Alternative Policy Scenarios Research Articles

TRIBUTE: Trip-based urban transportation emissions model for municipalities

ABSTRACTThis research aims at developing modeling and scenario-comparison tools to explore the impacts of various transportation and land use planning policies on changing travel behavior and eventually greenhouse gas (GHG) emissions. A Trip-Based Urban Transportation Emissions (TRIBUTE) model is developed. Data required for TRIBUTE comes from household travel surveys and emissions inventories, which is a major advantage in cases where a detailed transportation network model is unavailable. TRIBUTE is composed of two main parts: a mode choice model and an emissions forecasting model. The mode choice model is responsible for estimating modal shares of alternative modes of travel in response to changes in personal, modal, and land use attributes. The emissions forecasting model translates the modal shares into vehicle kilometers traveled, and subsequently GHG emissions. TRIBUTE is a macroscopic model intended to assist municipalities evaluate alternative transportation and land use policy scenarios and eventually select the one(s) that help them meet their future GHG emission targets. This paper reports on the conceptual framework of the developed model and presents a case study.

Analysis of policy scenarios for achieving renewable energy sources targets: A fuzzy TOPSIS approach

The growing need to tackle climate change and mitigate greenhouse gas emissions has led to strong interest in renewable energy sources and the setting of specific renewable energy sources targets in countries and regions within Europe. Recent political discussions have mainly revolved around the question of the most effective and efficient renewable energy sources target and how to achieve it. In this context, European and national policy makers have to address difficult issues: On the one hand, how to support the successful achievement of renewable energy targets in the short and medium term and in a time horizon up to 2030, and, on the other hand, how to share the efforts required among individual entities such as single European Member States or groups of European Member States. This paper presents a multi-criteria approach based on an extension of the Fuzzy Technique for Order Preference by Similarity to Ideal Solution for group decision support in order to evaluate alternative policy scenarios for achieving the 2030 renewable energy target. Different effort-sharing arrangements among Member States are evaluated to determine the optimal burden sharing of the common renewable energy target among countries. The results and conclusions obtained can help to reduce uncertainty in the field of energy and climate policy, and aid policy makers in designing effective policies based on the findings.

Estimating potential productivity cobenefits for crops and trees from reduced ozone with U.S. coal power plant carbon standards

AbstractA standard for carbon dioxide emissions from power plants in the United States, known as the Clean Power Plan, has been finalized by the Environmental Protection Agency. Decreases in carbon dioxide emissions from fossil fuel combustion have the potential cobenefit of reductions in emissions of oxides of nitrogen, which contribute to the formation of ground‐level ozone. Emissions of ozone precursors may result in elevated ozone concentrations nearby or downwind. Chronic exposure of sensitive vegetation to tropospheric ozone reduces its potential productivity. To evaluate the cobenefits of the Clean Power Plan to sensitive vegetation, we estimate ozone concentrations in the continental U.S. in 2020 with a chemical transport model in accordance with reference and alternative Clean Power Plan policy scenarios, which represent a range of possible approaches to reducing carbon dioxide emissions from power plants. The reductions in biomass, or the potential productivity losses, due to the exposure of 4 crops and 11 tree species to ozone are as large as 1.9% and 32%, respectively, in the reference scenario. The least stringent policy scenario reduces these losses by less than 3% for any given species; however, the scenarios consistent with policies resulting in more rigorous nitrogen oxide reductions produce potential productivity losses lower than the reference scenario by as much as 16% and 13% for individual crops or tree species, respectively. This analysis affords the opportunity to consider public welfare cobenefits of a regulation that is designed to reduce carbon dioxide emissions from power plants.

