Articles | Volume 14, issue 2
https://doi.org/10.5194/essd-14-651-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-651-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
15 Feb 2022
Data description paper |
| 15 Feb 2022
| 15 Feb 2022
A global seamless 1 km resolution daily land surface temperature dataset (2003–2020)
Tao Zhang
Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA, 50011, USA
Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA, 50011, USA
Zhengyuan Zhu
Department of Statistics, Iowa State University, Ames, IA, 50011, USA
Xiaoma Li
College of Landscape Architecture and Art Design, Hunan Agricultural University, Changsha, Hunan, 410128, China
Ghassem R. Asrar
Universities Space Research Association, Columbia, MD, 21046, USA
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We generated a global 1 km daily maximum and minimum near-surface air temperature (Tmax and Tmin) dataset (2003–2020) using a novel statistical model. The average root mean square errors ranged from 1.20 to 2.44 °C for Tmax and 1.69 to 2.39 °C for Tmin. The gridded global air temperature dataset is of great use in a variety of studies such as the urban heat island phenomenon, hydrological modeling, and epidemic forecasting.
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Most existing global urban products with future projections were developed in urban and non-urban categories, which ignores the gradual change of urban development at the local scale. Using annual global urban extent data from 1985 to 2015, we forecasted global urban fractional changes under eight scenarios throughout 2100. The developed dataset can provide spatially explicit information on urban fractions at 1 km resolution, which helps support various urban studies (e.g., urban heat island).
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Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-15, https://doi.org/10.5194/gmd-2023-15, 2023
Revised manuscript not accepted
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Earth Syst. Sci. Data, 14, 5637–5649, https://doi.org/10.5194/essd-14-5637-2022, https://doi.org/10.5194/essd-14-5637-2022, 2022
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We generated a global 1 km daily maximum and minimum near-surface air temperature (Tmax and Tmin) dataset (2003–2020) using a novel statistical model. The average root mean square errors ranged from 1.20 to 2.44 °C for Tmax and 1.69 to 2.39 °C for Tmin. The gridded global air temperature dataset is of great use in a variety of studies such as the urban heat island phenomenon, hydrological modeling, and epidemic forecasting.
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The study presents long-term altitudinal changes and variability (spatial and temporal; during 2000–2017) in the coverage of snow and glaciers in one of the world’s largest mountainous regions, i.e., the Hindu Kush Himalayan (HKH) region. The western zone and high-altitude regions (above 6000 m) show no significant decline in snow cover, whereas the lower-altitude regions (< 6000 m) show a variable but statistically significant decline in snow cover in the central and eastern zones (5 %–15 %).
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Dalei Hao, Ghassem R. Asrar, Yelu Zeng, Qing Zhu, Jianguang Wen, Qing Xiao, and Min Chen
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We generated a long-term (1985–2015) and medium-resolution (30 m) product of phenology indicators in urban domains in the conterminous US using Landsat satellite observations. The derived phenology indicators agree well with in situ observations and provide more spatial details in complex urban areas compared to the existing coarse resolution phenology products (e.g., MODIS). The published data are of great use for urban phenology studies (e.g., pollen-induced respiratory allergies).
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In this study, we have developed a dense station-based, long-term dataset of daily surface solar radiation in China with high accuracy. The dataset consists of estimates of global, direct and diffuse radiation at 2473 meteorological stations from the 1950s to 2021. Validation indicates that our station-based radiation dataset clearly outperforms the satellite-based radiation products. Our dataset will contribute to climate change research and solar energy applications in the future.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Mark Omara, Ritesh Gautam, Madeleine A. O'Brien, Anthony Himmelberger, Alex Franco, Kelsey Meisenhelder, Grace Hauser, David R. Lyon, Apisada Chulakadabba, Christopher Chan Miller, Jonathan Franklin, Steven C. Wofsy, and Steven P. Hamburg
Earth Syst. Sci. Data, 15, 3761–3790, https://doi.org/10.5194/essd-15-3761-2023, https://doi.org/10.5194/essd-15-3761-2023, 2023
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We acquire, integrate, and analyze ~ 6 million geospatial oil and gas infrastructure data records based on information available in the public domain and develop an open-access global database including all the major oil and gas facility types that are important sources of methane emissions. This work helps fulfill a crucial geospatial data need, in support of the assessment, attribution, and mitigation of global oil and gas methane emissions at high resolution.
