CarbonDew Library

‍Al-Qasim, A.S., Alzayani, A., Almuaibid, A., Yousef, A., Burba, G., Fratini, G., Griessbaum, F. and Facius, D., 2023. The intelligent Carbon Leakage Surveillance (iCLS) System. Abu Dhabi International Petroleum Exhibition and Conference, Paper Number: SPE-216502-MS, 18 pp. DOI: 10.2118/216502-MS

Anić, M., Ostrogović Sever, M.Z., Alberti, G., Balenović, I., Paladinić, E., Peressotti, A., Tijan, G., Večenaj, Ž., Vuletić, D. and Marjanović, H., 2018. Eddy covariance vs. biometric based estimates of net primary productivity of pedunculate oak (Quercus robur L.) forest in Croatia during ten years. Forests, 9(12), p.764. See at MDPI

Ashburn, L., 2024. Flux stations are a critical measurement tool in the agrifood industry's quest to reach climate goals. CarbonSpace [online]. https://carbonspace.tech/blog/fluxstations

Ashburn, L., 2024. Net ecosystem exchange: A paradigm shift for tracking the carbon footprint of land use. CarbonSpace [online]. https://carbonspace.tech/blog/nee

Baldocchi, D.D., 2020. How eddy covariance flux measurements have contributed to our understanding of Global Change Biology. Global Change Biology, 26(1), pp.242–260. DOI: 10.1111/gcb.14807

Bautista, N., Marino, B.D. and Munger, J.W., 2021. Science to commerce: a commercial-scale protocol for carbon trading applied to a 28-year record of forest carbon monitoring at the Harvard Forest. Land, 10(2), p.163. See at MDPI

Burba, G., 2022. Eddy Covariance Method for Scientific, Regulatory, and Commercial Applications. Lincoln, USA: LI-COR Biosciences, Hard- and Softbound, 702 pp. ISBN: 978-0-578-97714-0. See at LI-COR

Burba, G., 2025. Harvesting Carbon: Fields & Grasslands. A guide to utilizing direct flux measurements for assessment and verification of carbon sequestration and GHG emission rates over areas. ESS Open Archive, 42 pp. DOI: 10.22541/essoar.173884298.81896551/v1

Burba, G., 2025. Harvesting Carbon: Forests, Orchards, & Wooded Wetlands. A guide to utilizing direct flux measurements for assessment and verification of carbon sequestration and GHG emission rates over areas. ESS Open Archive, 45 pp. DOI: 10.22541/essoar.173884304.47041905/v1

Burba, G., 2025. Harvesting Carbon: Lakes, Ponds, & Wetlands. A guide to utilizing direct flux measurements for assessment and verification of carbon sequestration and GHG emission rates over areas. ESS Open Archive, 46 pp.

Burba, G., Madsen, R. and Feese, K., 2013. Eddy covariance method for CO₂ emission measurements in CCUS applications: principles, instrumentation, and software. Energy Procedia, 40, pp.329–336. See at ScienceDirect

Burba, G., McDermitt, D., Xu, L., Li, J., Green, R., Chanton, J. and Welding, K., 2016. Using automated eddy-covariance stations for studying landfill methane emissions. Air & Waste Management Association — Air Quality Measurement Methods & Technology Conference, 2016, pp.159–170. See at ResearchGate

Burba, G., Metzger, S., Awada, T., Demidov, O., Desai, A., Desjardins, R., Durden, D., Elston, J., Granat, R., Hemes, K., Kannenberg, S., Kayode, J.S., Koeppel, A., Koren, G., Lee, S.C., Mutambala, L., Mwape, A., Pashkin, V., Runkle, B., Schodel, S., Senthilvalavan, P., Shanahan, J. and Surendran, U.P., 2023. CarbonDew coordinated response to the draft federal strategy to advance greenhouse gas emissions measurement and monitoring for the agriculture and forest sectors. ESS Open Archive, 8 pp. DOI: 10.22541/essoar.169418018.80680586/v2

