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.

Particulate matter characterization in a steelworks using conventional sampling and innovative lidar observations

Particulate matter （PM） emissions from steelworks cause public concern. Although end-of-pipe and pro- cess integrated measures have led to a significant drop in emissions of large particles from stacks, fine aerosols were not specifically considered, nor were emissions from fugitive and open sources. In this study, we deployed aerosol samplers together with a scanning ultra-violet （UV） lidar to characterize total suspended particles （TSP）, PM10, and PM2.5, in emissions from a large integrated steelworks in Spain over a 16-day period. We determined the content of carbonaceous, soluble inorganic, mineral dust, and metal species. A positive matrix factorization was carried out on our dataset. Despite mineral dust being predominant in all size fractions, the steelworks was clearly a source of carbonaceous species, resulting in production of secondary inorganic aerosols. In particular, stack emissions were a major contributor of fine particles, while open sources dominated the emissions of TSP, yielding up to 80% of particles larger than PM10. UV lidar provided 2D maps of aerosols in real time, with an ability to detect PM emissions and to visualize complex plumes. We suggest that air quality management of steelworks needs to focus on controlling large and coarse oarticle emissions, esoeciallv those from onen sources.