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Auswahl der wissenschaftlichen Literatur zum Thema „High-Resolution emission monitoring“
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Zeitschriftenartikel zum Thema "High-Resolution emission monitoring"
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Ctvrtlik, Radim, Jan Tomastik, Lukas Vaclavek, Ben D. Beake, Adrian J. Harris, Alberto Sanchez Martin, Michal Hanak und Petr Abrham. „High-Resolution Acoustic Emission Monitoring in Nanomechanics“. JOM 71, Nr. 10 (05.08.2019): 3358–67. http://dx.doi.org/10.1007/s11837-019-03700-8.
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Chen, Wenjian, Yi Wang, Xuan Li, Wei Gao, Shiwei Ma, Yuanyuan Duan und Xiaopeng Shao. „Hazardous Gas Emission Monitoring Based on High-Resolution Images“. Journal of Spectroscopy 2018 (2018): 1–7. http://dx.doi.org/10.1155/2018/2698025.
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Air pollution presents unprecedentedly severe challenges to humans today. Various measures have been taken to monitor pollution from gas emissions and the changing atmosphere, of which imaging is of crucial importance. By images of target scenes, intuitional judgments and in-depth data are achievable. However, due to the limitations of imaging devices, effective and efficient monitoring work is often hindered by low-resolution target images. To deal with this problem, a superresolution reconstruction method was proposed in this study for high-resolution monitoring images. It was based on the idea of sparse representation. Particularly, multiple dictionary pairs were trained according to the gradient features of samples, and one optimal pair of dictionaries was chosen to reconstruct by judging the weighting of the information in different directions. Furthermore, the K-means singular value decomposition algorithm was used to train the dictionaries and the orthogonal matching pursuit algorithm was employed to calculate the sparse coding coefficients. Finally, the experiment’s results demonstrated its advantages in both visual fidelity and numerical measures.
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Chen, Xiaochun, Jianhui Li, Min Jia, Shaobo Chen, Shangxuan Zhang, Xin Bo, Xue Feng und Guangxia Dong. „High Spatial Resolution Emission Inventory of Air Pollutants and Carbon in China’s Independent Coking Industry“. Atmosphere 14, Nr. 2 (09.02.2023): 348. http://dx.doi.org/10.3390/atmos14020348.
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China is the largest producer and exporter of coke globally, which means that it is very important to understand the characteristics of air pollutants and carbon emissions from China’s independent coking industry. This study was the first to establish a bottom-up inventory of the air pollutants and carbon emissions of China’s independent coking industry during 2001–2018 based on continuous emission monitoring system online monitoring data and unit-based corporate information. Based on the developed emission inventory, four scenarios were established to analyze potential emissions reduction of air pollutants and carbon dioxide (CO2) in future. The emissions of particulate matter (PM10 and PM2.5), sulfur dioxide (SO2), black carbon (BC) and organic carbon (OC) decreased by 62.11%, 63.41%, 72.85%, 63.41% and 63.41%, respectively. CO2, carbon monoxide (CO), volatile organic compounds (VOCs) and nitrogen oxides (NOX) emissions increased by 355.51%, 355.51%, 355.51% and 99.74%, respectively. In 2018, PM10, PM2.5, SO2, NOx, BC, OC, CO, VOCs and CO2 emissions were, respectively. 45.20, 16.91, 63.84, 117.71, 5.07, 5.92, 554.91, 1026.58 Gg, and 176.88 Tg. Shanxi province made the greatest contributions to the total emissions of air pollutants and CO2 from this industry by 25.01%. The emission source that contributed most to PM2.5 (SO2 and NOX) emissions was coke pushing (quenching and the coke oven chimney respectively) in 2018. Under the ULE scenario (2018–2035), PM2.5 and SO2 emissions will reduce by more than 30%. Under the PCP scenario, PM2.5 and SO2 emissions will reduce by more than 55%. Under the CBP scenario, CO2 emissions will peak at 197.99 Tg in 2025 and decrease to 70% of the peak in 2035. The results showed the emission characteristics of air pollutants and CO2, future emission with several scenarios and cooperative reduction potential in China’s independent coking industry, which provides scientific support for the development of pollution control strategies.
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Huang, Qing, Hao Han, Zhan Yi Zhang, Bo Guang Wang und Chun Lin Zhang. „The Methodology to Establish a High Temporal Resolution Emission Inventory for Tunnel Source in City“. Advanced Materials Research 955-959 (Juni 2014): 1380–83. http://dx.doi.org/10.4028/www.scientific.net/amr.955-959.1380.
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Tunnel source is an important emission source in urban microenvironment, and the influence of emission pollutants from tunnel source to air quality in surrounding area could not be ignored. In this study the monitoring data in the entrance and the exit of the tunnel was used to calculate the emission amount from tunnel source. Then the methodology to establish the tunnel source emission inventory with a high temporal resolution was discussed in this paper. This research would provide basis for the establishment of the emission inventory in urban microenvironment, and provide a more realistic emissions inventory to Air Quality Model.
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Bandiera, Rino, Paola Focardi, Aldo Altamore, Corinne Rossi und Otmar Stahl. „High-resolution emission line profiles in blue luminous stars“. International Astronomical Union Colloquium 113 (1989): 279–80. http://dx.doi.org/10.1017/s0252921100004620.
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Emission lines are often observed in high luminosity stars and provide evidence of the presence of extended stellar envelopes. Ha is the most frequently observed across the H-R diagram, but lines of Hel or Fell are also found in emission in these stars. They could be used as diagnostics of the structure of their outer atmospheres and winds. High resolution (1/dl ~ 105) high S/N profiles of Ha and Hel 5876 in the galactic LBVs η Car, AG and HR Car, and in the LMC star S22 have been obtained with the ESO CAT-CES during 1984-87, and are described in Figs.1-5. We find that these stars show a large variety of profiles with narrow and broad emissions, wide or multiple blue-shifted absorptions. The profiles are largely variable. Once, a kind of inverse P Cyg profile was observed in HR Car (Fig.4). These results indicate the presence of large scale phenomena and high velocity fields which are dramatically variable in time. Continuous HIRES monitoring of these stars is urgently needed.
