Future Risk Management Research Articles

Digital acceleration: How to build a robust enterprise data framework

This paper addresses data as a corporate asset that needs to be protected, but also shared and made accessible. The paper recognises data's role as the bedrock of the analytics that drive business decisions and that should be gathered routinely during normal, transactional operations. The paper acknowledges that the volume and sources of data and its users are diverse, global and continue to multiply. This, in turn, identifies the need for flexibility to design and develop a scalable model for data management that will support future growth and risk management capabilities. This paper outlines how to build a data framework, recognises the scale and complexity of the problem and recommends courses of action. These recommendations include data scoping, awareness of context, the wider macro trends and pressures, goal definition and the need to be outcome led. The paper further identifies that although most firms are already at some stage of their digital journey, there is no real ‘end goal’; it is a constant process. To successfully build a robust enterprise data framework, it therefore becomes crucial to work diligently and understand the steps required. The paper discusses approaches, pitfalls and the constantly evolving solution landscape. The paper concludes that the journey to a robust data management framework is complex, but, through embracing digital acceleration, it is possible to gain the competitive advantage to which the framework aspires.

Modeling Household Earthquake Hazard Adjustment Intentions: An Extension of the Protection Motivation Theory

While existing literature has explored how hazard experience, salience, and demographics characteristics shape threat appraisal and hazard adjustment intentions, this study expands on past studies by exploring how additional factors such as qualitative characteristics of the hazard, political ideology, and oil entanglements shape threat appraisals, coping appraisals, and adjustment intentions in response to a techna hazard. This study builds on protection motivation theory (PMT) to explore factors that shape Oklahomans’ intentions to adjust to induced seismicity using data collected from households (n=866) across 27 counties in Oklahoma that have experienced varying levels of seismic activity resulting from oil and gas exploration. Correlational analyses and structural equation modeling show that several variables not included in the original PMT, such as feelings of dread or negative emotions associated with earthquakes, are important predictors of intentions to adopt hazard adjustments. This study concludes with examining the effect of additional factors on adjustment intentions and risk perceptions that can help guide future earthquake risk management in identifying and taking appropriate actions that will stimulate precautionary behavior of private actors.

Generation of polystyrene-specific antibodies for developing immunoassays to analyze microplastics and nanoplastics

Micro- and nano-plastics (MNPs) are emerging pollutants that have drawn worldwide attention due to their negative impacts on the health and sustainability of our ecosystem. Quantitative analysis of MNPs, especially those at nano-scale, is still challenging due to lack of efficient analytical methods. Different antibody-based immunoassay platforms have been well established and readily available for rapid, specific, and quantitative analysis of targets with a broad size range. The key to developing immunoassays for MNP analysis is to generate plastic-specific antibodies, which is still lacking. In this study, we conjugated the nanoparticles of polystyrene (PS), a widely studied representative MNPs, to different carrier proteins for rabbit immunizations. The PS-specific antibodies were significantly induced upon immunization (up to 128-fold increase in IgG titer), which was validated by multi-tier immunoassays using different PS products. Notably, the PS-specific antibodies did not react with polypropylene, a different plastic. Using PS antibody-based enzyme-linked immunoassay, we further demonstrated suitability of the antibody-based immunoassay for quantitative analysis of the PS particles that have been exposed to diverse matrices. Together, this study, for the first time, demonstrates the feasibility of producing plastic-specific antibodies, and lays the groundwork to develop innovative antibody-based immunoassays for future risk assessment and management of MNPs, particularly those at nano-scale.

Uncertainty Quantification for Epidemic Risk Management: Case of SARS-CoV-2 in Morocco.

In this paper, we propose a new method for epidemic risk modelling and prediction, based on uncertainty quantification (UQ) approaches. In UQ, we consider the state variables as members of a convenient separable Hilbert space, and we look for their representation in finite dimensional subspaces generated by truncations of a suitable Hilbert basis. The coefficients of the finite expansion can be determined by approaches established in the literature, adapted to the determination of the probability distribution of epidemic risk variables. Here, we consider two approaches: collocation (COL) and moment matching (MM). Both are applied to the case of SARS-CoV-2 in Morocco, as an epidemic risk example. For all the epidemic risk indicators computed in this study (number of detections, number of deaths, number of new cases, predictions and human impact probabilities), the proposed models were able to estimate the values of the state variables with precision, i.e., with very low root mean square errors (RMSE) between predicted values and observed ones. Finally, the proposed approaches are used to generate a decision-making tool for future epidemic risk management, or, more generally, a quantitative disaster management approach in the humanitarian supply chain.

