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The Data Distribution Centre (DDC) of the Intergovernmental Panel on Climate Change (IPCC) celebrates its 25th anniversary in 2022. The DKRZ (German Climate Computing Center; German: Deutsches Klimarechenzentrum) is the only remaining DDC Partner from the original group jointly managing the DDC. In spite of changes in prioritization, it has been supporting the IPCC Assessments and preserving the quality-assured, citable climate model data underpinning the Assessment Reports over these years over the long term. An active and engaged collaborative community achieved advances in data standardization, data management best practices, and infrastructure developments. These evolving standards are reflected in the activities of the DDC. The introduction of the IPCC FAIR Guidelines into the current Sixth IPCC Assessment Report (AR6) has significantly changed the role of the DDC Partner DKRZ from an independent partner for long-term data preservation into an active partner involved in the IPCC's Sixth Assessment cycle. As a result, the DDC has gained exposure and visibility, posing a challenge and an opportunity to operationalize the IPCC's FAIR Guidelines and long-term preservation approaches. While the value of DDC services has been recognized, DDC sustainability remains unresolved and is currently being discussed within the IPCC as part of a general AR6 review process to formulate recommendations for the AR7 data management.

Data citation has become a core service for data infrastructures and data repositories, integrated in author guidelines and project proposals. It provides an essential piece in Open Science supporting reuse and enabling credit by integration into the established scientific credit system of scientific references (Scholix) and the envisioned FAIR Digital Object framework. Humans and machines need to be supported for provision and access of the information.Modern data infrastructures are federated and without central funding, especially that of international collaborations. Providing and maintaining state-of-the-art data services does not fit within current funding structures, even though these infrastructures provide core services to a broad community, like the data infrastructure of the Coupled Model Intercomparison Project (CMIP). For the citation service of CMIP6, currently a single person effort, the newly established CMIP Task Team (TT) Data Citation is exploring a set of options for a sustainable data citation service for CMIP7 and further WCRP activities in a cost-benefit approach. Due to the different experiences of its members, the TT brings infrastructure aspects together with the needs of researchers. A governance structure for sustainability, standard agreements and the coordination of further developments will be framed. The background to the TT and first experiences are shared.

A new paradigm for Intergovernmental Panel on Climate Change (IPCC) Working Group I (WGI) data publication has been implemented. IPCC Data Distribution Centre (DDC) partners at the Centre for Environmental Data Analysis (CEDA), the German Climate Computing Centre (DKRZ) and the Spanish Research Council (CSIC) have worked with the IPCC Technical Support Unit (TSU) for WGI to publish figure data from the Sixth Assessment Report (AR6). The work was guided by the IPCC Task Group on Data Support for Climate Change Assessments (TG-Data) recommendations for Open Science and FAIR data (making data Findable, Accessible, Interoperable, and Reusable) with a general aim to enhance the transparency and accessibility of AR6 outcomes. We highlight the achievement of implementing FAIR for AR6 figure data and discuss the lessons learned on the road to FAIRness in the unique context of the IPCC.Findable - The CEDA catalogue record for each figure dataset enhances findability. Keywords can be easily searched. Records are organised into collections for each AR6 chapter. There is a two-way link between the catalogue record and the figure on the AR6 website. CEDA catalogue records are duplicated on the IPCC-DDC. Accessible - Scientific language is understandable, acronyms and specific terminology are fully explained. CEDA services provide tools to access and download the data. Interoperable - Where possible data variables follow standard file format conventions such as CF-netCDF and have standard names, where this is not feasible readme files describe the file structure and content. Reusable - The data can be reused, shared and adapted elsewhere, with credit, under a Creative Commons Attribution 4.0 licence (CC BY 4.0). Catalogue records link to relevant documentation such as the Digital Object Identifier (DOI) for the code and other supplementary information. The code used to create the figures allows users to reproduce the figures from the report independently. CEDA catalogue records provide a platform to acknowledge the specific work of IPCC authors and dataset creators whose work supports the scientific basis of AR6. Catalogue records for figure datasets were created at CEDA with data archived in the CEDA repository and the corresponding code stored on GitHub and referenced via Zenodo. For instances where the data and code were blended in a processing chain that could not be easily separated, we developed criteria to categorise the different blends of data and code and created a decision tree to decide how best to archive them. Key intermediate datasets were also archived at CEDA.Careful definition of metadata requirements at the beginning of the archival process is important for handling the diversity of IPCC figure data which includes data derived from climate model simulations, historical observations and other sources of climate information. The reality of the implementation meant that processes for gathering data and information from authors were specified later in the preparation of AR6. This presented challenges with data management workflows and the separation of figure datasets from the intermediate data and code that generated them. We present recommendations for AR7 and scaling up this work in a feasible way.

