scholarly journals Updated SO<sub>2</sub> emission estimates over China using OMI/Aura observations

2018 ◽  
Vol 11 (3) ◽  
pp. 1817-1832 ◽  
Author(s):  
Maria Elissavet Koukouli ◽  
Nicolas Theys ◽  
Jieying Ding ◽  
Irene Zyrichidou ◽  
Bas Mijling ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Satellite Observations ◽  
Ozone Monitoring Instrument ◽  
So2 Emissions ◽  
Transport Modelling ◽  
So2 Emission ◽  
Bottom Up ◽  
Beijing Area ◽  
Entire Domain ◽  
Particulate Matter Emissions

Abstract. The main aim of this paper is to update existing sulfur dioxide (SO2) emission inventories over China using modern inversion techniques, state-of-the-art chemistry transport modelling (CTM) and satellite observations of SO2. Within the framework of the EU Seventh Framework Programme (FP7) MarcoPolo (Monitoring and Assessment of Regional air quality in China using space Observations) project, a new SO2 emission inventory over China was calculated using the CHIMERE v2013b CTM simulations, 10 years of Ozone Monitoring Instrument (OMI)/Aura total SO2 columns and the pre-existing Multi-resolution Emission Inventory for China (MEIC v1.2). It is shown that including satellite observations in the calculations increases the current bottom-up MEIC inventory emissions for the entire domain studied (15–55° N, 102–132° E) from 26.30 to 32.60 Tg annum−1, with positive updates which are stronger in winter ( ∼  36 % increase). New source areas were identified in the southwest (25–35° N, 100–110° E) as well as in the northeast (40–50° N, 120–130° E) of the domain studied as high SO2 levels were observed by OMI, resulting in increased emissions in the a posteriori inventory that do not appear in the original MEIC v1.2 dataset. Comparisons with the independent Emissions Database for Global Atmospheric Research, EDGAR v4.3.1, show a satisfying agreement since the EDGAR 2010 bottom-up database provides 33.30 Tg annum−1 of SO2 emissions. When studying the entire OMI/Aura time period (2005 to 2015), it was shown that the SO2 emissions remain nearly constant before the year 2010, with a drift of −0.51 ± 0.38 Tg annum−1, and show a statistically significant decline after the year 2010 of −1.64 ± 0.37 Tg annum−1 for the entire domain. Similar findings were obtained when focusing on the greater Beijing area (30–40° N, 110–120° E) with pre-2010 drifts of −0.17 ± 0.14 and post-2010 drifts of −0.47 ± 0.12 Tg annum−1. The new SO2 emission inventory is publicly available and forms part of the official EU MarcoPolo emission inventory over China, which also includes updated NOx, volatile organic compounds and particulate matter emissions.

scholarly journals Updated SO<sub>2</sub> emission estimates over China using OMI/Aura observations

2017 ◽  
Author(s):  
Maria-Elissavet Koukouli ◽  
Nicolas Theys ◽  
Jieying Ding ◽  
Irene Zyrichidou ◽  
Bas Mijling ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Satellite Observations ◽  
So2 Emissions ◽  
Transport Modelling ◽  
So2 Emission ◽  
Bottom Up ◽  
Beijing Area ◽  
Entire Domain ◽  
North East ◽  
The North

Abstract. The main aim of this paper is to update existing sulphur dioxide (SO2), emission inventories over China using novel inversion techniques, state-of-the-art chemistry transport modelling (CTM), and satellite observations of SO2. Within the framework of the EU FP7 Monitoring and Assessment of Regional air quality in China using space Observations, MarcoPolo project, a new SO2 emission inventory over China was calculated using the CHIMERE v2013b CTM simulations, ten years of OMI/Aura total SO2 columns and the pre-existing Multi-resolution Emission Inventory for China (MEIC v1.2). It is shown that including satellite observations in the calculations increases the current bottom-up MEIC inventory emissions for the entire domain studied [102° to 132° E and 15° to 55° N] from 26.30 Tg/annum to 32.60 Tg/annum, with positive updates which are stronger in winter [~ 36 % increase]. New source areas where identified in the South West [25–35° N and 100–110° E] as well as in the North East [40–50° N and 120–130° E] of the domain studied as high SO2 levels were observed by OMI, resulting in increased emissions in the aposteriori inventory that do not appear in the original MEIC v1.2 dataset. Comparisons with the independent Emissions Database for Global Atmospheric Research, EDGAR v4.3.1, show a satisfying agreement since the EDGAR 2010 bottom-up database provides 33.30 Tg/annum of SO2 emissions. When studying the entire OMI/Aura time period [2005 to 2015 inclusive], it was shown that the SO2 emissions remain nearly constant before year 2010 with a drift of −0.51 ± 0.38 Tg/annum and show a statistically significant decline after year 2010 of −1.64 ± 0.37 Tg/Annum for the entire domain. Similar findings were obtained when focusing on the Greater Beijing Area [110° to 120° E and 30° to 40° N] with pre-2010 drifts of −0.17 ± 0.14 and post-2010 drifts of −0.47 ± 0.12 Tg/annum. The new SO2 emission inventory is publicly available and forms part of the official EU MarcoPolo emission inventory over China which also includes updated NOx, VOCs and PM emissions.