Campioli, M., Malhi, Y., Vicca, S., Luyssaert, S., Papale, D., Peñuelas, J., Reichstein, M., Migliavacca, M., Arain, M.A. and Janssens, I.A., 2016. Evaluating the convergence between eddy-covariance and biometric methods for assessing carbon budgets of forests. Nature Communications, 7(1), p.13717. See at Nature

Chen, S., Liu, L., Ma, Y., Zhuang, Q. and Shurpali, N.J., 2024. Quantifying global wetland methane emissions with in situ methane flux data and machine learning approaches. Earth's Future, 12, e2023EF004330. DOI: 10.1029/2023EF004330

Chu, H., Luo, X., Ouyang, Z., Chan, W.S., Dengel, S., Biraud, S.C., Torn, M.S., Metzger, S., Kumar, J., Arain, M.A. et al., 2021. Representativeness of eddy-covariance flux footprints for areas surrounding AmeriFlux sites. Agricultural and Forest Meteorology, 301–302, p.108350. DOI: 10.1016/j.agrformet.2021.108350

Davis, K.J., Deng, A., Lauvaux, T., Miles, N.L., Richardson, S.J., Sarmiento, D.P., Gurney, K.R., Hardesty, R.M., Bonin, T.A., Brewer, W.A. et al., 2017. The Indianapolis Flux Experiment (INFLUX): a test-bed for developing urban greenhouse gas emission measurements. Elementa: Science of the Anthropocene, 5, p.21. DOI: 10.1525/elementa.188

Demuzere, M., Harshan, S., Järvi, L., Roth, M., Grimmond, C.S.B., Masson, V., Oleson, K.W., Velasco, E. and Wouters, H., 2017. Impact of urban canopy models and external parameters on the modelled urban energy balance in a tropical city. Quarterly Journal of the Royal Meteorological Society, 143, pp.1581–1596. DOI: 10.1002/qj.3028

Desai, A., 2024. The invisible hand of carbon dioxide on forest productivity. EOS Editor Highlights. See at EOS

Diaz, M.B., Roberti, D.R., Carneiro, J.V., de Arruda Souza, V. and de Moraes, O.L.L., 2019. Dynamics of the superficial fluxes over a flooded rice paddy in southern Brazil. Agricultural and Forest Meteorology, 276, p.107650. See at ScienceDirect

Dilley, M. and Grimes, D., 2024. Policy brief: promoting mitigation and biodiversity by increasing the value of natural carbon sequestration. See at Hyphen

Goettemoeller, J. and Gas Analysers Team, 2016. Tools for mapping greenhouse gas emissions in urban environments. International Environmental Technology, 9/10, 2 pp.

Gurney, K. and Shepson, P., 2021. The power and promise of improved climate data infrastructure. Proceedings of the National Academy of Sciences, 118(35), p.e2114115118. DOI: 10.1073/pnas.2114115118

Haniff, M.H., Ibrahim, A., Jantan, N.M., Shahabudin, N., Mos, H. and Yusup, Y., 2016. Carbon dioxide and energy fluxes above an oil palm canopy in peninsular Malaysia. International Journal of Agronomy and Agricultural Research, 9(2), pp.137–146. See at ResearchGate

Haniff, M.H., Ibrahim, A., Jantan, N.M., Shahabudin, N., Mos, H., Afifah, A.R. and Yusup, Y., 2018. Influence of eddy covariance sensor height above the oil palm canopy on CO₂ and energy fluxes. Journal of Oil Palm Research, 30(March 2018), pp.94–100. DOI: 10.21894/jopr.2018.0005

Hemes, K.S., Runkle, B.R., Novick, K.A., Baldocchi, D.D. and Field, C.B., 2021. An ecosystem-scale flux measurement strategy to assess natural climate solutions. Environmental Science & Technology, 55(6), pp.3494–3504. DOI: 10.1021/acs.est.0c06421

Hutley, L.B., Leuning, R., Beringer, J. and Cleugh, H.A., 2005. The utility of the eddy covariance techniques as a tool in carbon accounting: tropical savanna as a case study. Australian Journal of Botany, 53(7), pp.663–675. See at Academia

Hyphen Global, 2024. Building trust in carbon markets through atmospheric-based greenhouse gas monitoring and verification. See at Hyphen

