Spatio-Temporal Characterization of Agriculture Residue Burning in Punjab and Haryana, India, Using MODIS and Suomi NPP VIIRS Data

Thumaty, Kiran Chand; Rodda, Suraj Reddy; Singhal, Jayant; Gopalakrishnan, Rajashekar; Jha, Chandra Shekhar; Parsi, Gururao Diwakar; Dadhwal, V. K.

doi:10.18520/cs/v109/i10/1850-1868

Cited by 22 publications

(11 citation statements)

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“…We first sum daily MODIS Terra and Aqua FRP during each post-monsoon burning season and over each state. This step assumes that the agricultural fires in this region are short-lived (~ 1/2 hour), following Thumaty et al (2015), and that the instruments detect different fires at the overpass times, Terra at 10:30 a.m. and Aqua at 1:30 p.m. Here we use the maximum FRP from the MOD/MYD14A1 gridded active fire product and apply an agricultural mask derived from MCD12Q1 to ensure that only cropland fires are considered and conservatively exclude FRP in intermixed land covers.…”

Section: Adjustment Of Frp Based On Survey Data and Additional Satellmentioning

confidence: 99%

“…One difficulty in monitoring agricultural fires in this region is the coarse spatio-temporal resolution of satellite measurements (Liu et al 2019a). The small size and duration of the fires, as well as increasing haziness from the smoke itself, also complicate interpretation of satellite observations (Thumaty et al 2015, Liu et al 2019a. These challenges may lead to gross underestimation of fire emissions driving atmospheric models (Cusworth et al 2018, Dekker et al 2019, Lasko et al 2017.…”

Section: Introductionmentioning

confidence: 99%

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Crop residue burning practices across north India inferred from household survey data: bridging gaps in satellite observations

Liu¹,

Mickley²,

Singh³

et al. 2020

Preprint

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In north India, agricultural burning adversely affects local and regional air quality during the post-monsoon season (October to November), when the prevailing meteorology is favorable for smog and haze formation. Quantifying the contribution of smoke to air pollution in this region, however, is challenging. While the Moderate Resolution Imaging Spectroradiometer (MODIS), aboard NASA’s Terra and Aqua satellites, provides a nearly 20-year record of global fire activity, the sensor cannot adequately capture small, short-lasting agricultural fires due to its moderate spatial resolution (500 m to 1 km) and limited overpasses (twice daily for each satellite), as well as the hazy conditions that typically obscure the north India land surface at this time of year. Moreover, current global fire emissions inventories based on MODIS observations can differ by up to an order of magnitude in this region. Here we incorporate household survey data to bridge gaps in MODIS observations and improve estimates of fire emissions over the states of Punjab, Haryana, Uttar Pradesh, and Bihar during the 2003-2018 post-monsoon burning seasons. We develop a novel method that adjusts MODIS Fire Radiative Power (FRP) for: (1) small fires detected by the Visible Infrared Imaging Radiometer Suite (VIIRS) at 375-m spatial resolution, (2) cloud/haze gaps in satellite observations, (3) partial-field burning practices, and (4) the diurnal cycle of fire activity. Adjusting FRP for the fire diurnal cycle yields the largest boost to emissions due to the short lifetime of the fires (~1/2 hour) and the brief windows of satellite detection. Using adjusted FRP, we estimate on average 10.8 ± 2.7 Tg dry matter (DM) burned each year, yielding emissions of 68 ± 17 Gg organic carbon (OC), 5.8 ± 1.5 Gg black carbon (BC), 821 ± 206 Gg CO, and 15.4 ± 3.9 Tg CO2. On average, our OC+BC emissions are ~250% higher than estimates from five widely used global fire emissions inventories. Our estimate for Punjab, which contributes two-thirds of emissions in the region, is consistent with our bottom-up validation, which uses burn rates from the household survey and government crop production statistics in 2016 and 2017. We spatially disaggregate the state-level emissions to construct a gridded inventory at daily, 0.25° x 0.25° resolution over north India from 2003-2018. The inventory, SAGE-IGP (Survey Constraints on FRP-based Agricultural Fire Emissions in the Indo-Gangetic Plain), improves modeling assessments of air quality impacts from agricultural burning, thus supporting effective policy development.

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Section: Adjustment Of Frp Based On Survey Data and Additional Satellmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Crop residue burning practices across north India inferred from household survey data: bridging gaps in satellite observations

Liu¹,

Mickley²,

Singh³

et al. 2020

Preprint

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“…However, the smoke from postmonsoon crop residue burning, primarily during October to November, amplifies severe haze events in the region (Kaskaoutis et al 2014, Bikkina et al 2019, such as that observed in early November 2016 (Cusworth et al 2018). Of particular concern is the observed increase in aerosol loading associated with an increasing trend in post-monsoon burned area and shift toward a later peak in post-monsoon fires in northwestern India (Thumaty et al 2015, Jethva et al 2018, Liu et al 2019. Here we use daily satellite remote sensing data to better quantify the temporal shift toward later burning in the state of Punjab, the "breadbasket" of India.…”