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Schuit, Berend J., Joannes D. Maasakkers, Pieter Bijl, Gourav Mahapatra, Anne-Wil van den Berg, Sudhanshu Pandey, Alba Lorente et al. „Automated detection and monitoring of methane super-emitters using satellite data“. Atmospheric Chemistry and Physics 23, Nr. 16 (19.09.2023): 9071–98. http://dx.doi.org/10.5194/acp-23-9071-2023.
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Abstract. A reduction in anthropogenic methane emissions is vital to limit near-term global warming. A small number of so-called super-emitters is responsible for a disproportionally large fraction of total methane emissions. Since late 2017, the TROPOspheric Monitoring Instrument (TROPOMI) has been in orbit, providing daily global coverage of methane mixing ratios at a resolution of up to 7×5.5 km2, enabling the detection of these super-emitters. However, TROPOMI produces millions of observations each day, which together with the complexity of the methane data, makes manual inspection infeasible. We have therefore designed a two-step machine learning approach using a convolutional neural network to detect plume-like structures in the methane data and subsequently apply a support vector classifier to distinguish the emission plumes from retrieval artifacts. The models are trained on pre-2021 data and subsequently applied to all 2021 observations. We detect 2974 plumes in 2021, with a mean estimated source rate of 44 t h−1 and 5–95th percentile range of 8–122 t h−1. These emissions originate from 94 persistent emission clusters and hundreds of transient sources. Based on bottom-up emission inventories, we find that most detected plumes are related to urban areas and/or landfills (35 %), followed by plumes from gas infrastructure (24 %), oil infrastructure (21 %), and coal mines (20 %). For 12 (clusters of) TROPOMI detections, we tip and cue the targeted observations and analysis of high-resolution satellite instruments to identify the exact sources responsible for these plumes. Using high-resolution observations from GHGSat, PRISMA, and Sentinel-2, we detect and analyze both persistent and transient facility-level emissions underlying the TROPOMI detections. We find emissions from landfills and fossil fuel exploitation facilities, and for the latter, we find up to 10 facilities contributing to one TROPOMI detection. Our automated TROPOMI-based monitoring system in combination with high-resolution satellite data allows for the detection, precise identification, and monitoring of these methane super-emitters, which is essential for mitigating their emissions.
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Zhao, Y., L. P. Qiu, R. Y. Xu, F. J. Xie, Q. Zhang, Y. Y. Yu, C. P. Nielsen et al. „Advantages of a city-scale emission inventory for urban air quality research and policy: the case of Nanjing, a typical industrial city in the Yangtze River Delta, China“. Atmospheric Chemistry and Physics 15, Nr. 21 (12.11.2015): 12623–44. http://dx.doi.org/10.5194/acp-15-12623-2015.
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Abstract. With most eastern Chinese cities facing major air quality challenges, there is a strong need for city-scale emission inventories for use in both chemical transport modeling and the development of pollution control policies. In this paper, a high-resolution emission inventory (with a horizontal resolution of 3 × 3 km) of air pollutants and CO2 for Nanjing, a typical large city in the Yangtze River Delta, is developed, incorporating the best available information on local sources. Emission factors and activity data at the unit or facility level are collected and compiled using a thorough on-site survey of major sources. Over 900 individual plants, which account for 97 % of the city's total coal consumption, are identified as point sources, and all of the emission-related parameters including combustion technology, fuel quality, and removal efficiency of air pollution control devices (APCD) are analyzed. New data-collection approaches including continuous emission monitoring systems and real-time monitoring of traffic flows are employed to improve spatiotemporal distribution of emissions. Despite fast growth of energy consumption between 2010 and 2012, relatively small interannual changes in emissions are found for most air pollutants during this period, attributed mainly to benefits of growing APCD deployment and the comparatively strong and improving regulatory oversight of the large point sources that dominate the levels and spatial distributions of Nanjing emissions overall. The improvement of this city-level emission inventory is indicated by comparisons with observations and other inventories at larger spatial scale. Relatively good spatial correlations are found for SO2, NOx, and CO between the city-scale emission estimates and concentrations at nine state-operated monitoring sites (R = 0.58, 0.46, and 0.61, respectively). The emission ratios of specific pollutants including BC to CO, OC to EC, and CO2 to CO compare well to top-down constraints from ground observations. The interannual variability and spatial distribution of NOx emissions are consistent with NO2 vertical column density measured by the Ozone Monitoring Instrument (OMI). In particular, the Nanjing city-scale emission inventory correlates better with satellite observations than the downscaled Multi-resolution Emission Inventory for China (MEIC) does when emissions from power plants are excluded. This indicates improvement in emission estimation for sectors other than power generation, notably industry and transportation. A high-resolution emission inventory may also provide a basis to consider the quality of instrumental observations. To further improve emission estimation and evaluation, more measurements of both emission factors and ambient levels of given pollutants are suggested; the uncertainties of emission inventories at city scale should also be fully quantified and compared with those at national scale.
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Kulenkampff, Johannes, Marion Gründig, Abdelhamid Zakhnini und Johanna Lippmann-Pipke. „Geoscientific process monitoring with positron emission tomography (GeoPET)“. Solid Earth 7, Nr. 4 (18.08.2016): 1217–31. http://dx.doi.org/10.5194/se-7-1217-2016.
