principiascientificinternational--2020-05-25--Why Masks Don’t Work Against COVID-19

Why Masks Don’t Work Against COVID-19

Masks and respirators do not work .
There have been extensive randomized controlled trial ( RCT ) studies , and meta-analysis reviews of RCT studies , which all show that masks and respirators do not work to prevent respiratory influenza-like illnesses , or respiratory illnesses believed to be transmitted by droplets and aerosol particles .
Furthermore , the relevant known physics and biology , which I review , are such that masks and respirators should not work .
It would be a paradox if masks and respirators worked , given what we know about viral respiratory diseases : The main @ @ @ @ @ @ @ < 2.5 μm ) , which are too fine to be blocked , and the minimum-infective-dose is smaller than one aerosol particle .
The present paper about masks illustrates the degree to which governments , the mainstream media , and institutional propagandists can decide to operate in a science vacuum , or select only incomplete science that serves their interests .
Such recklessness is also certainly the case with the current global lockdown of over 1 billion people , an unprecedented experiment in medical and political history .
Review of the Medical Literature @ @ @ @ @ @ @ extensive scientific literature that establishes that wearing surgical masks and respirators ( e.g.
, “ N95 ” ) does not reduce the risk of contracting a verified illness : Jacobs , J. L. et al .
( 2009 ) “ Use of surgical face masks to reduce the incidence of the common cold among health care workers in Japan : A randomized controlled trial ” , nAmerican Journal of Infection Control , Volume 37 , Issue 5 , 417 – 419. https : //www.ncbi.nlm.nih.gov/pubmed/19216002 N95-masked health-care workers ( HCW ) were significantly more @ @ @ @ @ @ @ use in HCW was not demonstrated to provide benefit in terms of cold symptoms or getting colds .
Cowling , B. et al .
( 2010 ) “ Face masks to prevent transmission of influenza virus : A systematic review ” , Epidemiology and Infection , 138 ( 4 ) , 449-456. doi:10.1017/S0950268809991658 https : //www.cambridge.org/core/journals/epidemiology-and-infection/article/facemasks-to-prevent-transmission-of-influenza-virus-a systematicreview/64D368496EBDE0AFCC6639CCC9D8BC05 None of the studies reviewed showed a benefit from wearing a mask , in either HCW or community members in households ( H ) .
See summary Tables 1 and 2 therein .
bin-Reza et al @ @ @ @ @ @ @ of masks and respirators to prevent transmission of influenza : a systematic review of the scientific evidence ” , Influenza and Other Respiratory Viruses 6 ( 4 ) , 257–267 .
https : //onlinelibrary.wiley.com/doi/epdf/10.1111/j.1750-2659.2011.00307.x Conclusion Regarding that Masks Do Not Work No RCT study with verified outcome shows a benefit for HCW or community members in households to wearing a mask or respirator .
There is no such study .
There are no exceptions .
Likewise , no study exists that shows a benefit from a broad policy to wear masks in public @ @ @ @ @ @ @ Furthermore , if there were any benefit to wearing a mask , because of the blocking power against droplets and aerosol particles , then there should be more benefit from wearing a respirator ( N95 ) compared to a surgical mask , yet several large meta-analyses , and all the RCT , prove that there is no such relative benefit .
Masks and respirators do not work .
Precautionary Principle Turned on Its Head with Masks In light of the medical research , therefore , it is difficult to understand why public-health authorities @ @ @ @ @ @ @ scientific result , since the distributed psychological , economic and environmental harm from a broad recommendation to wear masks is significant , not to mention the unknown potential harm from concentration and distribution of pathogens on and from used masks .
In this case , public authorities would be turning the precautionary principle on its head ( see below ) .
Physics and Biology of Viral Respiratory Disease and of Why Masks Do Not Work In order to understand why masks can not possibly work , we must review established knowledge about viral @ @ @ @ @ @ @ variation of excess deaths from pneumonia and influenza , the aerosol mechanism of infectious disease transmission , the physics and chemistry of aerosols , and the mechanism of the so-called minimum-infective-dose .
In addition to pandemics that can occur anytime , in the temperate latitudes there is an extra burden of respiratory-disease mortality that is seasonal , and that is caused by viruses .
For example , see the review of influenza by Paules and Subbarao ( 2017 ) .
This has been known for a long time , and the seasonal pattern @ @ @ @ @ @ @ see Figure 1 of Viboud ( 2010 ) , which has The seasonality of the phenomenon was largely not understood until a decade ago .
Until recently , it was debated whether the pattern arose primarily because of seasonal change in virulence of the pathogens , or because of seasonal change in susceptibility of the host ( such as from dry air causing tissue irritation , or diminished daylight causing vitamin deficiency or hormonal stress ) .
For example , see Dowell ( 2001 ) .
In a landmark study , Shaman et @ @ @ @ @ @ @ the seasonal pattern of extra respiratory-disease mortality can be explained quantitatively on the sole basis of absolute humidity , and its direct controlling impact on transmission of airborne pathogens .
Lowen et al .
( 2007 ) demonstrated the phenomenon of humidity-dependent airborne-virus virulence in actual disease transmission between guinea pigs , and discussed potential underlying mechanisms for the measured controlling effect of humidity .
The underlying mechanism is that the pathogen-laden aerosol particles or droplets are neutralized within a half-life that monotonically and significantly decreases with increasing ambient humidity .
This is @ @ @ @ @ @ @ ( 1961 ) .
Harper experimentally showed that viral-pathogen-carrying droplets were inactivated within shorter and shorter times , as ambient humidity was increased .
Harper argued that the viruses themselves were made inoperative by the humidity ( “ viable decay ” ) , however , he admitted that the effect could be from humidity-enhanced physical removal or sedimentation of the droplets ( “ physical loss ” ) : The latter ( “ physical loss ” ) seems more plausible to me , since humidity would have a universal physical effect of causing particle @ @ @ @ @ @ @ all tested viral pathogens have essentially the same humidity-driven “ decay ” .
Furthermore , it is difficult to understand how a virion ( of all virus types ) in a droplet would be molecularly or structurally attacked or damaged by an increase in ambient humidity .
A “ virion ” is the complete , infective form of a virus outside a host cell , with a core of RNA or DNA and a capsid .
The actual mechanism of such humidity-driven intra-droplet “ viable decay ” of a virion has not been @ @ @ @ @ @ @ , the explanation and model of Shaman et al .
( 2010 ) is not dependent on the particular mechanism of the humidity-driven decay of virions in aerosol / droplets .
Shaman ’ s quantitatively demonstrated model of seasonal regional viral epidemiology is valid for either mechanism ( or combination of mechanisms ) , whether “ viable decay ” or “ physical loss ” .
The breakthrough achieved by Shaman et al .
is not merely some academic point .
Rather , it has profound health-policy implications , which have been entirely ignored @ @ @ @ @ @ @ .
In particular , Shaman ’ s work necessarily implies that , rather than being a fixed number ( dependent solely on the spatial-temporal structure of social interactions in a completely susceptible population , and on the viral strain ) , the epidemic ’ s basic reproduction number ( R0 ) is highly or predominantly dependent on ambient absolute humidity .
For a definition of R0 , see HealthKnowlege-UK ( 2020 ) : R0 is The average R0 for influenza is said to be 1.28 ( 1.19–1.37 ) ; see the comprehensive review @ @ @ @ @ @ @ ) .
In fact , Shaman et al .
showed that R0 must be understood to seasonally vary between humid summer values of just larger than “ 1 ” and dry-winter values typically as large as “ 4 ” ( for example , see their Table 2 ) .
In other words , the seasonal infectious viral respiratory diseases that plague temperate latitudes every year go from being intrinsically mildly contagious to virulently contagious , due simply to the bio-physical mode of transmission controlled by atmospheric humidity , irrespective of any other consideration @ @ @ @ @ @ @ modelling of the benefits of mediating policies ( such as social distancing ) , which assumes humidity-independent R0 values , has a large likelihood of being of little value , on this basis alone .
For studies about modelling and regarding mediation effects on the effective reproduction number , see Coburn ( 2009 ) and Tracht ( 2010 ) .
To put it simply , the “ second wave ” of an epidemic is not a consequence of human sin regarding mask wearing and hand shaking .
Rather , the “ second wave @ @ @ @ @ @ @ air-dryness-driven many-fold increase in disease contagiousness , in a population that has not yet attained immunity .
If my view of the mechanism is correct ( i.e.
, “ physical loss ” ) , then Shaman ’ s work further necessarily implies that the dryness-driven high transmissibility ( large R0 ) arises from small aerosol particles fluidly suspended in the air ; as opposed to large droplets that are quickly gravitationally removed from the air .
Such small aerosol particles fluidly suspended in air , of biological origin , are of every variety @ @ @ @ @ @ @ virion-sizes ( Despres , 2012 ) .
It is not entirely unlikely that viruses can thereby be physically transported over inter-continental distances ( e.g.
, Hammond , 1989 ) .
More to the point , indoor airborne virus concentrations have been shown to exist ( in day-care facilities , health centres , and onboard airplanes ) primarily as aerosol particles of diameters smaller than 2.5 μm , such as in the work of Yang et al .
( 2011 ) : Such small particles ( < 2.5 μm ) are part of air @ @ @ @ @ @ @ sedimentation , and would not be stopped by long-range inertial impact .
This means that the slightest ( even momentary ) facial misfit of a mask or respirator renders the design filtration norm of the mask or respirator entirely irrelevant .
In any case , the filtration material itself of N95 ( average pore size ~0.3−0.5 μm ) does not block virion penetration , not to mention surgical masks .
For example , see Balazy et al .
( 2006 ) .
Mask stoppage efficiency and host inhalation are only half of the @ @ @ @ @ @ @ infective dose ( MID ) must also be considered .
For example , if a large number of pathogen-laden particles must be delivered to the lung within a certain time for the illness to take hold , then partial blocking by any mask or cloth can be enough to make a significant difference .
On the other hand , if the MID is amply surpassed by the virions carried in a single aerosol particle able to evade mask-capture , then the mask is of no practical utility , which is the case .
@ @ @ @ @ @ @ in their review of the MID , point out relevant features : • most respiratory viruses are as infective in humans as in tissue culture having optimal laboratory susceptibility • it is believed that a single virion can be enough to induce illness in the host • the 50 % -probability MID ( “ TCID50 ” ) has variably been found to be in the range 100−1000 virions • there are typically 103−107 virions per aerolized influenza droplet with diameter 1 μm −10 μm • the 50 % -probability MID easily fits into @ @ @ @ @ @ @ For further background : • A classic description of dose-response assessment is provided by Haas ( 1993 ) .
• Zwart et al .
( 2009 ) provided the first laboratory proof , in a virus-insect system , that the action of a single virion can be sufficient to cause disease .
