Abstract

Abstract. The objective of this study is to derive methane (CH4) emissions from three landfills, which are found to be the most significant CH4 sources in the metropolitan area of Madrid in Spain. We derive CH4 emissions from the CH4 enhancements observed by spaceborne and ground-based instruments. We apply satellite-based measurements from the TROPOspheric Monitoring Instrument (TROPOMI) and the Infrared Atmospheric Sounding Interferometer (IASI) together with measurements from the ground-based COllaborative Carbon Column Observing Network (COCCON) instruments. In 2018, a 2-week field campaign for measuring the atmospheric concentrations of greenhouse gases was performed in Madrid in the framework of Monitoring of the Greenhouse Gases Concentrations in Madrid (MEGEI-MAD) project. Five COCCON instruments were deployed at different locations around the Madrid city center, enabling the observation of total column-averaged CH4 mixing ratios (XCH4). Considering the prevalent wind regimes, we calculate the wind-assigned XCH4 anomalies for two opposite wind directions. Pronounced bipolar plumes are found when applying the method to NO2, which implies that our method of wind-assigned anomaly is suitable to estimate enhancements of trace gases at the urban level from satellite-based measurements. For quantifying the CH4 emissions, the wind-assigned plume method is applied to the TROPOMI XCH4 and to the lower tropospheric CH4 / dry-air column ratio (TXCH4) of the combined TROPOMI+IASI product. As CH4 emission strength we estimate 7.4 × 1025 ± 6.4 × 1024 molec. s−1 from the TROPOMI XCH4 data and 7.1 × 1025 ± 1.0 × 1025 molec. s−1 from the TROPOMI+IASI merged TXCH4 data. We use COCCON observations to estimate the local source strength as an independent method. COCCON observations indicate a weaker CH4 emission strength of 3.7 × 1025 molec. s−1 from a local source (the Valdemingómez waste plant) based on observations from a single day. This strength is lower than the one derived from the satellite observations, and it is a plausible result. This is because the analysis of the satellite data refers to a larger area, covering further emission sources in the study region, whereas the signal observed by COCCON is generated by a nearby local source. All emission rates estimated from the different observations are significantly larger than the emission rates provided via the official Spanish Register of Emissions and Pollutant Sources.

Highlights

  • Methane (CH4) is the second most important anthropogenic greenhouse gas (GHG) after carbon dioxide (CO2) and contributes about 23.4 % to the radiative forcing by long-lived GHGs in the atmosphere (Etminan et al, 2016)

  • The mean value of TROPOspheric Monitoring Instrument (TROPOMI) XCH4 is calculated by collecting observations within a radius of 5 km around each COllaborative Carbon Column Observing Network (COCCON) station

  • The present study analyzes TROPOMI XCH4 and Infrared Atmospheric Sounding Interferometer (IASI) CH4 retrievals over an area around Madrid for more than 400 d within a rectangle of 39.5–41.5◦ N and 4.5–3.0◦ W (125 km × 220 km) from 10 November 2017 until 10 October 2020

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Summary

Introduction

Methane (CH4) is the second most important anthropogenic greenhouse gas (GHG) after carbon dioxide (CO2) and contributes about 23.4 % to the radiative forcing by long-lived GHGs in the atmosphere (Etminan et al, 2016). The global atmospheric CH4 emissions are approximately 40 % caused by natural sources (e.g., wetlands and termites), and about 60 % of emissions are from anthropogenic sources (Saunois et al, 2020). The anthropogenic sources of CH4 mainly originate from production and burning of fossil fuels, ruminant animals, agriculture and waste management (Bousquet et al, 2006; Chynoweth et al, 2001; Kirschke et al, 2013; Saunois et al, 2020). The waste management sector accounts for 21.5 % of the total anthropogenic CH4 emissions (Crippa et al, 2019), in which ∼ 44 % of emissions are from landfills. The quantification of CH4 emission from landfills using spaceborne and ground-based observations is of importance for future climate emission scenarios and for monitoring changes in emissions

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