Daily Archives: April 27, 2015

Routine Storage Tank Cleaning Necessary to Eliminate Opportunistic Pathogens in Sediments

Struewing I, Yelton S, Ashbolt N. Molecular Survey of Occurrence and Quantity of Legionella spp., Mycobacterium spp., Pseudomonas aeruginosa and Amoeba Hosts in Municipal Drinking Water Storage Tank Sediments. Journal of Applied Microbiology. 2015 Apr 17. doi: 10.1111/jam.12831.

AIM: To examine the occurrence and quantity of potential pathogens and an indicator of microbial contamination in the sediments of municipal drinking water storage tanks (MDWSTs), given the absence of such data across the United States.

METHODS AND RESULTS: Sediment samples (87 MDWST) from eighteen locations across ten states of the U.S. were collected and assayed by qPCR for a range of potential enteric and opportunistic microbial pathogens and a sewage-associated Bacteroides marker. Potential opportunistic pathogens dominated, with the highest detection of occurrence (% positive detection; average cell equivalence [CE]) being Mycobacterium spp. (88.9%; 6.7 ± 8.5 x104 CE g-1 ), followed by Legionella spp. (66.7%; 5.2 ±5.9 x 103 CE g-1 ), Pseudomonas aeruginosa (22.2%; 250 ± 880 CE g-1 ), and Acanthamoeba spp. (38.9%; 53 ± 70 CE g-1 ), with no detected Naegleria fowleri. Most enteric pathogens (Campylobacter jejuni, Escherichia coli 0157:H7, Salmonella enterica, Cryptosporidium parvum and Giardia duodenalis) were not detected, except for a trace signal for Campylobacter spp. There was significant correlation between the qPCR signals of Legionella spp. and Acanthamoeba spp. (R2 =0.61, n=87, P=0.0001). Diverse Legionella spp. including L. pneumophila, L. pneumophila sg1 and L. anisa were identified, each of which might cause legionellosis.

CONCLUSIONS: These results imply that potential opportunistic pathogens are common within MDWST sediments and could act as a source of microbial contamination, but needing downstream growth to be of potential concern.

SIGNIFICANCE AND IMPACT OF THE STUDY: The results imply that opportunistic pathogen risks may need to be managed by regular tank cleaning or other management practices.

Click here for paper (fee).

Climate Models are Unreliable for Predicting the Future

This latest study is simply one more to confirm the unreliability of climate models. By fiddling with the assumptions an analyst can generate just about any outcome they would like. Consider this comparison of the various climate models and actual measurements.


Relying on climate models to predict or even comment on the future is squarely in the category of fortune telling. Such analyses are useful and worthwhile from an academic perspective, but they are being applied in a cavalier manner (e.g. here). Climate models are fraught with implicit assumptions that drive the outcome. To take just one, even Philosopher David Hume would object to the implicit assumption in every model that the future will be even remotely like the past. This is true even for the newest model in the paper cited below. There is no sound basis for this assumption. 

Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise Patrick T. Brown, Wenhong Li, Eugene C. Cordero, Steven A. Mauget. Scientific Reports; April 2015, Vol. 5 Issue: 1 p9957-9957

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20thcentury does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario’s forced signal, but is likely inconsistent with the steepest emission scenario’s forced signal.

Click here for full paper (Open Access).


Arsenic and Cardiovascular Disease, Inner Mongolia, China

The association between arsenic exposure and cardiovascular disease is not new. Whether the findings of this study apply to a general population elsewhere is highly debatable.

Wade TJ, Xia Y, Mumford J, Wu K, Le XC, Sams E, Sanders WE. Cardiovascular disease and arsenic exposure in Inner Mongolia, China: a case control study. Environmental health 2015 Apr 12;14(1):35.

Background: Millions of people are at risk from the adverse effects of arsenic exposure through drinking water. Increasingly, non-cancer effects such as cardiovascular disease have been associated with drinking water arsenic exposures. However, most studies have been conducted in highly exposed populations and lacked individual measurements.

Objective: To evaluate the association between cardiovascular disease and well-water arsenic exposure.

Methods: We conducted a hospital based case control study in Inner Mongolia, China. Cases and controls were prospectively identified and enrolled from a large hospital in the Hangjin Hou area. Cases were patients diagnosed with cardiovascular disease and controls were patients free from cardiovascular disease, admitted for conditions unrelated to arsenic exposure. Water from the primary water source and toenail samples were collected from each subject and tested for inorganic arsenic.

Results: Arsenic exposures were moderate with mean and median arsenic exposures of 8.9 μg/L and 13.1 μg/L, respectively. A total of 298 cases and 275 controls were enrolled. The adjusted odds ratio (AOR) and corresponding 95% confidence interval (95% CI) for a 10 μg/L increase in water arsenic were 1.19 (95% CI: 1.03, 1.38). Compared to exposures less than 10 μg/L, the AOR for water arsenic exposures above 40 μg/L was 4.05 (95% CI: 1.1-14.99, p = 0.04). Nail arsenic above 1.38 μg/g was also associated with an increased risk of cardiovascular disease.

Conclusions: By using standardized case definitions and collecting individual measurements of arsenic, this study addressed several limitations of previous studies. The results provide further evidence of the association between cardiovascular disease and arsenic at moderate exposures.

Click here for paper (Open Access).