Exploring the effects of landscape structure onaerosol optical depth (AOD) patterns using GIS andHJ-1B images

A GIS approach and HJ-1B images were employed to determine the effect of landscape structure on aerosol optical depth (AOD) patterns. Landscape metrics, fractal analysis and contribution analysis were proposed to quantitatively illustrate the impact of land use on AOD patterns. The high correlation between the mean AOD and landscape metrics indicates that both the landscape composition and spatial structure affect the AOD pattern. Additionally, the fractal analysis demonstrated that the densities of built-up areas and bare land decreased from the high AOD centers to the outer boundary, but those of water and forest increased. These results reveal that the built-up area is the main positive contributor to air pollution, followed by bare land. Although bare land had a high AOD, it made a limited contribution to regional air pollution due to its small spatial extent. The contribution analysis further elucidated that built-up areas and bare land can increase air pollution more strongly in spring than in autumn, whereas forest and water have a completely opposite effect. Based on fractal and contribution analyses, the different effects of cropland are ascribed to the greater vegetation coverage from farming activity in spring than in autumn. The opposite effect of cropland on air pollution reveals that green coverage and human activity also influence AOD patterns. Given that serious concerns have been raised regarding the effects of built-up areas, bare land and agricultural air pollutant emissions, this study will add fundamental knowledge of the understanding of the key factors influencing urban air quality

Responses of soil microbial communities to nutrient limitation in thedesert-grassland ecological transition zone

Soil microorganisms are crucial to indicate ecosystem functions of terrestrial ecosystems. However, the responses of microbial communities to soil nutrient limitation in desert-grassland are still poorly understood. Hence, we investigated soil microbial community structures and metabolic characteristics in a desert-grassland ecological transition zone from the northern Loess Plateau, China, and explored the association of microbial communities with nutrient limitation via high-throughput sequencing. Threshold elemental ratios (TER) indicated that the microbial communities were strongly limited by nitrogen (N) under A. ordosica and P. tabuliformis communities. The phosphorus (P) limitation of microbial communities was observed in the aeolian sandy soil. The results imply that soil microbial communities had strong nutrient competition for N and P with aboveground vegetation in arid and oligotrophic ecosystems. The LEfSe and linear regression analysis revealed that the microbial taxa of Micrococcales, Micrococcaceae and Herpotrichiellaceae were significantly correlated with microbial N limitation. The Thermoleophilia taxa were significantly correlated with microbial P limitation. These biomarkers related to microbial nutrient limitation could be considered as the key microbial taxa to shape microbial communities and functions. Furthermore, N form had different effects on microbial communities, which NH4+-N strongly affected bacterial communities, whereas NO3--N had a significant influence on fungal communities. The different responses indicate that soil microorganisms had corresponding nutrient preferences for bacterial and fungal communities, which might alleviate the nutrient limitations and environmental stress. This study provided important insights on microbial community structures linking to community functions and on the mechanisms governing microbial N and P limitation in arid land ecosystems

Proper land use for heavy metal-polluted soil based on enzymeactivity analysis around a Pb-Zn mine in Feng County, China

Enzymes in the soil are useful for assessing heavy metal soil pollution. We analyzed the activity of a number of enzymes, including urease, protease, catalase, and alkaline phosphatase, in three types of land (farmland, woodland, and grassland) to evaluate soil pollution by heavy metals (Pb, Zn, and Cd). Our results showed that the tested soil was polluted by a combination of Pb, Zn, and Cd, but the primary pollutant was Cd. An ecological dose analysis demonstrated that urease was the most sensitive enzyme to Pb and Cd in the farmland, and catalase and phosphatase were the most sensitive enzymes to Pb, Zn, and Cd in the woodland and grassland. The ecological risk of Cd (E Cd ) was the smallest in all three types of land, suggesting that Cd was the major metal inhibiting enzyme activity. Electrical conductivity (EC) was shown to be a negative regulator, while nitrogen, phosphorus, and clay contents were positive regulators of soil enzyme activity. The total enzyme index (TEI) inhibition rates in the woodland were 22.2 and 38.6% under moderate and heavy pollution, respectively, which were lower than those of the other two types of land. Therefore, woodlands might be the optimum land use choice in relieving heavy metal pollution. Taken together, this study identified the key metal pollutant inhibiting soil enzyme activity and suitable land use patterns around typical metal mine. These results provide possible improvement strategies to the phytomanagement of metal-contaminated land around world

Responses of soil bacterial communities, enzyme activities, and nutrients to agricultural-to-natural ecosystem conversion in the Loess Plateau, China