Section: Introductionmentioning

confidence: 99%

Detection of delay in post-monsoon agricultural burning across Punjab, India: potential drivers and consequences for air quality

Liu¹,

Mickley²,

Gautam³

et al. 2019

Preprint

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Since the Green Revolution in the mid-1960s, a widespread transition to a rice-wheat rotation in the Indian state of Punjab has led to steady increases in crop yield and production. After harvest of the summer monsoon rice crop, the burning of excess crop residue in Punjab from October to November allows for rapid preparation of fields for sowing of the winter wheat crop. Here we use daily satellite remote sensing data to show that the timing of peak post-monsoon fire activity in Punjab and regional aerosol optical depth (AOD) has shifted later by approximately two weeks in Punjab from 2003-2016. This shift is consistent with delays of 11-15 days in the timing of maximum greenness of the monsoon crop and smaller delays of 4-6 days in the timing of minimum greenness during the monsoon-to-winter crop transition period. The resulting compression of the harvest-to-sowing period coincides with a 40% increase in total burning and ~50% increase in regional AOD. Potential drivers of these trends include agricultural intensification and a recent groundwater policy that delays sowing of the monsoon crop. The delay and amplification of burning into the late post-monsoon season suggest greater air quality degradation and public health consequences across the densely-populated Indo-Gangetic Plain.

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“…However, slant satellite viewing geometry may dilute the signal of small, short-lasting fires, whose detection is already hindered by coarse sensor spatio-temporal resolution. In India, agricultural fires typically last no more than half an hour (Thumaty et al 2015). We find an omission error of >90% by the MODIS active fires product.…”

Section: Ignitionsmentioning

confidence: 69%

“…In addition, we find an average step increase of 54%-65% in BA ModL2T and BA MCD64A1 from the 2003-07 to 2008-16 time period. Building on Thumaty et al (2015), we find that the timing of peak post-monsoon burning, indicated by 5-day block mean active fire counts, has shifted from mid-October to early-November during the 14-year period ( figure S6). In 2009, the Punjab and Haryana governments officially implemented the 'Preservation of Sub-soil Water Act, 2009' (Ordinance in 2008) to counteract groundwater depletion by delaying rice transplanting to after June 10 and 15, respectively (Singh 2009, Tripathi et al 2016.…”

Section: Trends In Landholding Size Combine Harvesters and Agricultmentioning

confidence: 74%

Missing emissions from post-monsoon agricultural fires in northwestern India: regional limitations of MODIS burned area and active fire products

Liu

Marlier

Karambelas

et al. 2019

Environ. Res. Commun.

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A rising source of outdoor emissions in northwestern India is crop residue burning, occurring after the monsoon (kharif ) and winter (rabi) crop harvests. In particular, post-monsoon rice residue burning, which occurs annually from October to November and is linked to increasing mechanization, coincides with meteorological conditions that enhance short-term air quality degradation. Here we examine the Global Fire Emissions Database (GFED), whose bottom-up emissions are based on the 500-m burned area product, MCD64A1, derived from Moderate Resolution Imaging Spectroradiometer (MODIS) observations. Using a household survey from 2016, we find that MCD64A1 tends to underestimate burned area in many surveyed villages, leading to poor representation of small, scattered fires and consequent spatial biases in model results. To more accurately allocate such small fires and resolve sub-village heterogeneity, we use an experimental hybrid MODIS-Landsat method (ModL2T) to map burned area at 30-m spatial resolution, which results in 44±21% higher burned area than MCD64A1 and up to 105±52% increase in dry matter emissions over GFEDv4s. In our validation and assessments, we find that ModL2T performs better relative to MCD64A1 in terms of bias and omission error, but may introduce commission error due to conflation of burning with harvest and still underestimate burned area due to Landsat's coarse temporal resolution (every 16 days). We conclude that while MODIS and Landsat provide more than two decades worth of observations, their spatio-temporal resolution is too coarse to overcome several region-specific challenges: small median landholding size (1-3 ha), quick harvest-to-sowing turnover period, prevalence of partial burning, and increasing haziness. To further constrain agricultural fire emissions in northwestern India and improve model estimates of associated public health impacts, integration of finer resolution imagery, as well as better understanding of the spatial patterns in burn rates, burn practices, and fuel loading, is requisite.

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Spatio-Temporal Characterization of Agriculture Residue Burning in Punjab and Haryana, India, Using MODIS and Suomi NPP VIIRS Data

Cited by 22 publications

References 0 publications

Crop residue burning practices across north India inferred from household survey data: bridging gaps in satellite observations

Crop residue burning practices across north India inferred from household survey data: bridging gaps in satellite observations

Detection of delay in post-monsoon agricultural burning across Punjab, India: potential drivers and consequences for air quality

Missing emissions from post-monsoon agricultural fires in northwestern India: regional limitations of MODIS burned area and active fire products

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