Assessment of risks for adaptation to climate change: the case of land-slides

This paper describes how relatively detailed knowledge about probabilities of natural hazards can be used to make decisions to develop areas and control the risk within hazard zones. The assessment serves two purposes. First, it shows how information can support decisions. Second, decision criteria put leads on what information is required. This is helpful to identify unavailable information. We show by an example from a land-slide prone area in Norway how a relatively reliable estimate of the probability of slides ends up in a rather uncertain estimate of the risk. Uncertainty about the risk represented by natural hazards imply great challenges to the development of adaptation policies to meet climate change, but they are required. We develop a simplified criterion for optimal adaptation, and estimate the added social value required to defend development in hazard prone areas instead of developing a risk-free alternative. The value is estimated between 0 and 0.40 Euros per Euro invested in the case area, depending on type of slide, category of asset and other costs that occur in the wake of slides.     

Early detection of fetal cardiac abnormalities: how effective is it and how should we manage these patients?

Congenital heart defects (CHDs), the most commonly occurring congenital malformations, cause significant mortality and morbidity. With the recognition of early markers for CHD and the development of better ultrasound resolution, interest has turned toward performing a screening anomaly scan, including the heart, together with the nuchal scan. It is also possible, with adequate skill and training, to competently perform an echocardiogram <16 weeks' gestation. This article reviews the detection of major CHD in the first trimester and early second trimester including specific markers that help to identify high-risk groups for early fetal echocardiography (EFEC). CHD detection during first-trimester screening is low (2.3–56%) depending on the center's experience and the population studied. An increased nuchal translucency, abnormal ductus venosus flow, and tricuspid regurgitation in the first trimester are associated with an increased CHD risk and can be used together to identify high-risk fetuses for EFEC. EFEC requires skilled scanning and the expertise of a fetal echocardiographer. In high-risk populations, it is 78.5% sensitive with a 74.5% concordance between the EFEC and the mid-gestational echocardiogram. The availability of qualified personnel and diagnostic accuracy are prerequisites before EFEC can be introduced into management protocols. The limitations of EFEC should be recognized, and a later confirmatory echocardiogram is recommended. © 2014 John Wiley & Sons, Ltd.     

Aseptically collected calf serum as an effective alternative to fetal calf serum in the culture of amniotic fluid cells

The growth-promoting activities of three different bovine sera have been compared in primary and secondary amniotic fluid cell cultures. In secondary amniotic fluid cell micro- cultures, aseptically collected calf serum (CS) was slightly, though not significantly more effective than fetal calf serum (FCS) in promoting DNA synthesis, while newborn calf serum (NCS) was significantly less effective than either CS or FCS. All three sera were optimally effective at concentrations of 10 per cent (v/v). Significant variation in quality occurred within four batches of each of CS and FCS, but not within four batches of NCS. A selected batch of CS was significantly more effective in promoting the growth of primary amniotic fluid cell cultures than were a number of batches of FCS then in routine laboratory use. It is suggested that CS may serve as an effective and economical alternative to FCS in the culture of amniotic fluid cells, thereby expanding the scope of serum batch testing. A possible explanation for the varying growth-promoting activities of different sera is discussed.     

Particulate matter concentration in ambient air and its effects on lung functions among residents in the National Capital Region, India