Metagenomic Insight into Microbiome and Antibiotic Resistance Genes of High Clinical Concern in Urban and Rural Hospital Wastewater of Northern India Origin: a Major Reservoir of Antimicrobial Resistance.

India is one of the largest consumers and producers of antibiotics and a hot spot for the emergence and proliferation of antimicrobial resistance genes (ARGs). Indian hospital wastewater (HWW) accumulates ARGs from source hospitals and often merges with urban wastewater, with the potential for environmental and human contamination. Despite its putative clinical importance, there is a lack of high-resolution resistome profiling of Indian hospital wastewater, with most studies either relying on conventional PCR-biased techniques or being limited to one city. In this study, we comprehensively analyzed antibiotic resistomes of wastewater from six Indian hospitals distributed in rural and urban areas of northern India through shotgun metagenomics. Our study revealed the predominance of ARGs against aminoglycoside, macrolide, carbapenem, trimethoprim, and sulfonamide antibiotics in all the samples through both read-based analysis and assembly-based analysis. We detected the mobile colistin resistance gene mcr-5.1 for the first time in Indian hospital sewage. blaNDM-1 was present in 4 out of 6 samples and was carried by Pseudomonas aeruginosa in HWW-2, Klebsiella pneumoniae in HWW-4 and HWW-6, and Acinetobacter baumanii in HWW-5. Most ARGs were plasmid-mediated and hosted by Proteobacteria. We identified virulence factors and transposable elements flanking the ARGs, highlighting the role of horizontal gene transmission of ARGs. IMPORTANCE There is a paucity of research on detailed antibiotic resistome and microbiome diversity of Indian hospital wastewater. This study reports the predominance of clinically concerning ARGs such as the beta-lactamases blaNDM and blaOXA and the colistin resistance gene mcr and their association with the microbiome in six different Indian hospital wastewaters of both urban and rural origin. The abundance of plasmid-mediated ARGs and virulence factors calls for urgent AMR crisis management. The lack of proper wastewater management strategies meeting international standards and open drainage systems further complicates the problem of containing the ARGs at these hospitals. This metagenomic study presents the current AMR profile propagating in hospital settings in India and can be used as a reference for future surveillance and risk management of ARGs in Indian hospitals.

Changes of hydro-meteorological trigger conditions for debris flows in a future alpine climate

Debris-flow activity is strongly controlled by hydro-meteorological trigger conditions, which are expected to change in a future climate. In this study we connect a regional hydro-meteorological susceptibility model for debris flows with climate projections until 2100 to assess changes of the frequency of critical trigger conditions for different trigger types (long-lasting rainfall, short-duration storm, snow-melt, rain-on-snow) in six regions in the Austrian Alps. We find limited annual changes of the number of days critical for debris-flow initiation when averaged over all regions, but distinct changes when separating between hydro-meteorological trigger types and study region. Changes become more evident at the monthly/seasonal scale, with a general trend of critical debris-flow trigger conditions earlier in the year. The outcomes of this study serve as a basis for the development of adaption strategies for future risk management.

Prehistoric pathways to Anthropocene adaptation: Evidence from the Red River Delta, Vietnam.

Over the past twenty years, government advisory bodies have placed increasing emphasis on the need for adaptive measures in response to the effects of human-induced climate change. Integrated Assessment Models (IAMs), which incorporate macroeconomic and climate variables, feature prominently in advisory content, though they rarely draw on data from outside strictly constrained hypothetical systems. This has led to assertions that they are not well-suited to approximate complex systemic human-environment processes. Modular, interdisciplinary approaches have offered a way to address this shortcoming; however, beyond climate records, prehistoric data continue to be under-utilised in developing such models. In this paper we highlight the contribution that archaeology and palaeoecology can make to the development of the next generation IAMs that are expected to enhance provision for more local and pro-active adaptations to future climate change. We present data from one of Southeast Asia's most heavily developed river deltas: the Red River (Song Hong) Delta, in Vietnam and localised analysis from the Tràng An Landscape Complex World Heritage Site, on the delta's southern margin. Comparison is made between Shared Socio-economic Pathways (SSP) 5-8.5 and SSP2-4.5 emission projection models and the Mid-Holocene inundation of the Red River Basin. We highlight the value to taking a scientific long view of coastal evolution through an illustrative set of eight research foci where palaeo-data can bring new and localised empirical data to bear on future risk management planning. We proceed to demonstrate the applicability of palaeoenvironmental, zooarchaeological and historical evidence to management and the development of sustainable conservation strategies using Tràng An as a case study. In so doing, we further highlight the importance of knowledge exchange between scientific, corporate, non-governmental, local, and state stakeholders to achieve tangible results on the ground.

