System inflammation response index: a novel inflammatory indicator to predict all-cause and cardiovascular disease mortality in the obese population.

AIM: This study aims to investigate the relationship between two novel inflammatory markers, namely, the Systemic Inflammatory Response Index (SIRI) and the Systemic Immune Inflammatory Index (SII), as well as the all-cause and cardiovascular disease (CVD) mortality in the obese population. MATERIALS AND METHODS: We conducted a prospective cohort study based on the data of 13,026 obese adults (age ≥ 18 years) from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2014 and followed until December 2019. SIRI was calculated by the formula: (neutrophil count × monocyte count) / lymphocyte count, while that of SII was: (platelet count × neutrophil count)/lymphocyte count. The association of SIRI and SII with all-cause and CVD mortality was evaluated using Cox regression. In addition, the nomogram was performed to predict 10-year survival probability. RESULTS: During a median follow-up of 137 months, 1959 and 553 all-cause and CVD deaths were recorded, respectively. Spearman correlation analysis indicated that SIRI and SII were unrelated to almost all baseline characteristics (r < 0.15). Multivariate Cox regression models displayed that each standard deviation (SD) increase in SIRI was associated with a 16% (HR 1.16; 95% CI 1.09-1.24) and 22% (HR 1.22; 95% CI 1.10-1.36) increase in the risk of all-cause and CVD mortality, respectively. Likewise, every SD increase in SII was correlated with a 9% (HR 1.09; 95% CI 1.02-1.16) and 14% (HR 1.14; 95% CI 1.04-1.26) increase in the risk of all-cause and CVD mortality, respectively. The predictive value of SIRI for all-cause and CVD mortality (AUC = 0.601 and 0.624) exceeded that of SII (AUC = 0.528 and 0.539). Moreover, the nomogram displayed a substantial predictive value for 10-year survival (AUC = 0.847) with sensitivity and specificity exceeding 75%. CONCLUSIONS: In the obese population, SIRI and SII are independent risk factors for all-cause and CVD mortality. Notably, the predictive ability of SIRI for both all-cause and CVD mortality significantly outperforms that of SII, suggesting that SIRI is a more valuable marker of inflammation.

Higher systemic immune-inflammation index and systemic inflammation response index levels are associated with stroke prevalence in the asthmatic population: a cross-sectional analysis of the NHANES 1999-2018.

Background: Significant evidence suggests that asthma might originate from low-grade systemic inflammation. Previous studies have established a positive association between the systemic immune-inflammation index (SII) and the systemic inflammation response index (SIRI) levels and the risk of stroke. However, it remains unclear whether SII, SIRI and the prevalence of stroke are related in individuals with asthma. Methods: The present cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2018. SII was calculated using the following formula: (platelet count × neutrophil count)/lymphocyte count. SIRI was calculated using the following formula: (neutrophil count × monocyte count)/lymphocyte count. The Spearman rank correlation coefficient was used to determine any correlation between SII, SIRI, and the baseline characteristics. Survey-weighted logistic regression was employed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) to determine the association between SII, SIRI, and stroke prevalence. The predictive value of SII and SIRI for stroke prevalence was assessed through receiver operating characteristic (ROC) curve analysis, with the area under the ROC curve (AUC) being indicative of its predictive value. Additionally, clinical models including SIRI, coronary heart disease, hypertension, age, and poverty income ratio were constructed to evaluate their clinical applicability. Results: Between 1999 and 2018, 5,907 NHANES participants with asthma were identified, of which 199 participants experienced a stroke, while the remaining 5,708 participants had not. Spearman rank correlation analysis indicated that neither SII nor SIRI levels exhibited any significant correlation with the baseline characteristics of the participants (r<0.1). ROC curves were used to determine the optimal cut-off values for SII and SIRI levels to classify participants into low- and high-level groups. Higher SII and SIRI levels were associated with a higher prevalence of stroke, with ORs of 1.80 (95% CI, 1.18-2.76) and 2.23 (95% CI, 1.39-3.57), respectively. The predictive value of SIRI (AUC=0.618) for stroke prevalence was superior to that of SII (AUC=0.552). Furthermore, the clinical model demonstrated good predictive value (AUC=0.825), with a sensitivity of 67.1% and specificity of 87.7%. Conclusion: In asthmatics, higher levels of SII and SIRI significantly increased the prevalence of stroke, with its association being more pronounced in individuals with coexisting obesity and hyperlipidaemia. SII and SIRI are relatively stable novel inflammatory markers in the asthmatic population, with SIRI having a better predictive value for stroke prevalence than SII.

