until 2032 under the assumption of a flexible power system. Further restrictions of curtailment as well as lower system flexibility strongly increase storage requirements. By 2050, at least 10GW of storage are required for surplus integration, of which a sizeable share is seasonal storage. Results suggest that policy makers should work toward avoiding surplus generation, in particular by decreasing the must-run of thermal generators. Concerns about surpluses should not be regarded as an obstacle to further renewable expansion. The findings are also relevant for other countries that shift toward fluctuating renewables.

Modelling the Early life-course (MELC): A Microsimulation Model of Child Development in New Zealand

To understand the factors upon which policies can be devised to improve the lives of children and young people, we have developed a dynamic discrete-time micro-simulation model called Modelling the early life-course (MELC). MELC models child development from birth through to age 13, encompassing changes in material and family circumstances, family functioning and early education. MELC focusses on three main outcomes: health service use, early literacy, and conduct problems. A synthetic base population (n=10,000) derived from the 2006 New Zealand Census is used, and transitions through the life-course are determined from estimates derived by analysing three New Zealand child cohort studies: the Christchurch Health and Development Study, the Dunedin Multidisciplinary Health and Development Study, and the Pacific Islands Families Study. The model has been validated against New Zealand norms for reading, general practitioner visits and hospital admissions. Three scenarios were demonstrated. First, we tested the impact of a number of putatively important factors on early literacy, and found small effects. Second, we found that halving the prevalence of single parenting reduced the prevalence of conduct problems. Third, we changed a number of material and family factors for M?ori, Pacific and low-socio-economic groups to be equal to those for the general population, and found that this produced small improvements in reading, but large reductions in conduct problems for these groups. MELC has been deployed as a user friendly desktop application at a number of New Zealand government agencies, where it can be used to test policy-relevant scenarios.