CO2 Constraints Research Articles

Regional disparities in health and employment outcomes of China’s transition to a low-carbon electricity system

Understanding the costs and the spatial distribution of health and employment outcomes of low-carbon electricity pathways is critical to enable an equitable transition. We integrate an electricity system planning model (GridPath), a health impact model (InMAP), and a multiregional input–output model to quantify China’s provincial-level impacts of electricity system decarbonization on costs, health outcomes, employment, and labor compensation. We find that even without specific CO2 constraints, declining renewable energy and storage costs enable a 26% decline in CO2 emissions in 2040 compared to 2020 under the Reference scenario. Compared to the Reference scenario, pursuing 2 °C and 1.5 °C compatible carbon emission targets (85% and 99% decrease in 2040 CO2 emissions relative to 2020 levels, respectively) reduces air pollution-related premature deaths from electricity generation over 2020–2040 by 51% and 63%, but substantially increases annual average costs per unit of electricity demand in 2040 (21% and 39%, respectively). While the 2 °C pathway leads to a 3% increase in electricity sector-related net labor compensation, the 1.5 °C pathway results in a 19% increase in labor compensation driven by greater renewable energy deployment. Although disparities in health impacts across provinces narrow as fossil fuels phase out, disparities in labor compensation widen with wealthier East Coast provinces gaining the most in labor compensation because of materials and equipment manufacturing, and offshore wind deployment.

Numerical algorithm for environmental/economic load dispatch with emissions constraints

This paper presents a numerical algorithm for environmental/economic load dispatch (EELD) with emissions constraints, which takes into account the emissions trading system’s effect on electricity generation cost and is implemented using a Python computer program. The developed program is applied to a power system of six (6) fossil-fueled electricity generating units with NOx, SO2 and CO2 constraints and proved to be significantly beneficial not only for the environment but also for the power company and the consumers. The proposed algorithm uses multi-objective optimization and incorporates both fuel and emissions allowances costs. The schedule of generating units is calculated and the testing of all possible weighting factor combinations with resolution of 0.01 is carried out showing that the proposed algorithm is fast, cost effective and environmentally friendly.

Renewable electricity capacity planning with uncertainty at multiple scales

We formulate and compare optimization models of investment in renewable generation using a suite of social planning models that compute optimal generation capacity investments for a hydro-dominated electricity system where inflow uncertainty results in a risk of energy shortage. The models optimize the expected cost of capacity expansion and operation allowing for investments in hydro, geothermal, solar, wind, and thermal plant, as well as battery storage for smoothing load profiles. A novel feature is the integration of uncertain seasonal hydroelectric energy supply and short-term variability in renewable supply in a two-stage stochastic programming framework. The models are applied to data from the New Zealand electricity system and used to estimate the costs of moving to a 100% renewable electricity system by 2035. We also explore the outcomes obtained when applying different forms of CO2 constraint that limit respectively non-renewable capacity, non-renewable generation, and CO2 emissions on average, almost surely, or in a chance-constrained setting, and show how our models can be used to investigate the merits of a proposed pumped-hydro scheme in New Zealand’s South Island.

Bi-level and multi-objective optimization of renewable energy sources and storage planning to support existing overloaded electricity grids

The paper proposes a bi-level multi-objective optimization model to optimally design and operate renewable energy sources and storage systems in an existing electrical grid with increasing demand. while respecting network constraints based. The bi-level optimization model combines particle swarm optimization (PSO) and dynamic linear AC-optimal power flow (DLOPF). The aim of the bi-objective model is to minimize costs while limiting carbon emissions. PSO sizes and identifies the placement of battery energy storage (BES) systems, and DLOPF locates and sizes RES in a spatial–temporal framework using the Levelized Cost of Energy and Storage. Different scenarios were applied to the IEEE-30 bus system to reveal the behavior of the dynamic network for the different cases, and the associated effect of integrating RES and BES. The model resulted in optimized scenarios in terms of placement and sizing of RES and BES at the lowest cost while considering cost minimization and carbon constraints. This shows how the complexity of the CO2 constraints requires more RES and BES installations and thus more funds. The maximum CO2 limit achieved is 30%, which has reached the storage limits and increased the overall cost by $15 m.

