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The International Institute for Applied Systems Analysis (IIASA), in collaboration with its Japan National Member Organization (NMO), supported by Ministry of the Environment Japan (MOEJ) has initiated a joint research endeavor centered on Cities Transformation. The primary aim of this collaborative effort's inaugural phase is the compilation of a fast-track comprehensive report. This report aims to consolidate the current understanding of urban transformations, identifying critical knowledge gaps therein. It serves to support the scientific community, city stakeholders, and policy-makers in discerning areas warranting greater attention and, crucially, further investigation and study. Particularly, it provides updates on the IPCC 7th Assessment Cycle, with a specific focus on its Special Report on Climate Change and Cities. Commencing with an overview of global urbanization trends, the report delves into the status of informal urban settlement development (Section 2). Subsequently, it comprehensively discusses the physical aspects of climate change, including impacts, vulnerability, adaptation, and mitigation, with a spotlight on air pollution and waste challenges (Section 3). Section 4 shifts focus to systems transformation, examining sectors and cross-cutting perspectives through various case studies. Following this, Section 5 investigates the enabling conditions for city transformations, emphasizing the roles of governance, behavioral and lifestyle changes, innovation and technology, and finance. Expanding further, Section 6 assesses the synergies and trade-offs of mitigation and adaptation strategies, with a particular lens on Sustainable Development Goals (SDGs), health, and well-being. The report concludes by recognizing significant knowledge gaps highlighted through expert insights.

Record-breaking temperatures were recorded across the globe in 2023. Without climate action, adverse climate-related health impacts are expected to worsen worldwide, affecting billions of people. Temperatures in Europe are warming at twice the rate of the global average, threatening the health of populations across the continent and leading to unnecessary loss of life. The Lancet Countdown in Europe was established in 2021, to assess the health profile of climate change aiming to stimulate European social and political will to implement rapid health-responsive climate mitigation and adaptation actions. In 2022, the collaboration published its indicator report, tracking progress on health and climate change via 33 indicators and across five domains. This new report tracks 42 indicators highlighting the negative impacts of climate change on human health, the delayed climate action of European countries, and the missed opportunities to protect or improve health with health-responsive climate action. The methods behind indicators presented in the 2022 report have been improved, and nine new indicators have been added, covering leishmaniasis, ticks, food security, health-care emissions, production and consumption-based emissions, clean energy investment, and scientific, political, and media engagement with climate and health. Considering that negative climate-related health impacts and the responsibility for climate change are not equal at the regional and global levels, this report also endeavours to reflect on aspects of inequality and justice by highlighting at-risk groups within Europe and Europe's responsibility for the climate crisis.

South Asia is a global hotspot of air pollution, harboring 37 of the world's 40 most polluted cities. Sixty percent of its residents inhabit areas characterized by high pollution levels, where concentrations of fine particulate matter (PM2.5) - accountable for chronic respiratory diseases and over two million premature deaths annually in the region - surpass the least stringent air quality standard set by the World Health Organization (WHO). Addressing this problem with fragmented approaches is unlikely to yield significant results, as air pollution extends beyond geographical boundaries. Even if fully executed, existing policy measures will only offer partial relief in diminishing PM2.5 concentrations in South Asia. This study aims to identify and map air pollution hotspots in South Asia in terms of concentration and exposure, understand the various sources of pollution in hotspot areas, and help categorize policy actions and interventions based on a systematic analysis of costs and benefits using the GAINS modeling framework. A large variety of emission sources contribute to PM2.5 pollution in ambient air therefore, effective air quality management needs to balance measures across these sources. Our results reveal that the current environmental policies will decouple emissions from economic growth, however, will not be sufficient to deliver large reductions in ambient PM2.5 in the South Asia region. There is scope for further measures beyond current policies that could approach the WHO Interim Targets (35 µg/m3) for PM2.5. Finally, cost-optimal strategies for air quality management can achieve significant cost savings compared to conventional approaches; however, they require cooperation within states, regions and countries in South Asia. Monitoring of the chemical composition of PM2.5 reveals that a significant share of total fine particulate matter in ambient air in South Asia is composed of secondary particles, i.e., particles that are formed in the atmosphere

