Limited increases in Arctic offshore oil and gas production with climate change and the implications for energy markets

Climate change impacts on sea ice thickness is opening access to offshore Arctic resources. The degree to which these resources are exploited will depend on sea-ice conditions, technology costs, international energy markets, and the regulatory environment. We use an integrated human-Earth system model, GCAM, to explore the effects of spatial-temporal patterns of sea-ice loss under climate change on future Arctic offshore oil and gas extraction, considering interactions with global energy markets and emission reduction scenarios. We find that under SSP5, a "fossil-fueled development" scenario, the effects of sea-ice loss are larger for Arctic offshore oil production than gas. Under SSP5, future extraction of Arctic offshore oil and gas through 2100 adds roughly 0.8-2.6 EJ/year to oil and gas markets but does not have large impacts on global oil and gas markets. Surprisingly, a low-carbon scenario results in greater Arctic offshore oil production to offset the more emissions-intensive unconventional oil production.

China's energy-water-land system co-evolution under carbon neutrality goal and climate impacts

China's 2060 carbon neutrality goal has significant implications for energy, water, and land systems. However, the multi-sector dynamics among China's energy-water-land system have rarely been examined explicitly. This study adopts an integrated assessment framework to simulate China's energy-water-land system co-evolution under alternative carbon neutrality scenarios and climate impacts. Results show that although the net zero emission target provides the incentive for the energy system to move away from fossil fuels, total water withdrawal will increase due to the deployment of nuclear, bioenergy, and coal power plants with carbon capture and storage. Diversifying the negative emission technologies, by leveraging direct air capture technology, can alleviate the potential water stress and land use conflicts, which would otherwise be exacerbated by large-scale deployment of afforestation and bioenergy with carbon capture and storage. Northwest and northeast regions of China are the hotspots experiencing water withdrawal increases, while Bohai Rim and coastal regions are identified to experience fierce land competition. This study demonstrates the potential for general applicability to carry out resource planning and policy evaluation from the multi-sector coordination perspective.

Embedding nature-based solutions into the social cost of carbon

China, the world's largest CO₂ emitter, is making every effort to transition to a low-carbon economy and fulfill its part of a concerted global commitment to combating climate change. In tandem with decarbonizing energy and industries, feasible supplementary measures are urgently needed to help remove anthropogenic CO₂ from the atmosphere. A burgeoning literature has emphasized the CO₂ removal capability of land re-naturalization (such as afforestation and wetland restoration), thereby regarding cognate land-use conversions as Nature-based Solutions (NbS) and potential climate policy options. However, little empirical evidence exists concerning the effectiveness of different land re-naturalization pathways (such as converting wetlands to forests or agricultural lands to grasslands), and it also remains unclear how NbS alternatives (i.e., land-use conversions resulting in negative CO₂ emission) and non-NbS options (i.e., land-use conversions resulting in positive CO₂ emission) could affect the social cost of carbon (SCC), a conventional measurement for prescribing carbon mitigation approaches. This study aims to fill in this knowledge gap via embedding NbS into the dynamic integrated climate-economics (DICE) model to quantify their impacts on the SCC. Using the Pearl River Delta region (south China) as a case study for the temporal horizon during 2000-2020, we find that both positive and negative CO₂ fluxes have been brought by different natural/semi-natural land conversions, affecting the SCC correspondingly. A total of 7 out of 17 types of land-use conversions could be identified as feasible NbS interventions, including forest restoration, forest-to-wetland, grassland-to-forest, grassland-to-wetland, grassland-to-cropland, cropland-to-forest, and cropland-to-wetland conversions, which could reduce the SCC values (comparing 2020 base-year with 2000 base-year) by 0.0132, 0.0009, 0.0033, 0.0030, 0.0001, 0.0082, and 0.0001 (USD/tCO₂), respectively. While the SCC is mainly determined by energy and industrial structure, the overall effect of NbS is larger than the sum of land urbanization and non-NbS land-use conversions. Via embedding the real-world inter-dynamics of land-use conversions into the SCC quantification, this study presents a pioneer assessment of the impacts of NbS on the SCC in an integrated framework, sheds important insights into the effectiveness of NbS, and offers practical implications for policy-makers to devise comprehensive policies covering all feasible CO₂ abatement options.

