Fire emissions generate air pollutants ozone (O
) and aerosols that influence the land carbon cycle. Surface O
damages vegetation photosynthesis through stomatal uptake, while aerosols influence ...photosynthesis by increasing diffuse radiation. Here we combine several state-of-the-art models and multiple measurement datasets to assess the net impacts of fire-induced O
damage and the aerosol diffuse fertilization effect on gross primary productivity (GPP) for the 2002-2011 period. With all emissions except fires, O
decreases global GPP by 4.0 ± 1.9 Pg C yr
while aerosols increase GPP by 1.0 ± 0.2 Pg C yr
with contrasting spatial impacts. Inclusion of fire pollution causes a further GPP reduction of 0.86 ± 0.74 Pg C yr
during 2002-2011, resulting from a reduction of 0.91 ± 0.44 Pg C yr
by O
and an increase of 0.05 ± 0.30 Pg C yr
by aerosols. The net negative impact of fire pollution poses an increasing threat to ecosystem productivity in a warming future world.
Drought can have a substantial impact on the ecosystem and agriculture of the affected region and does harm to local economy. This study aims to analyze the relation between soil moisture and drought ...and predict agricultural drought in Xiangjiang River basin. The agriculture droughts are presented with the Precipitation-Evapotranspiration Index (SPEI). The Support Vector Regression (SVR) model incorporating climate indices is developed to predict the agricultural droughts. Analysis of climate forcing including El Niño Southern Oscillation and western Pacific subtropical high (WPSH) are carried out to select climate indices. The results show that SPEI of six months time scales (SPEI-6) represents the soil moisture better than that of three and one month time scale on drought duration, severity and peaks. The key factor that influences the agriculture drought is the Ridge Point of WPSH, which mainly controls regional temperature. The SVR model incorporating climate indices, especially ridge point of WPSH, could improve the prediction accuracy compared to that solely using drought index by 4.4% in training and 5.1% in testing measured by Nash Sutcliffe efficiency coefficient (NSE) for three month lead time. The improvement is more significant for the prediction with one month lead (15.8% in training and 27.0% in testing) than that with three months lead time. However, it needs to be cautious in selection of the input parameters, since adding redundant information could have a counter effect in attaining a better prediction.
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•The SVR model is applied in agricultural drought prediction in Xiangjiang River basin.•Drought index SPEI-6 is recommended to reflect the soil moisture condition.•Ridge point of WPSH is the key factor affecting SPEI-6 mainly through temperature.•Prediction of drought could be improved by incorporating climate indices in SVR model.
Assessments of climate change impacts on streamflow and sediment processes are essential for developing science‐based sustainable watershed management plans. We assessed climate change impacts on ...streamflow and sediment load in the upstream of the Mekong River Basin, as a case study. Future climate scenarios including an ensemble‐mean climate scenario (EnM scenario) were generated based on 20 GCMs in CMIP5, using a stochastic weather generator (LARS‐WG) coupled with a distribution‐free shuffle procedure. The SWAT model was applied to simulate changes in streamflow and sediment load for the future period 2071–2100 under RCP8.5 with respect to the baseline period 1971–2000. Results show that mean monthly maximum and minimum temperature were projected to increase by all the 20 GCMs, with an ensemble‐mean increase of 4.6–5.7°C and 4.2–5.8°C across the 12 months, respectively. An increase in mean annual precipitation (3.4–55.8%) and streamflow (1.0–72.7%) was also projected by all GCMs. However, projected changes in sediment load were not consistent. One half of the GCMs projected an increase (5.2–53.2%) in annual sediment load while the other half projected a decrease (5.1%–43.2%). In each month, at least three‐quarters of the GCMs projected an increase in monthly streamflow. For monthly sediment load, an increase in May to July was projected by over half of the GCMs, while a decrease was projected by a majority of the GCMs for other months. Our results indicate large uncertainties in streamflow and sediment projections under climate change, demonstrating the need to use multi‐model ensembles in climate change impact studies. Moreover, it was found that the streamflow and sediment loads simulated using the EnM scenario were often close to the ensemble means simulated using the 20 GCMs, which implies that the single EnM scenario has the potential of effectively and efficiently estimating the ensemble means of projections in a multi‐model ensemble.
Future temperature, precipitation and streamflow are projected to increase but uncertainties are large. Projected changes in sediment load are not consistent and more uncertain than streamflow. A single ensemble‐mean climate scenario generated using a stochastic approach has the potential of effectively estimating ensemble means of the simulated streamflow and sediment load in a multi‐GCM ensemble.
Recent results from the proton-proton collision data taken by the ATLAS experiment on exotic resonances are presented. A search for J/\psi p J / ψ p resonances in \Lambda_{b}→ J/\psi p K Λ b → J / ψ ...p K decays with large p K p K invariant masses is reported. A search for exotic resonances in the four-muon final state is shown.