Saroj Kumar Sahu, Poonam Mangaraj, and Gufran Beig
Earth Syst. Sci. Data, 15, 3183–3202, https://doi.org/10.5194/essd-15-3183-2023, https://doi.org/10.5194/essd-15-3183-2023, 2023
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The developed emission inventory identifies all the potential anthropogenic sources active in the Delhi NCR. The decadal change (2010–2020) and the changing policies have also been illustrated to observe the modulation in the sectorial emission trend. Emission hotspots with possible source-specific mitigation strategies have also been highlighted to improve the air quality of the Delhi NCR. The provided dataset is a vital tool for air quality and chemical transport modeling studies.
Steffen Beirle, Christian Borger, Adrian Jost, and Thomas Wagner
Earth Syst. Sci. Data, 15, 3051–3073, https://doi.org/10.5194/essd-15-3051-2023, https://doi.org/10.5194/essd-15-3051-2023, 2023
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We present a catalog of nitrogen oxide emissions from point sources (like power plants or metal smelters) based on satellite observations of NO2 combined with meteorological wind fields.
Monica Crippa, Diego Guizzardi, Tim Butler, Terry Keating, Rosa Wu, Jacek Kaminski, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Harrison Suchyta, Marilena Muntean, Efisio Solazzo, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Fabio Monforti-Ferrario, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Tabish Ansari, and Kristen Foley
Earth Syst. Sci. Data, 15, 2667–2694, https://doi.org/10.5194/essd-15-2667-2023, https://doi.org/10.5194/essd-15-2667-2023, 2023
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This study responds to the global and regional atmospheric modelling community's need for a mosaic of air pollutant emissions with global coverage, long time series, spatially distributed data at a high time resolution, and a high sectoral resolution in order to enhance the understanding of transboundary air pollution. The mosaic approach to integrating official regional emission inventories with a global inventory based on a consistent methodology ensures policy-relevant results.
Piers M. Forster, Christopher J. Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Sonia I. Seneviratne, Blair Trewin, Xuebin Zhang, Myles Allen, Robbie Andrew, Arlene Birt, Alex Borger, Tim Boyer, Jiddu A. Broersma, Lijing Cheng, Frank Dentener, Pierre Friedlingstein, José M. Gutiérrez, Johannes Gütschow, Bradley Hall, Masayoshi Ishii, Stuart Jenkins, Xin Lan, June-Yi Lee, Colin Morice, Christopher Kadow, John Kennedy, Rachel Killick, Jan C. Minx, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sophie Szopa, Peter Thorne, Robert Rohde, Maisa Rojas Corradi, Dominik Schumacher, Russell Vose, Kirsten Zickfeld, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 15, 2295–2327, https://doi.org/10.5194/essd-15-2295-2023, https://doi.org/10.5194/essd-15-2295-2023, 2023
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This is a critical decade for climate action, but there is no annual tracking of the level of human-induced warming. We build on the Intergovernmental Panel on Climate Change assessment reports that are authoritative but published infrequently to create a set of key global climate indicators that can be tracked through time. Our hope is that this becomes an important annual publication that policymakers, media, scientists and the public can refer to.
Shengyue Li, Shuxiao Wang, Qingru Wu, Yanning Zhang, Daiwei Ouyang, Haotian Zheng, Licong Han, Xionghui Qiu, Yifan Wen, Min Liu, Yueqi Jiang, Dejia Yin, Kaiyun Liu, Bin Zhao, Shaojun Zhang, Ye Wu, and Jiming Hao
Earth Syst. Sci. Data, 15, 2279–2294, https://doi.org/10.5194/essd-15-2279-2023, https://doi.org/10.5194/essd-15-2279-2023, 2023
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This study compiled China's emission inventory of air pollutants and CO2 during 2005–2021 (ABaCAS-EI v2.0) based on unified emission-source framework. The emission trends and its drivers are analyzed. Key sectors and regions with higher synergistic reduction potential of air pollutants and CO2 are identified. Future control measures are suggested. The dataset and analyses provide insights into the synergistic reduction of air pollutants and CO2 emissions for China and other developing countries.
Alessandro Flammini, Hanif Adzmir, Kevin Karl, and Francesco Nicola Tubiello
Earth Syst. Sci. Data, 15, 2179–2187, https://doi.org/10.5194/essd-15-2179-2023, https://doi.org/10.5194/essd-15-2179-2023, 2023
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This paper estimates the share of greenhouse gas (GHG) emissions attributable to non-renewable wood fuel harvesting for use in residential food-related activities. It adds to a growing research base estimating GHG emissions from across the entire agri-food value chain and contributes to the development of the FAOSTAT climate change domain.