ICOS, 2024. Monitor, report, and verify emissions to accelerate climate action. See at ICOS

Lipson, M., Grimmond, S., Best, M., Chow, W., Christen, A., Chrysoulakis, N., Coutts, A., Crawford, B., Earl, S., Evans, J., Fortuniak, K., Heusinkveld, B.G., Hong, J.-W., Hong, J., Järvi, L., Jo, S., Kim, Y.-H., Kotthaus, S., Lee, K., Masson, V., McFadden, J.P., Michels, O., Pawlak, W., Roth, M., Sugawara, H., Tapper, N., Velasco, E. and Ward, H.C., 2022. Harmonized gap-filled datasets from 20 urban flux tower sites. Earth System Science Data, 14, pp.5157–5178. DOI: 10.5194/essd-14-5157-2022

Maboni, C., Bremm, T., Aguiar, L.J.G., Scivittaro, W.B., de Arruda Souza, V., Zimermann, H.R., Teichrieb, C.A., de Oliveira, P.E.S., Herdies, D.L., Degrazia, G.A. and Roberti, D.R., 2021. The fallow period plays an important role in annual CH₄ emission in a rice paddy in southern Brazil. Sustainability, 13(20), p.11336. See at MDPI

Marras, S., Masia, S., Duce, P., Spano, D. and Sirca, C., 2015. Carbon footprint assessment on a mature vineyard. Agricultural and Forest Meteorology, 214, pp.350–356. DOI: 10.1016/j.agrformet.2015.08.270

McNicol, G., Fluet-Chouinard, E., Ouyang, Z., Knox, S., Zhang, Z., Aalto, T., Bansal, S., Chang, K.-Y., Chen, M., Delwiche, K. et al., 2023. Upscaling wetland methane emissions from the FLUXNET-CH4 eddy covariance network (UpCH4 v1.0): model development, network assessment, and budget comparison. AGU Advances, 4, e2023AV000956. DOI: 10.1029/2023AV000956

Meier, F., Pawlak, W., Roth, M., Theeuwes, N.E., Velasco, E., Vogt, R. and Teuling, A.J., 2022. Urban water storage capacity inferred from observed evapotranspiration recession. Geophysical Research Letters, 49(3), p.e2021GL096069. DOI: 10.1029/2021GL096069

Meili, N., Manoli, G., Burlando, P., Carmeliet, J., Chow, W., Coutts, A., Roth, M., Velasco, E., Vivoni, E. and Fatichi, S., 2021. Tree effects on urban microclimate: diurnal, seasonal and climatic temperature differences explained by separating radiation, evapotranspiration, and roughness effects. Urban Forestry & Urban Greening, 58, p.126970. DOI: 10.1016/j.ufug.2021.126970

Metzger, S., Burba, G., Aguilos, M., Bernier, T., Curtis, B., Demidov, O., Durden, D., Elston, J., Hamann, H., Hawkins, J., Kayode, J.S., Kisekka, I., Klein, L., Knox, S., Koren, G., Malone, S., Pierrat, Z., Runkle, B., Schodel, S., Shanahan, J., Shrestha, G., Udayar Pillai, S., Vargas, R., Velasco, E. and Yi, K., 2023. CarbonDew coordinated response to: the federal strategy to advance an integrated US greenhouse gas monitoring and information system. ESS Open Archive, 6 pp. DOI: 10.22541/essoar.168500353.39806527/v1

Metzger, S., Romano, N., Weintraub-Leff, S., Burba, G., Oikawa, P. et al., 2023. CarbonDew: Direct greenhouse gas exchange measurements for equitable worldwide emissions trading. Battelle 2023 Conference "Innovations in Climate Resilience", Columbus, Ohio, 28–30 March.

