Crop residue burning in China (2019-2021): Spatiotemporal patterns, environmental impact, and emission dynamics

Crop residue burning(CRB)is a major contributor to air pollution in China.Current fire detection methods,however,are limited by either temporal resolution or accuracy,hindering the analysis of CRB's diurnal characteristics.Here we explore the diurnal spatiotemporal patterns and environmental impacts of CRB in China from 2019 to 2021 using the recently released NSMC-Himawari-8 hourly fire product.Our analysis identifies a decreasing directionality in CRB distribution in the Northeast and a notable southward shift of the CRB center,especially in winter,averaging an annual southward movement of 7.5.Additionally,we observe a pronounced skewed distribution in daily CRB,predominantly between 17:00 and 20:00.Notably,nighttime CRB in China for the years 2019,2020,and 2021 accounted for 51.9%,48.5%,and 38.0%respectively,underscoring its significant environmental impact.The study further quantifies the hourly emissions from CRB in China over this period,with total emissions of CO,PM10,and PM_(2.5) amounting to 12,236,2,530,and 2,258 Gg,respectively.Our findings also reveal variable lag effects of CRB on regional air quality and pollutants across different seasons,with the strongest impacts in spring and more immediate effects in late autumn.This research provides valuable insights for the regulation and control of diurnal CRB before and after large-scale agricultural activities in China,as well as the associated haze and other pollution weather conditions it causes.

Integration of Multiple Spectral Data via a Logistic Regression Algorithm for Detection of Crop Residue Burned Areas:A Case Study of Songnen Plain,Northeast China

The burning of crop residues in fields is a significant global biomass burning activity which is a key element of the terrestrial carbon cycle,and an important source of atmospheric trace gasses and aerosols.Accurate estimation of cropland burned area is both crucial and challenging,especially for the small and fragmented burned scars in China.Here we developed an automated burned area mapping algorithm that was implemented using Sentinel-2 Multi Spectral Instrument(MSI)data and its effectiveness was tested taking Songnen Plain,Northeast China as a case using satellite image of 2020.We employed a logistic regression method for integrating multiple spectral data into a synthetic indicator,and compared the results with manually interpreted burned area reference maps and the Moderate-Resolution Imaging Spectroradiometer(MODIS)MCD64A1 burned area product.The overall accuracy of the single variable logistic regression was 77.38%to 86.90%and 73.47%to 97.14%for the 52TCQ and 51TYM cases,respectively.In comparison,the accuracy of the burned area map was improved to 87.14%and 98.33%for the 52TCQ and 51TYM cases,respectively by multiple variable logistic regression of Sentind-2 images.The balance of omission error and commission error was also improved.The integration of multiple spectral data combined with a logistic regression method proves to be effective for burned area detection,offering a highly automated process with an automatic threshold determination mechanism.This method exhibits excellent extensibility and flexibility taking the image tile as the operating unit.It is suitable for burned area detection at a regional scale and can also be implemented with other satellite data.

Estimating emissions from crop residue open burning in China based on statistics and MODIS fire products

With the objective of reducing the large uncertainties in the estimations of emissions from crop residue open burning, an improved method for establishing emission inventories of crop residue open burning at a high spatial resolution of 0.25°× 0.25° and a temporal resolution of1 month was established based on the moderate resolution imaging spectroradiometer（MODIS） Thermal Anomalies/Fire Daily Level3 Global Product（MOD/MYD14A1）. Agriculture mechanization ratios and regional crop-specific grain-to-straw ratios were introduced to improve the accuracy of related activity data. Locally observed emission factors were used to calculate the primary pollutant emissions. MODIS satellite data were modified by combining them with county-level agricultural statistical data, which reduced the influence of missing fire counts caused by their small size and cloud cover. The annual emissions of CO2, CO, CH4,nonmethane volatile organic compounds（NMVOCs）, N2O, NOx, NH3, SO2, fine particles（PM2.5）,organic carbon（OC）, and black carbon（BC） were 150.40, 6.70, 0.51, 0.88, 0.01, 0.13, 0.07, 0.43,1.09, 0.34, and 0.06 Tg, respectively, in 2012. Crop residue open burning emissions displayed typical seasonal and spatial variation. The highest emission regions were the Yellow-Huai River and Yangtse-Huai River areas, and the monthly emissions were highest in June（37%）.Uncertainties in the emission estimates, measured as 95% confidence intervals, range from a low of within ±126% for N2O to a high of within ± 169% for NH3.

Examining the policy-practice gap-The issue of crop burning induced Particulate Matter pollution in Northwest India

The study examine the efficacy of government policy interventions initiated since 2014 to curb FCRB in NW Indian states and the related air pollution in Delhi-NCR during 2014-2019.The regression analysis suggests an increase in PM2.5 of~69μg/m3/1000 surge in fires.VIIRS retrieved data suggest an overall declining trend of~1606 and~4308 fire counts per year across NW states during October-November respectively.The monthly PM2.5 concentrations in New Delhi exhibits a decline of~2.18μg/m3 and~5.17μg/m3 per year over the same period.Despite an overall increase of~17.6%rice productivity,a noted decrease in fire activity over the period is an encouraging move,likely a result of some control imposed by authorities on FCRB.Owing to a significant~35.5%rise in wheat productivity,data records rising trend in wheat residue burning activities in April(~1298/year)and May(~2402/year)but do not trigger extreme pollution due to difference in intensity of fires across harvesting seasons and relatively weak northwesterly wind direction.Nevertheless,the overall high PM2.5 levels in October-November and April-May compared to NAAQS 24-hour average of 60μg/m3,disproves the overall efficacy of government policies to curb FCRB and related air pollution in IGP region.

Size distributions of aerosol and water-soluble ions in Nanjing during a crop residual burning event

To investigate the impact on urban air pollution by crop residual burning outside Nanjing, aerosol concentration, pollution gas concentration, mass concentration, and water-soluble ion size distribution were observed during one event of November 4-9, 2010. Results show that the size distribution of aerosol concentration is bimodal on pollution days and normal days, with peak values at 60- 70 and 200-300 nm, respectively. Aerosol concentration is 104 cm-3.nm-1 on pollution days. The peak value of spectrum distribution of aerosol concentration on pollution days is 1.5-3.3 times higher than that on a normal day. Crop residual burning has a great impact on the concentration of fine particles. Diurnal variation of aerosol concentration is trimodal on pollution days and normal days, with peak values at 03：00, 09：00 and 19：00 local standard time. The first peak is impacted by meteorological elements, while the second and third peaks are due to human activities, such as rush hour traffic. Crop residual burning has the greatest impact on SO2 concentration, followed by NO2, 03 is hardly affected. The impact of crop residual burning on fine particles （〈 2.1 μm） is larger than on coarse particles （〉 2.1 μm）, thus ion concentration in fine particles is higher than that in coarse particles. Crop residual burning leads to similar increase in all ion components, thus it has a small impact on the water-soluble ions order. Crop residual burning has a strong impact on the size distribution of K^＋, Cl^-, Na^＋, and F- and has a weak impact on the size distributions of NH4^＋, Ca^2＋, NO3^- and SO4^2-.