森林雷击火的预报监测

本文介绍对森林雷击火预测的研究及其监测技术的进展与应用，以期作为大兴安岭雷电监测网全面开通后监测预报研究工作的新起点     

小型城市污水排放量预测模型研究——以楚雄市为例

针对小城市污水排放量历史数据较少,城市发展变化较大的特点,以楚雄市为例,提出了基于污水排放来源以及生成机理的预测方法。根据历史人口增长趋势以及城镇化率进行城区人口综合预测,运用定额法根据不同行业用水特点预测城市用水量,结合城市污水排放特点对楚雄市近期以及远期城市污水排放量进行科学合理的预测,并对预测结果进行了分析,可为城市发展规划提供决策参考。     

Water quality management worldwide

This article analyzes water quality on a global scale. An overview of the global water supply and demand situation is presented first, including regional and country information, as well as data on selected water use patterns. The focus then shifts to a discussion of water pollution, its various causes, impact, and remedies, with emphasis on legal and administrative solutions. Water pollution control expenditures and the resultant achievements are dealt with in the final third of the article, with projections to 1995. A wide variety of published sources was dovetailed to obtain a composite picture and most likely scenario; this was supplemented with primary interviews by the author conducted in North America, Western and Eastern Europe, and Oceania at the start of the 1980s.     

Household size and composition and implications for housing need in Kumasi,Ghana: a research note

A simple method of calculating the scale of housing need for Kumasi, Ghana, uses two likely variations in household size distribution and an overcrowding threshold of 3 p.p.r., and a measure of preference. The two household size distributions take account both of trends and of changes which may occur if and when new housing is provided. At that time, released from the current constraints, household formation along traditional lines may again be possible. The preferred supply equates households’ perceived need to their ability to pay at current rents. The resulting range of rooms required is wide but even the lowest need is so far in excess of supply that conventional approaches are self‐evidently inadequate and greater client involvement must be encouraged.     

Employing the shared socioeconomic pathways to predict CO2 emissions

Predicting CO₂ emissions is of significant interest to policymakers and scholars alike. The following article contributes to earlier work by using the recently released “shared socioeconomic pathways” (SSPs) to empirically model CO₂ emissions in the future. To this end, I employ in-sample and out-of-sample techniques to assess the prediction accuracy of the underlying model, before forecasting countries’ emission rates until 2100. This article makes three central contributions to the literature. First, as one of the first studies, I improve upon the Representative Concentration Pathways (RCPs) by incorporating the SSPs, which did not exist when the RCPs have been released. Second, I calculate predictions and forecasts for a global sample in 1960–2100, which circumvents issues of limited time periods and sample selection bias in previous research. Third, I thoroughly assess the prediction accuracy of the model, which contributes to providing a guideline for prediction exercises in general using in-sample and out-of-sample approaches. This research presents findings that crucially inform scholars and policymakers, especially in light of the prominent 2 °C goal: none of the five SSP scenarios is likely to be linked to emission patterns that would suggest achieving the 2 °C goal is realistic.     

Non-renewable resource prices: Deterministic or stochastic trends?

In this paper, we examine temporal properties of 11 natural resource real price series from 1870 to 1990. Recent studies by Ahrens and Sharma [Trends in natural resource commodity prices: deterministic or stochastic? J. Environ. Econom. Manage. 33(1997)59–74], Berck and Roberts [Natural resource prices: will they ever turn up? J. Environ. Econom. Manage. 31(1996)65–78], and Slade [Grade selection under uncertainty: least cost last and other anomalies, J. Environ. Econom. Manage. 15(1988)189–205], among others, find that many non-renewable resource prices have a stochastic trend. We revisit this issue by employing a Lagrangian multiplier unit root test that allows for two endogenously determined structural breaks with and without a quadratic trend. Contrary to previous research, we find evidence against the unit root hypothesis for all price series. Our findings support characterizing natural resource prices as stationary around deterministic trends with structural breaks. We additionally show that both pre-testing for unit roots with breaks and allowing for breaks in the forecast model can improve forecast accuracy. Overall, the results in this paper are important in both a positive and normative sense; without an appropriate understanding of the dynamics of a time series, empirical verification of theories, forecasting, and proper inference are potentially fruitless.     

Progress in developing an ANN model for air pollution index forecast

An air pollution index (API) reporting system is introduced to selected cities of China for public communication on air quality data. Shanghai is the first city in China providing daily average API reports and forecasts. This paper describes the development of an artificial neural network (ANN) model for the API forecasting in Shanghai. It is a multiple layer perceptron (MLP) network, with meteorological forecasting data as the main input, to output the next day average API values. However, the initial version of the MLP model did not work well. To improve the model, a series of tests were conducted with respect to the training method and structure optimization. Based on the test results, the training algorithm was modified and a new model was built. The new model is now being used in Shanghai for API forecasting. Its performance is shown reasonably well in comparison with observation. The application of the old model was only weakly correlated with observation. In 1-year application, the correlation coefficients were 0.2314, 0.1022 and 0.1710 for TSP, SO₂ and NO_x, respectively. But for the new model, for over 8 months application, the correlation coefficients are raised to 0.6056, 0.6993 and 0.6300 for PM₁₀, SO₂, and NO₂. Further, the new algorithm does not rely on manpower intervention so that it is now being applied in several other Chinese cities with quite different meteorological conditions. The structure of the model and the application results are presented in this paper and also the problems to be further studied.     

东北玉米热量指数预测方法研究(Ⅲ)——GM(1,1)预测方法

GM(1,1)是开展时间序列环境要素变化趋势预测的有效方法之一。通过对东北地区玉米热量指数的分析,建立了热量指数时间变化趋势的GM(1,1)预测模型,各模型的平均预测精度虽低于逐步回归统计模型,但也都达91%以上,可以应用该模型的预测结果指导农业生产。     

Predicting intertidal organism temperatures with modified land surface models

Animals and plants in the marine intertidal zone live at the interface between terrestrial and marine environments. This zone is likely to be a sensitive indicator of the effects of climate change in coastal ecosystems, because of several key characteristics including steep environmental gradients, rapid temperature changes during tide transitions, fierce competition for limited space, and a community of mostly sessile organisms. Here we describe a modular modeling approach using modifications to a meteorological land surface model to determine body temperatures of the ecologically dominant rocky intertidal mussel Mytilus californianus, as a tool that can be used as a proxy for ecological performance. We validate model results against in situ measurements made with biomimetic body temperature sensors. Model predictions lie within the range of variability of biomimetic measurements, based on observations over a 4-year period at sites along 1700 km of the US west coast from southern California (34.5°N) to northern Washington (48.4°N). Our modular approach can be easily applied to many situations in the intertidal zone, including bare rock, mussel, barnacle, and algal beds, salt-marsh grasses, and sand- and mud-flats, by modifying the “vegetation layer” in a standard meteorological land surface model. Biophysical models such as these, which link ecological processes to changing climates through predictions of body temperature, are essential for understanding biogeographic patterns of physiological stress and mortality risk.     

我国城市垃圾产量预测

运用统计预测的方法对我国城市垃圾产量进行了预测 ,并对各时期的预测结果进行分段分析 ,阐明了影响全国垃圾产量的因素及其贡献大小。