Due to drastic decreasing in mechanical properties at relative high temperature, traditional nickel based super alloys are replaced by Si-based non-oxide ceramics in the application of high ...temperature aero-engines. In order to reduce the spallation and deformation of aero-engine blades in the environment containing high temperature water vapor and oxygen, protection coatings on the surface of the ceramics are required. Owing to high temperature stability, superior oxidation resistance and corrosion resistance properties, rare earth (RE) silicates are promising as candidates and play an important role in improving the high-temperature mechanical/thermal properties of Si-based non-oxide ceramics. In this review, recent progress in the research and development of environmental barrier coatings (EBCs) are summarized. Development of EBCs is presented, and the multi-scale structures and properties of each part are introduced. In addition, the merits and demerits of each preparation technique are discussed. As a promising candidate for the application in high temperature aero-engines, Si/mullite/Lu2Si2O7–Lu2SiO5 EBCs are highlighted.
Innovation-driven development strategies have injected new momentum into haze management. In addition to its core innovation-driven role, innovative city pilot policy is significant for environmental ...enhancement and should not be overlooked. To assess the performance of the pilot policy in decreasing haze, a multiperiod double difference model was employed, and a spatial econometric model was used to empirically examine the potential spatial spillover effect of haze management as a regional synergistic concept between 2006 and 2020. Panel data from 282 prefecture-level cities were selected. To investigate and empirically examine the territorial spillover effect of haze reduction as a regional synergistic notion, a spatial econometric model was applied. Based on the study, the pilot construction significantly reduced haze pollution. In China’s eastern and central regions, small cities, and newer industrial bases, the inhibitory effect of pilot policies on haze pollution was more pronounced, according to heterogeneity analysis. Moreover, analysis of the heterogeneous environmental regulations revealed that the enforcement of policies would increase the sense of urgency of local governments, strengthen the concern and responsibility of the government for the environment, and further awaken the public’s concern for the environment, in addition to forcing enterprises to practice clean and sustainable production, thus achieving the effect of accelerated haze reduction. From the spatial perspective, innovative pilot cities have certain spatial spillover effects and thus can increase the effects of policy for neighboring regions, similar economic regions and local transportation regions.
Under the background of aging, how to make the elderly live comfortably and improve the quality of life have all become the main problems solved by the current society. Based on the relevant ...theoretical foundation, this paper constructs a aging adaptation design model of the urban residential environment. Principal component analysis and factor analysis are employed to simplify the data structure of living environment design and decrease the complexity of data analysis. Regression analysis and structural equations are combined to investigate the relationship between the living environment and age appropriateness. PLS regression analysis was used to solve the external weights or factor loadings to obtain the estimates of the latent variables and the path coefficients among the latent variables. To demonstrate the reasonableness of the factors influencing the quality of the environment, the reliability and validity of the perceived quality are analyzed. Combining the basic attributes and needs of the elderly is the basis of proposing an aging-friendly environment design strategy. The results show that In terms of architectural spatial perception, the master bedroom space scale exceeds 3.92m × 4.61m, which is a relatively optimal choice that can simultaneously meet the diversified needs of the family’s living behavior at different stages. In terms of road accessibility and greening perception, the width of the age-appropriate walkway can vary depending on different locations and the unit time flow of people. In the era of artificial intelligence, the design of the aging-adapted living environment should fully consider the physiological characteristics of the elderly and formulate more suitable living data for the elderly.
Snow and glacier are important components in the hydrological cycle of the Tibetan Plateau (TP). Air temperature, as the main driver in freezing and thawing processes, becomes vital for hydrological ...modelling and prediction in this region. Due to a sparse ground gauging network, spatial density of air temperature measurement is insufficient for hydro‐meteorological studies. Therefore, the aim of this study is to identify the best representative temperature data for hydrological applications from four widely used reanalysis products, including ERA‐Interim, ERA‐5, GLDAS‐2.1 and NCEP‐R2, with reference to in situ measurements and gridded snow depth from the year 2008–2017 over the entire TP. To reduce errors, Bayesian Joint Probability (BJP) approach based on K‐Nearest Neighbour (KNN) classification algorithm (KNN‐BJP) is proposed to post‐process gridded reanalyses. The results indicate that all the reanalysis datasets provide highly correlated but cold biased air temperature. The correlation ecoefficiency is greater than 0.85. The cold biases are near −3 ° C and mainly distributed in the southeastern TP. Bias in daily maximum temperature during Spring is greater than −8 ° C for most stations. ERA‐Interim is found to have the closest agreement with in situ measurements, closely followed by GLDAS‐2.1. KNN‐BJP is found to be effective within a distance smaller than 5°. After post‐processing, the prominent underestimation is efficiently corrected with Bias near 0. RMSE is markedly reduced to be smaller than 2.5 ° C. The post‐processed ERA‐5 and GLDAS‐2.1 are as accurate as ERA‐Interim, but able to provide more detailed information for extreme events due to their finer spatial resolution. Thus, ERA‐5 and GLDAS‐2.1 are more recommended to represent air temperature in the TP. Snow depth as complementary reference data is able to present spatial variance of air temperature. Our study can help alleviate the problem of sparse air temperature data over the TP.
Reanalysis datasets present high correlated but cold biased air temperature in the TP.
KNN‐BJP is found to be effective in correcting biases and the extrapolation distance to apply this post‐processing method is up to 5 ° .
ERA‐5 and GLDAS‐2.1reanalyses are more recommended to represent air temperature, and the coarse resolution for ERA‐Interim and NCEP‐R2 usually overlooks the detailed information, especially the regional extreme temperatures.
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