Wouter B. Mol, Wouter H. Knap, and Chiel C. van Heerwaarden
Earth Syst. Sci. Data, 15, 2139–2151, https://doi.org/10.5194/essd-15-2139-2023, https://doi.org/10.5194/essd-15-2139-2023, 2023
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We describe a dataset of detailed measurements of sunlight reaching the surface, recorded at a rate of one measurement per second for 10 years. The dataset includes detailed information on direct and scattered sunlight; classifications and statistics of variability; and observations of clouds, atmospheric composition, and wind. The dataset can be used to study how the atmosphere influences sunlight variability and to validate models that aim to predict this variability with greater accuracy.
Kanishka B. Narayan, Brian C. O'Neill, Stephanie Waldhoff, and Claudia Tebaldi
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-137, https://doi.org/10.5194/essd-2023-137, 2023
Preprint under review for ESSD
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Here, we present a consistent dataset of income distributions across 190 countries from 1958 to 2015 measured in terms of net income. We complement the observed values in this dataset with values imputed from a summary measure of the income distribution, specifically the GINI coefficient. We also present another version of this dataset aggregated from the country level to 32 geographical regions and the world as a whole.
Jie Chen, Qiancheng Lv, Shuang Wu, Yelu Zeng, Manchun Li, Ziyue Chen, Enze Zhou, Wei Zheng, Cheng Liu, Xiao Chen, Jing Yang, and Bingbo Gao
Earth Syst. Sci. Data, 15, 1911–1931, https://doi.org/10.5194/essd-15-1911-2023, https://doi.org/10.5194/essd-15-1911-2023, 2023
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The Himawari-8 fire product is the mainstream fire product with the highest temporal resolution, yet it presents large uncertainties and is not suitable for reliable real-time fire monitoring in China. To address this issue, we proposed an adaptive hourly NSMC (National Satellite Meteorological Center) Himawari-8 fire product for China; the overall accuracy increased from 54 % (original Himawari product) to 80 %. This product can largely enhance real-time fire monitoring and relevant research.
Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
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Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
Ruohan Li, Dongdong Wang, Weile Wang, and Ramakrishna Nemani
Earth Syst. Sci. Data, 15, 1419–1436, https://doi.org/10.5194/essd-15-1419-2023, https://doi.org/10.5194/essd-15-1419-2023, 2023
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There has been an increasing need for high-spatiotemporal-resolution surface downward shortwave radiation (DSR) and photosynthetically active radiation (PAR) data for ecological, hydrological, carbon, and solar photovoltaic research. This study produced a new 1 km hourly product of land surface DSR and PAR from the enhanced GeoNEX new-generation geostationary data. Our validation indicated that the GeoNEX DSR and PAR product has a higher accuracy than other existing products.
Nadine Borduas-Dedekind, Karen C. Short, and Samuel P. Carlson
Earth Syst. Sci. Data, 15, 1437–1440, https://doi.org/10.5194/essd-15-1437-2023, https://doi.org/10.5194/essd-15-1437-2023, 2023
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This article describes the use of the open-discussion manuscript review process as an educational exercise for early career scientists.
Can Cui, Shuping Li, Weichen Zhao, Binyuan Liu, Yuli Shan, and Dabo Guan
Earth Syst. Sci. Data, 15, 1317–1328, https://doi.org/10.5194/essd-15-1317-2023, https://doi.org/10.5194/essd-15-1317-2023, 2023
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Emerging economies face challenges regarding net-zero targets: inconsistencies in accounting calibers, missing raw data, non-transparent accounting methods, and a lack of detail about emissions. The authors established an accounting framework and compiled detailed inventories of energy-related CO2 emissions in 40 emerging economies, covering 47 sectors and eight energy types. The dataset will support emission reduction policymaking at global, national, and subnational levels.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
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This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Chuanlong Zhou, Biqing Zhu, Steven J. Davis, Zhu Liu, Antoine Halff, Simon Ben Arous, Hugo de Almeida Rodrigues, and Philippe Ciais
Earth Syst. Sci. Data, 15, 949–961, https://doi.org/10.5194/essd-15-949-2023, https://doi.org/10.5194/essd-15-949-2023, 2023
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Our work aims to analyze sectoral and country-based daily natural gas supply–storage–consumption based on ENTSOG, Eurostat, and multiple datasets in the EU27 and UK. We estimated the magnitude of the Russian gas gap if Russian gas imports were to stop as well as potential short-term solutions to fill this gap. Our datasets could be important in various fields, such as gas/energy consumption and market modeling, carbon emission and climate change research, and policy decision-making.
