Public Health Benefits From Improved Identification of Severe Air Pollution Events With Geostationary Satellite Data.

Despite improvements in ambient air quality in the US in recent decades, many people still experience unhealthy levels of pollution. At present, national-level alert-day identification relies predominately on surface monitor networks and forecasters. Satellite-based estimates of surface air quality have rapidly advanced and have the capability to inform exposure-reducing actions to protect public health.

Nowcasting Applications of Geostationary Satellite Hourly Surface PM Data.

The mass concentration of fine particulate matter (PM; diameters less than 2.5 μm) estimated from geostationary satellite aerosol optical depth (AOD) data can supplement the network of ground monitors with high temporal (hourly) resolution. Estimates of PM over the United States (US) were derived from NOAA's operational geostationary satellites Advanced Baseline Imager (ABI) AOD data using a geographically weighted regression with hourly and daily temporal resolution.

NO retrievals from NOAA-20 OMPS: Algorithm, evaluation, and observations of drastic changes during COVID-19.

We present the first NO measurements from the Nadir Mapper of Ozone Mapping and Profiler Suite (OMPS) instrument aboard the NOAA-20 satellite. NOAA-20 OMPS was launched in November 2017, with a nadir resolution of 17 × 13 km similar to the Ozone Monitoring Instrument (OMI). The retrieval of NOAA-20 NO vertical columns were achieved through the Direct Vertical Column Fitting (DVCF) algorithm, which was uniquely designed and successfully used to retrieve NO from OMPS aboard Suomi National Polar-orbiting Partnership (SNPP) spacecraft, predecessor to NOAA-20.

[Evaluation on the eco-economic benefits of small watershed in Beijing mountainous area: a case of Yanqi River watershed].

Based on the theory of harmonious development of ecological economy, a total of 13 evaluation indices were selected from the ecological, economic, and social sub-systems of Yanqi River watershed in Huairou District of Beijing. The selected evaluation indices were normalized by using trapezoid functions, and the weights of the evaluation indices were determined by analytic hierarchy process. Then, the eco-economic benefits of the watershed were evaluated with weighted composite index method.