Global Climate Goals Research Articles

The Impact of Sustainable Innovation Finance on Achieving Global Climate Goals

The Impact of Sustainable Innovation Finance on Achieving Global Climate Goals

Analytical review and systematization of available decarbonization options for oil and gas business

Introduction. Global climate goals call for an urgent and substantial decreasein greenhouse gas emissions. Being both a producer and a consumer of energy resources, oil and gas business is responsible for a significant part of global emissions, but also has great capacities to lower its carbon footprint. Analysis of the existing literature revealed that a wide range of decarbonizationoptions remains unsystematic, which complicates management and researchactivities in the field of low-carbon development of the oil and gas industry. Purpose. This article is aimed at systematizing decarbonization options for oil and gas business. Materials and Methods. The research refers to the publicly available resources. The materials are the academic papers about decarbonization, carbon neutrality, development of oil and gas business in the context of low carbon agenda, reports of the research and analytical international organizations, reports of the governmental organizations. The study applied the desk analysis methods, content analysis, decomposition,grouping, analysis (critical and comparative) and synthesis. Results. The requirements and approaches to accounting for greenhouse gas emissions were analyzed, and the main sources of emissions in oil and gas production were identified. The fundamental concepts in relation to the decarbonizationof the oil and gas business are systematized. The paper describes the proposedsystematization of decarbonization options for the oil and gas business with the focus on a hierarchy from general areas of activity to groups of options, decarbonization options and specific technologies (techniques). Conclusion. The research outlined four areas of decarbonization for oil and gas business:(1) improvement of operational activities; (2) transition to low-carbon energysources; (3) work with associated components and production wastes; (4) application of corporate management methods. The paper describes the examples of compensation options available to oil and gas companies and distributes decarbonization options by production stages and by coverage areas.

A MODEL TO ASSESS THE ECONOMIC VIABILITY OF RENEWABLE ENERGY MICROGRIDS: A CASE STUDY OF IMUFU NIGERIA

This paper explores the economic viability of renewable energy microgrids in remote regions, focusing on their potential to provide reliable and sustainable energy solutions. Renewable energy microgrids, which integrate sources such as solar and wind power with advanced energy storage, offer a promising alternative to traditional energy systems, particularly for regions that lack access to conventional power grids. Remote regions often face significant challenges in accessing reliable and affordable energy. The dependence on diesel generators leads to high operational costs and environmental concerns. Renewable energy microgrids present an innovative solution to these issues by harnessing locally available renewable resources, reducing greenhouse gas emissions, and providing consistent energy supply. The assessment involves analyzing initial capital investment and operational costs, comparing the economic performance of renewable microgrids against conventional energy systems, evaluating environmental and social benefits, and reviewing government policies, incentives, and regulatory frameworks that impact the deployment of microgrids. Data is gathered from case studies, existing projects, academic research, and industry reports to develop economic models and scenarios for analysis. While the initial setup cost for renewable microgrids is relatively high, advancements in technology and increased production scale are driving costs down. Significant savings are achieved over time through reduced fuel and maintenance expenses compared to diesel generators. Microgrids can achieve a favorable return on investment (ROI) within 5-10 years, contingent upon local conditions and system scale. Adoption of renewable microgrids leads to substantial reductions in greenhouse gas emissions, supporting global climate goals. Improved energy reliability enhances the quality of life, supports economic development, and promotes social welfare in remote communities. Effective policies, subsidies, and incentives are crucial for reducing financial barriers and encouraging investment in renewable microgrids. Establishing clear and supportive regulatory environments is essential for the successful integration and scalability of microgrid systems. Despite the promising outlook, several challenges remain. The significant upfront investment required for microgrid infrastructure is a major hurdle. The lack of technical skills for installation, operation, and maintenance in remote regions can hinder successful deployment. Additionally, variability in local renewable resources like solar and wind can affect the reliability and performance of microgrids. To overcome these challenges, it is recommended to focus on reducing costs through technological advancements and enhancing local capacity through training and education. Developing policies and incentives that support renewable energy projects and reduce financial barriers is also essential. Engaging local communities in the planning and implementation process ensures the systems meet their needs and gain local support. Renewable energy microgrids are economically viable and environmentally sustainable solutions for providing reliable energy in remote regions. Despite initial cost challenges, the long-term benefits, including operational savings, emission reductions, and enhanced energy access, make them a compelling option. With strategic investments, supportive policies, and community involvement, renewable microgrids can significantly transform energy access and drive sustainable development in remote areas. Keywords: Economic Viability, Microgrinds, Sustainability, Energy, Nigeria.