scholarly journals A new global anthropogenic SO<sub>2</sub> emission inventory for the last decade: a mosaic of satellite-derived and bottom-up emissions

2018 ◽  
Vol 18 (22) ◽  
pp. 16571-16586 ◽  
Author(s):  
Fei Liu ◽  
Sungyeon Choi ◽  
Can Li ◽  
Vitali E. Fioletov ◽  
Chris A. McLinden ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Correlation Coefficients ◽  
In Situ Measurements ◽  
Point Sources ◽  
Ozone Monitoring Instrument ◽  
So2 Emissions ◽  
Bottom Up ◽  
Earth Observing System ◽  
The Us

Abstract. Sulfur dioxide (SO2) measurements from the Ozone Monitoring Instrument (OMI) satellite sensor have been used to detect emissions from large point sources. Emissions from over 400 sources have been quantified individually based on OMI observations, accounting for about a half of total reported anthropogenic SO2 emissions. Here we report a newly developed emission inventory, OMI-HTAP, by combining these OMI-based emission estimates and the conventional bottom-up inventory, HTAP, for smaller sources that OMI is not able to detect. OMI-HTAP includes emissions from OMI-detected sources that are not captured in previous leading bottom-up inventories, enabling more accurate emission estimates for regions with such missing sources. In addition, our approach offers the possibility of rapid updates to emissions from large point sources that can be detected by satellites. Our methodology applied to OMI-HTAP can also be used to merge improved satellite-derived estimates with other multi-year bottom-up inventories, which may further improve the accuracy of the emission trends. OMI-HTAP SO2 emissions estimates for Persian Gulf, Mexico, and Russia are 59 %, 65 %, and 56 % larger than HTAP estimates in 2010, respectively. We have evaluated the OMI-HTAP inventory by performing simulations with the Goddard Earth Observing System version 5 (GEOS-5) model. The GEOS-5 simulated SO2 concentrations driven by both HTAP and OMI-HTAP were compared against in situ measurements. We focus for the validation on 2010 for which HTAP is most valid and for which a relatively large number of in situ measurements are available. Results show that the OMI-HTAP inventory improves the agreement between the model and observations, in particular over the US, with the normalized mean bias decreasing from 0.41 (HTAP) to −0.03 (OMI-HTAP) for 2010. Simulations with the OMI-HTAP inventory capture the worldwide major trends of large anthropogenic SO2 emissions that are observed with OMI. Correlation coefficients of the observed and modeled surface SO2 in 2014 increase from 0.16 (HTAP) to 0.59 (OMI-HTAP) and the normalized mean bias dropped from 0.29 (HTAP) to 0.05 (OMI-HTAP), when we updated 2010 HTAP emissions with 2014 OMI-HTAP emissions in the model.

scholarly journals A new global anthropogenic SO<sub>2</sub> emission inventory for the last decade: A mosaic of satellite-derived and bottom-up emissions

2018 ◽  
Author(s):  
Fei Liu ◽  
Sungyeon Choi ◽  
Can Li ◽  
Vitali E. Fioletov ◽  
Chris A. McLinden ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Correlation Coefficients ◽  
In Situ Measurements ◽  
Point Sources ◽  
Ozone Monitoring Instrument ◽  
So2 Emissions ◽  
Bottom Up ◽  
Earth Observing System ◽  
The Us

