Search Results (20)

The “top-down” global stocktake (GST) requires the processing of vast volumes of hyperspectral data to derive emission information, placing greater demands on data processing efficiency. Deep learning, leveraging its strengths in the automated and rapid analysis of image datasets, holds significant potential to enhance the efficiency and effectiveness of data processing in the GST. This paper develops a method for detecting carbon dioxide (CO₂) emission hotspots using a convolutional neural network (CNN) with short-lived and co-emitted nitrogen dioxide (NO₂) as a proxy. To address the data gaps in model parameter training, we constructed a dataset comprising over 210,000 samples of NO₂ plumes and emissions based on atmospheric dispersion models. The trained model performed well on the test set, with most samples achieving an identification accuracy above 80% and more than half exceeding 94%. The trained model was also applied to the NO₂ column data from the TROPOspheric Monitoring Instrument (TROPOMI) for hotspot detection, and the detections were compared with the MEIC inventory. The results demonstrate that in high-emission areas, the proposed method successfully identifies emission hotspots with an average accuracy of over 80%, showing a high degree of consistency with the emission inventory. In areas with multiple observations from TROPOMI, we observed a high degree of consistency between high NO₂ emission areas and high CO₂ emission areas from the Global Open-Source Data Inventory for Anthropogenic CO₂ (ODIAC), indicating that high NO₂ emission hotspots can also indicate CO₂ emission hotspots. In the future, as hyperspectral and high spatial resolution remote sensing data for CO₂ and NO₂ continue to grow, our methods will play an increasingly important role in global data preprocessing and global emission estimation. Full article

Satellite XCO₂ retrievals have been widely used in estimating fossil fuel carbon (FFC) emissions at point and urban scales. However, at the regional scale, it remains a significant challenge. Furthermore, current global and regional atmospheric inversions often overlook the uncertainties associated with FFC emissions. To meet the needs of the global carbon stocktake, we developed an inversion method based on Bayesian statistical theory and OCO-2 satellite XCO₂ observations to optimize FFC emissions alongside terrestrial ecosystem carbon fluxes (NEE). The methodology’s core is to distinguish the contributions of NEE and FFC to the observed concentrations using their different spatial distributions. We designed an observing system simulation experiment to invert the 2016 FFC emissions. The results showed that posterior FFC emissions were significantly optimized during the non-growing seasons in the regions with high emissions, with the optimization effect diminishing as emissions shrank. Average FFC emissions uncertainty reductions are in the range of 13–82% in the non-growing season for the eight largest emitting regions globally. By assuming the same uncertainty reduction for FFC emissions in both the growing and non-growing seasons, we can optimize annual emissions for high-emission areas. We believe this study provides a new idea for the inversion of FFC emissions at the regional scale, which is important for achieving the goal of carbon neutrality. Full article

The adaptation finance gap is widening as the impact of climate change grows more disruptive around the globe. Although progress in adaptation planning and implementation has been observed across all sectors and regions, this trend of a widening resource gap calls for more ‘effective’ climate adaptation projects. Therefore, the purpose of this paper is to provide a comprehensive analysis to explore potential factors contributing to the effectiveness of climate change projects in developing countries with a particular focus on water management financed under multilateral funds that have been implemented on the ground, completed and documented. Thirty-five projects from the multilateral funds were collected and analyzed for this purpose. Project evaluation documents have been studied, and the effectiveness rating at completion has been assessed against possible contributing factors through regression analysis. The results showed that the factors contributing to project effectiveness converge around several elements: (i) capacity building and education (|r| > 0.3); (ii) healthy and resilient livelihoods (|r| > 0.2); and (iii) climate data and a robust theory of change (stated by >30% of projects). The implications from this study can provide a useful quantitative ground for discussion around the effective adaptation projects in water management as well as inform relevant international processes such as the Global Goal on Adaptation and global stocktake. Full article

PVC has a special status, as chlorine is a component of the polymer molecule. The properties of chlorine are the reason why the polymer molecule needs additivation. PVC is the mass plastic to which the most diverse and quantitatively largest number of additives are added. This makes PVC difficult to recycle. More than three decades ago, the PVC industry announced its commitment to improve the sustainability of the material through material recycling. We analysed the latest figures from the European PVC industry, ensuring that the statistics included the quantities that enter the market as recyclate. We also analysed the significance of replacing virgin PVC with recyclates. We conclude from this that, after a good three decades, the recycling result is rather meagre. The lion’s share of PVC waste in Europe is still going to waste-to-energy plants, where it tends to be a nuisance. The many announcements to close the chlorine cycle via waste incineration have not got very far either. And the announcements to expand chemical recycling in parallel have not been successful. On the basis of this stocktaking, we have analysed, in a second separately published part, which conclusions can be drawn for regulatory measures, building on a current ECHA investigation report. Full article

