Irrigation plays an essential role in the Earth system by changing water, energy, and carbon fluxes, and then affecting the climate. Many previous studies have been conducted to explore its impacts on near-surface climate, highlighting its cooling effects on air temperature, especially during hot extremes. However, most studies do the exploration during the historical period and only focus on temperature. Projected greenhouse gas emissions and land use datasets have made it possible to extend the investigation under future scenarios, but there are no datasets about predicted irrigation techniques shares information. To address this issue, we create a dataset containing spatial distribution of drip, sprinkler, and flood irrigation techniques, based on a simple assumption that richer and drier countries will invest more in irrigation system upgrades. Then, the Community Earth System Model version 2 (CESM2) is developed to be able to represent different irrigation techniques for one crop type in one gridcell. Finally, with the newly created dataset and modified CESM2, we detect irrigation's impacts on heat and moist-heat stress under SSP1-2.6 and SSP3-7.0. Simulation outputs indicate that irrigation will experience various changes among regions and scenarios. In irrigation hot spots, irrigation will continue to reduce the probability of high-temperature extremes under both scenarios but cannot reverse the warming signal caused by other forcings. Moreover, irrigation's impacts on apparent temperature are very small, and even increase the hours exposed to wet bulb temperature extremes in some regions. This study reveals that irrigation's cooling impacts will persist in the future, but will not be an effective solution to the global warming issue. As for moist-heat stress, irrigation's effects are much more complicated due to its enhancing impacts on air humidity.

The linear no-threshold assumption misunderstands the complex multiphasic biological response to ionizing radiation, focusing solely on the initial physical radiogenic damage. This misunderstanding is enabled (masked and amplified) by a number of mathematical approaches that bias results in favor of linear no-threshold and away from alternatives, like hormesis, that take biological response into account. Here we explore a number of these mathematical approaches in some detail, including the use of frequentist rather than Bayesian statistical rules and methods. We argue that a Bayesian approach cuts through an epidemiological stalemate, in part because it enables a better understanding of the concept of plausibility, which in turn properly rests on empirical evidence of actual physical and biological mechanisms. Misuse of the concept of plausibility has sometimes been used to justify the mathematically simple and convenient linearity-without-a-threshold assumption, in particular with the everywhere-positive slope that is central to linear no-threshold and its variants. Linear no-threshold’s dominance in the area of dose regulation further rests on a misapplication of the precautionary principle, which only holds when a putative caution has positive effects that outweigh the negative unintended consequences. In this case the negative consequences far outweigh the presumed hazards.

TO THE EDITOR: Duncan et al., in their latest entry ([1][1]) in the ongoing debate between us, which has been permitted by the editors to continue, focus on 2 points in our previous entry ([2][2]). This permits us to focus on the same 2 points. The first point is our assertion that “…the repair

TO THE EDITOR: Contrary to Siegel et al.'s commentary ([1][1]), we find little reason to believe that "dose optimization to minimize radiation risk for children … is misguided and detrimental." Although Siegel et al. acknowledge that ionizing radiation causes DNA double-strand breaks (DSBs)

The 2006 National Academy of Sciences Biologic Effects of Ionizing Radiation (BEIR) VII report is a well-recognized and frequently cited source on the legitimacy of the linear no-threshold (LNT) model—a model entailing a linear and causal relationship between ionizing radiation and human cancer risk. Linearity means that all radiation causes cancer and explicitly excludes a threshold below which radiogenic cancer risk disappears. However, the BEIR VII committee has erred in the interpretation of its selected literature; specifically, the in vitro data quoted fail to support LNT. Moreover, in vitro data cannot be considered as definitive proof of cancer development in intact organisms. This review is presented to stimulate a critical reevaluation by a BEIR VIII committee to reassess the validity, and use, of LNT and its derived policies.

