New challenges are emerging in fine-scale air quality modeling in China due to a lack of high-resolution emission maps.Currently,only a few emission sources have accurate geographic locations(point sources),while a la...New challenges are emerging in fine-scale air quality modeling in China due to a lack of high-resolution emission maps.Currently,only a few emission sources have accurate geographic locations(point sources),while a large part of sources,including industrial plants,are estimated as provincial totals(area sources)and spatially disaggregated onto grid cells based on proxies;this approach is reasonable to some extent but is highly questionable at fine spatial resolutions.Here,we compile a new comprehensive point source database that includes nearly 100,000 industrial facilities in China.We couple it with the frame of Multi-resolution Emission Inventory for China(MEIC),estimate point source emissions,combine point and area sources,and finally map China’s anthropogenic emissions of 2013 at the spatial resolution of 30’’*30’’(~1 km).Consequently,the percentages of point source emissions in the total emissions increase from less than 30%in the MEIC up to a maximum of 84%for SO_(2)in 2013.The new point source-based emission maps show the uncoupled distribution of emissions and populations in space at fine spatial scales,however,such a pattern cannot be reproduced by any spatial proxy used in the conventional emissions mapping.This new accurate high-resolution emission mapping approach reduces the modeled biases of air pollutant concentrations in the densely populated areas compared to the raw MEIC inventory,thus improving the assessment of population exposure.展开更多
The rapid growth of China’s economy has led to severe air pollution characterized by acid rain,severe pollu-tion in cities,and regional air pollution.High concentrations are found for various pollutants such as sulfu...The rapid growth of China’s economy has led to severe air pollution characterized by acid rain,severe pollu-tion in cities,and regional air pollution.High concentrations are found for various pollutants such as sulfur dioxides(SO2),nitrogen oxides(NOx),and fine particulates.Great efforts have thus been undertaken for the control of air pollution in the country.This paper discusses the development and application of appropriate technologies for reducing the major pollutants produced by coal and vehicles,and investi-gates air quality modeling as an important support for policy-making.展开更多
Spatial distributions of traffic-related pollutants in street canyons were investigated by field measurements and Computational Fluid Dynamics （CFD）. Two typical street canyons were selected for field monitoring, an...Spatial distributions of traffic-related pollutants in street canyons were investigated by field measurements and Computational Fluid Dynamics （CFD）. Two typical street canyons were selected for field monitoring, and a three-dimensional numerical model was built based on Reynolds-averaged Navier-Stokes equations equipped with the standard κ-ε turbulence models for CFD simulations. The study shows that the pollutant concentrations of vehicle emission correlate well with the traffic volume variation, wind direction and wind speed. The wind direction and speed at the roof level determine overwhellmingly the flow field and the distributions of pollutant concentrations in the street canyon. When the wind speed is equal to zero, the pollutant concentrations on the breath height of the both sides of the street canyon are almost the same. When the wind direction is perpendicular to the street, one main vortex is formed with a shape depending on the building structure on both sides of the street, the pollutant is accumulated on the leeward side, and the pollutant concentrations at the breath height on the leeward side are 2 to 3 times as those at the breath height on the windward side. If the wind direction makes some angles with the street canyon, the pollutant concentration will be higher on the leeward side because one main vortex will also be formed in the vertical section of the canyon by the perpendicular component of the wind. But pollutant concentrations decrease in the canyon because pollutants are dispersed along the axis of the street. Pollutants at different heights of the vertical section decrease with height, i.e. there are concentration gradients in the vertical section, and the pollutant concentrations on the leeward side of the upstream building are much higher than those on the windward side of the downstream building.展开更多
