广西喀斯特干旱农业区干旱遥感监测模型研究

广西中部喀斯特平原区是广西重要的粮食生产基地,但旱灾已成为该地区经济发展的障碍.利用EOS/MODIS数据,采用植被状态指数(IVC)和温度条件指数(ITC),构建了干旱指数ID的遥感监测模型, 统计分析了ID与农业受旱率的相关系数,从而确定了模型中各参数的权重系数.将该模型应用于2005年秋旱监测,经与旱情实况及前人研究成果进行对比分析,验证了干旱指数ID的有效性.通过对ID随ITC和IVC变化的敏感性评价,结果表明,ITC和IVC都能反映旱情变化,但ITC反映旱情的敏感性高于IVC,以ITC和IVC为因子构建的干旱遥感监测模型适用于广西中部喀斯特干旱农业区的旱情遥感监测.     

Modeling urban solar energy with high spatiotemporal resolution: A case study in Toronto,Canada

This research presents a method to determine the maximum potential for the capturing of solar radiation on the rooftop of buildings in an urban environment. This involves the modeling of solar energy potential and comparison to historical building energy demand profiles through the use of 3-D solar simulation software tools and geographic information systems (GIS). The objective is to accurately identify the amount of surface area that is suitable for solar photovoltaic (PV) installations and to estimate the hourly PV electricity generation potential of existing building rooftops in an urban environment. This study demonstrates a viable approach for modeling urban solar energy and offers valuable information for electricity distributors, policy makers, and urban energy planners to facilitate the substantial design of a green built environment. The developed methodology is comprised of three main sections: (1) determination of suitable rooftop area, (2) determination of the amount of incident solar radiation available per rooftop, and (3) estimation of hourly solar PV electricity generation potential. A case study was performed using this method for Ryerson University, located in Toronto, Canada. It was found that solar PV could supply up to 19% of the study area’s electricity demands during peak consumption hours. The potential benefits of solar PV was also estimated based upon hourly greenhouse gas emission intensity factors as well as Time-of-Use (TOU) savings through the Ontario Feed-in-Tariff (FIT) program, which allows for better representation of the positive impacts of solar technologies.     

Research and application of method of oxygen isotope of inorganic phosphate in Beijing agricultural soils

Phosphorus (P) in agricultural ecosystems is an essential and limited element for plants and microorganisms. However, environmental problems caused by P accumulation as well as by P loss have become more and more serious. Oxygen isotopes of phosphate can trace the sources, migration, and transformation of P in agricultural soils. In order to use the isotopes of phosphate oxygen, appropriate extraction and purification methods for inorganic phosphate from soils are necessary. Here, we combined two different methods to analyze the oxygen isotopic composition of inorganic phosphate (δ¹⁸O_P) from chemical fertilizers and different fractions (Milli-Q water, 0.5 mol L^?1 NaHCO₃ (pH = 8.5), 0.1 mol L^?1 NaOH and 1 mol L^?1 HCl) of agricultural soils from the Beijing area. The δ¹⁸O_P results of the water extracts and NaHCO₃ extracts in most samples were close to the calculated equilibrium value. These phenomena can be explained by rapid P cycling in soils and the influence of chemical fertilizers. The δ¹⁸O_P value of the water extracts and NaHCO₃ extracts in some soil samples below the equilibrium value may be caused by the hydrolysis of organic P fractions mediated by extracellular enzymes. The δ¹⁸O_P values of the NaOH extracts were above the calculated equilibrium value reflecting the balance state between microbial uptake of phosphate and the release of intracellular phosphate back to the soil. The HCl extracts with the lowest δ¹⁸O_P values and highest phosphate concentrations indicated that the HCl fraction was affected by microbial activity. Hence, these δ¹⁸O_p values likely reflected the oxygen isotopic values of the parent materials. The results suggested that phosphate oxygen isotope analyses could be an effective tool in order to trace phosphate sources, transformation processes, and its utilization by microorganisms in agricultural soils.     

Combination of biochar amendment and phytoremediation for hydrocarbon removal in petroleum-contaminated soil

Remediation of soils contaminated with petroleum is a challenging task. Four different bioremediation strategies, including natural attenuation, biochar amendment, phytoremediation with ryegrass, and a combination of biochar and ryegrass, were investigated with greenhouse pot experiments over a 90-day period. The results showed that planting ryegrass in soil can significantly improve the removal rate of total petroleum hydrocarbons (TPHs) and the number of microorganisms. Within TPHs, the removal rate of total n-alkanes (45.83 %) was higher than that of polycyclic aromatic hydrocarbons (30.34 %). The amendment of biochar did not result in significant improvement of TPH removal. In contrast, it showed a clear negative impact on the growth of ryegrass and the removal of TPHs by ryegrass. The removal rate of TPHs was significantly lower after the amendment of biochar. The results indicated that planting ryegrass is an effective remediation strategy, while the amendment of biochar may not be suitable for the phytoremediation of soil contaminated with petroleum hydrocarbons.     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

Plasticity in metamorphic traits of <Emphasis Type="Italic">Rana kukunoris</Emphasis> tadpoles: The interactive effects of food level and rearing temperature

Larval amphibians are particularly likely to encounter variation in rearing temperature and resource availability due to variation in aquatic breeding habitats. In this study, plasticity in growth rates, larval mass, larval period, and size at metamorphosis were examined in Rana kukunoris Nikolskii, 1918 under different combinations of temperature and food level. Larval period and larval body mass was sensitive to food level, and varied with temperature. Tadpoles metamorphosed at an older age at low temperature than those reared at warm temperature. Food level was a significant affect on larval period at low temperature, but not at warm temperature. Mass was heavier for tadpoles reared at low temperatures than those reared at warm temperatures. The effect of food level depended on temperature, because larvae reared at low temperature that were offered a high food level achieved a larger size than larvae offered a low food level, but this did not occur at warm temperature. Therefore, we suggest that high food availability at low temperature prolonged developmental periods, thus larvae are larger as metamorphs than those reared at warm temperatures.     