Summary: „The future is already here.It's just not evenly distributed yet” [W. Gibson] •FAIR scientific software citation is a reality in 2023 •FAIR scientific software citation is a service (-> needs service management) •Define and manage service quality –> Service level agreements ? •Customer relationship management ! (software project community feedback !) •Managage continual improvement (goal TRL 9: „Flight proven“ research infrastructures) •Needed: A cross-community vocabulary for the service („nice story bro, got DOI ?“)

Software and data citation are emerging best practices in scholarly communication. This article provides structured guidance to the academic publishing community on how to implement software and data citation in publishing workflows. These best practices support the verifiability and reproducibility of scientific results; sharing and reuse of valuable data and software tools, and attribution to the creators of the software and data. While data citation is increasingly well-established, software citation is rapidly maturing. With the current intensive use of software, including specialized tools and models for scientific research problems, the research community has begun to recognize that software, as a key research result and resource, requires the same level of transparency, accessibility, and disclosure as data. Software and data that support scientific results should be preserved and shared in scientific repositories for discovery, transparency, and use by other researchers. These goals can be supported by citing these products in the Reference Section of papers and effectively associating them to the software and data preserved in scientific repositories. Publishers need to mark up these references in a specific way to enable downstream processes, specifically those that enable automated attribution. Academic publishers wishing to stay current with best practices in the field are encouraged to follow the guidance provided here.

The IPCC Task Group on Data Support for Climate Change Assessments (TG-Data) recommends the implementation of FAIR (Findable, Accessible, Interoperable, Reusable) data principles and best practices for the documentation and curation of data that is assessed by the IPCC. The motivation to implement FAIR in the IPCC is to increase transparency and accessibility of the assessment, the implementation of the IPCC Error Protocol, and the long-term curation of the assessed digital information. This document introduces the implementation of FAIR data principles into the IPCC process and reflects the four elements of FAIR to find the data, produce and reproduce figures and, finally, to document the provenance for reusability. It presents standard (basic) measures that are recommended for all digital data that is assessed, intermediate measures that achieve reproducibility of assessed digital information, for example through the use of collaborative platforms for figure development, and also full (advanced) measures to achieve reusability of digital products with complete provenance documentation.

The Data Distribution Centre (DDC) of the Intergovernmental Panel on Climate Change (IPCC) celebrates its 25th anniversary in 2022. DKRZ is the last remaining founding member among the DDC Partners. The continuous developments in data standardization, data management best practices and infrastructure developments are reflected in the DDC’s operations. Examples for such milestones are the NetCDF/CF data standard, the DataCite data DOIs enabling data citation, the data preservation and stewardship standards of the World Data System (WDS), or the IPCC FAIR Guidelines for the current Sixth IPCC Assessment Report (AR6). The FAIR Guidelines significantly changed the role of the DDC Partner DKRZ from an independent partner for long-term data preservation into an active partner involved in IPCC’s Sixth Assessment cycle. As a result, the DDC has become more exposed and visible, posing a challenge and an opportunity to operationalize IPCC’s FAIR Guidelines and long-term preservation approaches. Combined with a long-term DDC strategy, the DDC can be positioned in the developing FAIR digital object research landscape as well as in the political and societal realm of climate change.

In Earth and Biological sciences, data are often preserved and publicly available in data repositories where the data are citable by DOIs and published under a Creative Commons CC-BY license. Researchers combine many datasets across disciplines, repositories, and regions to better understand processes, patterns, and drivers. Citing these many datasets is difficult as the large number does not fit into the references section of a paper but the licenses of the datasets require that credit is given to their creators. The Data Citation Community of Practice (CoP) was formed to target such challenges in data citation and other scholarly work that will support indexing and measuring the impact. The CoP identified a container as a solution for large numbers of data citations that holds the citations and its internal format, which is referred to as a 'reliquary'. The existing dataset collection methods have been gathered and evaluated using concrete citation use cases. Requirements for the reliquary content have been identified and applied to the use cases. In this presentation, we will report on the current progress on an approach to building a reliquary. Reliquaries are an important part of enabling cross-disciplinary analysis of large amounts of data stored in many repositories. The challenge with a reliquary will be to design a method that works across diverse repositories and domain citation practices and to enhance the indexing system to direct credit to the reliquary content and authors. The CoP is in the process of setting up a Research Data Alliance (RDA) Working Group on Complex Citations in the Earth, Space, and Environmental Sciences to broaden the discussion and to find further use cases for evaluation and interested early adopters.

