KIT-Campus Alpin - Research

2023

Xia, L.; Chen, W.; Lu, B.; et al. (2023). Climate mitigation potential of sustainable biochar production in China. Renewable and Sustainable Energy Reviews, 175, Art.-Nr.: 113145. doi:10.1016/j.rser.2023.113145

Friedl, J.; Warner, D.; Wang, W.; et al. (2023). Strategies for mitigating N2O and N2 emissions from an intensive sugarcane cropping system. Nutrient Cycling in Agroecosystems, 125 (2), 295–308. doi:10.1007/s10705-023-10262-4

Lee, H.; Pugh, T. A. M.; Patacca, M.; et al. (2023). Three billion new trees in the EU’s biodiversity strategy: low ambition, but better environmental outcomes?. Environmental Research Letters, 18 (3), Art.-Nr.: 034020. doi:10.1088/1748-9326/acb95c

Zhang, W.; Jung, M.; Migliavacca, M.; et al. (2023). The effect of relative humidity on eddy covariance latent heat flux measurements and its implication for partitioning into transpiration and evaporation. Agricultural and Forest Meteorology, 330, Art.Nr. 109305. doi:10.1016/j.agrformet.2022.109305

Olschewski, P.; Laux, P.; Wei, J.; et al. (2023). An ensemble-based assessment of bias adjustment performance, changes in hydrometeorological predictors and compound extreme events in EAS-CORDEX. Weather and Climate Extremes, 39, Art.-Nr.: 100531. doi:10.1016/j.wace.2022.100531

Polz, J.; Graf, M.; Chwala, C. (2023). Missing Rainfall Extremes in Commercial Microwave Link Data Due To Complete Loss of Signal. Earth and Space Science, 10 (2). doi:10.1029/2022EA002456

Speidel, J.; Vogelmann, H. (2023). Correct(ed) Klett–Fernald algorithm for elastic aerosol backscatter retrievals: a sensitivity analysis. Applied Optics, 62 (4), 861–868. doi:10.1364/AO.465944

Feldmann, D.; Laux, P.; Heckl, A.; et al. (2023). Near surface roughness estimation: A parameterization derived from artificial rainfall experiments and two-dimensional hydrodynamic modelling for multiple vegetation coverages. Journal of Hydrology, 617 (Part A), Art.-Nr.: 128786. doi:10.1016/j.jhydrol.2022.128786

Lapola, D. M.; Pinho, P.; Barlow, J.; et al. (2023). The drivers and impacts of Amazon forest degradation. Science, 379 (6630), Art.-Nr.: eabp8622. doi:10.1126/science.abp8622

Djibo, M.; Ouedraogo, W. Y. S. B.; Doumounia, A.; et al. (2023). Towards Innovative Solutions for Monitoring Precipitation in Poorly Instrumented Regions: Real-Time System for Collecting Power Levels of Microwave Links of Mobile Phone Operators for Rainfall Quantification in Burkina Faso. Applied System Innovation, 6 (1), 4. doi:10.3390/asi6010004

Okello, J.; Bauters, M.; Verbeeck, H.; et al. (2023). Temperature sensitivity of soil organic carbon respiration along a forested elevation gradient in the Rwenzori Mountains, Uganda. Biogeosciences, 20 (3), 719–735. doi:10.5194/bg-20-719-2023

Mortey, E. M.; Annor, T.; Arnault, J.; et al. (2023). Interactions between Climate and Land Cover Change over West Africa. Land, 12 (2), Art.-Nr.: 355. doi:10.3390/land12020355

Zavadilová, I.; Szatniewska, J.; Petrík, P.; et al. (2023). Sap flow and growth response of Norway spruce under long-term partial rainfall exclusion at low altitude. Frontiers in Plant Science, 14, Art.-Nr.: 1089706. doi:10.3389/fpls.2023.1089706

Cañadillas, B.; Wang, S.; Ahlert, Y.; et al. (2023). Coastal horizontal wind speed gradients in the North Sea based on observations and ERA5 reanalysis data. Meteorologische Zeitschrift. doi:10.1127/metz/2022/1166

Xia, L.; Cao, L.; Yang, Y.; et al. (2023). Integrated biochar solutions can achieve carbon-neutral staple crop production. Nature Food. doi:10.1038/s43016-023-00694-0