Abstract. Sulfur dioxide (SO2) measurements from the Ozone Monitoring Instrument (OMI) satellite sensor have been used to detect emissions from large point sources. Emissions from over 400 sources have been quantified individually based on OMI observations, accounting for about a half of total reported anthropogenic SO2 emissions. Here we report a newly developed emission inventory, OMI-HTAP, by combining these OMI-based emission estimates and the conventional bottom-up inventory, HTAP, for smaller sources that OMI is not able to detect. OMI-HTAP includes emissions from OMI-detected sources that are not captured in previous leading bottom-up inventories, enabling more accurate emission estimates for regions with such missing sources. OMI-HTAP SO2 emissions estimates for Persian Gulf, Mexico, and Russia are 59 %, 65 %, and 56 % higher than HTAP estimates, respectively, in year 2010. We have evaluated the OMI-HTAP inventory by performing simulations with the Goddard Earth Observing System version 5 (GEOS-5) model. The GEOS-5 simulated SO2 concentrations driven by both HTAP and OMI-HTAP were compared against in situ measurements. We focus the validation on year 2010 for which HTAP is most valid and a relatively large number of in situ measurements are available. Results show that the OMI-HTAP inventory improves the model agreement with observations, in particular over the US, with the normalized mean bias decreasing from 0.41 (HTAP) to −0.03 (OMI-HTAP) for year 2010. Additionally, our approach offers the possibility of rapid updates to emissions from large point sources that can be detected by satellites. Simulations with the OMI-HTAP inventory capture the worldwide major trends of large anthropogenic SO2 emissions that are observed with OMI. For example, correlation coefficients of the observed and modelled surface SO2 in 2014 increase from 0.16 (HTAP) to 0.59 (OMI-HTAP) and the normalized mean bias dropped from 0.29 (HTAP) to 0.05 (OMI-HTAP), when we updated 2010 HTAP emissions with 2014 OMI-HTAP emissions in the model. Our methodology applied to OMI-HTAP can also be used to merge improved satellite-derived estimates with other multi-year bottom-up inventories, which may further improve the accuracy of the emission trends.

scholarly journals Estimating European volatile organic compound emissions using satellite observations of formaldehyde from the Ozone Monitoring Instrument

2010 ◽  
Vol 10 (23) ◽  
pp. 11501-11517 ◽  
Author(s):  
G. Curci ◽  
P. I. Palmer ◽  
T. P. Kurosu ◽  
K. Chance ◽  
G. Visconti
Keyword(s):  
Satellite Observations ◽  
Atmospheric Composition ◽  
Ozone Monitoring Instrument ◽  
Top Down ◽  
Bottom Up ◽  
Voc Emissions ◽  
The Balkans ◽  
Monitoring Instrument ◽  
Volatile Organic ◽  
Ozone Monitoring

Abstract. Emission of non-methane Volatile Organic Compounds (VOCs) to the atmosphere stems from biogenic and human activities, and their estimation is difficult because of the many and not fully understood processes involved. In order to narrow down the uncertainty related to VOC emissions, which negatively reflects on our ability to simulate the atmospheric composition, we exploit satellite observations of formaldehyde (HCHO), an ubiquitous oxidation product of most VOCs, focusing on Europe. HCHO column observations from the Ozone Monitoring Instrument (OMI) reveal a marked seasonal cycle with a summer maximum and winter minimum. In summer, the oxidation of methane and other long-lived VOCs supply a slowly varying background HCHO column, while HCHO variability is dominated by most reactive VOC, primarily biogenic isoprene followed in importance by biogenic terpenes and anthropogenic VOCs. The chemistry-transport model CHIMERE qualitatively reproduces the temporal and spatial features of the observed HCHO column, but display regional biases which are attributed mainly to incorrect biogenic VOC emissions, calculated with the Model of Emissions of Gases and Aerosol from Nature (MEGAN) algorithm. These "bottom-up" or a-priori emissions are corrected through a Bayesian inversion of the OMI HCHO observations. Resulting "top-down" or a-posteriori isoprene emissions are lower than "bottom-up" by 40% over the Balkans and by 20% over Southern Germany, and higher by 20% over Iberian Peninsula, Greece and Italy. We conclude that OMI satellite observations of HCHO can provide a quantitative "top-down" constraint on the European "bottom-up" VOC inventories.

scholarly journals Evaluation of OMI operational standard NO<sub>2</sub> column retrievals using in situ and surface-based NO<sub>2</sub> observations