THE EDITOR: Despite our previous responses (1,2), Duncan et al. continue to offer assumptions and misconceptions, instead of evidence and rational argument.For example, they make the following 4 claims in their most recent Letter to the Editor (3):1.They continue to assert that most DNA double-strand breaks caused by ionizing radiation are repaired by nonhomologous end joining, an error-prone process.Such cells survive but are left with mutations as permanent ''information scars,'' and there is little, if any, evidence, they say, that these cells are later removed to eliminate the low but finite risk of future cancers.As we noted previously (1), the repair fidelity of the damage produced by low-dose, low-LET (linear energy transfer) radiation associated with medical imaging may be no less than that by homologous recombination for endogenously induced damage.This is because the damage produced endogenously and by low-dose, low-LET radiation (whether isolated double-strand breaks or other) occurs by the same mechanism-free radicals; the predominant mode of interaction of low-LET radiation is by indirect action.2. Duncan et al. quote us correctly as saying that mutations are not sufficient to produce clinical cancer.They then counterpose a study by Martincorena and Campbell (4) that they say shows that cancers are necessarily preceded by mounting numbers of mutations in the same cell.These are both true.That multiple mutations are necessary does not say that they are sufficient to produce clinical cancer.Only epidemiologic studies, of which there are many, that demonstrate lowered cancer rates among those exposed to low-dose radiation can decide the issue, as logical as assumptions about outcome may appear. Duncan et al. cite in vitro experiments to justify their claimthat surviving cells after radiation exposure contain DNA mutations that are not ''removed with sufficient reliability to eliminate the low but finite risk of future cancers.''They refer to these in vitro experiments as ''elegant,'' and although they may be elegant for limited purposes, in vitro data cannot be considered indicative of cancer development in intact organisms (5).In vitro experiments lack both the mitochondrial oxygen-metabolizing processes that produce continual and extensive DNA damage every second of every day and the immune systems that continually remove cells that could potentially initiate cancer development as well as the cells that have begun that process.If this were not true of immune surveillance, we would all develop cancer.Intact organisms possess a steady state of DNA-damaged cells that permit adaptive processes, stimulated further by low-dose radiation, to repair or remove not only most of the added DNA damaged cells due to the radiation, but also some of the preexisting steady-state DNA-damaged cells.The net effect is a decrease in the number of damaged cells relative to the preexposure steady-state number.That such repair or removal may not be 100% efficient is correct, but it is

This paper examines the birthing process of the linear no-threshold model with respect to genetic effects and carcinogenesis. This model was conceived >70 years ago but still remains a foundational element within much of the scientific thought regarding exposure to low-dose ionizing radiation. This model is used today to provide risk estimates for cancer resulting from any exposure to ionizing radiation down to zero dose, risk estimates that are only theoretical and, as yet, have never been conclusively demonstrated by empirical evidence. We are literally bathed every second of every day in low-dose radiation exposure due to natural background radiation, exposures that vary annually from a few mGy to 260 mGy, depending upon where one lives on the planet. Irrespective of the level of background exposure to a given population, no associated health effects have been documented to date anywhere in the world. In fact, people in the United States are living longer today than ever before, likely due to always improving levels of medical care, including even more radiation exposure from diagnostic medical radiation (eg, x-ray and computed tomography imaging examinations) which are well within the background dose range across the globe. Yet, the persistent use of the linear no-threshold model for risk assessment by regulators and advisory bodies continues to drive an unfounded fear of any low-dose radiation exposure, as well as excessive expenditures on putative but unneeded and wasteful safety measures.

More recent understandings of mutations disclose a substantial number of spontaneous, endogenous double-strand breaks (DSBs) (EDSBs), and further studies of the close fidelity of DSB repairs between EDSBs and radiation-induced DSBs (RIDSBs) for low doses/dose rates (as with CT scans) demonstrate that there can be no identifiable, increased CT-induced cancer risk compared with the background risk from spontaneous EDSBs in the whole body.This results from the body's adaptive responses to LDR.Many CT scans produce doses less than 10 mSv, most are less than 20 mSv, and all are low in the LDR range.For a typical, lowdose CT scan covering 10% of the body, current literature shows that such low doses affect only DNA in a small fraction of cells in the target mass/volume.The RIDSBs from those are only about 3 in 1 million of the spontaneous EDSBs occurring in the body over the same time.Un-or misrepaired RIDSBs from higher doses are about 0.001% of the un-or misrepaired EDSBs in the body over the same time.For an essentially equal repair fidelity of RIDSBs and EDSBs, as discussed previously (6), un-or misrepaired RIDSBs are only about 0.0003% of un-or misrepaired EDSBs in the body over the same time.Further, all un-or misrepaired DSBs still require other low-probability events (which are also addressed by adaptive response) to arrive at some cancerous prelude.Finally, the U.S. government has recently reported that cancer incidence declined by about 1%/y, and cancer mortality declined by about 1.6%/y over recent years, whereas CT usage has expanded, in support of increasing early detection and decreasing cancer mortality.Duncan et al. ( 1) repeat the words that ''a threshold requires processes that leave no cells harboring DNA mutations'' (3).Contradictorily, Duncan et al. ( 1) then cite how DNA errors of EDSB repair can lead to inactivating tumor suppression genes through premalignant lesions.These are obviously background, spontaneous DNA events, and with large contributions of EDSBs harboring DNA mutations, the fallacy of the quotation (3) is apparent: large, spontaneous, EDSB backgrounds exist in the body due to its metabolism, environments, and other factors; thresholds exist because LDR stimulates adaptive responses to remove IRDSBs and EDSB backgrounds, an enhanced dose response that reduces the body's inventory of potential cancer precursors.