According to WHO (World Health Organization), in 2020, 14% of people in global urban areas relied on polluting solid fuels and technologies, compared with 52% of the rural population. The health impacts of such inequality are massive. It was estimated that 3.2 million premature deaths per year (2020), particularly in low-income and middle-income countries due to household air pollution (HAP). Several studies provide estimates of the exposure to fine particulate matter (PM2.5) from household air pollution (HAP-PM2.5) for users of different fuel/cookstove types in rural and urban areas. However, hardly any studies estimate the population-weighted exposure to HAP-PM2.5 at the global scale. A Bayesian hierarchical model was developed to estimate PM2.5 exposure coefficients and their uncertainties for an annual average of HAP-PM2.5 personal exposure. The predicted HAP-PM2.5 exposure at the user level was used to estimate the national-level exposure for the population living in urban and rural areas. The results suggest that switching from polluting solid fuels (biomass, charcoal, coal) to cleaner fuels (gas and electricity) for heating and cooking can potentially reduce the national-level HAP-PM2.5 personal exposure on average by 53%. However, there exists a significant disparity between rural and urban areas, partly reflecting inequality in energy access. More specifically, switching from polluting solid fuels for heating and cooking to cleaner fuels can reduce the personal exposure to HAP-PM2.5 in rural areas by 54% and in urban areas by 38%. The study indicates that increased access to clean fuels and improved stove interventions are needed to achieve the goals of universal energy access and equality between urban and rural areas.

Ammonia has been proposed to replace heavy fuel oil (HFO) in the shipping industry by 2050. When produced with low-carbon electricity, ammonia can reduce greenhouse gas emissions. However, ammonia emissions also contribute to local air pollution via the formation of secondary particulate matter. We estimate the potential ammonia emissions from storage and bunkering operations for shipping in Singapore, a port that accounts for 20% of global bunker fuel sales, and their impacts on air quality and health. Fuel storage and bunkering can increase total gaseous ammonia emissions in Singapore by up to a factor of four and contribute to a 25%–50% increase in ambient PM2.5 concentration compared to a baseline scenario with HFO, leading to an estimated 210–460 premature mortalities in Singapore (30%–70% higher than the baseline). Proper abatement on storage and bunkering can reduce these emissions and even improve ambient PM2.5 concentrations compared to the baseline. Overall, while an energy transition from HFO to ammonia in the shipping industry could reduce global greenhouse gas and air pollutant burdens, local policies will be important to avoid negative impacts on the communities living near its supply chain.

Air pollution is still one of the most severe problems in northern China, especially in the Jing-Jin-Ji region around Beijing. In recent years, China has implemented many stringent policies to address the air quality issue, including promoting energy transition toward cleaner fuels in residential sectors. But until 2020, even in the Jing-Jin-Ji region, nearly half of the rural households still use solid fuels for heating. For residents who are not covered by the clean heating campaign, we analyze five potential mitigation strategies and evaluate their environmental effects as well as the associated health benefits and costs. We estimate that substitution with electricity or gas would reduce air pollution and premature mortality more strongly, while the relatively low investment costs of implementing clean coal or biomass pellet lead to a larger benefit–cost ratio, indicating higher cost efficiency. Hence, clean coal or biomass pellet could be transitional substitution options for the less developed or remote areas which cannot afford a total transition toward electricity or natural gas in the short term.

As China’s population ages rapidly, the health risks associated with a changing climate are becoming more threatening. The 2022 China report of the Lancet Countdown, led by Tsinghua University with the contributions of 73 experts from 23 leading global institutions, tracks progress in climate change and health in China through 27 indicators across five domains: (1) Climate change impacts, exposure, and vulnerability; (2) adaptation, planning, and resilience for health; (3) mitigation actions and health co-benefits; (4) economics and finance; and (5) public and political engagement. This report is the third China Lancet Countdown report, paying particular attention to the impacts on the elderly and highlighting the urgency of taking action. We selected the most urgent and relevant indicators to complete a policy brief that provides a better understanding of recent progress on climate change and health in China. We found heat-related health impacts increased from 2020 to 2021, increasing heat-related mortality, reducing labour capacity, and undermining the capacity to partake in physical activity due to rising temperature. In addition, exposure to wildfire, extreme drought, and extreme rainfall also increased in different regions across China. In 2021, compared with the 1986–2005 average, people in China had an average of 7.85 more heatwave days (which led to an extra 13185 heatwave-related deaths), and a loss of 0.67 more hours of safe outdoor physical exercise per day. The rising temperature also caused the annual average exposure to wildfire to increase by 60.0% between 2017–2021 compared with the 2001–2005 average. Meanwhile, the engagement on health and climate issues from individuals, scholars, and public sectors continues to grow rapidly. From 2020 to 2021, the number of climate-related articles and documents on the official websites of four Chinese Government departments grew by 1.83 times, and the number of climate-and-health-related articles and documents gr

