Dataset Information

Satellite NO₂ retrievals suggest China has exceeded its NO_x reduction goals from the twelfth Five-Year Plan.

ABSTRACT: China's twelfth Five-Year Plan included pollution control measures with a goal of reducing national emissions of nitrogen oxides (NO_x) by 10% by 2015 compared with 2010. Multiple linear regression analysis was used on 11-year time series of all nitrogen dioxide (NO₂) pixels from the Ozone Monitoring Instrument (OMI) over 18 NO₂ hotspots in China. The regression analysis accounted for variations in meteorology, pixel resolution, seasonal effects, weekday variability and year-to-year variability. The NO₂ trends suggested that there was an increase in NO₂ columns in most areas from 2005 to around 2011 which was followed by a strong decrease continuing through 2015. The satellite results were in good agreement with the annual official NO_x emission inventories which were available up until 2014. This shows the value of evaluating trends in emission inventories using satellite retrievals. It further shows that recent control strategies were effective in reducing emissions and that recent economic transformations in China may be having an effect on NO₂ columns. Satellite information for 2015 suggests that emissions have continued to decrease since the latest inventories available and have surpassed the goals of the twelfth Five-Year Plan.

SUBMITTER: de Foy B

PROVIDER: S-EPMC5082360 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Satellite NO2 retrievals suggest China has exceeded its NOx reduction goals from the twelfth Five-Year Plan.

de Foy Benjamin B Lu Zifeng Z Streets David G DG

Scientific reports 20161027

China's twelfth Five-Year Plan included pollution control measures with a goal of reducing national emissions of nitrogen oxides (NOx) by 10% by 2015 compared with 2010. Multiple linear regression analysis was used on 11-year time series of all nitrogen dioxide (NO2) pixels from the Ozone Monitoring Instrument (OMI) over 18 NO2 hotspots in China. The regression analysis accounted for variations in meteorology, pixel resolution, seasonal effects, weekday variabili ...[more]

PMID: 27786278

Similar Datasets

Project description:Advances in satellite retrieval of aerosol type can improve the accuracy of near-surface air quality characterization by providing broad regional context and decreasing metric uncertainties and errors. The frequent, spatially extensive and radiometrically consistent instantaneous constraints can be especially useful in areas away from ground monitors and progressively downwind of emission sources. We present a physical approach to constraining regional-scale estimates of PM2.5, its major chemical component species estimates, and related uncertainty estimates of chemical transport model (CTM; e.g., the Community Multi-scale Air Quality Model) outputs. This approach uses ground-based monitors where available, combined with aerosol optical depth and qualitative constraints on aerosol size, shape, and light-absorption properties from the Multi-angle Imaging SpectroRadiometer (MISR) on the NASA Earth Observing System's Terra satellite. The CTM complements these data by providing complete spatial and temporal coverage. Unlike widely used approaches that train statistical regression models, the technique developed here leverages CTM physical constraints such as the conservation of aerosol mass and meteorological consistency, independent of observations. The CTM also aids in identifying relationships between observed species concentrations and emission sources. Aerosol air mass types over populated regions of central California are characterized using satellite data acquired during the 2013 San Joaquin field deployment of the NASA Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) project. We investigate the optimal application of incorporating 275 m horizontal-resolution aerosol air-mass-type maps and total-column aerosol optical depth from the MISR Research Aerosol retrieval algorithm (RA) into regional-scale CTM output. The impact on surface PM2.5 fields progressively downwind of large single sources is evaluated using contemporaneous surface observations. Spatiotemporal R 2 and RMSE values for the model, constrained by both satellite and surface monitor measurements based on 10-fold cross-validation, are 0.79 and 0.33 for PM2.5, 0.88 and 0.65 for NO3 -, 0.78 and 0.23 for SO4 2-, and 1.01 for NH+, 0.73 and 0.23 for OC, and 0.31 and 0.65 for EC, respectively. Regional cross-validation temporal and spatiotemporal R2 results for the satellite-based PM2.5 improve by 30 % and 13 %, respectively, in comparison to unconstrained CTM simulations and provide finer spatial resolution. SO4 2- cross-validation values showed the largest spatial and spatiotemporal R2 improvement, with a 43 % increase. Assessing this physical technique in a well- instrumented region opens the possibility of applying it globally, especially over areas where surface air quality measurements are scarce or entirely absent.

Dataset Information

Satellite NO₂ retrievals suggest China has exceeded its NO_x reduction goals from the twelfth Five-Year Plan.

Publications

Satellite NO<sub>2</sub> retrievals suggest China has exceeded its NO<sub>x</sub> reduction goals from the twelfth Five-Year Plan.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets