New indicator approaches for effective urban air quality management

Measurements of urban air quality at monitoring stations in developed countries have frequently involved the criteria gaseous pollutants, particulates, hazardous air pollutants, perceived air quality and relevant meteorological conditions. Large numbers of indicators have therefore been established to quantify emissions, concentrations and environmental and human health impacts of each of these groups of substances. To simplify the data for management, several indicators have been grouped together to form urban air quality indices but the weightings of individual variables is contentious. In industrialising and developing countries, data may be limited and traditional air pollutant indicators cannot often be constructed. The emphasis therefore has to be placed on the development of policy-relevant indicators, such as Response Indicators that reflect different policy principles for regulating air pollutant emissions. Indices that quantify the air quality management capabilities and capacities at the city level provide further useful decision-relevant tools. Four sets of indices, namely, 1. air quality measurement capacity, 2. data assessment and availability, 3. emissions estimates, and 4. management enabling capabilities, and a composite index to evaluate air quality management capability, were constructed and applied to 80 cities. The indices revealed that management capability varied widely between the cities. In some of the cities, existing national knowledge on urban air quality could have been more effectively used for management. It was concluded that for effective urban air quality management, a greater emphasis should be given, not just to monitoring and data capture programmes, but to the development of indicators and indices that empower decision-makers to initiate management response strategies. Over-reliance on restricted, predetermined sets of traditional air quality indicators should be avoided.     

Mapping the Spatial Variability of Plant Diversity in a Tropical Forest: Comparison of Spatial Interpolation Methods

Knowledge of the spatial distribution of plant species is essential to conservation and forest managers in order to identify high priority areas such as vulnerable species and habitats, and designate areas for reserves, refuges and other protected areas. A reliable map of the diversity of plant species over the landscape is an invaluable tool for such purposes. In this study, the number of species, the exponent Shannon and the reciprocal Simpson indices, calculated from 141 quadrat sites sampled in a tropical forest were used to compare the performance of several spatial interpolation techniques used to prepare a map of plant diversity, starting from sample (point) data over the landscape. Means of mapped classes, inverse distance functions, kriging and co-kriging, both, applied over the entire studied landscape and also applied within vegetation classes, were the procedures compared. Significant differences in plant diversity indices between classes demonstrated the usefulness of boundaries between vegetation types, mapped through satellite image classification, in stratifying the variability of plant diversity over the landscape. These mapped classes, improved the accuracy of the interpolation methods when they were used as prior information for stratification of the area. Spatial interpolation by co-kriging performed among the poorest interpolators due to the poor correlation between the plant diversity variables and vegetation indices computed by remote sensing and used as covariables. This indicated that the latter are not suitable covariates of plant diversity indices. Finally, a within-class kriging interpolator yielded the most accurate estimates of plant diversity values. This interpolator not only provided the most accurate estimates by accounting for the indices' intra-class variability, but also provided additional useful interpretations of the structure of spatial variability of diversity values through the interpretation of their semi-variograms. This additional role was found very useful in aiding decisions in conservation planning.     

Use of Scale Invariance in Evaluating Judgement Indicators

Indicators are used to draw conclusions about ecological endpoints when these endpoints cannot be measured directly. In many cases, inferences about an endpoint are only possible because assumptions have been made about the relationship between indicator and endpoint; we refer to such indicators as judgement indicators. The validity of inferences made using a judgement indicator can be gauged by examining the known or assumed form of the general relationship between indicator and endpoint. The rules for this kind of inference are a consequence of scale invariance, which originates from measurement theory. For simple indicators comprised of a single indicator measurement, the inferences allowed – equivalence, rank, equality of intervals, and equality of ratios – depend on whether the data are nominal, ordinal, interval, or ratio scaled. For composite indicators containing two or more simple indicators, inferences are also affected by the mathematical form of combination; e.g., whether the terms are summed or multiplied. Standardizing simple or composite indicators can allow inferences about the relative importance of observations, based on the natural range of occurrence. Scale invariance is a particularly important consideration in landscape assessments, since these often make use of judgement indicators.     