Predictive value of estimated pulse wave velocity with all-cause and cause-specific mortality in the hypertensive population: the National Health and Nutrition Examination Surveys 1999-2014.

BACKGROUND: Estimated pulse wave velocity (ePWV) has been proposed as a potential approach to assess carotid-femoral pulse wave velocity (cfPWV). However, the potential ability of ePWV to predict all-cause and cause-specific mortality in the population group with hypertension remains unresolved. METHODS: We conducted a prospective cohort study using the data of 14 044 adults (age ≥18 years) from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2014, and followed this cohort until the end of December 2019. ePWV was calculated by using a regression equation for age and mean blood pressure (MBP), derived by the Arterial Stiffness Collaborative Group. RESULTS: The weighted mean age of the 14 044 adults included was 54.79 years; 49.42% of all participants were men. During the median follow-up period of 11 years, 3795 deaths were recorded. In the fully adjusted cox regression model, each 1 m/s increase in ePWV was associated with an increased risk of 56% [hazard ratio 1.61; 95% confidence interval (CI) 1.49-1.64] risk for all-cause mortality. Every 1 m/s increase in ePWV resulted in an increased risk of mortality from cardiovascular disease, cerebrovascular disease, respiratory disease, Alzheimer's disease, accidents, cancer, influenza and pneumonia by 60, 70, 47, 118, 73, 41 and 103%, respectively. ePWV has a robust predictive value for 5- and 10-year all-cause mortality in the hypertensive population with AUCs of 0.749 and 0.741, respectively. CONCLUSION: Elevated ePWV is positively correlated with all-cause mortality and most cause-specific mortalities, independent of traditional risk factors. Moreover, ePWV demonstrates high accuracy in predicting 5-year and 10-year all-cause mortality, outperforming Framingham Risk Score.

Machine Learning for Brain MRI Data Harmonisation: A Systematic Review.

BACKGROUND: Magnetic Resonance Imaging (MRI) data collected from multiple centres can be heterogeneous due to factors such as the scanner used and the site location. To reduce this heterogeneity, the data needs to be harmonised. In recent years, machine learning (ML) has been used to solve different types of problems related to MRI data, showing great promise. OBJECTIVE: This study explores how well various ML algorithms perform in harmonising MRI data, both implicitly and explicitly, by summarising the findings in relevant peer-reviewed articles. Furthermore, it provides guidelines for the use of current methods and identifies potential future research directions. METHOD: This review covers articles published through PubMed, Web of Science, and IEEE databases through June 2022. Data from studies were analysed based on the criteria of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Quality assessment questions were derived to assess the quality of the included publications. RESULTS: a total of 41 articles published between 2015 and 2022 were identified and analysed. In the review, MRI data has been found to be harmonised either in an implicit (n = 21) or an explicit (n = 20) way. Three MRI modalities were identified: structural MRI (n = 28), diffusion MRI (n = 7) and functional MRI (n = 6). CONCLUSION: Various ML techniques have been employed to harmonise different types of MRI data. There is currently a lack of consistent evaluation methods and metrics used across studies, and it is recommended that the issue be addressed in future studies. Harmonisation of MRI data using ML shows promises in improving performance for ML downstream tasks, while caution should be exercised when using ML-harmonised data for direct interpretation.