Mills, M.B., Malhi, Y., Ewers, R.M., Kho, L.K., Teh, Y.A., Both, S., Burslem, D.F., Majalap, N., Nilus, R., Huaraca Huasco, W. and Cruz, R., 2023. Tropical forests post-logging are a persistent net carbon source to the atmosphere. Proceedings of the National Academy of Sciences, 120(3), p.e2214462120. See at PNAS

Mos, H., Harun, M.H.H., Jantan, N.M.M., Hashim, Z., Ibrahim, A.S.S. and Yusup, Y., 2023. Differences in CO₂ emissions on a bare-drained peat area in Sarawak, Malaysia, based on different measurement techniques. Agriculture, 13, 622. DOI: 10.3390/agriculture13030622

Nelson, J.A., Pérez-Priego, O., Jung, M., Koirala, S., Migliavacca, M., Goulas, Y., Jägermeyr, J., Gentine, P., Reichstein, M. and Hilker, T., 2024. X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X. Biogeosciences, 21, pp.5079–5115. DOI: 10.5194/bg-21-5079-2024

Nicolini, G., Antoniella, G., Carotenuto, F., Christen, A., Ciais, P., Feigenwinter, C., Gioli, B., Stagakis, S., Velasco, E., Vogt, R., Ward, H.C., Barlow, J., Chrysoulakis, N., Karl, T., Graus, M., Helfter, C., Heusinkveld, B., Järvi, L., Marras, S., Masson, V., Matthews, B., Meier, F., Nemitz, E., Sabbatini, S., Scherer, D., Schume, H., Sirca, C., Spano, D., Steeneveld, G.J., Vagnoli, C., Wang, Y., Zaldei, A., Zheng, B. and Papale, D., 2022. Direct observations of CO₂ emission reductions due to COVID-19 lockdown across European urban districts. Science of the Total Environment, 830, p.154662. DOI: 10.1016/j.scitotenv.2022.154662

Novick, K.A., Metzger, S., Anderegg, W.R.L., Barnes, M., Cala, D.S., Guan, K., Hemes, K.S., Hollinger, D.Y., Kumar, J., Litvak, M., Lombardozzi, D., Normile, C.P., Oikawa, P., Runkle, B.R.K., Torn, M. and Wiesner, S., 2022. Informing nature-based climate solutions for the U.S. with the best-available science. Global Change Biology, pp.1–17. DOI: 10.1111/gcb.16156

Novick, K., Williams, C., Runkle, B., Anderegg, W.R.L., Hollinger, D., Litvak, M., Normile, C., Shrestha, G., Almaraz, M., Anderson, C., Barnes, M., Baldocchi, D., Colburn, L., Cullenward, D., Evans, M., Guan, K., Keenan, T., Lamb, R., Larson, L., Oldfield, E., Poulter, B., Reyes, J., Sanderman, J., Selmants, P., Sepulveda Carlo, E., Torn, M.S., Trugman, A. and Woodall, C., 2022. White Paper: The Science Needed for Robust, Scalable, and Credible Nature-Based Climate Solutions in the United States: Summary Report. Bloomington, IN: Indiana University, 16 pp. DOI: 10.5967/5968rgp-tc5911

Papale, D., Christen, A., Davis, K., Feigenwinter, C., Gioli, B., Järvi, L., Matthews, B., Velasco, E. and Vogt, R., 2022. Eddy covariance flux observations. Chapter B.i. In: IG3IS Urban Greenhouse Gas Emission Observation and Monitoring Good Research Practice Guidelines. GAW Report No. 275. Geneva: World Meteorological Organization, pp.114–123. See at WMO

Pastorello, G., Trotta, C., Canfora, E., Chu, H., Christianson, D., Cheah, Y.-W., Poindexter, C., Chen, J., Elbashandy, A., Humphrey, M. et al., 2020. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Scientific Data, 7, p.225. DOI: 10.1038/s41597-020-0534-3

Peddinti, S.R. and Kambhammettu, B.P., 2019. Dynamics of crop coefficients for citrus orchards of central India using water balance and eddy covariance flux partition techniques. Agricultural Water Management, 212, pp.68–77. See at ScienceDirect

Quinn, T., Boettiger, C., Carey, C., Dietze, M., Johnson, L., Kenney, M., McLachlan, J., Peters, J., Sokol, E., Weltzin, J., Willson, A., Woelmer, W., Barbosa, C., Bartolucci, N., Benson, M., Bhat, U., Bitters, M., Burba, G., Burnet, S., Ceja, P. et al., 2023. The NEON ecological forecasting challenge. Frontiers in Ecology and the Environment, 21(3), pp.112–113. DOI: 10.1002/fee.2616

