Thursday, May 2, 2024

Ilmatieteen laitos valmistautuu Copernicus CO2M -missioon

Vuonna 2015 solmitun Pariisin ilmastosopimuksen myötä ihmisten aiheuttamien kasvihuonekaasupäästöjen monitorointi on noussut entistä tärkeämmäksi. Tämän takia Euroopan komission maanseurantaohjelma Copernicus on valmistelemassa uutta CO2M-missiota, jonka tarkoituksena on erityisesti keskittyä ihmisten aiheuttamien hiilidioksidipäästöjen seurantaan. Satelliittikonstellaation on tarkoitus koostua kahdesta tai useammasta satelliitista, jotka havainnoivat hiilidioksidia (CO2) ja typpidioksidia (NO2) 250 km laajuisella kaistalla 4 km2 spatiaalisella resoluutiolla. Ensimmäinen satelliitti on tarkoitus laukaista vuonna 2026.

Ilmatieteen laitoksen vetämässä, vasta julkaistussa tutkimuksessa [1] datapohjaisia päästöestimointimenetelmiä sovellettiin Sentinel 5P -satelliitin TROPOMI-mittalaitteen typpidioksidihavaintoihin. Tutkimuksen tavoitteena oli tutkia Matimba/Medupi-kivihiilivoimaloiden päästöjä Etelä-Afrikassa. Koska voimaloiden päästö on typpimonoksidin ja typpidioksidin summa (NOx = NO + NO2) ja satelliitti mittaa pelkkää typpidioksidia, niin datapohjaiset päästöarviointimenetelmät tarvitsevat skaalauskertoimia, jotta NO2-pohjainen päästöarvio voidaan muuttaa oikeaan muotoon.  Tutkimuksessa osoitettiin, että tarvittavat skaalauskertoimet riippuvat sekä käytetystä päästöestimointimenetelmistä, että alueesta mistä päästöinformaatio tulee.



Tutkimuksessa käytettyjen MicroHH-simulointien perusteella johdetut skaalauskertoimet ovat huomattavasti (yli 50 %) korkeammat kuin kirjallisuudessa yleisesti käytetyt tyypilliset arvot todellisten NO2-havaintojen kanssa,” julkaistua tutkimusta vetänyt Janne Hakkarainen kertoo.

Ilmatieteen laitos oli mukana EU:n H2020-ohjelman CoCO2-hankkeessa. Hankkeen keskeisenä tavoitteena oli valmistautua tuleviin CO2M-mittalaitteen havaintoihin. Ilmatieteen laitoksen vetämässä työpaketissa kehitettiin datapohjaisia menetelmiä voimakkaiden päästölähteiden kuten kivihiilivoimaloiden ja kaupunkien päästöestimointiin. Tavoitteena oli myös verrata eri menetelmiä keskenään käyttäen hyväksi synteettisiä mittauksia.

Työpaketin seurauksena syntyi kolme uutta tieteellistä julkaisua aiemman Ilmatieteen laitoksen vetämän menetelmäpaperin lisäksi. Sveitsiläisen Empa-instituutin vetämässä artikkelissa [2] rakennettiin ddeq Python-kirjasto, jolla voidaan satelliittikuvista laskea pistelähteiden päästöt. Ranskalaisen LSCE-instituutin vetämässä julkaisussa [3] eri menetelmiä verrattiin keskenään.

 

Viitteet:

[1] Janne Hakkarainen, Gerrit Kuhlmann, Erik Koene, Diego Santaren, Sandro Meier, Maarten C. Krol, Bart J.H. van Stratum, Iolanda Ialongo, Frédéric Chevallier, Johanna Tamminen, Dominik Brunner, Grégoire Broquet,: Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods: a case study of Matimba/Medupi power stations in South Africa, Atmospheric Pollution Research, Volume 15, Issue 7, https://doi.org/10.1016/j.apr.2024.102171, 2024.

[2] Kuhlmann, G., Koene, E. F. M., Meier, S., Santaren, D., Broquet, G., Chevallier, F., Hakkarainen, J., Nurmela, J., Amorós, L., Tamminen, J., and Brunner, D.: The ddeq Python library for point source quantification from remote sensing images (Version 1.0), Geoscientific Model Development, https://doi.org/10.5194/egusphere-2023-2936, 2024.

[3] Santaren, D., Hakkarainen, J., Kuhlmann, G., Koene, E., Chevallier, F., Ialongo, I., Lindqvist, H., Nurmela, J., Tamminen, J., Amoros, L., Brunner, D., and Broquet, G.: Benchmarking data-driven inversion methods for the estimation of local CO2 emissions from XCO2 and NO2 satellite images, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-241, 2024.

Friday, September 22, 2023

Satellites capture socioeconomic disruptions during the 2022 full-scale war in Ukraine


Satellite observations show significantly reduced air pollution levels over the major Ukrainian cities, power plants and industrial areas.

Since February 2022, the full-scale war in Ukraine has been strongly affecting society and economy in Ukraine. Satellite observations provide crucial information to objectively monitor and assess the impacts of the war. A new paper published today on Scientific Reports utilizes satellite observations of air pollutants and other relevant parameters from multiple platforms to assess the impacts of the ongoing war on the Ukrainian society. Satellite observations show that the concentrations of nitrogen dioxide (NO₂), which is emitted through fossil fuel combustion processes, declined in 2022 over the major Ukrainian cities, power plants and industrial areas by 15–46%.

Such reductions reflect the decrease in population and corresponding emissions from the transport and commercial or residential sectors as well as the decline in industrial production, especially from the metallurgic and chemical industry, which led to a reduction in power demand and corresponding electricity production from power plants. Carbon dioxide (CO₂) observations also indicate reductions in fossil fuel combustion, especially in eastern Ukraine, where the largest emission sources are located.