Development of chemical emission scenarios using the Shared Socio-economic Pathways

The widespread use of chemicals has led to significant water quality concerns, and their use is still increasing. Hence, there is an urgent need to understand the possible future trends in chemical emissions to water systems. This paper proposes a general framework for developing emission scenarios for chemicals to water using the Shared Socio-economic Pathways (SSPs) based on an emission-factor approach. The proposed approach involves three steps: (i) identification of the main drivers of emissions, (ii) quantification of emission factors based on analysis of publicly available data, and (iii) projection of emissions based on projected changes in the drivers and emission factors. The approach was tested in Europe for five chemical groups and on a national scale for five specific chemicals representing pharmaceuticals, pesticides, and industrial chemicals. The resulting emission scenarios show widely diverging trends of increased emissions by 240% for ibuprofen in SSP3 (regional rivalry) to a 68% decrease for diclofenac in SSP1 (sustainable development) by 2050. While emissions typically decrease in SSP1, they follow the historical trend in SSP2 (middle-of-the-road scenario) and show an increase in the regional rivalry scenario SSP3 for most selected chemicals. Overall, the framework allows understanding of future chemical emissions trends as a function of the socio-economic trends as captured in the SSPs. Our scenarios for chemical emissions can thus be used to model future aqueous emissions to support risk assessment. While the framework can be easily extended to other pharmaceuticals and pesticides, it heavily leans on the availability and quality of historical emission data and a detailed understanding of emission sources for industrial chemicals.

The risks from climate change to sovereign debt

The exposure of sovereigns to climate risks is priced and can affect credit ratings and debt servicing costs. I argue that the climate risks to fiscal stability are not receiving adequate attention and discuss how to remedy the situation. After providing evidence of divergent climate risks to advanced economies, I describe the transmission channels from climate change to public finance. Then, I suggest how integrated assessment models (IAMs) can be linked with stochastic debt sustainability analysis (DSA) to inform our understanding of climate risks to sovereign debt dynamics and assess the available fiscal space to finance climate policies. I argue for adopting the narrative scenario architecture developed within the IPCC to bring structure and transparency to the analysis. The analysis is complicated by deep uncertainty -risks, ambiguity, and mis-specifications- of climate change. Using scenario trees, narrative scenarios, and ensembles of models, respectively, we can deal with these three challenges. I illustrate using two prominent IAMs to generate the debt dynamics of a high-debt country under climate risks to economic growth and find adverse effects from as early as 2030. I conclude with the policy implications for fiscal stability authorities.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10584-022-03373-4.

Quantifying the social benefits and costs of reducing phosphorus pollution under climate change

Excess phosphorus loading to waterbodies has led to increasing frequency and severity of harmful algal blooms, negatively impacting economic activity and human health. While interventions to improve water quality can create large societal benefits, these investments are costly and the value of benefits is often unknown. Understanding the social and economic impacts of reduced phosphorus loading is critical for developing effective land use policies and for generating public and political support for these initiatives. Here, we quantify the social benefits and costs of improving water quality in Lake Champlain under a range of phosphorus reduction and climate change scenarios between 2016 and 2050. We use statistical models to link water quality outputs from an established integrated assessment model with three categories of benefits: tourism expenditures, property sales, and avoided human health impacts. We estimate the costs of reducing phosphorus loading using data reported by the State of Vermont. We find that under the most aggressive phosphorus reduction scenario, the total benefits of improved water quality are $55 to $60 million between 2016 and 2050. Over this 35 year time horizon, the combined benefits do not outweigh the costs under any scenario. If the time horizon is extended to 2100 or beyond, however, the benefits may exceed the costs if the applied discount rate is less than 3%. Importantly, we almost certainly underestimate the value of clean water, due to the omission of other types of benefits. Despite this uncertainty, our study provides a tractable framework for disentangling the complex relationships between water quality and human well-being, and illuminates the value of reductions in phosphorus loading to society.