Roberti, D.R., Mergen, A., Gotuzzo, R.A., Veeck, G.P., Bremm, T., Marin, L., de Quadros, F.L.F. and Jacques, R.J.S., 2024. Sustainability in natural grassland in the Brazilian Pampa biome: livestock production with CO₂ absorption. Sustainability, 16(9), p.3672. See at MDPI

Roth, M., Jansson, C. and Velasco, E., 2017. Multi-year energy balance and carbon dioxide fluxes over a residential neighborhood in a tropical city. International Journal of Climatology, 37, pp.2679–2698. DOI: 10.1002/joc.4873

Runkle, B.R., Suvočarev, K., Reba, M.L., Reavis, C.W., Smith, S.F., Chiu, Y.L. and Fong, B., 2018. Methane emission reductions from the alternate wetting and drying of rice fields detected using the eddy covariance method. Environmental Science & Technology, 53(2), pp.671–681. See at NSF/PMC

Schreiner-McGraw, A.P., Ransom, C.J., Veum, K.S., Wood, J.D., Sudduth, K.A. and Abendroth, L.J., 2024. Quantifying the impact of climate smart agricultural practices on soil carbon storage relative to conventional management. Agricultural and Forest Meteorology, 344, p.109812. DOI: 10.1016/j.agrformet.2023.109812

Shrestha, O., Khan, A., Torrion, J.A., McVay, K., Powell, S.P., Sigler, A. and Stoy, P., Crop coefficients for cereal crops in Montana USA from eddy covariance observations. Preprint. See at ResearchGate

So, K., Rogers, C.A., Li, Y., Arain, M.A. and Gonsamo, A., 2024. Retention forestry as a climate solution: assessing biomass, soil carbon and albedo impacts in a northern temperate coniferous forest. Science of the Total Environment, p.174680. See at ScienceDirect

Stagakis, S., Feigenwinter, C., Vogt, R., Brunner, D., Kotthaus, S., Chrysoulakis, N. and Grimmond, S., 2023. A high-resolution monitoring approach of urban CO₂ fluxes. Part 2 – surface flux optimisation using eddy covariance observations. Science of the Total Environment, 903, p.166046. DOI: 10.1016/j.scitotenv.2023.166046

Talib, A., Desai, A.R., Huang, J., Thom, J., Panuska, J.C. and Stoy, P.C., 2024. Improving parameterization of an evapotranspiration estimation model with eddy covariance measurements for a regional irrigation scheduling program. Agricultural and Forest Meteorology, 350, p.109967. See at ScienceDirect

Teets, A., Fraver, S., Hollinger, D.Y., Weiskittel, A.R., Seymour, R.S. and Richardson, A.D., 2018. Linking annual tree growth with eddy-flux measures of net ecosystem productivity across twenty years of observation in a mixed conifer forest. Agricultural and Forest Meteorology, 249, pp.479–487. See at ScienceDirect

van Ramshorst, J.G.V., Knohl, A., Callejas-Rodelas, J.Á., Clement, R., Hill, T.C., Siebicke, L. and Markwitz, C., 2024. Lower-cost eddy covariance for CO₂ and H₂O fluxes over grassland and agroforestry. Atmospheric Measurement Techniques, 17, pp.6047–6071. DOI: 10.5194/amt-17-6047-2024

Vargas, R., Loescher, H.W., Arredondo, T., Huber-Sannwald, E., Lara-Lara, R. and Yépez, E.A., 2012. Opportunities for advancing carbon cycle science in Mexico: toward a continental scale understanding. Environmental Science & Policy, 21, pp.84–93. See at Academia

Vargas, R., Yépez, E.A., Andrade, J.L., Ángeles, G., Arredondo, T., Castellanos, A.E., Delgado, J., Garatuza-Payan, J., González-Castillo, E., Oechel, W., Sánchez-Azofeifa, A., Velasco, E., Vivoni, E.R. and Watts, C., 2013. Progress and opportunities for water and greenhouse gases flux measurements in Mexican ecosystems: the MexFlux network. Atmósfera, 26(3), pp.325–336. DOI: 10.1016/S0187-6236(13)71079-7

