Search

Formulating suitable policies is essential for resources and environmental management. In this study, an agricultural pollutants emission trading management model driven by water resources and pollutants control is developed to search reasonable policies for agricultural water resources allocation under multiple uncertainties. Random-fuzzy and interval information in water resources system that have directly impact on the effectiveness of management schemes is reflected through interval two-stage stochastic fuzzy-probability programming. The model was root from regional agricultural water resources system in Jining City, China under considering the relationship among effective precipitation, crop water demand, and pollutants emission. Two types policies (water consumption-control and pollutants emission-control) are designed for searching the related interaction on water resources management and water quality improvement. The results indicated that water resources policies would be of water and environmental double benefits, and a large rainfall would reduce irrigation amount from water sources and lead to a larger pollutants emission trading. The results will help for defining scientific and effective water resources protection and management policies and analyzing the related interacted effects on water consumption, pollutants control and system benefit., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

The study made a comprehensive effort to examine climatic uncertainties at both yearly and monthly scales, along with mapping flood risks based on different land use categories. Recent studies have progressively been engrossed in demonstrating regional climate variations and associated flood probability to maintain the geo-ecological balance at micro to macro-regions. To carry out this investigation, various historical remote sensing record, reanalyzed and in-situ data sets were acquired with a high level of spatial precision using the Google Earth Engine (GEE) web-based remote sensing platform. Non-parametric techniques and multi-layer integration methods were then employed to illustrate the fluctuations in climate factors alongside creating maps indicating the susceptibility to floods. The study reveals an increased pattern in LST (Land Surface Temperature) (0.03 °C/year), albeit marginal declined in southern coastal regions (-0.15 °C/year) along with uneven rainfall patterns (1.42 mm/year). Moreover, long-term LULC change estimation divulges increased trends of urbanization (16.4 km 2 /year) together with vegetation growth (8.7 km 2 /year) from 2002 to 2022. Furthermore, this inquiry involves numerous environmental factors that influence the situation (elevation data, topographic wetness index, drainage density, proximity to water bodies, slope, and soil properties) as well as socio-economic attributes (population) to assess flood risk areas through the utilization of Analytical Hierarchy Process and overlay methods with assigned weights. The outcomes reveal nearly 55 percent of urban land is susceptible to flood in 2022, which were 45 and 37 percent in 2012 and 2002 separately. Additionally, 106 km 2 of urban area is highly susceptible to inundation, whereas vegetation also occupies a significant proportion (52 km 2 ). This thorough exploration offers a significant chance to formulate flood management and mitigation strategies tailored to specific regions during the era of climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

In this study, the probability of occurrence of fumonisins in corn in the states of greatest production in Brazil was determined. The data were analyzed through quantitative risk analysis using the Monte Carlo simulation. The results indicated that there is a strong correlation between fumonisins contamination levels and the geographical region due to the influence of climatic characteristics, with temperature having the main influence. The Southern states presented higher risks of occurrence and concentration levels of fumonisins in corn due to the temperate climate with lower average temperature and higher relative humidity and precipitation indices. Cultivation in the best season indicates a significant reduction in the production of fumonisins when this period was evaluated, with average concentration levels up to 42% lower. The generated data are important for regulatory agencies and the agricultural sector, which needs to be aware that the chance of success in grain production depends on efficient planning of the growing season, mainly concerning the climatic conditions to which it is subject to minimize the risks. • Risk of fumonisins in corn was assessed using quantitative risk assessment; • Temperature plays a critical role in fumonisin incidence and level in corn; • Reduction in fumonisin of up to 42% when cultivation at the best time was assessed; • Strong correlation between fumonisins levels and the geographical region was found; • Low temperatures and high humidity increased the probability of fumonisin in corn. [ABSTRACT FROM AUTHOR]