Simulating deep CO2 emission reduction in transport in a general equilibrium framework: The GEM-E3T model

Transport sector restructuring to achieve deep GHG emission cuts has attracted much attention because transportation is important for the economy and inflexible in greenhouse gas emission reduction. The aim of this paper is to simulate transition towards low carbon transportation in the European Union until 2050 and to assess the ensuing macroeconomic and sectorial impacts. Transport restructuring is dynamically simulated using a new transport-oriented version of the computable general equilibrium model GEM-E3 which is linked with the PRIMES-TREMOVE energy and transport sectors model. The analysis draws from comparing a reference scenario projection for the EU member-states up to 2050 to alternative transport policy scenarios and sensitivities which involve deep cutting of CO2 emissions. The simulations show that transport restructuring affects the economy through multiple channels, including investment in infrastructure, the purchasing and manufacturing of new technology vehicles, the production of alternative fuels, such as biofuels and electricity. The analysis identifies positive impacts of industrial activity and other sectors stemming from these activities. However, the implied costs of freight and passenger transportation are of crucial importance for the net impact on GDP and income. Should the transport sector transformation imply high unit costs of transport services, crowding out effects in the economy can offset the benefits. This implies that the technology and productivity progress assumptions can be decisive for the sign of GDP impacts. A robust conclusion is that the transport sector decarbonisation, is likely to have only small negative impacts on the EU GDP compared to business as usual.

Simulation modelling as a tool for knowledge mobilisation in health policy settings: a case study protocol.

BackgroundEvidence-informed decision-making is essential to ensure that health programs and services are effective and offer value for money; however, barriers to the use of evidence persist. Emerging systems science approaches and advances in technology are providing new methods and tools to facilitate evidence-based decision-making. Simulation modelling offers a unique tool for synthesising and leveraging existing evidence, data and expert local knowledge to examine, in a robust, low risk and low cost way, the likely impact of alternative policy and service provision scenarios. This case study will evaluate participatory simulation modelling to inform the prevention and management of gestational diabetes mellitus (GDM). The risks associated with GDM are well recognised; however, debate remains regarding diagnostic thresholds and whether screening and treatment to reduce maternal glucose levels reduce the associated risks. A diagnosis of GDM may provide a leverage point for multidisciplinary lifestyle modification interventions. This research will apply and evaluate a simulation modelling approach to understand the complex interrelation of factors that drive GDM rates, test options for screening and interventions, and optimise the use of evidence to inform policy and program decision-making.Methods/DesignThe study design will use mixed methods to achieve the objectives. Policy, clinical practice and research experts will work collaboratively to develop, test and validate a simulation model of GDM in the Australian Capital Territory (ACT). The model will be applied to support evidence-informed policy dialogues with diverse stakeholders for the management of GDM in the ACT. Qualitative methods will be used to evaluate simulation modelling as an evidence synthesis tool to support evidence-based decision-making. Interviews and analysis of workshop recordings will focus on the participants’ engagement in the modelling process; perceived value of the participatory process, perceived commitment, influence and confidence of stakeholders in implementing policy and program decisions identified in the modelling process; and the impact of the process in terms of policy and program change.DiscussionThe study will generate empirical evidence on the feasibility and potential value of simulation modelling to support knowledge mobilisation and consensus building in health settings.

Spatial structure and evolution of infrastructure networks

Critical infrastructure systems are essential components of a nation's assets. They support economic development, enable growth and help to protect against hazard. In recent years, the demands placed upon these systems have been rapidly increasing, partly due to the shift from rural to urban living and partly due to increasing wealth. For example, in 1960, only 34% of the world's population lived in cities whereas, in 2014, this figure had risen rapidly to 54%. This shift has also caused a massive explosion in urban infrastructure systems and therefore a proportionately greater risk to social cohesion through the potential loss of critical infrastructure due to natural or manmade hazard. While it is possible to model the performance of these systems, the complexity of them makes it difficult to assess their contribution to economic development or their resilience to hazard. This deficiency stems from our inability to identify key generic features that would enable us to simplify the task and hence conduct probabilistic assessments or to recognise the underlying drivers that govern their evolution and thus enable us to make robust future decisions. In this paper we present an algorithm that can generate spatial nodal layouts which share a number of non-trivial features common to several types of real world networks. The synthetic networks generated by the algorithm can be used in planning studies to see how infrastructure may evolve in the future, considering alternate planning or policy scenarios for example, or in other scenario based assessments, such as hazard tolerance studies.