The arginine-vasopressin(AVP)hormone plays a pivotal role in regulating various physiological processes,such as hormone secretion,cardiovascular modulation,and social behavior.Recent studies have highlighted the V1a r...The arginine-vasopressin(AVP)hormone plays a pivotal role in regulating various physiological processes,such as hormone secretion,cardiovascular modulation,and social behavior.Recent studies have highlighted the V1a receptor as a promising therapeutic target.In-depth insights into V1a receptor-related pathologies,attained through in vivo imaging and quantification in both peripheral organs and the central nervous system(CNS),could significantly advance the development of effective V1a inhibitors.To address this need,we develop a novel V1a-targeted positron emission tomography(PET)ligand,[18F]V1A-2303([18F]8),which demonstrates favorable in vitro binding affinity and selectivity for the V1a receptor.Specific tracer binding in peripheral tissues was also confirmed through rigorous cell uptake studies,autoradiography,biodistribution assessments.Furthermore,[18F]8 was employed in PET imaging and arterial blood sampling studies in healthy rhesus monkeys to assess its brain permeability and specificity,whole-body distribution,and kinetic properties.Our research indicated[18F]8 as a valuable tool for noninvasively studying V1a receptors in peripheral organs,and as a foundational element for the development of next-generation,brain-penetrant ligands specifically designed for the CNS.展开更多
A modified CQESTR model, a simple yet useful model frequently used for estimating carbon sequestration in agricultural soils, was developed and applied to evaluate the effects of intensive cropping on soil organic mat...A modified CQESTR model, a simple yet useful model frequently used for estimating carbon sequestration in agricultural soils, was developed and applied to evaluate the effects of intensive cropping on soil organic matter （SOM） dynamics and mineralization as well as to estimate carbon dioxide emission from agricultural soils at seven sites on the Huang-Huai-Hai Plain of China. The model was modified using site-specific parameters from short- and mid-term buried organic material experiments at four stages of biomass decomposition. The predicted SOM results were validated using independent data from seven long-term （10- to 20-year） soil fertility experiments in this region. Regression analysis on 1 151 pairs of predicted and measured SOM data had an r2 of 0.91 （P≤0.01）. Therefore, the modified model was able to predict the mineralization of crop residues, organic amendments, and native SOM. Linear regression also showed that SOM mineralization rate （MR） in the plow layer increased by 0.22% when annual crop yield increased by 1 t ha^-1 （P ≤ 0.01）, suggesting an improvement in SOM quality. Apparently, not only did the annual soil respiration efftux merely reflect the intensity of soil organism and plant metabolism, but also the SOM MR in the plow layer. These results suggested that the modified model was simple yet valuable in predicting SOM trends at a single agricultural field and could be a powerful tool for estimating C-storage potential and reconstructing C storage on the Huang-Huai-Hai Plain of China.展开更多
基金supported by the National Natural Science Foundation of China(91744310,41625020 and 41921005)the National Research Program for Key Issues in Air Pollution Control(DQGG0201)。
文摘New challenges are emerging in fine-scale air quality modeling in China due to a lack of high-resolution emission maps.Currently,only a few emission sources have accurate geographic locations(point sources),while a large part of sources,including industrial plants,are estimated as provincial totals(area sources)and spatially disaggregated onto grid cells based on proxies;this approach is reasonable to some extent but is highly questionable at fine spatial resolutions.Here,we compile a new comprehensive point source database that includes nearly 100,000 industrial facilities in China.We couple it with the frame of Multi-resolution Emission Inventory for China(MEIC),estimate point source emissions,combine point and area sources,and finally map China’s anthropogenic emissions of 2013 at the spatial resolution of 30’’*30’’(~1 km).Consequently,the percentages of point source emissions in the total emissions increase from less than 30%in the MEIC up to a maximum of 84%for SO_(2)in 2013.The new point source-based emission maps show the uncoupled distribution of emissions and populations in space at fine spatial scales,however,such a pattern cannot be reproduced by any spatial proxy used in the conventional emissions mapping.This new accurate high-resolution emission mapping approach reduces the modeled biases of air pollutant concentrations in the densely populated areas compared to the raw MEIC inventory,thus improving the assessment of population exposure.
文摘The rapid growth of China’s economy has led to severe air pollution characterized by acid rain,severe pollu-tion in cities,and regional air pollution.High concentrations are found for various pollutants such as sulfur dioxides(SO2),nitrogen oxides(NOx),and fine particulates.Great efforts have thus been undertaken for the control of air pollution in the country.This paper discusses the development and application of appropriate technologies for reducing the major pollutants produced by coal and vehicles,and investi-gates air quality modeling as an important support for policy-making.
