Can global models provide insights into regional mitigation strategies? A diagnostic model comparison study of bioenergy in Brazil

The usefulness of global integrated assessment model (IAM) results for policy recommendation in specific regions has not been fully assessed to date. This study presents the variation in results across models for a given region, and what might be behind this variation and how model assumptions and structures drive results. Understanding what drives the differences across model results is important for national policy relevance of global scenarios. We focus on the use of bioenergy in Brazil, a country expected to play an important role in future bioenergy production. We use results of the Stanford University Energy Modeling Forum’s 33rd Study (EMF-33) model comparison exercise to compare and assess projections of Brazil’s bioenergy pathways under climate mitigation scenarios to explore how 10 global IAMs compare to recent trends in the country. We find that, in their current form, global IAMs have limited potential to supply robust insights into regional mitigation strategies. Our results suggest fertile ground for a new research agenda to improve regional representation in global IAMs with improved spatial and technological resolutions.

Reduced health burden and economic benefits of cleaner fuel usage from household energy consumption across rural and urban China

Energy consumption in the residential sector is increasing rapidly in China. This study applies an integrated assessment model to investigate the adverse impacts of household energy consumption by various fuel types across rural and urban areas on age- and sex- specific premature deaths associated with PM2.5 pollution at provincial levels for 2015. We further estimate the economic and health co-benefits of a switch from solid fuels to electricity within households. We find that energy consumed by Chinese urban households was nearly 1.8 times than that of rural households. However, premature deaths due to household energy usage was 1.1 times higher in rural areas compared to urban areas due to direct use of coal for heating in rural households. The majority of household consumption-related premature deaths are predominately in the Southern area of China due to the population size and aging population. By replacing coal and biomass with electricity, this paper estimates economic benefits equal to 0.09% (95% CI: 0.08%-0.1%) GDP for rural areas and 0.006% (0.005%-0.007%) of GDP for urban areas of China. The results suggest that mitigation measures such as the promotion and subsidization of cleaner fuels, modern stove within rural households would yield these potential significant economic benefits.

A multi-scale integrated assessment model to support urban sustainability

Tools purposed towards supporting the transition to more sustainable urban futures typically focus on specific phenomena at the local level. Whilst such approaches remain valuable, there is a need to complement this micro approach with broader integrated methods which deal with the interaction between different urban components as well as their relation to processes and policies enacted at higher scales. Through the adaptation of the World3 global model of Meadows et al. (The limits to growth, Universe Books, New York, 1972; Limits to growth: the 30-year update. Earthscan, London 2005), integrating both an urban system layer, and a national data layer inputting new data, we develop a proof-of-concept multi-scale integrated assessment model. This model is used to explore the relationship between the sustainability of the urban system relative to higher-scale contexts. By emphasising feedback, cascading effects, and unintended consequences, such a modelling framework allows for deeper consideration of coupling mechanisms between subsystems both within the urban system and across broader scales. Following the description of our model, we take Meadows et al. (2005)’s ‘Scenario 3’ as a starting point to generate several scenarios exploring potential intervention taken at the level of the individual urban system to tackle food security and localised pollution. Our results demonstrate that the evolution of the urban system is sensitively dependent on wider global events, and that while concerted intervention may mitigate some effects, the future of an individual system is largely at the mercy of the evolution of the global system. We argue that the results of this exercise suggest an important role for multi-scale models for informing the wider context of policy measures taken across different hierarchical scales. In an extended discussion section, we outline barriers and potential routes for building our work beyond a proof-of-concept relating to data, boundaries, politicisation, and building confidence in model outputs.

Health and Economic Impact Assessment of Transport and Industry PM2.5 Control Policy in Guangdong Province

PM2.5 pollution-related diseases lead to additional medical expenses and the loss of working hours, thus affecting the macro-economy. To evaluate the health-related economic impacts of PM2.5, the Integrated Assessment Model of Climate, Economic, and Environment (ICEEH), combined with the Computable General Equilibrium (CGE) model, the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model, and a health impact assessment module was constructed. The impact of different air pollution control strategies was analyzed in Guangdong Province by establishing a Without Control (WOC) scenario, an Air Control (AIC) scenario, and a Blue Sky (BLK) scenario. The results show that in the WOC scenario for 2035, the death rate for Guangdong Province is 71,690 persons/year and the loss of working hours is 0.67 h/person/year. In the AIC and BLK scenarios compared with WOC for 2035, the loss of working hours is reduced by 29.8% and 34.3%, and premature deaths are reduced by 33.0% and 37.5%, respectively; GDP would increase by 0.05% and 0.11%, respectively, through strict pollution control policies. Furthermore, improved labor force quality induced by better air conditions would promote the added value in labor-intensive industries, such as agriculture (0.233%), other manufacturing (0.172%), textiles (0.181%), food (0.176%), railways transport (0.137%), and services (0.129%). The added value in the waste (−0.073%), nature gas (−0.076%), and crude oil sectors (−0.072%) would decrease because of the increased investment installment in PM2.5 treatment equipment.

