Elevated Black Carbon Concentrations and Atmospheric Pollution around Singrauli Coal-Fired Thermal Power Plants (India) Using Ground and Satellite Data
Abstract:The tropospheric NO2 concentration from OMI AURA always shows high concentrations of NO2 at a few locations in India, one of the high concentrations of NO2 hotspots is associated with the locations of seven coal-fired Thermal Power plants (TPPs) in Singrauli. Emissions from TPPs are among the major sources of black carbon (BC) soot in the atmosphere. Knowledge of BC emissions from TPPs is important in characterizing regional carbonaceous particulate emissions, understanding the fog/haze/smog formation, evaluat… Show more
“… 32 , 33 Furthermore, BC concentrations reaching as high as 200 μg m –3 have been reported in transit regions in the vicinity of such thermal power plants. 34 In fact, the coupling between the BC concentrations and air mass origin, visualized using CWT maps ( Supporting Information Figure S3.c ), shows that BC at BCOB (although an order lower than expected in the vicinity of power plants; Supporting Information Figure S4 ) mostly arrived from the IGP.…”
Section: Resultsmentioning
confidence: 90%
“…PI is known to have significant emissions from C 4 -plants during this period, 38 − 40 while the coal combustion sources are smaller compared to the IGP. 12 , 32 − 34 We therefore judge the MCMC 3,C4 scenario to be the most fitting for MCOH, also since this implies a smaller change in the biomass source class contributions (up to 10% increase of C 4 -biomass) relative to BCOB, compared to the massive change in fossil fuel source class contributions (up to 27% increase in coal; MCMC 3,coal ) needed to be consistent with the isotope data. This conclusion is further corroborated by the FEG simulations, which suggest that the main potential geographical emission regions for MCOH during the winter period were a combination of PI and the IGP ( Supporting Information Figure S11 ).…”
Black
carbon (BC) aerosols perturb climate and impoverish air quality/human
health—affecting ∼1.5 billion people in South Asia.
However, the lack of source-diagnostic observations of BC is hindering
the evaluation of uncertain bottom-up emission inventories (EIs) and
thereby also models/policies. Here, we present dual-isotope-based
(Δ
14
C/δ
13
C) fingerprinting of wintertime
BC at two receptor sites of the continental outflow. Our results show
a remarkable similarity in contributions of biomass and fossil combustion,
both from the site capturing the highly populated highly polluted
Indo-Gangetic Plain footprint (IGP; Δ
14
C-
f
biomass
= 50 ± 3%) and the second site
in the N. Indian Ocean representing a wider South Asian footprint
(52 ± 6%). Yet, both sites reflect distinct δ
13
C-fingerprints, indicating a distinguishable contribution of C
4
-biomass burning from peninsular India (PI). Tailored-model-predicted
season-averaged BC concentrations (700 ± 440 ng m
–3
) match observations (740 ± 250 ng m
–3
), however,
unveiling a systematically increasing model-observation bias (+19%
to −53%) through winter. Inclusion of BC from open burning
alone does not reconcile predictions (
f
biomass
= 44 ± 8%) with observations. Direct source-segregated comparison
reveals regional offsets in anthropogenic emission fluxes in EIs,
overestimated fossil-BC in the IGP, and underestimated biomass-BC
in PI, which contributes to the model-observation bias. This ground-truthing
pinpoints uncertainties in BC emission sources, which benefit both
climate/air-quality modeling and mitigation policies in South Asia.
“… 32 , 33 Furthermore, BC concentrations reaching as high as 200 μg m –3 have been reported in transit regions in the vicinity of such thermal power plants. 34 In fact, the coupling between the BC concentrations and air mass origin, visualized using CWT maps ( Supporting Information Figure S3.c ), shows that BC at BCOB (although an order lower than expected in the vicinity of power plants; Supporting Information Figure S4 ) mostly arrived from the IGP.…”
Section: Resultsmentioning
confidence: 90%
“…PI is known to have significant emissions from C 4 -plants during this period, 38 − 40 while the coal combustion sources are smaller compared to the IGP. 12 , 32 − 34 We therefore judge the MCMC 3,C4 scenario to be the most fitting for MCOH, also since this implies a smaller change in the biomass source class contributions (up to 10% increase of C 4 -biomass) relative to BCOB, compared to the massive change in fossil fuel source class contributions (up to 27% increase in coal; MCMC 3,coal ) needed to be consistent with the isotope data. This conclusion is further corroborated by the FEG simulations, which suggest that the main potential geographical emission regions for MCOH during the winter period were a combination of PI and the IGP ( Supporting Information Figure S11 ).…”
Black
carbon (BC) aerosols perturb climate and impoverish air quality/human
health—affecting ∼1.5 billion people in South Asia.
