The changing character of household waste in the Czech Republic between 1999 and 2009 as a function of home heating methods

The authors of this paper report on the changing character of household waste, in the Czech Republic between 1999 and 2009 in households differentiated by their heating methods. The data presented are the result of two projects, financed by the Czech Ministry of Environment, which were undertaken during this time period with the aim of focusing on the waste characterisation and complete analysis of the physicochemical properties of the household waste. In the Czech Republic, the composition of household waste varies significantly between different types of households based on the methods of home heating employed. For the purposes of these studies, the types of homes were divided into three categories – urban, mixed and rural. Some of the biggest differences were found in the quantities of certain subsample categories, especially fine residue (matter smaller than 20 mm), between urban households with central heating and rural households that primarily employ solid fuel such coal or wood. The use of these solid fuels increases the fraction of the finer categories because of the higher presence of ash. Heating values of the residual household waste from the three categories varied very significantly, ranging from 6.8 MJ/kg to 14.2 MJ/kg in 1999 and from 6.8 MJ/kg to 10.5 MJ/kg in 2009 depending on the type of household and season. The same factors affect moisture of residual household waste which varied from 23.2% to 33.3%. The chemical parameters also varied significantly, especially in the quantities of Tl, As, Cr, Zn, Fe and Mn, which were higher in rural households. Because knowledge about the properties of household waste, as well as its physicochemical characteristics, is very important not only for future waste management, but also for the prediction of the behaviour and influence of the waste on the environment as the country continues to streamline its legislation to the European Union’s solid waste mandates, the results of these studies were employed by the Czech Ministry of Environment to optimise the national waste management strategy.     

Fatal occupational injuries in Jordan during the period 1980 through 1993

All fatal occupational injuries compensated by the Social Security Corporation (SSC) in Jordan during the period 1980–1993 were studied. Variables considered in the analysis included gender, age, nationality, occupation, salary, cause of injury, body part injured and cause of death. The overall fatality rate, of the 705 cases reviewed, was 25.5/100,000/year. The majority (98%) of fatalities were males. The risk of fatal injuries increased with age. Workers over 55 years, had the highest annual fatality rate (37.8). Immigrant workers had a higher fatality rate (32.26) than Jordanians (23.95). Unskilled workers constituted 58.3% of decedents and professionals had the highest fatality rate (52.9). Transportation sector had the highest fatality rate (122.4) followed by construction (50.6). Over the study period, fatality rates tended to decrease significantly in manufacturing, construction and trade economic sectors while no such trend was established by transportation, agriculture and services sectors. The leading causes of fatal injuries were motor-vehicle related accidents (63.0%) and fall of persons (11.1%). Head was the body part most injured and was involved in 46.6% of all deaths. Haemorrhage was the main reported cause of death (24.5%). It is concluded that intervention measures targeting specific occupations (transportation and construction) and causes of fatalities such as motor-vehicle incidents are needed.     

Use of Seawater in Flue Gas Desulfurization

For seasite power plants using seawater for condenser cooling, Bechtel developed a new process to remove better than 90 percent of flue gas SO₂ using seawater and lime. Tests demonstrate that marine life is not affected by the effluent from this unique scrubbing process; therefore, the aqueous effluent containing reacted products (gypsum) in solution at low concentration is suitable for discharge to the sea.     

The phosphorus footprint of China's food chain: implications for food security, natural resource management, and environmental quality

Efficient use of phosphorus (P) for producing food, preventing water pollution, and managing a dwindling rock P reserve are major challenges for China. We analyzed P stocks and flows in the Chinese food chain to identify where P use efficiency can be improved, where P leaks to the environment, and the research, technologies, and policies needed to improve P use. We found a high degree of inefficiency; of 6652 Gg P entering the food chain, only 1102 Gg P (18%) exit as food for humans. The greatest inefficiencies were a large build-up of soil P (3670 Gg P yr; 52% of P inputs) and high P losses to the environment from animal production (1582 Gg P yr; 60% of excreted P). Improving P use in China must focus on national-scale nutrient management strategies, better animal nutrition, and adoption of technologies and policies to reduce P discharges from the animal sector and recycle P as manures in agriculture.     

A New Mathematical Approach in Environmental and Life Sciences: Gene–Environment Networks and Their Dynamics

An important research area in life sciences is devoted to modeling, prediction, and dynamics of gene-expression patterns. As clearly understood in these days, this enterprise cannot become satisfactory without acknowledging the role of the environment. To a representation of past, present, and most likely future states, we also encounter measurement errors and uncertainties. This paper surveys and improves recent advances in understanding the foundations and interdisciplinary implications of the newly introduced gene–environment networks, and it integrates the important theme of carbon dioxide emission reduction into the networks and dynamics. We also introduce some operational and managerial issues of practical working and decision making, expressed in terms of sliding windows, quadrants (modules) of parametric effects, and navigating (controlling) between such effects and directing them. Given data from DNA microarray experiments and environmental records, we extract nonlinear ordinary differential equations that contain parameters that have to be determined. For this, we employ modern (Chebychevian) approximation and (generalized semi-infinite) optimization. After this is provided, time- discretized dynamical systems are studied. A combinatorial algorithm with polyhedra sequences allows to detect the region of parametric stability. Finally, we analyze the topological landscape of gene–environment networks with its structural (in)stability. By embedding as a module and investigating CO₂ emission control and figuring out game theoretical aspects, we conclude. This pioneering work is theoretically elaborated, practically devoted to health care, medicine, education, living conditions, and environmental protection, and it invites the readers to future research.      

