Assessment of yield losses in tropical wheat using open top chambers

The present study deals with the evaluation of effects of ambient gaseous air pollution on wheat (Triticum aestivum L. var. HUW-234) growing in a suburban area situated in eastern Gangetic plain of India, using open top chambers. Eight hourly air monitoring was conducted for ambient concentrations of SO₂, NO₂ and O₃ in filtered chambers (FCs), non-filtered chambers (NFCs) and open plots (OPs). Various morphological, physiological and biochemical parameters were assessed during different developmental stages and finally yield parameters were quantified at the time of harvest.Mean concentrations of SO₂, NO₂ and O₃ were 8.4, 39.9 and 40.1 ppb, respectively during the experiment in NFCs. Concentrations of SO₂, NO₂ and O₃ reduced by 74.6%, 84.7% and 90.4%, respectively in FCs as compared to NFCs. Plants grown in FCs showed higher photosynthetic rate, stomatal conductance, chlorophyll content and Fv/Fm ratio as compared to the plants in NFCs and OPs. Lipid peroxidation, proline, total phenol and ascorbic acid contents and peroxidase activity were higher in plants grown in NFCs. There were improvements in morphological parameters of plants growing in FCs as compared to those in NFCs and OPs. Yield of plants also increased significantly in FCs as compared to those ventilated with ambient air (NFCs) or grown in OPs. During the vegetative phase, NO₂ concentrations were higher than O₃, but O₃ became dominant pollutant during the time of grain setting and filling. The study concludes that O₃ and NO₂ are the main air pollutants in the sub-urban areas causing significant yield reductions in tropical wheat plants.     

Isomorphic chain graphs for modeling spatial dependence in ecological data

Graphical models (alternatively, Bayesian belief networks, path analysis models) are increasingly used for modeling complex ecological systems (e.g., Lee, In: Ferson S, Burgman M(eds) Quantative methods for conservation biology. Springer, Berlin Heilin Heideslperk New York, pp.127–147, 2000; Borsuk et al., J Water Res Plann Manage 129:271–282, 2003). Their implementation in this context leverages their utility in modeling interrelationships in multivariate systems, and in a Bayesian implementation, their intuitive appeal of yielding easily interpretable posterior probability estimates. However, methods for incorporating correlational structure to account for observations collected through time and/or space—features of most ecological data—have not been widely studied; Haas et al. (AI Appl 8:15–27, 1994) is one exception. In this paper, an “isomorphic” chain graph (ICG) model is introduced to account for correlation between samples by linking site-specific Bayes network models. Several results show that the ICG preserves many of the Markov properties (conditional and marginal dependencies) of the site-specific models. The ICG model is compared with a model that does not account for spatial correlation. Data from several stream networks in the Willamette River valley, Oregon (USA) are used. Significant correlation between sites within the same stream network is shown with an ICG model.     

Bayesian areal wombling via adjacency modeling

Recently, public health professionals and other geostatistical researchers have shown increasing interest in boundary analysis, the detection or testing of zones or boundaries that reveal sharp changes in the values of spatially oriented variables. For areal data (i.e., data which consist only of sums or averages over geopolitical regions), Lu and Carlin (Geogr Anal 37: 265–285, 2005) suggested a fully model-based framework for areal wombling using Bayesian hierarchical models with posterior summaries computed using Markov chain Monte Carlo (MCMC) methods, and showed the approach to have advantages over existing non-stochastic alternatives. In this paper, we develop Bayesian areal boundary analysis methods that estimate the spatial neighborhood structure using the value of the process in each region and other variables that indicate how similar two regions are. Boundaries may then be determined by the posterior distribution of either this estimated neighborhood structure or the regional mean response differences themselves. Our methods do require several assumptions (including an appropriate prior distribution, a normal spatial random effect distribution, and a Bernoulli distribution for a set of spatial weights), but also deliver more in terms of full posterior inference for the boundary segments (e.g., direct probability statements regarding the probability that a particular border segment is part of the boundary). We illustrate three different remedies for the computing difficulties encountered in implementing our method. We use simulation to compare among existing purely algorithmic approaches, the Lu and Carlin (2005) method, and our new adjacency modeling methods. We also illustrate more practical modeling issues (e.g., covariate selection) in the context of a breast cancer late detection data set collected at the county level in the state of Minnesota.     

环境激素及其危害

环境激素是环境中的激素类似物,它干扰体内正常分泌的激素,引起种种负面的生物学效应,威胁野生动物和人类的健康.文章阐述了环境激素给野生动物和人类带来的危害,可能的作用机制.介绍了环境激素的概念、种类、控制方法和日常生活中的预防措施.     