2014 ◽  
Vol 14 (10) ◽  
pp. 14519-14573 ◽  
Author(s):  
L. N. Lamsal ◽  
N. A. Krotkov ◽  
E. A. Celarier ◽  
W. H. Swartz ◽  
K. E. Pickering ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Transport Model ◽  
In Situ Measurements ◽  
Nox Emission ◽  
Data Sets ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Bottom Up ◽  
Tropospheric No2

Abstract. We assess the standard operational nitrogen dioxide (NO2) data product (OMNO2, version 2.1) retrieved from the Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite using a combination of aircraft and surface in situ measurements as well as ground-based column measurements at several locations and a bottom-up NOx emission inventory over the continental US. Despite considerable sampling differences, NO2 vertical column densities from OMI are modestly correlated (r = 0.3–0.8) with in situ measurements of tropospheric NO2 from aircraft, ground-based observations of NO2 columns from MAX-DOAS and Pandora instruments, in situ surface NO2 measurements from photolytic converter instruments, and a bottom-up NOx emission inventory. Overall, OMI retrievals tend to be lower in urban regions and higher in remote areas, but generally agree with other measurements to within ± 20%. No consistent seasonal bias is evident. Contrasting results between different data sets reveal complexities behind NO2 validation. Monthly mean vertical NO2 profile shapes from the Global Modeling Initiative (GMI) chemistry-transport model (CTM) used in the OMI retrievals are highly consistent with in situ aircraft measurements, but these measured profiles exhibit considerable day-to-day variation, affecting the retrieved daily NO2 columns by up to 40%. This assessment of OMI tropospheric NO2 columns, together with the comparison of OMI-retrieved and model-simulated NO2 columns, could offer diagnostic evaluation of the model.

Improved estimation of volcanic SO2 emissions from satellite observations and Lagrangian transport simulations: The 2019 Raikoke eruption case study

2021 ◽  
Author(s):  
Zhongyin Cai ◽  
Sabine Grießbach ◽  
Lars Hoffmann
Keyword(s):  
Emission Rate ◽  
Transport Model ◽  
Volcanic Eruptions ◽  
Satellite Observations ◽  
So2 Emissions ◽  
So2 Emission ◽  
Lagrangian Transport ◽  
Trajectory Approach ◽  
Volcanic Aerosols

&lt;p&gt;Monitoring and modeling of volcanic aerosols is important for understanding the influence of volcanic activity on climate. Here, we applied the Lagrangian transport model Massive-Parallel Trajectory Calculations (MPTRAC) to estimate the total injected SO2 by the stratosphere reaching eruption of the Raikoke volcano (48N, 153E) in June 2019 and its subsequent transport. We used SO2 observations from the AIRS and TROPOMI satellite instruments together with a backward trajectory approach to estimate the altitude-resolved SO2 emission timeseries. Then we applied a scaling factor to the initial estimate of the SO2 mass and added an exponential decay to simulate the time evolution of the total SO2 mass. By comparing the estimated SO2 mass and the observed mass from TROPOMI, we show that the volcano injected 2.1&amp;#177;0.2 Tg SO2 and the e-folding lifetime of the SO2 was about 13~17 days. Further, we compared simulations that were initialized by AIRS and TROPOMI satellite observations with a constant SO2 emission rate. The results show that the model captures the SO2 distributions in the first ~10 days after the eruption. The simulations using AIRS nighttime and TROPOMI measurements show comparable results and model skills which outperform the simulation using a constant emission rate. Our study demonstrates the potential of using combined satellite observations and transport simulations to further improve SO2 time- and height-resolved emission estimates of volcanic eruptions.&lt;/p&gt;

scholarly journals Estimating European volatile organic compound emissions using satellite observations of formaldehyde from the Ozone Monitoring Instrument

2010 ◽  
Vol 10 (8) ◽  
pp. 19697-19736 ◽  
Author(s):  
G. Curci ◽  
P. I. Palmer ◽  
T. P. Kurosu ◽  
K. Chance ◽  
G. Visconti
Keyword(s):  
A Priori ◽  
Satellite Observations ◽  
Ozone Monitoring Instrument ◽  
Top Down ◽  
Bottom Up ◽  
Voc Emissions ◽  
The Balkans ◽  
Monitoring Instrument ◽  
Volatile Organic ◽  
Ozone Monitoring