Economic and environmental implications of resource rent: A dual analysis of Venezuela's sustainability

AbstractVenezuela is among the several countries of the world endowed with natural resources such as oil rent and others. The influence of these resources, which can be felt in both economic and environmental development, is capable of impacting sustainable development goals of any country rich in them. Considering the global climate goals, it is essential to investigate the impact of natural resource rent on its sustainable development goals. We applied Venezuelan country‐specific data of 1972–2014 for an insightful study of the country's sustainable development amidst high resource rent with regard to both economic and environmental performance. The principles of the environmental Kuznets curve (EKC) and pollution haven and halo hypothesis (PHH) were considered to ascertain the pattern and effect of the economic growth and foreign direct investment (FDI) on Venezuelan environmental performance. Different methods such as the autoregressive distributed lag (ARDL) dynamics and bounds, structural break, and Granger causality test were applied for an accurate estimation and insightful analysis. From the ARDL estimations, we found an N‐shaped Kuznets curve, which counters the U‐shaped Kuznets, for the case of Venezuela. Both natural resources and FDI are found to impact positively on the environment, and this confirmed the pollution halo hypothesis for Venezuela. Fossil fuel energy source is found to impact negatively Venezuela's environment with positive relationship between energy use and CO2. From the Granger causality finding, a unidirectional Granger causality is found to transmit from FDI to environment, while bidirectional Granger causality is found to transmit between economic growth and environment. With the findings from both analyses, especially from the vector error correction model (VECM) Granger causality, a nexus is established among economic growth, environment, and FDI, which confirmed the pollution halo hypothesis.

The case for global regulation of carbon capture and storage and artificial intelligence for climate change

This article investigates the trends in the global law-making process as it relates to carbon capture and storage (CCS) and associated technology. It detects regulatory deficiencies and makes a case favouring robust global regulation of such technology in realizing climate aspirations. CCS is recognized as an indispensable ally in the worldwide enterprise that seeks to limit carbon dioxide emissions. This article probes the relatively new and developing area of international regulation of the process of CCS and related technology, in particular Artificial Intelligence (AI), a dimension that promises noteworthy results on the climate change front. It presents a case for the broader deployment of the CCS technology – including more advanced AI options – to enhance in a more radical fashion the prospect of meeting global climate goals and thus stabilising global temperature (that is, achieving net zero CO2 emissions globally in the early 2050s), identifies the need for new and revised sets of rules to govern the development, design and deployment of such technology, and argues in favour of the applicability of existing general sustainable development principles.

Implementation of Formic Acid as a Liquid Organic Hydrogen Carrier (LOHC): Techno-Economic Analysis and Life Cycle Assessment of Formic Acid Produced via CO2 Utilization

To meet the global climate goals agreed upon regarding the Paris Agreement, governments and institutions around the world are investigating various technologies to reduce carbon emissions and achieve a net-negative energy system. To this end, integrated solutions that incorporate carbon utilization processes, as well as promote the transition of the fossil fuel-based energy system to carbon-free systems, such as the hydrogen economy, are required. One of the possible pathways is to utilize CO2 as the base chemical for producing a liquid organic hydrogen carrier (LOHC), using CO2 as a mediating chemical for delivering H2 to the site of usage since gaseous and liquid H2 retain transportation and storage problems. Formic acid is a probable candidate considering its high volumetric H2 capacity and low toxicity. While previous studies have shown that formic acid is less competitive as an LOHC candidate compared to other chemicals, such as methanol or toluene, the results were based on out-of-date process schemes. Recently, advances have been made in the formic acid production and dehydrogenation processes, and an analysis regarding the recent process configurations could deem formic acid as a feasible option for LOHC. In this study, the potential for using formic acid as an LOHC is evaluated, with respect to the state-of-the-art formic acid production schemes, including the use of heterogeneous catalysts during thermocatalytic and electrochemical formic acid production from CO2. Assuming a hydrogen distribution system using formic acid as the LOHC, each of the production, transportation, dehydrogenation, and CO2 recycle sections are separately modeled and evaluated by means of techno-economic analysis (TEA) and life cycle assessment (LCA). Realistic scenarios for hydrogen distribution are established considering the different transportation and CO2 recovery options; then, the separate scenarios are compared to the results of a liquefied hydrogen distribution scenario. TEA results showed that, while the LOHC system incorporating the thermocatalytic CO2 hydrogenation to formic acid is more expensive than liquefied H2 distribution, the electrochemical CO2 reduction to formic acid system reduces the H2 distribution cost by 12%. Breakdown of the cost compositions revealed that reduction of steam usage for thermocatalytic processes in the future can make the LOHC system based on thermocatalytic CO2 hydrogenation to formic acid to be competitive with liquefied H2 distribution if the production cost could be reduced by 23% and 32%, according to the dehydrogenation mode selected. Using formic acid as a LOHC was shown to be less competitive compared to liquefied H2 delivery in terms of LCA, but producing formic acid via electrochemical CO2 reduction was shown to retain the lowest global warming potential among the considered options.