The first global stocktake (GST) at 2023 UN Climate Change Conference (COP28) pointed out that accelerating the phasing down of fossil fuels has become an important mitigation policy to maintain a maximum temperature limit of 1.5 °C. The optimal power portfolio for achieving Taiwan’s net-zero emissions by 2050 is evaluated from the perspective of sustainable development. This study is enhances the 2021 research findings of Wang et al. on the sustainable power model, incorporating homogenized cost and technical constraints for empirical analysis. The results indicated that renewable energy sources play a pivotal role in achieving net-zero emissions. Gas power generation requires careful consideration, including early decommissioning or the adoption of carbon capture and storage (CCS) technology to prevent carbon lock-in and compete with hydrogen energy technology. Notably, coal combined with CCS technology offers a viable option for a cost-effective roadmap for a decarburized power generation portfolio by 2050, serving as a reference for national planning strategies for promoting net-zero emissions. Full article

Sustainable energy development (SED) is a crucial component of the Sustainable Development Goals (SDG), aiming to maintain economic and social progress while protecting the environment and mitigating climate change’s effects. SED serves as a transition paradigm for sustainable development, providing a blueprint for energy peace and prosperity for people and all uses. This article presents the history of SED and then uses a critical discourse approach to summarize existing review studies in SED. Ten interlinked themes of SED are identified, with two of them considered to be among the least studied in existing SED reviews and in the current global discussion around climate change. This study explores these two themes, which include energy financing and the need for 100% renewable energy (RE), a sub-theme of decarbonization strategy working towards the 1.5–2.0 °C scenario. The study suggests that the current G20 countries’ contributions, if maintained continuously per annum, in addition to 80% more funding from private investment compared to the amount in the 1.5 °C scenario financial requirements for clean energy, are sufficient to limit global warming. In addition to the present drive for 100% RE, the article also discusses emerging issues, such as energy storage options with an indication of hydrogen as the most promising, other energy-related development agendas, and the need for regional security stability to prevent energy wars. Selected SED decarbonization strategies are presented across the power, transport, building, and industrial sectors. The study concludes with progress and directions for future research, mainly the need for re-defining nationally determined contribution (NDC) through an emissions budgeting and centralized global or regional emissions stock-taking strategy working towards the 1.5 °C scenario. Full article

The boom in technological advances in recent decades has led to increased demand for rare earth elements (REEs) (also known as rare earth metals) across various industries with wide-ranging industrial applications, including in the clean energy sector, but with some environmental, economic, and social footprint concerns. This paper reviews the complexities of the production, consumption, and reuse or recovery of REEs, presenting current trends in terms of potentials and challenges associated with this. This paper in particular focuses on the supply, demand, and (environmental and economic) sustainability of REEs, as a subset of critical raw materials. It does so via a critical stocktaking of key discussions and debates in the field over the past 15 years up until now, through a thematic analysis of the published and gray (policy) literature with a grounded theory approach. The paper finds that carefully balanced lifecycle sustainability assessments are needed for assessing the respective dimensions of the extraction, processing, and reuse or recovery methods for different types of REE sources and supplies to meet current and future demands. It furthermore diagnoses the need for taking into account some shifts and substitutions among REEs also for reasons of cost and locational supplies for the security of supply. Finally, the paper provides some overall policy recommendations for addressing current problems, with a conceptual framing of the UN Sustainable Development Goals. Full article

Currently, the primary method for determining the object coordinates is positioning using Global Navigation Satellite Systems (GNSS) supported by Inertial Navigation Systems (INS). The main goal of this solution is to ensure high positioning availability, particularly when access to satellite signals is limited (in tunnels, areas with densely concentrated buildings and in forest areas). The aim of this article is to determine whether the GNSS/INS system supported by the RTK receiver is suitable for the implementation of selected geodetic and construction tasks in railway engineering, such as determining the place and extent of rail track deformations (1 cm (p = 0.95)), the process of a rapid stocktaking of existing rail tracks (3 cm (p = 0.95)) and for design and construction works (10 cm (p = 0.95)), as well as what the impact of various terrain obstacles have on the obtained positioning accuracy of the tested system. During the research, one INS was used, the Ekinox2-U by the SBG Systems, which was supported by the Real-Time Kinematic (RTK) receiver. GNSS/INS measurements were conducted on three representative sections varying in terms of terrain obstacles that limit the access to satellite signals during mobile railway measurements in Tricity (Poland). The acquired data allowed us to calculate the basic position accuracy measures that are commonly used in navigation and transport applications. On this basis, it was concluded that the Ekinox2-U system can satisfy the positioning accuracy requirements for rapid stocktaking of existing rail tracks (3 cm (p = 0.95)), as well as for design and construction works (10 cm (p = 0.95)). On the other hand, the system cannot be used to determine the place and extent of rail track deformations (1 cm (p = 0.95)). Full article