Ecological consequences of a single introduced species to the Antarctic: terrestrial impacts of the invasive midge Eretmoptera murphyi on Signy Island

The nutrient-poor soils of Antarctica are sensitive to change. Recent increases in the number of anthropogenic introductions mean that understanding the impact of non-native species on Antarctic soils is pertinent, and essential for developing future risk assessments and management strategies. Through comparative baseline assessments of vegetation, microbes, soil chemistry, substrate composition and micro-arthropod abundance, this study explored if there are detectable terrestrial ecosystem impacts resulting from the introduction of the chironomid midge Eretmoptera murphyi to Signy Island in maritime Antarctica. The key finding was that E. murphyi is the likely driver of an increase in inorganic nitrogen availability within the nutrient-poor soils in which it occurs. When compared with the levels of inorganic nitrogen present in soils influenced by native vertebrate wildlife aggregations, the increase in local nitrate availability associated with E. murphyi was similar to that caused by deposits from seals and giant petrel colonies. Overall, available nitrate has increased by three- to five-fold in soils colonised by the midge, relative to undisturbed soils. This may ultimately impact rates of decomposition as well as the native plant and micro-arthropod communities of Signy Island.

Framework for multirisk climate scenarios across system receptors with application to the Metropolitan City of Venice.

Climate change influences the frequency of extreme events that affect both human and natural systems. It requires systemic climate change adaptation to address the complexity of risks across multiple domains and tackle the uncertainties of future scenarios. This paper introduces a multirisk analysis of climate hazard, exposure, vulnerability, and risk severity, specifically designed to hotspot geographic locations and prioritize system receptors that are affected by climate-related extremes. The analysis is demonstrated for the Metropolitan City of Venice. Representative scenarios (RCP4.5 and RCP8.5) of climate threats (i.e., storm surges, pluvial flood, heat waves, and drought) are selected and represented by projections of Regional Climate Models for a 30-year period (2021-2050). A sample of results is as follows. First, an increase in the risk is largely due to drought, pluvial flood, and storm surge, depending on the areas of interest, with the overall situation worsening under the RCP8.5 scenario. Second, particular locations have colocated vulnerable receptors at higher risk, concentrated in the urban centers (e.g., housing, railways, roads) and along the coast (e.g., beaches, wetlands, primary sector). Third, risk communication of potential environmental and socio-economic losses via the multirisk maps is useful to stakeholders and public administration. Fourth, the multirisk maps recommend priorities for future investigation and risk management, such as collection of sensor data, elaboration of mitigations, and adaptation plans at hotspot locations.

Exploring Spatio-Temporal Variations of Ecological Risk in the Yellow River Ecological Economic Belt Based on an Improved Landscape Index Method.

Intense human activities have led to profound changes in landscape patterns and ecological processes, generating certain ecological risks that seriously threaten human wellbeing. Ecological risk assessment from a landscape perspective has become an important tool for macroecosystem landscape management. This research improves the framework and indices of the ecological risk assessment from a landscape perspective, evaluates the land use pattern and landscape ecological risk dynamics in the Yellow River Ecological Economic Belt (YREEB), analyzes the spatiotemporal variation, and identifies key areas for ecological risk management. The results indicate the following: The main land use types in the region are grassland and cropland, but the area of cropland and grassland decreased during the study period, and with the accelerated urbanization, urban land is the only land use type that continued to increase over the 20-year period. The ecological risk in the YREEB tended to decrease, the area of low ecological risk zones increased, while the area of high ecological risk zones gradually decreased. Most areas are at medium risk level, but the risk in central Qinghai and Gansu is obviously higher, and there is a dispersed distribution of local high- and low-risk zones. A total of 37.7% of the study area is identified as critical area for future risk management, and the potential for increased risk in these areas is high. These results can provide a basis for sustainable development and planning of the landscape and the construction of ecological civilization in ecologically fragile areas.