Music and Brain Circuitry: Strategies for Strengthening Evidence-Based Research for Music-Based Interventions.

The neuroscience of music and music-based interventions (MBIs) is a fascinating but challenging research field. While music is a ubiquitous component of every human society, MBIs may encompass listening to music, performing music, music-based movement, undergoing music education and training, or receiving treatment from music therapists. Unraveling the brain circuits activated and influenced by MBIs may help us gain better understanding of the therapeutic and educational values of MBIs by gathering strong research evidence. However, the complexity and variety of MBIs impose unique research challenges. This article reviews the recent endeavor led by the National Institutes of Health to support evidence-based research of MBIs and their impact on health and diseases. It also highlights fundamental challenges and strategies of MBI research with emphases on the utilization of animal models, human brain imaging and stimulation technologies, behavior and motion capturing tools, and computational approaches. It concludes with suggestions of basic requirements when studying MBIs and promising future directions to further strengthen evidence-based research on MBIs in connections with brain circuitry.SIGNIFICANCE STATEMENT Music and music-based interventions (MBI) engage a wide range of brain circuits and hold promising therapeutic potentials for a variety of health conditions. Comparative studies using animal models have helped in uncovering brain circuit activities involved in rhythm perception, while human imaging, brain stimulation, and motion capture technologies have enabled neural circuit analysis underlying the effects of MBIs on motor, affective/reward, and cognitive function. Combining computational analysis, such as prediction method, with mechanistic studies in animal models and humans may unravel the complexity of MBIs and their effects on health and disease.

Acupuncture for de Quervain's tenosynovitis: A randomized controlled trial.

BACKGROUND: Acupuncture has been an alternative approach for de Quervain's tenosynovitis (DQt), but trial evidence is still lacking. PURPOSE: This study aimed to assess the efficacy of acupuncture in patients with DQt. STUDY DESIGN: A randomized controlled trial. METHODS: A total of 68 subjects with DQt were recruited from outpatients of Department of Orthopaedics and Traumatology, and Chinese medicine clinics, The University of Hong Kong, and were randomized into the acupuncture group (n = 34) and the waitlist group (n = 34). Subjects in the acupuncture group received 5 acupuncture sessions over 2 weeks, followed by a 10-week follow-up. The waitlist control group received assessments only in the first 6 weeks of the waiting period and received the same acupuncture treatment and follow-up as the treatment group in the next 12 weeks. The primary outcome was the general pain intensity using the Visual Analogue Scale (VAS) at the end of treatment (week 2). Secondary outcomes were grip and pinch strengths of affected hands, the quick Disabilities of the Arm, Shoulder and Hand Score (Q-DASH), and the World Health Organization Quality of Life-brief Questionnaire (WHOQOL-BREF) at weeks 2 and 6. RESULTS: From baseline to 2 weeks, the mean VAS score decreased by 19.5 points in the acupuncture group and by 3.4 points in the waitlist group. The difference for acupuncture vs waitlist control was -16.2 points (95% CI, -26.7 to -5.6, p = 0.003). Acupuncture effects sustained for 10 weeks (mean difference compared with baseline, -30.6; 95% CI, -39.6 to -21.7). Secondary outcomes showed that acupuncture reduced pain intensity, improved grip and pinch strength of affected hands, and Q-DASH scores, but not the scores of WHOQOL-BREF in patients. No serious adverse event occurred during the study period. CONCLUSIONS: Our findings support that 2-week of acupuncture is safe and effective in the reduction of pain intensity, and improvement of strengths and disabilities of hand in DQt patients. Acupuncture also has long-term effects on DQt. TRIAL REGISTRATION: This study was registered at clinicaltrials.gov (NCT03472443).

Characterization of natural antisense transcripts arisen from the locus encoding Toxoplasma gondii ubiquitin-like protease.