Globalization, sustainable development, and variation in cost of power plant technologies: A perspective of developing economies

This study evaluates the sustainable power plant cost in the outlook of global power plant efficiency to reduce fossil fuel dependency and greenhouse gas emissions. For this purpose, the Global Change Assessment Model (GCAM) applied for conducting the cost assessment of power zone technologies for all principal electricity generation. This study considers the characteristics of essential factors (cement, price of resources, possible increases in employees, and metals) that affect costs. This study suggests that the cost of electricity-generating technologies significantly affects growth efficiency, reduction in production cost, and improving environmental conditions. It also suggests that the cost of electricity-generating technologies, combined with technology mixture, is the key factor behind replacing existing technology in the electricity sector. EPRI cost assessments expanded by around 30% and 50% during 2015-2016. Factors like competition amongst power plant owners, the ambiguous marketplace, production procedures, and lack of environment-related strategies have resulted in massive environmental degradation in developing economies like Pakistan. Based on empirical findings, this study recommends designing efficient technologies, which would reduce power plant costs and ensure vertical prospects related to environmental conditions in the future.

Implications of near-term mitigation on China's long-term energy transitions for aligning with the Paris goals

In the international community, there are many appeals to ratcheting up the current nationally determined contributions (NDCs), in order to narrow the 2030 global emissions gap with the Paris goals. Near-term mitigation has a direct impact on the required efforts beyond 2030 to control warming within 2°C or 1.5°C successfully. In this study, implications of near-term mitigation on China's long-term energy transitions until 2100 for aligning with the Paris goals, are quantified using a refined Global Change Assessment Model (GCAM) with six mitigation scenarios. Results show that intensifying near-term mitigation will alleviate China's transitional challenges during 2030-2050 and long-term reliance on carbon dioxide removal technologies (CDR). Each five-year earlier peaking of CO₂ allows almost a five-year later carbon neutrality of China's energy system. To align with 2°C (1.5°C), peaking in 2025 instead of 2030 reduces the requirement of CDR over the century by 17% (13%). Intensifying near-term mitigation also tends to have economic benefits to China's Paris-aligned energy transitions. Under 2°C (1.5°C), peaking in 2025 instead of 2030, with larger near-term mitigation costs by 1.3 (1.6) times, has the potential to reduce China's aggregate mitigation costs throughout the century by 4% (6%). Although in what way China's NDC is to be updated is determined by decision-makers, transitional and economic benefits suggest China to try its best to pursue more ambitious near-term mitigation in accordance with its latest national circumstances and development needs.

Biomass residues as twenty-first century bioenergy feedstock-a comparison of eight integrated assessment models

In the twenty-first century, modern bioenergy could become one of the largest sources of energy, partially replacing fossil fuels and contributing to climate change mitigation. Agricultural and forestry biomass residues form an inexpensive bioenergy feedstock with low greenhouse gas (GHG) emissions, if harvested sustainably. We analysed quantities of biomass residues supplied for energy and their sensitivities in harmonised bioenergy demand scenarios across eight integrated assessment models (IAMs) and compared them with literature-estimated residue availability. IAM results vary substantially, at both global and regional scales, but suggest that residues could meet 7-50% of bioenergy demand towards 2050, and 2-30% towards 2100, in a scenario with 300 EJ/year of exogenous bioenergy demand towards 2100. When considering mean literature-estimated availability, residues could provide around 55 EJ/year by 2050. Inter-model differences primarily arise from model structure, assumptions, and the representation of agriculture and forestry. Despite these differences, drivers of residues supplied and underlying cost dynamics are largely similar across models. Higher bioenergy demand or biomass prices increase the quantity of residues supplied for energy, though their effects level off as residues become depleted. GHG emission pricing and land protection can increase the costs of using land for lignocellulosic bioenergy crop cultivation, which increases residue use at the expense of lignocellulosic bioenergy crops. In most IAMs and scenarios, supplied residues in 2050 are within literature-estimated residue availability, but outliers and sustainability concerns warrant further exploration. We conclude that residues can cost-competitively play an important role in the twenty-first century bioenergy supply, though uncertainties remain concerning (regional) forestry and agricultural production and resulting residue supply potentials.