Multi-Objective Optimization of Steel Off-Gas in Cogeneration Using the ε-Constraint Method: A Combined Coke Oven and Converter Gas Case Study

Increasingly demanding environmental regulations are forcing companies to reduce their impacts caused by their activity while defending the economic viability of their manufacturing processes, especially energy and carbon-intensive ones. Therefore, these challenges must be addressed by posing optimization problems that involve several objectives simultaneously, corresponding to different conditions, and often conflicting between. In this study, the residual gases of an integral steel factory were evaluated and modeled with the goal of developing an optimization problem considering two opposing objectives: CO2 emissions and profit. The problem was first approached in a mono-objective manner, optimizing profit through Mixed Integer Linear Programming (MILP), and then was extended to a bi-objective problem solved by means of the ε-constraint method, to find the Pareto front relating profit and CO2 emissions. The results show that multiobjective optimization is a very valuable resource for plant managers’ decision-making processes. The model makes it possible to identify inflection points from which the level of emissions would increase disproportionately. It gives priority to the consumption of less polluting fuels. The model also makes it possible to make the most of temporary buffers such as the gas holders, adapting to the hourly price of the electricity market. By applying this method, CO2 emissions decrease by more than 3%, and profit amounts up to 14.8% compared to a regular case under normal operating conditions. The sensitivity analysis of the CO2 price and CO2 constraints is also performed.

Contradictions of low-emission nZEB buildings

Based on the EPBD 2010 directive and the mandated method of cost-optimum calculation the forthcoming national regulations require “nearly zero energy buildings” which have high energy performance, significant share of renewables in covering the low energy need and harmonizing the requirement system and the cost-optimum all over in Europe. Known intention of the EU Member States as well as some research reports create the impression that predominant use of biomass in the forthcoming years will be the right way to fulfil the above requirements of nearly zero energy buildings. Taking advantage of regulations in many Member States, the amount of yearly primary energy demand is favourably influenced by the low primary energy conversion factor determined by the very states; besides the delivered energy does not decrease. The CO2 neutrality of biomass is not real. It is true that the emission of gas firing far exceeds that of wood firing, but emissions from the production of natural gas might be lower than that of the production of certain wood products. Overall, the lifecycle-based emission of biomass firing for the most converted fuels is already significant. In the case of wood combustion, the local pollutant emissions, which occur in cities, are significant, while the CO2 constraint take place in the forests.

Electric Vehicles as Flexibility Management Strategy for the Electricity System—A Comparison between Different Regions of Europe

This study considers whether electric vehicles (EVs) can be exploited as a flexibility management strategy to stimulate investments in and operation of renewable electricity under stringent CO2 constraints in four regions with different conditions for renewable electricity (Sweden, Germany, the UK, and Spain). The study applies a cost-minimisation investment model and an electricity dispatch model of the European electricity system, assuming three types of charging strategies for EVs. The results show that vehicle-to-grid (V2G), i.e., the possibility to discharging the EV batteries back to grid, facilitates an increase in investments and generation from solar photovoltaics (PVs) compare to the scenario without EVs, in all regions except Sweden. Without the possibility to store electricity in EV batteries across different days, which is a technical limitation of this type of model, EVs increase the share of wind power by only a few percentage points in Sweden, even if Sweden is a region with good conditions for wind power. Full electrification of the road transport sector, including also dynamic power transfer for trucks and buses, would decrease the need for investments in peak power in all four regions by at least 50%, as compared to a scenario without EVs or with uncontrolled charging of EVs, provided that an optimal charging strategy and V2G are implemented for the passenger vehicles.