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Abstract. Transport processes in geomaterials can be observed with input–output experiments, which yield no direct information on the impact of heterogeneities, or they can be assessed by model simulations based on structural imaging using µ-CT. Positron emission tomography (PET) provides an alternative experimental observation method which directly and quantitatively yields the spatio-temporal distribution of tracer concentration. Process observation with PET benefits from its extremely high sensitivity together with a resolution that is acceptable in relation to standard drill core sizes. We strongly recommend applying high-resolution PET scanners in order to achieve a resolution on the order of 1 mm. We discuss the particularities of PET applications in geoscientific experiments (GeoPET), which essentially are due to high material density. Although PET is rather insensitive to matrix effects, mass attenuation and Compton scattering have to be corrected thoroughly in order to derive quantitative values. Examples of process monitoring of advection and diffusion processes with GeoPET illustrate the procedure and the experimental conditions, as well as the benefits and limits of the method.
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Wu, Xiaomeng, Daoyuan Yang, Ruoxi Wu, Jiajun Gu, Yifan Wen, Shaojun Zhang, Rui Wu et al. „High-resolution mapping of regional traffic emissions using land-use machine learning models“. Atmospheric Chemistry and Physics 22, Nr. 3 (10.02.2022): 1939–50. http://dx.doi.org/10.5194/acp-22-1939-2022.
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Abstract. On-road vehicle emissions are a major contributor to significant atmospheric pollution in populous metropolitan areas. We developed an hourly link-level emissions inventory of vehicular pollutants using two land-use machine learning methods based on road traffic monitoring datasets in the Beijing–Tianjin–Hebei (BTH) region. The results indicate that a land-use random forest (LURF) model is more capable of predicting traffic profiles than other machine learning models on most occasions in this study. The inventories under three different traffic scenarios depict a significant temporal and spatial variability in vehicle emissions. NOx, fine particulate matter (PM2.5), and black carbon (BC) emissions from heavy-duty trucks (HDTs) generally have a higher emission intensity on the highways connecting to regional ports. The model found a general reduction in light-duty passenger vehicles when traffic restrictions were implemented but a much more spatially heterogeneous impact on HDTs, with some road links experiencing up to 40 % increases in the HDT traffic volume. This study demonstrates the power of machine learning approaches to generate data-driven and high-resolution emission inventories, thereby providing a platform to realize the near-real-time process of establishing high-resolution vehicle emission inventories for policy makers to engage in sophisticated traffic management.
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Zhao, Y., L. Qiu, R. Xu, F. Xie, Q. Zhang, Y. Yu, C. P. Nielsen et al. „Advantages of city-scale emission inventory for urban air quality research and policy: the case of Nanjing, a typical industrial city in the Yangtze River Delta, China“. Atmospheric Chemistry and Physics Discussions 15, Nr. 13 (09.07.2015): 18691–746. http://dx.doi.org/10.5194/acpd-15-18691-2015.
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Abstract. With most eastern Chinese cities facing major air quality challenges, there is a strong need for city-scale emission inventories for use in both chemical transport modeling and the development of pollution control policies. In this paper, a high-resolution emission inventory of air pollutants and CO2 for Nanjing, a typical large city in the Yangtze River Delta, is developed incorporating the best available information on local sources. Emission factors and activity data at the unit or facility level are collected and compiled using a thorough onsite survey of major sources. Over 900 individual plants, which account for 97 % of the city's total coal consumption, are identified as point sources, and all of the emission-related parameters including combustion technology, fuel quality, and removal efficiency of air pollution control devices (APCD) are analyzed. New data-collection approaches including continuous emission monitoring systems and real-time monitoring of traffic flows are employed to improve spatiotemporal distribution of emissions. Despite fast growth of energy consumption between 2010 and 2012, relatively small inter-annual changes in emissions are found for most air pollutants during this period, attributed mainly to benefits of growing APCD deployment and the comparatively strong and improving regulatory oversight of the large point sources that dominate the levels and spatial distributions of Nanjing emissions overall. The improvement of this city-level emission inventory is indicated by comparisons with observations and other inventories at larger spatial scale. Relatively good spatial correlations are found for SO2, NOx, and CO between the city-scale emission estimates and concentrations at 9 state-opertated monitoring sites (R = 0.58, 0.46, and 0.61, respectively). The emission ratios of specific pollutants including BC to CO, OC to EC, and CO2 to CO compare well to top-down constraints from ground observations. The inter-annual variability and spatial distribution of NOx emissions are consistent with NO2 vertical column density measured by the Ozone Monitoring Instrument (OMI). In particular, the Nanjing city-scale emission inventory correlates better with satellite observations than the downscaled Multi-resolution Emission Inventory for China (MEIC) does when emissions from power plants are excluded. This indicates improvement in emission estimation for sectors other than power generation, notably industry and transportation. High-resolution emission inventory may also provide a basis to consider the quality of instrumental observations. To further improve emission estimation and evaluation, more measurements of both emission factors and ambient levels of given pollutants are suggested; the uncertainties of emission inventories at city scale should also be fully quantified and compared with those at national scale.
Dissertationen zum Thema "High-Resolution emission monitoring"
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Baldauf, Thomas [Verfasser], und Michael [Akademischer Betreuer] Köhl. „Monitoring Reduced Emissions from Deforestation and Forest Degradation (REDD+) : Capabilities of High- Resolution Active Remote Sensing / Thomas Baldauf. Betreuer: Michael Köhl“. Hamburg : Staats- und Universitätsbibliothek Hamburg, 2013. http://d-nb.info/1036729591/34.
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Plauchu, Robin. „Assimilation de données satellitaires de concentrations atmosphériques pour le suivi des émissions de NOx et de CO en France“. Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASJ035.