Iron overload modulates follicular microenvironment via ROS/HIF-1α/FSHR signaling

Iron is essential for the health of reproductive system, and women with iron overload suffer from ovarian dysfunction and lack effective treatment in fertility preservation. However, the underlying mechanism of the detrimental effects of iron overload on ovarian function remains ambiguous. Here, we confirmed the excess iron in the circumjacent follicle near endometriomas, which negatively impacted the oocyte development in the affected ovaries. Further, by integrating cell line and chronic iron overload mice model, we demonstrated that iron overload can function as a ROS inducer to amplify mitochondria damage, which significantly elevated the release of cytochrome C and ultimately induced the apoptosis of granular cells. Besides, for the first time, our findings revealed that disruption of HIF-1α/FSHR/CYP19A1 signaling was critical for decreased estrogen synthesis of granular cells in response to iron overload, which can lead to apparent oocyte maldevelopment and subfertility. Overall. this study uncovered that iron overload modulated the follicular microenvironment and generated a deleterious effect on female infertility via ROS/HIF-1α/FSHR signaling. These results might provide potential implications for future clinical risk management of patients with endometrioma and hemopathy.

REIT Sector Implied Volatility Index: Liquidity and Information of Option Trading

An accurate volatility forecast is essential in financial investments and risk management. Existing literature finds that the implied volatility from options trading best predicts the realized volatility in various financial products. In 2016, real estate was added to the S&P 500 as the eleventh sector; however, a reliable implied volatility measure for the real estate sector has not been developed yet. The existing literature in real estate investment trusts (REITs) relies primarily on insufficient volatility forecasts, such as implied volatility for a broader market or time series analysis. In this research, we develop a REIT sector implied volatility index derived from options on the US Real Estate exchange-traded fund, IYR. As Whaley, the creator of the VIX (implied volatility on S&P 500), points out, enough liquidity in option trading is critical in developing an implied volatility index. This study shows that IYR option trading is liquid enough and informative that our REIT sector implied volatility index outperforms other volatility forecast measures. Our findings suggest that the REIT sector implied volatility index from option trading data can be utilized in future research and industry risk management.

Monitoring the Catastrophic Flood With GRACE-FO and Near-Real-Time Precipitation Data in Northern Henan Province of China in July 2021

Zhengzhou and its surrounding areas, located in northern Henan Province, China, receive continuous extreme rainfall from July 17 to July 22, 2021. Northern Henan Province experiences extensive flash floods and urban floods, causing severe casualties and property damage. Understanding the variation of hydrologic features during this flood event could be valuable for future flood emergency response work and flood risk management. This study first demonstrates the rainstorm process based on near-real-time precipitation data from the China Meteorological Administration Land Data Assimilation System (CLDAS-V2.0). To meet the temporal resolution required for monitoring this short-term flood event, reconstructed daily terrestrial water storage anomalies (TWSAs) based on GRACE and GRACE-FO data and CLDAS-V2.0 datasets are first introduced. The spatial and temporal evolution of the reconstructed daily TWSA is analyzed in the study area during this heavy rainfall event. We further employ a wetness index based on the reconstructed daily TWSA for flood warnings. Furthermore, the modeled soil moisture data and daily runoff data are used for flood monitoring. Results show that the reconstructed daily TWSA increases by 437.7 mm in just six days (from July 17 to July 22, 2021), with a terrestrial water storage increment of 9.4 km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> . Compared with ITSG-Grace2018, the reconstructed daily TWSA has better potential for near-real-time flood monitoring for short-term events in a small region. The wetness index derived from reconstructed daily TWSA is potential for flood early warning.

Farmers’ adoption intentions of water-saving agriculture under the risks of frequent irrigation-induced landslides

Water-saving agriculture (WSA) is often introduced as an effective strategy to reduce water infiltration and mitigate irrigation-induced landslide risks. The effects highly rely on smallholder farmers, who often would rather suffer from landslides than adapt. This study focused on farmers’ adoption intention of WSA in general and drip irrigation and drought-tolerant crop in specific, representing changes in technology and farming systems. An integrative theoretical model was developed based on the extended theory of planned behavior (TPB) with elements from the norm activation model and technology acceptance model. Hypotheses were tested using data from a questionnaire survey with 363 farmers in Loess Plateau, Northwest China. The results of structural equation modeling showed that the most crucial factor bolstering farmers’ adoption intention was subjective norm, regardless of different measures. Attitude was more influential than perceived behavior control in drip irrigation and vice versa in drought-tolerant crop adoption, indicating that attitude was more important in technology change and capacity played a crucial role in farming system shift. In addition, awareness of environmental consequences contributed positively to subjective norm and attitude, and perceived ease-of-use improved perceived behavior control. Most notably, the extended TPB model has more explanatory power than the classical one. By considering the moral and technical aspects, the extended model enhanced the comprehensiveness of explaining drivers of farmers’ WSA adoption intention under the irrigation-induced landslide risks. The findings shed light on future disaster risk management for China and other countries under the landslide risk.