Difference of the March-August mean tropospheric NO2 columns between 2022 and 2021 based on S5P/TROPOMI observations. Blue colors indicate reductions observed in 2022. Black dots correspond to the major cities, industrial areas and power plants.


“During peaceful times, reductions in nitrogen dioxide concentrations as those observed here would be considered as a welcome improvement of air quality and human health. In this case, the observed changes tell a different story about the extent of the disruption caused by the war on the Ukrainian society and economy. Also, the reductions in fossil fuel consumption in Ukraine might have been partly offset by an increase elsewhere”, explains senior researcher at the Finnish Meteorological Institute Iolanda Ialongo, who led the work.

Exceptional fire patterns near the front line  

Satellite imagery and fire detections indicate an anomalous distribution of fires along the front line, which are attributable to shelling or other war-related fires, rather than the typical homogeneously distributed fires related to crop harvesting. Satellite imagery data also show drastic changes over the city of Mariupol, which was attacked during the first three months of the war.

The signal from the hot smokes from the metallurgic industrial facilities in the city disappears from the satellite imagery after March 2022, which suggest an interruption of industrial activities, and, correspondingly, NO₂ levels decreased.

The results are based on the NO₂ retrievals from the European TROPOMI (TROPOspheric Monitoring Instrument), onboard the Sentinel 5 Precursor satellite, and the CO₂ observations from the NASA’s OCO-2 satellite. Also satellite imagery from the Sentinel 2 satellite was analyzed as well as fire detectionsfrom the Visible Infrared Imaging Radiometer Suite (VIIRS).

The research was carried on at the Finnish Meteorological Institute together with colleagues from the University of Lviv (Ukraine) and USRA (USA). The Finnish part of the research was supported by the Ministry for Foreign Affairs of Finland via theInterinstitutional Development Cooperation Instrument (ICI), UHMC-FMI Meteorology project and the Research Council of Finland.

Reference: Ialongo, I., Bun, R., Hakkarainen, J. et al. Satellites capture socioeconomic disruptions during the 2022 full-scale war in Ukraine. Sci Rep 13, 14954 (2023). https://doi.org/10.1038/s41598-023-42118-w

Sunday, September 17, 2023

Two weeks in China

Hello,

some while a go me and my buddy Prof. Dongxu Yang got a joint Finland-China cooperation project together. He got the money from the Chinese Academy of Sciences (CAS) to travel to Finland and I got the money from the Research council of Finland to travel to China.

During the COVID-19 it was difficult to travel. But finally, after a long wait, I got to travel to China in September 2023. The travel plan was quite simple: The first week I would be visiting Dongxu at the Institute of Atmospheric Physics (IAP), CAS, and the second one we would be in the ESA-MOST DRAGON symposium in Inner Mongolia.

The first week was full of interesting discussions with many different people. For example, I got to see the drone equipment and we had discussions how they are planning to estimate CO2 emissions from power plants and validate satellite-based results. They plan to use cross-sectional flux methods, as I have done in my own research. I was happy to see that they use sensors from the Finnish Vaisala company.


I also got to speak about my work on the IAP seminar. After the seminar, I had some nice discussion about my work with Kai Wu who has previously worked on MicroCarb project at the University of Edinburgh. Actually, surprisingly many of the people I met, have worked there. At IAP they have many seminars. On the same day that I gave my seminar presentation, we went to see some AI/ML seminar by some famous Chinese scientist. The seminar was in Chinese, so I couldn’t follow much even though the slides were in English.


The week was also full of interesting dinners with interesting people and some sightseeing of course. I also got the visit the Earth Lab with Dongxu. During my visit the institute also had its 95th birthday and during weekend they had big celebration at the Earth Lab.


On Sunday evening me, Dongxu and Prof. Liu traveled together on a high-speed train to Inner Mongolia’s capital Hohhot where the DRAGON symposium takes place. The train stations in China seem like airports and trains like airplanes. In general, on a technological level, it seems that Chinese people are ahead of Europeans. For example, everything is paid and done on a mobile app.

On Monday, Prof. Liu organized a Workshop on China-EU GHGs measurement from Space. I also got to present my work and we had discussions on co-operations between European Copernicus CO2M and China’s TanSat-2 missions.


Tuesday marked the official opening of the DRAGON Symposium and the symposium started with some traditional Inner Mongolian music. During the poster session I had interesting discussions with Qiangian Zhang, who has done similar work that I have. I also presented a paper poster.

Wednesday was our DRAGON project main day, and Prof. Liu presented the project very well. We also prepared a summary slide of our work that Ronald van der A presented at the final session summaries. Our recommendations to ESA and MOST were:
  1. High-level co-operation between TanSat-2 and Copernicus CO2M missions to be organized by ESA and MOST
  2. TanSat-2 to be included as an ESA Third Party Mission


On Friday afternoon I took a train back to Beijing with a fantastic duo from IAP/CAS: Lu Yao and Yuli Zhang. After the train arrived at Beijing, they were kind enough to put me in taxi on towards the airport hotel. On Saturday morning I started my journey back to Europe and on Sunday at 1:30 a.m. I arrived home. Then I rested.

Thank you!

Janne

Tuesday, February 21, 2023

Building a Bridge: Estimating Carbon Dioxide Emissions Using Satellites

Building a Bridge: Estimating Carbon Dioxide Emissions Using Satellites

 

A team of researchers estimated the carbon dioxide (CO2) emissions from coal-fired power plants and other major anthropogenic point sources in the South African Highveld region using space-based data. The results indicate that the CO2 emissions can be obtained also in challenging cases where the plumes from multiple sources overlap.

 

The new publication characterizes CO2 emissions using data from NASA’s Orbiting Carbon Observatory-3 (OCO-3) and European Copernicus Sentinel-5P/TROPOMI.