Srivastava, A. K.; Ewert, F.; Akinwumiju, A. S.; et al. (2023). Cassava yield gap—A model-based assessment in Nigeria. Frontiers in Sustainable Food Systems, 6, Art.-Nr.: 1058775. doi:10.3389/fsufs.2022.1058775

Arab, L.; Hoshika, Y.; Paoletti, E.; et al. (2023). Chronic ozone exposure impairs the mineral nutrition of date palm (Phoenix dactylifera) seedlings. Science of The Total Environment, 862, Art.-Nr.: 160675. doi:10.1016/j.scitotenv.2022.160675

2022

Wiens, M.; Klein, M.; Schultmann, F. (2022). Border Region Attachment: An Empirical Study on Regional Social Capital in the French–German Border Area. CESifo Economic Studies, 68 (4), 362–390. doi:10.1093/cesifo/ifac010

Paleri, S.; Desai, A. R.; Metzger, S.; et al. (2022). Space‐Scale Resolved Surface Fluxes Across a Heterogeneous, Mid‐Latitude Forested Landscape. Journal of Geophysical Research: Atmospheres, 127 (23), Art.Nr:e2022JD037138. doi:10.1029/2022JD037138

Petrovic, D.; Fersch, B.; Kunstmann, H. (2022). Droughts in Germany: performance of regional climate models in reproducing observed characteristics. Natural Hazards and Earth System Sciences, 22 (12), 3875–3895. doi:10.5194/nhess-22-3875-2022

Senatore, A.; Gochis, D. J. J.; Kunstmann, H.; et al. (2022). Preface – special issue on “coupled atmosphere‐hydrological processes: Novel system developments and cross‐compartment evaluations”. Hydrological Processes, 36 (12), Art.Nr. e14780. doi:10.1002/hyp.14780

Yao, Z.; Yan, G.; Ma, L.; et al. (2022). Soil C/N ratio is the dominant control of annual N

_{2}

O fluxes from organic soils of natural and semi-natural ecosystems. Agricultural and Forest Meteorology, 327, Art.Nr. 109198. doi:10.1016/j.agrformet.2022.109198

Piatka, D. R.; Venkiteswaran, J. J.; Uniyal, B.; et al. (2022). Dissolved oxygen isotope modelling refines metabolic state estimates of stream ecosystems with different land use background. Scientific Reports, 12, Art.-Nr.: 10204. doi:10.1038/s41598-022-13219-9

Lesiv, M.; Schepaschenko, D.; Buchhorn, M.; et al. (2022). Global forest management data for 2015 at a 100 m resolution. Scientific Data, 9 (1), 199. doi:10.1038/s41597-022-01332-3

Junkermann, W.; Hacker, J. (2022). Unprecedented levels of ultrafine particles, major sources, and the hydrological cycle. Scientific Reports, 12, Art.-Nr.: 7410. doi:10.1038/s41598-022-11500-5

Laso Bayas, J. C.; See, L.; Georgieva, I.; et al. (2022). Drivers of tropical forest loss between 2008 and 2019. Scientific Data, 9 (1), Artkl.Nr.:146. doi:10.1038/s41597-022-01227-3

Liao, C.; Chen, Y.; Wang, J.; et al. (2022). Disentangling land model uncertainty via Matrix-based Ensemble Model Inter-comparison Platform (MEMIP). Ecological Processes, 11 (1), Art.-Nr.: 14. doi:10.1186/s13717-021-00356-8

See, L.; Georgieva, I.; Duerauer, M.; et al. (2022). A crowdsourced global data set for validating built-up surface layers. Scientific data, 9 (1), 13. doi:10.1038/s41597-021-01105-4

Arnault, J.; Niezgoda, K.; Jung, G.; et al. (2022). Disentangling the Contribution of Moisture Source Change to Isotopic Proxy Signatures: Deuterium Tracing with WRF-Hydro-Iso-Tag and Application to Southern African Holocene Sediment Archives. Journal of Climate, 35 (22), 3855–3879. doi:10.1175/JCLI-D-22-0041.1