• Baccam et al .
( 2006 ) calculated from empirical data that , with influenza A in humans , “ we estimate that after a delay of ~6 h , infected cells begin producing influenza virus and continue to do @ @ @ @ @ @ @ of infected cells is ~11 h , and the half-life of free infectious virus is ~3 h. We calculated the [ in-body ] basic reproductive number , R0 , which indicated that a single infected cell could produce ~22 new productive infections.
” • Brooke et al .
( 2013 ) showed that , contrary to prior modeling assumptions , although not all influenza-A-infected cells in the human body produce infectious progeny ( virions ) , nonetheless , 90 % of infected cell are significantly impacted , rather than simply surviving unharmed .
@ @ @ @ @ @ @ if anything gets through ( and it always does , irrespective of the mask ) , then you are going to be infected .
Masks can not possibly work .
It is not surprising , therefore , that no bias-free study has ever found a benefit from wearing a mask or respirator in this application .
Therefore , the studies that show partial stopping power of masks , or that show that masks can capture many large droplets produced by a sneezing or coughing mask-wearer , in light of the above-described features of @ @ @ @ @ @ @ example , such studies as these : Leung ( 2020 ) , Davies ( 2013 ) , Lai ( 2012 ) , and Sande ( 2008 ) .
Why There Can Never Be an Empirical Test of a Nation-Wide Mask-Wearing Policy As mentioned above , no study exists that shows a benefit from a broad policy to wear masks in public .
There is good reason for this .
It would be impossible to obtain unambiguous and biasfree results : • Any benefit from mask-wearing would have to be a small effect , @ @ @ @ @ @ @ would be swamped by the larger effects , notably the large effect from changing atmospheric humidity .
• Mask compliance and mask adjustment habits would be unknown .
• Mask-wearing is associated ( correlated ) with several other health behaviours ; see Wada ( 2012 ) .
• The results would not be transferable , because of differing cultural habits .
• Compliance is achieved by fear , and individuals can habituate to fear-based propaganda , and can have disparate basic responses .
• Monitoring and compliance measurement are near-impossible , and subject @ @ @ @ @ @ @ such as in surveys ) is notoriously biased , because individuals have the self-interested belief that their efforts are useful .
• Progression of the epidemic is not verified with reliable tests on large population samples , and generally relies on non-representative hospital visits or admissions .
• Several different pathogens ( viruses and strains of viruses ) causing respiratory illness generally act together , in the same population and/or in individuals , and are not resolved , while having different epidemiological characteristics .
Unknown Aspects of Mask Wearing Many potential harms may @ @ @ @ @ @ @ masks , and the following unanswered questions arise : • Do used and loaded masks become sources of enhanced transmission , for the wearer and others ?
10 • Do masks become collectors and retainers of pathogens that the mask wearer would otherwise avoid when breathing without a mask ?
• Are large droplets captured by a mask atomized or aerolized into breathable components ?
Can virions escape an evaporating droplet stuck to a mask fiber ?
• What are the dangers of bacterial growth on a used and loaded mask ?
• @ @ @ @ @ @ @ dust and aerosols captured on the mask ?
• What are long-term health effects on HCW , such as headaches , arising from impeded breathing ?
• Are there negative social consequences to a masked society ?
• Are there negative psychological consequences to wearing a mask , as a fear-based behavioural modification ?
• What are the environmental consequences of mask manufacturing and disposal ?
• Do the masks shed fibres or substances that are harmful when inhaled ?
Conclusion By making mask-wearing recommendations and policies for the general public , or @ @ @ @ @ @ @ have both ignored the scientific evidence and done the opposite of following the precautionary principle .
In an absence of knowledge , governments should not make policies that have a hypothetical potential to cause harm .
The government has an onus barrier before it instigates a broad socialengineering intervention , or allows corporations to exploit fear-based sentiments .
Furthermore , individuals should know that there is no known benefit arising from wearing a mask in a viral respiratory illness epidemic , and that scientific studies have shown that any benefit must be residually @ @ @ @ @ @ @ factors .
Otherwise , what is the point of publicly funded science ?
The present paper about masks illustrates the degree to which governments , the mainstream media , and institutional propagandists can decide to operate in a science vacuum , or select only incomplete science that serves their interests .
Such recklessness is also certainly the case with the current global lockdown of over 1 billion people , an unprecedented experiment in medical and political history .
Endnotes : Baccam , P. et al .
( 2006 ) “ Kinetics of Influenza @ @ @ @ @ @ @ Journal of Virology Jul 2006 , 80 ( 15 ) 7590-7599 ; DOI : 10.1128/JVI.01623-05 https : //jvi.asm.org/content/80/15/7590 Balazy et al .
( 2006 ) “ Do N95 respirators provide 95 % protection level against airborne viruses , and how adequate are surgical masks ?
” , American Journal of Infection Control , Volume 34 , Issue 2 , March 2006 , Pages 51-57. doi:10.1016/j.ajic.2005.08.018 http : //citeseerx.ist.psu.edu/viewdoc/download ?
doi=10.1.1.488.4644 & rep=rep1 & type=pdf Biggerstaff , M. et al .
( 2014 ) “ Estimates of the reproduction number for seasonal , pandemic @ @ @ @ @ @ @ review of the literature ” , BMC Infect Dis 14 , 480 ( 2014 ) .
https : //doi.org/10.1186/1471-2334-14-480 Brooke , C. B. et al .
( 2013 ) “ Most Influenza A Virions Fail To Express at Least One Essential Viral Protein ” , Journal of Virology Feb 2013 , 87 ( 6 ) 3155-3162 ; DOI : 10.1128/JVI.02284-12 https : //jvi.asm.org/content/87/6/3155 Coburn , B. J. et al .
( 2009 ) “ Modeling influenza epidemics and pandemics : insights into the future of swine flu ( H1N1 ) ” , BMC @ @ @ @ @ @ @ Davies , A. et al .
( 2013 ) “ Testing the Efficacy of Homemade Masks : Would They Protect in an Influenza Pandemic ?
” , Disaster Medicine and Public Health Preparedness , Available on CJO 2013 doi:10.1017/dmp.2013.43 http : //journals.cambridge.org/abstract_S1935789313000438 Despres , V. R. et al .
( 2012 ) “ Primary biological aerosol particles in the atmosphere : a review ” , Tellus B : Chemical and Physical Meteorology , 64:1 , 15598 , DOI : 10.3402/tellusb.v64i0.15598 https : //doi.org/10.3402/tellusb.v64i0.15598 Dowell , S. F. ( 2001 ) “ Seasonal variation @ @ @ @ @ @ @ infectious diseases ” , Emerg Infect Dis .
2001 ; 7 ( 3 ) :369–374 .
doi:10.3201/eid0703.010301 https : //www.ncbi.nlm.nih.gov/pmc/articles/PMC2631809/ Hammond , G. W. et al .
( 1989 ) “ Impact of Atmospheric Dispersion and Transport of Viral Aerosols on the Epidemiology of Influenza ” , Reviews of Infectious Diseases , Volume 11 , Issue 3 , May 1989 , Pages 494–497 , https : //doi.org/10.1093/clinids/11.3.494 Haas , C.N .
et al .
( 1993 ) “ Risk Assessment of Virus in Drinking Water ” , Risk Analysis , 13 : 545-552.
@ @ @ @ @ @ @ 2020 ) “ Charter 1a – Epidemiology : Epidemic theory ( effective & basic reproduction numbers , epidemic thresholds ) & techniques for analysis of infectious disease data ( construction & use of epidemic curves , generation numbers , exceptional reporting & identification of significant clusters ) ” , HealthKnowledge.org.uk , accessed on 2020-04-10. https : //www.healthknowledge.org.uk/public-health-textbook/research-methods/1aepidemiology/epidemic-theory Lai , A. C. K. et al .
( 2012 ) “ Effectiveness of facemasks to reduce exposure hazards for airborne infections among general populations ” , J. R. Soc .
Interface .
9938–948 http : @ @ @ @ @ @ @ .
( 2020 ) “ Respiratory virus shedding in exhaled breath and efficacy of face masks ” , Nature Medicine ( 2020 ) .
https : //doi.org/10.1038/s41591-020-0843-2 Lowen , A. C. et al .
( 2007 ) “ Influenza Virus Transmission Is Dependent on Relative Humidity and Temperature ” , PLoS Pathog 3 ( 10 ) : e151 .
https : //doi.org/10.1371/journal.ppat.0030151 Paules , C. and Subbarao , S. ( 2017 ) “ Influenza ” , Lancet , Seminar| Volume 390 , ISSUE 10095 , P697-708 , August 12 , 2017. http : @ @ @ @ @ @ @ van der , M. et al .
( 2008 ) “ Professional and Home-Made Face Masks Reduce Exposure to Respiratory Infections among the General Population ” , PLoS ONE 3 ( 7 ) : e2618 .
doi:10.1371/journal.pone.0002618 https : //doi.org/10.1371/journal.pone.0002618 Shaman , J. et al .
( 2010 ) “ Absolute Humidity and the Seasonal Onset of Influenza in the Continental United States ” , PLoS Biol 8 ( 2 ) : e1000316 .
https : //doi.org/10.1371/journal.pbio.1000316 Tracht , S. M. et al .
( 2010 ) “ Mathematical Modeling of the Effectiveness @ @ @ @ @ @ @ Novel Influenza A ( H1N1 ) ” , PLoS ONE 5 ( 2 ) : e9018 .
doi:10.1371/journal.pone.0009018 https : //doi.org/10.1371/journal.pone.0009018 Viboud C. et al .
( 2010 ) “ Preliminary Estimates of Mortality and Years of Life Lost Associated with the 2009 A/H1N1 Pandemic in the US and Comparison with Past Influenza Seasons ” , PLoS Curr .
2010 ; 2 : RRN1153 .
Published 2010 Mar 20. doi:10.1371/currents.rrn1153 https : //www.ncbi.nlm.nih.gov/pmc/articles/PMC2843747/ Wada , K. et al .
( 2012 ) “ Wearing face masks in public during the influenza season may @ @ @ @ @ @ @ ” , BMC Public Health 12 , 1065 ( 2012 ) .
https : //doi.org/10.1186/1471-2458-12-1065 Yang , W. et al .
( 2011 ) “ Concentrations and size distributions of airborne influenza A viruses measured indoors at a health centre , a day-care centre and on aeroplanes ” , Journal of the Royal Society , Interface .
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Why Masks Don’t Work Against COVID-19
Written by Denis G. Rancourt, PhD
Masks and respirators do not work. There have been extensive randomized controlled trial (RCT) studies, and meta-analysis reviews of RCT studies, which all show that masks and respirators do not work to prevent respiratory influenza-like illnesses, or respiratory illnesses believed to be transmitted by droplets and aerosol particles.