Akash Biswal, Vikas Singh, Leeza Malik, Geetam Tiwari, Khaiwal Ravindra, and Suman Mor
Earth Syst. Sci. Data, 15, 661–680, https://doi.org/10.5194/essd-15-661-2023, https://doi.org/10.5194/essd-15-661-2023, 2023
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This paper presents detailed emission estimates of on-road traffic exhaust emissions of nine major pollutants for Delhi. We use advanced traffic data and emission factors as a function of speed to estimate emissions for each hour and 100 m × 100 m spatial resolution. We examine the source contribution according to the vehicle, fuel, road and Euro types to identify the most polluting vehicles. These data are useful for high-resolution air quality modelling for developing suitable strategies.
Auke M. van der Woude, Remco de Kok, Naomi Smith, Ingrid T. Luijkx, Santiago Botía, Ute Karstens, Linda M. J. Kooijmans, Gerbrand Koren, Harro A. J. Meijer, Gert-Jan Steeneveld, Ida Storm, Ingrid Super, Hubertus A. Scheeren, Alex Vermeulen, and Wouter Peters
Earth Syst. Sci. Data, 15, 579–605, https://doi.org/10.5194/essd-15-579-2023, https://doi.org/10.5194/essd-15-579-2023, 2023
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To monitor the progress towards the CO2 emission goals set out in the Paris Agreement, the European Union requires an independent validation of emitted CO2. For this validation, atmospheric measurements of CO2 can be used, together with first-guess estimates of CO2 emissions and uptake. To quickly inform end users, it is imperative that this happens in near real-time. To aid these efforts, we create estimates of European CO2 exchange at high resolution in near real time.
David F. Pollard, Frank Hase, Mahesh Kumar Sha, Darko Dubravica, Carlos Alberti, and Dan Smale
Earth Syst. Sci. Data, 14, 5427–5437, https://doi.org/10.5194/essd-14-5427-2022, https://doi.org/10.5194/essd-14-5427-2022, 2022
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We describe measurements made in Antarctica using an EM27/SUN, a near-infrared, portable, low-resolution spectrometer from which we can retrieve the average atmospheric concentration of several greenhouse gases. We show that these measurements are reliable and comparable to other, similar ground-based measurements. Comparisons to the ESA's Sentinel-5 precursor (S5P) satellite demonstrate the usefulness of these data for satellite validation.
Giacomo Grassi, Giulia Conchedda, Sandro Federici, Raul Abad Viñas, Anu Korosuo, Joana Melo, Simone Rossi, Marieke Sandker, Zoltan Somogyi, Matteo Vizzarri, and Francesco N. Tubiello
Earth Syst. Sci. Data, 14, 4643–4666, https://doi.org/10.5194/essd-14-4643-2022, https://doi.org/10.5194/essd-14-4643-2022, 2022
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Despite increasing attention on the role of land use CO2 fluxes in climate change mitigation, there are large differences in available databases. Here we present the most updated and complete compilation of land use CO2 data based on country submissions to United Nations Framework Convention on Climate Change and explain differences with other datasets. Our dataset brings clarity of land use CO2 fluxes and helps track country progress under the Paris Agreement.
Thorsten Hoeser, Stefanie Feuerstein, and Claudia Kuenzer
Earth Syst. Sci. Data, 14, 4251–4270, https://doi.org/10.5194/essd-14-4251-2022, https://doi.org/10.5194/essd-14-4251-2022, 2022
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The DeepOWT (Deep-learning-derived Offshore Wind Turbines) data set provides offshore wind energy infrastructure locations and their temporal deployment dynamics from July 2016 until June 2021 on a global scale. It differentiates between offshore wind turbines, platforms under construction, and offshore wind farm substations. It is derived by applying deep-learning-based object detection to Sentinel-1 imagery.