PurposeSoil microbial communities play critical function during nutrient cycling. However, with the increasing nutrient input into terrestrial ecosystems from human activities, the responses of soil microorganisms to the aboveground vegetation across agricultural-to-natural succession stages are still poorly understand. The aim of this study was to evaluate the changes of soil microbial communities in three typical succession stages (the cropland, the grassland, and the brushland, respectively).Materials and methodsA field experiment was carried out in an ecological restoration region. Soil samples were collected from three succession stages (the cropland, the grassland, and the brushland) based on their well-dated successional chronosequence in July 2016. Illumina MiSeq sequencing was used to identify the bacterial community structures. The responses of soil bacterial communities and its relationships with soil physicochemical properties and enzyme activities were assessed.Results and discussionThe results showed that soil nutrients (soil organic carbon(SOC), total N, and NH4+) and enzyme activities (-1,4-glucosidase and phosphatase) were significantly increased across the conversion from agricultural to natural ecosystem, and the enzyme activities were significantly affected by SOC and total N. It indicated that vegetation restoration greatly improved soil quality and nutrient cycling rates mediated by microbial metabolisms. Furthermore, there were no changes in soil bacterial community structures during the three vegetation succession stages, which implied the stability and adaption of microbial communities under the vegetation succession in semiarid climate. It should be noted that Firmicutes taxa were more sensitive than other taxa during natural vegetation recovery. Structural equation model (SEM) revealed that soil nutrients (soil organic matter (SOM) and total P), element stoichiometry (SOC:total P), and extracellular enzyme activities (urease and alkaline phosphatase) were dominant factors to shape the relative abundance of Firmicutes.ConclusionsFirmicutes can be considered as bio-indicators to monitor soil quality and nutrient turnover during natural vegetation recovery. This study presents better understanding about the connections among soil nutrient cycling, enzyme activities, and soil bacterial communities during vegetation natural restoration, especially in typical ecological critical zone

Modeling spatiotemporal distribution of PM10 using HJ-1 CCD data in Luoyang, China

Previous studies have proved that the statistical models between satellite-retrieved aerosol optical depth (AOD) and ground-level PM10 provide a feasible and effective way to obtain the extensive and continuous spatial distribution of ground-level PM10. The two-year annual mean PM10 was 119.9 +/- 66.5 mu g/ m(3) from 2014 to 2015, which significantly exceeded the annual WHO IT-1 standard for PM10 (70 mg/ m3), and the mean AOD was 0.56 +/- 0.21 in Luoyang. Statistical models were proposed using a combination of HJ-1 (Environment Satellite 1) CCD (charge-coupled device) AOD and PM10 acquired at monitoring sites. The fitting analysis of PM10 and AOD shows that PM10 agrees well with AOD, and the linear regression model is the most accurate one. By the land-use function analysis of PM10 hotspots using Google Earth, it is apparent that the prevalence of industrial or bare soil areas is the key factor in determining anthropogenic pollutant emissions. In view of the small HJ-1 data available for analyzing and the limitation of dark target algorithm in the season with sparse vegetation cover, further investigation should be conducted for a more accurate understanding of the PM10 monitoring. Despite the limitations of this work, the results prove the feasibility of retrieving remote sensing images for monitoring regional aerosol pollution, together with ground-level data. The combination of satellite images, ground monitoring and Google earth can help to better understand the spatial distributions and sources of PM on a regional scale. (C) 2016 Turkish National Committee for Air Pollution Research and Control. Production and hosting by Elsevier B.V. All rights reserved

Dominant factor affecting Pb speciation and the leaching risk among land- use types around Pb-Zn mine

Soil lead (Pb) pollution around the mining area has severely threaten human health. However, Pb leaching risk in soils with different land uses and which is the proper land use are still unknown. In this work, Pb speciation characteristics and the dominant soil factors affecting Pb speciation in three land uses (farmland, woodland, and grassland) surrounding the Pb-Zn mine in Feng Country, Shaanxi province were investigated. Moreover, the Pb leaching risk and associated determining factors were evaluated by the combination of leached Pb concentration and structural equation model (SEM). The results showed that farmland presented the highest total Pb content (410.1 mg kg(-1)) among three land use types. The reducible fraction of Pb (Fe-Mn oxides bound) was the major speciation ( > 50%) in all tested soils of three land-use types. Soil total phosphorus (TP), water content (WC), and pH play major role in regulating Pb speciation. Though soil biological properties, like microbial communities, catalase, and microbial biomass nitrogen (MBN) exhibited distinct responses to three different land uses, they showed minor influence on Pb speciation. More interestingly, SEM analysis indicated that Pb leaching risk was directly linked with bacteria abundance, total Pb content, clay content, and C/N. Grassland presented the higher predicted Pb leaching concentration (85.03 mg kg(-1)), compared with that in woodland, suggesting that grassland was the worst land-use type to buffer the Pb toxicity. Woodland could be recommended as the proper native land use to alleviate environmental risk. Overall, our results demonstrated the dominant factor to regulate Pb speciation and pointed out the proper land-use in relieving Pb leaching risk around Pb-Zn mine. These finding provides the new strategies to the remediation and management of metal-contaminated soil