Records and projections of increasing global average temperature call for improvements of global stocktake inputs, which are vital to achieving targets of intergovernmental agreements on climate change. Unmanned Aerial Vehicle (UAV)-based atmospheric observation of greenhouse gas (GHG) concentrations is an upcoming addition to the top-down measurement methods due to its advantageous spatial-temporal resolutions, greater coverage area and lower costs. Hence, we developed and tested a lightweight UAV payload enclosure integrating a non-dispersive diffusion infrared (NDIR) spectrometer and two electrochemical sensors for measurements of carbon dioxide (CO₂), carbon monoxide (CO) and nitrogen dioxide (NO₂). To achieve higher response times and maintain measurement qualities, we designed a custom air inlet on the rotor-facing side of the enclosure to reduce measurement fluctuations caused by rotor downwash airflow. To validate the payload design, we conducted a controlled test for comparing chambered and chamber-less NDIR spectrometer measurements. From the test we observed a reduction of 0.48 hPa in terms of standard deviation of pressure measurements and minimised downwash-flow-induced anomalous biases (+0.49 ppm and +0.08 hpa for chambered compared to −1.33 ppm and −1.05 hpa for chamber-less). We also conducted an outdoor in-situ measurement test with multiple flights reaching 500 m above ground level (ABGL). The test yielded high resolution results representing vertical distributions of mole fraction concentrations of three types of gases via two types of flight trajectory planning methods. Therefore, we provide an alternative UAV payload integration method for NDIR spectrometer CO₂ measurements that complement existing airborne GHG observation methodologies. Additionally, we also introduced an aerodynamic approach in reducing measurement noises and biases for a low response time sensor configuration. Full article

Across the world, policies and measures are being developed and implemented to reduce the risks of climate change and adapt to its current and projected adverse effects. The Paris Agreement established the global stocktake to evaluate the collective progress made on adaptation. Nevertheless, various challenges still exist when evaluating adaptation progress, among which is the lack of standard definitions to support evaluation efforts. Therefore, we investigated the views of experts regarding the definitions of adaptation given by the Intergovernmental Panel on Climate Change (IPCC) and the definition of successful adaptation by Doria et al., with a focus on Latin America. Using the Delphi method, we obtained relevant knowledge and perspectives. As a result, we identified a high level of consensus (85%) among the experts regarding the IPCC’s definition of climate adaptation. However, there was no consensus on the definition of successful adaptation. For both definitions, we present the elements on which the experts agreed and disagreed, as well as the proposed elements that could improve the definitions to support adaptation evaluation efforts. Additionally, we introduce a list of criteria and indicators that could improve the evaluation of adaptation at different management levels and facilitate the aggregation of information on adaptation progress. Full article

The rationale of this article is the need to elicit the trending themes relevant to the latest research on biodiversity conservation and tourism sustainability. Hence, the purpose of this study: stocktaking of cutting-edge research articles in this field and eliciting the critical trends and issues shaping the knowledge, future research, and technical development perspectives on biodiversity conservation and tourism sustainability. The focus is on the trends, which are pivotal for achieving the UN Sustainable Development Goals until 2030. A hierarchical cluster analysis was undertaken with a KH Coder 3.0 tool to elicit topical co-occurrence networks for thematic words in academic papers from 2015 to 2020 on the topic, quarried from Google Scholar. The article’s main findings are the seven identified major trending research themes on biodiversity conservation and tourism sustainability: (1) Community-based tourism development; (2) National Park management for tourism; (3) Sustainable tourist motivation; (4) Biodiversity conservation and ecotourism; (5) Landscape and land use changes; (6) Visitor satisfaction monitoring; and (7) Ecotourism modelling. The article’s main conclusion is that the criteria and conditions for responsible low-key tourism in protected areas, both for biodiversity and local communities, are pivotal factors to consider for future research on biodiversity conservation and tourism sustainability. Full article

The background of this feature article is a necessity to systematize a vast array of issues pertinent to the latest applications of remote sensing in coastal and marine conservation. Hence the purpose of this study: stocktaking of cutting-edge research articles in this field and eliciting the essential trends and issues shaping the knowledge and future research and technical development perspectives in coastal and marine nature conservation, which is pivotal for meeting the United Nations Sustainable Development Goals till 2030. A hierarchical cluster analysis was undertaken with the KH Coder 3.0 tool to elicit topical co-occurrence networks for thematic words in academic papers from 2015 to 2021 on the topic quarried from Scholar Google. The article’s main findings are the elicited four main trending themes in applications of remote sensing in coastal and marine conservation: (1) Remote Sensing-Based Classification and Modelling; (2) Conservation of Tropical Coastal and Marine Habitats; (3) Mapping of Habitats and Species Distribution; (4) Ecosystem and Biodiversity Conservation and Resource Management. The main conclusion of the article is that habitat vulnerability is a key factor to take into consideration for the future hybrid applications of remote sensing and “citizen science” inputs. Full article