 

The article analyses the emissions of six power stations (Kendal, Kriel, Matla, Majuba, Tutuka and Grootvlei) and the largest single emitter of greenhouse gas in the world, Secunda CTL synthetic fuel plant. The annual CO₂ emissions of the Secunda CTL exceed the emissions of several European countries, including Finland, Norway, and Portugal. 

 

Overall, the space-based emission estimates are in good agreement with the emission inventories. Thus, satellite observations can be used for CO2 emission estimation and are particularly useful when no other information is available.

 

Orbiting Carbon Observatory-3 mission operates on the International Space Station (ISS). To support the quantification and monitoring of anthropogenic CO₂ emissions, OCO-3 incorporates a new key capability that provides observations in Snapshot Area Maps (SAMs), providing contiguous images over regions as large as 80 km by 80 km in two minutes. Altogether the article analyzes six OCO-3 SAMs jointly with Sentinel-5P/TROPOMI nitrogen dioxide (NO2) columns.


Sentinel-5P/TROPOMI NO₂ and OCO-3 XCO₂ SAM observations on 21 January 2022.

The new article is a continuation of the previous work where the authors studied the emissions and NOx-to-CO₂ emission ratio of the isolated Matimba power station. The article extends the method to challenging cases where CO₂ plumes from multiple sources overlap.

 

The applicability of similar emission estimation approaches for future satellite missions such as the Copernicus Carbon Dioxide Monitoring mission CO2M are discussed. CO2M is Copernicus Sentinel Expansion missions and will focus on carbon dioxide released into the atmosphere specifically through human activity.

 

The research was carried on at Finnish Meteorological Institute together with colleagues from USRA, Colorado State University and Caltech/JPL. The Finnish part of the research was supported by European Space Agency (DACES), Academy of Finland (CitySpot, CoE inverse and ACCC) and EU-H2020 CoCO2.

 

The full publication by Hakkarainen and co-authors can be found at the following link: https://doi.org/10.1088/1748-9326/acb837

Wednesday, November 9, 2022

Optical flow

Hi Guys,

when I was visiting the inverse problems research group at the University of Helsinki I learned about the method called optical flow. We used this method in out paper on dynamic X-ray data.

Recently, I've been studying how the optical flow method could be applied to my current research on CO2 emission estimation.

Of course I had to try the optical flow method also on myself


Note that this method is not based on machine learning.

Cheers,

Janne

Saturday, July 9, 2022

Uusi menetelmä ihmisten aiheuttamien hiilidioksidipäästöjen seurantaan avaruudesta

Uusi menetelmä ihmisten aiheuttamien hiilidioksidipäästöjen seurantaan avaruudesta

 

Vuonna 2015 solmitun Pariisin ilmastosopimuksen myötä ihmisten aiheuttamien kasvihuonekaasupäästöjen monitorointi on noussut entistä tärkeämmäksi. Tämän johdosta Euroopan komission maanseurantaohjelma Copernicus on valmistelemassa uutta CO2M-missiota, jonka tarkoituksena on erityisesti keskittyä ihmisten aiheuttamien hiilioksidipäästöjen seurantaan. Satelliittikonstellaation on tarkoitus koostua kahdesta tai useammasta satelliitista, jotka havainnoivat hiilidioksidia (CO2) ja typpidioksidia (NO2) 250 km laajuisella kaistalla 4 km2 spatiaalisella resoluutiolla. Ensimmäinen satelliitti on tarkoitus laukaista vuonna 2025.


Simuloituja CO2M-satelliitin XCO2-havaointoja. Kuva: Gerrit Kuhlmann, Empa.


Julkaistussa tutkimuksessa kehitettiin uusi divergenssimenetelmä, jonka avulla voidaan laskea hiilidioksidin ja typen oksidien (NOx) päästöt kaupungeista ja voimaloista. Menetelmää sovellettiin mallisimulaatioista saatuihin synteettisiin CO2M-havaintoihin (esitetty kuvassa). Koska CO2-havaintojen tausta ja kohina ovat suuria verrattuna havaittuihin päästölisäyksiin, julkaisussa sovellettiin myös erilaisia kohinansuodatusmenetelmiä. Divergenssimenetelmä saadut päästöestimaatit ovat linjassa odotettujen arvojen kanssa. Julkaisussa keskusteltiin myös hiilidioksidipäästöjen laskemisesta NOx-päästöistä käyttäen hyväksi suoraan satelliittihavainnoista laskettua NOx:CO2-suhdetta. Yleisesti tutkimuksessa havaittiin, että divergenssimenetelmä antaa hyvän vaihtoehtoisen tavan laskea CO2-päästöt verrattuna esimerkiksi inversiomallinnusmenetelmiin ja menetelmiin, jotka laskevat päästöt yksittäisistä satelliittikuvista.

 

Tutkimus on tehty yhteistyössä Ilmatieteen laitoksen ja Sveitsiläisen Empa-instituutin kanssa. Sen rahoittamiseen ovat osallistuneet EU:n H2020-projekti CoCO2 ja Euroopan avaruusjärjestö ESA:n rahoittama projekti DACES, sekä Suomen Akatemia (CitySpot, ACCC, Inversiomallinnuksen ja kuvantamisen huippuyksikkö).




Viite: Janne Hakkarainen, Iolanda Ialongo, Erik Koene, Monika E. Szeląg, Johanna Tamminen, Gerrit Kuhlmann, Dominik Brunner: Analyzing Local Carbon Dioxide and Nitrogen Oxide Emissions From Space Using the Divergence Method: An Application to the Synthetic SMARTCARB Dataset, Frontiers in Remote Sensing, vol 3, 2022, doi:10.3389/frsen.2022.878731, Linkki


Friday, June 10, 2022

Anthropogenic Emission Monitoring with the Copernicus CO2 Monitoring Mission

Hi guys,

I am pleased to say that our manuscript was accepted today for the CO2M special issue “Anthropogenic Emission Monitoring with the Copernicus CO2 Monitoring Mission” in Frontiers in Remote Sensing.



