Satellite-based estimates of nitrogen oxide and methane emissions from gas flaring and oil production activities in Sakha Republic, Russia

Ialongo, Iolanda; Степанова, Н.Ю.; Hakkarainen, Janne; Virta, Henrik; Gritsenko, Daria

doi:10.1016/j.aeaoa.2021.100114

Cited by 31 publications

(34 citation statements)

References 28 publications

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“…The advantage of these methods is that they do not require complex atmospheric modeling and that they generally provide more robust emission estimates compared to individual satellite overpasses. In addition, these approaches have been successfully applied to instruments and locations, where the individual plumes are not detectable, but the emission signal becomes visible when multiple scenes are averaged (e.g., Ialongo et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Analyzing Local Carbon Dioxide and Nitrogen Oxide Emissions From Space Using the Divergence Method: An Application to the Synthetic SMARTCARB Dataset

Hakkarainen

Ialongo

Koene

et al. 2022

Front. Remote Sens.

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Since the Paris Agreement was adopted in 2015, the role of space-based observations for monitoring anthropogenic greenhouse gas (GHG) emissions has increased. To meet the requirements for monitoring carbon dioxide (CO2) emissions, the European Copernicus programme is preparing a dedicated CO2 Monitoring (CO2M) satellite constellation that will provide CO2 and nitrogen dioxide (NO2) observations at 4 km2 resolution along a 250 km wide swath. In this paper, we adapt the recently developed divergence method to derive both CO2 and nitrogen oxide (NOx) emissions of cities and power plants from a CO2M satellite constellation by using synthetic observations from the COSMO-GHG model. Due to its long lifetime, the large CO2 atmospheric background needs to be removed to highlight the anthropogenic enhancements before calculating the divergence. Since the CO2 noise levels are large compared to the anthropogenic enhancements, we apply different denoising methods and compare the effect on the CO2 emission estimates. The annual NOx and CO2 emissions estimated from the divergence maps using the peak fitting approach are in agreement with the expected values, although with larger uncertainties for CO2. We also consider the possibility to use co-emitted NOx emission estimates for quantifying the CO2 emissions, by using source-specific NOx-to-CO2 emission ratios derived directly from satellite observations. In general, we find that the divergence method provides a promising tool for estimating CO2 emissions, alternative to typical methods based on inverse modeling or on the analysis of individual CO2 plumes.

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Section: Introductionmentioning

confidence: 99%

Analyzing Local Carbon Dioxide and Nitrogen Oxide Emissions From Space Using the Divergence Method: An Application to the Synthetic SMARTCARB Dataset

Hakkarainen

Ialongo

Koene

et al. 2022

Front. Remote Sens.

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“…NOx is a kind of air pollutant, and manmade NOx emissions mainly come from energy consumption. Considering the seriousness of NOx emissions, large number of scholars have confirmed energy-intensive industries such as iron and steel [34], thermal power [35], cement [36,37] and petrochemicals [38] have bad influences on NOx emissions. After subdividing these industrial sectors, scholars proposed that the emission factors of power generation in the iron and steel industry should be reduced [39], and coal-fired power plants should implement ultra-low emissions policies [35], strengthen technology research and development [40] and reduce NOx emissions.…”

Section: Introductionmentioning

confidence: 99%

New Urbanization, Energy-Intensive Industries Agglomeration and Analysis of Nitrogen Oxides Emissions Reduction Mechanisms