Impact of climate change on hydro-meteorological trigger conditions for debris flows in Austria

Debris-flow activity is expected to change in a future climate. In this study we connect a susceptibility model for debris-flows on a regional scale with climate projections until 2100. We use this to assess changes of hydro-meteorological trigger conditions for debris flows in six regions in the Austrian Alps. We find limited changes on an annual basis, but distinct changes when separating between hydro-meteorological trigger types and regions. While regions in the east and in the south of Austria may experience less days susceptible to debris flows in summer, there is a general trend of increasing susceptibility earlier in the year for both, rainfall-related and snow-related trigger conditions. The outcomes of this study serve as a basis for the development of adaption strategies for future risk management from this debris-flow hazard.

Health risk assessment and cost-benefit analysis of agricultural soil remediation for tailing dam failure in Jinding mining area, SW China.

The impact of the tailing dams and the economic feasibility of the remediation process is significant for future risk management for tailing dams. In this research, we develop a hypothetical failure scenario for a tailing dam in the Jinding mining area, Southwest China. We assess the exposure with the Geo-Environmental Risk Assessment System, tier-1 model, and health impact with Disability-Adjusted Life Years (DALY). Cost and benefit are also analyzed for the following clean-up process. The result shows that the exposure dose (mg/kg-BW/d) of As, Cd, and Pb right after the dam failure is 1.07 × 10-2 for As, 1.76 × 10-4 for Cd, and 5.68 × 10-3 for Pb, respectively. The DALY caused by heavy metal exposure is 2.63 × 10-2 DALY per year, which significantly exceeds the tolerable level. This indicates that the tailing dam failure will pose a high health risk to the residents, and remediation is necessary. After remediation, the DALY is 1.24 × 10-8 DALY per year, indicating the clean-up process effectively reduces the resident's health impact. From the financial point of view, the net present value of the clean-up is $- 1.02 × 107. This indicates that the clean-up process is not economically feasible. Sensitivity analysis shows that the amount of released tailing influences the output result. The time span for benefit estimation is also an important issue. This research shows that the impact of a tailing dam failure will be severe, and remediation may be effective but economically infeasible. Therefore, preventing tailing dam failure is the most crucial task for the local government.

How Much Are Fans Willing to Pay to Help “Their” Soccer Clubs to Overcome a Crisis? An Analysis of Central European Fans during the COVID-19 Pandemic

Through restrictions and people’s behavioral changes with regard to public events, the COVID-19 pandemic has had a massive financial impact on professional team sports clubs. Particularly, many smaller clubs that are more dependent on match-day revenues were facing an existential struggle. In this study, we examined the willingness of fans to contribute financially to help their favorite teams to overcome financial difficulties caused by this unforeseen operational risk. Moreover, we investigated the significance of the level of team identification among fans as an antecedent for willingness to pay. Analyzing the data from an online survey with 178 respondents, we found that fans would be willing to participate in fundraising campaigns to support their favorite teams. Among the fans of small clubs, the level of identification drives the willingness to support. On the one hand, the findings are encouraging for clubs as they underscore the potential role fans could play in overcoming the current crisis while showing that including fans in future risk management strategies is a promising approach. On the other hand, for this to be successful, clubs need to unravel and invest in measures for nurturing the fans’ identification with the team.

Ashkenazi Jewish and Other White APC I1307K Carriers Are at Higher Risk for Multiple Cancers.