The Anthropocene thesis makes it necessary for the social sciences to engage with temporality in novel ways. The Anthropocene highlights interconnections between ‘natural’ and ‘social’ non-linear temporal processes. However, accounts of humanity’s Anthropocene history often reproduce linear, progressive narratives of human development. This forecloses the possibilities that thinking with non-linear temporalities would offer to the political sciences. Engaging with the temporal complexity of the Anthropocene as a moment of rupture that highlights non-linearity allows to acknowledge more fully the affective impact of living on a disrupted planet. As a discourse about temporal rupture, the Anthropocene is a stocktaking of the already vast insecurities and losses brought about by exploitative relationships with earth and its inhabitants. In this form, the Anthropocene thesis highlights how material and social legacies of inequality and exploitation shape our present and delimit our imaginaries of the future. By including a reckoning of violent pasts into future practices, a productive politics of mourning could take shape. Full article

High spatial resolution carbon dioxide (CO₂) flux inversion systems are needed to support the global stocktake required by the Paris Agreement and to complement the bottom-up emission inventories. Based on the work of Zhang, a regional CO₂ flux inversion system capable of assimilating the column-averaged dry air mole fractions of CO₂ (XCO₂) retrieved from Orbiting Carbon Observatory-2 (OCO-2) observations had been developed. To evaluate the system, under the constraints of the initial state and boundary conditions extracted from the CarbonTracker 2017 product (CT2017), the annual CO₂ flux over the contiguous United States in 2016 was inverted (1.08 Pg C yr⁻¹) and compared with the corresponding posterior CO₂ fluxes extracted from OCO-2 model intercomparison project (OCO-2 MIP) (mean: 0.76 Pg C yr⁻¹, standard deviation: 0.29 Pg C yr⁻¹, 9 models in total) and CT2017 (1.19 Pg C yr⁻¹). The uncertainty of the inverted CO₂ flux was reduced by 14.71% compared to the prior flux. The annual mean XCO₂ estimated by the inversion system was 403.67 ppm, which was 0.11 ppm smaller than the result (403.78 ppm) simulated by a parallel experiment without assimilating the OCO-2 retrievals and closer to the result of CT2017 (403.29 ppm). Independent CO₂ flux and concentration measurements from towers, aircraft, and Total Carbon Column Observing Network (TCCON) were used to evaluate the results. Mean bias error (MBE) between the inverted CO₂ flux and flux measurements was 0.73 g C m⁻² d⁻¹, was reduced by 22.34% and 28.43% compared to those of the prior flux and CT2017, respectively. MBEs between the CO₂ concentrations estimated by the inversion system and concentration measurements from TCCON, towers, and aircraft were reduced by 52.78%, 96.45%, and 75%, respectively, compared to those of the parallel experiment. The experiment proved that CO₂ emission hotspots indicated by the inverted annual CO₂ flux with a relatively high spatial resolution of 50 km consisted well with the locations of most major metropolitan/urban areas in the contiguous United States, which demonstrated the potential of combing satellite observations with high spatial resolution CO₂ flux inversion system in supporting the global stocktake. Full article

Mapping the spatial variation of forest aboveground biomass (AGB) at the national or regional scale is important for estimating carbon emissions and removals and contributing to global stocktake and balancing the carbon budget. Recently, several gridded forest AGB products have been produced for China by integrating remote sensing data and field measurements, yet significant discrepancies remain among these products in their estimated AGB carbon, varying from 5.04 to 9.81 Pg C. To reduce this uncertainty, here, we first compiled independent, high-quality field measurements of AGB using a systematic and consistent protocol across China from 2011 to 2015. We applied two different approaches, an optimal weighting technique (WT) and a random forest regression method (RF), to develop two observationally constrained hybrid forest AGB products in China by integrating five existing AGB products. The WT method uses a linear combination of the five existing AGB products with weightings that minimize biases with respect to the field measurements, and the RF method uses decision trees to predict a hybrid AGB map by minimizing the bias and variance with respect to the field measurements. The forest AGB stock in China was 7.73 Pg C for the WT estimates and 8.13 Pg C for the RF estimates. Evaluation with the field measurements showed that the two hybrid AGB products had a lower RMSE (29.6 and 24.3 Mg/ha) and bias (−4.6 and −3.8 Mg/ha) than all five participating AGB datasets. Our study demonstrated both the WT and RF methods can be used to harmonize existing AGB maps with field measurements to improve the spatial variability and reduce the uncertainty of carbon stocks. The new spatial AGB maps of China can be used to improve estimates of carbon emissions and removals at the national and subnational scales. Full article