The global anthropogenic emissions of air pollutants including sulfur dioxide (SO2), nitrogen oxides (NOx), ammonia (NH3), particulate matter (distinguishing PM2.5, PM10, BC, OC, OM), non-methane volatile organic compounds (VOC), carbon monoxide (CO), and methane (CH4) were developed at CIAM/IIASA[2]. These emission datasets have been produced with the GAINS model[1] (Amann et al., 2011) within work under UNECE Convention on Long-Range Transboundary Air Pollution (LRTAP) and cover the 1990-2050 period. The respective emission datasets consist of 5-yearly global annual and monthly emissions and include two to three scenarios, depending on the version of the dataset: a baseline that is referred to as current legislation case (LRTAP Baseline), a scenarios exploring technical mitigation potential for all pollutant species (LRTAP MTFR), and a scenario that combines climate policy, behavioral changes, and strong technical mitigation of all pollutants (LRTAP LOW) Brief explanation of assumptions used in these three scenarios. The current legislation scenario (LRTAP Baseline) assumes implementation and effective enforcement of all committed energy and environmental policies affecting emissions of air pollutants and greenhouse gases. CIAM has undertaken a review and update of historical data (up to 2020) driving emissions of all species in the GAINS model, drawing on the statistical information from EUROSTAT, International Energy Agency (IEA), UN Food and Agriculture Organization (FAO), as well as reporting of data and emissions to the Center on Emission Inventories and Projections[3]. For the EU27, the energy and agriculture projections are consistent with the objectives of the European Green Deal and Fit for 55 package making EU carbon neutral by 2050; these are consistent with the projections used in the EU third Clean Air Outlook [4]. For West Balkan, Republic of Moldova, Georgia, and Ukraine, a similar set of modelling tools was used as for the EU developing a new consi

The health threats posed by climate change in China are increasing rapidly. Each province faces different health risks. Without a timely and adequate response, climate change will impact lives and livelihoods at an accelerated rate and even prevent the achievement of the Healthy and Beautiful China initiatives. The 2021 China Report of the Lancet Countdown on Health and Climate Change is the first annual update of China’s Report of the Lancet Countdown. It comprehensively assesses the impact of climate change on the health of Chinese households and the measures China has taken. Invited by the Lancet committee, Tsinghua University led the writing of the report and cooperated with 25 relevant institutions in and outside of China. The report includes 25 indicators within five major areas (climate change impacts, exposures, and vulnerability; adaptation, planning, and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement) and a policy brief. This 2021 China policy brief contains the most urgent and relevant indicators focusing on provincial data: The increasing health risks of climate change in China; mixed progress in responding to climate change. In 2020, the heatwave exposures per person in China increased by 4.51 d compared with the 1986–2005 average, resulting in an estimated 92% increase in heatwave-related deaths. The resulting economic cost of the estimated 14500 heatwave-related deaths in 2020 is US$176 million. Increased temperatures also caused a potential 31.5 billion h in lost work time in 2020, which is equivalent to 1.3% of the work hours of the total national workforce, with resulting economic losses estimated at 1.4% of China’s annual gross domestic product. For adaptation efforts, there has been steady progress in local adaptation planning and assessment in 2020, urban green space growth in 2020, and health emergency management in 2019. 12 of 30 provinces reported that they have com