Furthermore, the relevant known physics and biology, which I review, are such that masks and respirators should not work. It would be a paradox if masks and respirators worked, given what we know about viral respiratory diseases: The main transmission path is long-residence-time aerosol particles (< 2.5 μm), which are too fine to be blocked, and the minimum-infective-dose is smaller than one aerosol particle.
The present paper about masks illustrates the degree to which governments, the mainstream media, and institutional propagandists can decide to operate in a science vacuum, or select only incomplete science that serves their interests. Such recklessness is also certainly the case with the current global lockdown of over 1 billion people, an unprecedented experiment in medical and political history.
Review of the Medical Literature
Here are key anchor points to the extensive scientific literature that establishes that wearing masks and respirators (e.g., “N95”) does not reduce the risk of contracting a verified illness:
Jacobs, J. L. et al. (2009) “Use of surgical face masks to reduce the incidence of the common cold among health care workers in Japan: A randomized controlled trial”,nAmerican Journal of Infection Control, Volume 37, Issue 5, 417 – 419. https://www.ncbi.nlm.nih.gov/pubmed/19216002
N95-masked health-care workers (HCW) were significantly more likely to experience headaches. Face mask use in HCW was not demonstrated to provide benefit in terms of cold symptoms or getting colds. Cowling, B. et al. (2010) “Face masks to prevent transmission of influenza virus: A systematic review”, Epidemiology and Infection, 138(4), 449-456. doi:10.1017/S0950268809991658
https://www.cambridge.org/core/journals/epidemiology-and-infection/article/facemasks-to-prevent-transmission-of-influenza-virus-a systematicreview/64D368496EBDE0AFCC6639CCC9D8BC05
None of the studies reviewed showed a benefit from wearing a mask, in either HCW or community members in households (H). See summary Tables 1 and 2 therein. bin-Reza et al. (2012) “The use of masks and respirators to prevent transmission of influenza: a systematic review of the scientific evidence”, Influenza and Other Respiratory Viruses 6(4), 257–267. https://onlinelibrary.wiley.com/doi/epdf/10.1111/j.1750-2659.2011.00307.x
“There were 17 eligible studies. … None of the studies established a conclusive relationship between mask ⁄ respirator use and protection against influenza infection.”
Smith, J.D. et al. (2016)
https://www.cmaj.ca/content/188/8/567 “Effectiveness of N95 respirators versus surgical masks in protecting health care workers from acute respiratory infection: a systematic review and meta-analysis”, CMAJ Mar 2016, cmaj.150835; DOI: 10.1503/cmaj.150835 “We identified 6 clinical studies … In the meta-analysis of the clinical studies, we found no significant difference between N95 respirators and surgical masks in associated risk of (a) laboratory-confirmed respiratory infection, (b)
influenza-like illness, or (c) reported work-place absenteeism.”
https://doi.org/10.1093/cid/cix681 Offeddu, V. et al. (2017) “Effectiveness of Masks and Respirators Against Respiratory Infections in Healthcare Workers: A Systematic Review and Meta-Analysis”, Clinical Infectious Diseases, Volume 65, Issue 11, 1 December 2017, Pages 1934–1942,https://doi.org/10.1093/cid/cix681 https://academic.oup.com/cid/article/65/11/1934/4068747 “Self-reported assessment of clinical outcomes was prone to bias. Evidence of a protective effect of masks or respirators against verified respiratory infection (VRI) was not statistically significant”; as per Fig. 2c therein: Radonovich, L.J. et al. (2019) “N95 Respirators vs Medical Masks for Preventing Influenza Among Health Care Personnel: A Randomized Clinical Trial”, JAMA. 2019; 322(9): 824–833. doi:10.1001/jama.2019.11645 https://jamanetwork.com/journals/jama/fullarticle/2749214 “Among 2862 randomized participants, 2371 completed the study and accounted for 5180 HCW-seasons. … Among outpatient health care personnel, N95 respirators vs medical masks as worn by participants in this trial resulted in no significant difference in the incidence of laboratory-confirmed influenza.” Long, Y. et al. (2020) “Effectiveness of N95 respirators versus surgical masks against influenza: A systematic review and meta-analysis”, J Evid Based Med. 2020; 1- 9. https://doi.org/10.1111/jebm.12381 https://onlinelibrary.wiley.com/doi/epdf/10.1111/jebm.12381 “A total of six RCTs involving 9 171 participants were included. There were no statistically significant differences in preventing laboratory-confirmed influenza, laboratory-confirmed respiratory viral infections, laboratory-confirmed respiratory infection and influenza-like illness using N95 respirators and surgical masks. Meta-analysis indicated a protective effect of N95 respirators against laboratory-confirmed bacterial colonization (RR = 0.58, 95% CI 0.43-0.78). The use of N95 respirators compared with surgical masks is not associated with a lower risk of laboratory-confirmed influenza.”
Conclusion Regarding that Masks Do Not Work
No RCT study with verified outcome shows a benefit for HCW or community members in households to wearing a mask or respirator. There is no such study. There are no exceptions. Likewise, no study exists that shows a benefit from a broad policy to wear masks in public
(more on this below).
Furthermore, if there were any benefit to wearing a mask, because of the blocking power against droplets and aerosol particles, then there should be more benefit from wearing a respirator (N95) compared to a surgical mask, yet several large meta-analyses, and all the RCT, prove that there is no such relative benefit. Masks and respirators do not work.
Precautionary Principle Turned on Its Head with Masks
In light of the medical research, therefore, it is difficult to understand why public-health authorities are not consistently adamant about this established scientific result, since the distributed psychological, economic and environmental harm from a broad recommendation to wear masks is significant, not to mention the unknown potential harm from concentration and distribution of pathogens on and from used masks. In this case, public authorities would be turning the precautionary principle on its head (see below).
Physics and Biology of Viral Respiratory Disease and of Why Masks Do Not Work
In order to understand why masks cannot possibly work, we must review established knowledge about viral respiratory diseases, the mechanism of seasonal variation of excess deaths from pneumonia and influenza, the aerosol mechanism of infectious disease transmission, the physics and chemistry of aerosols, and the mechanism of the so-called minimum-infective-dose.
In addition to pandemics that can occur anytime, in the temperate latitudes there is an extra burden of respiratory-disease mortality that is seasonal, and that is caused by viruses. For example, see the review of influenza by Paules and Subbarao (2017). This has been known for a long time, and the seasonal pattern is exceedingly regular.
For example, see Figure 1 of Viboud (2010), which has
“Weekly time series of the ratio of deaths from pneumonia and influenza to all deaths, based on the 122 cities surveillance in the US (blue line). The red line represents the expected baseline ratio in the absence of influenza activity,” here:
The seasonality of the phenomenon was largely not understood until a decade ago. Until recently, it was debated whether the pattern arose primarily because of seasonal change in virulence of the pathogens, or because of seasonal change in susceptibility of the host (such as from dry air causing tissue irritation, or diminished daylight causing vitamin deficiency or hormonal stress). For example, see Dowell (2001).
In a landmark study, Shaman et al. (2010) showed that the seasonal pattern of extra respiratory-disease mortality can be explained quantitatively on the sole basis of absolute humidity, and its direct controlling impact on transmission of airborne pathogens.
Lowen et al. (2007) demonstrated the phenomenon of humidity-dependent airborne-virus virulence in actual disease transmission between guinea pigs, and discussed potential mechanisms for the measured controlling effect of humidity.
The underlying mechanism is that the pathogen-laden aerosol particles or droplets are neutralized within a half-life that monotonically and significantly decreases with increasing ambient humidity. This is based on the seminal work of Harper (1961). Harper experimentally showed that viral-pathogen-carrying droplets were inactivated within shorter and shorter times, as ambient humidity was increased.
Harper argued that the viruses themselves were made inoperative by the humidity (“viable decay”), however, he admitted that the effect could be from humidity-enhanced physical removal or sedimentation of the droplets (“physical loss”):
“Aerosol viabilities reported in this paper are based on the ratio of virus titre to radioactive count in suspension and cloud samples, and can be criticized on the ground that test and tracer materials were not physically identical.”
The latter (“physical loss”) seems more plausible to me, since humidity would have a universal physical effect of causing particle / droplet growth and sedimentation, and all tested viral pathogens have essentially the same humidity-driven “decay”.
Furthermore, it is difficult to understand how a virion (of all virus types) in a droplet would be molecularly or structurally attacked or damaged by an increase in ambient humidity. A “virion” is the complete, infective form of a virus outside a host cell, with a core of RNA or DNA and a capsid.
The actual mechanism of such humidity-driven intra-droplet “viable decay” of a virion has not been explained or studied. In any case, the explanation and model of Shaman et al. (2010) is not dependent on the particular mechanism of the humidity-driven decay of virions in aerosol / droplets. Shaman’s quantitatively demonstrated model of seasonal regional viral epidemiology is valid for either mechanism (or combination of mechanisms), whether “viable decay” or “physical loss”.
The breakthrough achieved by Shaman et al. is not merely some academic point. Rather, it has profound health-policy implications, which have been entirely ignored or overlooked in the current coronavirus pandemic.
In particular, Shaman’s work necessarily implies that, rather than being a fixed number (dependent solely on the spatial-temporal structure of social interactions in a completely susceptible population, and on the viral strain), the epidemic’s basic reproduction number (R0) is highly or predominantly dependent on ambient absolute humidity.
For a definition of R0, see HealthKnowlege-UK (2020): R0 is
“the average number of secondary infections produced by a typical case of an infection in a population where everyone is susceptible.”
The average R0 for influenza is said to be 1.28 (1.19–1.37); see the comprehensive review by Biggerstaff et al. (2014).
In fact, Shaman et al. showed that R0 must be understood to seasonally vary between humid summer values of just larger than “1” and dry-winter values typically as large as “4” (for example, see their Table 2). In other words, the seasonal infectious viral respiratory diseases that plague temperate latitudes every year go from being intrinsically mildly contagious to virulently contagious, due simply to the bio-physical mode of transmission controlled by atmospheric humidity, irrespective of any other consideration.
Therefore, all the epidemiological mathematical modelling of the benefits of mediating policies (such as social distancing), which assumes humidity-independent R0 values, has a large likelihood of being of little value, on this basis alone. For studies about modelling and regarding mediation effects on the effective reproduction number, see Coburn (2009) and Tracht (2010).
To put it simply, the “second wave” of an epidemic is not a consequence of human sin regarding mask wearing and hand shaking. Rather, the “second wave” is an inescapable consequence of an air-dryness-driven many-fold increase in disease contagiousness, in a
population that has not yet attained immunity.