The Data Distribution Centre (DDC) of the Intergovernmental Panel on Climate Change (IPCC) celebrates its 25th anniversary in 2022. DKRZ is the last remaining founding member among the DDC Partners. The contribution looks back on the past 25 years of the DDC at DKRZ from its establishment to the present. It shows which the milestones have been introduced in the areas of data management and data standardization, e.g. the NetCDF/CF data standard, the DataCite data DOI assignment enabling data citation, the data preservation and stewardship standards of the World Data System (WDS), the Earth System Grid Federation (ESGF) as data infrastructure standard, or the IPCC FAIR Guidelines for the current 6th Assessment Report (AR6). In addition to the continuous effort to adopt new standards and curate the data holdings, current challenges - technical and organizational - and possible future directions are discussed. The most difficult of the challenges remains the long-term strategy for sustainable DDC services as a part of an increasingly interoperable data service environment, which is technically described in the FAIR digital object framework and which is contentwise guided by the UN Sustainable Development Goal 13 on climate action. (http://ipcc-data.org; http://ipcc.wdc-climate.de)

Data publication with DOI assignment has become common practice. The Citation Service for Coupled Model Intercomparison Project Phase 6 (CMIP6) was requested by the scientific panel WGCM, which is ...

The the amount of work and resources invested by the modelling centers to provide CMIP6 (Coupled Model Intercomparison Project Phase 6) experiments and climate projection datasets is huge, and therefore it is extremely important that the teams receive proper credit for their work. The Citation Service makes CMIP6 data citable with DOI references for the evolving CMIP6 model data published in the Earth System Grid Federation (ESGF). The Citation Service as a new piece of the CMIP6 infrastructure was developed upon the request from the CMIP Panel.CMIP6 provides new global climate model data assessed in the IPCC's (Intergovernmental Panel on Climate Change) Sixth Assessment Report (AR6). Led by the Technical Support Unit of IPCC Working Group I (WGI TSU), the IPCC Task Group on Data Support for Climate Change Assessment (TG-Data) developed FAIR data guidelines, for implementation by the TSUs of the three IPCC WGs and the IPCC Data Distribution Centre (DDC) Partners. A central part of the FAIR data guidelines are the documentation and citation of data used in the report.The contribution will show how CMIP6 data usage is documented in IPCC WGI AR6 from three angles: technical implementation, collection of CMIP6 data usage information from the IPCC authors, and a report users’ perspective. Links:CMIP6 Citation Service: http://cmip6cite.wdc-climate.de CMIP6: https://pcmdi.llnl.gov/CMIP6/ IPCC AR6: https://www.ipcc.ch/assessment-report/ar6/ IPCC AR6 WGI report: https://www.ipcc.ch/report/sixth-assessment-report-working-group-i/ IPCC TG-Data: https://www.ipcc.ch/data/

The Data Distribution Centre (DDC) of the Intergovernmental Panel on Climate Change provides a range of services to support the IPCC Assessment Process. The role of the DDC has evolved considerably since it was established in 1997, responding to the expanding range and complexity of the data products involved in the IPCC assessment process. The role of the IPCC assessments has also evolved from considering whether anthropomorphic climate change might have unwelcome consequences and how those consequences would vary under different socio-economic scenarios to reporting on the likely outcome of different global policy options.The DDC works both with datasets which underpin the key conclusions from the assessment and, increasingly, with data products generated by the scientists engaged in the assessment.Applying FAIR data principles to data products being produced in the highly constrained context of the assessment process brings many challenges. Working with the Technical Support Units of the IPCC Working Groups and the IPCC Task Group, the IPCC DDC has helped to create a process that not only captures information needed to document data products but supports the consistent and clear description of figures and tables within the report.