Background: Morbidity burdens from ambient air pollution are associated with market and non-market costs and are therefore important for policymaking. The estimation of morbidity burdens is based on concentration-response functions (CRFs). Most existing CRFs for short-term exposures to PM2.5 assume a fixed risk estimate as a log-linear function over an extrapolated exposure range, based on evidence primarily from Europe and North America. Objectives: We revisit these CRFs by performing a systematic review for seven morbidity endpoints previously assessed by the World Health Organization, including data from all available regions. These endpoints include all cardiovascular hospital admission, all respiratory hospital admission, asthma hospital admission and emergency room visit, along with the outcomes that stem from morbidity, such as lost work days, respiratory restricted activity days, and child bronchitis symptom days. Methods: We estimate CRFs for each endpoint, using both a log-linear model and a nonlinear model that includes additional parameters to better fit evidence from high-exposure regions. We quantify uncertainties associated with these CRFs through randomization and Monte Carlo simulations. Results: The CRFs in this study show reduced model uncertainty compared with previous CRFs in all endpoints. The nonlinear CRFs produce more than doubled global estimates on average, depending on the endpoint. Overall, we assess that our CRFs can be used to provide policy analysis of air pollution impacts at the global scale. It is however important to note that improvement of CRFs requires observations over a wide range of conditions, and current available literature is still limited. Discussion: The higher estimates produced by the nonlinear CRFs indicates the possibility of a large underestimation in current assessments of the morbidity impacts attributable to air pollution. Further studies should be pursued to better constrain the CRFs studied here, and to bette

South Africa currently faces a serious problem of air pollution in its cities. The approach used to manage air quality has not yet met the desired outcomes. In this study, potential mitigation options for ambient PM2.5 in the Vaal Triangle Airshed Priority Area (VTAPA)—one of the most industrialised regions in South Africa—were explored using the GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) model. Based on projections of economic activities and population, changes in PM2.5 concentrations were quantified, applying different assumptions on application rates of end-of-pipe control technologies for key emission sources of PM2.5 and its precursor gases NOx and SO2. Ambient PM2.5 concentrations were used to estimate the potential human health benefits of emission reductions. Our findings reveal that PM2.5 concentrations for the VTAPA will not reach recommended air quality limits by 2035 under the current legislation. By introducing stringent controls, emissions will be reduced by more than half, and national air quality standards are attained. Trajectories show that implementation costs in the alternative scenario will nearly be twice as high as those for the current policies. Analysis using the GAINS model has demonstrated the value of assessing the multiple dimensions of air pollution through applying an integrated approach to provide evidence-based support for policy decision-making.

Recent trajectories of production and consumption patterns have resulted in massively rising quantities of municipal solid waste (MSW). Building on the Shared Socioeconomic Pathways, we build two sets of global scenarios until 2050, namely baseline and mitigation scenarios. We assess trajectories of future MSW generation and the impact of MSW management strategies on methane and air pollutant emissions. In 2050, the adoption of mitigation strategies in the sustainability-oriented scenario yields earlier, and major, co-benefits compared to scenarios in which inequalities are reduced but that are focused solely on technical solutions. In 2050, the GHG emissions in the sustainability-oriented scenario amount to 182 Gg CO2eq/yr of CH4, to be released while particulate matter, and air pollutants from open burning of MSW can be virtually eliminated. We demonstrate that the 6.3 target of the SDG 6 can only be achieved through more ambitious sustainability-oriented scenarios that limit MSW generation and improve management.

Recent trajectories of production and consumption patterns have resulted in massively rising quantities of municipal solid waste (MSW). Building on the Shared Socioeconomic Pathways, we build two sets of global scenarios until 2050, namely baseline and mitigation scenarios. We assess trajectories of future MSW generation and the impact of MSW management strategies on methane and air pollutant emissions. In 2050, the adoption of mitigation strategies in the sustainability-oriented scenario yields earlier, and major, co-benefits compared to scenarios in which inequalities are reduced but that are focused solely on technical solutions. In 2050, the GHG emissions in the sustainability-oriented scenario amount to 182 Gg CO2eq/yr of CH4, to be released while particulate matter, and air pollutants from open burning of MSW can be virtually eliminated. We demonstrate that the 6.3 target of the SDG 6 can only be achieved through more ambitious sustainability-oriented scenarios that limit MSW generation and improve management.