However, the lack of source-diagnostic observations of BC is hindering
the evaluation of uncertain bottom-up emission inventories (EIs) and
thereby also models/policies. Here, we present dual-isotope-based
(Δ
14
C/δ
13
C) fingerprinting of wintertime
BC at two receptor sites of the continental outflow. Our results show
a remarkable similarity in contributions of biomass and fossil combustion,
both from the site capturing the highly populated highly polluted
Indo-Gangetic Plain footprint (IGP; Δ
14
C-
f
biomass
= 50 ± 3%) and the second site
in the N. Indian Ocean representing a wider South Asian footprint
(52 ± 6%). Yet, both sites reflect distinct δ
13
C-fingerprints, indicating a distinguishable contribution of C
4
-biomass burning from peninsular India (PI). Tailored-model-predicted
season-averaged BC concentrations (700 ± 440 ng m
–3
) match observations (740 ± 250 ng m
–3
), however,
unveiling a systematically increasing model-observation bias (+19%
to −53%) through winter. Inclusion of BC from open burning
alone does not reconcile predictions (
f
biomass
= 44 ± 8%) with observations. Direct source-segregated comparison
reveals regional offsets in anthropogenic emission fluxes in EIs,
overestimated fossil-BC in the IGP, and underestimated biomass-BC
in PI, which contributes to the model-observation bias. This ground-truthing
pinpoints uncertainties in BC emission sources, which benefit both
climate/air-quality modeling and mitigation policies in South Asia.
“…Similar results were reported for thermal power plants in and around Delhi. A study conducted near thermal power plants of Singrauli concluded high BC concentration >200 µg/m 3 with peaks during early morning and evening hours, compared to the outside domain of the study region (Singh et al, 2018).…”
Abstract. The exponentially growing population and related anthropogenic activities have led to modifications in local environment. The change in local environment, evolving pattern of land use, concentrations of greenhouse gases and aerosols alter the energy balance of our climate system. This alteration in climate is leading to premature deaths worldwide. This study analyses the air quality of Singrauli region, Madhya Pradesh, India for the past 15 years. Otherwise known as Urjanchal “the energy capital” of India has been declared as critically polluted by CPCB. The study provides an updated list of thermal power plants in the study area and their emission effects on the local environment. The pollutants analyzed in the study are carbon dioxide, methane, nitrogen dioxide, Sulphur dioxide and particulate matter. Long term remotely sensed data was obtained from NASA Giovanni for past 15 years. Statistical analysis is used to characterize seasonal and annual variations of trace gases in the study area. The study concluded that Methane, Carbon dioxide, Nitrogen dioxide and Sulphur dioxide are on an increasing trend with an average rate of 1.03, 0.99, 2.15 and 1.09 annually. Secondly, Methane & SO2, PM2.5 & NO2, PM10 & NO2, CO2 & Methane and PM2.5 & PM10 have strong correlations with a 95% significance. Furthermore, Methane, SO2 and CO2 exhibit cyclic variation with change in season. The study also indicated that maximum aerosols present in the study area are a result of anthropogenic activities.
“…However, the marked reduction in surface NO 2 concentrations observed in Delhi and Ludhiana were not uniform across the IGP. Singrauli, a city with a number of large coal-fired power plants in its vicinity (Singh et al, 2018), recorded no significant reduction in surface NO 2 concentrations, i.e. the means over the period February 15-March 15 2020 and April 1-30 3030 were both 42 µg/m 3 , suggesting that the emissions from these plants were not reduced during the…”
Section: Climatological Surface No 2 Data Is Available For Delhi Backmentioning
The COVID-19 lockdown provides an opportunity to the assess the impact of air pollution from the Indo-Gangetic Plain on the Himalaya. Air pollutions levels in cities in the western Indo-Gangetic Plain experienced marked drops that coincided with the lockdown. Across the Indo-Gangetic Plain and Himalaya, there were reductions in air pollution in the west and increases in the east.
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