Veeck, G.P., Dalmago, G.A., Bremm, T., Buligon, L., Jacques, R.J.S., Fernandes, J.M., Santi, A., Vargas, P.R. and Roberti, D.R., 2022. CO₂ flux in a wheat-soybean succession in subtropical Brazil: a carbon sink. Vol. 51, No. 5, pp.899–915. DOI: 10.1007/s13593-022-00808-3

Velasco, E., 2021. Impact of Singapore's COVID-19 confinement on atmospheric CO₂ fluxes at neighborhood scale. Urban Climate, 37, p.100822. DOI: 10.1016/j.uclim.2021.100822

Velasco, E., 2022. Services and limits of urban vegetation to mitigate climate change. Department of Architecture, National University of Singapore, Singapore, 14 January.

Velasco, E., 2023. Urban flux towers: applications and challenges. AmeriFlux Annual Meeting 2023, Harvard Forest, Petersham, Massachusetts, USA, 4–6 October.

Velasco, E., 2023. Urban warming, climate change and atmospheric pollution. First Colloquium on Urban Climates, Institute of Geography, National Autonomous University of Mexico, Mexico City, Mexico, 25 August.

Velasco, E., Lamb, B., Pressley, S., Allwine, E., Westberg, H., Jobson, B.T., Alexander, M., Prazeller, P., Molina, L. and Molina, M., 2005. Flux measurements of volatile organic compounds from an urban landscape. Geophysical Research Letters, 32(20), p.L20802. DOI: 10.1029/2005GL023773

Velasco, E., Perrusquia, R., Jiménez, E., Hernández, F., Camacho, P., Rodríguez, S., Retama, A. and Molina, L.T., 2014. Sources and sinks of carbon dioxide in a neighborhood of Mexico City. Atmospheric Environment, 97, pp.226–238. DOI: 10.1016/j.atmosenv.2014.08.018

Velasco, E., Pressley, S., Allwine, E., Grivicke, R., Molina, L.T. and Lamb, B., 2011. Energy balance in urban Mexico City: observation and parameterization during the MILAGRO/MCMA-2006 field campaign. Theoretical and Applied Climatology, 103, pp.501–517. DOI: 10.1007/s00704-010-0314-7

Velasco, E., Pressley, S., Allwine, E., Westberg, H. and Lamb, B., 2005. Measurements of CO₂ fluxes from the Mexico City urban landscape. Atmospheric Environment, 39(38), pp.7433–7446. DOI: 10.1016/j.atmosenv.2005.08.038

Velasco, E., Pressley, S., Grivicke, R., Allwine, E., Coons, T., Foster, W., Jobson, T., Westberg, H., Ramos, R., Hernández, F., Molina, L.T. and Lamb, B., 2009. Eddy covariance flux measurements of pollutant gases in urban Mexico City. Atmospheric Chemistry and Physics, 9, pp.7325–7342. DOI: 10.5194/acp-9-7325-2009

Velasco, E. and Roth, M., 2010. Cities as net sources of CO₂: review of atmospheric CO₂ exchange in urban environments measured by eddy covariance technique. Geography Compass, 4(9), pp.1238–1259. DOI: 10.1111/j.1749-8198.2010.00384.x

Velasco, E., Roth, M., Norford, L. and Molina, L.T., 2016. Does urban vegetation enhance carbon sequestration? Landscape and Urban Planning, 148, pp.99–107. DOI: 10.1016/j.landurbplan.2015.12.018

Velasco, E., Roth, M., Tan, S.H., Quak, M., Nabarro, S. and Norford, L., 2013. The role of vegetation in the CO₂ flux from a tropical urban neighborhood. Atmospheric Chemistry and Physics, 13, pp.10185–10202. DOI: 10.5194/acp-13-10185-2013

Velasco, E., Segovia, E. and Roth, M., 2023. High-resolution maps of carbon dioxide and moisture fluxes over an urban neighborhood. Environmental Science: Atmospheres, 3, pp.1110–1123. DOI: 10.1039/D3EA00007A