Abstract. Emission of non-methane Volatile Organic Compounds (VOCs) to the atmosphere stems from biogenic and human activities, and their estimation is difficult because of the many and not fully understood processes involved. In order to narrow down the uncertainty related to VOC emissions, which negatively reflects on our ability to simulate the atmospheric composition, we exploit satellite observations of formaldehyde (HCHO), an ubiquitous oxidation product of most VOCs, focusing on Europe. HCHO column observations from the Ozone Monitoring Instrument (OMI) reveal a marked seasonal cycle with a summer maximum and winter minimum. In summer, the oxidation of methane and other long-lived VOCs supply a slowly varying background HCHO column, while HCHO variability is dominated by most reactive VOC, primarily biogenic isoprene followed in importance by biogenic terpenes and anthropogenic VOCs. The chemistry-transport model CHIMERE qualitatively reproduces the temporal and spatial features of the observed HCHO column, but display regional biases which are attributed mainly to incorrect biogenic VOC emissions, calculated with the Model of Emissions of Gases and Aerosol from Nature (MEGAN) algorithm. These "bottom-up" or a-priori emissions are corrected through a Bayesian inversion of the OMI HCHO observations. Resulting "top-down" or a-posteriori isoprene emissions are lower than "bottom-up" by 40% over the Balkans and by 20% over Southern Germany, and higher by 20% over Iberian Peninsula, Greece and Italy. The inversion is shown to be robust against assumptions on the a-priori and the inversion parameters. We conclude that OMI satellite observations of HCHO can provide a quantitative "top-down" constraint on the European "bottom-up" VOC inventories.

scholarly journals Evaluation of OMI operational standard NO<sub>2</sub> column retrievals using in situ and surface-based NO<sub>2</sub> observations

2014 ◽  
Vol 14 (21) ◽  
pp. 11587-11609 ◽  
Author(s):  
L. N. Lamsal ◽  
N. A. Krotkov ◽  
E. A. Celarier ◽  
W. H. Swartz ◽  
K. E. Pickering ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Transport Model ◽  
In Situ Measurements ◽  
Nox Emission ◽  
Data Sets ◽  
Ozone Monitoring Instrument ◽  
Validation Data ◽  
Bottom Up ◽  
Tropospheric No2

Abstract. We assess the standard operational nitrogen dioxide (NO2) data product (OMNO2, version 2.1) retrieved from the Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite using a combination of aircraft and surface in~situ measurements as well as ground-based column measurements at several locations and a bottom-up NOx emission inventory over the continental US. Despite considerable sampling differences, NO2 vertical column densities from OMI are modestly correlated (r = 0.3–0.8) with in situ measurements of tropospheric NO2 from aircraft, ground-based observations of NO2 columns from MAX-DOAS and Pandora instruments, in situ surface NO2 measurements from photolytic converter instruments, and a bottom-up NOx emission inventory. Overall, OMI retrievals tend to be lower in urban regions and higher in remote areas, but generally agree with other measurements to within ± 20%. No consistent seasonal bias is evident. Contrasting results between different data sets reveal complexities behind NO2 validation. Since validation data sets are scarce and are limited in space and time, validation of the global product is still limited in scope by spatial and temporal coverage and retrieval conditions. Monthly mean vertical NO2 profile shapes from the Global Modeling Initiative (GMI) chemistry-transport model (CTM) used in the OMI retrievals are highly consistent with in situ aircraft measurements, but these measured profiles exhibit considerable day-to-day variation, affecting the retrieved daily NO2 columns by up to 40%. This assessment of OMI tropospheric NO2 columns, together with the comparison of OMI-retrieved and model-simulated NO2 columns, could offer diagnostic evaluation of the model.

scholarly journals A Sulfur Dioxide Covariance-Based Retrieval Algorithm (COBRA): application to TROPOMI reveals new emission sources

2021 ◽  
Author(s):  
Nicolas Theys ◽  
Vitali Fioletov ◽  
Can Li ◽  
Isabelle De Smedt ◽  
Christophe Lerot ◽  
...  
Keyword(s):  
Sulfur Dioxide ◽  
Principal Component ◽  
Great Sensitivity ◽  
Detection Methods ◽  
Retrieval Algorithm ◽  
Ozone Monitoring Instrument ◽  
So2 Emissions ◽  
Data Set ◽  
So2 Emission ◽  
Monitoring Instrument