Our paper is called “Analyzing local carbon dioxide and nitrogen oxide emissions from space using the divergence method: An application to the synthetic SMARTCARB dataset” and it is joint work between Finnish Meteorological Institute and Empa, Switzerland. The abstract is already online: https://www.frontiersin.org/articles/10.3389/frsen.2022.878731/abstract

I will write more about the paper when it is officially published!

Stay tuned!

Janne

Wednesday, February 2, 2022

Hi guys,

yesterday I was thinking what would happened if one would start Conway's Game of Life from the Ulam Spiral...


-Janne

Monday, September 13, 2021

Emissions from Siberian oil fields detected from space

Hi guys,

I wanted to advertize our new paper on Atmospheric Environmemt: X "Satellite-based estimates of nitrogen oxide and methane emissions from gas flaring and oil production activities in Sakha Republic, Russia." It is a very nice collaborative effort between natural and social sciences led by Iolanda. The results are strongly related to our ESA-funded DACES project.

In the paper there are lot of interesting analysis on nitrogen oxide and methane emissions in Tas-Yuryakh and Talakan oil fields. One of my favorite pictures is the one below illustrating methane anomalies as observed S5P/TROPOMI over Talakan. The patterns of the site are clearly visible.
TROPOMI/S5P methane enhancement over Talakan oil field. Credits: Ialongo et al., (2021), CC BY 4.0


To have more information please see this article in FMI-SPACE or in Finnish here. Please also check the full paper below:

Ialongo, I., Stepanova, N., Hakkarainen, J., Virta, H., Gritsenko, D.: Satellite-based estimates of nitrogen oxide and methane emissions from gas flaring and oil production activities in Sakha Republic, Russia, Atmospheric Environment: X, Volume 11,  https://doi.org/10.1016/j.aeaoa.2021.100114, 2021.

Cheers,
Janne



Wednesday, June 23, 2021

Carbon dioxide emission plumes from a large power station detected from space

Researchers at the Finnish Meteorological Institute developed a new methodology to derive source-specific NOₓ-to-CO₂ emission ratios using satellite observations. The method was applied to Matimba power station in South Africa. The results can be used to estimate carbon dioxide emissions.


Since the Paris agreement was adopted in 2015, the role of satellite observations in understanding anthropogenic CO2emissions has become increasingly important. Currently, the NASA’s CO2 instrument Orbiting Carbon Observatory-2 (OCO-2), launched in 2014, provides CO2 observations with the best coverage and resolution. However, the observations are obtained on a narrow swath (less than 10 km), which does allow the detection of the cross-sections of the emission plumes, but not the plumes in their entirety. Satellite observations of co-emitted species, such as NO2, facilitate the detection of the CO2 emission plumes. The European Commission is currently planning a new CO2 monitoring mission CO2M via the Copernicus Programme, which will observe both CO2 and NO2 over a larger swath (over 250 km).

OCO-2 and TROPOMI observations near Matimba power station (red triangle) in South Africa between May 2018 and November 2020. Image: Hakkarainen et al. 2021. CC BY 4.0.


Estimating CO2 emissions from individual sources using satellite data can be challenging due to the large background levels, while it is easier for short-lived gases like NO2. In a recently published study, a new methodology to calculate source-specific NOₓ-to-CO₂ emission ratio from satellite observations is developed. This ratio provides information on how clean the employed technology is and can be used to convert NOₓ emission into CO2 emission. The method was tested for the Matimba power station in South Africa, which is an optimal case study as it is a large emission source with several satellite overpasses, and it is also well isolated from other sources.


The results are based on the CO2 observations from the NASA’s OCO-2 satellite and the NO2 retrievals from the European TROPOMI (TROPOspheric Monitoring Instrument), operating onboard the Sentinel 5 Precursor satellite since late 2017. During the 2018–2020 period, 14 collocations over Matimba enabled the simultaneous detection of the CO2and NO2 plumes. The mean NOx-to-CO2 emission ratio was estimated as (2.6 ± 0.6) × 10-3 and the CO2 emission as 60 kton/day. The obtained CO₂ emission estimates are similar to those reported in existing inventories such as ODIAC.


The research was carried on in the DACES project, which focuses on detecting anthropogenic CO₂ emissions sources by exploiting the synergy between satellite-based observations of short-lived polluting gases (such as NO₂) and greenhouse gases.


The full publication by Hakkarainen and co-authors can be found at the following link:https://doi.org/10.1016/j.aeaoa.2021.100110

Monday, May 24, 2021

Ihmisperäisiä hiilidioksidipäästöjä metsästämässä – apurina satelliitit

Ilmatieteen laitoksella kehitettiin uusi menetelmä laskea yksittäisten päästölähteiden, kuten kaupunkien ja voimaloiden, NOₓ/CO₂-suhde avaruudesta käsin. Tuloksia voidaan hyödyntää myös hiilidioksidipäästöjen arvioinnissa. Uutta menetelmää sovellettiin Etelä-Afrikassa sijaitsevaan Matimba-hiilivoimalaan, joka on yksi maailman suurimmista.

Matimba-hiilivoimala Etelä-Afrikassa. Wikimedia commons. CC BY-SA 3.0

Vuonna 2015 solmitun Pariisin sopimuksen myötä ihmistoiminnasta peräisin olevien kasvihuonekaasupäästöjen rooli tutkimuksessa on noussut yhä tärkeämmäksi, sillä päästöjä ja niiden vähennyksiä halutaan seurata. Esimerkiksi Euroopan komissio suunnittelee uutta satelliittipohjaista CO2M-missiota ihmisperäisten hiilidioksidipäästöjen seuraamiseen osana Copernicus-maanseurantaohjelmaansa.