Software is as integral as a research paper, monograph, or dataset in terms of facilitating the full understanding and dissemination of research. This article provides broadly applicable guidance on software citation for the communities and institutions publishing academic journals and conference proceedings. We expect those communities and institutions to produce versions of this document with software examples and citation styles that are appropriate for their intended audience. This article (and those community-specific versions) are aimed at authors citing software, including software developed by the authors or by others. We also include brief instructions on how software can be made citable, directing readers to more comprehensive guidance published elsewhere. The guidance presented in this article helps to support proper attribution and credit, reproducibility, collaboration and reuse, and encourages building on the work of others to further research.

The Intergovernmental Panel on Climate Change (IPCC) currently prepares its Sixth Assessment Report (AR6). Its authors assess peer-reviewed scientific literature and recent climate datasets to info...

As information and communication technology has become pervasive in our society, we are increasingly dependent on both digital data and repositories that provide access to and enable the use of such resources. Repositories must earn the trust of the communities they intend to serve and demonstrate that they are reliable and capable of appropriately managing the data they hold. Following a year-long public discussion and building on existing community consensus1, several stakeholders, representing various segments of the digital repository community, have collaboratively developed and endorsed a set of guiding principles to demonstrate digital repository trustworthiness. Transparency, Responsibility, User focus, Sustainability and Technology: the TRUST Principles provide a common framework to facilitate discussion and implementation of best practice in digital preservation by all stakeholders., Puede accederse a una versión en español de este artículo haciendo clic en "Documentos relacionados"., Servicio de Difusión de la Creación Intelectual

The Earth System Documentation (ES-DOC) project aims to nurture an ecosystem of tools & services in support of Earth System documentation creation, analysis and dissemination. Such an ecosystem enables the scientific community to better understand and utilise Earth system model data.The ES-DOC infrastructure for the Coupled Model Intercomparison Project Phase 6 (CMIP6) modelling groups to describe their climate models and make the documentation available on-line has been available for 18 months, and more recently the automatic generation of documentation of every published simulation has meant that every CMIP6 dataset within the Earth System Grid Federation (ESGF) is now immediately connected to the ES-DOC description of the entire workflow that created it, via a “further info URL”.The further info URL is a landing page from which all of the relevant CMIP6 documentation relevant to the data may be accessed, including experimental design, model formulation and ensemble description, as well as providing links to the data citation information.These DOI landing pages are part of the Citation Service, provided by DKRZ. Data citation information is also available independently through the ESGF Search portal or in the DataCite search or Google’s dataset search. It provides users of CMIP6 data with the formal citation that should accompany any use of the datasets that comprise their analysis.ES-DOC services and the Citation Service form a CMIP6 project collaboration, and depend upon structured documentation provided by the scientific community. Structured scientific metadata has an important role in science communication, however it’s creation and collation exacts a cost in time, energy and attention. We discuss progress towards a balance between the ease of information collection and the complexity of our information handling structures. CMIP6: https://pcmdi.llnl.gov/CMIP6/ES-DOC: https://es-doc.org/Further Info URL: https://es-doc.org/cmip6-ensembles-further-info-url Citation Service: http://cmip6cite.wdc-climate.de

The Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC) have provided the scientific basis underpinning far reaching policy decisions.The reports also have a huge influence on public debate about climate change. The IPCC is not responsible either for the evaluation of climate data and related emissions and socioeconomic data and scenarios or for the provision of advice on policy (reports must be “neutral, policy-relevant but not policy-prescriptive”). These omissions may appear unreasonable at first sight, but they are part of the well-tested structure which enables the creation of authoritative reports on the complex and sensitive subject of climate change. The responsibility for evaluation of climate data and related emissions and socioeconomic data and scenarios remains with the global scientific community. The IPCC has the task of undertaking an expert, objective assessment of the state of scientific knowledge as expressed in the scientific literature. The exclusion of responsibility for providing policy advice from the IPCC remit allows the IPCC to stay clear of discussions of political priorities. These distinctions and limitations influence the way in which the findable, accessible, interoperable, and reusable (FAIR) data principles are applied to the work of the IPCC Assessment. There are hundreds of figures in the IPCC Assessment Reports, showing line graphs, global or regional maps, and many other displays of data and information. These figures are put together by the authors using data resources which are described in the scientific literature that is being assessed. The figures are there to illustrate or clarify points raised in the text of the assessment. Increasingly, the figures also provide quantitative information which is of critical importance for many individuals and organisations which are seeking to exploit IPCC knowledge. This presentation will discuss the process of implementing the FAIR data principles within the IPCC assessment process. It will also review both the value of the FAIR principles to the IPCC authors and the IPCC process and the value of the FAIR data products that the process is expected to generate.

