Global background methane concentrations calculated in support of the HTAP3-OPNS exercise
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This repository contains global average methane concentrations up to the year 2050 as calculated by EMEP MSC-W (MET Norway) in support of the HTAP3-OPNS exercise. The projections include a Maximum Feasible Technical Reduction (MTFR) and baseline (CLE, for Current Legislation) scenario, as described in more detail in the supporting emission-file repository (Klimont et al., 2025; https://zenodo.org/records/14748815). In addition, concentrations for a hybrid constructed "HILO" scenario have been calculated. The HILO scenario combines air pollutant emissions (VOC, CO, NOx) from the MTFR scenario with methane emissions from the CLE scenario. For all scenarios, greenhouse gases other than methane and pollutants other than VOC, CO, and NOx are taken from the SSP2-4.5 scenario. The methane projections are calculated using the MAGICC7 model (Meinshausen et al., 2020, 2011, 2009) following the approach outlined in van Caspel et al. (2024). The MAGICC7 model is a probabilistic earth system model emulator, developed to efficiently calculate future greenhouse gas concentrations and global mean temperature change under different anthropogenic emission scenarios. The emission scenarios are combined with global averaged observed methane concentrations from the NOAA network (Lan et al., 2024) over a historical reference period (here taken to be 2018-2023) to estimate biogenic methane emissions. The biogenic emissions (estimated at 205.7 Tg/yr) are kept fixed for the future projections, noting that the model includes temperature-dependent permafrost emissions. The MAGICC7 model is further run in its 600-ensemble probabilistic mode, with the provided methane concentrations representing ensemble averages. Each of the scenario files contain global average methane concentrations between the years 1990 and 2050, with years up to and including 2023 corresponding to observed concentrations. References: Klimont, Z., Heyes, C., Hoglund-Isaksson, L., Lindl, F., Kim, Y., Rafaj, P., Purohit, P., Kaltenegger, K., Gomez-Sanabria, A., Winiwarter, W., Warnecke, L., Schoepp, W., Kiesewetter, G., Sander, R., Nguyen, B., Zhang, S., Brocza, F., & Wagner, F. (2025). Global gridded anthropogenic emissions of air pollutants and methane for the period 1990-2050 (V2.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14748815 van Caspel, W. E., Klimont, Z., Heyes, C., and Fagerli, H.: Impact of methane and other precursor emission reductions on surface ozone in Europe: scenario analysis using the European Monitoring and Evaluation Programme (EMEP) Meteorological Synthesizing Centre – West (MSC-W) model, Atmos. Chem. Phys., 24, 11545–11563, https://doi.org/10.5194/acp-24-11545-2024, 2024. Lan, X., Thoning, K., and Dlugokencky, E.: Trends in globally-averaged CH4 , N2 O, and SF6 determined from NOAA Global Monitoring Laboratory measurements, Version 2024-07, https://doi.org/10.15138/P8XG-AA10, 2024. Meinshausen, M., Meinshausen, N., Hare, W., Raper, S. C., Frieler, K., Knutti, R., Frame, D. J., and Allen, M. R.: Greenhouse-gas emission targets for limiting global warming to 2 C, Nature, 458, 1158–1162, https://doi.org/10.1038/nature08017, 2009. Meinshausen, M., Raper, S. C. B., and Wigley, T. M. L.: Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 – Part 1: Model description and calibration, Atmos. Chem. Phys., 11, 1417–1456, https://doi.org/10.5194/acp-11-1417-2011, 2011. Meinshausen, M., Nicholls, Z. R. J., Lewis, J., Gidden, M. J., Vogel, E., Freund, M., Beyerle, U., Gessner, C., Nauels, A., Bauer, N., Canadell, J. G., Daniel, J. S., John, A., Krummel, P. B., Luderer, G., Meinshausen, N., Montzka, S. A., Rayner, P. J., Reimann, S., Smith, S. J., van den Berg, M., Velders, G. J. M., Vollmer, M. K., and Wang, R. H. J.: The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500, Geosci. Model Dev., 13, 3571–3605, https://doi.org/10.5194/gmd-13-3571-2020, 2020.