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L'objectif de cette thèse est de contribuer au développement de capacités de modélisation atmosphérique inverse pour l'estimation des émissions françaises de NOx et de CO à des échelles pertinentes pour les décideurs, de l'échelle nationale à celle de régions administratives ou de grandes agglomérations, de l'échelle annuelle à l'échelle hebdomadaire, pour aider à la définition de politiques de régulation et d'autre part, pour évaluer l'efficacité de ces politiques.Les politiques de régulation se basent historiquement sur des inventaires d'émissions s'appuyant sur des statistiques associées aux activités socio-économiques. Depuis plusieurs années, une approche complémentaire est développée : celle de l'inversion atmosphérique des émissions, qui exploite en synergie des méthodes statistiques d'inversion, des observations atmosphériques et des modèles de chimie-transport.Mes travaux de thèse ont donc porté sur l'inversion des émissions françaises de NOx et de CO, à la résolution horizontale relativement fine de 10 km². Pour cela, j'ai utilisé les récentes observations de l'instrument satellitaire TROPOspheric Monitoring Instrument (TROPOMI), qui fournit des colonnes troposphériques de NO2 et des colonnes totales de CO, à une résolution spatiale sans précédent. J'ai aussi utilisé le mode variationnel du Community Inversion Framework (CIF), qui pilote le modèle de chimie-transport régional CHIMERE, incluant un module de chimie prenant en compte la chimie complexe des NOx en phase gazeuse, et son adjoint.Une attention particulière a été portée sur la quantification des réductions des émissions françaises de NOx dues à la pandémie de COVID-19 et à ses confinements. De plus, à haute résolution spatiale, les erreurs associées à la modélisation du transport atmosphérique peuvent être importantes. Un moyen de contourner ce problème et d'exploiter l'information donnée par les images sur les structures spatiales telles que celles de NO2 dans les images TROPOMI est de définir un vecteur d'observation pour l'inversion basé sur des informations extraites des images, moins impactées par les erreurs de modélisation du transport que l'ensemble des pixels individuels de l'image, dont la valeur serait essentiellement pilotée par les émissions ciblées par l'inversion, et dont les erreurs de simulation ne seraient pas corrélées d'une observation à l'autre. Le potentiel d'une telle approche de changement de vecteur d'observation pour l'assimilation des images TROPOMI de NO2 sur la France dans un système d'inversion a été analysé.Ces travaux s'inscrivent dans l'effort de développement, à plus long terme, d'un outil opérationnel pour le suivi des émissions françaises de polluants et de gaz à effet de serre à haute résolutionThe objective of this thesis is to contribute to the development of inverse atmospheric modelling capabilities for estimating French NOx and CO emissions at scales relevant to decision makers, from the national level to administrative regions or large urban areas, and from annual to weekly scales. The aim is to support the formulation of regulatory policies and to evaluate their effectiveness.Historically, regulatory policies have been based on emission inventories derived from statistics related to socio-economic activities. In recent years, a complementary approach has been developed: atmospheric inversion of emissions, which uses statistical inversion methods, atmospheric observations, and chemistry-transport models in synergy.My PhD thesis therefore focused on the inversion of French NOx and CO emissions at a relatively fine horizontal resolution of 10 km². To achieve this, I used recent observations from the TROPOspheric Monitoring Instrument (TROPOMI), which provides tropospheric columns of NO2 and total columns of CO with unprecedented spatial resolution. I also used the variational mode of the Community Inversion Framework (CIF), which drives the regional chemistry-transport model CHIMERE, including a module that accounts for the complex gas-phase chemistry of NOx and its adjoint.Particular attention has been paid to quantifying the reduction in French NOx emissions due to the COVID-19 pandemic and its lockdowns. Moreover, at high spatial resolution, errors associated with atmospheric transport modelling can be significant. One way to overcome this problem and to exploit the information provided by satellite images on spatial structures, such as that of NO2 in the TROPOMI images, is to define an observation vector for the inversion based on information extracted from images that are less affected by transport modelling errors than individual pixels. This observation vector would predominantly reflect the emissions targeted by the inversion and would not contain correlated simulation errors between observations. The potential of such an approach, involving a change in the observation vector for the assimilation of TROPOMI NO2 images over France in an inversion system, has been analysed.This work is part of a longer-term effort to develop an operational tool for monitoring French pollutant and greenhouse gas emissions at high resolution
Buchteile zum Thema "High-Resolution emission monitoring"
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Dajuma, Alima, Siélé Silué, Kehinde O. Ogunjobi, Heike Vogel, Evelyne Touré N’Datchoh, Véronique Yoboué, Arona Diedhiou und Bernhard Vogel. „Biomass Burning Effects on the Climate over Southern West Africa During the Summer Monsoon“. In African Handbook of Climate Change Adaptation, 1515–32. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-45106-6_86.
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AbstractBiomass Burning (BB) aerosol has attracted considerable attention due to its detrimental effects on climate through its radiative properties. In Africa, fire patterns are anticorrelated with the southward-northward movement of the intertropical convergence zone (ITCZ). Each year between June and September, BB occurs in the southern hemisphere of Africa, and aerosols are carried westward by the African Easterly Jet (AEJ) and advected at an altitude of between 2 and 4 km. Observations made during a field campaign of Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa (DACCIWA) (Knippertz et al., Bull Am Meteorol Soc 96:1451–1460, 2015) during the West African Monsoon (WAM) of June–July 2016 have revealed large quantities of BB aerosols in the Planetary Boundary Layer (PBL) over southern West Africa (SWA).This chapter examines the effects of the long-range transport of BB aerosols on the climate over SWA by means of a modeling study, and proposes several adaptation and mitigation strategies for policy makers regarding this phenomenon. A high-resolution regional climate model, known as the Consortium for Small-scale Modelling – Aerosols and Reactive Traces (COSMO-ART) gases, was used to conduct two set of experiments, with and without BB emissions, to quantify their impacts on the SWA atmosphere. Results revealed a reduction in surface shortwave (SW) radiation of up to about 6.5 W m−2 and an 11% increase of Cloud Droplets Number Concentration (CDNC) over the SWA domain. Also, an increase of 12.45% in Particulate Matter (PM25) surface concentration was observed in Abidjan (9.75 μg m−3), Accra (10.7 μg m−3), Cotonou (10.7 μg m−3), and Lagos (8 μg m−3), while the carbon monoxide (CO) mixing ratio increased by 90 ppb in Abidjan and Accra due to BB. Moreover, BB aerosols were found to contribute to a 70% increase of organic carbon (OC) below 1 km in the PBL, followed by black carbon (BC) with 24.5%. This work highlights the contribution of the long-range transport of BB pollutants to pollution levels in SWA and their effects on the climate. It focuses on a case study of 3 days (5–7 July 2016). However, more research on a longer time period is necessary to inform decision making properly.This study emphasizes the need to implement a long-term air quality monitoring system in SWA as a method of climate change mitigation and adaptation.