Jing M. Chen, Rong Wang, Yihong Liu, Liming He, Holly Croft, Xiangzhong Luo, Han Wang, Nicholas G. Smith, Trevor F. Keenan, I. Colin Prentice, Yongguang Zhang, Weimin Ju, and Ning Dong
Earth Syst. Sci. Data, 14, 4077–4093, https://doi.org/10.5194/essd-14-4077-2022, https://doi.org/10.5194/essd-14-4077-2022, 2022
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Green leaves contain chlorophyll pigments that harvest light for photosynthesis and also emit chlorophyll fluorescence as a byproduct. Both chlorophyll pigments and fluorescence can be measured by Earth-orbiting satellite sensors. Here we demonstrate that leaf photosynthetic capacity can be reliably derived globally using these measurements. This new satellite-based information overcomes a bottleneck in global ecological research where such spatially explicit information is currently lacking.
Xunhe Zhang, Ming Xu, Shujian Wang, Yongkai Huang, and Zunyi Xie
Earth Syst. Sci. Data, 14, 3743–3755, https://doi.org/10.5194/essd-14-3743-2022, https://doi.org/10.5194/essd-14-3743-2022, 2022
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Photovoltaic (PV) power plants have been increasingly built across the world to mitigate climate change. A map of the PV power plants is important for policy management and environmental assessment. We established a map of PV power plants in China by 2020, covering a total area of 2917 km2. Based on the derived map, we found that most PV power plants were situated on cropland. In addition, the installation of PV power plants has generally decreased the vegetation cover.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Francesco N. Tubiello, Kevin Karl, Alessandro Flammini, Johannes Gütschow, Griffiths Obli-Laryea, Giulia Conchedda, Xueyao Pan, Sally Yue Qi, Hörn Halldórudóttir Heiðarsdóttir, Nathan Wanner, Roberta Quadrelli, Leonardo Rocha Souza, Philippe Benoit, Matthew Hayek, David Sandalow, Erik Mencos Contreras, Cynthia Rosenzweig, Jose Rosero Moncayo, Piero Conforti, and Maximo Torero
Earth Syst. Sci. Data, 14, 1795–1809, https://doi.org/10.5194/essd-14-1795-2022, https://doi.org/10.5194/essd-14-1795-2022, 2022
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The paper presents results from the new FAOSTAT database on food system emissions, covering all countries over the time series 1990–2019. Results indicate and further clarify – updated to 2019 – the relevance of emissions from crop and livestock production processes within the farm gate; from conversion of natural ecosystems to agriculture, such as deforestation and peat degradation; and from use of fossil fuels for energy and other industrial processes along food supply chains.
Mauricio Osses, Néstor Rojas, Cecilia Ibarra, Víctor Valdebenito, Ignacio Laengle, Nicolás Pantoja, Darío Osses, Kevin Basoa, Sebastián Tolvett, Nicolás Huneeus, Laura Gallardo, and Benjamín Gómez
Earth Syst. Sci. Data, 14, 1359–1376, https://doi.org/10.5194/essd-14-1359-2022, https://doi.org/10.5194/essd-14-1359-2022, 2022
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This paper presents a detailed estimate of on-road vehicle emissions for Chile, between 1990–2020, and an analysis of emission trends for greenhouse gases and local pollutants. Data are disaggregated by type of vehicle and region at 0.01° × 0.01°. While the vehicle fleet grew 5-fold, CO2 emissions increased at a lower rate and local pollutants decreased. These trends can be explained by changes in improved vehicle technologies, better fuel quality and enforcement of emission standards.
Daniel Moran, Peter-Paul Pichler, Heran Zheng, Helene Muri, Jan Klenner, Diogo Kramel, Johannes Többen, Helga Weisz, Thomas Wiedmann, Annemie Wyckmans, Anders Hammer Strømman, and Kevin R. Gurney
Earth Syst. Sci. Data, 14, 845–864, https://doi.org/10.5194/essd-14-845-2022, https://doi.org/10.5194/essd-14-845-2022, 2022
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This paper presents the modeling methods used for the website https://openghgmap.net, which provides estimates of CO2 emissions for 108 000 European cities.
Alessandro Flammini, Xueyao Pan, Francesco Nicola Tubiello, Sally Yue Qiu, Leonardo Rocha Souza, Roberta Quadrelli, Stefania Bracco, Philippe Benoit, and Ralph Sims
Earth Syst. Sci. Data, 14, 811–821, https://doi.org/10.5194/essd-14-811-2022, https://doi.org/10.5194/essd-14-811-2022, 2022
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Fossil-fuel-based energy used in agriculture, for crop and livestock production as well as in fisheries, generates significant amounts of greenhouse gases (GHG), which are typically not accounted for within the agriculture sector of national GHG inventories. Using activity data from UNSD and IEA, we construct a new database of energy use in agriculture and related emissions, covering the period 1970–2019 by country and by fossil fuel type, including emissions from electricity used on the farm.