Low-carbon pathways consistent with the 2°C and 1.5°C long-term climate goals defined in the Paris Agreement are likely to induce substantial co-benefits for air pollution and associated health impacts. In this analysis, using five global integrated assessment models, we quantify the emission reductions in key air pollutants resulting from the decarbonization of energy systems and the resulting changes in premature mortality attributed to the exposure to ambient concentrations of fine particulate matter. The emission reductions differ by sectors. Sulfur emissions are mainly reduced from power plants and industry, cuts in nitrogen oxides are dominated by the transport sector, and the largest abatement of primary fine particles is achieved in the residential sector. The analysis also shows that health benefits are the largest when policies addressing climate change mitigation and stringent air pollution controls are coordinated. We decompose the key factors that determine the extent of health co-benefits, focusing on Asia: changes in emissions, urbanization rates, population growth and ageing. Demographic processes, particularly due to ageing population, counteract in many regions the mortality reductions realized through lower emissions.

Despite low per capita emissions, with over a billion population, India is pivotal for climate change mitigation globally, ranking as the third largest emitter of greenhouse gases. We linked a previously published multidimensional population projection with emission projections from an integrated assessment model to quantify the localised (i.e. state-level) health benefits from reduced ambient fine particulate matter in India under global climate change mitigation scenarios in line with the Paris Agreement targets and national scenarios for maximum feasible air quality control. We incorporated assumptions about future demographic, urbanisation and epidemiological trends and accounted for model feedbacks. Our results indicate that compared to a business-as-usual scenario, pursuit of aspirational climate change mitigation targets can avert up to 8.0 million premature deaths and add up to 0.7 years to life expectancy (LE) at birth due to cleaner air by 2050. Combining aggressive climate change mitigation efforts with maximum feasible air quality control can add 1.6 years to life expectancy. Holding demographic change constant, we find that climate change mitigation and air quality control will contribute slightly more to increases in LE in urban areas than in rural areas and in states with lower socio-economic development.

For the Chinese, French, German, and Spanish translations of the abstract see Supplementary Materials section.

Nationally determined contributions (NDCs) serve to meet the goals of the Paris Agreement of staying "well below 2°C", which could also yield substantial health co-benefits in the process. However, existing NDC commitments are inadequate to achieve this goal. Placing health as a key focus of the NDCs could present an opportunity to increase ambition and realise health co-benefits. We modelled scenarios to analyse the health co-benefits of NDCs for the year 2040 for nine representative countries (ie, Brazil, China, Germany, India, Indonesia, Nigeria, South Africa, the UK, and the USA) that were selected for their contribution to global greenhouse gas emissions and their global or regional influence.

The problem of solid waste management presents an issue of increasing importance in many low-income settings, including the progressively urbanised context of Kenya. Kisumu County is one such setting with an estimated 500 tonnes of waste generated per day and with less than half of it regularly collected. The open burning and natural decay of solid waste is an important source of greenhouse gas (GHG) emissions and atmospheric pollutants with adverse health consequences. In this paper, we use system dynamics modelling to investigate the expected impact on GHG and PM2.5 emissions of (i) a waste-to-biogas initiative and (ii) a regulatory ban on the open burning of waste in landfill. We use life tables to estimate the impact on mortality of the reduction in PM2.5 exposure. Our results indicate that combining these two interventions can generate over 1.1 million tonnes of cumulative savings in GHG emissions by 2035, of which the largest contribution (42%) results from the biogas produced replacing unclean fuels in household cooking. Combining the two interventions is expected to reduce PM2.5 emissions from the waste and residential sectors by over 30% compared to our baseline scenario by 2035, resulting in at least around 1,150 cumulative life years saved over 2021-2035. The contribution and novelty of this study lies in the quantification of a potential waste-to-biogas scenario and its environmental and health impact in Kisumu for the first time.

This paper describes a global research programme on the complex systemic connections between urban development and health. Through transdisciplinary methods the Complex Urban Systems for Sustainability and Health (CUSSH) project will develop critical evidence on how to achieve the far-reaching transformation of cities needed to address vital environmental imperatives for planetary health in the 21st Century. CUSSH’s core components include: (i) a review of evidence on the effects of climate actions (both mitigation and adaptation) and factors influencing their implementation in urban settings; (ii) the development and application of methods for tracking the progress of cities towards sustainability and health goals; (iii) the development and application of models to assess the impact on population health, health inequalities, socio-economic development and environmental parameters of urban development strategies, in order to support policy decisions; (iv) iterative in-depth engagements with stakeholders in partner cities in low-, middle- and high-income settings, using systems-based participatory methods, to test and support the implementation of the transformative changes needed to meet local and global health and sustainability objectives; (v) a programme of public engagement and capacity building. Through these steps, the programme will provide transferable evidence on how to accelerate actions essential to achieving population-level health and global climate goals through, amongst others, changing cities’ energy provision, transport infrastructure, green infrastructure, air quality, waste management and housing.