Vogel, F.R., Frey, M., Wenger, A., Guillevic, M., Brunner, D., Wu, D., Feigenwinter, C., Oney, B., Leuenberger, M., Steinbacher, M. et al., 2024. Using eddy-covariance to measure the effects of COVID-19 restrictions on CO₂ emissions in a neighborhood of Indianapolis, IN. Carbon Balance and Management, 19(1). DOI: 10.1080/17583004.2024.2365900

Wall, A.M., Campbell, D.I., Mudge, P.L. and Schipper, L.A., 2020. Temperate grazed grassland carbon balances for two adjacent paddocks determined separately from one eddy covariance system. Agricultural and Forest Meteorology, 287, p.107942. DOI: 10.1016/j.agrformet.2020.107942

Wang, X., Che, T., Xiao, J., Wang, T., Tan, J., Zhang, Y., Ren, Z., Geng, L., Wang, H., Xu, Z., Liu, S. and Li, X., 2025. A post-processed carbon flux dataset for 34 eddy covariance flux sites across the Heihe River basin, China. Earth System Science Data, 17, pp.1329–1346. DOI: 10.5194/essd-17-1329-2025

Ward, P.R., Micin, S.F. and Fillery, I.R.P., 2012. Application of eddy covariance to determine ecosystem-scale carbon balance and evapotranspiration in an agroforestry system. Agricultural and Forest Meteorology, 152, pp.178–188. DOI: 10.1016/j.agrformet.2011.09.007

Wiesner, S., Desai, A.R., Duff, A.J., Metzger, S. and Stoy, P.C., 2022. Quantifying the natural climate solution potential of agricultural systems by combining eddy covariance and remote sensing. Journal of Geophysical Research: Biogeosciences, 127(9), p.e2022JG006895. See at Wiley

Williams, C. et al., 2022. North American Carbon Program Science Implementation Plan. NACP, 161 pp. See at NACARBON

Xia, Y., Sanderman, J., Watts, J.D., Machmuller, M.B., Mullen, A.L., Rivard, C., Endsley, A., Hernandez, H., Kimball, J., Ewing, S.A. and Litvak, M., 2025. Coupling remote sensing with a process model for the simulation of rangeland carbon dynamics. Journal of Advances in Modeling Earth Systems, 17(3), p.e2024MS004342. DOI: 10.1029/2024MS004342

Yi, K., Novick, K.A., Stoy, P.C., Reichstein, M., Jung, M., Law, B.E. and Baldocchi, D., 2026. Bioclimatic reorganization of carbon–water–energy coupling revealed by eddy covariance and interpretable machine learning. Global Change Biology Communications, e70012. DOI: 10.1002/gcb4.70012

Yuan, J., Jose, S., Hu, Z., Pang, J., Hou, L. and Zhang, S., 2018. Biometric and eddy covariance methods for examining the carbon balance of a Larix principis-rupprechtii forest in the Qinling Mountains, China. Forests, 9(2), p.67. See at MDPI

Yusup, Y., Ramli, N.K., Kayode, J.S., Yin, C.S., Hisham, S., Mohamad Isa, H. and Ahmad, M.I., 2020. Atmospheric carbon dioxide and electricity production due to lockdown. Sustainability, 12, p.9397. DOI: 10.3390/su12229397

Zalakeviciute, R., Alexander, M.L., Allwine, E., Jimenez, J.L., Jobson, B.T., Molina, L.T., Nemitz, E., Pressley, S.N., VanReken, T.M., Ulbrich, I.M. and Velasco, E., 2012. Chemically-resolved aerosol eddy covariance flux measurements in urban Mexico City during MILAGRO 2006. Atmospheric Chemistry and Physics, 12(16), pp.7809–7823. DOI: 10.5194/acp-12-7809-2012

Zhuravlev, R., Dara, A., Santos, A.L.D.D., Demidov, O. and Burba, G., 2022. Globally scalable approach to estimate net ecosystem exchange based on remote sensing, meteorological data, and direct measurements of eddy covariance sites. Remote Sensing, 14(21), p.5529. DOI: 10.3390/rs14215529

Last updated July 28, 2026