Responses of Physical, Chemical, and Biological Indicators of Water Quality to a Gradient of Agricultural Land Use in the Yakima River Basin, Washington

The condition of 25 stream sites in the Yakima River Basin, Washington, were assessed by the U.S. Geological Survey's National Water-Quality Assessment Program. Multimetric condition indices were developed and used to rank sites on the basis of physical, chemical, and biological characteristics. These indices showed that sites in the Cascades and Eastern Cascades ecoregions were largely unimpaired. In contrast, all but two sites in the Columbia Basin ecoregion were impaired, some severely. Agriculture (nutrients and pesticides) was the primary factor associated with impairment and all impaired sites were characterized by multiple indicators of impairment. All indices of biological condition (fish, invertebrates, and algae) declined as agricultural intensity increased. The response exhibited by invertebrates and algae suggested a threshold response with conditions declining precipitously at relatively low levels of agricultural intensity and little response at moderate to high levels of agricultural intensity. This pattern of response suggests that the success of mitigation will vary depending upon where on the response curve the mitigation is undertaken. Because the form of the community condition response is critical to effective water-quality management, the National Water-Quality Assessment Program is conducting studies to examine the response of biota to gradients of land-use intensity and the relevance of these responses to water-quality management. These land-use gradient pilot studies will be conducted in several urban areas starting in 1999.     

Structural-temporal organization of a rodent community in the Teletskaya Taiga,Altai Mountains

The structural-temporal organization of a murine rodent community in the taiga has been studied near Lake Teletskoe, Mountain Altai. The results show that the long-term dynamics of indices characterizing community diversity depend mainly on changes in the structure of dominance rather than on the population dynamics of species. The distribution of species in the factor space corresponds to their preference for certain biotopes, from dry to relatively moist. An analysis of relationships within the rodent community has revealed the synchronous dynamics of species abundance and antiphase pattern of changes in the structural indices of dominant species.     

河流型硅藻水华研究进展

通过对硅藻水华发生机制相关文献的研究分析,对硅藻水华发生机制做了一般性探讨,并重点关注了河流型水华的发生机制的独特点。河流水华种类主要为中心硅藻纲,静水生态系统水华种类除中心硅藻纲还包括部分羽纹硅藻纲种类。河流水华硅藻种类对营养盐浓度、温度和光照等环境因子具有一定的适应范围。与静水生态系统相比,河流硅藻水华受气象和水文等物理指标的影响更为明显。河流硅藻水华中常具有时滞现象,其中由气象和水文因素引起的时滞现象最为明显。目前河流硅藻水华的防治仍然以上游水库下泄稀释为主,但是这种方法会造成一定的水资源浪费。河流水华硅藻的生理属性、硅藻水华对生态系统的影响、节水与抑制水华的统筹以及其他控制水华的方法都是未来河流硅藻水华研究的重点。     

三峡库区泥沙对不同初始浓度硅藻生长影响

三峡库区含沙量大，库区蓄水后，泥沙沉降对水环境的影响不容忽视。为了探讨含沙水体对藻类生长的影响，丰富和深化富营养化的研究内容和相关理论，在适宜硅藻生长的光照、水温、营养盐等条件下，通过泥沙对不同初始浓度硅藻的生长影响试验研究。结果表明：适量的泥沙含量对硅藻生长有利。含沙量分别为0．0和0．2kg／m^3的两种初始硅藻浓度水样中，叶绿素a浓度峰值都远远高于试验初始硅藻叶绿素a量，明显高于该组其它4个含沙水样。     

Ordination of Plant Communities in Forest Biogeocenoses under Conditions of Air Pollution in the Northern Kola Peninsula

The species diversity and structure of the tree, herb–dwarf shrub, and moss–lichen layers in the biogeocenoses (BGCs) of pine forests of the Kola Peninsula were analyzed in the zone affected by the Pechenganikel Combined Works. Relationships of the diversity of phytocenoses with the amount of atmospheric fallout and the concentrations of accessible compounds of polluting elements (nickel and copper) and nutrients (potassium, magnesium, and nitrogen) in forest litters were revealed.     

The impact of heat waves on daily mortality in Belgrade (Serbia) during summer

In this paper, we are dealing with two extreme events in temperature and population – heat wave and mortality. Our aim is to assess the relation between high temperatures and daily mortality counts during the summer months in the period 2000–2010 in Belgrade (Serbia). In order to establish this connection, we used Poisson regression and two different measures of heat wave: Warm Spell Duration Index (WSDI) and apparent temperature (T _app). As mean daily temperature increases over 90th, 95th and 99th percentiles, average number of deaths increases for 15.3% (p?<?.01), 22.4% (p?<?.05) and 32.0% (insignificant for p?<?.1). We tested three different thresholds (90th, 95th, 99th) for WSDI and T _app in order to separate the hottest heat-wave episodes. On average, mortality is higher than expected for 13.4%, 16.7% and 28.3% (90th, 95th and 99th percentiles for WSDI) and 16.1%, 17.3% and 32.5% (90th, 95th and 99th percentiles for T _app). Estimated mortality excess with heat-wave indices is in accordance with regression output, meaning that WSDI and T _app are good tools for heat-wave identification. During the most severe episode in July 2007, absolute temperature maximum (43.6°C) and daily maximum mortality counts (94 dead) were recorded in the same day (24 July 2007).