本仓库包含由隶属于挪威气象局的欧洲监测与评估计划气象合成中心-西部（EMEP MSC-W）为支持HTAP3-OPNS演习所计算的截至2050年的全球平均甲烷浓度数据。该预测包含最大可行技术减排（Maximum Feasible Technical Reduction, MTFR）情景与现行立法基线（Current Legislation, CLE）情景，详细说明可参阅配套排放数据集仓库（Klimont等，2025；https://zenodo.org/records/14748815）。此外，本研究还计算了人工构建的混合“HILO”情景下的浓度数据：该情景将MTFR情景中的空气污染物排放（挥发性有机物（Volatile Organic Compounds, VOC）、一氧化碳（Carbon Monoxide, CO）、氮氧化物（Nitrogen Oxides, NOx））与CLE情景中的甲烷排放相结合。对于所有情景，除甲烷外的温室气体以及除VOC、CO、NOx外的污染物均采用共享社会经济路径2-4.5（Shared Socioeconomic Pathway 2-4.5, SSP2-4.5）情景的数据。 甲烷浓度预测采用MAGICC7模型（Meinshausen等，2020、2011、2009），遵循van Caspel等（2024）提出的方法进行计算。MAGICC7模型是一款概率性地球系统模型模拟器，旨在高效计算不同人为排放情景下未来温室气体浓度与全球平均气温变化。研究人员将排放情景与历史参考期（本文取2018-2023年）内美国国家海洋和大气管理局（National Oceanic and Atmospheric Administration, NOAA）观测网络的全球平均甲烷浓度数据（Lan等，2024）相结合，以估算生物源甲烷排放量。本次估算的生物源排放量为205.7太克/年（Teragram per year, Tg/yr），未来预测中将保持固定；需说明的是，模型已纳入温度依赖的永久冻土甲烷排放模块。本研究采用MAGICC7模型的600成员集合概率运行模式，提供的甲烷浓度数据为集合平均值。 所有情景文件均包含1990年至2050年的全球平均甲烷浓度，其中2023年及之前的年份数据为实测浓度。 参考文献 Klimont, Z., Heyes, C., Hoglund-Isaksson, L., Lindl, F., Kim, Y., Rafaj, P., Purohit, P., Kaltenegger, K., Gomez-Sanabria, A., Winiwarter, W., Warnecke, L., Schoepp, W., Kiesewetter, G., Sander, R., Nguyen, B., Zhang, S., Brocza, F., & Wagner, F. (2025). 1990-2050年全球网格化人为空气污染物与甲烷排放（V2.1）[数据集]. Zenodo. https://doi.org/10.5281/zenodo.14748815 van Caspel, W. E., Klimont, Z., Heyes, C., and Fagerli, H.: 甲烷与其他前体物减排对欧洲地表臭氧的影响：基于欧洲监测与评估计划气象合成中心-西部（EMEP MSC-W）模型的情景分析. 大气化学与物理, 24, 11545–11563, https://doi.org/10.5194/acp-24-11545-2024, 2024. Lan, X., Thoning, K., and Dlugokencky, E.: 基于NOAA全球监测实验室观测数据的全球平均CH4、N2O和SF6变化趋势（2024-07版）, https://doi.org/10.15138/P8XG-AA10, 2024. Meinshausen, M., Meinshausen, N., Hare, W., Raper, S. C., Frieler, K., Knutti, R., Frame, D. J., and Allen, M. R.: 全球升温限制在2℃的温室气体排放目标. 自然, 458, 1158–1162, https://doi.org/10.1038/nature08017, 2009. Meinshausen, M., Raper, S. C. B., and Wigley, T. M. L.: 用简化模型模拟耦合大气-海洋与碳循环模型：MAGICC6——第1部分：模型描述与校准. 大气化学与物理, 11, 1417–1456, https://doi.org/10.5194/acp-11-1417-2011, 2011. Meinshausen, M., Nicholls, Z. R. J., Lewis, J., Gidden, M. J., Vogel, E., Freund, M., Beyerle, U., Gessner, C., Nauels, A., Bauer, N., Canadell, J. G., Daniel, J. S., John, A., Krummel, P. B., Luderer, G., Meinshausen, N., Montzka, S. A., Rayner, P. J., Reimann, S., Smith, S. J., van den Berg, M., Velders, G. J. M., Vollmer, M. K., and Wang, R. H. J.: 共享社会经济路径（SSP）温室气体浓度及其延伸至2500年的预测. 地球科学模型开发, 13, 3571–3605, https://doi.org/10.5194/gmd-13-3571-2020, 2020.