High-Resolution Carbon Accounting Framework for Urban Water Supply Systems.

Decarbonization of urban infrastructure systems is imperative to meeting global climate goals. Urban water supply systems (UWSSs) account for 1-3% of urban electricity consumption in the U.S., a value expected to increase, as municipalities tap nontraditional water supplies that are either more distant or require more energy-intensive treatment. Reducing the carbon intensity of UWSSs will require a combination of infrastructure upgrades, operational modifications, and behavioral interventions, but urban water planners, water treatment system operators, and consumers lack transparent tools for quantifying the carbon emission implications of these decisions. We propose a high-resolution carbon accounting framework that allows for attribution of carbon emissions to individual water sources, water system components, or individual consumers in a UWSS. The high temporal resolution of this framework also enables rapid assessment of the potential for operational and behavioral interventions to reduce the carbon intensity of UWSSs. We demonstrate this carbon accounting framework on a real-world UWSS serving a city of roughly 100 000 residents. The high spatial and temporal resolution, coupled with the scalability of this approach, makes it a valuable tool for consulting engineers, operators, and consumers seeking to deliver Net Zero water supplies.

AIRCC-Clim: A user-friendly tool for generating regional probabilistic climate change scenarios and risk measures

Complex physical models are the most advanced tools available for producing realistic simulations of the climate system. However, such levels of realism imply high computational cost and restrictions on their use for policymaking and risk assessment. Two central characteristics of climate change are uncertainty and that it is a dynamic problem in which international actions can significantly alter climate projections and information needs, including partial and full compliance of global climate goals. Here we present AIRCC-Clim, a simple climate model emulator that produces regional probabilistic climate change projections of monthly and annual temperature and precipitation, as well as risk measures, based both on standard and user-defined emissions scenarios for six greenhouse gases. AIRCC-Clim emulates 37 atm-ocean coupled general circulation models with low computational and technical requirements for the user. This standalone, user-friendly software is designed for a variety of applications including impact assessments, climate policy evaluation and integrated assessment modelling.

Using deep convolutional neural networks to forecast spatial patterns of Amazonian deforestation

Abstract Tropical forests are subject to diverse deforestation pressures while their conservation is essential to achieve global climate goals. Predicting the location of deforestation is challenging due to the complexity of the natural and human systems involved but accurate and timely forecasts could enable effective planning and on‐the‐ground enforcement practices to curb deforestation rates. New computer vision technologies based on deep learning can be applied to the increasing volume of Earth observation data to generate novel insights and make predictions with unprecedented accuracy. Here, we demonstrate the ability of deep convolutional neural networks (CNNs) to learn spatiotemporal patterns of deforestation from a limited set of freely available global data layers, including multispectral satellite imagery, the Hansen maps of annual forest change (2001–2020) and the ALOS PALSAR digital surface model, to forecast deforestation (2021). We designed four model architectures, based on 2D CNNs, 3D CNNs, and Convolutional Long Short‐Term Memory (ConvLSTM) Recurrent Neural Networks (RNNs), to produce spatial maps that indicate the risk to each forested pixel (~30 m) in the landscape of becoming deforested within the next year. They were trained and tested on data from two ~80,000 km2 tropical forest regions in the Southern Peruvian Amazon. The networks could predict the location of future forest loss to a high degree of accuracy (F1 = 0.58–0.71). Our best performing model (3D CNN) had the highest pixel‐wise accuracy (F1 = 0.71) when validated on 2020 forest loss (2014–2019 training). Visual interpretation of the mapped forecasts indicated that the network could automatically discern the drivers of forest loss from the input data. For example, pixels around new access routes (e.g. roads) were assigned high risk, whereas this was not the case for recent, concentrated natural loss events (e.g. remote landslides). Convolutional neural networks can harness limited time‐series data to predict near‐future deforestation patterns, an important step in harnessing the growing volume of satellite remote sensing data to curb global deforestation. The modelling framework can be readily applied to any tropical forest location and used by governments and conservation organisations to prevent deforestation and plan protected areas.