Ilmatieteen laitoksella on tutkittu ihmisperäisiä kasvihuonekaasuja avaruudesta käsin vuodesta 2016 alkaen. Tutkimuksessa on hyödynnetty erityisesti vuonna 2014 laukaistua NASAn OCO-2-satelliittia, joka on edelleen paras mittalaite tähän työhön. Ihmisperäisten hiilidioksidipäästöjen kartoittamisen kannalta sen kapea mittauskaista asettaa kuitenkin haasteita.

Eräs keskeisistä ongelmista ilmakehätieteissä on laskea päästöt yksittäisistä päästölähteistä kuten kaupungeista ja voimaloista. Tämä on erityisen haastavaa hiilidioksidin (CO₂) kohdalla, kun taas typen oksidien NOₓ-päästöjä on monitoroitu satelliiteista lähes rutiininomaisesti jo 1990-luvulta alkaen. Ilmanlaadun kannalta NOₓ- ja CO₂-päästöjen välinen suhde kertoo käytetyn tekniikan puhtaudesta.

Juuri julkaistussa tutkimuksessa kehitettiin uusi menetelmä, jolla voidaan laskea NOₓ/CO₂-suhde avaruudesta käsin. Näin laskettua suhdetta voidaan hyödyntää myös, jos halutaan kääntää NOₓ-päästöt hiilidioksidipäästöiksi. Tutkimuksessa tätä menetelmää sovellettiin Etelä-Afrikassa sijaitsevaan Matimba-hiilivoimalaan. Se on tutkimuksen kannalta erinomainen koelaboratorio, sillä se on voimakas pistemäinen päästölähde ja suhteellisen etäällä muista päästölähteistä.

Tutkimuksessa hyödynnettiin vuonna 2017 laukaistun eurooppalaisen Sentinel 5 Precursor S5P-satelliitin tekemiä mittauksia, jotka mahdollistavat ensi kertaa yksittäisten typpidioksidipilvien (NO₂-pilvet) kartoittamisen satelliitista käsin. Tutkimuksessa yhdistettiin S5P-satelliitin havaitsemat NO₂-pilvet ja OCO-2-satelliitin CO₂-havainnot. Vuosilta 2018–2020 löydettiin yhteensä 14 satelliitin ylilentoa, jossa kapealla kaistalla mittaavan OCO-2-satelliitin havainnot kyettiin kytkemään S5P-satelliittiin mittaamiin NO₂-pilviin.

Kuvassa S5P ja OCO-2-satelliittien havaintoja vuosilta 2018–2020 yhdistettynä. Matimba-hiilivoimala on merkitty kuvaan punaisella kolmiolla. Hiilivoimalasta peräisin olevat NOₓ-päästöt näkyvät kuvassa punaisesta kolmiosta lähtevänä pilvenä lähialueella. OCO-2-satelliittin tekemät mittaukset hiilidioksidista näkyvät kapeina viivoina kuvassa. Nämä havainnot yhdistämällä voidaan laskea NOₓ/CO₂-suhde. Kuva: Hakkarainen et al. 2021. CC BY 4.0.


Ilmakehää mallinnettiin FLEXPART-mallilla ja tuloksena saatiin Matimba-hiilivoimalan NOₓ/CO₂-suhteeksi (2.6 ± 0.6) × 10-3 ja hiilidioksidipäästöiksi noin 60 kilotonnia päivässä, joka on suuruusluokaltaan noin puolet koko Suomen hiilidioksidipäästöistä. Tutkimuksessa lasketut arviot ovat yhteneviä aikaisempien päästöinventaarioiden (esim. ODIAC) tulosten kanssa.

Tutkimusta on tehty erityisesti Euroopan Avaruusjärjestö ESAn rahoittamassa DACES-projektissa, josta voit lukea lisää projektin verkkosivuilta.

Viite:
Janne Hakkarainen, Monika E. Szeląg, Iolanda Ialongo, Christian Retscher, Tomohiro Oda, and David Crisp: Analyzing nitrogen oxides to carbon dioxide emission ratios from space: A case study of Matimba Power Station in South Africa, Atmospheric Environment: Volume 10, 2021.

Lue tieteellinen artikkeli täältä: https://doi.org/10.1016/j.aeaoa.2021.100110

Tuesday, April 20, 2021

Analyzing nitrogen oxides to carbon dioxide emission ratios from space: A case study of Matimba Power Station in South Africa

Hi guys,

I just wanted to say that we have a new paper on Atmospheric Environment: X

The paper Analyzing nitrogen oxides to carbon dioxide emission ratios from space: A case study of Matimba Power Station in South Africa was written by myself, Iolanda Ialongo, Monika Szeląg, Christian Retscher, Tomohiro Oda, and David Crisp.

Highlights:
  • A new methodology to derive source-specific NOx-to-CO2 emission ratios.
  • The method is applied for TROPOMI and OCO-2 satellite observations.
  • The mean emission ratio of (2.6±0.6)×10−3 is obtained for Matimba Power Station.
  • The annual CO2 emissions for Matimba are ∼60 kt/d.
  • The emission estimates are consistent with existing inventories such as ODIAC.

The Journal Pre-proof version is already available online: https://doi.org/10.1016/j.aeaoa.2021.100110
I will write more about this paper later.

Stay tuned!

Janne

Wednesday, March 17, 2021

Pandigital π

Hah!

Yesterday I was watching this Numberphile video

   

and like Dr. James Grime, I did not like the pandigital formula for π. So I decided to play a little with pen and paper, and found the following
I think it is quite neat. Of course, I knew beforehand that 355/113 approximates π quite well, up to 6 decimal places. Actually, it is called Milü

Cheers,
Janne

Saturday, February 13, 2021

Faktoja ilmastonmuutoksesta: hiilinielu vai hiilivarasto?

