SCOPE: Effects of dairy consumption on body weight and body composition have been inconsistently observed in randomized control trials (RCTs). Our meta-analysis aims to systematically evaluate the effects of dairy consumption on body weight and body composition among the adults. METHODS AND RESULTS: We conducted a comprehensive search of the Cochrane Library, PubMed, and Embase databases of the relevant studies from 1966 to Mar 2017 regarding dairy consumption on body weight and body composition including body fat, lean mass, and waist circumference (WC). The summary results are pooled by using a random-effects meta-analysis. Thirty-seven RCTs with 184 802 participants are included in this meta-analysis. High dairy intervention increased body weight (0.01, 95% CI: -0.25, 0.26, I(2) = 78.3%) and lean mass (0.37, 95% CI: 0.11, 0.62, I(2) = 83.4%); decreased body fat (-0.23, 95% CI: -0.48, 0.02, I(2) = 78.2%) and WC (-1.37, 95% CI: -2.28, -0.46, I(2) = 98.9%) overall. In the subgroup analysis, we found that consumption of dairy products increases body weight (0.36, 95% CI: 0.01, 0.70, I(2) = 83.1%) among participants without energy restriction. Dairy consumption decreases body weight (-0.64, 95% CI: -1.05, -0.24, I(2) = 60.2%), body fat (-0.56, 95%CI: -0.95, -0.17, I(2) = 66.6%), and waist circumference (-2.18, 95%CI: -4.30, -0.06, I(2) = 99.0%) among the adults with energy restriction. CONCLUSIONS: This meta-analysis suggests a beneficial effect of energy-restricted dairy consumption on body weight and body composition. However, high dairy consumption in the absence of caloric restriction may increase body weight.
China is an agricultural country with the largest population in the world. However, intensification of droughts and floods has substantial impacts on agricultural production. For effective agricultural disaster management, it is significant to understand and quantify the influence of droughts and floods on crop production. Compared with droughts, the influence of floods on crop production and a comprehensive evaluation of effects of droughts and floods are given relatively less attention. The impact of droughts and floods on crop production is therefore investigated in this study, considering spatial heterogeneity with disaster and yield datasets for 1949-2015 in China mainland. The empirical relationships between drought and flood intensity and yield fluctuation for grain, rice, wheat, maize and soybean are identified using a Bayesian hierarchical model. They are then used to explore what social-economic factors influenced the grain sensitivity to droughts and floods by the Pearson's coefficient and locally weighted regression (LOSEE) plots. The modeling results indicate that: (a) droughts significantly reduce grain yields in 28 of 31 provinces and obvious spatial variability in drought sensitivity exists, with Loess Plateau having highest probability of crop failure caused by droughts; (b) floods significantly reduce grain yield in 20 provinces, while show positive effect in the northwestern and southwestern China; (c) the spatial patterns of influence direction of droughts and floods on rice, maize and soybean are consistent with the grain's results; and (d) promoting capital investments and improving access to technical inputs (fertilizer, pesticide, and irrigation) can help effectively buffer grain yield lose from droughts.
Nocturnal reactive nitrogen compounds play an important role in regional air pollution. Here we present the measurements of dinitrogen pentoxide (N2O5) associated with nitryl chloride (ClNO2) and particulate nitrate (pNO(3)(-)) at a suburban site of Beijing in the summer of 2016. High levels of N2O5 and ClNO2 were observed in the outflow of the urban Beijing air masses, with 1 min average maxima of 937 and 2900 pptv, respectively. The N2O5 uptake coefficients, gamma, and ClNO2 yield, f, were experimentally determined from the observed parameters. The N2O5 uptake coefficient ranged from 0.012 to 0.055, with an average of 0.034 +/- 0.018, which is in the upper range of previous field studies reported in North America and Europe but is a moderate value in the North China Plain (NCP), which reflects efficient N2O5 heterogeneous processes in Beijing. The ClNO2 yield exhibited high variability, with a range of 0.50 to unity and an average of 0.73 +/- 0.25. The concentration of the nitrate radical (NO3) was calculated assuming that the thermal equilibrium between NO3 and N2O5 was maintained. In NOx-rich air masses, the oxidation of nocturnal biogenic volatile organic compounds (BVOCs) was dominated by NO3 rather than O-3. The production rate of organic nitrate (ON) via NO3 + BVOCs was significant, with an average of 0.10 +/- 0.07 ppbvh(-1). We highlight the importance of NO3 oxidation of VOCs in the formation of ON and subsequent secondary organic aerosols in summer in Beijing.