Methodological scheme for designing the monitoring of genetically modified crops at the regional scale

According to EC regulations the deliberate release of genetically modified (GM) crops into the agro-environment needs to be accompanied by environmental monitoring to detect potential adverse effects, e.g.unacceptable levels of gene flow from GM to non-GM crops, or adverse effects on single species or species groups thus reducing biodiversity. There is, however, considerable scientific and public debate on how GM crops should be monitored with sufficient accuracy, discussing questions of potential adverse effects, agro-environmental variables or indicators to be monitored and respective detection methods; Another basic component, the appropriate number and location of monitoring sites, is hardly considered. Currently, no consistent GM crop monitoring approach combines these components systematically. This study focuses on and integrates spatial agro-environmental aspects at a landscape level in order to design monitoring networks. Based on examples of environmental variables associated with the cropping of Bt-Maize (Zea maize L.), herbicide-tolerant (HT) winter oilseed rape (Brassica napus L.), HT sugar beet (Beta vulgaris L.), and starch-modified potato (Solanum tuberosum L.), we develop a transferable framework and assessment scheme that comprises anticipated adverse environmental effects, variables to be measured and monitoring methods.These we integrate with a rule-based GIS (geographic information system) analysis, applying widely available spatial area and point information from existing environmental networks. This is used todevelop scenarios with optimised regional GM crop monitoring networks.     

An integrated quantitative risk analysis method for natural gas pipeline network

Natural gas industry is developing rapidly, and its accidents are threatening the urban safety. Risk management through quantitative assessment has become an important way to improve the safety performance of the natural gas supply system. In this paper, an integrated quantitative risk analysis method for natural gas pipeline network is proposed. This method is composed of the probability assessment of accidents, the analysis of consequences and the evaluation of risk. It is noteworthy that the consequences analyzed here include those of the outside and inside gas pipelines. The analysis of consequences of the outside pipelines focuses on the individual risk and societal risk caused by different accidents, while those of the inside pipelines concerns about the risk of the economic loss because of the pressure re-distribution. Risk of a sample urban gas pipeline network is analyzed to demonstrate the presented method. The results show that this presented integrated quantitative risk analysis method for natural gas pipeline network can be used in practical application.     

LaSVM-based big data learning system for dynamic prediction of air pollution in Tehran

Due to critical impacts of air pollution, prediction and monitoring of air quality in urban areas are important tasks. However, because of the dynamic nature and high spatio-temporal variability, prediction of the air pollutant concentrations is a complex spatio-temporal problem. Distribution of pollutant concentration is influenced by various factors such as the historical pollution data and weather conditions. Conventional methods such as the support vector machine (SVM) or artificial neural networks (ANN) show some deficiencies when huge amount of streaming data have to be analyzed for urban air pollution prediction. In order to overcome the limitations of the conventional methods and improve the performance of urban air pollution prediction in Tehran, a spatio-temporal system is designed using a LaSVM-based online algorithm. Pollutant concentration and meteorological data along with geographical parameters are continually fed to the developed online forecasting system. Performance of the system is evaluated by comparing the prediction results of the Air Quality Index (AQI) with those of a traditional SVM algorithm. Results show an outstanding increase of speed by the online algorithm while preserving the accuracy of the SVM classifier. Comparison of the hourly predictions for next coming 24 h, with those of the measured pollution data in Tehran pollution monitoring stations shows an overall accuracy of 0.71, root mean square error of 0.54 and coefficient of determination of 0.81. These results are indicators of the practical usefulness of the online algorithm for real-time spatial and temporal prediction of the urban air quality.     

What Forces Dictate the Design of Pollution Monitoring Networks?

The US Environmental Protection Agency maintains networks of pollution monitors for two basic purposes: to check and enforce the attainment of national ambient air quality standards (NAAQS) and to provide useful data for studying pollution and its effects. These purposes imply conflicting criteria for the locations of a limited number of monitors. To check the attainment of standards, monitors are placed where pollution levels are highest. Monitors are not required where standards have always been met and there are no new pollution sources. To provide useful data for studying pollution and its effects, monitors would be placed to observe outcomes under a variety of pollution levels. This study asks the following questions. What factors affect when a monitor is retired from the network? What drives the decision to add a new site? What causes year-to-year changes in the number of monitors? We tackle these questions with a particular focus on the role of regulatory compliance and pollution levels in the context of monitors for tropospheric ozone (O₃). Using a panel dataset of monitors in the contiguous US spanning the years 1993 to 2011, we find that the peak O₃ readings in the prior period are significantly associated with the regulator’s decision of whether to add or to drop a monitor in the following period. While compliance with the NAAQS for O₃ is not consistently associated with network composition, compliance with the PM_2.5 NAAQS does appear to affect changes to the network.