Wang

2021

Atmosphere

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With the deepening of urbanization and industrialization, as well as the exacerbation of energy consumption, China is facing a severe situation in which nitrogen oxide (NOx) emissions reduction is imperative. In this study, it is aimed to put forward countermeasures and suggestions to reduce NOx emissions by analyzing the impact and mechanism of new urbanization, the agglomeration of energy-intensive industries and mutual interactions on China’s NOx emissions. By analyzing the data of 30 provinces in China from 2006 to 2017, this paper adopted the system generalized method of moments (SYS-GMM) and intermediary effect model to introduce four variables, such as: energy efficiency, human capital, industrial structure and energy structure, which were for empirical analysis. From the results, it was shown that: (1) NOx emissions in China have an accumulated effect; (2) new urbanization inhibits NOx emissions, whilst the agglomeration of energy-intensive industries intensifies NOx emissions. New urbanization weakens the negative impact of the agglomeration of energy-intensive industries on NOx emissions reduction and, (3) among the impacts of new urbanization on NOx emissions, the energy efficiency and human capital reflect the intermediary effect mechanism. At the same time, in the impact of the agglomeration of energy-intensive industries on NOx emissions, the industrial structure and energy structure show the mechanisms of the intermediary effect and masking effect, respectively.

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“…Regarding the environment, CH 4 is the second most important anthropogenic GHG in terms of impact on climate and influence on air quality [4]. There is a high concentration of carbon dioxide (CO 2 ) in the atmosphere, yet CH 4 has a global warming potential approximately 28 times higher on a 100-year scale than that of CO 2 [5][6][7][8][9]. Calculations of CH 4 impact on climate change must consider indirect effects.…”

Section: Introductionmentioning

confidence: 99%

“…Due to CH 4 s explosive properties and the limited accessibility of the source (in the case of major gas leaks), remote sensing is a powerful tool, already validated up to quantification [24]. Satellite sounders, such as TROPOMI (TROPOspheric Monitoring Instrument) [25] on ESA's Sentinel-5 Precursor satellite, are suitable instruments to study CH 4 emissions on a global scale [9]. However, their kilometric spatial resolution is unsuitable for mapping anthropogenic CH 4 from industry.…”

Section: Introductionmentioning

confidence: 99%

Joint Use of in-Scene Background Radiance Estimation and Optimal Estimation Methods for Quantifying Methane Emissions Using PRISMA Hyperspectral Satellite Data: Application to the Korpezhe Industrial Site

Nesme

Marion

Lezeaux³

et al. 2021

Remote Sensing

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Methane (CH4) is one of the most contributing anthropogenic greenhouse gases (GHGs) in terms of global warming. Industry is one of the largest anthropogenic sources of methane, which are currently only roughly estimated. New satellite hyperspectral imagers, such as PRISMA, open up daily temporal monitoring of industrial methane sources at a spatial resolution of 30 m. Here, we developed the Characterization of Effluents Leakages in Industrial Environment (CELINE) code to inverse images of the Korpezhe industrial site. In this code, the In-Scene Background Radiance (ISBR) method was combined with a standard Optimal Estimation (OE) approach. The ISBR-OE method avoids the use of a complete and time-consuming radiative transfer model. The ISBR-OEM developed here overcomes the underestimation issues of the linear method (LM) used in the literature for high concentration plumes and controls a posteriori uncertainty. For the Korpezhe site, using the ISBR-OEM instead of the LM -retrieved CH4 concentration map led to a bias correction on CH4 mass from 4 to 16% depending on the source strength. The most important CH4 source has an estimated flow rate ranging from 0.36 ± 0.3 kg·s−1 to 4 ± 1.76 kg·s−1 on nine dates. These local and variable sources contribute to the CH4 budget and can better constrain climate change models.

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Satellite-based estimates of nitrogen oxide and methane emissions from gas flaring and oil production activities in Sakha Republic, Russia

Cited by 31 publications

References 28 publications

Analyzing Local Carbon Dioxide and Nitrogen Oxide Emissions From Space Using the Divergence Method: An Application to the Synthetic SMARTCARB Dataset

Analyzing Local Carbon Dioxide and Nitrogen Oxide Emissions From Space Using the Divergence Method: An Application to the Synthetic SMARTCARB Dataset

New Urbanization, Energy-Intensive Industries Agglomeration and Analysis of Nitrogen Oxides Emissions Reduction Mechanisms

Joint Use of in-Scene Background Radiance Estimation and Optimal Estimation Methods for Quantifying Methane Emissions Using PRISMA Hyperspectral Satellite Data: Application to the Korpezhe Industrial Site

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