How Much Does Large-Scale Crop Residue Burning Affect the Air Quality in Delhi?

2020 ◽  
Vol 54 (8) ◽  
pp. 4790-4799 ◽  
Author(s):  
Santosh H. Kulkarni ◽  
Sachin D. Ghude ◽  
Chinmay Jena ◽  
Rama K. Karumuri ◽  
Baerbel Sinha ◽  
...  
Keyword(s):  
Air Quality ◽  
Large Scale ◽  
Crop Residue ◽  
Crop Residue Burning

scholarly journals Impact of crop residue burning in Haryana on the air quality of Delhi, India

Heliyon ◽  
2021 ◽  
Vol 7 (5) ◽  
pp. e06973
Author(s):  
Pallavi Saxena ◽  
Saurabh Sonwani ◽  
Ananya Srivastava ◽  
Madhavi Jain ◽  
Anju Srivastava ◽  
...  
Keyword(s):  
Air Quality ◽  
Crop Residue ◽  
Crop Residue Burning

Crop Residue Burning: A Threat to South Asian Air Quality

Eos ◽  
2014 ◽  
Vol 95 (37) ◽  
pp. 333-334 ◽  
Author(s):  
Ramesh P. Singh ◽  
Dimitris G. Kaskaoutis
Keyword(s):  
Air Quality ◽  
South Asian ◽  
Crop Residue ◽  
Crop Residue Burning

Quantification of crop residue burning in the field and its influence on ambient air quality in Suqian, China

2008 ◽  
Vol 42 (9) ◽  
pp. 1961-1969 ◽  
Author(s):  
Shijian Yang ◽  
Hongping He ◽  
Shangling Lu ◽  
Dong Chen ◽  
Jianxi Zhu
Keyword(s):  
Air Quality ◽  
Crop Residue ◽  
Ambient Air ◽  
Ambient Air Quality ◽  
Crop Residue Burning

scholarly journals New eastern China agricultural burning fire emission inventory and trends analysis from combined geostationary (Himawari-8) and polar-orbiting (VIIRS-IM) fire radiative power products

2020 ◽  
Author(s):  
Tianran Zhang ◽  
Mark C. de Jong ◽  
Martin J. Wooster ◽  
Weidong Xu ◽  
Lili Wang
Keyword(s):  
Remote Sensing ◽  
Air Quality ◽  
Crop Residue ◽  
Eastern China ◽  
Post Harvest ◽  
Crop Residue Burning ◽  
Radiative Power ◽  
Agricultural Burning ◽  
Emissions Inventories ◽  
Fire Radiative Power

Abstract. Open burning of agricultural crop residues is widespread across eastern China, and during certain post-harvest periods this activity is believed to significantly influence air quality. However, the exact contribution of crop residue burning to major air quality exceedances and air quality episodes has proven difficult to quantify. Whilst highly successful in many regions, in areas dominated by agricultural burning MODIS-based fire emissions inventories such as GFAS and GFED are suspected of significantly underestimating the magnitude of biomass burning emissions due to the typically very small, but highly numerous, fires involved that are quite easily missed by coarser spatial resolution remote sensing observations. To address this issue, we here use twice daily fire radiative power (FRP) observations from the ‘small fire optimised’ VIIRS-IM FRP product, and combine it with fire diurnal cycle information taken from the geostationary Himawari-8 satellite. Using this we generate a unique high spatio-temporal resolution agricultural burning inventory for eastern China for the years 2012–2015, designed to fully take into account small fires well below the MODIS burned area or active fire detection limit, focusing on dry matter burned (DMB) and emissions of CO2, CO, PM2.5 and black carbon. We calculate DMB totals 100 to 400 % higher than reported by GFAS and GFED4.1s, and quantify interesting spatial and temporal patterns previously un-noted. Wheat residue burning, primarily occurring in May–June, is responsible for more than half of the annual crop residue burning emissions of all species, whilst a secondary peak in autumn (Sept–Oct) is associated with rice and corn residue burning. We further identify a new winter (Nov–Dec) burning season, hypothesised to be caused by delays in burning driven by the stronger implementation of residue burning bans during the autumn post-harvest season. Whilst our emissions estimates are far higher than those of other satellite-based emissions inventories for the region, they are lower than estimates made using traditional ‘crop yield-based approaches’ (CYBA) by a factor of between 2 and 5 x. We believe that this is at least in part caused by outdated and overly high burning ratios being used in the CYBA approach, leading to the overestimation of DMB. Therefore we conclude that that satellite remote sensing approaches which adequately detect the presence of agricultural fires are a far better approach to agricultural fire emission estimation.

