Evidence of Carbon Uptake Associated with Vegetation Greening Trends in Eastern China

Persistent and widespread increase of vegetation cover, identified as greening, has been observed in areas of the planet over late 20th century and early 21st century by satellite-derived vegetation indices. It is difficult to verify whether these regions are net carbon sinks or sources by studying vegetation indices alone. In this study, we investigate greening trends in Eastern China (EC) and corresponding trends in atmospheric CO₂ concentrations. We used multiple vegetation indices including NDVI and EVI to characterize changes in vegetation activity over EC from 2003 to 2016. Gap-filled time series of column-averaged CO₂ dry air mole fraction (XCO₂) from January 2003 to May 2016, based on observations from SCIAMACHY, GOSAT, and OCO-2 satellites, were used to calculate XCO₂ changes during growing season for 13 years. We derived a relationship between XCO₂ and surface net CO₂ fluxes from two inversion model simulations, CarbonTracker and Monitoring Atmospheric Composition and Climate (MACC), and used those relationships to estimate the biospheric CO₂ flux enhancement based on satellite observed XCO₂ changes. We observed significant growing period (GP) greening trends in NDVI and EVI related to cropland intensification and forest growth in the region. After removing the influence of large urban center CO₂ emissions, we estimated an enhanced XCO₂ drawdown during the GP of −0.070 to −0.084 ppm yr⁻¹. Increased carbon uptake during the GP was estimated to be 28.41 to 46.04 Tg C, mainly from land management, which could offset about 2–3% of EC’s annual fossil fuel emissions. These results show the potential of using multi-satellite observed XCO₂ to estimate carbon fluxes from the regional biosphere, which could be used to verify natural sinks included as national contributions of greenhouse gas emissions reduction in international climate change agreements like the UNFCC Paris Accord

Evaluación de los niveles de metano en zona de producción petrolera mediante el uso de imágenes satelitales bajo el enfoque de la ciencia de datos

En el contexto de una inminente crisis climática, monitorear los principales gases de efecto invernadero es una tarea imprescindible para la toma de decisiones. El metano (CH4) es el gas de efecto invernadero más importante después del dióxido de carbono (CO2). Debido a que es 80 veces más efectivo que el CO2 para atrapar calor en la atmósfera en un período de 20 años, y su tiempo de permanencia en el ambiente es de una década, la reducción de las emisiones de CH4 ha sido propuesta como una estrategia efectiva a corto plazo para mitigar el cambio climático. Entre las fuentes antropogénicas de CH4 se encuentra la industria del gas y el petróleo, que representa la oportunidad de menor costo y máxima disponibilidad para la reducción de las emisiones de este gas. En este trabajo se evalúan los niveles de CH4 sobre Argentina y sobre la cuenca Neuquina durante 2002-2019, mediante el análisis de los productos satelitales de los sensores SCIAMACHY, TANSO-FTS y TROPOMI. Se identificaron áreas con niveles mínimos y máximos dentro del territorio nacional y en la cuenca, coincidiendo en esta con las instalaciones hidrocarburíferas. Los niveles de CH4 se incrementaron a lo largo del período de análisis a una tasa de 6.95 ppb/año, con una oscilación estacional con máximos en meses fríos y mínimos en verano. Este comportamiento puede deberse al aumento de producción y consumo de gas para calefacción, pero tambíen a una menor dispersión atmosférica en invierno y mayor remoción del CH4 en verano. Dentro de la cuenca, la concentración media durante 2019 fue de 1787 ppb, sin embargo, se localizaron concentraciones por encima de los 2000 ppb en una zona puntual cercana a sitios de venteo no declarados. La información satelital para el monitoreo de rutina de CH4 en las instaciones de gas y petróleo presenta gran potencial, aunque aún es necesario el desarrollo tecnolgico que posibilite mediciones de alta resolución en las capas bajas de la atmósfera cercanas a las fuentes.Facultad de Ciencias Exacta

Exploring the Use of Remote Sensing CO2 Data to Measure the CO2 Concentration Enhancements Caused by Coal-fired Power Plants