An assessment of alternative carbon mitigation policies for achieving the emissions reduction of the Clean Power Plan: Case study for the state of Indiana

National carbon mitigation policy included in the Clean Power Plan (CPP) targets electric power generation facilities and may have substantial impacts at the national level. The subnational impacts will vary because the level of dependence on coal for electricity generation varies substantially across states. Indiana represents a state where the CPP impacts may be relatively large due to heavy dependence on coal for electricity generation. Therefore, this paper presents analysis of the efficacy and cost of alternative approaches to carbon mitigation policy, taking Indiana as an example.A state-level energy system model, IN-MARKAL, was developed based on the MARKAL framework to explore alternative policy scenarios. Results show that a renewable portfolio standard (RPS) is relatively cost effective in achieving carbon emissions reduction for Indiana from the perspective of the power system alone, but that the RPS may also lead to a generation mix dominated by coal and wind. Carbon cap and carbon tax outperform the RPS when considering the entire energy system modeled in IN-MARKAL, which also lead to a more diverse generation portfolio for the state.

Quasi-monetary and quasi-fiscal policy rules at the zero-lower bound

This paper assesses adjustments at the zero lower bound (ZLB) in an economy incorporating financial frictions and nominal price stickiness. We examine the dynamic paths of key variables under recurring real (productivity) and financial (net worth) shocks under three alternative policy scenarios: removal of the zero lower bound (to allow for negative rates), quantitative easing policies at the ZLB, and the use of endogenous tax-rates rules for consumption and labor income at the ZLB. The results show that the fiscal tax-rate rules (acting like a quasi-monetary policy with direct effects on consumption) can be as effective as quantitative easing (a quasi-fiscal policy with indirect effects on investment) in times of prolonged crises due to recurring negative shocks.

Towards a low carbon growth in Mexico: Is a double dividend possible? A dynamic general equilibrium assessment

This paper simulates the medium- and long-term impact of proposed and expected energy policy on the environment and on the Mexican economy. The analysis has been conducted with a Multi-sector Macroeconomic Model for the Evaluation of Environmental and Energy policy (Three-ME). This model is well suited for policy assessment purposes in the context of developing economies as it indicates the transitional effects of policy intervention. Three-ME estimates the carbon tax required to meet emissions reduction targets within the Mexican “Climate Change Law”, and assesses alternative policy scenarios, each reflecting a different strategy for the recycling of tax revenues. With no compensation, the taxation policy would reduce CO2 emissions by more than 75% by 2050 with respect to Business as Usual (BAU), but at high economic costs. Under full redistribution of carbon tax revenues, a double dividend arises: the policy appears beneficial both in terms of GDP and CO2 emissions reduction.

Mixed policies give more options in multifunctional tropical forest landscapes

Summary Tropical forest landscapes face competing demands for conserving biodiversity, sustaining ecosystem services and accommodating production systems such as forestry and agriculture. Land‐sparing and land‐sharing have emerged as contrasting strategies to manage trade‐offs between production and biodiversity conservation. Both strategies are evident in land‐management policies at local‐to‐international scales. However, studies rarely report the impacts of these strategies, assessed for multiple stakeholders and multiple ecosystem services, particularly in real landscapes. Using a case study from a high‐priority region for forest protection, restoration and rural development in Central Kalimantan, Indonesia, we analysed the potential outcomes under 10 alternative policy scenarios, including land‐sharing, land‐sparing and mixed strategies. We used a novel optimization process integrating integer programming with conservation‐planning software (Marxan with Zones) to identify production possibility frontiers (PPFs), highlighting the trade‐off between smallholder agriculture and oil palm, subject to achievement of a set of carbon, timber and biodiversity conservation targets. All policy scenarios modelled proved to be capable of achieving all targets simultaneously. Most strategies resulted in an expansion of the PPF from the baseline, increasing the flexibility of land allocation to achieve all targets. Mixed strategies gave the greatest flexibility to achieve targets, followed closely by land‐sparing. Land‐sharing only performed better than the baseline when no yield penalties were incurred, and resulted in PPF contraction otherwise. Strategies assessed required a minimum of 29–37% to be placed in conservation zones, notably protecting the majority of remaining forest, but requiring little reforestation. Policy implications. Production possibility frontiers (PPFs) can evaluate a broad spectrum of land‐use policy options. When using targets sought by multiple stakeholders within an ecosystem services framework, PPFs can characterize biophysical, socio‐economic and institutional dimensions of policy trade‐offs in heterogeneous landscapes. All 10 policy strategies assessed in our case study are biophysically capable of achieving all stakeholder objectives, provided at least 29–37% of the landscape is conserved for biodiversity. This novel methodological approach provides practical options for systematic analysis in complex, multifunctional landscapes, and could, when integrated within a larger planning and implementation process, inform the design of land‐use policies that maximize stakeholder satisfaction and minimize conflict.