Shang, S.; Arnault, J.; Zhu, G.; et al. (2022). Recent Increase of Spring Precipitation over the Three-River Headwaters Region—Water Budget Analysis Based on Global Reanalysis (ERA5) and ET-Tagging Extended Regional Climate Modeling. Journal of Climate, 35 (22), 3599–3617. doi:10.1175/JCLI-D-21-0829.1

Friedlingstein, P.; O’Sullivan, M.; Jones, M. W.; et al. (2022). Global Carbon Budget 2022. Earth System Science Data, 14 (11), 4811–4900. doi:10.5194/essd-14-4811-2022

Grados, D.; Butterbach-Bahl, K.; Chen, J.; et al. (2022). Synthesizing the evidence of nitrous oxide mitigation practices in agroecosystems. Environmental Research Letters, 17 (11), Art.-Nr.: 114024. doi:10.1088/1748-9326/ac9b50

Brown, C.; Seo, B.; Alexander, P.; et al. (2022). Agent‐Based Modeling of Alternative Futures in the British Land Use System. Earth’s Future, 10 (11), Art.: e2022EF002905. doi:10.1029/2022EF002905

Lan, C.; Liu, H.; Katul, G. G.; et al. (2022). Turbulence Structures in the Very Stable Boundary Layer Under the Influence of Wind Profile Distortion. Journal of Geophysical Research: Atmospheres, 127 (20), Art.: e2022JD036565. doi:10.1029/2022JD036565

Blettner, N.; Chwala, C.; Haese, B.; et al. (2022). Combining Commercial Microwave Link and Rain Gauge Observations to Estimate Countrywide Precipitation: A Stochastic Reconstruction and Pattern Analysis Approach. Water Resources Research, 58 (10), Art.: e2022WR032563. doi:10.1029/2022WR032563

Schulz-Stellenfleth, J.; Emeis, S.; Dörenkämper, M.; et al. (2022). Coastal impacts on offshore wind farms – a review focussing on the German Bight area. Meteorologische Zeitschrift, 31 (4), 289–315. doi:10.1127/metz/2022/1109

Vogelmann, H.; Speidel, J.; Perfahl, M.; et al. (2022). Transverse-pumping approach for a powerful single-mode Ti:sapphire laser for near infrared lidar applications. Applied Optics, 61 (29), 8553–8562. doi:10.1364/AO.463257

Desai, A. R.; Paleri, S.; Mineau, J.; et al. (2022). Scaling Land‐Atmosphere Interactions: Special or Fundamental?. Journal of Geophysical Research: Biogeosciences, 127 (10), e2022JG007097. doi:10.1029/2022JG007097

Mousavian, R.; Mashhadi Hossainali, M.; Mashhadi Hossainali, M.; et al. (2022). Copula, a new approach for optimum design of Voxel-based GNSS tropospheric tomography based on the atmospheric dynamics. GPS Solutions, 26 (4), Art.Nr. 149. doi:10.1007/s10291-022-01340-1

Winder, S. G.; Lee, H.; Seo, B.; et al. (2022). An open‐source image classifier for characterizing recreational activities across landscapes. People and Nature, 4 (5), 1249–1262. doi:10.1002/pan3.10382

Gaglio, M.; Pace, R.; Muresan, A. N.; et al. (2022). Species-specific efficiency in PM2.5 removal by urban trees: From leaf measurements to improved modeling estimates. Science of The Total Environment, 844, Artkl.Nr.: 157131. doi:10.1016/j.scitotenv.2022.157131

Bhagat, S. K.; Tiyasha, T.; Al-khafaji, Z.; et al. (2022). Establishment of Dynamic Evolving Neural-Fuzzy Inference System Model for Natural Air Temperature Prediction. Complexity, 2022, Art.Nr. 1047309. doi:10.1155/2022/1047309

Lorenz, M.; Kilchert, F.; Nürnberg, P.; et al. (2022). Local Volume Conservation in Concentrated Electrolytes Is Governing Charge Transport in Electric Fields. The Journal of Physical Chemistry Letters, 13 (37), 8761–8767. doi:10.1021/acs.jpclett.2c02398

Ti, C.; Yan, X.; Xia, L.; et al. (2022). Improving nitrogen safety in China: Nitrogen flows, pollution and control. Frontiers of Agricultural Science and Engineering, 9 (3), 465–474. doi:10.15302/J-FASE-2022454

