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Can short-term memory processes be accurately detected? A reexamination of existing definitions
Get PDFOne major inadequacy in using the sample autocorrelation function (ACF) is the results from sample properties. Hassani’s [Formula: see text] theorem demonstrates that the sum of the sample ACF is always [Formula: see text] for any time series with any length. This result has led to doubts about methodologies that sum sample ACFs for diagnostics and analyses. Thus, the current tools and approaches fall short in detecting short-memory processes with due accuracy. Perhaps the larger question that looms here is about whether, with such definitions and methods, short-memory processes can really be picked up? Resolving this issue stands as a basic precursor to strong predictions and to precluding model mis-specification
Leveraging Citizen Data to Improve Public Services and Measure Progress Toward Sustainable Development Goal 16
Get PDFThis paper presents the results of a pilot study conducted in Ghana that utilized citizen data approaches for monitoring a governance indicator within the SDG framework, focusing on indicator 16.6.2 citizen satisfaction with public services . This indicator is a crucial measure of governance quality, as emphasized by the UN Sustainable Development Goals (SDGs) through target 16.6 Develop effective, accountable, and transparent institutions at all levels . Indicator 16.6.2 specifically measures satisfaction with key public services, including health, education, and other government services, such as government‐issued identification documents through a survey. However, with only 5 years remaining to achieve the SDGs, the lack of data continues to pose a significant challenge in monitoring progress toward this target, particularly regarding the experiences of marginalized populations. Our findings suggest that well‐designed citizen data initiatives can effectively capture the experiences of marginalized individuals and communities. Additionally, they can serve as valuable supplements to official statistics, providing crucial data on population groups typically underrepresented in traditional surveys
Finding Common Climate Action Among Contested Worldviews: Stakeholder-Informed Approaches in Austria
No full textOur goal was to identify and understand perspectives of different stakeholders in the field of climate policy and test a process of co-creative policy development to support the implementation of climate protection measures. As the severity of climate change grows globally, perceptions of climate science and climate-based policy have become increasingly polarized. The one-solution consensus or compromise that has encapsulated environmental policymaking has proven insufficient or unable to address accurately or efficiently the climate issue. Because climate change is often described as a wicked problem (multiple causes, widespread impacts, uncertain outcomes, and an array of potential solutions), a clumsy solution that incorporates ideas and actions representative of varied and divergent worldviews is best suited to address it. This study used the Theory of Plural Rationality, which uses a two-dimensional spectrum to identify four interdependent worldviews as well as a fifth autonomous perspective to define the differing perspectives in the field of climate policy in Austria. Stakeholder inputs regarding general worldviews, climate change, and climate policy were evaluated to identify agreeable actions representative of the multiple perspectives. Thus, we developed and tested a co-creative process for developing clumsy solutions. This study concludes that while an ideological consensus is unlikely, agreement is more likely to occur on the practical level of concrete actions (albeit perhaps for different reasons). Findings suggested that creating an ecological tax reform was an acceptable policy action to diverse stakeholders. Furthermore, the study illuminated that the government is perceived to have the most potential influence on climate protection policy and acts as a key “broker”, or linkage, between other approaches that are perceived to be more actualized but less impactful
The 2025 China report of the Lancet Countdown on health and climate change: empowering cities for synergistic action
No full textAir pollution health and economic co-benefits of keeping warming below 2 °C in India
No full textThe current trajectory of emissions will increase warming and deteriorate air quality in India, leading to severe health and economic impacts. We comparatively assess ambient PM2.5-related health and economic consequences for mid-century under GAINS-simulated business-as-usual (BAU) pathway, which considers current emissions, policies, and mitigation measures will resume in future; and 2°C warming scenario (2°C-WS) that may restrict the warming upto 2°C by 2100. Ambient PM2.5 exposure would change from 14.6–126.4 μg m−3 in baseline across India to 13–136.1 μg m−3 under BAU pathway, but to reduce between 7.4 and 84.4 μg m−3 under 2°C-WS. Projecting socio-demographic determinants, we estimate that the 2°C-WS driven control measures could prevent 0.77 ± 0.19 million annual premature deaths and 18.7 ± 4.3 million DALYs by mid-century, benefiting 18.9 ± 2.8 billion Euros. Emission controls in the domestic, energy, and waste sectors would be pivotal. Here, we show that India should accelerate climate actions to meet 2°C target and align clean-air and health policies for substantial health benefits