scholarly journals Trends in eastern China agricultural fire emissions derived from a combination of geostationary (Himawari) and polar (VIIRS) orbiter fire radiative power products

2020 ◽  
Vol 20 (17) ◽  
pp. 10687-10705
Author(s):  
Tianran Zhang ◽  
Mark C. de Jong ◽  
Martin J. Wooster ◽  
Weidong Xu ◽  
Lili Wang
Keyword(s):  
Remote Sensing ◽  
Air Quality ◽  
Crop Residue ◽  
Eastern China ◽  
Fire Emissions ◽  
Crop Residue Burning ◽  
Radiative Power ◽  
Agricultural Burning ◽  
Emissions Inventories ◽  
Fire Radiative Power

Abstract. Open burning of agricultural crop residues is widespread across eastern China, and during certain post-harvest periods this activity is believed to significantly influence air quality. However, the exact contribution of crop residue burning to major air quality exceedances and air quality episodes has proven difficult to quantify. Whilst highly successful in many regions, in areas dominated by agricultural burning, MODIS-based (MODIS: Moderate Resolution Imaging Spectroradiometer) fire emissions inventories such as the Global Fire Assimilation System (GFAS) and Global Fire Emissions Database (GFED) are suspected of significantly underestimating the magnitude of biomass burning emissions due to the typically very small, but highly numerous, fires involved that are quite easily missed by coarser-spatial-resolution remote sensing observations. To address this issue, we use twice-daily fire radiative power (FRP) observations from the “small-fire-optimised” VIIRS-IM FRP product and combine them with fire diurnal cycle information taken from the geostationary Himawari-8 satellite. Using this we generate a unique high-spatio-temporal-resolution agricultural burning inventory for eastern China for the years 2012–2015, designed to fully take into account small fires well below the MODIS burned area or active fire detection limit, focusing on dry matter burned (DMB) and emissions of CO2, CO, PM2.5, and black carbon. We calculate DMB totals 100 % to 400 % higher than reported by the GFAS and GFED4.1s, and we quantify interesting spatial and temporal patterns previously un-noted. Wheat residue burning, primarily occurring in May–June, is responsible for more than half of the annual crop residue burning emissions of all species, whilst a secondary peak in autumn (September–October) is associated with rice and corn residue burning. We further identify a new winter (November–December) burning season, hypothesised to be caused by delays in burning driven by the stronger implementation of residue burning bans during the autumn post-harvest season. Whilst our emissions estimates are far higher than those of other satellite-based emissions inventories for the region, they are lower than estimates made using traditional “crop-yield-based approaches” (CYBAs) by a factor of between 2 and 5. We believe that this is at least in part caused by outdated and overly high burning ratios being used in the CYBA, leading to the overestimation of DMB. Therefore, we conclude that satellite remote sensing approaches which adequately detect the presence of agricultural fires are a far better approach to agricultural fire emission estimation.

scholarly journals Enhancing Accuracy of Air Quality and Temperature Forecasts During Paddy Crop Residue Burning Season in Delhi Via Chemical Data Assimilation

2020 ◽  
Vol 125 (17) ◽  
Author(s):  
Rajesh Kumar ◽  
Sachin D. Ghude ◽  
Mrinal Biswas ◽  
Chinmay Jena ◽  
Stefano Alessandrini ◽  
...  
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
Crop Residue ◽  
Chemical Data ◽  
Crop Residue Burning ◽  
Paddy Crop

scholarly journals Spatiotemporal Variations and Uncertainty in Crop Residue Burning Emissions over North China Plain: Implication for Atmospheric CO2 Simulation