Returns on investment in watershed conservation: Application of a best practices analytical framework to the Rio Camboriú Water Producer program, Santa Catarina, Brazil

Watershed management may have widespread potential to cost-effectively deliver hydrologic services. Mobilizing the needed investments requires credible assessments of how watershed conservation compares to conventional solutions on cost and effectiveness, utilizing an integrated analytical framework that links the bio-, litho-, hydro- and economic spheres and uses counterfactuals. We apply such a framework to a payment for watershed services (PWS) program in Camboriú, Santa Catarina State, Brazil. Using 1 m resolution satellite imagery, we assess recent land use and land cover (LULC) change and apply the Land Change Modeler tool to predict future LULC without the PWS program. We use current and predicted counterfactual LULC, site costs and a Soil and Water Assessment Tool model calibrated to the watershed to both target watershed interventions for sediment reduction and predict program impact on total suspended solids (TSS) concentrations at the municipal water intake-the principal program objective. Using local water treatment and PWS program costs, we estimate the return on investment (ROI; benefit/costs) of the program. Program ROI exceeds 1 for the municipal water utility in year 44, well within common drinking water infrastructure planning horizons. Because some program costs are borne by third parties, over that same period, for overall (social) program ROI to exceed 1 requires delivery of very modest flood and supply risk reduction and biodiversity co-benefits, making co-benefits crucial for social program justification. Transaction costs account for half of total program costs, a result of large investments in efficient targeting and program sustainability. Co-benefits justify increased cost sharing with other beneficiaries, which would increase ROI for the utility, demonstrating the sensitivity of the business case for watershed conservation to its broader social-economic case and the ability to forge institutional arrangements to internalize third-party benefits.

The value of knowledge accumulation on climate sensitivity uncertainty: comparison between perfect information, single stage and act then learn decisions

In COP21 followed by the Paris Agreement, the world is now seriously planning actions to mitigate greenhouse gas emissions toward a "below 2 °C above preindustrial levels" future. Currently, we are still far from identifying the emission pathways to achieve this target because of the various uncertainties in both climate science and the human behavior. As a part of the ICA-RUS project, conducted by Dr. Seita Emori of the National Institute for Environmental Studies we have studied how these uncertainties are eliminated by the accumulation of scientific knowledge and the decision-making processes. We consider the following three questions: first, when and how will the uncertainty range on the global temperature rise be eliminated, second which global emission pathway should be chosen before we get the perfect information, and third how much expenditure is justified in reducing the climate uncertainties. The first question has been investigated by one of the authors. Shiogama et al. (Sci Rep 6:18903, 2016) developed the Allen-Stott-Kettleborough (ASK) method further to estimate how quickly and in what way the uncertainties in future global mean temperature changes can decline when the current observation network of surface air temperature is maintained. Fourteen global climate model results in CMIP5 (CMIP http://cmip-pcmdi.llnl.gov/, 2017) are used as virtual observations of surface air temperature. The purpose of this study is to answer the remaining two questions. Based on the ASK research outcomes, we apply the multi stage decision-making known as Act Then Learn (ATL) process to an integrated assessment model MARIA which includes energy technologies, economic activities, land use changes and a simple climate model block. We reveal how accumulating observations helps to mitigate economic losses by expanding the existing ATL method to deal with the uncertainty eliminating process by ASK. The primary findings are as follows. First, the value of information largely increases as the climate target policy is more stringent. Second, even if the uncertainties in the equilibrium climate sensitivity are not fully resolved, scientific knowledge is still valuable. In other words, the expenditure for scientific researches is rationalized when we really concern the global climate changes.