Monilla tuntuu menevän käsitteet hiilinielu ja hiilivarasto lahjakkaasti sekaisin. Erityisen harmilliselta tämä tuntuu, jos kyseessä on ns. vakavasti otettava tutkija.

Fakta 1. Toisin kun yleensä luullaan vanhat metsät kuten Amazonin sademetsä ei ole voimakas hiilinielu. Nuoret metsät (alle 140 vuotta) taas ovat. Yleistajuisesti voi PNAS-lehdessä julkaistusta tutkimuksesta voi lukea täältä.

(Myös muut tutkimustulokset, kuten omani, ovat päätyneet samaan johtopäätökseen, mutta se ei nyt varsinaiset liity tähän.)

Tämä ei ole oikeastaan yllättävää. On selvää, että hyvin vanha metsä (yli 150 vuotta) ei enää toimi hiilinieluna vaan voi jopa toimia päästölähteenä. Toisaalta nuori parhaassa kasvuiässä oleva metsä toimii voimakkaana hiilinieluna eli se poistaa ilmakehästä hiiltä. Vanha metsä voi toki olla suurempi hiilivarasto kuin nuori metsä, mutta nieluna se ei enää toimi. Jos siis halutaan, että metsät toimivat hiilinieluina olisi oltava mahdollisimman paljon 20–80-vuotiasta metsää.

Fakta 2. Hiilinielu ei ole hiilivarasto. Nielu on prosessi, toiminta tai mekanismi, joka sitoo kasvihuonekaasun, aerosolin tai niiden esiasteen ilmakehästä. Lähde taas tarkoittaa prosessia, toimintaa tai mekanismia, joka vapauttaa kasvihuonekaasun, aerosolin tai niiden esiasteen ilmakehään. Hiilivarasto taas kertoo yksinkertaisesti paljonko johonkin on varastoitunut hiiltä. Yksinkertaisesti voi ajatella, että puuliiterissä olevat klapit ovat hiilivarastossa, mutta muuttuvat päästöiksi saunan pesässä. Kun saunan vieressä oleva puu kasvaa (ja poistaa ilmakehästä hiiltä), niin se toimii nieluna.

Fakta 3. Hiilivaraston muutos ei ole hiilinielu. Tehdään ajatuskoe. Käyt lähimetsässä ja poimit metsästä kilogramman edestä hiiltä. Nyt metsän hiilivarasto on pienentynyt kilogramman verran, mutta ilmakehä ei tiedä tästä mitään eli et ole aiheuttanut päästöjä. Vastaavasti jos viet hiilen takaisin metsään, niin metsä ei ole ymmärrettävästi toiminut ilmakehän hiilinieluna. Jos veistät löytämästä puusta lusikoita, se toimii hiilivarastona (ei nieluna!) ja jos taas poltat löytämäsi puun, aiheutat päästöjä.

Bonus. Puut eivät tulevat maasta vaan ilmasta kertoo Richard Feynman.

Friday, December 18, 2020

Virtual Inverse Days 2020

Virtual Inverse Days 2020

 

University of Helsinki and Finnish Meteorological Institute co-organized 26th Inverse Days of the Finnish Inverse Problems Society. This year the conference was organized virtually, and the chair of the Scientific committee was Tatiana Bubba from the University of Helsinki. The conference had altogether 59 scientific talks and more than 180 registered participants.

 

Inverse Days is the annual scientific conference of the Finnish Inverse Problems Society (FIPS). The first Inverse Days were organized at the University of Oulu in 1995. This year the conference was organized virtually for the first time due to the global COVID-19 pandemic. The conference was divided in 10 scientific session. The sessions covered both theoretical and applied inverse problems. Application areas included 3D X-ray tomography, electrical impedance tomography, forestry, uncertainty quantification and atmospheric inverse problems among others. The themes followed the themes of the Finnish Centre of Excellence in Inverse Modelling and Imaging. The session number 2 was dedicated to the memory of the late Mikko Kaasalainen (born 1965, died 12 April 2020), who was a professor of mathematics at the Tampere University and an important member of the Finnish Inverse Problems Society. The conference had 25 highlight talks, 29 regular talks and five plenary talks. The plenary talks were given by Chris Johnson (U. Utah), Silvia Gazzola (U. Bath), Valery Serov (U. Oulu), Simon Pfreunschuh (Chalmers U. Tech.) and Barbara Kaltenbacher (U. Klagenfurt). Number of registered participants was all-time record: 185.

 

In addition to scientific program, the conference also had a special session to celebrate the 60th birthday of Prof. Erkki Somersalo, the founding president of FIPS. The birthday program included scientific talks related to Erkki Somersalo’s research and career along with more humoristic ones. Master of the ceremony was Prof. Samuli Siltanen, the current president of FIPS. For the first time, the Inverse days also had virtual lab excursions. The lab excursion included: 

·      X-ray Tomography Laboratory (UH), Alexander Meaney

·      Spectrometers in Atmospheric Measurements (FMI), Tomi Karppinen

·      Log X-ray Systems (Finnos Oy), Jere Heikkinen

·      Biomed. Optical Imaging and Ultrasound Lab (UEF), Aki Pulkkinen

·      Process Tomography Laboratory (UEF), Aku Seppänen

 

Virtual lab excursions will be also uploaded to the Inverse Problems YouTube channel: https://www.youtube.com/channel/UCqSbbWIqt9ZhWbAlJgEOGZg

 

Please pay extra attention to the amazing short film by Aku Seppänen!

 

The Inverse Days week also included a special session “Women in FIPS”, and the annual meeting of the Finnish Inverse Problems Society.

