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

Abstract

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.

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

“…The gases and aerosols released by open fires not only degrade regional air quality and increase risk to acute respiratory infection and other lung and cardiac diseases (Bikkina et al 2019, Chakrabarti et al 2019, but may also damage crops due to elevated surface ozone exposure (Burney and Ramanathan 2014, Sinha et al 2015, Ghude et al 2016. Despite the health and environmental hazards of emissions from these fires, standard estimates can differ by an order of magnitude (Liu et al 2019a), depending on the species and year. Here we diagnose the key reasons for the differences among existing emission inventories and provide an improved inventory constrained by on-the-ground survey data and additional satellite observations.…”

“…Mechanical harvesting generates abundant root-bound and loose crop residues that are difficult to manage manually, and steady increases in crop production have added to the volume of excess residues. For many farmers, burning is a convenient, cost-effective method to remove crop residues and quickly transition between the monsoon (kharif) and winter (rabi) crops; observations of active fires and burned area shows increases of ~40-142% from 2003-2016 in the western Indo-Gangetic Plain (IGP) (Liu et al 2019a(Liu et al , 2019b. Both satellites and ground-based monitors have detected enhanced aerosol loading downwind of smoke plumes from agricultural fires across north India in recent years (Badarinath et al 2009, Kaskaoutis et al 2014, Jethva et al 2018, Sarkar et al 2018.…”

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

“…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.…”

“…Here we use daily active fire and surface reflectance data from MODIS to investigate trends in crop phenology and agricultural fire activity in Punjab. While the moderate spatial resolution of MODIS likely leads to large underestimates in total post-monsoon agricultural fire activity in northwestern India (Liu et al 2019), here we aim to quantify linear trends using the relative temporal distribution, which is impacted less by spatial resolution. We also determine whether the seasonal cycle of monsoon to post-monsoon vegetation greenness reveals similar temporal shifts.…”

Theoretical uncertainties for global satellite-derived burned area estimates

“…FireCCI50 also has relative uncertainties >100% for croplands and forests in Australia, boreal North America and Europe. As these products are often also used at national to regional scales, it is important to consider the reliability of the current products at these scales Liu et al (2018); Zhu et al (2017); Roy and Boschetti (2009). The uncertainty estimates here are therefore useful for these users to discern any limitations of products at the appropriate scale.…”