Developing a System Dynamics Model for the Nizhniy Kaban and Sredniy Kaban Lakes, Kazan, Russia, Assessing the Impacts of Phosphorus and Nitrogen Inputs on Lake Ecology

The Kaban Lakes Integrated Assessment Model (KLIAM) was developed for the lake hydrology, chemistry, and plankton dynamics of the Nizhniy Kaban and Sredniy Kaban lakes, Kazan, Russia. KLIAM is able to describe the variations seen in the Kaban lakes chemical and biological states as far seen through measurements available at the moment. KLIAM is able to reconstruct the lake history as it is approximately known from the data and written narratives. KLIAM was used to assess the measures to return the lakes to their original pre-urban status as alkaline and semi-oligotrophic lakes. The Kaban Lakes periodically goes through plankton blooms, as seen in the lake in the last decades since before World War II, which are caused by plankton growth promoted by phosphorus and nitrogen coming to the lakes as pollution from the human environment. In the new plans for development of the area surrounding the Nizhniy Kaban and Sredniy Kaban lakes, we suggest that attention is paid to reducing phosphorus and nitrogen flows to the lakes, as the best way to improve their ecological status. This is based on simulations with KLIAM. We recommend that the monitoring of lake chemistry and lake ecology is improved with reoccurring analysis of samples from the Kaban Lakes.

Deep mitigation of CO2 and non-CO2 greenhouse gases toward 1.5 °C and 2 °C futures

Stabilizing climate change well below 2 °C and towards 1.5 °C requires comprehensive mitigation of all greenhouse gases (GHG), including both CO2 and non-CO2 GHG emissions. Here we incorporate the latest global non-CO2 emissions and mitigation data into a state-of-the-art integrated assessment model GCAM and examine 90 mitigation scenarios pairing different levels of CO2 and non-CO2 GHG abatement pathways. We estimate that when non-CO2 mitigation contributions are not fully implemented, the timing of net-zero CO2 must occur about two decades earlier. Conversely, comprehensive GHG abatement that fully integrates non-CO2 mitigation measures in addition to a net-zero CO2 commitment can help achieve 1.5 °C stabilization. While decarbonization-driven fuel switching mainly reduces non-CO2 emissions from fuel extraction and end use, targeted non-CO2 mitigation measures can significantly reduce fluorinated gas emissions from industrial processes and cooling sectors. Our integrated modeling provides direct insights in how system-wide all GHG mitigation can affect the timing of net-zero CO2 for 1.5 °C and 2 °C climate change scenarios.

REMIND2.1: transformation and innovation dynamics of the energy-economic system within climate and sustainability limits

This paper presents the new and now open-source version 2.1 of the REgional Model of INvestments and Development (REMIND). REMIND, as an integrated assessment model (IAM), provides an integrated view of the global energy–economy–emissions system and explores self-consistent transformation pathways. It describes a broad range of possible futures and their relation to technical and socio-economic developments as well as policy choices. REMIND is a multiregional model incorporating the economy and a detailed representation of the energy sector implemented in the General Algebraic Modeling System (GAMS). It uses non-linear optimization to derive welfare-optimal regional transformation pathways of the energy-economic system subject to climate and sustainability constraints for the time horizon from 2005 to 2100. The resulting solution corresponds to the decentralized market outcome under the assumptions of perfect foresight of agents and internalization of external effects. REMIND enables the analyses of technology options and policy approaches for climate change mitigation with particular strength in representing the scale-up of new technologies, including renewables and their integration in power markets. The REMIND code is organized into modules that gather code relevant for specific topics. Interaction between different modules is made explicit via clearly defined sets of input and output variables. Each module can be represented by different realizations, enabling flexible configuration and extension. The spatial resolution of REMIND is flexible and depends on the resolution of the input data. Thus, the framework can be used for a variety of applications in a customized form, balancing requirements for detail and overall runtime and complexity.

Global and regional aggregate damages associated with global warming of 1.5 to 4 °C above pre-industrial levels

We quantify global and regional aggregate damages from global warming of 1.5 to 4 °C above pre-industrial levels using a well-established integrated assessment model, PAGE09. We find mean global aggregate damages in 2100 of 0.29% of GDP if global warming is limited to about 1.5 °C (90% confidence interval 0.09–0.60%) and 0.40% for 2 °C (range 0.12–0.91%). These are, respectively, 92% and 89% lower than mean losses of 3.67% of GDP (range 0.64–10.77%) associated with global warming of 4 °C. The net present value of global aggregate damages for the 2008–2200 period is estimated at $48.7 trillion for ~ 1.5 °C global warming (range $13–108 trillion) and $60.7 trillion for 2 °C (range $15–140 trillion). These are, respectively, 92% and 90% lower than the mean NPV of $591.7 trillion of GDP for 4 °C warming (range $70–1920 trillion). This leads to a mean social cost of CO2 emitted in 2020 of ~ $150 for 4 °C warming as compared to $30 at ~ 1.5 °C warming. The benefits of limiting warming to 1.5 °C rather than 2 °C might be underestimated since PAGE09 is not recalibrated to reflect the recent understanding of the full range of risks at 1.5 °C warming.