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Das, Poppy, und Hemalatha K. „HYBRID IMAGING: A NEW FRONTIER IN MEDICINE“. In Futuristic Trends in Pharmacy & Nursing Volume 3 Book 5, 270–89. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bapn5ch26.
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Medical imaging facilitates the visualization of the internal organs and tissues in the human body. It helps to monitor the anatomy, morphology, and physiology of the body, and diagnose any abnormalities. There are several imaging techniques which are being used for many decades such as ultrasonography, X-ray, positron emission tomography (PET), magnetic resonance imaging (MRI), computed tomography (CT), and single-photon emission computed tomography (SPECT). These imaging techniques offer a wide range of application ranging from diagnosis of cancer, neurological disorders, cardiovascular disorders, bone defects, gastrointestinal disorders, planning of radiation therapy for cancer, monitoring treatment progress and many others. However, these techniques have certain limitations which has led to the fusion of multiple imaging modalities. These hybrid imaging techniques provide better reliability, high resolution images, and detailed information while ensuring safety, specificity, and sensitivity. This chapter provides information on some of the hybrid imaging techniques used in modern medicine.
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J. Palestro, Christopher. „PET Imaging of Infection“. In Pericarditis - Diagnosis and Management Challenges [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.110633.
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Nuclear medicine has played an important part in the diagnosis of infection for 50 years. Gallium-67 citrate was one of the first radionuclides used for diagnosing and localizing infection. The development of techniques for radiolabeling leukocytes and monitoring their migration to foci of infection was a significant advance. More recently, investigators have worked on developing positron-emitting radiopharmaceuticals for diagnosing infection. Positron emission tomography (PET) provides high-resolution three-dimensional images, facilitating precise localization of radiopharmaceutical uptake. Semiquantitative analysis could facilitate the differentiation of infectious from noninfectious conditions and could be used to monitor treatment response. Not surprisingly, the first PET agent investigated was fluorine 18-fluorodeoxyglucose (18F-FDG). Although 18F-FDG has proved to be invaluable for diagnosing infection, it is not specific, and also accumulates in neoplasms, and noninfectious inflammatory conditions. Considerable effort has been devoted to developing PET radiopharmaceuticals that are specific, or at least more specific than 18F-FDG, for infection. Investigators have explored the potential of leukocytes labeled in vitro with various PET radiopharmaceuticals, gallium-68 citrate, gallium-68 labeled peptides, iodine-124 fialuridine, and 18F-fluorodeoxysorbitol. This chapter reviews the role of 18F-FDG for diagnosing infection and monitoring treatment response and other PET agents whose potential for diagnosing infection has been studied.
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Ulloa-Vásquez, Fernando, Víctor Heredia-Figueroa, Cristóbal Espinoza-Iriarte, José Tobar-Ríos und Fernanda Aguayo-Reyes. „Characterization of the Electrical Consumption Pattern of Household Appliances for Home Energy Management Using High-Resolution Measurement Techniques in IoT Environments“. In Sustainable Development. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.110355.
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For future smart cities, smart homes will be required. The key elements are the smart use of energy and smart communication systems that are connected to homes. Along with this, the devices inside the house will need to be monitored and managed efficiently. One of the current proposals is the use of Home Energy Management Systems (HEMS) allowing to solve problems associated with efficient management, the economy of electrical energy, and failures/alarms regarding the operation and safety of appliances. This work proposes a model for the recognition of patterns of energy consumption in household appliances, based on the capture of electrical parameters through Smart Socket, using an intrusive method in the electric charge. The data acquisition system corresponds to an IoT platform that uses automatic meter reading elements, which, connected via Wi-Fi, send data to a cloud service. The results obtained allow a characterization of household appliance consumption profiles, with high levels of reliability and under multiple operating states. Because of the foregoing, the detection, monitoring, and control of household appliances connected to the electrical network allow the reduction of both household billing and CO2 emissions.
Konferenzberichte zum Thema "High-Resolution emission monitoring"
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Karim, Andrew, Abdullah Algharrash, Arnav Ranjekar, Asmamaw Esayas, Helen Haile, Jash Dagli, Pranav P R et al. „Small Satellite Design for High-Resolution Methane Emissions Monitoring“. In 31st IAA Symposium on Small Satellite Missions, Held at the 75th International Astronautical Congress (IAC 2024), 374–81. Paris, France: International Astronautical Federation (IAF), 2024. https://doi.org/10.52202/078365-0042.
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Turlej, Tymoteusz, Krzysztof Kolodziejczyk und Jedrzej Minda. „MONITORING SOLAR FARMS USING DRONES - UTILIZED TECHNIQUES AND BENEFITS“. In 24th SGEM International Multidisciplinary Scientific GeoConference 24, 149–56. STEF92 Technology, 2024. https://doi.org/10.5593/sgem2024/4.1/s17.19.