Market-Based Multi-Agent Coordination to Manage Energy Balance in Smart Grids

Widespread adoption of sustainable energy sources is driving electricity grid operators to supplement hierarchical control regimes with market-based control that better motivates stakeholder involvement. However, to prevent market failures, such controls require testing before real-world implementation. The Power Trading Agent Competition is a competitive simulation of distribution grids that mirrors real-world scenarios and tests alternative policy and business scenarios. In Power TAC, broker agents acquire energy through bidding in a forward wholesale market to satisfy their customers’ overall demand on an hourly basis. In addition, a balancing market is intended to resolve real-time energy imbalances caused by broker prediction errors using demand response resources. As part of the annual alignment process, we discovered that brokers in the 2015 competition were persistently buying insufficient energy on the wholesale market to satisfy their customer demand. Instead, the balancing market made up the deficit, charging brokers a premium over the wholesale price. Also, demand response resources were heavily underused. We studied the economic impact of this systematic imbalance on brokers and discovered that they were behaving rationally, given the prices they faced in the two markets. We present the process and results of this analysis, and show how the balancing market’s pricing mechanism can be adjusted for the 2016 competition to make it rational for brokers to achieve an overall neutral imbalance.

Carrot or stick: Impacts of alternative climate and energy policy scenarios on agriculture

The climate and energy strategy of the European Union presents the aims for all economic sectors to cut carbon dioxide emissions. In this paper, we studied what kind of conflicts, synergies, opportunities and control measures the climate and energy policy brings to farms in Finland. We used the Delphi method to assess possible outcomes of three scenarios based on the strength of mitigation policy. The scenarios scrutinised were (1) Baseline, (2) Tight Control and (3) Energy Plus Food. These scenarios create different adaptive needs and measures on farms. Baseline scenario follows the present and forthcoming development in agriculture and Tight Control scenario, in turn, constitutes all possible mitigation measures recently introduced in the scientific discussion. In Energy Plus Food scenario, farms increasingly produce renewable energy in addition to food and, therefore, have new opportunities to develop their businesses. The Delphi panel estimated how the farms would cope with different future developments represented by the scenarios. Based on our results, it is evident that interdisciplinary analysis in research and inter-sectoral cooperation between agricultural and energy policies are required.

India–ASEAN Free Trade Agreement: An ex post evaluation

Ex post effects of the India–ASEAN Free Trade Agreement reveal that India's balance of trade with ASEAN has deteriorated and there is a weak correspondence between tariff reforms and trade expansion. The aggregate value of the net surplus with the government after taxing gainers and subsidizing losers was positive up to 2012 but has been declining ever since and became negative 2013 as trade with the rest of the world has fallen for both India as well as ASEAN owing to the global slowdown. We show that had the slowdown not been there the surplus would always have been positive for India. We also propose two alternative policy scenarios where the surplus would always have been positive: an FTA with rest of the world and a schedule where tariff elastic goods were given priority.

What is needed to phase out residential oil heating in Finnish single-family houses?

There are approximately 200,000 single-family houses heated with oil in Finland and the substitution of oil heating embodies significant carbon dioxide emission reduction potential in the residential sector. We analyze the economics of replacing oil heating with a ground source heat pump (GSHP) or a pellet heating from the consumers’ perspective in alternative policy and oil price scenarios. We differentiated between cases where the oil burner is replaced in the end of its lifetime or before it.The results indicate that the level and uncertainty associated with future crude oil price are major factors in the profitability of replacement. If the international oil market price remains low, an early replacement is not likely to be economical for the consumer in Finland. Yet, with a recovering oil price even an early replacement can be optimal. If oil burner cannot be used anymore, it is in most scenarios economical to replace it with pellet or GSHP if some subsidy for heating renovation is available. Subsidies improve the profitability of both pellet and GSHP investments more than fuel taxation. Consumer discount rate also affects the results.