Ferretto, A.; Matthews, R.; Brooker, R.; et al. (2022). Planetary Boundaries and the Doughnut frameworks: A review of their local operability. Anthropocene, 39, Art.-Nr.: 100347. doi:10.1016/j.ancene.2022.100347

Wangari, E. G.; Mwanake, R. M.; Kraus, D.; et al. (2022). Number of Chamber Measurement Locations for Accurate Quantification of Landscape‐Scale Greenhouse Gas Fluxes: Importance of Land Use, Seasonality, and Greenhouse Gas Type. Journal of Geophysical Research: Biogeosciences, 127 (9), Nr. e2022JG006901. doi:10.1029/2022JG006901

Murray-Tortarolo, G.; Poulter, B.; Vargas, R.; et al. (2022). A Process‐Model Perspective on Recent Changes in the Carbon Cycle of North America. Journal of Geophysical Research: Biogeosciences, 127 (9), e2022JG006904. doi:10.1029/2022JG006904

Vrieling, A.; Fava, F.; Leitner, S.; et al. (2022). Identification of temporary livestock enclosures in Kenya from multi-temporal PlanetScope imagery. Remote Sensing of Environment, 279, Art.-Nr.: 113110. doi:10.1016/j.rse.2022.113110

Yuan, K.; Zhu, Q.; Li, F.; et al. (2022). Causality guided machine learning model on wetland CH

_{4}

emissions across global wetlands. Agricultural and Forest Meteorology, 324, Art.-Nr.: 109115. doi:10.1016/j.agrformet.2022.109115

Merkle, M.; Alexander, P.; Brown, C.; et al. (2022). Downscaling population and urban land use for socio-economic scenarios in the UK. Regional Environmental Change, 22 (3), 106. doi:10.1007/s10113-022-01963-7

Ramm, E.; Liu, C.; Mueller, C. W.; et al. (2022). Alder-induced stimulation of soil gross nitrogen turnover in a permafrost-affected peatland of Northeast China. Soil Biology and Biochemistry, 172, Art.-Nr.: 108757. doi:10.1016/j.soilbio.2022.108757

Krause, J.; Harfoot, M.; Hoeks, S.; et al. (2022). How more sophisticated leaf biomass simulations can increase the realism of modelled animal populations. Ecological Modelling, 471, Artkl.Nr.:110061. doi:10.1016/j.ecolmodel.2022.110061

Wang, R.; Pan, Z.; Liu, Y.; et al. (2022). Full straw incorporation into a calcareous soil increased N

_{2}

O emission despite more N

_{2}

O being reduced to N

_{2}

in the winter crop season. Agriculture, Ecosystems and Environment, 335, Art.Nr. 108007. doi:10.1016/j.agee.2022.108007

Oberpriller, J.; Herschlein, C.; Anthoni, P.; et al. (2022). Climate and parameter sensitivity and induced uncertainties in carbon stock projections for European forests (using LPJ-GUESS 4.0). Geoscientific Model Development, 15 (16), 6495–6519. doi:10.5194/gmd-15-6495-2022

Borne, M.; Lorenz, C.; Portele, T. C.; et al. (2022). Seasonal sub-basin-scale runoff predictions: A regional hydrometeorological Ensemble Kalman Filter framework using global datasets. Journal of Hydrology: Regional Studies, 42, Art.-Nr.: 101146. doi:10.1016/j.ejrh.2022.101146

Estoque, R. C.; Dasgupta, R.; Winkler, K.; et al. (2022). Spatiotemporal pattern of global forest change over the past 60 years and the forest transition theory. Environmental Research Letters, 17 (8), Art.-Nr.: 084022. doi:10.1088/1748-9326/ac7df5

Wan, L.; Lv, H.; Qasim, W.; et al. (2022). Heavy metal and nutrient concentrations in top- and sub-soils of greenhouses and arable fields in East China – Effects of cultivation years, management, and shelter. Environmental Pollution, 307, Art.Nr. 119494. doi:10.1016/j.envpol.2022.119494

Haas, E.; Carozzi, M.; Massad, R. S.; et al. (2022). Long term impact of residue management on soil organic carbon stocks and nitrous oxide emissions from European croplands. Science of The Total Environment, 836, Art.Nr. 154932. doi:10.1016/j.scitotenv.2022.154932

