Quantifying the influence of agricultural fires in northwest India on urban air pollution in Delhi, India

Cusworth, Daniel H.; Mickley, Loretta J.; Sulprizio, Melissa P.; Liu, Tianjia; Marlier, Miriam E.; DeFries, Ruth; Guttikunda, Sarath; Gupta, Pawan

doi:10.1088/1748-9326/aab303

Cited by 170 publications

(114 citation statements)

References 34 publications

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“…FINN better resolves emissions from these small fires compared to some other fire emission data sets (Reddington et al, ). However, it is likely that emissions from agricultural fires are still underestimated in our study (Cusworth et al, ). Biomass burning emissions are largest in spring (MAM) and late autumn (ON), due to open crop residue burning postharvesting season, and smallest in the summer (JJA) (Venkataraman et al, ).…”

Section: Methodsmentioning

confidence: 81%

Current and Future Disease Burden From Ambient Ozone Exposure in India

et al. 2018

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Long‐term ambient ozone (O3) exposure is a risk factor for human health. We estimate the source‐specific disease burden associated with long‐term O3 exposure in India at high spatial resolution using updated risk functions from the American Cancer Society Cancer Prevention Study II. We estimate 374,000 (95UI: 140,000–554,000) annual premature mortalities using the updated risk function in India in 2015, 200% larger than estimates using the earlier American Cancer Society Cancer Prevention Study II risk function. We find that land transport emissions dominate the source contribution to this disease burden (35%), followed by emissions from power generation (23%). With no change in emissions by 2050, we estimate 1,126,000 (95UI: 421,000–1,667,000) annual premature mortalities, an increase of 200% relative to 2015 due to population aging and growth increasing the number of people susceptible to air pollution. We find that the International Energy Agency New Policy Scenario provides small changes (+1%) to this increasing disease burden from the demographic transition. Under the International Energy Agency Clean Air Scenario we estimate 791,000 (95UI: 202,000–1,336,000) annual premature mortalities in 2050, avoiding 335,000 annual premature mortalities (45% of the increase) compared to the scenario of no emission change. Our study highlights that critical public health benefits are possible with stringent emission reductions, despite population growth and aging increasing the attributable disease burden from O3 exposure even under such strong emission reductions. The disease burden attributable to ambient fine particulate matter exposure dominates that from ambient O3 exposure in the present day, while in the future, they may be similar in magnitude.

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Section: Methodsmentioning

confidence: 81%

Current and Future Disease Burden From Ambient Ozone Exposure in India

et al. 2018

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“…For high PM concentrations, anthropogenic sources like biomass burning products with downwind directions were reported as one of the principal contributors. Crop residue burning is identified and well documented as the primary cause of high PM 10 concentrations in the studied regions [51][52][53].…”

Section: Time Series Of Measured Pm 10 Concentrationsmentioning

confidence: 90%

Validation of Low-Cost Sensors in Measuring Real-Time PM10 Concentrations at Two Sites in Delhi National Capital Region

Sahu

Dixit

Mishra

et al. 2020

Sensors

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In the present study, we assessed for the first time the performance of our custom-designed low-cost Particulate Matter (PM) monitoring devices (Atmos) in measuring PM 10 concentrations. We examined the ambient PM 10 levels during an intense measurement campaign at two sites in the Delhi National Capital Region (NCR), India. In this study, we validated the un-calibrated Atmos for measuring ambient PM 10 concentrations at highly polluted monitoring sites. PM 10 concentration from Atmos, containing laser scattering-based Plantower PM sensor, was comparable with that measured from research-grade scanning mobility particle sizers (SMPS) in combination with optical particle sizers (OPS) and aerodynamic particle sizers (APS). The un-calibrated sensors often provided accurate PM 10 measurements, particularly in capturing real-time hourly concentrations variations. Quantile-Quantile plots (QQ-plots) for data collected during the selected deployment period showed positively skewed PM 10 datasets. Strong Spearman's rank-order correlations (r s = 0.64-0.83) between the studied instruments indicated the utility of low-cost Plantower PM sensors in measuring PM 10 in the real-world context. Additionally, the heat map for weekly datasets demonstrated high R 2 values, establishing the efficacy of PM sensor in PM 10 measurement in highly polluted environmental conditions.

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“…Biomass burning only plays a minor role in the CO enhancement: on average 1-2% at ground-level, and only 1% to the total column pollution level. In earlier studies, it was found that the GFAS biomass burning data, used in our analyses, likely underestimate the actual emissions of CO (Mota and Wooster, 2018;Cusworth et al, 2018;Huijnen et al, 2016). The comparison of TROPOMI data with our WRF simulations, based on MACCity and GFAS data, confirms that CO emissions are underestimated in the 11-14 20 November period.…”

Section: Meteorological Conditions 10mentioning

confidence: 84%

“…There are strong indications that GFAS might severely underestimate the fire emissions (Mota and Wooster, 2018). Cusworth et al (2018) concluded in their recent paper on biomass burning in India that the resolution of the MODIS satellite instrument, on which GFAS fire emissions are partly based, misses many small fires. In addition, thick smoke from fires might lead to an 10 underestimation of fire emissions from GFAS, as MODIS might identify these as clouds, as was found in a recent study over Indonesia (Huijnen et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

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What caused the extreme CO concentrations during the 2017 high pollution episode in India?

Dekker¹,

Houweling²,

Pandey³

et al. 2018

Preprint

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The TROPOspheric Monitoring Instrument (TROPOMI), launched 13 October 2017, measures carbon monoxide (CO) concentrations in the Earth's atmosphere since early November 2017. In the first measurements, TROPOMI was able to measure CO concentrations of the high pollution event in India of November 2017. In this paper we studied the extent of the pollution in India, comparing the TROPOMI CO with modelled data from the Weather Research and Forecast model (WRF) to identify the most important sources contributing to the high pollution, both at ground-level and in the total column. We 5 investigated the period between 11 and 19 November 2017. We found that residential and commercial combustion was a much more important source of CO pollution than the post-monsoon crop burning during this period, which is in contrast to what media suggested and some studies on aerosol emissions found. Also, the high pollution was not limited to Delhi and its direct neighbourhood but the accumulation of pollution extended over the whole Indo-Gangetic Plain (IGP) due to the unfavourable weather conditions in combination with extensive emissions. From the TROPOMI data and WRF simulations, we observed 10 a build-up of CO during 11-14 November and a decline in CO after the 15 th of November. The meteorological situation, characterized by low wind speeds and shallow atmospheric boundary layers, was most likely the primary explanation for the temporal accumulation and subsequent dispersion of regionally emitted CO in the atmosphere, emphasizing the important role of atmospheric dynamics. Due to its rapidly growing population and economy, India is expected to encounter similar pollution events more often in future post-monsoon and winter seasons unless significant policy measures are taken to reduce residential 15 and commercial emissions.

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Quantifying the influence of agricultural fires in northwest India on urban air pollution in Delhi, India

Cited by 170 publications

References 34 publications

Current and Future Disease Burden From Ambient Ozone Exposure in India

Current and Future Disease Burden From Ambient Ozone Exposure in India

Validation of Low-Cost Sensors in Measuring Real-Time PM10 Concentrations at Two Sites in Delhi National Capital Region

What caused the extreme CO concentrations during the 2017 high pollution episode in India?

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