Expansion of conservation areas should be informed by sectoral interlinkages
No full textIn the context of nature conservation, a nexus can be defined as the interlinkages of biodiversity in protected and conserved areas with food, water, health, or climate. Evidence of nature conservation expansion scenarios suggest that such interlinkages are ubiquitous across management types, realms, and scales. Ignoring these interlinkages, including synergies, co-benefits, leakages, and trade-offs, can reduce the effectiveness and cross-sectoral benefits of future protected and conserved area expansions. Integrated planning that is inclusive of different value and knowledge systems can help to bridge disciplines and mitigate severe trade-offs impacting effectiveness of these areas. To enable appropriate expansion of protected and conserved areas to 30% of land and sea by 2030, identifying and including such interlinkages in spatial planning is essential
Emerging climate impact on carbon sinks in a consolidated carbon budget
No full textDespite the adoption of the Paris Agreement ten years ago, fossil CO2 emissions continue to rise, pushing atmospheric CO2 levels to 423 ppm in 2024 and driving human-induced warming to 1.36°C, within years of breaching the 1.5°C limit 1,2. Accurate reporting of anthropogenic and natural CO2 sources and sinks is a prerequisite to tracking the effectiveness of climate policy and detecting carbon sink responses to climate change. Yet notable mismatches between reported emissions and sinks have so far prevented confident interpretation of their trends and drivers 1. Here, we present and integrate recent advances in observations and process understanding to address some long-standing issues in the global carbon budget estimates. We show that the magnitude of the natural land sink is substantially smaller than previously estimated, while net emissions from anthropogenic land-use change are revised upwards 1. The ocean sink is 15% larger than the land sink, consistent with new evidence from oceanic and atmospheric observations 3,4. Climate change reduces the efficiency of the sinks, particularly on land, contributing 8.3 ± 1.4 ppm to the atmospheric CO2 increase since 1960. The combined effects of climate change and deforestation turn Southeast Asian and large parts of South American tropical forests from CO2 sinks to sources. This underscores the need to halt deforestation and limit warming to prevent further loss of carbon stored on land. Improved confidence in assessments of CO2 sources and sinks is fundamental for effective climate policy
The role of artificial intelligence for early warning systems: Status, applicability, guardrails, and ways forward
No full textArtificial intelligence (AI) is gaining momentum in earth sciences as a tool to analyze complex natural hazards and their impacts. Such analyses are critical for effective Early Warning Systems (EWSs), which is aiming to generate timely and actionable risk information to protect sectors, systems, and people. Despite advancements in AI, its role in EWS remains underexplored across the four pillars of the Early Warning for All (EW4All) framework; risk knowledge, forecasting, warning dissemination and communication and response preparedness. This study draws on a systematic literature review to assess AI methods utilized in the context of EWS, examines their challenges and opportunities and discusses guiding questions for responsible use. Our study highlights key gaps across knowledge, application and policy. Moreover, we call for coordinated efforts to develop responsible AI frameworks that enhance EWS while ensuring they remain inclusive, accessible, and people-centred that ultimately supports the goal of EW4All by 2027
Critical Review of Climate and Resource Costs and Benefits of Machinery and Equipment
No full textEnvironmental input–output analysis suggests that we use one-third of all metals to produce machinery and equipment (ME) and that their production causes 5% of greenhouse gas emissions globally. Yet, our empirical understanding of material use and emissions associated with ME remains limited, making it the least researched major aspect of material consumption. Machines are not represented explicitly in climate change mitigation models and there is little research considering mitigation opportunities related to ME. Meanwhile the practice and potential for circular material flows, which have dynamic interactions with machinery, have yet to be explored. ME is a very diverse category and so economic statistics and input–output models are essential for a holistic understanding. Mitigation, however, can only be understood through bottom-up engineering research. We identify data sources for future empirical research and suggest how to combine these. Future demand for ME can in part be foreseen by assuming that lower-income countries will use machines to increase their productivity to levels seen in high-income countries. Additional demand will arise from the introduction of autonomous machines, service robots, and artificial intelligence in workplaces and homes. We describe knowledge gaps and outline research questions important for anticipating the future requirements for machines and their potential contributions as both causes of and solutions to climate change and resource overconsumption