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The article describes commonly used imaging techniques for monitoring solar farms using drones, highlighting the advantages of each method and the benefits of precise flight path planning. Thermal imaging is discussed for its ability to detect temperature variations and identify potential issues like cell degradation and electrical failures without physical inspection. High-resolution imaging provides detailed visual inspections to identify physical damages, dirt accumulation, and shading issues, enhancing maintenance scheduling and operational efficiency. Multispectral imaging captures data across various wavelengths, aiding in performance assessment and identifying aging panels, thereby supporting better maintenance decisions. Intelligent flight path planning algorithms are also highlighted for their role in optimizing drone inspections, ensuring comprehensive data collection, and minimizing inspection time. The article also summarizes the overall benefits of using drones for solar farm monitoring, including cost-effectiveness by reducing labor and downtime, increased safety by eliminating the need for physical inspections in hazardous areas, and time efficiency due to rapid data collection. Additionally, drones provide comprehensive data collection, supporting informed decision-making and long-term planning, and contribute to environmental sustainability by optimizing the performance and efficiency of solar panels, thus reducing greenhouse gas emissions. Through these advancements, drones play a crucial role in enhancing the management and sustainability of solar farms, driving the transition towards a greener future.
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Schmidt, M., S. Gorny, N. Rüssmeier und K. Partes. „Investigation on Laser Cladding Processes Using High-Resolution In-Line Atomic Emission Spectroscopy“. In ITSC2022. DVS Media GmbH, 2022. http://dx.doi.org/10.31399/asm.cp.itsc2022p0876.
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Abstract Process monitoring and control methods during direct metal deposition (DMD) are used to ensure a consistent manufacturing quality of the process. In the optical regime, naturally occurring process emission provides therefore selective and specific element lines, which can be obtained by optical spectrometers. However, DMD processes are in the heat conduction regime and superimposed broad spectral emissions dominate the wavelength specific signals. The aim of this work is to investigate the occurrence of different elemental lines in DMD processes as well as deposition track cross-sectional dimensions. Therefore, experiments were simultaneously conducted by using a high-resolution spectrometer (resolution = approx. 47 pm FWHM at 522 nm and 55 pm FWHM at 407.5 nm) and a medium resolution spectrometer (resolution = 0.73 nm FWHM), which were coupled by a bifurcated optical fibre. A parameter study of 27 single track DMD experiments using Co-Cr-based (MetcoClad21) powder on low-alloyed tool steel C45W (1.1730) substrate material, varying laser power, scan velocity and powder feed rate was conducted. Series of spectra were obtained for all sets of parameters with a scan rate of 100 Hz. The individual wavelength spectrum was analysed and classified by an algorithm into two types. Type-A spectra, with specific element emission lines and Type-B spectra, without significant emission lines with mostly predominant thermal emission radiation. Each deposition track was coupled to cross-sectional dimensions, including height, welding depth and melted areas. In addition, certain elemental lines contained in Type-A spectra were verified by using data from the NIST atomic spectra database. The investigation indicates that the relative number of Type-A spectra with respect to the total quantity of spectra, correlates significant to the process parameters. All detected and identified element lines occurred to be non-ionised elements, especially Cr I, Fe I and Mn I lines were frequently observed.
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LIU, CHEN, OLIVER NAGLER, FLORIAN TREMMEL, MARIANNE UNTERREITMEIER, JESSICA J. FRICK und DEBBIE G. SENESKY. „ACOUSTIC EMISSION SIGNAL PROCESSING STUDY OF NANOINDENTATION ON THIN FILM STACK STRUCTURES USING GAUSSIAN MIXTURE MODEL“. In Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36364.
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This investigation utilizes a material testing system that integrates acoustic emission (AE) testing with a nanoindentation system for crack generation and detection in Al-Cu top thin-film stack structures. The suitability of using the AE method was verified with scanning electron microscope (SEM) images of indent cross-sections. In order to cluster the AE signals based on a different physical meaning, a signal processing approach based on the Gaussian mixture model (GMM) clustering algorithm was applied. Principal component analysis (PCA) and autoencoder feature extraction methods were used to reduce the dimension of the signal. This signal processing approach has the promising ability to distinguish AE events associated with crack formation and metal layer plastic deformation. This integrated test system and signal processing approach provide a high-resolution mechanical testing platform for studying and enabling automatic, non-destructive crack detection in wafer probing.
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Sears, Trevor J. „High-resolution spectroscopy of chemical intermediates“. In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1990. http://dx.doi.org/10.1364/oam.1990.wc1.
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Infrared and UV-vis laser spectroscopy has been used to study a number of small free radicals, with an emphasis on those exhibiting large amplitude vibrational motion or a strong breakdown of the Born-Oppenheimer approximation. Recently, we have detected gas phase infrared absorption spectra of the ethyl (C2H5) and carboxyl (HOCO) radicals for the first time. The C2H5 spectrum shows clear evidence for nearly free rotation of the CH2 radical center relative to the CH3 end of the molecule, while the HOCO spectrum appears to be somewhat simpler although analysis is far from complete. Following spectroscopic characterization of these species, infrared absorption will offer a precise and sensitive method for monitoring the radical concentrations on a state-by-state basis. Other species including NCS, C3, and NCO have been studied by laser induced fluorescence in a supersonic free jet expansion. Highly excited vibrational states have been accessed by optical double resonance (stimulated emission pumping) and the experimental data demand extensions of the standard effective Hamiltonian treatments describing the energy levels of these and similar species as increasing amounts of energy are placed in the internal modes.
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Hilton, Moira, Alan H. Lettington und Chris W. Wilson. „Gas Turbine Exhaust Emissions Monitoring Using Non-Intrusive Infrared Spectroscopy“. In ASME 1997 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/97-gt-180.
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Infrared (IR) spectra of the exhaust emissions from a static gas turbine engine have been studied using Fourier Transform (FT) spectroscopic techniques. Passive detection of the infrared emission from remote (range ∼ 3 m) hot exhaust gases was obtained non-intrusively using a high spectral resolution (0.25 cm−1) FTIR spectrometer. Remote gas temperatures were determined from their emission spectra using the total radiant flux method or by analysis of rotational line structure. The HITRAN database of atmospheric species was used to model the emission from gas mixtures at the relevant temperatures. The spatial distribution of molecular species across a section transverse to the exhaust plume −10 cm downstream of the jet pipe nozzle was studied using a tomographic reconstruction procedure. Spectra of the infrared emission from the plume were taken along a number of transverse lines of sight from the centreline of the engine outwards. A mathematical matrix inversion technique was applied to reconstruct the molecular concentrations of CO and CO2 in concentric regions about the centreline. Quantitative measurements of the molecular species concentrations determined non-intrusively were compared with results from conventional extractive sampling techniques.