Nicolás Álamos, Nicolás Huneeus, Mariel Opazo, Mauricio Osses, Sebastián Puja, Nicolás Pantoja, Hugo Denier van der Gon, Alejandra Schueftan, René Reyes, and Rubén Calvo
Earth Syst. Sci. Data, 14, 361–379, https://doi.org/10.5194/essd-14-361-2022, https://doi.org/10.5194/essd-14-361-2022, 2022
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This study presents the first high-resolution national inventory of anthropogenic emissions for Chile (Inventario Nacional de Emisiones Antropogénicas, INEMA). Emissions for vehicular, industrial, energy, mining and residential sectors are estimated for the period 2015–2017 and spatially distributed onto a high-resolution grid (1 × 1 km). This inventory will support policies seeking to mitigate climate change and improve air quality by providing qualified scientific spatial emission information.
Paula Castesana, Melisa Diaz Resquin, Nicolás Huneeus, Enrique Puliafito, Sabine Darras, Darío Gómez, Claire Granier, Mauricio Osses Alvarado, Néstor Rojas, and Laura Dawidowski
Earth Syst. Sci. Data, 14, 271–293, https://doi.org/10.5194/essd-14-271-2022, https://doi.org/10.5194/essd-14-271-2022, 2022
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This work presents the results of the first joint effort of South American and European researchers to generate regional maps of emissions. The PAPILA dataset is a collection of annual emission inventories of reactive gases (CO, NOx, NMVOCs, NH3, and SO2) from anthropogenic sources in the region for the period 2014–2016. This was developed on the basis of the CAMS-GLOB-ANT v4.1 dataset, enriching it with derived data from locally available emission inventories for Argentina, Chile, and Colombia.
Hou Jiang, Ling Yao, Ning Lu, Jun Qin, Tang Liu, Yujun Liu, and Chenghu Zhou
Earth Syst. Sci. Data, 13, 5389–5401, https://doi.org/10.5194/essd-13-5389-2021, https://doi.org/10.5194/essd-13-5389-2021, 2021
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A multi-resolution (0.8, 0.3, and 0.1 m) photovoltaic (PV) dataset is established using satellite and aerial images. The dataset contains 3716 samples of PVs installed on various land and rooftop types. The dataset can support multi-scale PV segmentation (e.g., concentrated PVs, distributed ground PVs, and fine-grained rooftop PVs) and cross applications between different resolutions (e.g., from satellite to aerial samples and vice versa), as well as other research related to PVs.
Margarita Choulga, Greet Janssens-Maenhout, Ingrid Super, Efisio Solazzo, Anna Agusti-Panareda, Gianpaolo Balsamo, Nicolas Bousserez, Monica Crippa, Hugo Denier van der Gon, Richard Engelen, Diego Guizzardi, Jeroen Kuenen, Joe McNorton, Gabriel Oreggioni, and Antoon Visschedijk
Earth Syst. Sci. Data, 13, 5311–5335, https://doi.org/10.5194/essd-13-5311-2021, https://doi.org/10.5194/essd-13-5311-2021, 2021
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People worry that growing man-made carbon dioxide (CO2) concentrations lead to climate change. Global models, use of observations, and datasets can help us better understand behaviour of CO2. Here a tool to compute uncertainty in man-made CO2 sources per country per year and month is presented. An example of all sources separated into seven groups (intensive and average energy, industry, humans, ground and air transport, others) is presented. Results will be used to predict CO2 concentrations.
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Short summary
We generated a global seamless 1 km daily (mid-daytime and mid-nighttime) land surface temperature (LST) dataset (2003–2020) using MODIS LST products by proposing a spatiotemporal gap-filling framework. The average root mean squared errors of the gap-filled LST are 1.88°C and 1.33°C, respectively, in mid-daytime and mid-nighttime. The global seamless LST dataset is unique and of great use in studies on urban systems, climate research and modeling, and terrestrial ecosystem studies.
We generated a global seamless 1 km daily (mid-daytime and mid-nighttime) land surface...
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