Responses of soil microbial communities to nutrient limitation in the desert-grassland ecological transition zone

Soil microorganisms are crucial to indicate ecosystem functions of terrestrial ecosystems. However, the responses of microbial communities to soil nutrient limitation in desert-grassland are still poorly understood. Hence, we investigated soil microbial community structures and metabolic characteristics in a desert-grassland ecological transition zone from the northern Loess Plateau, China, and explored the association of microbial communities with nutrient limitation via high-throughput sequencing.Threshold elemental ratios (TER) indicated that the microbial communities were strongly limited by nitrogen (N) under A. ordosica and P. tabuliformis communities. The phosphorus (P) limitation of microbial communities was observed in the aeolian sandy soil. The results imply that soil microbial communities had strong nutrient competition for N and P with aboveground vegetation in arid and oligotrophic ecosystems. The LEfSe and linear regression analysis revealed that the microbial taxa of Micrococcales, Micrococcaceae and Herpotrichiellaceae were significantly correlated with microbial N limitation. The Thermoleophilia taxa were significantly correlated with microbial P limitation. These biomarkers related to microbial nutrient limitation could be considered as the key microbial taxa to shape microbial communities and functions. Furthermore. N form had different effects on microbial communities, which NH4+-N strongly affected bacterial communities, whereas NO3--N had a significant influence on fungal communities. The different responses indicate that soil microorganisms had corresponding nutrient preferences for bacterial and fungal communities, which might alleviate the nutrient limitations and environmental stress. This study provided important insights on microbial community structures linking to community functions and on the mechanisms governing microbial N and P limitation in arid land ecosystems. (C) 2018 Elsevier B.V. All rights reserved

Ecoenzymatic stoichiometry and microbial nutrient limitation in rhizosphere soil in the arid area of the northern Loess Plateau, China

Arid ecosystems are characterized as having stressful conditions of low energy and nutrient availability for soil microorganisms and vegetation. The rhizosphere serves as the one of most active microorganism habitats, however, the general understanding of the ecoenzymatic stoichiometry (exoenzymes) and microbial nutrient acquisition in rhizosphere soil is limited. Here, we investigated the vegetation communities and determined the soil physicochemical properties, microbial biomass, and enzymatic activities in rhizosphere under different vegetation and soil types in the arid area of the northern Loess Plateau. Type II standard major axis (SMA) regression analysis showed that the plants played a more important role than soil properties in determining ecoenzymatic stoichiometry. Linear regression analysis displayed a microbial stoichiometric homeostasis (community-level) in rhizosphere. The Threshold Elemental Ratio (TER) revealed that the microbial nutrient metabolisms of rhizosphere were co-limited by N and P in the A. ordosica and A. cristatum communities of loess, and A. cristatum communities of feldspathic sandstone weathered soil. Binding spatial ordination analysis (RDA and CCA) demonstrated that soil physical properties (e.g., soil moisture, silt and clay contents) have more contribution to ecoenzymatic stoichiometry than the other investigated soil parameters, whereas soil nutrients (e.g., total organic carbon, nitrogen, and phosphorus) predominantly controlled microbial nutrient ratios. Therefore, the ecoenzymatic stoichiometry in rhizosphere is greatly regulated by plants and soil physical properties. The microbial N and P are co-limited under Gramineae plant in loess and feldspathic sandstone weathered soil regions. Meanwhile, the microbial nutrient limitation is mainly affected by soil nutrient supply. These findings could be crucial for illuminating rhizosphere microbial metabolism and revealing the nutrient cycling of root-soil interface under arid and oligotrophic ecosystems

Proton and Copper Binding to Humic Acids Analyzed by XAFS Spectroscopy and Isothermal Titration Calorimetry

Proton and copper (Cu) binding to soil and lignite-based humic acid (HA) was investigated by combining X-ray absorption fine structure (XAFS) spectroscopy, isothermal titration calorimetry (ITC), and nonideal-competitive-adsorption (NICA) modeling. NICA model calculations and XAFS results showed that bidentate and monodentate complexation occurred for Cu binding to HA. The site-type-specific thermodynamic parameters obtained by combining ITC measurements and NICA calculations revealed that copper binding to deprotonated carboxylic-type sites was entropically driven and that to deprotonated phenolic-type sites was driven by entropy and enthalpy. Copper binding to HA largely depended on the site-type and coordination environment, but the thermodynamic binding mechanisms for Cu binding to the specific site-types were similar for the different HAs studied. By comparing the site-type-specific thermodynamic parameters of HA-Cu complexation with those of low molar mass organic acids, the Cu coordination could be further specified. Bidentate carboxylic Cu complexes made the dominating contributions to Cu binding to HA. The present study not only yields molecular-scale mechanisms of ion binding to carboxylic- and phenolic-type sites of HA but also provides the new insight that the universal nature of site-type-specific thermodynamic data enables quantitative estimation of the binding structures of heavy metal ions to humic substances