Natural antisense transcripts (NATs) are non-protein coding RNAs that could play an important role in regulating the expression of their counterpart protein encoding sense transcript. Although NATs are widespread in most eukaryotic genomes, very little is known about their functions. This study focuses on gaining a better understanding of the function of NATs in Toxoplasma gondii, a pathogenic unicellular eukaryote. Previously, we characterized the gene encoding the first committed enzyme in sumoylation, named ubiquitin-like protease 1 (TgUlp1), and showed that the expression of TgUlp1 is vital to the life cycle of T. gondii. Interestingly, the locus of TgUlp1 also transcribes a NAT species. Using a dual luciferase assay, we identified the promoter of TgUlp1 NAT to be located within the 3'-region of its counterpart coding sequence. While TgUlp1 mRNA level was detected at a lower level throughout the life cycle of T. gondii, its NAT level was upregulated when the parasite converts from actively replicating tachyzoite form to slowly growing bradyzoite form. To investigate the effect of TgUlp1 NAT on the expression of its counterpart mRNA, we used a reporter system bearing TgUlp1 mRNA sequences and showed that the single-stranded TgUlp1 NAT and its in vitro RNase III processed products have the ability to lower the expression of the reporter system. Using a transgenic Dicer-knockout (TgDicer-KO) strain, we showed that TgDicer is required for the function of TgUlp1 NAT in vivo. The findings strongly suggest that the RNA interference pathway is necessary for the function of TgUlp1 NAT.

Effects of natural organic matters on bioavailability of petroleum hydrocarbons in soil-water environments.

The bioremediation efficiency of petroleum hydrocarbons in natural soil-water systems is regulated by active microbial populations and other system parameters. Relevant factors include the transfer rate of petroleum contaminants from a medium into microorganisms, the partitioning behavior of contaminants from water into the soil organic matter (SOM), and the influence of the dissolved organic matter (DOM) on the contaminant level in water. The objectives of this study was aimed to determine the correlation among bioavailability of petroleum hydrocarbons, SOM content, and DOM level in soil-water systems. Heptadecane, pristane, and decylcyclohexane were selected as model hydrocarbon contaminants. The bioavailability of target contaminants in soil was examined using soils of different SOM contents (2% and 20%) in slurry bioreactors. In addition, the contaminant bioavailability as affected by various DOM levels (0-100 mgC/L) was also examined. The results showed that the SOM content affected the degrading rate of hydrocarbons significantly, where the rate constant was 4 times higher in 2% SOM microcosm than in the 20% SOM bioreactor for heptadecane degradation. Similarly, the pristane degrading efficiency after 240 h operation was 95% for the 2% SOM microcosm and only 38% for the 20% SOM microcosm. The hydrocarbon degradation rates in water phase were found to be enhanced by the added DOM level. A positive correlation existed between the contaminant bioavailability and the contaminant level in water as impacted by the SOM content in soil and the DOM level in water.

Application of molecular biological tools for monitoring efficiency of trichloroethylene remediation.

Trichloroethylene (TCE) is one of the most ubiquitous halogenated organic compounds of concerns of carcinogens in groundwater in Taiwan. Bioremediation has been recognized as a cost-effective approach in reducing TCE concentration. Five pilot-scale wells were constructed to monitor TCE concentrations in contaminated groundwater. With injection of EOS®, TCE was effectively degraded to 42%-93% by the end of 175 days. The biostimulation with EOS® was useful in establishing a micro-site anaerobic but with limited contribution. Dilution of the aquifer movement also caused the TCE reduction among injection and monitoring wells. The degradability was affected by the location and the proximity from the injection well. TCE concentrations found to be negatively correlated with the associated Dehalococcoides spp. and functional genes levels. Dhc concentration of 108 copies L-1 caused the initial 40% of TCE degradation. The well with the optimal degradation owned tceA of 109 cells L-1. T-RFLP results indicate the wells with the superior TCE degradability also performed the highest Shannon index number (means the highest diversity), which occurred on the same day that Dhc levels started to enlarge. Desulfovibrio desulfuricans and Desulfuromonas chloroethenica were predominant species identified in the T-RFLP fingerprint profile. In brief, a variety of different factors including well locations, geochemical indicators, and microbial contribution were useful to explain the site-specific optimal TCE remediation approach. The consistence among TCE degradation, Dhc growing pattern, functional gene levels, and the dynamics of the microbial community structure present the novelty of this study.