Purpose: APC I1307K has a higher prevalence among Ashkenazi Jews (AJ), and a two-fold increased risk for colorectal cancer (CRC) compared to non-Jewish populations. We assessed CRC and extracolonic malignancies among I1307K carriers from AJ and non-AJ whites (NAW). Methods: We compared the rate of I1307K in cancer patients who underwent germline genetic testing via a multi-gene panel with healthy subjects retrieved from the gnomAD database. Cases undergoing testing were not selected and testing was undertaken through a commercial laboratory. Results: Overall, 586/7624 (7.6%) AJ with cancer carried I1307K compared to 342/4918 (6.9%) in the AJ control group (p = NS). In the NAW, 318/141,673 (0.2%) cancer patients and 73/58,918 (0.1%) controls carried the variant [OR = 1.8, (95% CI 1.41−2.35), p < 0.001]. I1307K in NAW was associated with an increased risk of CRC [OR = 1.95, (95% CI 1.39−2.73), p < 0.01], melanoma [OR = 2.54, (95% CI 1.57−3.98)], breast [females, OR = 1.73, (95% CI 1.18−2.65), p < 0.01], and prostate cancer [males, OR = 2.42, (95% CI 1.45−3.94), p < 0.01]. Among AJ, the variant increased the risk for CRC [OR = 1.67, (95% CI 1.36−2.05), p < 0.001] and renal cancer [OR = 1.64, (95% CI 1.04−2.47)]. AJ men had a higher risk for any cancer [OR = 1.32, (95% CI 1.05−1.66), p < 0.05] and melanoma [OR = 2.04, (95% CI 1.24−3.22); p < 0.05]. Conclusions: This is the most extensive study to date conducted on I1307K carriers, although it is amenable to selection bias. NAW carrying I1307K had a higher risk of any cancer and several specific cancer types, whereas AJ carrying the variant had a risk for only a few select cancers. Our data add to the research base on I1307 carriers concerning future risk management.

Introducing NARCliM1.5: Evaluation and projection of climate extremes for southeast Australia

NARCliM1.5 is the second generation of New South Wales and Australian Regional Climate Modelling (NARCliM) project, which is designed to produce an ensemble of regional climate projections for CORDEX Australasia and southeast Australia. The selected global climate models (GCMs) are used to drive Weather Research and Forecasting (WRF) model for dynamical downscaling. In this study, we evaluate how well the two generations of NARCliM (N1.0 and N1.5) represent the observed record for 12 selected climate extremes and examine their projected changes for southeast Australia. N1.5 ensemble substantially improves upon N1.0 in capturing the spatial patterns of precipitation extremes, however, there is little difference between the two ensembles for temperature extremes. Both N1.0 and N1.5 underestimate dry extreme (consecutive dry day - CDD), hot extremes (warmest daily maximum temperature – TXx, and number of days when maximum temperature is greater than 35 °C - TXge35) and daily temperature range (DTR) but overestimate wet extremes (annual sum of daily precipitation above 99th percentile - R99p, consecutive wet days - CWD, days when precipitation is at least 10 mm - R10mm, maximum 1-day precipitation - Rx1Day and total wet day precipitation -PRCPTOT) and cold extreme (coldest daily minimum temperature - TNn). N1.0 and N1.5 project different spatial patterns of future changes in precipitation extremes but similar changes in temperature extremes. Differences in climate extremes between N1.0 and N1.5 could be attributed to the driving GCMs. The combined future projections of both N1.0 and N1.5 provide a more complete sampling of the future change space. Future projections indicate that precipitation and temperature extremes will become more intense, raising implications for future planning and risk management.

Shower water contributes viable nontuberculous mycobacteria to indoor air.

Nontuberculous mycobacteria (NTM) are frequently present in municipal drinking water and building plumbing, and some are believed to cause respiratory tract infections through inhalation of NTM-containing aerosols generated during showering. However, the present understanding of NTM transfer from water to air is insufficient to develop NTM risk mitigation strategies. This study aimed to characterize the contribution of shower water to the abundance of viable NTM in indoor air. Shower water and indoor air samples were collected, and 16S rRNA and rpoB genes were sequenced. The sequencing results showed that running the shower impacted the bacterial community structure and NTM species composition in indoor air by transferring certain bacteria from water to air. A mass balance model combined with NTM quantification results revealed that on average 1/132 and 1/254 of NTM cells in water were transferred to air during 1 hour of showering using a rain and massage showerhead, respectively. A large fraction of the bacteria transferred from water to air were membrane-damaged, i.e. they had compromised membranes based on analysis by live/dead staining and flow cytometry. However, the damaged NTM in air were recoverable as shown by growth in a culture medium mimicking the respiratory secretions of people with cystic fibrosis, implying a potential infection risk by NTM introduced to indoor air during shower running. Among the recovered NTM, Mycobacterium mucogenicum was the dominant species as determined by rpoB gene sequencing. Overall, this study lays the groundwork for future pathogen risk management and public health protection in the built environment.