 

The Finnish Inverse Prize, annual award of the Finnish Inverse Problems Society, was awarded to Jesse Railo who defended his PhD thesis “Geodesic Tomography Problems on Riemannian Manifold” with distinction at the University of Jyväskylä in 2019. In addition to University of Jyväskylä, Jesse has also worked at U. Tampere, U. Helsinki and the Finnish Meteorological Institute, and is now a Postdoctoral scientist at the ETH Zürich. Congratulations Jesse!

 

The scientific committee of the conference was

·      Tatiana Bubba (chair)

·      Janne Hakkarainen

·      Marko Laine

·      Matti Lassas

·      Samuli Siltanen

·      Johanna Tamminen

 

Special thanks to Antti Mikkonen for his work on putting together the Virtual Lab tours, Rashmi Murthy for taking care excellently of the technical arrangements for the conference and Lauri Ylinen for his work on the website. A job well done!

 

“I love math” logo: Joe Volzer

 

Conference website: https://www.fips.fi/id2020.php

Wednesday, October 21, 2020

Sum of three cubes re-revisited

Abstract

Computer assisted searches of solutions of the Diophantine equation $x^3 +y^3 +z^3 = k$ have been made since 1954. Thanks to some intelligent people, modern super computing facilities and a YouTube channel, we finally now 66 years later have solutions for all $k < 100$. Here we report an interesting solution when $k=2^3$.

Keywords: Sum of three cubes, Diophantine equation, taxicab number.

Introduction

In 2015, on a Numberphile video “The uncracked problem with 33” Prof. Tim Browning discussed the Diophantine equation \begin{equation*} x^3+y^3+z^3=k \end{equation*} that has interested mathematicians a quite some time now. As explained in the video, it is know that this equation has no integer solutions for $k \equiv 4$ or $5\,(\mathrm{mod}\,9)$, i.e., $4,5,13,14, 22, 23, \ldots$ For other values of $k$, it has been conjectured that there are infinitely many solutions [1]. In 1953, for $k=3$, Prof. Louis J. Mordell now famously wrote [2]: “I do not know anything about the integer solutions of $x^3+y^3+z^3=3$ beyond the existence of the four sets $(1, 1, 1)$, $(4, 4, -5)$, etc.; and it must be very difficult indeed to find out anything about any other solutions.” This led to the first computer assisted search for $k < 100$ in 1954 [3].

Since those days, for values $k <1\,000$, several searches have been made and more effective algorithms proposed. For example, in 2007, Andreas-Stephan Elsenhans and Jörg Jahnel searched systematically for solutions where the positive integer $k < 100$ is neither a cube nor twice a cube and $|x|,|y|,|z| k < 10^{14}$ [4]. These values “New sums of three cubes” are tabulated here. At this point, they reported 14 unsolved values below $1\,000$: 33, 42, 74,114, 165, 390, 579, 627, 633, 732, 795, 906, 921, and 975.

In 2016, motivated by the original Numberphile video, Sander Huisman extended the search of Elsenhans and Jahnel up to $10^{15}$ [5]. In his report “Newer sums of three cubes,” he found 966 new solutions. The most exciting one was the discovery of the first solution for $k = 74$: \begin{equation*} 74 = (-284650292555885)^3 + 66229832190556^3 + 283450105697727^3. \end{equation*} This result was discussed by Browning on a follow-up Numberphile video “74 is cracked.

It was this follow-up video that got mathematician Andrew Booker hooked. In 2019, he proposed a new algorithm [6] and searched solutions for unsolved values below $1\,000$. He found the first known solution for $k = 33$: \begin{equation*} 33 = 8866128975287528^3 +(-8778405442862239)^3 +(-2736111468807040)^3. \end{equation*} This results was, of course, reported on a Numberphile video “42 is the new 33” indicating that after the discoveries by Huisman and Booker, the only unsolved value below 100 was $k=42$. In his paper, Booker also searched for solutions for $k = 3$, addressing a question of Prof. Mordell, but found none. He also reported the first known solution for $k = 795$: \begin{equation*} 795 = (14219049725358227)^3+(14197965759741571)^3+(2337348783323923)^3. \end{equation*} At this point, also I got interested.

Methodology

Albeit having a PhD degree in applied mathematics, I don't have any formal education on number theory, let alone, have no experience of computer searches of this type. It was quite obvious, that an exhaustive search for the range $10^{16}$ was out of my reach. The only way I thought I could participate was to randomly sample large values of $x$, $y$ and $z$ and then test if the sum of their cubes gives a small solution, say less than $1\,000$. With a little bit of online research, I wrote the Python code used in this study.

import random

for x in range(10**13):
    a = random.randint(10**14,10**18)
    b = random.randint(10**14,10**18)
    c = random.randint(10**14,10**18)

    if a > b:
        if a > c:
            val = a**3 -b**3-c**3
        else:
            val = c**3 -b**3-a**3
    elif b > c:
        val = b**3 -a**3-c**3
    else:
        val = c**3-a**3-b**3

    if abs(val) < 1000:
        print(a)
        print(b)
        print(c)
        print(val)
        Outa = open("a.txt","w")
        Outb = open("b.txt","w")
        Outc = open("c.txt","w")
        Outval = open("val.txt","w")
        Outa.write(str(a))
        Outa.close()
        Outb.write(str(b))
        Outb.close()
        Outc.write(str(c))
        Outc.close()
        Outval.write(str(val))
        Outval.close()
        break
    elif (x % 10**6) == 0:
        print(x)
                       
I knew that I would need to sample many many times in order to find a new solution. As noted by Huisman [5], the number of solutions for each decade up to search bounds $B$ in the range from $10^2$ to $10^{14}$ have been roughly $1\,000$ solutions per decade, which is in accordance with [1]. This gave me some initial hope, but I soon realized, after discovering a little error in my calculations, that the probability of finding a new solution was virtually non-existent. I still decided to give it a go.