The U.S. power sector decarbonization: Investigating technology options with MARKAL nine-region model

The U.S. economy decarbonization over the next 35 years requires a large transformation of the energy system. The main finding of this study is that it is technically feasible to achieve 80% greenhouse gas (GHG) emissions reduction below the 2005 levels by 2050 through deployment of existing or near-commercially available technologies. GHG reductions are primarily achieved through high levels of electricity sector decarbonization, electrification of end uses, and exchange of the remaining end-uses to lower carbon fuels such as natural gas. However, deep decarbonization by 2050 triggers very high marginal CO2 reduction costs, unless significant cost reductions of zero and near-zero carbon technologies occur.The results show that CO2 reduction policies accelerate the deployment of renewables and carbon capture and storage (CCS) only in the scenarios where the decarbonization policies are more stringent than those in the Clean Power Plan (CPP). Electricity generation mixes in the reference scenarios are largely dependent on the price of natural gas, but also show significant sensitivity to cost reductions in CCS. When increased CCS learning rates are incorporated into the model runs, more CCS is optimal in the medium-term and long-term future in the scenarios with CO2 constraints. An 80% reduction scenario also prompts electrification in end-use demand sectors, creating even more dependence on CO2 management in the electricity generation sector.

The CarbonTracker Data Assimilation System for CO<sub>2</sub> and <i>δ</i><sup>13</sup>C (CTDAS-C13 v1.0): retrieving information on land–atmosphere exchange processes

Abstract. To improve our understanding of the global carbon balance and its representation in terrestrial biosphere models, we present here a first dual-species application of the CarbonTracker Data Assimilation System (CTDAS). The system's modular design allows for assimilating multiple atmospheric trace gases simultaneously to infer exchange fluxes at the Earth surface. In the prototype discussed here, we interpret signals recorded in observed carbon dioxide (CO2) along with observed ratios of its stable isotopologues 13CO2∕12CO2 (δ13C). The latter is in particular a valuable tracer to untangle CO2 exchange from land and oceans. Potentially, it can also be used as a proxy for continent-wide drought stress in plants, largely because the ratio of 13CO2 and 12CO2 molecules removed from the atmosphere by plants is dependent on moisture conditions.The dual-species CTDAS system varies the net exchange fluxes of both 13CO2 and CO2 in ocean and terrestrial biosphere models to create an ensemble of 13CO2 and CO2 fluxes that propagates through an atmospheric transport model. Based on differences between observed and simulated 13CO2 and CO2 mole fractions (and thus δ13C) our Bayesian minimization approach solves for weekly adjustments to both net fluxes and isotopic terrestrial discrimination that minimizes the difference between observed and estimated mole fractions.With this system, we are able to estimate changes in terrestrial δ13C exchange on seasonal and continental scales in the Northern Hemisphere where the observational network is most dense. Our results indicate a decrease in stomatal conductance on a continent-wide scale during a severe drought. These changes could only be detected after applying combined atmospheric CO2 and δ13C constraints as done in this work. The additional constraints on surface CO2 exchange from δ13C observations neither affected the estimated carbon fluxes nor compromised our ability to match observed CO2 variations. The prototype presented here can be of great benefit not only to study the global carbon balance but also to potentially function as a data-driven diagnostic to assess multiple leaf-level exchange parameterizations in carbon-climate models that influence the CO2, water, isotope, and energy balance.

Significance of CO2-free hydrogen globally and for Japan using a long-term global energy system analysis

In this paper, the significance of CO2-free hydrogen is discussed using a long-term global energy system. The energy demand–supply system including CO2-free hydrogen was assumed, though there are still large uncertainties as to whether a global CO2-free hydrogen energy system will be deployed. System analysis was conducted using the global and long-term intertemporal optimization energy model GRAPE under severe CO2 emission constraints. Applied global CO2 constraints for 2050 were a 50% reduction from 1990 levels. CO2 constraints accounting for Intended Nationally Determined Contributions (INDCs) in each region were also considered. A variety of energy resources and technologies were considered in this model. Hydrogen can be produced from low-grade coal or natural gas with CO2 capture and electricity from renewable energy. The hydrogen CIF (cost, insurance, and freight) price for Japan was about 3.2 cents/MJ in 2030. Hydrogen demand technologies considered in this paper are hydrogen-fired power plants, direct combustion, combined heat and power (fuel cells, gas engines, and gas turbines), fuel cell vehicles, and hydrogen internal combustion engine vehicles. The majority of CO2-free hydrogen was deployed in the transportation sector. CO2-free hydrogen was utilized in the power sector, where deployment of other zero emission technology has some constraints. From an economic viewpoint, CO2-free hydrogen can reduce the global energy system cost. From the viewpoint of a localized region, such as Japan, deployment of CO2-free hydrogen can improve energy security and environmental indicators.