The World Health Organization has estimated that air pollution is responsible for 1.4 % of all deaths and 0.8 % of disability-adjusted life years. NOIDA, located at the National Capital Region, India, was declared as one of the critically air-polluted areas by the Central Pollution Control Board of the Government of India. Studies on the relationship of reduction in lung functions of residents living in areas with higher concentrations of particulate matter (PM) in ambient air were inconclusive since the subjects of most of the studies are hospital admission cases. Very few studies, including one from India, have shown the relationship of PM concentration and its effects of lung functions in the same location. Hence, a cross-sectional study was undertaken to study the effect of particulate matter concentration in ambient air on the lung functions of residents living in a critically air-polluted area in India. PM concentrations in ambient air (PM_1, PM_2.5) were monitored at residential locations and identified locations with higher (NOIDA) and lower concentrations (Gurgaon). Lung function tests (FEV₁, PEFR) were conducted using a spirometer in 757 residents. Both air monitoring and lung function tests were conducted on the same day. Significant negative linear relationship exists between higher concentrations of PM₁ with reduced FEV₁ and increased concentrations of PM_2.5 with reduced PEFR and FEV₁. The study shows that reductions in lung functions (PEFR and FEV₁) can be attributed to higher particulate matter concentrations in ambient air. Decline in airflow obstruction in subjects exposed to high PM concentrations can be attributed to the fibrogenic response and associated airway wall remodeling. The study suggests the intervention of policy makers and stake holders to take necessary steps to reduce the emissions of PM concentrations, especially PM_1, PM_2.5, which can lead to serious respiratory health concerns in residents.     

Accuracy and uncertainty assessment on geostatistical simulation of soil salinity in a coastal farmland using auxiliary variable

Understanding the spatial soil salinity aids farmers and researchers in identifying areas in the field where special management practices are required. Apparent electrical conductivity measured by electromagnetic induction instrument in a fairly quick manner has been widely used to estimate spatial soil salinity. However, methods used for this purpose are mostly a series of interpolation algorithms. In this study, sequential Gaussian simulation (SGS) and sequential Gaussian co-simulation (SGCS) algorithms were applied for assessing the prediction accuracy and uncertainty of soil salinity with apparent electrical conductivity as auxiliary variable. Results showed that the spatial patterns of soil salinity generated by SGS and SGCS algorithms showed consistency with the measured values. The profile distribution of soil salinity was characterized by increasing with depth with medium salinization (EC_e 4–8 dS/m) as the predominant salinization class. SGCS algorithm privileged SGS algorithm with smaller root mean square error according to the generated realizations. In addition, SGCS algorithm had larger proportions of true values falling within probability intervals and narrower range of probability intervals than SGS algorithm. We concluded that SGCS algorithm had better performance in modeling local uncertainty and propagating spatial uncertainty. The inclusion of auxiliary variable contributed to prediction capability and uncertainty modeling when using densely auxiliary variable as the covariate to predict the sparse target variable.     

Spatial patterns of heavy metals in soil under different geological structures and land uses for assessing metal enrichments

One hundred and thirty composite soil samples were collected from Hamedan county, Iran to characterize the spatial distribution and trace the sources of heavy metals including As, Cd, Co, Cr, Cu, Ni, Pb, V, Zn, and Fe. The multivariate gap statistical analysis was used; for interrelation of spatial patterns of pollution, the disjunctive kriging and geoenrichment factor (EF_G) techniques were applied. Heavy metals and soil properties were grouped using agglomerative hierarchical clustering and gap statistic. Principal component analysis was used for identification of the source of metals in a set of data. Geostatistics was used for the geospatial data processing. Based on the comparison between the original data and background values of the ten metals, the disjunctive kriging and EF_G techniques were used to quantify their geospatial patterns and assess the contamination levels of the heavy metals. The spatial distribution map combined with the statistical analysis showed that the main source of Cr, Co, Ni, Zn, Pb, and V in group A land use (agriculture, rocky, and urban) was geogenic; the origin of As, Cd, and Cu was industrial and agricultural activities (anthropogenic sources). In group B land use (rangeland and orchards), the origin of metals (Cr, Co, Ni, Zn, and V) was mainly controlled by natural factors and As, Cd, Cu, and Pb had been added by organic factors. In group C land use (water), the origin of most heavy metals is natural without anthropogenic sources. The Cd and As pollution was relatively more serious in different land use. The EF_G technique used confirmed the anthropogenic influence of heavy metal pollution. All metals showed concentrations substantially higher than their background values, suggesting anthropogenic pollution.