New Zealand's emissions trading scheme

Jiang, Nan; Sharp, Basil; Sheng, Mingyue

doi:10.1080/00779950902803993

Cited by 30 publications

(21 citation statements)

References 3 publications

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“…The set U D is the projection of U on the space of the data for constraint (37). Note that (P1) has a form similar to Problem RS omitting (29)- (31) and the binary restrictions on some variables.…”

Section: Hybrid Modelmentioning

confidence: 99%

“…For example, in 2005 the European Union instituted a carbon emission trading scheme (EU ETS) for the energy-intensive industries with the aim of reducing greenhouse gas emissions by at least 20% below 1990 levels [16]. Also, the New Zealand Emissions Trading Scheme (NZ ETS) was introduced in 2009 [37]. In 2012, Australia introduced a carbon tax of $23 AUD per tonne of emitted CO2 on selected fossil fuels consumption [42].…”

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confidence: 99%

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Robust design of a closed-loop supply chain network for uncertain carbon regulations and random product flows

Gao

Ryan

2014

EURO Journal on Transportation and Logistics

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This paper addresses a multi-period capacitated closed-loop supply chain (CLSC) network design problem subject to uncertainties in the demands and returns as well as the potential carbon emission regulations. Two promising regulatory policy settings are considered: namely, (a) a carbon cap and trade system, or (b) a tax on the amount of carbon emissions. A traditional CLSC network design model using stochastic programming is extended to integrate robust optimization to account for regulations of the carbon emissions caused by transportation. We propose a hybrid model to account for both regulatory policies and derive tractable robust counterparts under box and ellipsoidal uncertainty sets. Implications for network configuration, product allocation and transportation configuration are obtained via a detailed case study. We also present computational results that illustrate how the problem formulation under an ellipsoidal uncertainty set allows the decision maker to balance the trade-off between robustness and performance. The proposed method yields solutions that provide protection against the worst-case scenario without being too conservative. Abstract This paper addresses a multi-period capacitated closed-loop supply chain (CLSC) network design problem subject to uncertainties in the demands and returns as well as the potential carbon emission regulations. Two promising regulatory policy settings are considered; namely, (a) a carbon cap and trade system, or (b) a tax on the amount of carbon emissions. A traditional CLSC network design model using stochastic programming is extended to integrate robust optimization to account for regulations of the carbon emissions caused by transportation. We propose a hybrid model to account for both regulatory policies and derive tractable robust counterparts under box and ellipsoidal uncertainty sets. Implications for network configuration, product allocation and transportation configuration are obtained via a detailed case study. We also present computational results that illustrate how the problem formulation under an ellipsoidal uncertainty set allows the decision maker to balance the trade-off between robustness and performance. The proposed method yields solutions that provide protection against the worst case scenario without being too conservative.

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Section: Hybrid Modelmentioning

confidence: 99%

mentioning

confidence: 99%

Robust design of a closed-loop supply chain network for uncertain carbon regulations and random product flows

Gao

Ryan

2014

EURO Journal on Transportation and Logistics

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“…From 1992, New Zealand became a net importer of N fertilizer and, in 2005, 72.5% of N fertilizer used was imported (Jiang et al, 2009). …”

Section: Fertilizermentioning

confidence: 99%

Determination and modelling of energy consumption in wheat production using neural networks: “A case study in Canterbury province, New Zealand”