This Excel workbook contains the data used in the plotting of the figures in the manuscript titled "Household contributions to and impacts from air pollution in India” (to be) published in Nature Sustainability in 2021. Note that the final figure counter in the paper were shifted by one, thus the published Fig. 2 corresponds to the Fig 1 tab in the Excel sheets.

Left unmitigated, climate change poses a catastrophic risk to human health, demanding an urgent and concerted response from every country. The 2015 Lancet Commission on Health and Climate Change and The Lancet Countdown: Tracking Progress on Health and Climate Change have been initiated to map out the impacts of climate change and the necessary policy responses. To meet these challenges, Tsinghua University, partnering with the University College London and 17 Chinese and international institutions, has prepared the Chinese Lancet Countdown report, which has a national focus and builds on the work of the global Lancet Countdown: Tracking Progress on Health and Climate Change. Drawing on international methodologies and frameworks, this report aims to deepen the understanding of the links between public health and climate change at the national level and track them with 23 indicators. This work is part of the Lancet's Countdown broader efforts to develop regional expertise on this topic, and coincides with the launch of the Lancet Countdown Regional Centre in Asia, based at Tsinghua University. The data and results of this report are presented at the provincial level, where possible, to facilitate targeted response strategies for local decision-makers. Based on the data and findings of the 2020 Chinese Lancet Countdown report, five recommendations are proposed to key stakeholders in health and climate change in China: (1) Enhance inter-departmental cooperation. Climate change is a challenge that demands an integrated response from all sectors, urgently requiring substantial inter-departmental cooperation among health, environment, energy, economic, financial, and education authorities. (2) Strengthen health emergency preparedness. Knowledge and findings on current and future climate-related health threats still lack the required attention and should be fully integrated into the emergency preparedness and response system. (3) Support research and raise awareness. Addit

This dataset provides complementary information supporting the manuscript Potentials for reductions of global GHG and air pollutants from circular municipal waste management systems, submitted for publication as a research article in Nature Communications. The dataset provides detailed information on emission estimates of methane, particulate matter and air pollutants from municipal solid waste, including emission factors, and municipal solid waste generation and treatment, globally as well as by region (urban-rural) and scenario.

Airborne fine particulate matter (PM2.5) is the largest environmental risk factor for premature mortality worldwide, and the probable cause of several hundred thousand premature deaths every year in India. Indian households contribute to ambient PM2.5 directly from several sources, including biomass-burning cook stoves and transport, and indirectly through the manufacturing of products triggered by their purchases. Here, we quantify consumption-based PM2.5 contributions from, as well as the mortality burden suffered by, urban and rural households by income deciles. Indirect PM2.5 emissions contribute almost twice as much to ambient PM2.5 concentrations as direct emissions from biomass cook stoves. We find that the impacts are distributed differently from contributions. We show that the mortality risk from indirect sources falls disproportionately on lower-income households. This suggests that industry‐wide pollution controls can reduce inequity in the impacts of ambient air pollution. However, as low-income households face an order of magnitude higher mortality risks from indoor air pollution, clean cooking fuels remain the most effective way to reduce the number of premature deaths from air pollution in India.

The Lancet Countdown is an international collaboration established to provide an independent, global monitoring system dedicated to tracking the emerging health profile of the changing climate. The 2020 report presents 43 indicators across five sections: climate change impacts, exposures, and vulnerabilities; adaptation, planning, and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. This report represents the findings and consensus of the 35 leading academic institutions and UN agencies that make up The Lancet Countdown, and draws on the expertise of climate scientists, geographers, engineers, experts in energy, food, and transport, economists, social, and political scientists, data scientists, public health professionals, and doctors.