Combining the comprehensive effects of temperature and humidity, this study applies a heat stress index to project future population exposure to high temperature and related health-risks over China under different climate change scenarios. Results show that the number of high temperature days, population exposure and their related health-risks will increase significantly in the future compared to the reference period (1985-2014), which is mainly caused by the change of >T99p (the wet bulb globe temperature >99th percentile derived from the reference period). The population effect is absolutely dominant in influencing the decrease in exposure to T90-95p (the wet bulb globe temperature is in the range of (90th, 95th]) and T95-99p (the wet bulb globe temperature is in the range of (95th, 99th]), and the climate effect is the most prominent contributor to the upsurge in exposure to > T99p in most areas. An additional 0.1 billion person-days increase in population exposure to T90-95p, T95-99p and >T99p in a given year is associated with the number of deaths by 1002 (95% CI: 570-1434), 2926 (95% CI: 1783-4069) and 2635 (95% CI: 1345-3925), respectively. Compared with the reference period, total exposure to high temperature under the SSP2-4.5 (SSP5-8.5) scenario will increase to 1.92 (2.01) times in the near-term (2021-2050) and 2.16 (2.35) times in the long-term (2071-2100), which will increase the number of people at heat risk by 1.2266 (95% CI: 0.6341-1.8192) [1.3575 (95% CI: 0.6926-2.0223)] and 1.5885 (95% CI: 0.7869-2.3902) [1.8901 (95% CI:0.9230-2.8572)] million, respectively. Significant geographic variations exist in the changes of exposure and related health-risks. The change is greatest in the southwest and south, whereas it is relatively small in the northeast and north. The findings provide several theoretical references for climate change adaptation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

COVID-19 forced the human population to rethink its way of living. The threat posed by the potential spread of the virus via an airborne transmission mode through ventilation systems in buildings and enclosed spaces has been recognized as a major concern. To mitigate this threat, researchers have explored different technologies and methods that can remove or decrease the concentration of the virus in ventilation systems and enclosed spaces. Although many technologies and methods have already been researched, some are currently available on the market, but their effectiveness and safety concerns have not been fully investigated. To acquire a broader view and collective perspective of the current research and development status, this paper discusses a comprehensive review of various workable technologies and methods to combat airborne viruses, e.g., COVID-19, in ventilation systems and enclosed spaces. These technologies and methods include an increase in ventilation, high-efficiency air filtration, ionization of the air, environmental condition control, ultraviolet germicidal irradiation, non-thermal plasma and reactive oxygen species, filter coatings, chemical disinfectants, and heat inactivation. Research gaps have been identified and discussed, and recommendations for applying such technologies and methods have also been provided in this article., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Effective river water quality management and planning is a complex issue challenged by various complexities and uncertainties. A simulation-based interval chance-constrained quadratic programming (ICCQP) model is developed for the seasonal planning of water quality management (WQM) under various uncertainties. The proposed model incorporates interval quadratic programming, chance-constrained programming, and a seasonal water quality simulation model within a general framework for WQM. Uncertainties associated with the objective and the coefficients in the left-hand sides of the constraints are tackled as intervals. Meanwhile, parameter uncertainties on the right-hand sides are characterized using probability distributions. Nonlinearities in the cost function are reflected by quadratic programming. A multi-segment water quality model is used to simulate the dynamic interactions between wastewater discharges and river water quality. The proposed ICCQP-WQM model is applied in a real case study for the control of total phosphorus (TP) in the central Grand River in Ontario, Canada. The results demonstrate that the proposed model is able to incorporate uncertainties expressed as intervals and probability information into an optimization framework and provide interval solutions. Thus, different cost-effective schemes for seasonal WQM could be generated. The results show the Kitchener wastewater treatment plant (WWTP) affects the value of the objective function more than the other WWTPs in the study area. It is also found that the Kitchener WWTP's cost accounts for the highest proportion (approximately 35.1-37.9%) of the total annual cost, which implies the control of TP at the Kitchener plant is the most important to the system. Moreover, river water TP standards in spring and autumn are usually difficult to meet, indicating different TP control strategies are needed in these two seasons. The generated results are valuable for local decision makers to generate TP control strategies, and also to identify optimized solutions under various uncertainties. The proposed ICCQP-WQM model can be extended to other watersheds to support effective water quality management and planning., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Issues of water scarcity, food crisis, and ecological degradation pose great challenges to the sustainable development of Central Asia. In this study, a bi-level chance-constrained programming (BCCP) method is developed for planning water-food-ecology (WFE) nexus system of the Amu Darya River basin, where the efficiency of water-trading mechanism and the impact of uncertain water-availability are examined. This is the first attempt for planning WFE nexus system by incorporating chance-constrained programming (CCP) within a bi-level optimization framework. BCCP can reflect the risk of violating probabilistic constraint under uncertainty as well as balance the tradeoff between two-level decision makers in the WFE nexus system. Under trading scheme, multiple scenarios in association with different food demand, ecological-water requirement, and water availability are examined. Major findings are: (i) compared with that under non-trading, system benefits would increase [3.9, 20.4]% under trading scenarios, disclosing that water trading is an effective mechanism for the study basin; (ii) when food demand increases 10.5%, water allocated to ecological use would decrease [0.9, 2.7]% under all scenarios, revealing that agriculture can squeeze ecological water; (iii) both system benefit and water allocation would increase with p level, implying there is a tradeoff between system benefit and system-failure risk. These findings can gain insight into the interaction between two-level stakeholders and objectives as well as provide decision support for WFE nexus synergetic management., (Copyright © 2020 Elsevier Inc. All rights reserved.)