Safa

Samarasinghe

2011

Energy

116

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New Zealand farmers practice a form of ‗industrialised' agriculture that relies on relatively high inputs of fossil fuels, not only to power machinery directly but also for manufacturing artificial fertilizers and agrichemicals (Wells, 2001). Consequently, New Zealand is one of the countries with the highest energy input per unit weight (in agriculture) in the world (Conforti & Giampietro, 1997). Furthermore, in terms of shipping, the influence of increasing global fuel costs is greater on New Zealand farming than in other countries. The main aim of this study was to estimate energy consumption in wheat production. Energy determination can give a clear picture of farms in order to compare different farming systems and energy inputs. The second main target of this study was to develop a neural network model to simulate and predict energy use in wheat production under different conditions incorporating social, geographical, and technical factors. Additionally, the interaction effects between different factors were examined in this study.This study was conducted on irrigated and dryland wheat fields in Canterbury, New Zealand, in the 2007-2008 harvest year. Canterbury represents 87% of the wheat area and 66% of the arable area harvested in New Zealand.Energy consumption here is defined as the energy used for the production of wheat until it leaves the farm. The data were collected from three different sources:questionnaire, literature review, and field measurements. The energy inputs estimated in this study are those that go into on-farm production systems before the post-harvest processes. The study considered only the energy used in wheat production, without taking into account the natural sources of energy (radiation, wind, rain, etc). IVA survey was conducted to collect the most important data and to identify farmers' attitudes and opinions about energy consumption. In this study, 40 arable farms were selected randomly, as far as possible. From the initial analysis, it was found that 30 farms were irrigated and the rest were dryland farms. Irrigated farms were irrigated between one to ten times annually depending on the rainfall. Some irrigated farms have also been converted to dryland farms, or vice versa, in different years. The data for a large number of farming factors were gathered in the survey.Average energy consumption for wheat production was estimated at around 22,600 MJ/ha. On average, fertilizer and electricity (mostly for irrigation) were used more than other energy sources, at around 10,654 MJ/ha (47%) and 4,870 MJ/ha (22%), respectively. The average energy consumption for wheat production in irrigated farming systems and dryland farming systems was estimated at 25,600 and 17,458 MJ/ha, respectively. This study is the first to create an appropriate Artificial Neural Network (ANN) model to predict energy consumption in wheat production with optimum variables. This study would be the first to investigate the factors related to the efficient use of energy in agricultural production. A careful study o...

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“…In the following sub-sections, the contributions of these articles and their results are discussed in greater detail. Data for two PES schemes were used in Articles II, III, and IV: (1) a market-based climate mitigation focused PES scheme comparable to the New Zealand Emissions Trading Scheme (NZ ETS) (Jiang et al 2009) using European Union Emissions Trading Scheme (EU ETS) futures prices to determine compensation, and (2) a government initiated biodiversity conservation focused PES scheme based on the Finnish governments' Trading in Nature (Natural) Values (TNV) scheme that uses private bids for service provisioning contracts (Juutinen et al 2013). The climate regulating PES scheme was evaluated in all three studies, and the biodiversity conservation PES scheme only considered in Articles II and III.…”

Section: Methodology and Resultsmentioning

confidence: 99%

A service-dominant perspective on payments for ecosystem service offerings

Matthies¹

2016

Diss. For.

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The ecosystem service (ES) approach is a means of evaluating service value flows from ecosystems to humans for their wellbeing. The approach suggests that ecosystem functions are divided into categories according to the benefits derived and utilized by beneficiaries. The ES approach has become a tool for public and private decision-makers, driven by the need to more accurately incorporate environmental externalities into the value creation processes of economic actors.This research addresses two knowledge gaps within the ES literature. First, a service-centric approach to ES offerings is lacking, resulting in misuse of the appropriate concepts and terms when discussing their role in value networks and value creation. Second, there is limited available knowledge about how to efficiently internalize ES offerings within value networks.In the first article, a service-dominant value creation (SVC) framework, with supporting terms and concepts, was developed to guide interdisciplinary discussions about the role of ES offerings within value creation processes. The term value-in-impact was proposed as a means for discussing the trade-offs and impacts concerning ES offerings within those processes.The subsequent three articles addressed the following design aspects of Payment for Ecosystem Service (PES) schemes: (1) sensitivity to parameter inputs, (2) price volatility impacts on service providers, and (3) behavioural economic contributions. Consideration for trade-offs among ES offerings, and between ES offerings and economic objectives were also incorporated. The results indicated that the holistic accounting of ES indicators, to determine the optimal species mixtures, and uncorrelated ES price interactions, to determine the optimal allocation of forest for conservation, led to ecological and financial diversification benefits for service providers. Nudging service providers also led to more socially efficient ES provisioning. In each case, the proposed Ecosystem Service Expectation Value (ESEV) was used to more accurately describe the perpetual provisioning of multiple ES offerings on forestland.

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New Zealand's emissions trading scheme

Cited by 30 publications

References 3 publications

Robust design of a closed-loop supply chain network for uncertain carbon regulations and random product flows

Robust design of a closed-loop supply chain network for uncertain carbon regulations and random product flows

Determination and modelling of energy consumption in wheat production using neural networks: “A case study in Canterbury province, New Zealand”

A service-dominant perspective on payments for ecosystem service offerings

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