Interannual variations and trends of gross primary production and transpiration of four mature deciduous broadleaf forest sites during 2000–2020
Not provided.
Environmental Sciences & Ecology↗
Engineering topics
Pan, Li
Publications and source records attributed to Pan, Li.
A demonstrator for a real-time AI-FPGA-based triggering system for sPHENIX at RHIC
The RHIC interaction rate at sPHENIX will reach around 3 MHz in pp collisions and requires the detector readout to reject events by a factor of over 200 to fit the DAQ bandwidth of 15 kHz. Some critical measurements, such as heavy flavor production in pp collisions, often require the analysis of particles produced at low momentum. This prohibits adopting the traditional approach, where data rates are reduced through triggering on rare high momentum probes. We explore a new approach based on real-time AI technology, adopt an FPGA-based implementation using a custom designed FELIX-712 board with the Xilinx Kintex Ultrascale FPGA, and deploy the system in the detector readout electronics loop for real-time trigger decision.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Updating and Evaluating Anthropogenic Emissions for NOAA’s Global Ensemble Forecast Systems for Aerosols (GEFS-Aerosols): Application of an SO 2 Bias-Scaling Method
We updated the anthropogenic emissions inventory in NOAA’s operational Global Ensemble Forecast for Aerosols (GEFS-Aerosols) to improve the model’s prediction of aerosol optical depth (AOD). We used a methodology to quickly update the pivotal global anthropogenic sulfur dioxide (SO 2 ) emissions using a speciated AOD bias-scaling method. The AOD bias-scaling method is based on the latest model predictions compared to NASA’s Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA2). The model bias was subsequently applied to the CEDS 2019 SO 2 emissions for adjustment. The monthly mean GEFS-Aerosols AOD predictions were evaluated against a suite of satellite observations (e.g., MISR, VIIRS, and MODIS), ground-based AERONET observations, and the International Cooperative for Aerosol Prediction (ICAP) ensemble results. The results show that transitioning from CEDS 2014 to CEDS 2019 emissions data led to a significant improvement in the operational GEFS-Aerosols model performance, and applying the bias-scaled SO 2 emissions could further improve global AOD distributions. The biases of the simulated AODs against the observed AODs varied with observation type and seasons by a factor of 3~13 and 2~10, respectively. The global AOD distributions showed that the differences in the simulations against ICAP, MISR, VIIRS, and MODIS were the largest in March–May (MAM) and the smallest in December–February (DJF). When evaluating against the ground-truth AERONET data, the bias-scaling methods improved the global seasonal correlation (r), Index of Agreement (IOA), and mean biases, except for the MAM season, when the negative regional biases were exacerbated compared to the positive regional biases. The effect of bias-scaling had the most beneficial impact on model performance in the regions dominated by anthropogenic emissions, such as East Asia. However, it showed less improvement in other areas impacted by the greater relative transport of natural emissions sources, such as India. The accuracies of the reference observation or assimilation data for the adjusted inputs and the model physics for outputs, and the selection of regions with less seasonal emissions of natural aerosols determine the success of the bias-scaling methods. A companion study on emission scaling of anthropogenic absorbing aerosols needs further improved aerosol prediction.
54 ENVIRONMENTAL SCIENCES↗
Impact of the 2008 Global Recession on Air Quality over the United States: Implications for Surface Ozone Levels from Changes in NOx Emissions
Satellite and ground observations detected large variability in nitrogen oxides (NOx) during the 2008 economic recession, but the impact of the recession on air quality has not been quantified. This study combines observed NOx trends and a regional chemical transport model to quantify the impact of the recession on surface ozone (O3) levels over the continental United States. The impact is quantified by simulating O3 concentrations under two emission scenarios: business-as-usual (BAU) and recession. In the BAU case, the emission projection from the Cross-State Air Pollution Rule is used to estimate the would-be NOx emission level in 2011. In the recession case, the actual NO2 trends observed from Air Quality System ground monitors and the Ozone Monitoring Instrument on the Aura satellite are used to obtain realistic changes in NOx emissions. The model prediction with the recession effect agrees better with ground O3 observations over time and space than the prediction with the BAU emission. The results show that the recession caused a 12ppbv decrease in surface O3 concentration over the eastern United States, a slight increase (0.51ppbv) over the Rocky Mountain region, and mixed changes in the Pacific West. The gain in air quality benefits during the recession, however, could be quickly offset by the much slower emission reduction rate during the post-recession period.
NOx emissions↗