In this study, a factorial Bayesian copula (FBC) method is proposed to quantify parameter uncertainties in copula-based models and then reveal their impacts on hydrologic risk inferences within a multivariate context. In detail, Bayesian inference and factorial analysis are integrated into copula-based multivariate risk models to (1) quantify parameter uncertainties, (ii) reveal their individual and interactive effects, and (iii) identify their detailed contributions to uncertain risk inferences. Streamflow observations at Xiangxi and Wei River basins is China are used to illustrate the applicability of FBC. The results indicate that imprecise parameters in marginal distributions and the dependence structure would lead to extensive uncertainties in predictive joint return periods and failure probabilities. Also, individual and interactive effects of parameters are well revealed through multilevel factorial analysis, and the detailed contributions of one parameter to different failure probabilities under different service time scenarios are identified., (Copyright © 2020 Elsevier Inc. All rights reserved.)

In this study, a factorial fuzzy chance-constrained programming (FFCP) method is developed for planning urban agglomeration ecosystem under uncertainty. FFCP cannot only address uncertainties presented as possibility distributions and random variables, but also quantitatively evaluate the individual and the interactive effects of multiple eco-environmental factors on urban agglomeration ecosystem. The FFCP method is applied to planning the Guangzhou-Foshan-Zhaoqing (GFZ) urban agglomeration, one of the most important economic circles of the Pearl River Delta region. With rapid industrialization, urbanization and population growth, a number of eco-environmental issues (e.g., water contamination, air pollution, and ecological deterioration) are becoming more and more serious. Results reveal that (i) the main environmental problem of Guangzhou is water pollution due to excessive chemical oxygen demand (COD) discharge (with a contribution of 53.1%), (ii) Foshan would suffer air pollution due to sulfur dioxide (SO 2 ) emitted from industrial processing and production, and (iii) solid waste disposal would continue to be challenge faced by Zhaoqing. Results also disclose that multiple uncertainties in system components have sound effects on the urban agglomeration ecosystem management as well as eco-environmental constraints have individual and/or joint effects on the system benefit. Different probability levels would lead to changed land-use patterns. Decisions at a lower violation level would lead to an increased reliability in fulfilling ecosystem requirement but with a lower system benefit. The findings can help decision makers to gain insights into tradeoff between economic development and eco-environmental protection as well as generate synergetic development strategies of urban agglomeration in an economic-effective and ecological-harmonious way., (Copyright © 2019 Elsevier Inc. All rights reserved.)