Molecular analysis of methanogens involved in methanogenic degradation of tetramethylammonium hydroxide in full-scale bioreactors.

This study investigated methanogenic communities involved in degradation of tetramethylammonium hydroxide (TMAH) in three full-scale bioreactors treating TMAH-containing wastewater. Based on the results of terminal-restriction fragment-length polymorphism (T-RFLP) and quantitative PCR analyses targeting the methyl-coenzyme M reductase alpha subunit (mcrA) genes retrieved from three bioreactors, Methanomethylovorans and Methanosarcina were the dominant methanogens involved in the methanogenic degradation of TMAH in the bioreactors. Furthermore, batch experiments were conducted to evaluate mcrA messenger RNA (mRNA) expression during methanogenic TMAH degradation, and the results indicated that a higher level of TMAH favored mcrA mRNA expression by Methansarcina, while Methanomethylovorans could only express considerable amount of mcrA mRNA at a lower level of TMAH. These results suggest that Methansarcina is responsible for methanogenic TMAH degradation at higher TMAH concentrations, while Methanomethylovorans may be important at a lower TMAH condition.

Biological treatment of TMAH (tetra-methyl ammonium hydroxide) in a full-scale TFT-LCD wastewater treatment plant.

This study evaluated biological treatment of TMAH in a full-scale methanogenic up-flow anaerobic sludge blanket (UASB) followed by an aerobic bioreactor. In general, the UASB was able to perform a satisfactory TMAH degradation efficiency, but the effluent COD of the aerobic bioreactor seemed to increase with an increased TMAH in the influent wastewater. The batch test results confirmed that the UASB sludge under methanogenic conditions would be favored over the aerobic ones for TMAH treatment due to its superb ability of handling high strength of TMAH-containing wastewaters. Based on batch experiments, inhibitory chemicals present in TFT-LCD wastewater like surfactants and sulfate should be avoided to secure a stable methanogenic TMAH degradation. Finally, molecular monitoring of Methanomethylovorans hollandica and Methanosarcina mazei in the full-scale plant, the dominant methanogens in the UASB responsible for TMAH degradation, may be beneficial for a stable TMAH treatment performance.

Effects of soil organic matter and ageing on remediation of diesel-contaminated soil.

Bioremediation of diesel-contaminated soil was investigated for the effects of soil organic matter (SOM) and ageing time in two sets of experiments (Batch I and II, respectively). This study examined degradation efficiency in soil artificially contaminated with diesel oil (maximum total petroleum hydrocarbons (TPH) concentration of 9000 mg/kg soil). Batch I data showed that the values of the first-order degradation rate, k, were relatively high in the low-SOM soil batches. The quantity of SOM negatively correlated with the TPH degradation rates and with the total TPH degradation efficiency (%). Introduction of rhamnolipid to the soil proved to be a useful solution to resolve the problem of the residual TPH in the soil with high SOM. In Batch II, the k values decreased with the length of ageing time: 0.0245, 0.0128 and 0.0090 l/d in samples ST0 (freshly contaminated), ST38 (aged for 38 days) and ST101 (aged for 101 days), respectively. The TPH degradation efficiency (%) also decreased along with the ageing time. The research also applied molecular technology to analyse the bacterial community dynamics during the bioremediation course. Multivariate statistics based on terminal-restriction fragment length data indicated: 1) the soils with different SOM resulted in separate bacterial community structures, 2) ageing time created a variety of bacterial communities, 3) the bacterial community dynamics was associated with the hydrocarbon consumption. The SOM content in soils affected the TPH degradation rate and efficiency and the bacterial community structures. Aged soil is more difficult to remediate than freshly contaminated soil, and the resulting bacterial community was less dynamic and showed a lack of succession.