基金Project supported by the National Natural Science Foundation of China (Grant No 50808124)the China Postdoctoral Science Foundation (Grant No 20060400647)
文摘Spatial distributions of traffic-related pollutants in street canyons were investigated by field measurements and Computational Fluid Dynamics （CFD）. Two typical street canyons were selected for field monitoring, and a three-dimensional numerical model was built based on Reynolds-averaged Navier-Stokes equations equipped with the standard κ-ε turbulence models for CFD simulations. The study shows that the pollutant concentrations of vehicle emission correlate well with the traffic volume variation, wind direction and wind speed. The wind direction and speed at the roof level determine overwhellmingly the flow field and the distributions of pollutant concentrations in the street canyon. When the wind speed is equal to zero, the pollutant concentrations on the breath height of the both sides of the street canyon are almost the same. When the wind direction is perpendicular to the street, one main vortex is formed with a shape depending on the building structure on both sides of the street, the pollutant is accumulated on the leeward side, and the pollutant concentrations at the breath height on the leeward side are 2 to 3 times as those at the breath height on the windward side. If the wind direction makes some angles with the street canyon, the pollutant concentration will be higher on the leeward side because one main vortex will also be formed in the vertical section of the canyon by the perpendicular component of the wind. But pollutant concentrations decrease in the canyon because pollutants are dispersed along the axis of the street. Pollutants at different heights of the vertical section decrease with height, i.e. there are concentration gradients in the vertical section, and the pollutant concentrations on the leeward side of the upstream building are much higher than those on the windward side of the downstream building.
基金the National Natural Science Foundation of China(Nos.82071974,82102107,and 82371998)the Science and Technology Program of Guangzhou,China(Nos.202206010106 and 2023A04J1921)the Guangdong Science and Technology Planning Project,China(2022A0505050042).
文摘The arginine-vasopressin(AVP)hormone plays a pivotal role in regulating various physiological processes,such as hormone secretion,cardiovascular modulation,and social behavior.Recent studies have highlighted the V1a receptor as a promising therapeutic target.In-depth insights into V1a receptor-related pathologies,attained through in vivo imaging and quantification in both peripheral organs and the central nervous system(CNS),could significantly advance the development of effective V1a inhibitors.To address this need,we develop a novel V1a-targeted positron emission tomography(PET)ligand,[18F]V1A-2303([18F]8),which demonstrates favorable in vitro binding affinity and selectivity for the V1a receptor.Specific tracer binding in peripheral tissues was also confirmed through rigorous cell uptake studies,autoradiography,biodistribution assessments.Furthermore,[18F]8 was employed in PET imaging and arterial blood sampling studies in healthy rhesus monkeys to assess its brain permeability and specificity,whole-body distribution,and kinetic properties.Our research indicated[18F]8 as a valuable tool for noninvasively studying V1a receptors in peripheral organs,and as a foundational element for the development of next-generation,brain-penetrant ligands specifically designed for the CNS.
基金Project supported by the National Key Technologies Research and Development Program of China during the 10th Five-Year Plan Period (No. 2004BA520A14C02) and the Program for Changjiang Scholars and Innovative Research Team in University of China (No. IRT0412).
文摘A modified CQESTR model, a simple yet useful model frequently used for estimating carbon sequestration in agricultural soils, was developed and applied to evaluate the effects of intensive cropping on soil organic matter （SOM） dynamics and mineralization as well as to estimate carbon dioxide emission from agricultural soils at seven sites on the Huang-Huai-Hai Plain of China. The model was modified using site-specific parameters from short- and mid-term buried organic material experiments at four stages of biomass decomposition. The predicted SOM results were validated using independent data from seven long-term （10- to 20-year） soil fertility experiments in this region. Regression analysis on 1 151 pairs of predicted and measured SOM data had an r2 of 0.91 （P≤0.01）. Therefore, the modified model was able to predict the mineralization of crop residues, organic amendments, and native SOM. Linear regression also showed that SOM mineralization rate （MR） in the plow layer increased by 0.22% when annual crop yield increased by 1 t ha^-1 （P ≤ 0.01）, suggesting an improvement in SOM quality. Apparently, not only did the annual soil respiration efftux merely reflect the intensity of soil organism and plant metabolism, but also the SOM MR in the plow layer. These results suggested that the modified model was simple yet valuable in predicting SOM trends at a single agricultural field and could be a powerful tool for estimating C-storage potential and reconstructing C storage on the Huang-Huai-Hai Plain of China.