Research on the structural features and influence mechanism of the green ICT transnational cooperation network

Green information and communication technology (ICT) innovations are key to achieving global climate goals. Cross-border technological cooperation has become a strategic choice for countries to achieve technological breakthroughs. Based on 49,731 patents, this study uses social network analysis method (SNA) and quadratic assignment procedure (QAP) to discuss the structural features and influence mechanisms of the worldwide green ICT cooperation network from 2000 to 2019. The results indicate the following: (1) The scale of the global green ICT cooperation network is still small, but the links among countries are getting closer and closer; (2) The USA is the “heart” of the network, and it has a sharp core–periphery structure; India, China, Germany, and the UK play sub-center roles in Asia and Europe, respectively; (3) Green ICT’s cooperative innovation mode is dominated by core countries; (4) Technological proximity, social proximity, ICT development level, climate change, and technological innovation capability are the key driving elements for the growth of the green ICT patent cooperation network; however, the role of institutional distance becomes insignificant over time; and (5) The influence mechanism of the network has the characteristics of heterogeneity in different climate change environments and ICT development levels. Countries should participate in green ICT cooperation with a more open attitude and promote the green transformation of the traditional ICT industry.

КОРУПЦІЙНІ РИЗИКИ ЯК ЗАВАДА ДЛЯ МІЖНАРОДНО-ПРАВОВОГО РЕЖИМУ ЗМІНИ КЛІМАТУ

The United Nations Climate Change Conference (Glasgow, 2021), the largest conference of the parties to date, shaped the respective international legal regime according to state-of-the-art vision. Its outcome documents reflect the principal need for immediate actions during this critical decade to keep as reachable an aim to limit global temperature rise to 1.5°C above pre-industrial levels. The reasons for the current limited success in realization of the global climate goals are rooted not in issues of macrolevel, such as North–South divide, exclusively. Though never mentioned in the principal documents of the climate change regime, the corrupt practices significantly reduce the ability to address this global challenge. The article provides an overview of the key areas of actions that all parties of the regime are expected to take in order to accelerate their efforts pursuant to the Glasgow Climate Pact. Within this framework, mitigation, adaptation, finance and collaboration are examined taking into consideration corruption risks associated with them. The article argues that implementation of the commitment to mobilize not less than USD100 billion annually for adaptation measures, as well as growing mitigation finance, a priori possess a high corruption potential. Corruption challenges impeding sectors of the global climate action such as international carbon markets, phasing-down coal power, sustainable forestry and construction projects for adaptation, are considered. The article points to 'conventional' and new, associated with uncertainty and lack of the relevant experience forms of corruption. It is noted that Glasgow efforts to fully operationalize the Paris Agreement provisions by coming to an understanding on a new mechanism and standards for international carbon markets, common reporting requirements on emissions and support, as well as common timeframes for emissions reductions targets will inhibit corruption, but will not be able to totally eradicate it. Both, climate change and corruption, have become priority issues of international concern. The article claims that responding to existing challenges the climate change international legal regime will interact with the international legal framework against corruption. Though particular forms and directions for such interaction are not clear to the moment, knowledge, norms and techniques shaped within the anti-corruption framework will be potentially useful for global climate change actions.