Clean production pathways for regional power-generation system under emission constraints: A case study of Shanghai, China

China is now facing pressures of emission reduction both from greenhouse gases (GHGs) and local air pollutants (LAPs). Considering power generation system contributes a great share of CO2 and PM2.5 emissions, a regional power generation system modelling and optimization framework using Long-range Energy Alternatives Planning System (LEAP) is conducted in order to explore the cost-effective cleaner capacity expansion pathways under various emissions constraints. A case study of Shanghai follows, focusing on analysis of capacity additions for different power generation technologies, as well as energy inputs, reduction co-benefits and system costs. The results indicate that: i) the clean production pathways differentiate along with stricter CO2 constraints; ii) Ultra-supercritical coal-fired units have significant advantage under no emission constraint, which are substitute by cleaner power generation units such as wind power, solar power and Integrated Gasification Combined Cycle (IGCC) under the CO2 constrained scenario and the combined CO2-PM2.5 constrained scenario; iii) CO2 constraint displays stronger reduction co-benefits than that of PM2.5; iv) Emission constraints are conductive to energy savings that will increase system cost. Finally, policy recommendations are made through sensitivity analysis that only when the price of natural gas declines sharply can natural gas units become one of the alternatives that reduce coal consumption and the related CO2 emissions.

Decarbonizing the EU energy system by 2050: an important role for BECCS

This article examines the implications for the EU’s energy system if an 80% reduction in CO2 emissions is to be achieved by 2050 against 1990 levels, using the European TIMES Model (ETM-UCL) to project a least-cost pathway that meets this CO2 constraint (‘Policy Success’), along with milestone targets for 2020. A Reference scenario (no CO2 constraints post-2020) was analysed to allow for comparison. The key conclusions are as follows: (a) the achievement of negative emissions in the power sector via the use of biomass with carbon capture and storage (BECCS) allows for much more limited decarbonization in the buildings and transport sectors; (b) CCS is also extensively used for decarbonization of the industrial sector; (c) because of the absence in the model of options for transport mode-switching and building fabric efficiency improvements, the transport and buildings sectors achieve relatively little abatement by 2050 – the inclusion of these options could considerably reduce the need for BECCS and the cost of abatement; (d) decarbonization of the EU’s energy system by 2050 would increase energy system costs by 14% compared to a Reference scenario with no CO2 constraints; and (e) average EU-wide marginal CO2 abatement costs in Policy Success reach $300/tCO2 in 2050. Such a value is within the (wide) range of marginal carbon prices produced by comparable scenarios in other studies.Policy relevanceThe EU has set itself a target of reducing its greenhouse gas emissions by at least 80% by 2050, against 1990 levels. This will require a reduction of at least 80% in CO2 emissions from the energy system. This article, using results from the European TIMES Model (ETM-UCL), demonstrates that in the absence of significant decarbonization in the buildings and road transport sectors, substantial negative emissions in the power sector must be achieved, through as-yet unproven technologies (involving BECCS) . Therefore, a comprehensive strategy to reduce emissions across all energy-using sectors is required if this outcome is to be avoided. In addition, this article adds further evidence to the notion that substantial decarbonization of the EU’s energy system may be achieved through a relatively small additional investment above that required anyway.

Bioenergy futures in Sweden – Modeling integration scenarios for biofuel production

Use of bioenergy can contribute to greenhouse gas emission reductions and increased energy security. However, even though biomass is a renewable resource, the potential is limited, and efficient use of available biomass resources will become increasingly important. This paper aims to explore system interactions related to future bioenergy utilization and cost-efficient bioenergy technology choices under stringent CO2 constraints. In particular, the study investigates system effects linked to integration of advanced biofuel production with district heating and industry under different developments in the electricity sector and biomass supply system. The study is based on analysis with the MARKAL_Sweden model, which is a bottom-up, cost-optimization model covering the Swedish energy system. A time horizon to 2050 is applied. The results suggest that system integration of biofuel production has noteworthy effects on the overall system level, improves system cost-efficiency and influences parameters such as biomass price, marginal CO2 emission reduction costs and cost-efficient biofuel choices in the transport sector. In the long run and under stringent CO2 constraints, system integration of biofuel production has, however, low impact on total bioenergy use, which is largely decided by supply-related constraints, and on total transport biofuel use, which to large extent is driven by demand.

