Sugar cane bagasse is one of the largest fuels used for electricity generation in Brazil and its usage has continuously increased to supply the energy demand. This paper presents emission inventory based on power plan...Sugar cane bagasse is one of the largest fuels used for electricity generation in Brazil and its usage has continuously increased to supply the energy demand. This paper presents emission inventory based on power plants burning sugar cane bagasse. The inventory involves the spatial distribution and the estimated flows for the following major pollutants: nitrogen oxides (NOx), particulate material (PM), carbon dioxide (CO2) and total organic carbon (TOC). A total of 384 power plants were inventoried, representing a generated power of 9.9 GW, about 26% of the energy produced by thermal power plants sector. The plants are concentrated in two main poles: one of them in S?o Paulo State and nearby areas and the other one in coast of Brazilian Northeast. The limits proposed by the AP-42 Regulations of the US Environmental Protection Agency (USEPA) for the emission factors were applied. Additional emission factors identified in the scientific literature were also included in the analysis in order to assess the uncertainties associated to the estimative. The estimated emissions showed values in the range 16.0 - 20.5 Gg?year?1 for NOx, 18.0 - 267.0 Gg?year?1 for MP and 20.5 - 26.7 Tg?year?1 for CO2. The contribution of TOC showed a minor contribution around 10 - 20 Mg?year?1. PM showed to be the most representative pollutant emitted by the thermal plants burning sugar cane bagasse, but with a large range of uncertainty. There is a high level of uncertainty associated to the preparation of cane as well as the use of collectors to control particulate emissions. The adequate control over all stages could reduce the bagasse ash content in 90% or more.展开更多
Land cover classification is one of the main components of the modern weather research and forecasting models, which can influence the meteorological variable, and in turn the concentration of air pollutants. In this ...Land cover classification is one of the main components of the modern weather research and forecasting models, which can influence the meteorological variable, and in turn the concentration of air pollutants. In this study the impact of using two traditional land use classifications, the United States Geological Survey (USGS) and the Moderate-resolution Imaging Spectroradiometer (MODIS), were evaluated. The Weather Research and Forecasting model (WRF, version 3.2.1) was run for the period 18 - 22 August, 2014 (dry season) at a grid spacing of 3 km centered on the city of Manaus. The comparison between simulated and ground-based observed data revealed significant differences in the meteorological fields, for instance, the temperature. Compared to USGS, MODIS classification showed better skill in representing observed temperature for urban areas of Manaus, while the two files showed similar results for nearby areas. The analysis of the files suggests that the better quality of the simulations favorable to the MODIS file is straightly related to its better representation of urban class of land use, which is observed to be not adequately represented by USGS.展开更多
基金This work received funding support from CNPq(National Counsel of Technological and Scientific Development,process 404104/2013-4)CAPES(Coordination for the Improvement of Higher Education Personnel)and Araucária Foundation
文摘Sugar cane bagasse is one of the largest fuels used for electricity generation in Brazil and its usage has continuously increased to supply the energy demand. This paper presents emission inventory based on power plants burning sugar cane bagasse. The inventory involves the spatial distribution and the estimated flows for the following major pollutants: nitrogen oxides (NOx), particulate material (PM), carbon dioxide (CO2) and total organic carbon (TOC). A total of 384 power plants were inventoried, representing a generated power of 9.9 GW, about 26% of the energy produced by thermal power plants sector. The plants are concentrated in two main poles: one of them in S?o Paulo State and nearby areas and the other one in coast of Brazilian Northeast. The limits proposed by the AP-42 Regulations of the US Environmental Protection Agency (USEPA) for the emission factors were applied. Additional emission factors identified in the scientific literature were also included in the analysis in order to assess the uncertainties associated to the estimative. The estimated emissions showed values in the range 16.0 - 20.5 Gg?year?1 for NOx, 18.0 - 267.0 Gg?year?1 for MP and 20.5 - 26.7 Tg?year?1 for CO2. The contribution of TOC showed a minor contribution around 10 - 20 Mg?year?1. PM showed to be the most representative pollutant emitted by the thermal plants burning sugar cane bagasse, but with a large range of uncertainty. There is a high level of uncertainty associated to the preparation of cane as well as the use of collectors to control particulate emissions. The adequate control over all stages could reduce the bagasse ash content in 90% or more.
基金This work received funding support from CNPq(National Counsel of Technological and Scientific Development,process 404104/2013-4)CAPES(Coordination for the Improvement of Higher Education Personnel)and Araucária Foundation
文摘Land cover classification is one of the main components of the modern weather research and forecasting models, which can influence the meteorological variable, and in turn the concentration of air pollutants. In this study the impact of using two traditional land use classifications, the United States Geological Survey (USGS) and the Moderate-resolution Imaging Spectroradiometer (MODIS), were evaluated. The Weather Research and Forecasting model (WRF, version 3.2.1) was run for the period 18 - 22 August, 2014 (dry season) at a grid spacing of 3 km centered on the city of Manaus. The comparison between simulated and ground-based observed data revealed significant differences in the meteorological fields, for instance, the temperature. Compared to USGS, MODIS classification showed better skill in representing observed temperature for urban areas of Manaus, while the two files showed similar results for nearby areas. The analysis of the files suggests that the better quality of the simulations favorable to the MODIS file is straightly related to its better representation of urban class of land use, which is observed to be not adequately represented by USGS.