Assessment of mitigation strategies as tools for risk management under future uncertainties: a multi-model approach

Although the world understands the possible threat of the future of climate changes, there remain serious barriers to be resolved in terms of policy decisions. The scientific and the societal uncertainties in the climate change policies must be the large part of this barrier. Following the Paris Agreement, the world comes to the next stage to decide the next actions. Without a view of risk management, any decision will be "based on neglecting alternatives" behavior. The Ministry of the Environment, Japan has established an inter-disciplinary research project, called Integrated Climate Assessment-Risks, Uncertainties, and Society (ICA-RUS) conducted by Dr. Seita Emori, National Institute for Environmental Studies. ICA-RUS consists of five research themes, i.e., (1) synthesis of global climate risks, (2) optimization of land, water, and ecosystem for climate risks, (3) analysis of critical climate risks, (4) evaluation of climate risk management options, and (5) interactions between scientific and social rationalities. We participated in the fourth theme to provide the quantitative assessment of technology options and policy measures by integrating assessment model simulations. We employ the multi-model approach to deal with the complex relationships among various fields such as technology, economics, and land use changes. Four different types of integrated assessment models, i.e., MARIA-14 (Mori), EMEDA (Washida), GRAPE (Kurosawa), and AIM (Masui), participate in the fourth research theme. These models contribute to the ICA-RUS by providing two information categories. First, these models provide common simulation results based on shared socioeconomic pathway scenarios and the shared climate policy cases given by the first theme of ICA-RUS to see the ranges of the evaluation. Second, each model also provides model-specific outcomes to answer special topics, e.g., geoengineering, sectoral trade, adaptation, and decision making under uncertainties. The purpose of this paper is to describe the outline and the main outcomes of the multi-model inter-comparison among the four models with a focus upon the first and to present the main outcomes. Furthermore, in this study, we introduce a statistical meta-analysis of the multi-model simulation results to see whether the differently structured models provide the inter-consistent findings. The major findings of our activities are as follows: First, in the stringent climate target, the regional economic losses among models tend to diverge, whereas global total economic loss does not. Second, both carbon capture and storage (CCS) as well as BECCS are essential for providing the feasibility of stringent climate targets even if the deployment potential varies among models. Third, the models show small changes in the crop production in world total, whereas large differences appear between regions. Fourth, the statistical meta-analysis of the multi-model simulation results suggests that the models would have an implicit but common relationship between gross domestic product losses and mitigation options even if their structures and simulation results are different. Since this study is no more than a preliminary exercise of the statistical meta-analysis, it is expected that more sophisticated methods such as data mining or machine learning could be applicable to the simulation database to extract the implicit information behind the models.

Projecting state-level air pollutant emissions using an integrated assessment model: GCAM-USA

Integrated Assessment Models (IAMs) characterize the interactions among human and earth systems. IAMs typically have been applied to investigate future energy, land use, and emission pathways at global to continental scales. Recent directions in IAM development include enhanced technological detail, greater spatial and temporal resolution, and the inclusion of air pollutant emissions. These developments expand the potential applications of IAMs to include support for air quality management and for coordinated environmental, climate, and energy planning. Furthermore, these IAMs could help decision makers more fully understand tradeoffs and synergies among policy goals, identify important cross-sector interactions, and, via scenarios, consider uncertainties in factors such as population and economic growth, technology development, human behavior, and climate change. A version of the Global Change Assessment Model with U.S. state-level resolution (GCAM-USA) is presented that incorporates U.S.-specific emission factors, pollutant controls, and air quality and energy regulations. Resulting air pollutant emission outputs are compared to U.S. Environmental Protection Agency 2011 and projected inventories. A Quality Metric is used to quantify GCAM-USA performance for several pollutants at the sectoral and state levels. This information provides insights into the types of applications for which GCAM-USA is currently well suited and highlights where additional refinement may be warranted. While this analysis is specific to the U.S., the results indicate more generally the importance of enhanced spatial resolution and of considering national and sub-national regulatory constraints within IAMs.