Source impacts by volatile organic compounds in an industrial city of southern Taiwan.

This study investigates source impacts by airborne volatile organic compounds (VOC) at two sites designated for traffic and industry, in the largest industrial area Kaohsiung, southern Taiwan. The samples were collected at the two sites simultaneously during rush and non-rush hours in summer and autumn seasons. Same pattern of VOC groups were found at both sites: most abundant aromatics (78-95%) followed by alkanes (2-16%) and alkenes (0-6%). The BTEX concentration measured at the two sites ranged from 69 to 301 ppbC. Toluene, isopentane, ethylbenzene, and benzene were found to be the most abundant species. Speciation of VOCs was characterized with several skills including principal component factor analysis and BTEX characteristic ratios. Each of the resulted principal factors at the two sites explained over 80% of the VOCs data variance, and indicated that both of the sampling sites were influenced by both traffic and industrial sources with separately different levels. The remarkable patterns of the first two factors described not only the similarity but also the discrepancy at the two sampling sites, in terms of the source impacts. The high T/B ratios (7.56-14.25) observed at the industrial site implied the important impact from mobile emissions. The indicators, m,p-xylene/benzene and o-xylene/benzene, also confirmed the potential source of motor vehicles at both of the sampling sites. Air age assessment showed that more than half of the total observations located in the domain of fresh air. Low X/E ratios implied somewhat aged air mass transported to the sampling sites. The industrial site might not only encounter emissions from the industry sources, but also under unavoidable impact from the traffic sources.

Preliminary investigation of greenhouse gas emissions from the environmental sector in Taiwan.

The United Nations Framework Conventions on Climate Change (UNFCCC) asks their Parties to submit a National Inventory Report (NIR) for greenhouse gas (GHG) emissions on an annual basis. However, when many countries are quickly growing their economy, resulting in substantial GHG emissions, their inventory reporting systems either have not been established or been able to be linked to planning of mitigation measures at national administration levels. The present research was aimed to quantify the GHG emissions from an environmental sector in Taiwan and also to establish a linkage between the developed inventories and development of mitigation plans. The "environmental sector" consists of public service under jurisdiction of the Taiwan Environmental Protection Administration: landfilling, composting, waste transportation, wastewater treatment, night soil treatment, and solid waste incineration. The preliminary results were compared with that of the United States, Germany, Japan, United Kingdom, and Korea, considering the gaps in the scopes of the sectors. The GHG emissions from the Taiwanese environmental sector were mostly estimated by following the default methodology in the Intergovernmental Panel on Climate Change guideline, except that of night soil treatment and waste transportation that were modified or newly developed. The GHG emissions from the environmental sectors in 2004 were 10,225 kilotons of CO2 equivalent (kt CO2 Eq.). Landfilling (48.86%), solid waste incineration (27%), and wastewater treatment (21.5%) were the major contributors. Methane was the most significant GHG (70.6%), followed by carbon dioxide (27.8%) and nitrous oxide (1.6%). In summary, the GHG emissions estimated for the environmental sector in Taiwan provided reasonable preliminary results that were consistent and comparable with the existing authorized data. On the basis of the inventory results and the comparisons with the other countries, recommendations of mitigation plans were made, including wastewater and solid waste recycling, methane recovery for energy, and waste reduction/sorting.

Establishment of a Box-Jenkins multivariate time-series model to simulate ground-level peak daily one-hour ozone concentrations at Ta-Liao in Taiwan.