Ontario’s power generation system is undergoing significant changes towards a modern and sustainable electricity system. One significant objective for the planned system transition is to reduce CO2 emissions. CO2 emissions from Ontario’s power generation are expected to be cut significantly as coal is phased out and more renewables and natural gas capacity are incorporated into the provincial electricity supply. This restructuring of Ontario’s electricity system and associated reduction of CO2 emissions need to be monitored. Equally, the dynamics of CO2 in the atmosphere are also a major issue of interest in the scientific world and how the reduced CO2 emissions from power plants can influence the distribution of CO2 concentration remains an important question. In this regard, remote sensing which provides global-coverage, near real-time and 3-D information on atmospheric CO2 is proposed as a useful tool for monitoring the processes and phenomena of interest. The ongoing space-based instruments such as GOSAT TANSO provide accurate CO2 concentration information at different altitudes especially near the Earth’s surface where interactions between power-generation CO2 emissions and the atmosphere are intensive. These data can be used for both long-term CO2 monitoring and short-term CO2 detection by measuring the emitting activities of power plants. Therefore, this project examines the use of remote sensing to estimate the change of CO2 enhancements due to the variation of coal-fired power generation intensity and to evaluate the effect of Ontario’s energy decision/policy. Partial column CO2 data are more capable of presenting the surface CO2 fluxes compared to column CO2 data. By introducing the ‘background’ observations, the fossil fuel CO2 flux in the Nanticoke area can be clearly detected and identified. The reduction of coal-fired power generation by Nanticoke Generating Station leads to decreased enhancement of local atmospheric CO2 concentrations. It is shown that Ontario’s decision to shut down coal-fired power plants is an effective measure to reduce atmospheric CO2 and to mitigate climate change. More policies and actions are encouraged along with new monitoring techniques that include remote sensing tools

Atmospheric Research 2018 Technical Highlights

Atmospheric research in the Earth Sciences Division (610) consists of research and technology development programs dedicated to advancing knowledge and understanding of the atmosphere and its interaction with the climate of Earth. The Divisions goals are to improve understanding of the dynamics and physical properties of precipitation, clouds, and aerosols; atmospheric chemistry, including the role of natural and anthropogenic trace species on the ozone balance in the stratosphere and the troposphere; and radiative properties of Earths atmosphere and the influence of solar variability on the Earths climate. Major research activities are carried out in the Mesoscale Atmospheric Processes Laboratory, the Climate and Radiation Laboratory, the Atmospheric Chemistry and Dynamics Laboratory, and the Wallops Field Support Office. The overall scope of the research covers an end-to-end process, starting with the identification of scientific problems, leading to observation requirements for remote sensing platforms, technology and retrieval algorithm development; followed by flight projects and satellite missions; and eventually, resulting in data processing, analyses of measurements, and dissemination from flight projects and missions

Determination of the methane budget of the Amazon region utilizing airborne methane observations in combination with atmospheric transport and vegetation modeling