Mwanake, R. M.; Gettel, G. M.; Ishimwe, C.; et al. (2022). Basin‐scale estimates of greenhouse gas emissions from the Mara River, Kenya: Importance of discharge, stream size, and land use/land cover. Limnology and Oceanography, 67 (8), 1776–1793. doi:10.1002/lno.12166

Zheng, Y.; Wu, S.; Xiao, S.; et al. (2022). Global methane and nitrous oxide emissions from inland waters and estuaries. Global Change Biology, 28 (15), 4713–4725. doi:10.1111/gcb.16233

Li, Y.; Feng, H.; Dong, Q.; et al. (2022). Ammoniated straw incorporation increases wheat yield, yield stability, soil organic carbon and soil total nitrogen content. Field Crops Research, 284, Art.-Nr.: 108558. doi:10.1016/j.fcr.2022.108558

Brunn, M.; Hafner, B. D.; Zwetsloot, M. J.; et al. (2022). Carbon allocation to root exudates is maintained in mature temperate tree species under drought. New Phytologist, 235 (3), 965–977. doi:10.1111/nph.18157

Pan, B.; Zhang, Y.; Xia, L.; et al. (2022). Nitrous oxide production pathways in Australian forest soils. Geoderma, 420, Art.-Nr.: 115871. doi:10.1016/j.geoderma.2022.115871

Rehschuh, R.; Ruehr, N. K. (2022). Diverging responses of water and carbon relations during and after heat and hot drought stress in Pinus sylvestris. (D. Tissue, Ed.) Tree Physiology, 42 (8), 1532–1548. doi:10.1093/treephys/tpab141

Maire, J.; Sattar, A.; Henry, R.; et al. (2022). How different COVID-19 recovery paths affect human health, environmental sustainability, and food affordability: a modelling study. The Lancet Planetary Health, 6 (7), e565–e576. doi:10.1016/S2542-5196(22)00144-9

Friedl, J.; Deltedesco, E.; Keiblinger, K. M.; et al. (2022). Amplitude and frequency of wetting and drying cycles drive N

_{2}

and N

_{2}

O emissions from a subtropical pasture. Biology and Fertility of Soils, 58 (5), 593–605. doi:10.1007/s00374-022-01646-9

Rahimi, J.; Fillol, E.; Mutua, J. Y.; et al. (2022). A shift from cattle to camel and goat farming can sustain milk production with lower inputs and emissions in north sub-Saharan Africa’s drylands. Nature Food, 3 (7), 523–531. doi:10.1038/s43016-022-00543-6

Wang, Y.; Yao, Z.; Zheng, X.; et al. (2022). A synthesis of nitric oxide emissions across global fertilized croplands from crop‐specific emission factors. Global Change Biology, 28 (14), 4395–4408. doi:10.1111/gcb.16193

Qasim, W.; Wan, L.; Lv, H.; et al. (2022). Impact of anaerobic soil disinfestation on seasonal N

_{2}

O emissions and N leaching in greenhouse vegetable production system depends on amount and quality of organic matter additions. Science of The Total Environment, 830, Art.-Nr.: 154673. doi:10.1016/j.scitotenv.2022.154673

Shu, X.; He, J.; Zhou, Z.; et al. (2022). Organic amendments enhance soil microbial diversity, microbial functionality and crop yields: A meta-analysis. Science of The Total Environment, 829, Artk.Nr.: 154627. doi:10.1016/j.scitotenv.2022.154627

De Rosa, D.; Biala, J.; Nguyen, T. H.; et al. (2022). Environmental and economic trade‐offs of using composted or stockpiled manure as partial substitute for synthetic fertilizer. Journal of environmental quality, 51 (4), 589–601. doi:10.1002/jeq2.20255

Bliefernicht, J.; Salack, S.; Waongo, M.; et al. (2022). Towards a historical precipitation database for West Africa: Overview, quality control and harmonization. International Journal of Climatology, 42 (7), 4001–4023. doi:10.1002/joc.7467

Dong, N.; Wei, J.; Yang, M.; et al. (2022). Model Estimates of China’s Terrestrial Water Storage Variation Due To Reservoir Operation. Water Resources Research, 58 (6), e2021WR031787. doi:10.1029/2021WR031787