Climate change data and information is among those of the highest interest for cross-domain researchers, policy makers and the general public. Serving climate projection data to these diverse users requires detailed and accessible documentation.Thus, the CMIP6 (Coupled Model Intercomparison Project Phase 6) data infrastructure consists not only of the ESGF (Earth System Grid Federation) as the data dissemination component but additionally of ES-DOC (Earth System Documentation) and the Citation Service for describing the provenance of the data. These services provide further information on the data creation process (experiments, models, …) and data reuse (data references and licenses) and connect the data to other external resources like research papers.The contribution will present documentation of the climate change workflow around the furtherInfoURL page serving as an entry point. The challenges are to collect quality-controlled information from the international research community in different infrastructure components and to display them seamlessly alongside on the furtherInfoURL page. References / Links:CMIP6: https://pcmdi.llnl.gov/CMIP6/ ES-DOC: https://es-doc.org/ Citation Service: http://cmip6cite.wdc-climate.de

The information provided in the Intergovernmental Panel on Climate Change (IPCC; http://ipcc.ch ) Assessment Reports (ARs) inform climate change policy development. Within the IPCC the scientific coordination of the ARs is conducted by three Working Groups (WGs) comprising of the Bureaus supported by their Technical Support Units (TSUs). Data management support is provided by the IPCC Data Distribution Centre (DDC; http://ipcc-data.org ), which is overseen by the Task Group on Data Support for Climate Change Assessments (TG-Data; formerly TGICA). The DDC is a federated structure that is currently managed by the Centre for Environmental Data Analysis (CEDA; http://www.ceda.ac.uk/ ), United Kingdom; the World Data Center for Climate (WDCC; http://www.wdc-climate.de ), Germany; and the Center for International Earth Science Information Network (CIESIN; http://www.ciesin.columbia.edu/ ) at Columbia University, U.S. For the IPCC Sixth Assessment cycle (AR6), analyses of climate simulations and observations published in scientific literature will be assessed. The reports will include figures and tables prepared from the underlying digital information. The DDC plays an increasingly important role in facilitating the exchange of data, as well as curating the assessed datasets, scripts and provenance records to facilitate the assessment process and to support the traceability of AR6 results through long-term continuity of data management and curation. These issues, among others, are addressed by the DDC support group ( https://cedadev.github.io/ipcc_ddc ) currently consisting of members from the three TSUs and the three DDC managers.

Software is as integral as a research paper, monograph, or dataset in terms of facilitating the full understanding and dissemination of research. This article provides broadly applicable guidance on software citation for the communities and institutions publishing academic journals and conference proceedings. We expect those communities and institutions to produce versions of this document with software examples and citation styles that are appropriate for their intended audience. This article (and those community-specific versions) are aimed at authors citing software, including software developed by the authors or by others. We also include brief instructions on how software can be made citable, directing readers to more comprehensive guidance published elsewhere. The guidance presented in this article helps to support proper attribution and credit, reproducibility, collaboration and reuse, and encourages building on the work of others to further research.

A new initiative collects, archives, and documents climate forcing data sets to support coordinated modeling activities that study past, present, and future climates.

[1] The new Max-Planck-Institute Earth System Model (MPI-ESM) is used in the Coupled Model Intercomparison Project phase 5 (CMIP5) in a series of climate change experiments for either idealized CO2-only forcing or forcings based on observations and the Representative Concentration Pathway (RCP) scenarios. The paper gives an overview of the model configurations, experiments related forcings, and initialization procedures and presents results for the simulated changes in climate and carbon cycle. It is found that the climate feedback depends on the global warming and possibly the forcing history. The global warming from climatological 1850 conditions to 2080–2100 ranges from 1.5°C under the RCP2.6 scenario to 4.4°C under the RCP8.5 scenario. Over this range, the patterns of temperature and precipitation change are nearly independent of the global warming. The model shows a tendency to reduce the ocean heat uptake efficiency toward a warmer climate, and hence acceleration in warming in the later years. The precipitation sensitivity can be as high as 2.5% K−1 if the CO2 concentration is constant, or as small as 1.6% K−1, if the CO2 concentration is increasing. The oceanic uptake of anthropogenic carbon increases over time in all scenarios, being smallest in the experiment forced by RCP2.6 and largest in that for RCP8.5. The land also serves as a net carbon sink in all scenarios, predominantly in boreal regions. The strong tropical carbon sources found in the RCP2.6 and RCP8.5 experiments are almost absent in the RCP4.5 experiment, which can be explained by reforestation in the RCP4.5 scenario.