2021 ◽  
Vol 13 (19) ◽  
pp. 3880
Author(s):  
Yu Fu ◽  
Hao Gao ◽  
Hong Liao ◽  
Xiangjun Tian
Keyword(s):  
Air Quality ◽  
Biomass Burning ◽  
Crop Residue ◽  
North China Plain ◽  
North China ◽  
Transport Model ◽  
Spatial Uncertainty ◽  
Burned Area ◽  
Crop Residue Burning ◽  
The Impact

Large uncertainty exists in the estimations of greenhouse gases and aerosol emissions from crop residue burning, which could be a key source of uncertainty in quantifying the impact of agricultural fire on regional air quality. In this study, we investigated the crop residue burning emissions and their uncertainty in North China Plain (NCP) using three widely used methods, including statistical-based, burned area-based, and fire radiative power-based methods. The impacts of biomass burning emissions on atmospheric carbon dioxide (CO2) were also examined by using a global chemical transport model (GEOS-Chem) simulation. The crop residue burning emissions were found to be high in June and followed by October, which is the harvest times for the main crops in NCP. The estimates of CO2 emission from crop residue burning exhibits large interannual variation from 2003 to 2019, with rapid growth from 2003 to 2012 and a remarkable decrease from 2013 to 2019, indicating the effects of air quality control plans in recent years. Through Monte Carlo simulation, the uncertainty of each estimation was quantified, ranging from 20% to 70% for CO2 emissions at the regional level. Concerning spatial uncertainty, it was found that the crop residue burning emissions were highly uncertain in small agricultural fire areas with the maximum changes of up to 140%. While in the areas with large agricultural fire, i.e., southern parts of NCP, the coefficient of variation mostly ranged from 30% to 100% at the gridded level. The changes in biomass burning emissions may lead to a change of surface CO2 concentration during the harvest times in NCP by more than 1.0 ppmv. The results of this study highlighted the significance of quantifying the uncertainty of biomass burning emissions in a modeling study, as the variations of crop residue burning emissions could affect the emission-driven increases in CO2 and air pollutants during summertime pollution events by a substantial fraction in this region.

scholarly journals A high-resolution inventory of air pollutant emissions from crop residue burning in China

2018 ◽  
Author(s):  
Xiaohui Zhang ◽  
Yan Lu ◽  
Qin'geng Wang ◽  
Xin Qian
Keyword(s):  
Air Quality ◽  
Air Pollutants ◽  
Crop Residue ◽  
Eastern China ◽  
Temporal Variations ◽  
Air Pollutant ◽  
Central China ◽  
Pollutant Emissions ◽  
Activity Data ◽  
Crop Residue Burning

Abstract. Crop residue burning is an important source of air pollutants and strongly affects the regional air quality and global climate change. This study presents a detailed emission inventory of major air pollutants from crop residue burning for the year of 2014 in China. Activity data were investigated for 296 prefecture-level cities, and emissions were firstly estimated for each city and then redistributed using 1-km resolution land use data. Temporal variation was determined according to the farming practice in different regions. The MODIS fire product was applied to verify the spatial and temporal variations of the inventory. Results indicates that the total emissions of BC, OC, PM2.5, PM10, SO2, NOX, NH3, CH4, NMVOC, CO and CO2 from crop residue burning (including open and household fuel burnings) were estimated to be 0.16, 0.82, 2.30, 2.66, 0.09, 0.70, 0.14, 0.81, 1.70, 13.70 and 309.04 Tg, respectively. Rice, wheat and corn were the three major contributors, but their relative contributions varied with region and season. High emissions were generally located in the eastern China, central China and northeastern China, and temporally peaking in June and October relating with harvesting time. The spatially and temporal distributions agree well with the fire pixel counts from MODIS. Uncertainties were estimated using the Monte Carlo method. This study provides a useful basis for air quality modeling and the policy making of pollution control strategies.

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