Nocturnal reactive nitrogen compounds play an important role in regional air pollution. Here we present the measurements of dinitrogen pentoxide (N2O5) associated with nitryl chloride (ClNO2) and particulate nitrate (pNO3-) in a suburban site of Beijing in the summer of 2016. High levels of N2O5 and ClNO2 were observed in the outflow of the urban Beijing air masses, with 1-min average maxima of 937 pptv and 2900 pptv, respectively. The N2O5 uptake coefficients, γ, and ClNO2 yield, f, were experimentally determined from the observed parameters. The N2O5 uptake coefficient ranged from 0.012 to 0.055, with an average of 0.034 ± 0.018, which is in the upper range of previous field studies reported in North America and Europe but is a moderate value in the North China Plain (NCP), which reflects efficient N2O5 heterogeneous processes in Beijing. The ClNO2 yield exhibited high variability, with a range of 0.50 to unity and an average of 0.73 ± 0.25. The concentration of the nitrate radical (NO3) was calculated assuming that the thermal equilibrium between NO3 and N2O5 was maintained. In NOx-rich air masses, the oxidation of nocturnal biogenic volatile organic compounds (BVOCs) was dominated by NO3 rather than O3. The production rate of organic nitrate (ON) via NO3+BVOCs was significant, with an average of 0.10 ± 0.07 ppbv h-1. We highlight the importance of NO3 oxidation of VOCs in the formation of ON and subsequent secondary organic aerosols in summer in Beijing.
Gyrotron oscillator, as one kind of efficient terahertz (THz) source, is developed with the capability of frequency and power tuning to meet diverse application demands. Due to system nonlinearity, it is quite difficult to achieve high frequency stabilization (FS) during power tuning without using external auxiliary components. This paper proposes an FS scheme with simultaneous power tuning in gyrotron backward-wave oscillator state. This is realized by compensating the detuning electron cyclotron frequency during the electronic tuning process. The required quasi-linear relationship between the electron-beam pitch factor and the accelerating voltage is numerically verified by using the SLAC EGUN code. The investigation focuses on a Watt-level open-cavity gyrotron oscillator. The tens-of-Watts-level output power can be tuned by over 40% at the FS point, and especially the self-adaptive FS reaches the accuracy of about 10-MHz level. The proposed scheme would be attractive for the high-stability THz-wave heating in material sciences and biomedicines.
The oil sands (OS) of Alberta, Canada, which are classified as unconventional oil, are the third-largest oil reserves in the world. We describe here a 6-year effort to improve the emissions data used for air quality (AQ) modeling of the roughly 100 km x 100 km oil extraction and processing industrial complex operating in the Athabasca Oil Sands Region (AOSR) of northeastern Alberta. This paper reviews the national, provincial, and sub-provincial emissions inventories that were available during the three phases of the study, supplemented by hourly SO2 and NOx emissions and stack characteristics for larger point sources measured by a continuous emission monitoring system (CEMS), as well as daily reports of SO2 from one AOSR facility for a 1-week period during a 2013 field campaign when the facility experienced upset conditions. Next it describes the creation of several detailed hybrid emissions inventories and the generation of model-ready emissions input files for the Global Environmental Multiscale-Modelling Air quality and CHemistry (GEM-MACH) AQ modeling system that were used during the 2013 field study and for various post-campaign GEM-MACH sensitivity studies, in particular for a high-resolution model domain with 2.5 km grid spacing covering much of western Canada and centered over the AOSR. Lastly, it compares inventory-based bottom-up emissions with aircraft-observation-based top-down emissions estimates. Results show that emissions values obtained from different data sources can differ significantly, such as a possible 10-fold difference in PM2.5 emissions and approximately 40 and 20% differences for total VOC (volatile organic compound) and SO2 emissions. A novel emissions-processing approach was also employed to allocate emissions spatially within six large AOSR mining facilities in order to address the urban-scale spatial extent of the facilities and the high-resolution 2.5 km model grid. Gridded facility-and process-specific spatial surrogate fields that were generated using spatial information from GIS (geographic information system) shapefiles and satellite images were used to allocate non-smokestack emissions for each facility to multiple grid cells instead of treating these emissions as point sources and allocating them to a single grid cell as is normally done. Facility-and process-specific temporal profiles and VOC speciation profiles were also developed. The pre-2013 vegetation and land-use databases normally used to estimate biogenic emissions and meteorological surface properties were modified to account for the rapid change in land use in the study area due to marked, year-by-year changes in surface mining activities, including the 2013 opening of a new mine. Lastly, mercury emissions data were also processed in addition to the seven criteria-air-contaminant (CAC) species (NO x, VOC, SO2, NH3, CO, PM2.5, and PM10) to support AOSR mercury modeling activities. Six GEM-MACH modeling papers in this special issue used some of these new sets of emissions and land-use input files.