If my view of the mechanism is correct (i.e., “physical loss”), then Shaman’s work further necessarily implies that the dryness-driven high transmissibility (large R0) arises from small aerosol particles fluidly suspended in the air; as opposed to large droplets that are quickly
gravitationally removed from the air.
Such small aerosol particles fluidly suspended in air, of biological origin, are of every variety and are everywhere, including down to virion-sizes (Despres, 2012). It is not entirely unlikely that viruses can thereby be physically transported over inter-continental distances (e.g., Hammond, 1989).
More to the point, indoor airborne virus concentrations have been shown to exist (in day-care facilities, health centres, and onboard airplanes) primarily as aerosol particles of diameters smaller than 2.5 μm, such as in the work of Yang et al. (2011):
“Half of the 16 samples were positive, and their total virus concentrations ranged from 5800 to 37 000 genome copies m−3. On average, 64 per cent of the viral genome copies were associated with fine particles smaller than 2.5 µm, which can remain suspended for hours. Modelling of virus concentrations indoors suggested a source strength of 1.6 ± 1.2 × 105 genome copies m−3 air h−1 and a deposition flux onto surfaces of 13 ± 7 genome copies m−2 h−1 by Brownian motion. Over 1 hour, the inhalation dose was estimated to be 30 ± 18 median tissue culture infectious dose (TCID50), adequate to induce infection. These results provide quantitative support for the idea that the aerosol route could be an important mode of influenza transmission.”
Such small particles (< 2.5 μm) are part of air fluidity, are not subject to gravitational sedimentation, and would not be stopped by long-range inertial impact. This means that the slightest (even momentary) facial misfit of a mask or respirator renders the design filtration
norm of the mask or respirator entirely irrelevant. In any case, the filtration material itself of N95 (average pore size ~0.3−0.5 μm) does not block virion penetration, not to mention surgical masks.
For example, see Balazy et al. (2006). Mask stoppage efficiency and host inhalation are only half of the equation, however, because the minimal infective dose (MID) must also be considered. For example, if a large number of pathogen-laden particles must be delivered to the lung within a certain time for the illness to take hold, then partial blocking by any mask or cloth can be enough to make a significant difference.
On the other hand, if the MID is amply surpassed by the virions carried in a single aerosol particle able to evade mask-capture, then the mask is of no practical utility, which is the case. Yezli and Otter (2011), in their review of the MID, point out relevant features:
• most respiratory viruses are as infective in humans as in tissue culture having optimal laboratory susceptibility
• it is believed that a single virion can be enough to induce illness in the host
• the 50%-probability MID (“TCID50”) has variably been found to be in the range 100−1000
virions
• there are typically 103−107 virions per aerolized influenza droplet with diameter 1 μm −10 μm
• the 50%-probability MID easily fits into a single (one) aerolized droplet
For further background:
• A classic description of dose-response assessment is provided by Haas (1993).
• Zwart et al. (2009) provided the first laboratory proof, in a virus-insect system, that the
action of a single virion can be sufficient to cause disease.
• Baccam et al. (2006) calculated from empirical data that, with influenza A in humans,
“we estimate that after a delay of ~6 h, infected cells begin producing influenza virus
and continue to do so for ~5 h. The average lifetime of infected cells is ~11 h, and the
half-life of free infectious virus is ~3 h. We calculated the [in-body] basic reproductive
number, R0, which indicated that a single infected cell could produce ~22 new
productive infections.”
• Brooke et al. (2013) showed that, contrary to prior modeling assumptions, although not
all influenza-A-infected cells in the human body produce infectious progeny (virions),
nonetheless, 90% of infected cell are significantly impacted, rather than simply surviving
unharmed.
All of this to say that: if anything gets through (and it always does, irrespective of the mask), then you are going to be infected. Masks cannot possibly work. It is not surprising, therefore, that no bias-free study has ever found a benefit from wearing a mask or respirator in this application.
Therefore, the studies that show partial stopping power of masks, or that show that masks can capture many large droplets produced by a sneezing or coughing mask-wearer, in light of the above-described features of the problem, are irrelevant. For example, such studies as these:
Leung (2020), Davies (2013), Lai (2012), and Sande (2008).
Why There Can Never Be an Empirical Test of a Nation-Wide Mask-Wearing Policy
As mentioned above, no study exists that shows a benefit from a broad policy to wear masks in public. There is good reason for this. It would be impossible to obtain unambiguous and biasfree results:
• Any benefit from mask-wearing would have to be a small effect, since undetected in controlled experiments, which would be swamped by the larger effects, notably the large effect from changing atmospheric humidity.
• Mask compliance and mask adjustment habits would be unknown.
• Mask-wearing is associated (correlated) with several other health behaviours; see Wada (2012).
• The results would not be transferable, because of differing cultural habits.
• Compliance is achieved by fear, and individuals can habituate to fear-based propaganda, and can have disparate basic responses.
• Monitoring and compliance measurement are near-impossible, and subject to large errors.
• Self-reporting (such as in surveys) is notoriously biased, because individuals have the self-interested belief that their efforts are useful.
• Progression of the epidemic is not verified with reliable tests on large population samples, and generally relies on non-representative hospital visits or admissions.
• Several different pathogens (viruses and strains of viruses) causing respiratory illness generally act together, in the same population and/or in individuals, and are not resolved, while having different epidemiological characteristics.
Unknown Aspects of Mask Wearing
Many potential harms may arise from broad public policies to wear masks, and the following unanswered questions arise:
• Do used and loaded masks become sources of enhanced transmission, for the wearer and others?
• Do masks become collectors and retainers of pathogens that the mask wearer would
otherwise avoid when breathing without a mask?
• Are large droplets captured by a mask atomized or aerolized into breathable components? Can virions escape an evaporating droplet stuck to a mask fiber?
• What are the dangers of bacterial growth on a used and loaded mask?
• How do pathogen-laden droplets interact with environmental dust and aerosols captured on the mask?
• What are long-term health effects on HCW, such as headaches, arising from impeded breathing?
• Are there negative social consequences to a masked society?
• Are there negative psychological consequences to wearing a mask, as a fear-based behavioural modification?
• What are the environmental consequences of mask manufacturing and disposal?
• Do the masks shed fibres or substances that are harmful when inhaled?
Conclusion
By making mask-wearing recommendations and policies for the general public, or by expressly condoning the practice, governments have both ignored the scientific evidence and done the opposite of following the precautionary principle.
In an absence of knowledge, governments should not make policies that have a hypothetical potential to cause harm. The government has an onus barrier before it instigates a broad socialengineering intervention, or allows corporations to exploit fear-based sentiments.
Furthermore, individuals should know that there is no known benefit arising from wearing a mask in a viral respiratory illness epidemic, and that scientific studies have shown that any benefit must be residually small, compared to other and determinative factors. Otherwise, what is the point of publicly funded science?
The present paper about masks illustrates the degree to which governments, the mainstream media, and institutional propagandists can decide to operate in a science vacuum, or select only incomplete science that serves their interests. Such recklessness is also certainly the case with the current global lockdown of over 1 billion people, an unprecedented experiment in medical and political history.
Endnotes:
Baccam, P. et al. (2006) “Kinetics of Influenza A Virus Infection in Humans”, Journal of Virology
Jul 2006, 80 (15) 7590-7599; DOI: 10.1128/JVI.01623-05
https://jvi.asm.org/content/80/15/7590
Balazy et al. (2006) “Do N95 respirators provide 95% protection level against airborne viruses,
and how adequate are surgical masks?”, American Journal of Infection Control, Volume 34,
Issue 2, March 2006, Pages 51-57. doi:10.1016/j.ajic.2005.08.018
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.488.4644&rep=rep1&type=pdf
Biggerstaff, M. et al. (2014) “Estimates of the reproduction number for seasonal, pandemic, and
zoonotic influenza: a systematic review of the literature”, BMC Infect Dis 14, 480 (2014).
https://doi.org/10.1186/1471-2334-14-480
Brooke, C. B. et al. (2013) “Most Influenza A Virions Fail To Express at Least One Essential Viral
Protein”, Journal of Virology Feb 2013, 87 (6) 3155-3162; DOI: 10.1128/JVI.02284-12
https://jvi.asm.org/content/87/6/3155
Coburn, B. J. et al. (2009) “Modeling influenza epidemics and pandemics: insights into the
future of swine flu (H1N1)”, BMC Med 7, 30. https://doi.org/10.1186/1741-7015-7-30
Davies, A. et al. (2013) “Testing the Efficacy of Homemade Masks: Would They Protect in an
Influenza Pandemic?”, Disaster Medicine and Public Health Preparedness, Available on CJO
2013 doi:10.1017/dmp.2013.43
http://journals.cambridge.org/abstract_S1935789313000438
Despres, V. R. et al. (2012) “Primary biological aerosol particles in the atmosphere: a review”,
Tellus B: Chemical and Physical Meteorology, 64:1, 15598, DOI: 10.3402/tellusb.v64i0.15598
https://doi.org/10.3402/tellusb.v64i0.15598
Dowell, S. F. (2001) “Seasonal variation in host susceptibility and cycles of certain infectious
diseases”, Emerg Infect Dis. 2001;7(3):369–374. doi:10.3201/eid0703.010301
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2631809/
Hammond, G. W. et al. (1989) “Impact of Atmospheric Dispersion and Transport of Viral
Aerosols on the Epidemiology of Influenza”, Reviews of Infectious Diseases, Volume 11, Issue 3,
May 1989, Pages 494–497, https://doi.org/10.1093/clinids/11.3.494
Haas, C.N. et al. (1993) “Risk Assessment of Virus in Drinking Water”, Risk Analysis, 13: 545-552.
doi:10.1111/j.1539-6924.1993.tb00013.x
https://doi.org/10.1111/j.1539-6924.1993.tb00013.x
12
HealthKnowlege-UK (2020) “Charter 1a – Epidemiology: Epidemic theory (effective & basic
reproduction numbers, epidemic thresholds) & techniques for analysis of infectious disease
data (construction & use of epidemic curves, generation numbers, exceptional reporting &
identification of significant clusters)”, HealthKnowledge.org.uk, accessed on 2020-04-10.
https://www.healthknowledge.org.uk/public-health-textbook/research-methods/1aepidemiology/epidemic-theory
Lai, A. C. K. et al. (2012) “Effectiveness of facemasks to reduce exposure hazards for airborne
infections among general populations”, J. R. Soc. Interface. 9938–948
http://doi.org/10.1098/rsif.2011.0537
Leung, N.H.L. et al. (2020) “Respiratory virus shedding in exhaled breath and efficacy of face
masks”, Nature Medicine (2020). https://doi.org/10.1038/s41591-020-0843-2
Lowen, A. C. et al. (2007) “Influenza Virus Transmission Is Dependent on Relative Humidity and
Temperature”, PLoS Pathog 3(10): e151. https://doi.org/10.1371/journal.ppat.0030151
Paules, C. and Subbarao, S. (2017) “Influenza”, Lancet, Seminar| Volume 390, ISSUE 10095,
P697-708, August 12, 2017.