An integrated risk is a scene in the future associated with some adverse incident caused by multiple hazards. An integrated probability risk is the expected value of disaster. Due to the difficulty of assessing an integrated probability risk with a small sample, weighting methods and copulas are employed to avoid this obstacle. To resolve the problem, in this paper, we develop the information diffusion technique to construct a joint probability distribution and a vulnerability surface. Then, an integrated risk can be directly assessed by using a small sample. A case of an integrated risk caused by flood and earthquake is given to show how the suggested technique is used to assess the integrated risk of annual property loss., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Objectives: Simulate how the effect of exposure on disease occurrence and fatality influences the presence and magnitude of bias in survivor cohorts, motivated by an actual survivor cohort under study., Methods: We simulated a cohort of 50,000 subjects exposed to a disease-causing exposure over time and followed forty years, where disease incidence was the outcome of interest. We simulated this 'inception' cohort under different assumptions about the effect of exposure on disease occurrence and fatality after disease occurrence. We then created a corresponding 'survivor' (or 'cross-sectional') cohort, where cohort enrollment took place at a specific date after exposure began in the inception cohort; subjects dying prior to that enrollment date were excluded. The disease of interest caused all deaths in our simulations, but was not always fatal. In the survivor cohort, person-time at risk began before enrollment for all subjects who did not die prior to enrollment. We compared exposure-disease associations in each inception cohort to those in corresponding survivor cohorts to determine how different assumptions impacted bias in the survivor cohorts. All subjects in both inception and survivor cohorts were considered equally susceptible to the effect of exposure in causing disease. We used Cox proportional hazards regression to calculate effect measures., Results: There was no bias in survivor cohort estimates when case fatality among diseased subjects was independent of exposure. This was true even when the disease was highly fatal and more highly exposed subjects were more likely to develop disease and die. Assuming a positive exposure-response in the inception cohort, survivor cohort rate ratios were biased downwards when case fatality was greater with higher exposure., Conclusions: Survivor cohort effect estimates for fatal outcomes are not always biased, although precision can decrease., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Seafood consumption is associated with both risks and beneficial effects to human health. Consequently, an integrated exposure assessment of intake of toxic and nutritious agents in seafood is of importance prior to determination of dietary advisories. We have developed a probabilistic model for the estimation of simultaneous intake of methylmercury (MeHg) and long-chain n-3 polyunsaturated fatty acids (LC-n3 PUFAs) from seafood, to estimate the population proportion at risk for exceeding tolerable MeHg intake and not reaching adequate intake of PUFAs. Seafood consumption data was collected among women of childbearing age using a food frequency questionnaire. A database of mercury and fatty acids concentration in seafood was constructed. A Latin Hypercube simulation was used to calculate the intake of MeHg and LC n-3 PUFAs. Eleven percent of the population exceeded the MeHg reference dose of 0.1 μg/kg bw/day, whereas only 44% reached an adequate PUFA intake. A small proportion (3.7%) exceeded the MeHg reference dose while at the same time did not reach an adequate PUFA intake. Furthermore, we simulated two scenarios in which seafood is consumed according to a general recommendation of three servings per week, whereof one serving of oily seafood. The first scenario included seafood with typically low MeHg concentrations (mean 0.056 and 0.027 μg MeHg/g fish in lean and oily species, respectively), and the second included seafood typically high in MeHg concentrations (mean 0.50 and 0.26 μg MeHg/g fish in lean and oily species, respectively). In the "high"scenario, almost 100% of the population exceeded the reference dose, whereas the corresponding proportion was only 5% in the "low" scenario. Overall, the results stress the importance of communicating species specific seafood consumption advisories for women of childbearing age in general and for pregnant women in particular, while at the same time encourage them to consume more seafood., (Copyright © 2010 Elsevier Inc. All rights reserved.)

In vivo bone lead measurements with 109Cd-based K-shell X-ray fluorescence (XRF) have been used to assess long-term lead exposure in adults. Tibia lead levels were measured in 210 children (106 boys, 104 girls) of 11-12(1/2) years of age in a lead smelter town and in a control (nonexposed) town. Tibia lead levels, methodological uncertainties, and models of some of the factors influencing them are presented. 109Cd-based K-shell XRF tibia lead methodological uncertainty in children is comparable to that in adults., (Copyright 2001 Academic Press.)

Regulatory guidelines regarding methylmercury exposure depend on dose-response models relating observed mercury concentrations in maternal blood, cord blood, and maternal hair to developmental neurobehavioral endpoints. Generalized estimates of the maternal blood-to-hair, blood-to-intake, or hair-to-intake ratios are necessary for linking exposure to biomarker-based dose-response models. Most assessments have used point estimates for these ratios; however, significant interindividual and interstudy variability has been reported. For example, a maternal ratio of 250 ppm in hair per mg/L in blood is commonly used in models, but a 1990 WHO review reports mean ratios ranging from 140 to 370 ppm per mg/L. To account for interindividual and interstudy variation in applying these ratios to risk and safety assessment, some researchers have proposed representing the ratios with probability distributions and conducting probabilistic assessments. Such assessments would allow regulators to consider the range and like-lihood of mercury exposures in a population, rather than limiting the evaluation to an estimate of the average exposure or a single conservative exposure estimate. However, no consensus exists on the most appropriate distributions for representing these parameters. We discuss published reviews of blood-to-hair and blood-to-intake steady state ratios for mercury and suggest statistical approaches for combining existing datasets to form generalized probability distributions for mercury distribution ratios. Although generalized distributions may not be applicable to all populations, they allow a more informative assessment than point estimates where individual biokinetic information is unavailable. Whereas development and use of these distributions will improve existing exposure and risk models, additional efforts in data generation and model development are required.