Rousset, C.; Clough, T. J.; Grace, P. R.; et al. (2022). Wetting and drainage cycles in two New Zealand soil types: Effects on relative gas diffusivity and N

_{2}

O emissions. Geoderma Regional, 29, e00504. doi:10.1016/j.geodrs.2022.e00504

Ganzenmüller, R.; Bultan, S.; Winkler, K.; et al. (2022). Land-use change emissions based on high-resolution activity data substantially lower than previously estimated. Environmental Research Letters, 17 (6), 064050. doi:10.1088/1748-9326/ac70d8

Schucknecht, A.; Seo, B.; Krämer, A.; et al. (2022). Estimating dry biomass and plant nitrogen concentration in pre-Alpine grasslands with low-cost UAS-borne multispectral data – a comparison of sensors, algorithms, and predictor sets. Biogeosciences, 19 (10), 2699–2727. doi:10.5194/bg-19-2699-2022

Li, X.; Fang, G.; Wen, X.; et al. (2022). Characteristics analysis of drought at multiple spatiotemporal scale and assessment of CMIP6 performance over the Huaihe River Basin. Journal of Hydrology: Regional Studies, 41, Art.Nr. 101103. doi:10.1016/j.ejrh.2022.101103

Wallace, A. J.; Armstrong, R. D.; Grace, P. R.; et al. (2022). Nitrogen use efficiency and N

_{2}

O emissions vary according to seasonal water supply across different cereal production systems of south eastern Australia. Geoderma Regional, 29, Art.-Nr.: e00498. doi:10.1016/j.geodrs.2022.e00498

Suman, M.; Maity, R.; Kunstmann, H. (2022). Precipitation of Mainland India: Copula‐based bias‐corrected daily CORDEX climate data for both mean and extreme values. Geoscience Data Journal, 9 (1), 58–73. doi:10.1002/gdj3.118

Kraus, D.; Werner, C.; Janz, B.; et al. (2022). Greenhouse Gas Mitigation Potential of Alternate Wetting and Drying for Rice Production at National Scale—A Modeling Case Study for the Philippines. Journal of Geophysical Research: Biogeosciences, 127 (5), e2022JG006848. doi:10.1029/2022JG006848

Seiler, C.; Melton, J. R.; Arora, V. K.; et al. (2022). Are Terrestrial Biosphere Models Fit for Simulating the Global Land Carbon Sink?. Journal of Advances in Modeling Earth Systems, 14 (5), e2021MS002946. doi:10.1029/2021MS002946

Rabin, S. S.; Gérard, F. N.; Arneth, A. (2022). The influence of thinning and prescribed burning on future forest fires in fire-prone regions of Europe. Environmental Research Letters, 17 (5), Artkl.Nr.: 055010. doi:10.1088/1748-9326/ac6312

Ti, C.; Han, X.; Chang, S. X.; et al. (2022). Mitigation of agricultural NH

_{3}

emissions reduces PM

_{2.5}

pollution in China: A finer scale analysis. Journal of Cleaner Production, 350, Art.-Nr.: 131507. doi:10.1016/j.jclepro.2022.131507

Klaas-Witt, T.; Emeis, S. (2022). The five main influencing factors for lidar errors in complex terrain. Wind Energy Science, 7 (1), 413–431. doi:10.5194/wes-7-413-2022

Preisler, Y.; Hölttä, T.; Grünzweig, J. M.; et al. (2022). The importance of tree internal water storage under drought conditions. (R. Oren, Ed.) Tree Physiology, 42 (4), 771–783. doi:10.1093/treephys/tpab144

Mozaffari, A.; Langguth, M.; Gong, B.; et al. (2022). HPC-oriented Canonical Workflows for Machine Learning Applications in Climate and Weather Prediction. Data Intelligence, 4 (2), 271–285. doi:10.1162/dint_a_00131

Lee, H.; Seo, B.; Cord, A. F.; et al. (2022). Using crowdsourced images to study selected cultural ecosystem services and their relationships with species richness and carbon sequestration. Ecosystem Services, 54, 101411. doi:10.1016/j.ecoser.2022.101411

Smith, P.; Arneth, A.; Barnes, D. K. A.; et al. (2022). How do we best synergize climate mitigation actions to co-benefit biodiversity?. Global Change Biology, 28 (8), 2555–2577. doi:10.1111/gcb.16056