http://dx.doi.org/10.1016/S0140-6736(17)30129-0
Sande, van der, M. et al. (2008) “Professional and Home-Made Face Masks Reduce Exposure to
Respiratory Infections among the General Population”, PLoS ONE 3(7): e2618.
doi:10.1371/journal.pone.0002618
https://doi.org/10.1371/journal.pone.0002618
Shaman, J. et al. (2010) “Absolute Humidity and the Seasonal Onset of Influenza in the
Continental United States”, PLoS Biol 8(2): e1000316.
https://doi.org/10.1371/journal.pbio.1000316
Tracht, S. M. et al. (2010) “Mathematical Modeling of the Effectiveness of Facemasks in
Reducing the Spread of Novel Influenza A (H1N1)”, PLoS ONE 5(2): e9018.
doi:10.1371/journal.pone.0009018
https://doi.org/10.1371/journal.pone.0009018
Viboud C. et al. (2010) “Preliminary Estimates of Mortality and Years of Life Lost Associated
with the 2009 A/H1N1 Pandemic in the US and Comparison with Past Influenza Seasons”, PLoS
Curr. 2010; 2:RRN1153. Published 2010 Mar 20. doi:10.1371/currents.rrn1153
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2843747/
Wada, K. et al. (2012) “Wearing face masks in public during the influenza season may reflect
other positive hygiene practices in Japan”, BMC Public Health 12, 1065 (2012).
https://doi.org/10.1186/1471-2458-12-1065
Yang, W. et al. (2011) “Concentrations and size distributions of airborne influenza A viruses
measured indoors at a health centre, a day-care centre and on aeroplanes”, Journal of the Royal
Society, Interface. 2011 Aug;8(61):1176-1184. DOI: 10.1098/rsif.2010.0686.
https://royalsocietypublishing.org/doi/10.1098/rsif.2010.0686
Yezli, S., Otter, J.A. (2011) “Minimum Infective Dose of the Major Human Respiratory and
Enteric Viruses Transmitted Through Food and the Environment”, Food Environ Virol 3, 1–30.
https://doi.org/10.1007/s12560-011-9056-7
Zwart, M. P. et al. (2009) “An experimental test of the independent action hypothesis in virus–
insect pathosystems”, Proc. R. Soc. B. 2762233–2242
http://doi.org/10.1098/rspb.2009.0064
Download the full PDF at www.researchgate.net
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principiascientificinternational--2020-05-25--Nobel Laureate: UK Lockdown Killed More Than It Saved

Nobel Laureate : UK Lockdown Killed More Than It Saved Professor Michael Levitt of Stanford University predicts that the UK will be rid of Covid-19 within weeks but the bad news is that he believes the lockdown could have caused more deaths than it saved .
Nobel laureate scientist , Michael Levitt said that the modelling that caused the government to bring in the lockdown – carried out by Professor Neil Ferguson – over-estimated the death toll by ’ 10 or 12 times ’ , and suggested that the decision was motivated by ’ panic ’ rather than the best @ @ @ @ @ @ @ national newspaper , The Telegraph , the Stanford University professor was scathing at how panic measures took over from sensible science .
The Telegraph reports : “ Michael Levitt , a Stanford University professor who correctly predicted the initial trajectory of the pandemic , sent messages to Professor Neil Ferguson in March telling the influential government advisor he had over-estimated the potential death toll by “ 10 or 12 times ” .
The Imperial College professor ’ s modelling , a major factor in the Government ’ s apparent abandoning of a so-called @ @ @ @ @ @ @ unnecessary “ panic virus ” which spread among global political leaders , Prof Levitt now tells the Telegraph.
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Help Our Non-Profit Mission To Defend The Scientific Method .

Nobel Laureate: UK Lockdown Killed More Than It Saved
Written by John O'Sullivan
Professor Michael Levitt of Stanford University predicts that the UK will be rid of Covid-19 within weeks but the bad news is that he believes the lockdown could have caused more deaths than it saved.
Nobel laureate scientist, Michael Levitt said that the modelling that caused the government to bring in the lockdown – carried out by Professor Neil Ferguson – over-estimated the death toll by ’10 or 12 times’, and suggested that the decision was motivated by ’panic’ rather than the best science.
Speaking to the British daily national newspaper, The Telegraph, the Stanford University professor was scathing at how panic measures took over from sensible science. The Telegraph reports:
“Michael Levitt, a Stanford University professor who correctly predicted the initial trajectory of the pandemic, sent messages to Professor Neil Ferguson in March telling the influential government advisor he had over-estimated the potential death toll by “10 or 12 times”. The Imperial College professor’s modelling, a major factor in the Government’s apparent abandoning of a so-called herd-immunity policy, was part of an unnecessary “panic virus” which spread among global political leaders, Prof Levitt now tells the Telegraph.”
More at www.telegraph.co.uk
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principiascientificinternational--2020-05-26--‘Man-made warming’ demolished in 500 words

The United Nations IPCC says ongoing warming is due to man ’ s CO2 emissions , hence ‘ Anthropogenic Global Warming ’ ( AGW ) .
The 3 pillars on which they base this claim are unscientific and quickly disproved .
• Earth ’ s average surface temperature and man ’ s CO2 emissions have both risen since 1850 , so CO2 must have caused the warming • What else has risen ?
The Sun ’ s magnetic output , affecting cloudiness ( Svensmark ) , more than doubled from 1901 to 1991 ( Lockwood ) , to its highest @ @ @ @ @ @ @ ) .
In those last 10,000 years … • simple visual cross-correlation shows changes in temperature lagged 60-160 years behind solar-output changes , due to the ocean ’ s vast heat capacity and slow mixing ( Higgs 1 , 2 ) & • … temperature and CO2 were uncorrelated , until their joint rise from the late 1800s .
• CO2 is still rising ( NOAA ) , but Earth has cooled since 2016 ( Met .
Office ) .
Every passing day not ‘ warmest ever ’ for that date , at @ @ @ @ @ @ @ .
• Warming since 1910 paused 1945-75 ( 30 years ) and 1998-2012 but CO2 kept rising .
• Global warming ’ s continuance despite the Sun ’ s weakening after 1991 absolves the Sun and incriminates CO2 This mismatch is simply due to the oceanic time-lag , currently about 60 years .
Thus global warming will continue ( with ups and downs , mainly due to the Sun ’ s 11-year cycles ) until around 2050 , about 60 years after the Sun ’ s 1991 grand peak ( Higgs 2 ) @ @ @ @ @ @ @ ’ s 2013 ‘ Fifth Assessment Report ’ , Chapter 10 ( IPCC 1 p.887 , co-author Lockwood [ see ( 1 ) above ] , citing 4 of his own papers ) .
But IPPC already knew about the lag , Chapter 3 having stated the “ ocean ’ s huge heat capacity and slow circulation lend it significant thermal inertia ” ( IPCC 2 p.266 ) .
Pillar III .
Sea level ( SL ) for the last few thousand years varied less than 25cm , so the 30cm SL rise @ @ @ @ @ @ @ The 25 cm claim ( only “ medium confidence ” ; IPCC 3 p.385 ) is based on selected evidence ( Higgs 3 ) and on dismissal of the famed 1961 SL curve ( Fairbridge ; Wiki ) with SL oscillations of 2 to 5 metres in the last 6,000 years , confirmed by dozens of later geologists worldwide , and lately with very strong archaeological support ( Higgs 4 , 5 , 6 ) .
• That ’ s it .
That ’ s all they have .
Be surprised .
• @ @ @ @ @ @ @ driver of global temperature for the last 10,000 years .
• CO2 is innocent ; it has no climate effect ; the simultaneous rise in temperature and CO2 is pure accident ; CO2 ’ s residual ‘ greenhouse effect ’ is effectively nil ( Higgs 7 , 8 ) .
• The IPCC urgently needs to consult geologists ( Higgs 9 , 10 ) .
PRINCIPIA SCIENTIFIC INTERNATIONAL , legally registered in the UK as a company incorporated for charitable purposes .
Head Office : 27 Old Gloucester Street , London WC1N 3AX @ @ @ @ @ @ @ The Scientific Method .

‘Man-made warming’ demolished in 500 words
Written by Dr Roger Higgs (DPhil Oxford, geology, 1982-86)
The United Nations IPCC says ongoing warming is due to man’s CO2 emissions, hence ‘Anthropogenic Global Warming’ (AGW). The 3 pillars on which they base this claim are unscientific and quickly disproved.
IPCC’s Three Pillars
PILLAR I: Earth’s average surface temperature and man’s CO2 emissions have both risen since 1850, so CO2 must have caused the warming
Five disproofs …
What else has risen? The Sun’s magnetic output, affecting cloudiness (Svensmark), more than doubled from 1901 to 1991 (Lockwood), to its highest peak in 10,000 years (Higgs 1).
In those last 10,000 years …
simple visual cross-correlation shows changes in temperature lagged 60-160 years behind solar-output changes, due to the ocean’s vast heat capacity and slow mixing (Higgs 1, 2) &
… temperature and CO2 were uncorrelated, until their joint rise from the late 1800s.
CO2 is still rising (NOAA), but Earth has cooled since 2016 (Met. Office). Every passing day not ‘warmest ever’ for that date, at multiple sites worldwide, embarrasses the IPCC.
Warming since 1910 paused 1945-75 (30 years) and 1998-2012 but CO2 kept rising
PILLAR II: Global warming’s continuance despite the Sun’s weakening after 1991 absolves the Sun and incriminates CO2
Disproof …
This mismatch is simply due to the oceanic time-lag, currently about 60 years. Thus global warming will continue (with ups and downs, mainly due to the Sun’s 11-year cycles) until around 2050, about 60 years after the Sun’s 1991 grand peak (Higgs 2).
Pillar II was asserted in IPCC’s 2013 ‘Fifth Assessment Report’, Chapter 10 (IPCC 1 p.887, co-author Lockwood [see (1) above], citing 4 of his own papers). But IPPC already knew about the lag, Chapter 3 having stated the “ocean’s huge heat capacity and slow circulation lend it significant thermal inertia” (IPCC 2 p.266).
PILLAR III: Sea level (SL) for the last few thousand years varied less than 25cm, so the 30cm SL rise since 1850 proves abnormal warming by CO2
Disproof …
The 25 cm claim (only “medium confidence”; IPCC 3 p.385) is based on selected evidence (Higgs 3) and on dismissal of the famed 1961 SL curve (Fairbridge; Wiki) with SL oscillations of 2 to 5 metres in the last 6,000 years, confirmed by dozens of later geologists worldwide, and lately with very strong archaeological support (Higgs 4, 5, 6).