Implication of Paris Agreement in the context of long-term climate mitigation goals

The Paris Agreement confirmed the global aim to achieve a long-term climate goal, in which the global increase in mean temperature is kept below 2 °C compared to the preindustrial level. We investigated the implications of the near-term emissions targets (for around the year 2030) in the context of the long-term climate mitigation goal using the Asia-Pacific Integrated Model framework. To achieve the 2 °C goal, a large greenhouse gas emissions reduction is required, either in the early or latter half of this century. In the mid-term (from 2030 to 2050), it may be necessary to consider rapid changes to the existing energy or socioeconomic systems, while long-term measures (after 2050) will rely on the substantial use of biomass combined with carbon capture and storage technology or afforestation, which will eventually realize so-called negative CO₂ emissions. With respect to the policy context, two suggestions are provided here. The first is the review and revision of the nationally determined contributions (NDCs) in 2020, with an additional reduction target to the current NDCs being one workable alternative. The second suggestion is a concrete and numerical mid-term emissions reduction target, for example to be met by 2040 or 2050, which could also help to achieve the long-term climate goal.

An integrated assessment of two decades of air pollution policy making in Spain: Impacts, costs and improvements

This paper analyses the effects of policy making for air pollution abatement in Spain between 2000 and 2020 under an integrated assessment approach with the AERIS model for number of pollutants (NOx/NO2, PM10/PM2.5, O3, SO2, NH3 and VOC). The analysis of the effects of air pollution focused on different aspects: compliance with the European limit values of Directive 2008/50/EC for NO2 and PM10 for the Spanish air quality management areas; the evaluation of impacts caused by the deposition of atmospheric sulphur and nitrogen on ecosystems; the exceedance of critical levels of NO2 and SO2 in forest areas; the analysis of O3-induced crop damage for grapes, maize, potato, rice, tobacco, tomato, watermelon and wheat; health impacts caused by human exposure to O3 and PM2.5; and costs on society due to crop losses (O3), disability-related absence of work staff and damage to buildings and public property due to soot-related soiling (PM2.5). In general, air quality policy making has delivered improvements in air quality levels throughout Spain and has mitigated the severity of the impacts on ecosystems, health and vegetation in 2020 as target year. The findings of this work constitute an appropriate diagnosis for identifying improvement potentials for further mitigation for policy makers and stakeholders in Spain.

A comparative assessment of economic-incentive and command-and-control instruments for air pollution and CO2 control in China's iron and steel sector

China's iron and steel sector is faced with increasing pressure to control both local air pollutants and CO2 simultaneously. Additional policy instruments are needed to co-control these emissions in this sector. This study quantitatively evaluates and compares two categories of emission reduction instruments, namely the economic-incentive (EI) instrument of a carbon tax, and the command-and-control (CAC) instrument of mandatory application of end-of-pipe emission control measures for CO2, SO2 and NOx. The comparative evaluation tool is an integrated assessment model, which combines a top-down computable general equilibrium sub-model and a bottom-up technology-based sub-model through a soft-linkage. The simulation results indicate that the carbon tax can co-control multiple pollutants, but the emission reduction rates are limited under the tax rates examined in this study. In comparison, the CAC instruments are found to have excellent effects on controlling different pollutants separately, but not jointly. Such results indicate that no single EI or CAC instrument is overwhelmingly superior. The environmental and economic effectiveness of an instrument highly depends on its specific attributes, and cannot be predicted by the general policy category. These findings highlight the necessity of clearer identification of policy target priorities, and detail-oriented and integrated policy-making among different governmental departments.