Environmental impacts of coal subsidies in Turkey: A general equilibrium analysis

In this study we aim at providing an analytical framework for Turkey to study the macroeconomics and environmental impacts of the existing coal subsidization scheme. To this end we develop a regionally differentiated applied general equilibrium model spanning over 2015–2030. Our analytical apparatus focuses exclusively on the fiscal implications as well as the environmental repercussions of the removal of the subsidies on greenhouse gas emissions. With the aid of a set of alternative policy scenarios against a “business as usual” path, we study the regional and sectorial performances of growth, employment, investment and capital accumulation, consumption/welfare and trade balance. Our results indicate that by simple elimination of the coal subsidization scheme, Turkey can reduce its aggregate gaseous emissions by as much as 5% without a significant loss in its GDP.

Simulating land use changes under alternative policy scenarios for conservation of native forests in south-central Chile

In this study, we combined policy analysis with landscape change modeling to simulate outcomes of alternative forest conservation instruments proposed by opposing policy coalitions. In 1992, concern over rapid land conversion to timber plantations (Pinus radiata and Eucalyptus spp.) in Chile gave rise to a protracted policy process resulting in the 2008 Native Forest Law (NFL), which subsidizes reforestation and management with native forest. To date, however, NFL has had little impact on native forest conservation. To understand how the policy process that created the NFL shaped its outcomes, we employed the Dyna-CLUE modeling approach to simulate land use changes in south-central Chile from 1993 to 2007, based on 3 scenarios: (1) enactment of NFL in 1993 when the law was originally debated, and the different configurations of subsidies and regulations proposed in the NFL policy debate by (2) the industrial forestry coalition and (3) the forest conservation coalition. We observed no major difference in native forest loss between simulated outcomes of the industry-advocated policy and the actual NFL legislation. The conservation coalition’s policy scenario increased native forest area, primarily in shrub steppe areas, but also via conversion of pine plantations if incentive payments were large enough. However, NFL payments are inadequate to make native forest management a viable economic land use alternative to industrial pine plantations, which are also subsidized in Chile. Gains in native forest cover occurred mostly on lands under ancestral indigenous claims (unrelated to the discussion of the NFL). We conclude that the NFL, even if enacted in 1993, would have been ineffective in preventing native forest loss, because tree plantations are more profitable and NFL regulations were weakened by the industrial coalition that opposed—and strongly shaped—the final legislation. Effective incentives for protecting early-successional forests and shrublands are needed to mitigate further losses and foster recovery of Chile’s native forests.

Quality-related regional differences in entrepreneurship based on the GEDI methodology: The case of Hungary

This paper presents a regional application of the Global Entrepreneurship and Development Index (GEDI) methodology of Acs et al. (2013) to examine the level of entrepreneurship across Hungary’s seven NUTS-2 level regions between 2006 and 2012. The Regional Entrepreneurship and Development Index (REDI) has been constructed for capturing the individual efforts, and their contextual features, of entrepreneurship across regions. The REDI method builds on a Systems of Entrepreneurship Theory and provides a way to profile Regional Systems of Entrepreneurship. Important aspects of the REDI method include the Penalty for Bottleneck analysis, which helps in identifying constraining factors in Regional Systems of Entrepreneurship, and Policy Portfolio Optimisation analysis, which helps policymakers consider trade-offs between alternative policy scenarios and associated allocations of policy resources. The paper describes the entrepreneurial disparities amongst Hungarian regions and provides public policy suggestions to improve the level of entrepreneurship and to optimise resource allocation over the 14 pillars of entrepreneurship in the seven Hungarian regions.

Impact of air pollutants from surface transport sources on human health: A modeling and epidemiological approach