The linear no-threshold (LNT) assumption is over 70 years old and holds that all ionizing radiation exposure leaves cumulative effects, all of which are harmful regardless of how low the dose or dose rate is. The claimed harm centers on the risk of future radiogenic cancer. This has been shown countless times to be fallacious, and hundreds of scientific studies—both experimental and observational/epidemiological—demonstrate that at low enough doses and dose rates, ionizing radiation stimulates an evolved adaptive response and therefore is beneficial to health, lowering rather than raising the risk of cancer. Yet the myth of uncorrected lifetime cumulative risk still pervades the field of radiation science and underlies the policies of virtually all regulatory agencies around the world. This article explores some of the motivations behind, and methods used to assure, the extreme durability of the LNT myth in the face of the preponderance of contrary evidence and the manifest harms of radiophobia. These include subservience to the voice of authority, tactics such as claiming agnosticism on behalf of the entire field, transparent references to contrary evidence while dismissing the findings without refutation, and seeking shelter behind the legally protective medical standard of care.

Siegel, Jeffry A. PhD*; Sacks, Bill PhD, MD†; Pennington, Charles W. MS, MBA‡; Welsh, James S. MS, MD, FACRO§ Author Information

A debate exists within the medical community on whether the linear no-threshold model of ionizing radiation exposure accurately predicts the subsequent incidence of radiogenic cancer. In this article, we evaluate evidence refuting the linear no-threshold model and corollary efforts to reduce radiation exposure from CT and nuclear medicine imaging in accord with the as-low-as-reasonably-achievable principle, particularly for children. Further, we review studies demonstrating that children are not, in fact, more radiosensitive than adults in the radiologic imaging dose range, rendering dose reduction for children unjustifiable and counterproductive. Efforts to minimize nonexistent risks are futile and a major source of persistent radiophobia. Radiophobia is detrimental to patients and parents, induces stress, and leads to suboptimal image quality and avoidance of imaging, thus increasing misdiagnoses and consequent harm while offering no compensating benefits.

Radiologic imaging is claimed to carry an iatrogenic risk of cancer, based on an uninformed commitment to the 70-y-old linear no threshold hypothesis (LNTH). Credible evidence of imaging-related low-dose (<100 mGy) carcinogenic risk is nonexistent; it is a hypothetical risk derived from the demonstrably false LNTH. On the contrary, low-dose radiation does not cause, but more likely helps prevent, cancer. The LNTH and its offspring, ALARA (as low as reasonably achievable), are fatally flawed, focusing only on molecular damage while ignoring protective, organismal biologic responses. Although some grant the absence of low-dose harm, they nevertheless advocate the "prudence" of dose optimization (i.e., using ALARA doses); but this is a radiophobia-centered, not scientific, approach. Medical imaging studies achieve a diagnostic purpose and should be governed by the highest science-based principles and policies. The LNTH is an invalidated hypothesis, and its use, in the form of ALARA dosing, is responsible for misguided concerns promoting radiophobia, leading to actual risks far greater than the hypothetical carcinogenic risk purportedly avoided. Further, the myriad benefits of imaging are ignored. The present work calls for ending the radiophobia caused by those asserting the need for dose optimization in imaging: the low-dose radiation of medical imaging has no documented pathway to harm, whereas the LNTH and ALARA most assuredly do.