Connecting water and energy: Assessing the impacts of carbon and water constraints on China’s power sector

Energy, water and carbon are inextricably linked. The limited endowments, uneven temporal and spatial distribution of energy and water resources pose great challenges to China’s sustainable development. In this paper, a bottom-up model (China TIMES model) is developed to integrate China’s energy system with water resources, to project water demand in power sector and to assess the impacts of China’s Intended Nationally Determined Contributions (INDC) and water constraints on power generation portfolio out to the year 2050. The modelling results show that: (1) under reference scenario, electricity generation will increase from 4518TWh in 2010 to 13,270TWh in 2050, with CO2 emission from 3.1Gt to 6.1Gt and water withdrawal from 59Gm3 to 104Gm3; (2) CO2 mitigation target can help reduce water withdrawal in power sector by promoting the expansion of renewable technologies; (3) by affecting the cooling mixture, water cost has significant impact on water withdrawal in power sector; (4) when both CO2 and water constraints are considered, renewable technologies will be more prevalent.

Incorporating travel behaviour and travel time into TIMES energy system models

Achieving ambitious climate change mitigation targets clearly requires a focus on transport that should include changes in travel behaviour in addition to increased vehicle efficiency and low-carbon fuels. Most available energy/economy/environment/engineering (E4) modelling tools focus however on technology and fuel switching and tend to poorly incorporate mitigation options from travel behaviour, and in particular, switching between modes is not an option. This paper describes a novel methodology for incorporating competition between private cars, buses and trains in a least-cost linear optimisation E4 model, called TIMES. This is achieved by imposing a constraint on overall travel time in the system, which represents the empirically observed fixed travel time budget (TTB) of individuals, and introducing a cost for infrastructural investments (travel time investment, TTI), which reduces the travel time of public transport. Two case studies from California and Ireland are developed using a simple TIMES model, and results are generated to 2030 for a reference scenario, an investments scenario and a CO2 emissions reduction scenario. The results show that with no travel time constraint, the model chooses public transport exclusively. With a travel time constraint, mode choice is determined by income and investment cost assumptions, and the level of CO2 constraint, with greater levels of public transport in the mitigation scenario. At low travel investment cost, new rail is introduced for short distances and increased bus capacity for longer distances. At higher investment costs rail is increasingly chosen for long distances also.

Environmental tax reforms in Switzerland a computable general Equilibrium impact analysis

Summary The Swiss energy strategy until 2050 envisages ambitious CO2 emission reduction targets along with substantial cutbacks in electricity consumption to establish a low-carbon economy without nuclear energy. Our computable general equilibrium analysis finds that compliance with stringent CO2 constraints requires high CO2 taxes on economic activities which are not eligible for international emissions trading; likewise, electricity consumers are burdened with substantial electricity taxes. Environmental tax reforms are not likely to generate welfare gains without accounting for the benefits of improved environmental quality. However, economic adjustment costs to a low carbon economy without nuclear energy remain modest and can be markedly reduced through revenue-neutral cuts of initial distortionary taxes. On the other hand, alternative recycling strategies pose a trade-off between efficiency and distributional justice which has to be resolved on normative grounds.

A study on forecasting paths of genuine savings and wealth without and with carbon dioxide constraints: development of shadow price functions

This paper has developed a method for forecasting the future paths of genuine savings (GS) with and without carbon dioxide (CO2) emissions constraints. GS calculations require shadow prices, which can be endogenously determined for variables and constraints in a model. However, in case of a ‘business as usual’ model (BAU), the shadow prices required for calculating GS without constraints show theoretically zero. This research derives the shadow prices required to measure GS for the BAU case as a function of several variables available in the optimal (economically efficient) case. This function is estimated from endogenously obtained variables from a model with environmental constraints. Subsequently, this function is used to calculate shadow prices with and without CO2 constraints, which are further employed to compute future paths of GS according to two methods applied in the papers by Arrow et al. We successfully estimated GS (or GSnt; GS with changes in population and technology) under the BAU case, however, suggest that GS (or GSnt) measures depend, to a great extent, on the time span under consideration (truncation year) for wealth accounting and the accounting methods by Arrows’ papers used for its estimation. In some cases, especially according to the methodology used by Arrow’s paper in 2004 using adjusted consumption in wealth accounting, the sign of GS (or GSnt) changes from negative to positive when changes in total factor productivity are taken into consideration. These aspects should be explored before measuring (un)sustainability of a particular path based on the GS (or GSnt) indicator.