Abstract. Sensitive and accurate detection of sulfur dioxide (SO2) from space is important for monitoring and estimating global sulfur emissions. Inspired by detection methods applied in the thermal infrared, we present here a new scheme to retrieve SO2 columns from satellite observations of ultraviolet back-scattered radiances. The retrieval is based on a measurement error covariance matrix to fully represent the SO2-free radiance variability, so that the SO2 slant column density is the only retrieved parameter of the algorithm. We demonstrate this approach, named COBRA, on measurements from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor (S-5P) satellite. We show that the method reduces significantly both the noise and biases present in the current TROPOMI operational DOAS SO2 retrievals. The performance of this technique is also benchmarked against that of the Principal Component Algorithm (PCA) approach. We find that the quality of the data is similar and even slightly better with the proposed COBRA approach. The ability of the algorithm to retrieve SO2 accurately is also further supported by comparison with ground-based observations. We illustrate the great sensitivity of the method with a high-resolution global SO2 map, considering two and a half years of TROPOMI data. In addition to the known sources, we detect many new SO2 emission hotspots worldwide. For the largest sources, we use the COBRA data to estimate SO2 emission rates. Results are comparable to other recently published TROPOMI-based SO2 emissions estimates, but the associated uncertainties are significantly lower than with the operational data. Next, for a limited number of weak sources, we demonstrate the potential of our data for quantifying SO2 emissions with a detection limit of about 8 kt yr-1, a factor of 4 better than the emissions derived from the Ozone Monitoring Instrument (OMI). We anticipate that the systematic use of our TROPOMI COBRA SO2 column data set at a global scale will allow identifying and quantifying missing sources, and help improving SO2 emission inventories.

scholarly journals Reduction in air pollution using the ‘basa njengo magogo’ method and the applicability to low-smoke fuels

2009 ◽  
Vol 20 (3) ◽  
pp. 3-10 ◽  
Author(s):  
Lukas J. Le Roux ◽  
Mark Zunckel ◽  
Shirley McCormick
Keyword(s):  
Cost Savings ◽  
Particulate Emissions ◽  
Volatile Content ◽  
So2 Emissions ◽  
So2 Emission ◽  
Bottom Up ◽  
Cooking Temperature ◽  
Coal Fires ◽  
Orange Farm ◽  
Fire Ignition

The then Department of Minerals and Energy (DME) piloted the top-down Basa njengo Magogo alternative fire ignition method at Orange Farm dur-ing the winter of 2003. In total, 76% of households reported less smoke in their homes, while 67%reported less smoke in the streets after one month of using the method (Palmer Development Consulting, 2003). Work by Nova (Schoonraad & Swanepoel, 2003) in eMbalenhle (actual environ-mental tests) indicated up to a 60% reduction in smoke compared with the conventional method of bottom-up ignition. To support the findings of the environmental studies, the CSIR were appointed by the DME to conduct an experiment under con-trolled laboratory conditions to gather quantitative data on the reduction in particulate emissions asso-ciated with the Basa njengo Magogo method of lighting coal fires. The CSIR was further contracted to assess whether the Basa njengo Magogo technol-ogy was viable with low-smoke fuels.The experiment was conducted using traditional D-Grade coal in both the conventional bottom-up and the Basa njengo Magogo ignition techniques. Three low volatile fuels were also assessed using the Basa njengo Magogo method namely:•    Anthracite (volatile content of 10.6%)•    Anthracite (volatile content of 12%)•    Low volatile coal (volatile content of 20.8%), from Slater Coal in Dundee.All four fuels using the Basa njengo Magogo method recorded similar times of between 11 and 13 minutes from ignition to the fires reaching cook-ing temperature. The bottom-up fire for conven-tional D-Grade coal reached cooking temperature after 55 minutes.Particulate emissions from all the Basa njengo Magogo fires were similar and up to 92% lower in particulate emissions than that of the D-Grade coal in the bottom-up fire. SO2 emissions from the two D-Grade coal fires were the lowest and were identical. The highest SO2 emission resulted from the low volatile coal. The method of lighting the fire does not have a significant effect on the SO2 emissions. The Basa njengo Magogo method of ignition uses approximately 1 kg less coal to reach cooking temperature than the traditional bottom–up method. At a cost of approximately R1.00 per kilo-gram of coal, this translates into a cost savings of approximately R30 per month.

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