Numerical simulation of an array of fences in Saemangeum reclaimed land

This paper discusses about the quantitative effect of windbreak fences on wind velocity in the reclaimed land at Saemangeum in South Korea. Windbreak fences were constructed in the reclaimed land to reduce the wind velocity to prevent the generation and diffusion of dust. However, up to this time, no in-depth studies were conducted to quantitatively measure the effect of the windbreak fences on wind velocity thus an optimum windbreak structure is not yet determined. Using CFD simulations, the effects of fence porosity, fence height, and the distance between the adjacent fences were investigated. A wind tunnel experiment was initially conducted and data gathered were used to develop the CFD models. From the experiments and CFD simulations, the overall percentage difference of the measured velocities was 7.20% which is generally acceptable to establishing the reliability of the CFD models. The reduction effect on wind velocity was measured in between the adjacent fences up to a height of 0.6 m from the ground surface. In terms of porosity ( = 0, 0.2, 0.4, 0.6), 0.2 was found to be the optimum value. Conversely, the effect of fence height (0.6, 0.8 and 1.0 m) showed no significant difference; therefore, 0.6 m height is recommended. In addition, the reduction effect of distance between the adjacent fences (2, 4 and 6 m) on wind velocity having a 0.2 porosity has decreased to about 75% regardless of the distance. In the case of the reclaimed land in Saemangeum, a decrease of 75% can prevent the generation and diffusion of dusts. However, the source of dusts is very large. Therefore, constructing an array of windbreak with 6 m distance between them is deemed necessary.     

Suppression of precipitation by dust particles originated in the Tibetan Plateau

Dust aerosols play an important role in modulating the hydrologic cycle. The Tibetan Plateau (TP) is little polluted by human activities as an ideal site to study the effect of dust aerosol on precipitation. In this study, observational data of dust storms and precipitation in the TP and its vicinities as well as CALIPSO satellite data were used to analyze the distributions and vertical structure of dust storms on the plateau. The results showed that dust storms occur with high frequency and raise dust particles into the troposphere from ground level to a height of 5–9 km to modulate the hydrologic cycle in the TP. There are significant negative correlations between dust aerosol and precipitation in the dust source regions during the period of both 40 and 200 years. It is found that the role of precipitation in suppressing dust storms could be unimportant, while dust aerosol may play an important role in suppressing precipitation in the hinterland of the TP. Our study provides a potential approach to better understand the climate changes in the TP.     

China's grazed temperate grasslands are a net source of atmospheric methane

A budget for the methane (CH₄) cycle in the Xilin River basin of Inner Mongolia is presented. The annual CH₄ budget in this region depends primarily on the sum of atmospheric CH₄ uptake by upland soils, emission from small wetlands, and emission from grazing ruminants (sheep, goats, and cattle). Flux rates for these processes were averaged over multiple years with differing summer rainfall. Although uplands constitute the vast majority of land area, they consume much less CH₄ per unit area than is emitted by wetlands and ruminants. Atmospheric CH₄ uptake by upland soils was ?3.3 and ?4.8 kg CH₄ ha^?1 y^?1 in grazed and ungrazed areas, respectively. Average CH₄ emission was 791.0 kg CH₄ ha^?1 y^?1 from wetlands and 8.6 kg CH₄ ha^?1 y^?1 from ruminants. The basin area-weighted average of all three processes was 6.8 kg CH₄ ha^?1 y^?1, indicating that ruminant production has converted this basin to a net source of atmospheric CH₄. The total CH₄ emission from the Xilin River basin was 7.29 Gg CH₄ y^?1. The current grazing intensity is about eightfold higher than that which would result in a net zero CH₄ flux. Since grazing intensity has increased throughout western China, it is likely that ruminant production has converted China's grazed temperate grasslands to a net source of atmospheric CH₄ overall.     

Ionic composition of TSP and PM2.5 during dust storms and air pollution episodes at Xi'an,China

TSP and PM_2.5 samples were collected at Xi'an, China during dust storms (DSs) and several types of pollution events, including haze, biomass burning, and firework displays. Aerosol mass concentrations were up to 2 times higher during the particulate matter (PM) events than on normal days (NDs), and all types of PM led to decreased visibility. Water-soluble ions (Na⁺, NH₄⁺, K⁺, Mg²⁺, Ca²⁺, F^?, Cl^?, NO₃^?, and SO₄^2?). were major aerosol components during the pollution episodes, but their concentrations were lower during DSs. NH₄⁺, K⁺, F^?, Cl^?, NO₃^?, and SO₄^2? were more abundant in PM_2.5 than TSP but the opposite was true for Mg²⁺ and Ca²⁺. PM collected on hazy days was enriched with secondary species (NH₄⁺, NO₃^?, and SO₄²) while PM from straw combustion showed high K⁺ and Cl^?. Firework displays caused increases in K⁺ and also enrichments of NO₃^? relative to SO₄^2?. During DSs, the concentrations of secondary aerosol components were low, but Ca²⁺ was abundant. Ion balance calculations indicate that PM from haze and straw combustion was acidic while the DSs samples were alkaline and the fireworks' PM was close to neutral. Ion ratios (SO₄^2?/K⁺, NO₃^?/SO₄^2?, and Cl^?/K⁺) proved effective as indicators for different pollution episodes.