Conclusions
That’s it. That’s all they have. Be surprised. The Sun was by far the main driver of global temperature for the last 10,000 years. CO2 is innocent; it has no climate effect; the simultaneous rise in temperature and CO2 is pure accident; CO2’s residual ‘greenhouse effect’ is effectively nil (Higgs 7, 8). The IPCC urgently needs to consult geologists (Higgs 9, 10). Another Sun-driven large sea-level rise is predictable (Higgs 11).
References
Fairbridge 1961 sea-level curve, latest revision 1977, fig. 2c here … https://www.nature.com/articles/268413a0
Higgs 1 2020 https://www.researchgate.net/publication/340869622
Higgs 2 2020 https://www.researchgate.net/publication/341078096 Higgs 3 2019 https://www.researchgate.net/publication/336414520 Higgs 4 2020 https://www.researchgate.net/publication/339875642 Higgs 5 2020 https://www.researchgate.net/publication/338556345 Higgs 6 2017 https://www.researchgate.net/publication/316601390 Higgs 7 2019 https://www.researchgate.net/publication/332245803 Higgs 8 2020 https://www.researchgate.net/publication/340869622 Higgs 9 2018 https://www.researchgate.net/publication/331928229
Higgs 10 2019 https://www.researchgate.net/publication/331974185 Higgs 11 2020 https://www.researchgate.net/publication/341597747 IPCC 1 2013
https://www.ipcc.ch/site/assets/uploads/2018/02/WG1AR5_Chapter10_FINAL.pdf IPCC 2 2013
https://www.ipcc.ch/site/assets/uploads/2018/02/WG1AR5_Chapter03_FINAL.pdf IPCC 3 2013 https://www.ipcc.ch/site/assets/uploads/2018/02/WG1AR5_Chapter05_FINAL.pdf Lockwood 1999 http://www.personal.reading.ac.uk/~ym901336/pdfs/170_Lockwoodetal_nature.pdf Meteorological Office UK 2020
https://www.metoffice.gov.uk/hadobs/monitoring/index.html
NOAA 2020 https://www.esrl.noaa.gov/gmd/ccgg/trends/index.html
Svensmark 2007 https://academic.oup.com/astrogeo/article/48/1/1.18/220765 Wiki 2020 https://en.wikipedia.org/wiki/Rhodes_Fairbridge
Question everything
Download the PDF at www.researchgate.net
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principiascientificinternational--2020-05-26--Appeal to U.S. President Urging Action on Hydroxychloroquine

WASHINGTON – After spending the last weekend talking to agency heads helping to break the logjam holding up the distribution of 30 million tablets of hydroxychloroquine ( HCQ ) donated by Novartis to the Strategic National Stockpile , Sen. Ron Johnson ( R-Wis. ) turned his attention this week to helping give patients the right to try this drug early in the course of their COVID-19 diagnosis .
Senator Johnson quickly determined that absent guidance from the FDA and the CDC encouraging its use , far too many doctors and hospitals were reluctant to assume the liability “ off label @ @ @ @ @ @ @ fact , he heard reports that some state medical licensing boards were actually threatening doctors with sanctions if they prescribed HCQ “ off label.
” In order to break this prescribing logjam , Senator Johnson has spearheaded a campaign to solicit support for a letter urging President Trump to take two specific actions : 1 .
Issue a presidential directive to remove the FDA Emergency Use Authorization restriction that states hydroxychloroquine ( HCQ ) and chloroquine ( CQ ) from the Strategic National Stockpile are only approved “ for certain hospitalized patients , @ @ @ @ @ @ @ include the option of early outpatient use of these medications .
2 .
Issue a presidential directive or executive order to a ) prohibit governors from arbitrarily restricting hydroxychloroquine ( HCQ ) to only hospitalized patients , and b ) prohibit state medical boards and state pharmacy boards from threats of disciplinary action ( now occurring in multiple states ) against doctors and pharmacists legally prescribing and dispensing HCQ and CQ off-label for early treatment or prophylaxis for COVID-19 in outpatients or at-risk or exposed persons .
That letter began circulating among practicing @ @ @ @ @ @ @ ET .
By noon ET , 776 practicing physicians had already agreed to sign the letter .
Having obtained that level of support in only 14 hours , Senator Johnson submitted the letter to the White House .
Until the president has taken this action , Senator Johnson is asking practicing physicians around the country to add their voice to this effort by reviewing and signing the letter showing their support for giving patients the right to try HCQ early in the treatment of COVID-19 when it is believed to be most effective @ @ @ @ @ @ @ .
CLICK HERE TO SIGN THE LETTER .
We , the undersigned practicing physicians , urgently ask that you take two steps to help us treat patients according to our best ability and medical judgment , using the clinical and basic science data we already have on the effectiveness of certain established medicines in this war against COVID-19 : 1 .
A Presidential Directive to remove the FDA Emergency Use Authorization restriction that states Hydroxychloroquine ( HCQ ) and Chloroquine ( CQ ) from the Strategic National Stockpile , are only approved “ @ @ @ @ @ @ @ to direct the FDA to include the option of early out-patient use of these medications .
2 .
A Presidential Directive or Executive Order to a ) prohibit Governors from arbitrarily restricting hydroxychloroquine ( HCQ ) to only hospitalized patients , and b ) prohibit State Medical Boards and State Pharmacy Boards from threats of disciplinary action ( now occurring in multiple states ) against doctors and pharmacists legally prescribing and dispensing HCQ and CQ off-label for early treatment or prophylaxis for COVID-19 in out-patients or at-risk or exposed persons .
Restricting use @ @ @ @ @ @ @ critical early window of opportunity to : ( 1 ) prevent the virus attaching to host cells , ( 2 ) reduce viral replication that prolongs time of infectivity and spread , ( 3 ) reduce the number of hospitalizations and need for intubation and mechanical ventilators , and ( 4 ) reduce risk of multi-organ damage and death or permanent lung impairment after recovery .
Evidence of successful treatment in thousands of patients is accumulating from many countries as well as U.S. physicians ; it is far beyond “ anecdotal.
” HCQ @ @ @ @ @ @ @ , and it is now also approved for treating lupus and rheumatoid arthritis , with an impressive safety record .
When World Health Organization and U.S. academic experts say there is “ no evidence that any medicine can prevent or cure ” COVID-19 , they correctly mean that we don ’ t yet have a randomized , placebo-controlled , doubleblind clinical trial ( RCT ) .
But designing , setting up , conducting , and analyzing any RCT takes many months or years .
We can ’ t wait months for a completed @ @ @ @ @ @ @ dying every day .
Staggering numbers of people have lost jobs , incomes , and ability to live life normally , all of which lead to loss of life that could quickly exceed losses from the virus .
Physicians taking care of patients in our communities across the country must be free to use the medicines at hand free of politicians and bureaucrats ’ second-guessing and threats .
It is unprecedented—and lethal—for state governors and medical boards to forbid physicians ’ freedom to prescribe long-approved and safely used medications .
In a war @ @ @ @ @ @ @ we must fight with all the weapons we have at hand .

Written by Sen. Ron Johnson
WASHINGTON – After spending the last weekend talking to agency heads helping to break the logjam holding up the distribution of 30 million tablets of hydroxychloroquine (HCQ) donated by Novartis to the Strategic National Stockpile, Sen. Ron Johnson (R-Wis.) turned his attention this week to helping give patients the right to try this drug early in the course of their COVID-19 diagnosis.
Senator Johnson quickly determined that absent guidance from the FDA and the CDC encouraging its use, far too many doctors and hospitals were reluctant to assume the liability “off label” use of HCQ posed. In fact, he heard reports that some state medical licensing boards were actually threatening doctors with sanctions if they prescribed HCQ “off label.”
In order to break this prescribing logjam, Senator Johnson has spearheaded a campaign to solicit support for a letter urging President Trump to take two specific actions:
1. Issue a presidential directive to remove the FDA Emergency Use Authorization restriction that states hydroxychloroquine (HCQ) and chloroquine (CQ) from the Strategic National Stockpile are only approved “for certain hospitalized patients,” and to direct the FDA to include the option of early outpatient use of these medications.
2. Issue a presidential directive or executive order to a) prohibit governors from arbitrarily restricting hydroxychloroquine (HCQ) to only hospitalized patients, and b) prohibit state medical boards and state pharmacy boards from threats of disciplinary action (now occurring in multiple states) against doctors and pharmacists legally prescribing and dispensing HCQ and CQ off-label for early treatment or prophylaxis for COVID-19 in outpatients or at-risk or exposed persons.
That letter began circulating among practicing physicians Thursday evening at 10 p.m. ET. By noon ET, 776 practicing physicians had already agreed to sign the letter. Having obtained that level of support in only 14 hours, Senator Johnson submitted the letter to the White House.
Until the president has taken this action, Senator Johnson is asking practicing physicians around the country to add their voice to this effort by reviewing and signing the letter showing their support for giving patients the right to try HCQ early in the treatment of COVID-19 when it is believed to be most effective.
Text of the letter is below. CLICK HERE TO SIGN THE LETTER.


principiascientificinternational--2020-05-26--Bridging the Gap in Greenhouse Gas Theory  – One Plate Test

Bridging the Gap in Greenhouse Gas Theory – One Plate Test Today , we present further refinement and details of an experiment that destroys climate alarm .
In an earlier article I showed that back radiant calculations behind man-made global warming theory are wrong .
For new readers , please check out that original post , ‘ Bridging The Gap !
Greenhouse Gas Theory Fail.
’ [ 1 ] A flat plate in space , at standard Earth Orbit distance , with no other objects around it will arrive at a temperature of 394K , as confirmed by NASA in @ @ @ @ @ @ @ to call this Hypothesis 1 .
This is with an input of 1367 watts on one side , that absorbing side , will warm until it reaches resonating equilibrium with the intensity of radiation that it is in receipt of .
That being 394k .
[ 2 ] Promoters of the discredited greenhouse gas theory who employ misleading back radiant maths would have us believe that the temperature of the same flat plate in space would arrive at is 331k , much lower than observed reality .
I am going to call this @ @ @ @ @ @ @ aka ‘ computer models ’ ) .
In our universe ( ‘ reality ’ ) , it does not work like that , hence why it is false .
So how to prove this without going into space ?
Herein is the data for anyone to check and to dissect .
This is real science .
Empirical evidence , demonstrated in a laboratory using standard scientific equipment properly calibrated and readily open to be replicated by others , is the way solid , traditional science is done .
Forget theoretical computer models which @ @ @ @ @ @ @ ( just look at how computer models by ‘ experts ’ grossly over-estimated the impact of the COVID-19 pandemic ! )
.