Construction and Demolition Residuals as Raw Materials for the Production of Novel Geopolymer Building Materials

The increasing number of new construction projects requiring high-quality building products, which, in turn, emit enormous amounts of CO2, runs counter to European and global climate goals. The increasing occupation of valuable landfill space is also an ecological problem. To meet these challenges without having to lower living standards, more ecological building materials should be used in the future. Geopolymers or alkali-activated materials, which, unlike conventional building materials, can be produced and used without a prior burning or calcination process, offer a comparatively low-CO2 alternative. Significant CO2 emissions can already be saved by using this technology. The aim of this work is to investigate whether geopolymers can also be produced from construction and demolition residuals generated by the construction industry in order to counteract the problem of the increasing use of landfill space and, at the same time, to further reduce greenhouse gas emissions in the production of building materials. For this purpose, various residual materials from the construction and demolition industry are investigated by means of XRF, XRD, and IR spectroscopy for their setting behavior by alkaline activation. At the same time, the characteristic values of compressive strength, flexural strength, bulk density, and thermal conductivity, which are important for building materials, are determined in order to test the possible applications of the resulting materials as building materials.

Assessment of the influence of demand-side responses on high-proportion renewable energy system: An evidence of Qinghai, China

The development of renewable energy (RE) is a critical path to achieve global climate goals and energy conversion. The understanding of Demand-side response (DR) is crucial for the stability and efficiency of renewable energy system (RES). The DR strategies are performed by coordinating various energy sources and electricity demand optimally in the operation of high penetration of renewable generations across different seasons from 2015 to 2050 using Qinghai, China as an example. The results show the reduced peak demand by DR is various in different seasons, and the shifted peak demand will be 56.8 GWh-596.5 GWh in 2050. In general, DR could cause a significant reduction of the total costs by avoiding unnecessary installed capacity from ￥2.19 billion to ￥28.62 billion in 2050. In the short-term, the structure of high-proportion RES cannot rapidly adjust to a new form. However, in the long-term, hydropower will have a large share in RES due to the ability of improving the synergistic stability of the high-proportion RES. In addition, the adoption of DR demonstrates a great potential on reducing PV curtailment and wind curtailment.

Extension services can promote pasture restoration: Evidence from Brazil’s low carbon agriculture plan

Innovation and improved practices in the livestock sector represent key opportunities tomeet global climate goals. This paper provides evidence that extension services can pro-mote pasture restoration in cattle ranching in Brazil. We use a randomized controlledtrial implemented in the context of the ABC Cerrado (a large-scale program launched in2014 aimed at fostering technology adoption through a combination of training andtechnical assistance) to examine the effects of different types of extension on agriculturalpractices, input use, and productivity. Providing technical assistance to previously trainedproducers promoted pasture restoration, induced farmers to use inputs more intensively,helped them to improve their management and soil conservation practices, and substan-tially increased revenues. A cost–benefit calculation indicates that US$1 invested in theABC Cerrado program increased profits by US$1.08 to $1.45. Incorporating carbonsavings amplifies this return considerably.

How is Environmental Sustainability a Key to Innovation?

The private sector plays an important role in the global climate goals and the 1.5°C target set during the Paris Agreement. Through investment in green projects and technology and energy efficiency initiatives, their carbon management strategy is paramount to achieve sustainability and good business practices. It is crucial to understand the proposals that the industry has established to reduce its environmental impact by applying supply chain optimization and technological advances or by participating in the carbon market. By identifying key aspects related to climate action within an organization’s sustainability reports and linking them to climate change and carbon management literature from global entities and peer review assessments, the present research evaluates how the IT sector is acting towards increasing emissions. More specifically, this case study analyzes Hewlett Packard´s climate action performance, emissions estimates, and reduction methods, as one of the most sustainable technology companies in the world. During 2020, Hewlett Packard claims to have emitted 44,891,000 tons of carbon dioxide equivalent (tCO2e) which represented an emissions reduction compared to 2019, considering their increasing renewable energy consumption, waste management applications, product optimization, and energy efficiency projects. However, by comparing with what other leaders in the IT sector are doing, improving environmental indicator monitoring and determination, increasing renewable energy and green projects implementation, developing a resilient life-cycle assessment program, and effectively engaging supplier stakeholders, are urgent tasks to achieve better emissions monitoring and abatement. Thus, by engaging with these set of objectives the company and the IT sector, will be able to effectively cope with climate change and establish mitigation and adaptation strategies that will support global environmental targets.