Over the last decades, energy and pollution control policies combined with structural changes in the economy decoupled emission trends from economic growth, increasingly also in the developing world. It is found that effective implementation of the presently decided national pollution control regulations should allow further economic growth without major deterioration of ambient air quality, but will not be enough to reduce pollution levels in many world regions. A combination of ambitious policies focusing on pollution controls, energy and climate, agricultural production systems and addressing human consumption habits could drastically improve air quality throughout the world. By 2040, mean population exposure to PM2.5 from anthropogenic sources could be reduced by about 75% relative to 2015 and brought well below the WHO guideline in large areas of the world. While the implementation of the proposed technical measures is likely to be technically feasible in the future, the transformative changes of current practices will require strong political will, supported by a full appreciation of the multiple benefits. Improved air quality would avoid a large share of the current 3–9 million cases of premature deaths annually. At the same time, the measures that deliver clean air would also significantly reduce emissions of greenhouse gases and contribute to multiple UN sustainable development goals.

The implied emission factors in CPAT are based on the GAINS model. The GAINS model methodology is described in (Amann et al., 2011). It is an integrated assessment model of air pollution, and features both an emissions model for various air pollutants and greenhouse gases (relevant here are primary PM2.5, SO2, NOx, NH3 and VOC, as well as CO2, CH4, BC, OC), as well as impact modules (which have not been used in the present exercise).

© 2019, The Author(s). In the last decade, instigated by the Paris agreement and United Nations Climate Change Conferences (COP22 and COP23), the efforts to limit temperature increase to 1.5 °C above pre-industrial levels are expanding. The required reductions in greenhouse gas emissions imply a massive decarbonization worldwide with much involvement of regions, cities, businesses, and individuals in addition to the commitments at the national levels. Improving end-use efficiency is emphasized in previous IPCC reports (IPCC 2014). Serving as the primary ‘agents of change’ in the transformative process towards green economies, households have a key role in global emission reduction. Individual actions, especially when amplified through social dynamics, shape green energy demand and affect investments in new energy technologies that collectively can curb regional and national emissions. However, most energy-economics models—usually based on equilibrium and optimization assumptions—have a very limited representation of household heterogeneity and treat households as purely rational economic actors. This paper illustrates how computational social science models can complement traditional models by addressing this limitation. We demonstrate the usefulness of behaviorally rich agent-based computational models by simulating various behavioral and climate scenarios for residential electricity demand and compare them with the business as usual (SSP2) scenario. Our results show that residential energy demand is strongly linked to personal and social norms. Empirical evidence from surveys reveals that social norms have an essential role in shaping personal norms. When assessing the cumulative impacts of these behavioral processes, we quantify individual and combined effects of social dynamics and of carbon pricing on individual energy efficiency and on the aggregated regional energy demand and emissions. The intensity of social interactions and learning plays an equally import

In the last decade, instigated by the Paris agreement and United Nations Climate Change Conferences (COP22 and COP23), the efforts to limit temperature increase to 1.5 °C above pre-industrial levels are expanding. The required reductions in greenhouse gas emissions imply a massive decarbonization worldwide with much involvement of regions, cities, businesses, and individuals in addition to the commitments at the national levels. Improving end-use efficiency is emphasized in previous IPCC reports (IPCC 2014). Serving as the primary ‘agents of change’ in the transformative process towards green economies, households have a key role in global emission reduction. Individual actions, especially when amplified through social dynamics, shape green energy demand and affect investments in new energy technologies that collectively can curb regional and national emissions. However, most energy-economics models—usually based on equilibrium and optimization assumptions—have a very limited representation of household heterogeneity and treat households as purely rational economic actors. This paper illustrates how computational social science models can complement traditional models by addressing this limitation. We demonstrate the usefulness of behaviorally rich agent-based computational models by simulating various behavioral and climate scenarios for residential electricity demand and compare them with the business as usual (SSP2) scenario. Our results show that residential energy demand is strongly linked to personal and social norms. Empirical evidence from surveys reveals that social norms have an essential role in shaping personal norms. When assessing the cumulative impacts of these behavioral processes, we quantify individual and combined effects of social dynamics and of carbon pricing on individual energy efficiency and on the aggregated regional energy demand and emissions. The intensity of social interactions and learning plays an equally important role for the uptake