A test rig , which can apply a known quantity of heat and then simply observe the maximum temperature of a flat plate .
If the final temperature closely aligns with the temperature pre-determined using Hypothesis 1 method , then that is the correct model and not Hypothesis 2 , which predicts much cooler temperatures .
My test rig is my taller tower borosilicate glass chamber , and I have put @ @ @ @ @ @ @ I have then dangled with fishing wire , a 120mm diameter flat black plate and on the back of this plate in the centre I will place a 1000 C capable temperature probe which connects back to a data logger .
The space between the lamp and the plate will be as small as I can get it , a few mm , with no physical contact and the lamp is wrapped with Aluminium , to ensure as much as the light which goes downwards is reflected upwards to reduce losses and get @ @ @ @ @ @ @ to the plate as possible .
I took some close ups too , to show some more detail .
No Contact with bulb and plate .
This is held up from the side of the glass chamber , with putty , string and Velcro straps .
Hypothesis 1 , would predict a maximum temperate of the flat plate of 355 C° .
This is because the area of the 120mm diameter plate , considering only one side is 11,309.73mm2 and 100 watts evenly spread across this area is equivalent to 8,841.94 watts per @ @ @ @ @ @ @ , if we had an area of 1m2 we would be heating that area up with 88.41 100 watt bulbs .
This equates back to a temperature of 628.41k or 355 C° .
Similarly if we took the averaging back radiation approach , the area of emission of the plate in the calculation doubles 22,619.47mm2 , we would expect a steady state temperature of 528.43K or 255 C° Therefore all we need to do now , is set the rig up , evacuate all the air , switch on the bulb and then @ @ @ @ @ @ @ on until steady state temperatures of the flat plate are achieved and see what results this brings and simply compare this to the predictions expected from the two hypothesis .
I did several tests , test no 2 , the middle one below , I have uploaded onto You-tube , the results of the data log are as below .
https : //www.youtube.com/watch ?
v=NhHb6PGBwxQ & list=PLF66zq1SOYiuDC5M51y7iMOO2-DnImyfq The data log is above .
The maximum temperature achieved with my set up is 312.6 C° in test 1 , in test 2 it was @ @ @ @ @ @ @ 308.40 C° .
In test 3 a support bracket , which was supporting the data logger , dropped down onto the plate , you can see this above , it caused the temperature to drop from 295 to 291 and then it took a bit longer to reach maximum temperature than the other two tests This is far in excess of the 255 predicted by the false universe hypothesis 2 and not far off from Hypothesis 1 .
I can repeat this test , again & again & again and get similar results @ @ @ @ @ @ @ ’ t get to full predicted temperature of 355 is there is a problem of efficiency of heat transfer from the bulb to the plate .
The process is not 100 % efficient , no process ever is , as not all of the energy emitted by the bulb is going upwards .
A portion is being lost going downwards and a portion is lost being emitted outwardly to the sides also , these losses are visible .
I attempted to reduce these loses with the aluminium foil , wrapped around the bulb @ @ @ @ @ @ @ upwards as possible .
There is also some non-radiation conduction heat losses occurring due to the presence of the spacers between the glass and the plate .
Those are there to stop the plate from touching the glass , which it does using hanging wires .
There are conduction losses from the wires which are hanging the plate also , as well as the temperature probe itself .
After I switch it off , expose it to air again and touch the probe it is too hot to handle .
The wires are @ @ @ @ @ @ @ with putty , that putty contains water and when the glass warms it cause it to evaporate which is then having a cooling effect on the plate as the moisture circulates in the chamber .
With these losses the overall efficiency of heat transfer from the 100 watt bulb to the plate is approximately 76 % .
In Test 2 , the test ended prematurely as the logger fell of the side as can be seen in the you tube clip .
We know so well all the make believe nonsense detractors are @ @ @ @ @ @ @ , so let ’ s address those non-issues now : This is the kind of thought process that greenhouse gas theory believers will indulge in : “ Back radiance from the glass wasn ’ t eliminated , it exists , this is the cause of the higher temperature rise , all you did was prove back radiance.
” Firstly , If we assumed that back radiant hypothesis was real with a 76 % efficient heat transfer process and we performed the necessary fake back radiant mathematics , we arrive at a predicted temperature @ @ @ @ @ @ @ if the external glass along its entire length reached a temperature of 200 C° .
If we assumed 100 % efficiency , which is a complete nonsense we still only get 288 .
The time to end your delusions is now .
Your science is false .
As can be seen from the you tube videos the temperature of the glass at the point where the plate is , only reached a mere 77 C° .
This is not sufficient to emit the rate of energy required to explain the observed temperatures if @ @ @ @ @ @ @ it was .
Although it is hot enough to melt the glue on the Velcro straps which caused the bracket to fall off holding the data logger , on test 2 .
The strap and bracket also fell off on experiment 3 , but I had 2 brackets so the date logger still held in place and the experiment continued .
The bracket dropping , just caused a small dip in the temperature and meant it took a bit longer to reach the maximum .
Secondly , see the improvements to experiment section @ @ @ @ @ @ @ dumb detraction can be eliminated entirely .
The false legs the false universe climate crisis rests upon are being removed as we speak .
What is actually happening .
What is actually happening is that the temperature on the lamp side of the plate is being determined entirely by the intensity of the radiation incident upon it .
The atoms of the plate are then increasing their rate of vibration ( warming ) which is what is causing the temperature rise .
When the intensity of vibration of the molecules matches the intensity @ @ @ @ @ @ @ warming stops .
This is the steady state temperature .
Vibrational state of atoms go by another name This is the important word which needs to be remembered .
Not back radiance or radiant forcing .
The rate of heat transfer from the molecules at the front to the back of the plate , the thermal conductivity of the aluminium , here which is 237 w/m K , or for 1mm , 237,000 w/mm K , means that the temperature on the reverse side of the 1mm plate is virtually identical to the @ @ @ @ @ @ @ plate .
The fast vibrating atoms at the front of the plate bump the atoms beside them , transferring energy , that simple .
You don ’ t average the temperature of the plate , to find an emission of 100 watts each side .
What you do is determine the rate of temperature to match the rate of absorption of 100 watts and then calculate the temperature of the other side depending upon the thickness of the plate and the rate of thermal conductivity of the material under consideration .
( Assuming @ @ @ @ @ @ @ designing satellites this is the process rocket scientists will perform , calculating the thermal resistance of the material to determine the path of least resistance that heat flows are most likely to go .
False universe back radiant maths , is not the process utilised , because it fails , it will give you the wrong answer , just like in this test .
I can do this same test with a solid cube and measure the temperature of the solid cube on all its sides , or even a hollow cube , @ @ @ @ @ @ @ sphere .
Back radiance & pathetic averaging calculations can be ignored in their entirety , they are non- relevant as the effect is non-present and their results predicted entirely wrong .
What matters is the rate of absorption & the rate of thermal transfer of the material .
A material with high conductivity enables higher temperatures around the cube than one with a lower conductivity .
This is why if we had a 100 % efficient heat transfer system , the plate would reach 355 C° , on both its sides .
When @ @ @ @ @ @ @ be at that temperature .
An idiot faker , whom believes in back radiance would wrongly then say , it is emitting 100 watts from both sides , therefore it is emitting 200 watts , which is an idiotic fallacy to say the least .
It is not , it is radiating at the resonating rate of intensity which matches the resonating rate of intensity of the radiation which is incident upon it on the absorbing side from the 100 watt light bulb .
Nothing else is in play here .
The atoms @ @ @ @ @ @ @ absorption .
They do not radiate at a much lower rate so that 50 % of energy incoming radiates out each side of the atom .
That ’ s just silly and quite childish thinking .
How could an atom perform this feat ?
Yet this is the thinking behind believers in the false physics of the greenhouse gas theory .
This is the fallacy behind all climate carbon regulation and it is the fallacy which is being undone and all such legislation , taxes and such like also need to be undone @ @ @ @ @ @ @ experiment .
Below are a list of improvements which can be made to the experiment to improve it further .
With the assistance of PSI we are going to seek funding for further refinements and attain 100 % confidence that the nonsense about man made global warming , claimed by believers in the greenhouse gas theory , simply is not happening at all .
These are as follows : - • Replace hanging wires with wooden ones also .
• Have a larger vacuum chamber .
( Remove need for spacers altogether ) @ @ @ @ @ @ @ shapes also , cubes , spheres , mutli-plates etc .
• Replace support putty , with something which does not contain water , to reduce convective and evaporative cooling which was evident .
• Make the Vacuum chamber super cooled and black , so as to remove all radiation absorption incident upon it so as to remove all source of back radiance , thereby eliminating its non-effects in their entirety .
These are the very real improvements which can be made to show that anyone who persists in saying back radiant heating is @ @ @ @ @ @ @ claims .
What are they going to say , when the lid is IR transparent ?
There is no back radiance and yet the temperature I achieve is achieved ?
What are they going to say when the entire column is IR transparent ?
What are they going to say when the entire test is performed in a black absorbing super cooled container and there is NO BACK RADIANCE AT ALL , AS ALL OUTWARD RADIANCE IS ABSORBED AND TAKEN AWAY BY REFRIGERANT ?
Radiation Greenhouse effect , climate crisis , back radiant @ @ @ @ @ @ @ lie , no getting away from that any more .
One BIG LIE .
For more on their lies you can see my book .
https : //www.amazon.co.uk/Black-Dragon-Breaking-Frizzle-Frazzle/dp/1949267008 The results of these improved experiments will be made open to academia , industry and the general populace at large .
Done in accordance with the improvements mentioned , this test the supposed back radiant heating mechanism theory and fake radiation greenhouse theory .
CO2 thus can have no heating effect on the surface of the Earth whatsoever .
PRINCIPIA SCIENTIFIC INTERNATIONAL , legally registered @ @ @ @ @ @ @ for charitable purposes .
Head Office : 27 Old Gloucester Street , London WC1N 3AX .
Help Our Non-Profit Mission To Defend The Scientific Method .

Bridging the Gap in Greenhouse Gas Theory – One Plate Test
Written by Geraint Hughes
Today, we present further refinement and details of an experiment that destroys climate alarm. In an earlier article I showed that back radiant calculations behind man-made global warming theory are wrong. For new readers, please check out that original post, ‘Bridging The Gap! Greenhouse Gas Theory Fail.’ [1]
To recap the article:-
A flat plate in space, at standard Earth Orbit distance, with no other objects around it will arrive at a temperature of 394K, as confirmed by NASA in the link below. I am going to call this Hypothesis 1. This is with an input of 1367 watts on one side, that absorbing side, will warm until it reaches resonating equilibrium with the intensity of radiation that it is in receipt of. That being 394k. [2]
Promoters of the discredited greenhouse gas theory who employ misleading back radiant maths would have us believe that the temperature of the same flat plate in space would arrive at is 331k, much lower than observed reality. I am going to call this Hypothesis 2, the false universe (aka ‘computer models’). In our universe (‘reality’), it does not work like that, hence why it is false.
