Variation of the Atmospheric Boundary Layer Height at the Eastern Edge of the Tibetan Plateau

This paper utilized the high temporal and spatial resolution temperature profile data observed by the multi-channel microwave radiometer at the Large High Altitude Air Shower Observatory (LHAASO) on the eastern slope of the Tibetan Plateau from February to May and August to November 2021, combined with the ERA5 reanalysis data products for the whole year of 2021, to study the daily, monthly, and seasonal variations of the atmospheric boundary layer height (ABLH). The results are as follows: (1) The ABLH on sunny days showed obvious fluctuations with peaks and valleys. The ABLH continued to rise with the increase of surface temperature after sunrise and usually reached its maximum value in the afternoon around 18:00, then rapidly decreased until sunset. (2) The average ABLH in April was the highest at about 1200 m, while it was only around 600 m in November. The ABLH fluctuated greatly during the day and was stable at around 400 m at night. The ABLH results obtained from ERA5 were slightly smaller overall but had a consistent trend of change with the microwave radiometer. (3) The maximum ABLH appeared in spring, followed by summer and autumn, and winter had the lowest value, with all peaks reached around 14:00-15:00. These results are of great significance for understanding the ABLH on the eastern slope of the Tibetan Plateau, and provide reference for the absolute calibration of photon numbers of the LHAASO telescope and the atmospheric monitoring plan, as well as for evaluating the authenticity and accuracy of existing reanalysis datasets

A Satellite-Driven Model to Estimate Long-Term Particulate Sulfate Levels and attributable Mortality Burden in China

Ambient fine particulate matter (P

Differential responses of carbon-degrading enzyme activities to warming: implications for soil respiration

Extracellular enzymes catalyze rate‐limiting steps in soil organic matter decomposi-tion, and their activities (EEAs) play a key role in determining soil respiration (SR).Both EEAs and SR are highly sensitive to temperature, but their responses to cli-mate warming remain poorly understood. Here, we present a meta‐analysis on theresponse of soil cellulase and ligninase activities and SR to warming, synthesizingdata from 56 studies. We found that warming significantly enhanced ligninase activ-ity by 21.4% but had no effect on cellulase activity. Increases in ligninase activitywere positively correlated with changes in SR, while no such relationship was foundfor cellulase. The warming response of ligninase activity was more closely related tothe responses of SR than a wide range of environmental and experimental method-ological factors. Furthermore, warming effects on ligninase activity increased withexperiment duration. These results suggest that soil microorganisms sustain long‐term increases in SR with warming by gradually increasing the degradation of therecalcitrant carbon pool

Mitigating NO_x emissions does not help alleviate wintertime particulate pollution in Beijing-Tianjin-Hebei (BTH), China

Stringent mitigation measures have reduced wintertime PM_(2.5) concentrations by 42.2% from 2013 to 2018 in the BTH. The observed nitrate aerosols have not exhibited a significant decreasing trend and constituted a major fraction (about 20%) of the total PM_(2.5), although the surface-measured NO₂ level has decreased by over 20%. It still remains elusive about contributions of nitrogen oxides (NO_x) emissions mitigation to the nitrate and PM_(2.5) level. The WRF-Chem model simulations of a persistent haze episode in January 2019 in the BTH reveal that NO_x emissions mitigation does not help lower wintertime nitrate and PM_(2.5) concentrations under current conditions in the BTH, because the substantial O₃ increase induced by NO_x mitigation offsets the HNO₃ loss and enhances sulfate and secondary organic aerosols formation. Our results are further consolidated by occurrence of the severe PM pollution in the BTH during the COVID-19 outbreak with a significant reduction of NO₂

Mitigating NO_x emissions does not help alleviate wintertime particulate pollution in Beijing-Tianjin-Hebei (BTH), China

Stringent mitigation measures have reduced wintertime PM_(2.5) concentrations by 42.2% from 2013 to 2018 in the BTH. The observed nitrate aerosols have not exhibited a significant decreasing trend and constituted a major fraction (about 20%) of the total PM_(2.5), although the surface-measured NO₂ level has decreased by over 20%. It still remains elusive about contributions of nitrogen oxides (NO_x) emissions mitigation to the nitrate and PM_(2.5) level. The WRF-Chem model simulations of a persistent haze episode in January 2019 in the BTH reveal that NO_x emissions mitigation does not help lower wintertime nitrate and PM_(2.5) concentrations under current conditions in the BTH, because the substantial O₃ increase induced by NO_x mitigation offsets the HNO₃ loss and enhances sulfate and secondary organic aerosols formation. Our results are further consolidated by occurrence of the severe PM pollution in the BTH during the COVID-19 outbreak with a significant reduction of NO₂

Contributions of residential coal combustion to the air qualityin Beijing–Tianjin–Hebei (BTH), China: a case study

In the present study, the WRF-Chem model is used to assess contributions of residential coal combustion (RCC) emissions to the air quality in Beijing-Tianjin-Hebei (BTH) during a persistent air pollution episode from 9 to 25 January 2014. In general, the predicted temporal variations and spatial distributions of the mass concentrations of air pollutants are in good agreement with observations at monitoring sites in BTH. The WRF-Chem model also reasonably reproduces the temporal variations in aerosol species when compared with the aerosol mass spectrometer measurements in Beijing. The RCC emissions play an important role in the haze formation in BTH, contributing about 23.1% of PM2.5 (fine particulate matter) and 42.6% of SO2 during the simulation period on average. Organic aerosols dominate the PM2.5 from the RCC emissions in BTH, with a contribution of 42.8 %, followed by sulfate (17.1 %). The air quality in Beijing is remarkably improved when the RCC emissions in BTH and the surrounding areas are excluded in model simulations, with a 30% decrease in PM2.5 mass concentrations. However, if only the RCC emissions in Beijing are excluded, the local PM2.5 mass concentration is decreased by 18.0% on average. Our results suggest that the implementation of the residential coal replacement by clean energy sources in Beijing is beneficial to the local air quality. Should residential coal replacement be carried out in BTH and its surrounding areas, the air quality in Beijing would be improved remarkably. Further studies would need to consider uncertainties in the emission inventory and meteorological fields

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure