Three global emission maps derived from population counts and three different types of nighttime lights: NPP-VIIRS (a), RCP-DMSP-OLS (b), and SLP-DMSP-OLS (c).

<p>The population data is from the U.S. Department of Energy at Oak Ridge National Laboratory (DOE/ORNL), and the three nighttime lights are from the Earth Observation Group in National Oceanic and Atmospheric Administration’s National Geophysical Data Center (NOAA/NGDC).</p

Evaluation of NPP-VIIRS Nighttime Light Data for Mapping Global Fossil Fuel Combustion CO₂ Emissions: A Comparison with DMSP-OLS Nighttime Light Data

<div><p>Recently, the stable light products and radiance calibrated products from Defense Meteorological Satellite Program’s (DMSP) Operational Linescan System (OLS) have been useful for mapping global fossil fuel carbon dioxide (CO₂) emissions at fine spatial resolution. However, few studies on this subject were conducted with the new-generation nighttime light data from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) Satellite, which has a higher spatial resolution and a wider radiometric detection range than the traditional DMSP-OLS nighttime light data. Therefore, this study performed the first evaluation of the potential of NPP-VIIRS data in estimating the spatial distributions of global CO₂ emissions (excluding power plant emissions). Through a disaggregating model, three global emission maps were then derived from population counts and three different types of nighttime lights data (NPP-VIIRS, the stable light data and radiance calibrated data of DMSP-OLS) for a comparative analysis. The results compared with the reference data of land cover in Beijing, Shanghai and Guangzhou show that the emission areas of map from NPP-VIIRS data have higher spatial consistency of the artificial surfaces and exhibit a more reasonable distribution of CO₂ emission than those of other two maps from DMSP-OLS data. Besides, in contrast to two maps from DMSP-OLS data, the emission map from NPP-VIIRS data is closer to the Vulcan inventory and exhibits a better agreement with the actual statistical data of CO₂ emissions at the level of sub-administrative units of the United States. This study demonstrates that the NPP-VIIRS data can be a powerful tool for studying the spatial distributions of CO₂ emissions, as well as the socioeconomic indicators at multiple scales.</p></div

The proportions of CO₂ emissions in each land cover of the three cities: Beijing (a), Shanghai (b), and Guangzhou (c).

<p>The proportions of CO₂ emissions in each land cover of the three cities: Beijing (a), Shanghai (b), and Guangzhou (c).</p

Comparison of the global emission maps based on nightlight and population data to the Vulcan inventory for U.S. domain at the 0.1° resolution.

<p>Comparison of the global emission maps based on nightlight and population data to the Vulcan inventory for U.S. domain at the 0.1° resolution.</p

Comparison of the global emission maps only distributed by nightlights to the Vulcan inventory for U.S. domain at the 0.1° resolution

<p>Comparison of the global emission maps only distributed by nightlights to the Vulcan inventory for U.S. domain at the 0.1° resolution</p

Regional spatial distributions of CO₂ emissions in the PRD China (a), Northeastern USA (b), and Western Europe (c).

<p>Regional spatial distributions of CO₂ emissions in the PRD China (a), Northeastern USA (b), and Western Europe (c).</p

The original Landsat Thematic Mapper images, land cover dataset, and three global emission maps of three cities (Beijing, Shanghai, and Guangzhou).

<p>The Landsat Thematic Mapper images of these cities are from the United States Geological Survey (USGS), and the land cover dataset is from the National Geomatics Center of China (NGCC).</p

Comparison of emission results only distributed by three different types of nighttime lights at the state unit of the United States: NPP-VIIRS (a), RCP-DMSP-OLS (b), and SLP-DMSP-OLS (c).

<p>Comparison of emission results only distributed by three different types of nighttime lights at the state unit of the United States: NPP-VIIRS (a), RCP-DMSP-OLS (b), and SLP-DMSP-OLS (c).</p

Comparison between the actual statistical data of CO₂ emissions and the estimated emissions of different emission maps at the state unit of the United States.

<p>Comparison between the actual statistical data of CO₂ emissions and the estimated emissions of different emission maps at the state unit of the United States.</p

A Biophysicochemical Model for NO Removal by the Chemical Absorption–Biological Reduction Integrated Process

The chemical absorption-biological reduction (CABR) integrated process is regarded as a promising technology for NO_<i>x</i> removal from flue gas. To advance the scale-up of the CABR process, a mathematic model based on mass transfer with reaction in the gas, liquid, and biofilm was developed to simulate and predict the NO_<i>x</i> removal by the CABR system in a biotrickling filter. The developed model was validated by the experimental results and subsequently was used to predict the system performance under different operating conditions, such as NO and O₂ concentration and gas and liquid flow rate. NO distribution in the gas phase along the biotrickling filter was also modeled and predicted. On the basis of the modeling results, the liquid flow rate and total iron concentration were optimized to achieve >90% NO removal efficiency. Furthermore, sensitivity analysis of the model revealed that the performance of the CABR process was controlled by the bioreduction activity of Fe­(III)­EDTA. This work will provide the guideline for the design and operation of the CABR process in the industrial application