Renal effects of cadmium exposure in people living in a cadmium-nonpolluted area in Japan were investigated. The population consisted of 1501 inhabitants (558 men and 743 women) over 50 years of age. Urinary cadmium was employed as an indicator of internal dose, and total urinary protein, beta 2-microglobulin, and N-acetyl-beta-glucosaminidase were used as indicators of renal dysfunction. Multiple regression analysis and a logistic regression analysis were performed to study the relationship between urinary cadmium excretion and these indicators of renal dysfunction. In both procedures, urinary cadmium concentrations were significantly associated with indicators of renal dysfunction. These results suggest the existence of renal dysfunction induced by exposure to environmental cadmium in a cadmium-nonpolluted area in Japan.

This study demonstrates the use of probability plots for assessing exposure-disease relationships in case-control studies. We reanalyze data from a study of childhood asthma and exposure to environmental tobacco smoke, comparing alternative measures of smoking intensity. Previous analyses showed a higher mean urinary cotinine-to-creatinine ratio (CCR) in cases as compared with controls and a statistically significant odds ratio with exposure defined as 30 ng/mg CCR or higher. Using probability plots, we compare alternative exposure metrics and exposure cutpoints with respect to their ability to detect a statistically significant exposure-disease effect. A strong exposure-disease response is evident, overall, and the results are fairly robust to the choice of exposure cutpoint.

Screening programs for lead overexposure typically target high-risk populations by identifying regions with common risk markers (older housing, poverty, etc.). While more useful than untargeted screening programs, targeted programs are limited by the geographic resolution of the risk-factor information. A geographic information system can make screening programs more effective and more cost-efficient by mapping cases of overexposure, identifying high-incidence neighborhoods warranting screening, and validating risk-factor-based prediction rules.

The determination of blood lead levels was included in a Swiss population survey on cardiovascular risk factors in 1984-1985; 931 men and 843 women aged 25 to 75 years participated in the study. Mean blood lead levels (+/- SD) were 0.63 +/- 0.27 mumole/liter for men and 0.44 +/- 0.19 mumole/liter for women, respectively, with a slight increase with age for both sexes. These values are below the maximum level recommended by the Commission of the European Community in 1977; 18 cases were found with blood lead higher than 1.5 mumole/liter and in six of these, a professional exposure was suspected. Smoking habits, drinking habits, and consumption of dairy products were selected as lifestyle descriptors and educational level, occupational category, and size of the community as sociodemographic indicators. Smoking and alcohol consumption show a direct association with blood lead, consuming dairy products an inverse one. Occupation and level of education are significantly related to blood lead only for men, blue-collar workers and less-educated men being more exposed. A higher blood lead level in cities was only found for women presumably because they stay at home more often than men and are therefore more sensitive to local exposure. In a multiple stepwise logistic regression, the lifestyle indicators showed a consistently stronger effect on blood lead than sociodemographic indicators. For men, smoking has an effect on blood lead for blue-collar workers much stronger than that for nonindustrial employees and may compound in some way the professional exposure to lead. This stresses the fact that interactions between lifestyle and environmental factors on blood lead are significant, complex, and need further investigation.

While lead paint has long been known to be a major source of lead poisoning, only a few small epidemiologic studies have attempted to assess directly the relative risk of lead poisoning due to the presence of lead paint. Using data from over 200,000 screening tests of children in the city of Chicago performed between 1976 and 1980, the relative risks can be quantified for children living in a major urban area. Lead paint was found to be a significant predictor of the probability of a child having lead toxicity. As expected, the reduction in leaded gasoline sales during the period reduced mean blood lead levels and increased the percentage of lead toxic children whose toxicity could be attributed to paint lead. Poisson regression models indicated that with the elimination of leaded gasoline, the relative risk of lead toxicity given lead paint exposure was 5.70 (95% CI, 4.13-7.86) during the winter and fall. The relative risk rose to 12.81 (95% CI, 7.33-22.4) in the spring and 15.8 (95% CI, 8.90-28.1) in the summer, probably due to increased exposure to window wells.