So how to prove this without going into space?
Test Rig
Herein is the data for anyone to check and to dissect. This is real science. Empirical evidence, demonstrated in a laboratory using standard scientific equipment properly calibrated and readily open to be replicated by others, is the way solid, traditional science is done.
Forget theoretical computer models which are unreliable and prone to gross error (just look at how computer models by ‘experts’ grossly over-estimated the impact of the COVID-19 pandemic!).
A test rig, which can apply a known quantity of heat and then simply observe the maximum temperature of a flat plate. If the final temperature closely aligns with the temperature pre-determined using Hypothesis 1 method, then that is the correct model and not Hypothesis 2, which predicts much cooler temperatures.
My test rig is my taller tower borosilicate glass chamber, and I have put in a 100 watt reflector lamp and I have then dangled with fishing wire, a 120mm diameter flat black plate and on the back of this plate in the centre I will place a 1000 C capable temperature probe which connects back to a data logger. The space between the lamp and the plate will be as small as I can get it, a few mm, with no physical contact and the lamp is wrapped with Aluminium, to ensure as much as the light which goes downwards is reflected upwards to reduce losses and get as much as the 100 watts going to the plate as possible.
I took some close ups too, to show some more detail.
No Contact with bulb and plate.
Close up of Data Logger
This is held up from the side of the glass chamber, with putty, string and Velcro straps.
Close up of Temperature Probe 1000 C° Capability
Predictions (Final Steady State Temperature)
Hypothesis 1, would predict a maximum temperate of the flat plate of 355 C°. This is because the area of the 120mm diameter plate, considering only one side is 11,309.73mm2 and 100 watts evenly spread across this area is equivalent to 8,841.94 watts per m2. Or in simple layman terms, if we had an area of 1m2 we would be heating that area up with 88.41 100 watt bulbs. This equates back to a temperature of 628.41k or 355 C°. Similarly if we took the averaging back radiation approach, the area of emission of the plate in the calculation doubles 22,619.47mm2, we would expect a steady state temperature of 528.43K or 255 C°
Actual Experiment
Therefore all we need to do now, is set the rig up, evacuate all the air, switch on the bulb and then perform a test and leave light bulb on until steady state temperatures of the flat plate are achieved and see what results this brings and simply compare this to the predictions expected from the two hypothesis.
Results
I did several tests, test no 2, the middle one below, I have uploaded onto You-tube, the results of the data log are as below. https://www.youtube.com/watch?v=NhHb6PGBwxQ&list=PLF66zq1SOYiuDC5M51y7iMOO2-DnImyfq
Test 1, 2 & 3.
The data log is above. The maximum temperature achieved with my set up is 312.6 C° in test 1, in test 2 it was 306.80 C° in test 3 it was 308.40 C°. In test 3 a support bracket, which was supporting the data logger, dropped down onto the plate, you can see this above, it caused the temperature to drop from 295 to 291 and then it took a bit longer to reach maximum temperature than the other two tests This is far in excess of the 255 predicted by the false universe hypothesis 2 and not far off from Hypothesis 1. I can repeat this test, again & again & again and get similar results each time.
The reason it didn’t get to full predicted temperature of 355 is there is a problem of efficiency of heat transfer from the bulb to the plate. The process is not 100{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} efficient, no process ever is, as not all of the energy emitted by the bulb is going upwards. A portion is being lost going downwards and a portion is lost being emitted outwardly to the sides also, these losses are visible. I attempted to reduce these loses with the aluminium foil, wrapped around the bulb so as to reflect as much light upwards as possible.
There is also some non-radiation conduction heat losses occurring due to the presence of the spacers between the glass and the plate. Those are there to stop the plate from touching the glass, which it does using hanging wires.
There are conduction losses from the wires which are hanging the plate also, as well as the temperature probe itself. After I switch it off, expose it to air again and touch the probe it is too hot to handle.
The wires are supported onto the side of the glass with putty, that putty contains water and when the glass warms it cause it to evaporate which is then having a cooling effect on the plate as the moisture circulates in the chamber.
With these losses the overall efficiency of heat transfer from the 100 watt bulb to the plate is approximately 76{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117}.
In Test 2, the test ended prematurely as the logger fell of the side as can be seen in the you tube clip.
After rectification, test 3 was conducted.
Defeating Determined Detractors
We know so well all the make believe nonsense detractors are going to put forward when seeing this, so let’s address those non-issues now:
Back Radiance from the Glass Chamber.
This is the kind of thought process that greenhouse gas theory believers will indulge in: “Back radiance from the glass wasn’t eliminated, it exists, this is the cause of the higher temperature rise, all you did was prove back radiance.”
Firstly, If we assumed that back radiant hypothesis was real with a 76{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} efficient heat transfer process and we performed the necessary fake back radiant mathematics, we arrive at a predicted temperature of 257 C° and that would be if the external glass along its entire length reached a temperature of 200 C°. If we assumed 100{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} efficiency, which is a complete nonsense we still only get 288. The time to end your delusions is now. Your science is false. As can be seen from the you tube videos the temperature of the glass at the point where the plate is, only reached a mere 77 C°. This is not sufficient to emit the rate of energy required to explain the observed temperatures if we assumed the false universe was how it was.
Although it is hot enough to melt the glue on the Velcro straps which caused the bracket to fall off holding the data logger, on test 2. The strap and bracket also fell off on experiment 3, but I had 2 brackets so the date logger still held in place and the experiment continued. The bracket dropping, just caused a small dip in the temperature and meant it took a bit longer to reach the maximum.
Secondly, see the improvements to experiment section as to why this fake climate crisis dumb detraction can be eliminated entirely. The false legs the false universe climate crisis rests upon are being removed as we speak.
What is actually happening.
What is actually happening is that the temperature on the lamp side of the plate is being determined entirely by the intensity of the radiation incident upon it. The atoms of the plate are then increasing their rate of vibration (warming) which is what is causing the temperature rise. When the intensity of vibration of the molecules matches the intensity of the radiation incident upon it, warming stops. This is the steady state temperature.
Vibrational state of atoms go by another name Resonance. This is the important word which needs to be remembered. Not back radiance or radiant forcing.
The rate of heat transfer from the molecules at the front to the back of the plate, the thermal conductivity of the aluminium, here which is 237 w/m K, or for 1mm, 237,000 w/mm K, means that the temperature on the reverse side of the 1mm plate is virtually identical to the temperature on the hot side of the plate. The fast vibrating atoms at the front of the plate bump the atoms beside them, transferring energy, that simple.
You don’t average the temperature of the plate, to find an emission of 100 watts each side. What you do is determine the rate of temperature to match the rate of absorption of 100 watts and then calculate the temperature of the other side depending upon the thickness of the plate and the rate of thermal conductivity of the material under consideration. (Assuming black body of course.)
When designing satellites this is the process rocket scientists will perform, calculating the thermal resistance of the material to determine the path of least resistance that heat flows are most likely to go. False universe back radiant maths, is not the process utilised, because it fails, it will give you the wrong answer, just like in this test.
I can do this same test with a solid cube and measure the temperature of the solid cube on all its sides, or even a hollow cube, or a solid sphere or a hollow sphere. Back radiance & pathetic averaging calculations can be ignored in their entirety, they are non- relevant as the effect is non-present and their results predicted entirely wrong.
What matters is the rate of absorption & the rate of thermal transfer of the material. A material with high conductivity enables higher temperatures around the cube than one with a lower conductivity.
This is why if we had a 100{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} efficient heat transfer system, the plate would reach 355 C°, on both its sides. When viewed with an IR camera it would be at that temperature. An idiot faker, whom believes in back radiance would wrongly then say, it is emitting 100 watts from both sides, therefore it is emitting 200 watts, which is an idiotic fallacy to say the least. It is not, it is radiating at the resonating rate of intensity which matches the resonating rate of intensity of the radiation which is incident upon it on the absorbing side from the 100 watt light bulb.
Nothing else is in play here. The atoms are vibrating to match the rate of absorption. They do not radiate at a much lower rate so that 50{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} of energy incoming radiates out each side of the atom. That’s just silly and quite childish thinking. How could an atom perform this feat?
Yet this is the thinking behind believers in the false physics of the greenhouse gas theory.
This is the fallacy behind all climate carbon regulation and it is the fallacy which is being undone and all such legislation, taxes and such like also need to be undone.
Improvements which can be made to experiment.
Below are a list of improvements which can be made to the experiment to improve it further.
With the assistance of PSI we are going to seek funding for further refinements and attain 100{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} confidence that the nonsense about man made global warming, claimed by believers in the greenhouse gas theory, simply is not happening at all.
These are as follows :-
Replace spacers with wood.
Replace hanging wires with wooden ones also.
Improve reflector around bulb.
Have a larger vacuum chamber. (Remove need for spacers altogether)
Improved vacuum pump.
Peform more detailed tests with other shapes also, cubes, spheres, mutli-plates etc.
Replace support putty, with something which does not contain water, to reduce convective and evaporative cooling which was evident.
Make the Vacuum chamber IR transparent.
Make the Vacuum Chamber lid IR Transparent.
Make the Vacuum chamber super cooled and black, so as to remove all radiation absorption incident upon it so as to remove all source of back radiance, thereby eliminating its non-effects in their entirety.
These are the very real improvements which can be made to show that anyone who persists in saying back radiant heating is real is making clearly unscientific, unproven claims.
What are they going to say, when the lid is IR transparent? There is no back radiance and yet the temperature I achieve is achieved? What are they going to say when the entire column is IR transparent?
What are they going to say when the entire test is performed in a black absorbing super cooled container and there is NO BACK RADIANCE AT ALL, AS ALL OUTWARD RADIANCE IS ABSORBED AND TAKEN AWAY BY REFRIGERANT?
Radiation Greenhouse effect, climate crisis, back radiant fake physics, it is all a lie, no getting away from that any more. One BIG LIE.
For more on their lies you can see my book. https://www.amazon.co.uk/Black-Dragon-Breaking-Frizzle-Frazzle/dp/1949267008
The results of these improved experiments will be made open to academia, industry and the general populace at large.
Done in accordance with the improvements mentioned, this test completely slays the supposed back radiant heating mechanism theory and fake radiation greenhouse theory. CO2 thus can have no heating effect on the surface of the Earth whatsoever.
[1] https://principia-scientific.com/bridging-the-gap-greenhouse-gas-theory-fail/
[2] https://www.grc.nasa.gov/www/k-12/Numbers/Math/Mathematical_Thinking/estimating_the_temperature.htm
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