Hospitable Archean Climates Simulated by a General Circulation Model

Evidence from ancient sediments indicates that liquid water and primitive life were present during the Archean despite the faint young Sun. To date, studies of Archean climate typically utilize simplified one-dimensional models that ignore clouds and ice. Here, we use an atmospheric general circulation model coupled to a mixed-layer ocean model to simulate the climate circa 2.8 billion years ago when the Sun was 20% dimmer than it is today. Surface properties are assumed to be equal to those of the present day, while ocean heat transport varies as a function of sea ice extent. Present climate is duplicated with 0.06 bar of CO2 or alternatively with 0.02 bar of CO2 and 0.001 bar of CH4. Hot Archean climates, as implied by some isotopic reconstructions of ancient marine cherts, are unattainable even in our warmest simulation having 0.2 bar of CO2 and 0.001 bar of CH4. However, cooler climates with significant polar ice, but still dominated by open ocean, can be maintained with modest greenhouse gas amounts, posing no contradiction with CO2 constraints deduced from paleosols or with practical limitations on CH4 due to the formation of optically thick organic hazes. Our results indicate that a weak version of the faint young Sun paradox, requiring only that some portion of the planet's surface maintain liquid water, may be resolved with moderate greenhouse gas inventories. Thus, hospitable late Archean climates are easily obtained in our climate model.

Prospects for Coalbed Methane and Shale Gas in a Carbon-Constrained World: A Preliminary Analysis

Using a regionally disaggregated global energy system model with a detailed treatment of the natural gas resource base, this paper analyzes the competitiveness of coalbed methane and shale gas in the global primary energy mix and the cost-optimal pattern of their production in regional detail over the period 2010-2050 under a constraint of halving global energy-related CO2 emissions in 2050 compared to the 2000 level. It is first shown that neither coalbed methane nor shale gas could become an important fuel in the global primary energy mix throughout the time horizon, although each of them could become an important source of world natural gas production from around 2030 onwards. It is then shown that unlike findings of previous studies, coalbed methane would be more attractive than shale gas as a primary energy source globally under the CO2 constraint used here. The results indicate that North America continues to be the world’s largest coalbed methane producer until 2030, after which China overtakes North America and retains this position until 2050. Also, India, Russia, South Africa, and Australia contribute noticeably to world coalbed methane production. The results also indicate that North America continues to dominate world shale gas production until 2040, after which a number of world regions, notably India, Europe, and China, begin to participate visibly in world shale gas production.

Prospects for Renewable and Fossil-Based Electricity Generation in a Carbon-Constrained World

In this paper, a regionally disaggregated global energy system model with a detailed treatment of the electricity supply sector is used to derive the cost-optimal choice of electricity generation technologies for each of 70 world regions over the period 2010-2050 under a constraint of halving global energy-related CO2 emissions in 2050 compared to the 2000 level. It is first shown that the long-term global electricity generation mix under the CO2 constraint becomes highly diversified, which includes coal, natural gas, nuclear, biomass, hydro, geothermal, onshore and offshore wind, solar photovoltaics (PV), and concentrated solar power (CSP). In this carbon-constrained world, 89.9% of the electricity generation from coal, natural gas, and biomass is combined with CO2 capture and storage (CCS) in 2050. It is then shown that the long-term electricity generation mix under the CO2 constraint varies significantly by world region. Fossil fuels with CCS enter the long-term electricity generation mix in all world regions. In contrast, there is a sharp regional difference in the renewable generation technology of choice in the long term. For example, the world regions suitable for PV plants include the US, Western Europe, Japan, Korea, and China, while those suitable for CSP plants include the Middle East, Africa, Australia, and western Asia. Offshore wind is deployed on a large scale in the UK, Ireland, Nordic countries, the southern part of Latin America, and Japan.