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Grisar, R., U. Klocke, W. J. Riedel, H. Wolf und G. Schmidtke. „Gas imission and emission monitoring by tunable IR diode lasers“. In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1989. http://dx.doi.org/10.1364/oam.1989.thnn2.
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A number of gas analysis systems based on lead chalcogenide diode laser spectroscopy have been developed recently in our laboratory for both ¡mission and emission measurement on gas samples in nearly Doppler-limited conditions. Here we describe two instruments. One was conceived for atmospheric trace gas monitoring using derivative signal processing and the other one for car exhaust gas analysis with millisecond time resolution using a pulsed integrative signal processing scheme. Both systems rely on specific diode laser properties as tunability, narrow linewidth, diffraction-limited beam quality, and high modulation rate. In atmospheric trace gas monitoring with unattended operation over several days, detection limits between 50 ppt and 1 ppb were obtained for NO2, HNO3, NO, and SO2. In time-resolved analysis of NO and CO in car exhaust gas, a rise time below 10 ms was found. Such a value is sufficient to resolve the emission related to a single stroke of one cylinder of the engine and will allow for an efficient optimization of the dynamic engine parameters in view of low fuel consumption and pollution levels.
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Dawson, K. W., B. J. Smith, I. Stocker und P. Evans. „Assessing the Application of Drone TDLAS Methane Emissions Monitoring Technology in the Intertropical Convergence Zone Using Machine“. In APOGCE 2024. SPE, 2024. http://dx.doi.org/10.2118/221317-ms.
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Abstract Global energy stakeholders are increasingly becoming more committed to global methane reduction and emissions transparency. These organizations have global reach and production processes which can pose unique problems for consistent measurement and verification techniques. To help provide more consistent measurements across the globe, this study evaluates the efficacy of a drone-mounted TDLAS sensor for use in the Inter-tropical Convergence Zone (ITCZ), an area of the world plagued with dampened windspeeds often less than 2 m s-1. This environment makes accurate measurements of point source emission rates challenging for advanced emissions monitoring technologies which is a substantial roadblock in the implementation of OGMP 2.0 best practices for Level 5 emissions monitoring. We simulated errors in mass-balance derived methane emission rates by utilizing a Gaussian plume model and drone flight paths with a vertical raster pattern at a 10Hz sensor sampling frequency. The Gaussian plume model allows for simple theoretical equations as a function of plume rise, downwind distance from the source, plume dispersion, and altitude-dependent wind velocity to be explicitly accounted for to understand sensitivity from errors in each of these terms. We conducted a Monte Carlo simulation and explored uncertainty across all sources. Finally, we built a machine learning (ML) random forest (RF) classifier to predict survey success based on prevailing conditions and survey design parameters to offer a comprehensive approach to assessing and mitigating uncertainties in methane emission measurements. We find that survey settings need to be carefully considered along with plume effects to provide accurate measurements in the field. To illustrate, we show a case study with two flights, both surveying flares but with different flight settings, to achieve the desired error < 30%. Our case study showed that mid-range wind speeds can achieve high survey success with lower resolution surveys (i.e., faster flight velocity and larger vertical step) whereas low-range wind speeds require higher resolution for best results (i.e., lower flight velocity and lower vertical step).
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Chang, Z., A. Rundquist, H. Wang, H. C. Kapteyn, M. M. Murnane, X. Liu, B. Shan et al. „Demonstration of a 0.54 Picosecond X-Ray Streak Camera“. In Applications of High Field and Short Wavelength Sources. Washington, D.C.: Optica Publishing Group, 1997. http://dx.doi.org/10.1364/hfsw.1997.the4.
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X-ray streak camera detectors are important as diagnostics for monitoring fast x-ray processes such as the emission from laser-produced plasmas, and also for obtaining high time-resolution in x-ray studies done using quasi-CW x-ray sources such as synchrotrons. In work in 1990, an x-ray streak camera was demonstrated to have 2 ps time resolution;1 however, in subsequent years, progress in obtaining faster resolution has been slow. Progress has been limited by two factors: the intrinsic time response of the streak camera itself, and the time duration of the x-ray source itself (usually a laser-produced plasma with x-ray pulse duration of ~ 1-2 ps).
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Odunsi, Lola, Matt Mueller und Mamdouh El Oufy. „A Deep Dive on the Global Outlook from Methane Emissions Monitoring in the Oil and Gas Industry, Using Data Insights from Satellites and Aircrafts“. In ADIPEC. SPE, 2024. http://dx.doi.org/10.2118/222037-ms.