This study adopted an integrated ‘source-to-receptor’ assessment paradigm in order to determine the effects of emissions from passenger transport on urban air quality and human health in the megacity, Delhi. The emission modeling was carried out for the base year 2007 and three alternate (ALT) policy scenarios along with a business as usual (BAU) scenario for the year 2021. An Activity-Structure-Emission Factor (ASF) framework was adapted for emission modeling, followed by a grid-wise air quality assessment using AERMOD and a health impact assessment using an epidemiological approach. It was observed that a 2021-ALT-III scenario resulted in a maximum concentration reduction of ~24%, ~42% and ~58% for carbon monoxide (CO), nitrogen dioxide (NO2) and particulate matter (PM), respectively, compared to a 2021-BAU scenario. Further, it results in significant reductions in respiratory and cardiovascular mortality, morbidity and Disability Adjusted Life Years (DALY) by 41% and 58% on exposure to PM2.5 and NO2 concentrations when compared to the 2021-BAU scenario, respectively. In other words, a mix of proposed policy interventions namely the full-phased introduction of the Integrated Mass Transit System, fixed bus speed, stringent vehicle emission norms and a hike in parking fees for private vehicles would help in strengthening the capability of passenger transport to cater to a growing transport demand with a minimum health burden in the Delhi region. Further, the study estimated that the transport of goods would be responsible for ~5.5% additional VKT in the 2021-BAU scenario; however, it will contribute ~49% and ~55% additional NO2 and PM2.5 concentrations, respectively, in the Delhi region. Implementation of diesel particulate filters for goods vehicles in the 2021-ALT-IV-O scenario would help in the reduction of ~87% of PM2.5 concentration, compared to the 2021-BAU scenario; translating into a gain of 1267 and 505 DALY per million people from exposure to PM2.5 and NO2 concentrations, respectively. These findings suggest that significant health benefits are possible if goods transport is also included while designing strategies and polices in order to improve the overall urban air quality and minimize health impacts in city areas.

Reconciling oil palm expansion and climate change mitigation in Kalimantan, Indonesia.

Our society faces the pressing challenge of increasing agricultural production while minimizing negative consequences on ecosystems and the global climate. Indonesia, which has pledged to reduce greenhouse gas (GHG) emissions from deforestation while doubling production of several major agricultural commodities, exemplifies this challenge. Here we focus on palm oil, the world’s most abundant vegetable oil and a commodity that has contributed significantly to Indonesia’s economy. Most oil palm expansion in the country has occurred at the expense of forests, resulting in significant GHG emissions. We examine the extent to which land management policies can resolve the apparently conflicting goals of oil palm expansion and GHG mitigation in Kalimantan, a major oil palm growing region of Indonesia. Using a logistic regression model to predict the locations of new oil palm between 2010 and 2020 we evaluate the impacts of six alternative policy scenarios on future emissions. We estimate net emissions of 128.4–211.4 MtCO2 yr-1 under business as usual expansion of oil palm plantations. The impact of diverting new plantations to low carbon stock land depends on the design of the policy. We estimate that emissions can be reduced by 9-10% by extending the current moratorium on new concessions in primary forests and peat lands, 35% by limiting expansion on all peat and forestlands, 46% by limiting expansion to areas with moderate carbon stocks, and 55–60% by limiting expansion to areas with low carbon stocks. Our results suggest that these policies would reduce oil palm profits only moderately but would vary greatly in terms of cost-effectiveness of emissions reductions. We conclude that a carefully designed and implemented oil palm expansion plan can contribute significantly towards Indonesia’s national emissions mitigation goal, while allowing oil palm area to double.

Planning robust policing futures: modelling using multimethodology

Purpose– The resourcing of policing activity is characterised by a level of complexity, particularly where evaluating alternative policy options is concerned. In this paper, a case study using multimethodological modelling to compare alterative policy choice in a group context is outlined with respect to response-patrol officer (RPO) deployment within a UK police force. The paper aims to discuss these issues.Design/methodology/approach– The application of a three phase modelling process is illustrated where scenario planning is used to generate the scope of the system elements to be modelled. This is followed by causal mapping to identify the barriers to improving officer resourcing, and system dynamics modelling is used to simulate the impacts of a range of policy options within this policing function. A group model building approach was applied throughout the modelling phases with an expert group to negotiate a shared view of the structure and dynamics of the resourcing policy challenges.Findings– A fully validated system dynamics model emerged from the multi-phase modelling process which allowed a series of alternative future policy scenarios to be explored and evaluated. Useful policy insights were generated by the system dynamics simulation model which suggested more efficient rules for resource allocation in the police force’s RPO function.Originality/value– The insights from this case study demonstrates that multi-phase modelling has potential application in policy exploration across a range of emergency service providers whose actions are governed by both variable demand and constrained supply of resource.