Box-Jenkins univariate autoregressive integrated moving average (ARIMA) and regression with time-series error (RTSE) models were established to simulate historical peak daily 1-hr ozone concentrations at Ta-Liao, Taiwan, 1997-2001. During 1995-2003, the 600 days of Pollution Standard Index (PSI) more than 100 (peak daily 1-hr ozone concentrations detected by greater than 120 ppm) at Tao-Liao showed the highest ozone exceedances among the six monitoring stations in Kaohsiung County. To improve the predictability of extremely high ozone, two different principal components, PC1 and PC(1 + 2), were introduced in the RTSE model. Four typical predictors (particular matter with an aerodynamic diameter less than or equal to 10 microm, temperature, wind speed, and wind direction) plus a PC trigger remained significant in the RTSE model. The model performance statistics concluded that the RTSE model with PC1 was optimal, compared with the univariate ARIMA, the RTSE model without PC, and RTSE model with PC(1 + 2). The contingency table shows that the successful predictions of the univariate model were only 12.9% of that of the RTSE model with PC1. Also, the POD value was improved approximately 5-fold when the univariate model was replaced by the RTSE model, and almost 8-fold when it was replaced by the RTSE model with PC1. Moreover, introducing the PC trigger indeed enhanced the ozone predictability. After the PC trigger was introduced in the RTSE model, the POD was increased 69.9%, and the FAR was reduced 8.3%. The overall correlation between the observed and simulated ozone was improved 9.6%. Also, the first principal component was more useful than the first two components in playing the "trigger" role, though it counted only for 58.62% of the environmental variance during the high ozone days.

Forecasting peak daily ozone levels: part 2--A regression with time series errors model having a principal component trigger to forecast 1999 and 2002 ozone levels.

A modified time series approach, a Box-Jenkins regression with time series errors (RTSE) model plus a principal component (PC) trigger, has been developed to forecast peak daily 1-hr ozone (O3) in real time at the University of Wisconsin-Milwaukee North (UWM-N) during 1999 and 2002. The PC trigger acts as a predictor variable in the RTSE model. It tries to answer the question: will the next day be a possible high O3 day? To answer this question, three PC trigger rules were developed: (1) Hi-Low Checklist, (2) Discriminant Function Approach I, and (3) Discriminant Function Approach II. Also, a pure RTSE model without including the PC trigger and a persistence approach were tested for comparison. The RTSE model with DFA I successfully forecast the only two 1-hr federal exceedances (124 ppb), one in 1999 and one in 2002. In terms of the O3 100-ppb exceedances, 60-80% of the incorrect forecasts occurred with incorrect PC decisions. A few others may have been caused by unexpected O3-weather relations. When the three approaches used UWM-N data to forecast a 100-ppb exceedance somewhere in the Milwaukee, WI, metropolitan area, their performance was dramatically improved: the false alarm rate was reduced from 0.89 to 0.44, and the probability of detection was increased from 0.71 to 0.88.

Forecasting peak daily ozone levels--I. A regression with time series errors model having a principal component trigger to fit 1991 ozone levels.

This research was motivated by the need to warn the population of Milwaukee, WI, on high-ozone days. A statistical model for the peak daily 1-hr ozone level is proposed. A Regression with Time Series Errors (RTSE) model, which includes a principal component (PC) trigger, is the basis for forecasting the peak daily 1-hr ozone level. The RTSE model, with a PC trigger, is first employed to estimate daily peak ozone measured at the University of Wisconsin, Milwaukee-North (UWM-N), during the 1991 ozone season. The RTSE model uses peak daily temperature, morning vector average wind direction, and the PC trigger as predictor variables. The PC trigger was designed to summarize atmospheric circumstances when peak ozone was greater than 100 parts per billion (ppb). It is verified that the RTSE model, with a PC trigger, significantly improves the prediction of peak daily ozone, particularly peak ozone greater than 100 ppb. In comparison with the RTSE model without the PC trigger, the RTSE model with a PC trigger raised the R2 from 0.680 to 0.809. It is suggested that the RTSE model, with the PC trigger, is an adequate statistical model that has the potential for real-time ozone forecasting.