Most climate and climate impact studies include data analyses and therefore rely on scientific data. Generally, only a small part out of the whole available data of an experiment or model run is used. Hosting these data and making it easily accessible meets two challenges: First, the community of data users virtual organization (VO) grows and becomes more diverse, e.g. the Geographical Information System (GIS) users have started to use scientific climate data. The community investigates natural scientific as well as political, economical and social scientific questions (e.g. climate impact). And as heterogeneous as their questions are their data requirements. The second challenge lies in the continuous intensive growth of the amount of data, which is spread over different specialized data archives worldwide. Researchers create greater amounts of data in a shorter amount of time on the quickly evolving high-performance computing systems, whereas the storage amounts and network capacities develop less rapidly.

Measurements and model developments with the objective to improve the quality and resolution of estimations of anthropogenic emissions are described. Measurement results on a chassis dynamometer were used to determine VOC profiles for exhaust gas emissions of passenger cars for different vehicle and fuel types and different driving modes. Further measurements resulted in emission factors and VOC profiles for lignite burning in residential stoves. Using remote sensing techniques benzene emission factors of gas stations and the efficiency of gasoline vapour recovery systems were measured.

The emission rates of diffuse and heterogeneous distributed sources are difficult to determine because point measurements are not representative. Therefore a method was further developed to determine gaseous emission rates by measurements of path-integrated mixing ratios with open-path spectroscopic systems in the exhaust plume (VOC, NH3, CH4, N2O, CO, CO2) and of meteorological parameters. Inverse dispersion modeling is used to quantify the emission rates afterwards with these data. The measurements are performed by Fourier Transform Infrared (FTIR) spectroscopy and Differential Optical Absorption Spectroscopy (DOAS) at 50 to 500 m optical path lengths about 1 to 20 m above ground level. The measurement accuracy for greenhouse gases and ammonia is about plus or minus 10% and for BTX about plus or minus 30%. The whole method was validated at a livestock building with a single exhaust chimney. The Gaussian model PAL was applied for inverse modeling to investigate limited pieces of land and isolated facilities in flat terrain. Including the accuracy of the dispersion simulations the determined emission rates have an error margin of about plus or minus 30%. Results of measurement campaigns are discussed as emission rates of ammonia from slurry spreading as well as of benzene from gas stations and a tank farm.© (1999) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Up to now emission source strengths of diffuse and heterogenous emission of important VOCs are not well known especially from gas stations and gasoline tank farms. To estimate the total emission of these sources non-intrusive measurements were performed by a differential optical absorption spectroscopy (DOAS) system to determine the path- integrated concentrations of exhaust compounds downwind of the source through the whole exhaust plume. Simultaneously, the meteorological parameters were measured for modeling the dispersion of the plume inversely to obtain the emission source strengths of these compounds. The emissions by road traffic were determined by an additional open-path DOAS measurement. Measurement campaigns were performed during different wether conditions and at different sources which were characterized by well defined and easy air flow conditions. The emission source strengths were calculated with the Gaussian model PAL. The determined total emission of gas stations with gasoline vapor recovery system are about 20 mg benzene per kg refueled gasoline and the emission from refueling activities vary between 1 and 9 benzene per kg refueled gasoline depending on the technical behavior of the gasoline vapor recovery system. These values which were found from measurements during times with a and without refueling activities show a high amount of diffuse emissions. The emission rates from a gasoline taken farm were measured on an open path through the middle of that area and a maximum of 8 (mu) g/(m2s) was determined.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The dielectric absorption spectrum between some MHz and 36 GHz has been measured at 20 degrees C for S(-)-lactic acid methylester, succinic acid dimethylester, L(-)- malic acid dimethylester and L(+)-tartaric acid diethylester, over the whole concentration range of benzene solutions of these substances. The loss function can be described by up to four Debye type spectral components. The relaxation parameters are reported and discussed in particular with respect to association effects.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Inverse modelling with a Gaussian dispersion model is used to determine emission rates of diffuse sources. The path-integrated gaseous concentrations of an exhaust are measured downwind of the source by FTIR absorption spectroscopy. Results of emission investigations from slurry spreading and a livestock building are discussed.