The U.S. Environmental Protection Agency sampled air in 49 government-owned buildings (six buildings with no asbestos-containing material, six buildings with asbestos-containing material in generally good condition, and 37 buildings with damaged asbestos-containing material). This is the most comprehensive study to date of airborne asbestos levels in U.S. public buildings during normal building activities. The air outside each building was also sampled. Air samples were analyzed by transmission electron microscopy using a direct transfer preparation technique. The results show an increasing trend in average airborne asbestos levels; outdoor levels are lowest and levels in buildings with damaged asbestos-containing material are highest. However, the measured levels and the differences between indoors and outdoors and between building categories are small in absolute magnitude. Comparable studies from Canada and the UK, although differing in their estimated concentrations, also conclude that while airborne asbestos levels may be elevated in buildings that contain asbestos, levels are generally low. This conclusion does not eliminate the possibility of higher airborne asbestos levels during maintenance or renovation that disturbs the asbestos-containing material.

EPA's TEAM Study has measured exposures to 20 volatile organic compounds in personal air, outdoor air, drinking water, and breath of approximately 400 residents of New Jersey, North Carolina, and North Dakota. All residents were selected by a probability sampling scheme to represent 128,000 inhabitants of Elizabeth and Bayonne, New Jersey, 131,000 residents of Greensboro, North Carolina, and 7000 residents of Devils Lake, North Dakota. Participants carried a personal monitor to collect two 12-hr air samples and gave a breath sample at the end of the day. Two consecutive 12-hr outdoor air samples were also collected on identical Tenax cartridges in the backyards of some of the participants. About 5000 samples were collected, of which 1500 were quality control samples. Ten compounds were often present in personal air and breath samples at all locations. Personal exposures were consistently higher than outdoor concentrations for these chemicals and were sometimes 10 times the outdoor concentrations. Indoor sources appeared to be responsible for much of the difference. Breath concentrations also often exceeded outdoor concentrations and correlated more strongly with personal exposures than with outdoor concentrations. Some activities (smoking, visiting dry cleaners or service stations) and occupations (chemical, paint, and plastics plants) were associated with significantly elevated exposures and breath levels for certain toxic chemicals. Homes with smokers had significantly increased benzene and styrene levels in indoor air. Residence near major point sources did not affect exposure.

We present a method we developed to overcome some of the problems that are encountered in the attempts to identify acute health effects of environmental stimuli such as air pollution. To illustrate this method we have used daily records of asthmatic attacks in New York City. We also review some of the shortcomings of the presently used regression techniques, where a health variable is regressed on one or more environmental variables.

In animal experiments, the probability that pleural tumors will develop after mineral fiber implantation is dependent upon the fiber's size. This was originally analyzed in relation to the number of injected fibers with specific dimensional characteristics and, more recently, in relation to average aspect ratio (average length/diameter ratio). New experimental data on various mineral fibers suggest that the carcinogenic potency of a solid particle depends on two parameters: the nature of the mineral and therefore the nature of active surface sites, and the aspect ratio of the particle. These two parameters can intervene in a mechanism of model reaction involving the basic properties of lateral faces of fibers.

To minimize the problems of sample mass inconsistency associated with limited fiber counts, a model has been developed to predict the particle size distribution for crocidolite asbestos fibers with lengths exceeding the median log length value. With this model, it is possible to predict the dimensions of many more fibers than it is practical to measure by typical electron microscopic techniques. Thus, sample mass extrapolations, required for animal implantation studies, can be based on a much larger number of particles, reducing error that could occur, for example, from the presence of one or two very large particles. The model assumes a linear relationship between length and width. The number of fibers predicted in each length category is determined from the measured data. Particle lengths were randomly chosen within size classes, and the corresponding widths were predicted using the model. The similarity of the predicted population to the actual population was tested by comparing the width distributions using the chi-square test at the 90% confidence level. Model populations ranging from 250 to 10,000 particles were predicted. Those populations with 2500 or more fibers were similar to the actual sample in their size characteristics. Predicted populations in excess of 7500 fibers were required to produce consistent sample masses.

Pregnancy outcome was studied in three parishes situated around a chemical factory from which air and water pollution was considered to have occurred. Data on health variables were mainly obtained from registries supplemented with hospital record information. No definite reproductive hazards could be demonstrated but an unusually high perinatal death rate among twins born in the area was noticed. The paper discusses principles involved in the design of a study of this type.