中国资源型城市房价时空变化与影响因素分析

基于禧泰数据库的全国城市二手房价监测数据,利用描述统计和GIS空间分析方法详细分析了2011—2018年126个中国资源型城市房价时空变化特征,并采用空间杜宾模型进一步揭示了其影响因素。研究结果表明：（1）2011年和2018年中国资源型城市平均房价分别为4105元/m²和5675元/m²,再生型城市、成熟型城市、成长型城市和衰退型城市的平均房价依次递减;（2）2011—2018年中国资源型城市平均房价呈现出波动上升的态势,房价增长率为38.2%,远低于全国城市平均房价增长幅度55.3%,且不同类型资源型城市房价的增长幅度有所差异,以成熟型和再生型城市的房价增幅相对较大;（3）中国资源型城市房价和变化存在显著的空间集聚特征,房价热点区主要集中在东部地区和中部地区城市,房价冷点区主要以东北地区和西部地区城市为主;（4）空间杜宾模型显示,人均GDP、人均住房开发投资、多样化指数、专业化指数和工业废水排放强度是影响中国资源型城市房价空间差异的主要因素。     

Spatial and temporal variation of haze in China from 1961 to 2012

The purpose of this study is to analyze the climatic characteristics and long-term spatial and temporal variations of haze occurrence in China. The impact factors of haze trends are also discussed. Meteorological data from 1961 to 2012 and daily PM₁₀ concentrations from 2003 to 2012 were employed in this study. The results indicate that the annual-average hazy days at all stations have been increasing rapidly from 4 days in 1961 to 18 days in 2012. The maximum number of haze days occur in winter (41.1%) while the minimum occur in summer (10.4%). During 1961-2012, the high occurrence areas of haze shifted from central to south and east regions of China. The Beijing-Tianjin-Hebei (Jing-Jin-Ji) region, Shanxi, Shaanxi, and Henan Province are the high occurrence areas for haze, while the Yangtze River Delta (YRD) and the Pearl River Delta (PRD) have become regions with high haze occurrences in the last 25 years. Temperature and pressure are positively correlated with the number of haze days. However, wind, relative humidity, precipitation, and sunshine duration are negatively correlated with the number of haze days. The key meteorological factors affecting the formation and dissipation of haze vary for high and low altitudes, and are closely related to anthropogenic activities. In recent years, anthropogenic activities have played a more important role in haze occurrences compared with meteorological factors.     

Effects assessment: boron compounds in the aquatic environment

In previous studies, boron compounds were considered to be of comparatively low toxicity in the aquatic environment, with predicted no effect concentration (PNEC) values ranging around 1 mg B/L (expressed as boron equivalent). In the present study, we describe an evaluation of toxicity data for boron available for the aquatic environment by different methods.For substances with rich datasets, it is often possible to perform a species sensitivity distribution (SSD). The typical outcome of an SSD is the Hazardous Concentration 5% (HC₅), the concentration at which 95% of all species are protected with a probability of 95%. The data set currently available on the toxic effects of boron compounds to aquatic organisms is comprehensive, but a careful evaluation of these data revealed that chronic data for aquatic insects and plants are missing. In the present study both the standard assessment factor approach as well as the SSD approach were applied. The standard approach led to a PNEC of 0.18 mg B/L (equivalent to 1.03 mg boric acid/L), while the SSD approach resulted in a PNEC of 0.34 mg B/L (equivalent to 1.94 mg boric acid/L). These evaluations indicate that boron compounds could be hazardous to aquatic organisms at concentrations close to the natural environmental background in some European regions. This suggests a possible high sensitivity of some ecosystems for anthropogenic input of boron compounds. Another concern is that the anthropogenic input of boron could lead to toxic effects in organisms adapted to low boron concentration.     

Agricultural ammonia emissions inventory and spatial distribution in the North China Plain

An agricultural ammonia (NH₃) emission inventory in the North China Plain (NCP) on a prefecture level for the year 2004, and a 5 × 5 km² resolution spatial distribution map, has been calculated for the first time. The census database from China's statistics datasets, and emission factors re-calculated by the RAINS model supported total emissions of 3071 kt NH₃-N yr⁻¹ for the NCP, accounting for 27% of the total emissions in China. NH₃ emission from mineral fertilizer application contributed 1620 kt NH₃-N yr⁻¹, 54% of the total emission, while livestock emissions accounted for the remaining 46% of the total emissions, including 7%, 27%, 7% and 5% from cattle, pigs, sheep and goats, and poultry, respectively. A high-resolution spatial NH₃ emissions map was developed based on 1 × 1 km land use database and aggregated to a 5 × 5 km grid resolution. The highest emission density value was 198 kg N ha⁻¹ yr⁻¹.     

Spatial effects and strategic behavior in a multiregional transboundary pollution dynamic game

We analyze a transboundary pollution differential game where pollution control is spatially distributed among a number of agents with predetermined spatial relationships. The analysis emphasizes, first, the effects of the different geographical relationships among decision makers; and second, the strategic behaviour of the agents. The dynamic game considers a pollution stock (the state variable) distributed among one large region divided in subregions which control their own emissions of pollutants. The emissions are also represented as distributed variables. The dynamics of the pollution stock is defined by a parabolic partial differential equation. We numerically characterize the feedback Nash equilibrium of a discrete-space model that still captures the spatial interactions among agents. We evaluate the impact of the strategic and spatially dynamic behaviour of the agents on the design of equilibrium environmental policies.     

Ease vs. noise: Long-run changes in the value of transport (dis)amenities

For a complete cost-benefit analysis of durable infrastructures, it is important to understand how the value of non-market goods such as transit time and environmental quality changes as incomes rise in the long-run. We use difference-in-differences and spatial differencing to estimate the land price capitalization effects of metro rail in Berlin, Germany today and a century ago. Over this period, the negative implicit hedonic price of rail noise tripled. Our results imply income elasticities of the value of noise reduction and transport access of 2.2 and 1.4, substantially exceeding cross-sectional contingent valuation estimates.