The Amazon basin is an important player in the global methane cycle. Objectives of this work are to establish a forward and inverse modelling framework on regional scale and to determine the methane budget in the Amazon region. Within the BARCA project (Balanço Atmosférico Regional de Carbono na Amazônia) to airborne measurement campaigns were conducted, one in November 2008 and one in May 2009. The analysis of the methane observations confirms that the Amazon basin is a strong source of methane. The majority of the emissions is found to have biogenic origin, i.e. from wetlands. A comparison of five global methane inversions shows the advantage of using satellite observations in inversion systems. The WRF (Weather Research and Forecasting) Greenhouse Gas model was developed to perform high-resolution simulations of the atmospheric methane distribution in the Amazon region. The newly written code is available within the official WRF-Chem version 3.4 release. Simulations for the two months of the BARCA campaigns with two different wetland models and three different wetland maps were conducted with the WRF Greenhouse Gas model. The comparison to observations indicates that the choice of the wetland map is more important than the choice of the wetland model for a comparison to aircraft observations. Flights with a good representation of the atmospheric transport in the model show a higher correlation between observations and simulations. The two-step regional inversion scheme TM3-STILT was applied to the Amazon region for the year 2009 using observations from the 35 m high TT34 tower. The inversion shows improvements in the representation of the seasonal cycle of the methane emissions in the Amazon basin. However, the determination of the methane budget in the Amazon basin is still highly uncertain.Das Amazonasgebiet ist eine bedeutende Methanquelle im globalen Methankreislauf. Gegenstand dieser Dissertation ist der Aufbau einer Modellinfrastruktur auf regionaler Skala sowie die Bestimmung des Methanbudgets im Amazonasgebiet. Innerhalb des BARCA Projektes (Balanço Atmosférico Regional de Carbono na Amazônia) wurden zwei Flugzeugmesskampagnen im Amazonasgebiet im November 2008 und im Mai 2009 durchgeführt. Die Analyse der Methandaten bestätigt, dass das Amazonasgebiet eine starke Methanquelle ist und der Großteil der Emissionen aus Feuchtgebieten (sogenannten „Wetlands“) stammt. Vergleiche mit fünf globalen Methaninversionen zeigen den Vorteil der Nutzung von Satellitendaten in Inversionssystemen. Das WRF (Weather Research and Forecasting) Greenhouse Gas Modell wurde entwickelt, um hoch aufgelöste Simulationen der atmosphärischen Methanverteilung im Amazonasgebiet durchführen zu können. Der Programmcode steht innerhalb der offiziellen WRF-Chem Version 3.4 zu wissenschaftlichen Zwecken frei zur Verfügung. Hiermit wurden für die beiden Monate der BARCA Flugzeugkampagnen Methansimulationen mit zwei verschiedenen Wetland-Modellen und drei verschiedenen Wetland-Karten durchgeführt. Der Vergleich mit den Beobachtungen zeigt, dass die richtige Wahl der Wetland-Karte für den Vergleich mit Flugzeugdaten entscheidender ist als die Wahl des Wetland-Modells. Flüge, bei denen das Atmosphärentransportmodell den konvektiven Transport in der Atmosphäre gut wiedergibt, zeigen eine höhere Korrelation von Beobachtungen und Simulationen. Das zweistufige regionale Inversionsschema TM3-STILT wurde für das Jahr 2009 für Methan unter Zuhilfenahme von TT34-Turmbeobachtungen in 35 m Höhe für das Amazonasgebiet angewendet. Die Inversion zeigte Verbesserungen bei der korrekten Wiedergabe des saisonalen Verlaufs der Methanemissionen im Amazonasgebiet. Insgesamt ist die Bestimmung des Methanbudgets im Amazonasgebiet immer noch mit sehr großen Unsicherheiten behaftet

Geostatistical Analysis of CH4 Columns over Monsoon Asia Using Five Years of GOSAT Observations

The aim of this study is to evaluate the Greenhouse gases Observation SATellite (GOSAT) column-averaged CH4 dry air mole fraction (XCH4) data by using geostatistical analysis and conducting comparisons with model simulations and surface emissions. Firstly, we propose the use of a data-driven mapping approach based on spatio-temporal geostatistics to generate a regular and gridded mapping dataset of XCH4 over Monsoon Asia using five years of XCH4 retrievals by GOSAT from June 2009 to May 2014. The prediction accuracy of the mapping approach is assessed by using cross-validation, which results in a significantly high correlation of 0.91 and a small mean absolute prediction error of 8.77 ppb between the observed dataset and the prediction dataset. Secondly, with the mapping data, we investigate the spatial and temporal variations of XCH4 over Monsoon Asia and compare the results with previous studies on ground and other satellite observations. Thirdly, we compare the mapping XCH4 with model simulations from CarbonTracker-CH4 and find their spatial patterns very consistent, but GOSAT observations are more able to capture the local variability of XCH4. Finally, by correlating the mapping data with surface emission inventory, we find the geographical distribution of high CH4 values correspond well with strong emissions as indicated in the inventory map. Over the five-year period, the two datasets show a significant high correlation coefficient (0.80), indicating the dominant role of surface emissions in determining the distribution of XCH4 concentration in this region and suggesting a promising statistical way of constraining surface CH4 sources and sinks, which is simple and easy to implement using satellite observations over a long term period