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Abstract This paper examines the impact of satellites in orbit, in relation to methane emissions and net-zero goals. Leveraging insights from global mappers and point source satellites, it elucidates the valuable information obtained and its significance in the O&G industry. Furthermore, this paper highlights the pioneering efforts of GHGSat in this field, its expansion into CO2 monitoring, along with advancements in quantification, detection threshold, spatial resolution, and the enhancements of its next generation aircraft sensor capabilities. This manuscript presents insights and data obtained from emissions monitoring satellites, with a focus on their role in mitigating emissions, understanding trends, and solving pertinent industry challenges. Utilizing a sophisticated data analytics Esri-based Arc-GIS platform, SPECTRA, GHGSat generates metrics that provide valuable insights into emissions monitoring. Key techniques employed include wide-area coverage, tip and cueing mechanisms, automation, and innovative processing capabilities to optimize observations and generated plumes. Additionally, statistical data and the distribution of global O&G emissions, with specific attention to case studies from the United Arab Emirates (UAE) and Gulf Cooperation Council (GCC) countries. This presentation will reveal the critical importance of frequency of observations in the efficacy of emissions monitoring efforts, emphasizing the need for consistent and timely data collection. For example, GHGSat monitored 300% more observations in 2023 and more than 183MTCO2e emissions, 2.3 times increase in Oil and Gas detections, in comparison to 2022. This is attributable to its growing constellation and high spatial resolution of 25m, and detection threshold of 100 kg/hr. The insights provided by emissions monitoring satellites are instrumental in informing mitigation strategies, understanding emissions trends, and addressing industry challenges. Moreover, the involvement of satellite companies and advancements in satellite technology have significantly enhanced GHGSat's ability to monitor and address emissions in the O&G industry. Regulatory compliance and International Frameworks for emission monitoring will also be discussed, and how source level measurements fit into the various scopes. GHGSat's top-down approach and its incorporation of its evergreening aircraft sensor solutions and developments for higher resolution (of less than 1m) and lower detection thresholds (down to 5 kg/hr) will be reviewed. This study underscores the invaluable contributions of emissions monitoring satellites in advancing sustainability efforts and shaping the future of the O&G industry towards a greener and more sustainable trajectory. GHGSat, a pioneering force in this space, has notably launched 12 satellites between 2016 and 2023, with a significant influx occurring in 2023, and plans to deploy five more satellites starting in 2025. By harnessing the capabilities of satellite and aircraft sensor technologies for onshore and offshore monitoring, the Oil and Gas industry stands poised to make informed decisions, drive sustainable practices, and contribute to global efforts towards emissions reduction and environmental stewardship.
Berichte der Organisationen zum Thema "High-Resolution emission monitoring"
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Aalto, Juha, und Ari Venäläinen, Hrsg. Climate change and forest management affect forest fire risk in Fennoscandia. Finnish Meteorological Institute, Juni 2021. http://dx.doi.org/10.35614/isbn.9789523361355.
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Forest and wildland fires are a natural part of ecosystems worldwide, but large fires in particular can cause societal, economic and ecological disruption. Fires are an important source of greenhouse gases and black carbon that can further amplify and accelerate climate change. In recent years, large forest fires in Sweden demonstrate that the issue should also be considered in other parts of Fennoscandia. This final report of the project “Forest fires in Fennoscandia under changing climate and forest cover (IBA ForestFires)” funded by the Ministry for Foreign Affairs of Finland, synthesises current knowledge of the occurrence, monitoring, modelling and suppression of forest fires in Fennoscandia. The report also focuses on elaborating the role of forest fires as a source of black carbon (BC) emissions over the Arctic and discussing the importance of international collaboration in tackling forest fires. The report explains the factors regulating fire ignition, spread and intensity in Fennoscandian conditions. It highlights that the climate in Fennoscandia is characterised by large inter-annual variability, which is reflected in forest fire risk. Here, the majority of forest fires are caused by human activities such as careless handling of fire and ignitions related to forest harvesting. In addition to weather and climate, fuel characteristics in forests influence fire ignition, intensity and spread. In the report, long-term fire statistics are presented for Finland, Sweden and the Republic of Karelia. The statistics indicate that the amount of annually burnt forest has decreased in Fennoscandia. However, with the exception of recent large fires in Sweden, during the past 25 years the annually burnt area and number of fires have been fairly stable, which is mainly due to effective fire mitigation. Land surface models were used to investigate how climate change and forest management can influence forest fires in the future. The simulations were conducted using different regional climate models and greenhouse gas emission scenarios. Simulations, extending to 2100, indicate that forest fire risk is likely to increase over the coming decades. The report also highlights that globally, forest fires are a significant source of BC in the Arctic, having adverse health effects and further amplifying climate warming. However, simulations made using an atmospheric dispersion model indicate that the impact of forest fires in Fennoscandia on the environment and air quality is relatively minor and highly seasonal. Efficient forest fire mitigation requires the development of forest fire detection tools including satellites and drones, high spatial resolution modelling of fire risk and fire spreading that account for detailed terrain and weather information. Moreover, increasing the general preparedness and operational efficiency of firefighting is highly important. Forest fires are a large challenge requiring multidisciplinary research and close cooperation between the various administrative operators, e.g. rescue services, weather services, forest organisations and forest owners is required at both the national and international level.
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Ddiba, Daniel, Mahboubeh Rahmati Abkenar und Carla Liera. Methods for Measuring Greenhouse Gas Emissions from Sanitation and Wastewater Management Systems: A Review of Method Features, Past Applications and Facilitating Factors for Researchers, Practitioners and Other Stakeholders. Stockholm Environment Institute, Juli 2024. http://dx.doi.org/10.51414/sei2024.030.
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This report presents an analysis of seven categories of enclosure-based and open methods described previously, and discusses their applicability across different sanitation and wastewater management technologies and geographical contexts. The report’s findings, based on a scoping literature review and interviews with a selection of experts, highlight key methodological gaps and opportunities for innovation. The findings reveal the predominant use of enclosure-based methods, such as static and flow-through flux chambers, which, despite their widespread adoption, are constrained by scale limitations and potential for measurement disturbances. In contrast, emerging methodologies like optical methods and remote sensing offer new avenues for broadscale, high-resolution emissions monitoring but are currently limited by their high cost and technical demands. With this report, the authors advocate for a holistic approach to greenhouse gas measurement in the sanitation and wastewater sector, emphasizing the need for adaptable methodologies that can be tailored to the varied conditions of sanitation systems worldwide. They call for enhanced collaboration among researchers, policymakers and practitioners to foster methodological advancements and standardization, thereby enabling more effective and widespread empirical data collection. Furthermore, the report underscores the critical importance of increased funding and capacity-building efforts to democratize access to advanced measurement techniques.