Results

On 10 July 2019 I set a computer search for finding a new solution. At the meantime, Andrew Booker had teamed up with Andrew Sutherland and with computer resources from Charity Engine they were searching for new solutions, too. On September 2019, while I was waiting my first solution to appear, they announced a solution for $k=42$: \begin{equation*} (-80538738812075974)^3 + 80435758145817515^3 + 12602123297335631^3=42, \end{equation*} and again, a new Numberphile video “The Mystery of 42 is Solved” was made. This marked the end of the journey that was started in 1954, as we now had solutions for all $k < 100$. This left the original question of Mordell still unanswered, but three weeks later, they also found: \begin{equation*} 569936821221962380720^3 + (-569936821113563493509)^3 + (-472715493453327032)^3 = 3, \end{equation*} and yet again a new Numberphile video was made “3 as the sum of the 3 cubes.” Booker and Sutherland report these results and two other new solutions on a preprint [7].

I left my computer search to go on for some months, but at some point the computer was rebooted or I stopped the script for running, I don't quite remember anymore which one was it. Anyways, no new solutions were found.

On 15 October 2020, during a Finnish Autumn school break, I decided to revisit this question. It was pretty obvious again, that the original code was not going to give me a solution, so I decided to check what kind of solution I would get if I would limit the search to $10^4$ and would also be satisfied with a solution of the same size. After running the script, it printed the numbers $7\,576, 4\,112, 7\,960$ and $4\,096$ which I arranged to a solution \begin{equation*} -7576^3-4112^3+7960^3 = 4096. \end{equation*} I immediately recognized $4\,096$ as a power of 2, i.e, $2^{12}$, so I decided to check the prime factors of the other numbers, too. I found that $7\,576 = 2^3 \times 947$, $4\,112 = 2^4 \times 257$ and $7\,960 = 2^3 \times 5 \times 199$, so the original solution given by the algorithm could be re-arranged to \begin{equation*} -947^3-514^3+995^3 = 2^3. \end{equation*} I found this solution quite fascinating, as also $k=2^3$ is a cube and the other numbers are relatively large. I decided to right away communicate this mesmerizing solution to the mathematical community via Twitter. At the time of writing this text, a day later, this tweet has already gotten zero likes and retweets combined.

The question that rises with $k$ being a cube is: Are there any others? At first glance, it would seem that requiring $k$ being a cube would make things more complicated, but this is not the case. For example, if we think about it a little bit (and even if we don't), the equations \begin{equation*} a^3+0^3+0^3 = a^3 \end{equation*} and \begin{equation*} a^3+a^3+0^3 = 2 a^3 \end{equation*} always give solutions. This is quite likely the reason why cubes and twice the cubes were not included in the original dataset of Elsenhans and Jahnel: here.

Moreover, if we read the article “Diophantine Equation--3rd Powers” on Wolfram MathWorld, we find that the general rational solution to $x^3+y^3+z^3=k^3$ exists. For example, famously, Plato's number $216 = 6^3$ is the sum of the cubes for the Pythagorean triple $(3, 4, 5)$ \begin{equation*} 3^3 + 4^3 + 5^3 = 6^3 \end{equation*} and is also the case $a=1, b=0$ of Ramanujan's formula: \begin{equation*} (3a^2+5ab-5b^2)^3 + (4a^2-4ab+6b^2)^3 + (5a^2-5ab-3b^2)^3 = (6a^2-4ab+4b^2)^3. \end{equation*} In fact, when $k$ is a cube the question is related to the famous story of Ramanujan and G. H. Hardy, and how the taxicab number $1\,729$ is the smallest integer that can be expressed as a sum of two positive integer cubes in two distinct ways: \begin{equation*} 1729 = 1^3 + 12^3 = 9^3 + 10^3. \end{equation*} If we allow also negative numbers, we can re-arrange the earlier example with Plato's number and have even smaller sum: \begin{equation*} 91 = 6^3 - 5^3 = 4^3 + 3^3. \end{equation*} The smallest sum that our re-arranged solution would give is the following: \begin{equation*} 135\,796\,752 = 995^3-947^3 = 514^3 + 2^3. \end{equation*} On the other hand, Euler conjectured that there were no positive integral solutions to \begin{equation*} a^4 + b^4 + c^4 = d^4. \end{equation*} In 1988, the smallest possible counterexample was found [8]: \begin{equation*} 95800^4 + 217519^4 + 414560^4 = 422481^4. \end{equation*}

Acknowledgements

Most of my knowledge on this topic comes from the series of Numberphile videos “Sums of three cubes.” Do yourself a favor and go find the originals.

References

[1] D. R. Heath-Brown, The density of zeros of forms for which weak approximation fails, Math. Comp. 59 (1992), no. 200, 613–623.
[2] L. J. Mordell, On the integer solutions of the equation x2 + y2 + z2 + 2xyz = n, J. London Math. Soc. 28 (1953), 500–510.
[3] J. C. P. Miller and M. F. C. Woollett, Solutions of the Diophantine equation x3 +y3 +z3 = k, J. London Math. Soc. 30 (1955), 101–110.
[4] Andreas-Stephan Elsenhans and J ̈org Jahnel, New sums of three cubes, Math. Comp. 78 (2009), no. 266, 1227–1230.
[5] Sander G. Huisman, Newer sums of three cubes, arXiv:1604.07746, 2016.
[6] A. R. Booker, Cracking the problem with 33, Res. Number Theory 5 (2019), no. 3, 5:26.
[7] Andrew R. Booker and Andrew V. Sutherland, On a question of Mordell, arXiv:2007.01209, 2020.
[8] N. D. Elkies, On A4 + B4 + C4 = D4, Math. of Comp. 51 (1988), 825–835.