Drugă, B.; Ramm, E.; Szekeres, E.; et al. (2022). Long-term acclimation might enhance the growth and competitive ability of Microcystis aeruginosa in warm environments. Freshwater Biology, 67 (4), 589–602. doi:10.1111/fwb.13865

Li, C.; Budde, M.; Tremper, P.; et al. (2022). SmartAQnet 2020: A New Open Urban Air Quality Dataset from Heterogeneous PM Sensors. ProScience, 8. doi:10.14644/dust2021.001

Amartuvshin, N.; Kim, J.; Cho, N.; et al. (2022). Local and regional steppe vegetation palatability at grazing hotspot areas in Mongolia. Journal of Ecology and Environment, 46, Art.Nr. 08. doi:10.5141/jee.22.009

Dieng, D.; Cannon, A. J.; Laux, P.; et al. (2022). Multivariate Bias‐Correction of High‐Resolution Regional Climate Change Simulations for West Africa: Performance and Climate Change Implications. Journal of Geophysical Research: Atmospheres, 127 (5), e2021JD034836. doi:10.1029/2021JD034836

Kim, D.-G.; Bond-Lamberty, B.; Ryu, Y.; et al. (2022). Ideas and perspectives: Enhancing research and monitoring of carbon pools and land-to-atmosphere greenhouse gases exchange in developing countries. Biogeosciences, 19 (5), 1435–1450. doi:10.5194/bg-19-1435-2022

Zeeman, M.; Holst, C. C.; Kossmann, M.; et al. (2022). Urban Atmospheric Boundary-Layer Structure in Complex Topography: An Empirical 3D Case Study for Stuttgart, Germany. Frontiers in Earth Science, 10, Art.-Nr.: 840112. doi:10.3389/feart.2022.840112

Rummler, T.; Wagner, A.; Arnault, J.; et al. (2022). Lateral terrestrial water fluxes in the LSM of WRF‐Hydro: Benefits of a 2D groundwater representation. Hydrological Processes, 36 (3), Art.-Nr.: e14510. doi:10.1002/hyp.14510

Yue, H.; Liu, C.; Zhang, W.; et al. (2022). How to Improve Cumulative Methane and Nitrous Oxide Flux Estimations of the Non‐Steady‐State Chamber Method?. Journal of Geophysical Research: Biogeosciences, 127 (3), e2021JG006641. doi:10.1029/2021JG006641

Havermann, F.; Ghirardo, A.; Schnitzler, J.-P.; et al. (2022). Modeling Intra‐ and Interannual Variability of BVOC Emissions From Maize, Oil‐Seed Rape, and Ryegrass. Journal of Advances in Modeling Earth Systems, 14 (3), e2021MS002683. doi:10.1029/2021MS002683

Hikino, K.; Danzberger, J.; Riedel, V. P.; et al. (2022). High resilience of carbon transport in long-term drought-stressed mature Norway spruce trees within 2 weeks after drought release. Global Change Biology, 28 (6), 2095–2110. doi:10.1111/gcb.16051

Hornick, T.; Richter, A.; Harpole, W. S.; et al. (2022). An integrative environmental pollen diversity assessment and its importance for the Sustainable Development Goals. Plants People Planet, 4 (2), 110–121. doi:10.1002/ppp3.10234

Hannigan, J. W.; Ortega, I.; Shams, S. B.; et al. (2022). Global Atmospheric OCS Trend Analysis From 22 NDACC Stations. Journal of Geophysical Research: Atmospheres, 127 (4), Art-Nr:e2021JD035764. doi:10.1029/2021JD035764

Janz, B.; Havermann, F.; Lashermes, G.; et al. (2022). Effects of crop residue incorporation and properties on combined soil gaseous N

_{2}

O, NO, and NH

_{3}

emissions—A laboratory-based measurement approach. Science of the Total Environment, 807 (2), Art.-Nr.: 151051. doi:10.1016/j.scitotenv.2021.151051

Redlich, S.; Zhang, J.; Benjamin, C.; et al. (2022). Disentangling effects of climate and land use on biodiversity and ecosystem services—A multi-scale experimental design. Methods in Ecology and Evolution, 13 (2), 514–527. doi:10.1111/2041-210X.13759

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