Post‐pandemic recovery through landscape restoration

Land degradation as one of the mega drivers of loss of biodiversity and ecosystem services has affected billions globally, resulting in rampant loss of livelihoods and accelerated distress migration. India, one of the land degradation hotspots in Asia, has also been reeling under the impacts of the ongoing climate and pandemic crises, which have seriously imperiled local livelihoods and human well‐being. Boosting livelihood‐based social support programs can be a transformative approach to scale up Nature‐based Solutions to achieve Land Degradation Neutrality and to realize global restoration, climate, and biodiversity conservation goals. In this article, we provide evidence for enhancing landscape restoration success by creating green job opportunities to achieve post‐pandemic recovery. The Mahatma Gandhi National Rural Employment Guarantee Scheme (MGNREGS) was initiated as a poverty alleviation program in India and can be transformative approach to achieve global climate and sustainable development goals. We use cases from diverse ecological contexts of India to demonstrate the potential of MGNREGS. To revolutionize the process, we propose developing and mainstreaming national‐level landscape restoration guidelines by using locally relevant knowledge for addressing critical gaps, identifying institutions and their roles, developing local capacity, leveraging technology to facilitate decision‐making, encouraging multi‐stakeholder involvement, and promoting inclusiveness and community participation.

Plastics in blue carbon ecosystems: a call for global cooperation on climate change goals

Plastics in blue carbon ecosystems: a call for global cooperation on climate change goals

Benchmarking GHG Emissions Forecasting Models for Global Climate Policy

Climate change and pollution fighting have become prominent global concerns in the twenty-first century. In this context, accurate estimates for polluting emissions and their evolution are critical for robust policy-making processes and ultimately for solving stringent global climate challenges. As such, the primary objective of this study is to produce more accurate forecasts of greenhouse gas (GHG) emissions. This in turn contributes to the timely evaluation of the progress achieved towards meeting global climate goals set by international agendas and also acts as an early-warning system. We forecast the evolution of GHG emissions in 12 top polluting economies by using data for the 1970–2018 period and employing six econometric and machine-learning models (the exponential smoothing state-space model (ETS), the Holt–Winters model (HW), the TBATS model, the ARIMA model, the structural time series model (STS), and the neural network autoregression model (NNAR)), along with a naive model. A battery of robustness checks is performed. Results confirm a priori expectations and consistently indicate that the neural network autoregression model (NNAR) presents the best out-of-sample forecasting performance for GHG emissions at different forecasting horizons by reporting the lowest average RMSE (root mean square error) and MASE (mean absolute scaled error) within the array of predictive models. Predictions made by the NNAR model for the year 2030 indicate that total GHG emissions are projected to increase by 3.67% on average among the world’s 12 most polluting countries until 2030. Only four top polluters will record decreases in total GHG emissions values in the coming decades (i.e., Canada, the Russian Federation, the US, and China), although their emission levels will remain in the upper decile. Emission increases in a handful of developing economies will see significant growth rates (a 22.75% increase in GHG total emissions in Brazil, a 15.75% increase in Indonesia, and 7.45% in India) that are expected to offset the modest decreases in GHG emissions projected for the four countries. Our findings, therefore, suggest that the world’s top polluters cannot meet assumed pollution reduction targets in the form of NDCs under the Paris agreement. Results thus highlight the necessity for more impactful policies and measures to bring the set targets within reach.

Building voluntary partnerships for climate action: An exploratory study from Iceland

The Paris Agreement called for voluntary cooperation between firms, NGOs, and the state, to meet global climate goals. This study examines the development of voluntary carbon projects (VCPs) in Iceland – a country aiming to be carbon neutral by 2040. There is little empirical evidence on what catalyzes voluntary and inter-organizational climate cooperation. To fill this gap, we use a mixed methods research design, surveying firms to understand their awareness and commitment to VCPs, and interviewing state and non-state actors involved in VCPs. In interviews, we tested a cooperation framework with six ‘levers’ to enable cooperation: a superordinate goal, group identity, trust, accountability, communication, and reward distribution . Individualist and collectivist cultural dynamics influence these mechanisms. Survey results showed a general awareness of and support for VCPs, but concerns around their robustness. In interviews, the six cooperation mechanisms offered structured pathways for enabling and strengthening VCPs. • Iceland aims to be carbon neutral through voluntary carbon projects (VCPs). • There is broad awareness of VCPs among firms, but concerns on their robustness. • A shared group identity focused on climate action, is critical for cooperation. • Group identity and trust are strengthened by face-to-face communication. • Explicit goals are foundational for group accountability and cooperation.

The CUSSH programme: supporting cities' transformational change towards health and sustainability.

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.