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Aviation emissions from landing and takeoff operations (LTO) can degrade local and regional air quality leading to adverse health outcomes in populations near airports and downwind. In this study we aim to quantify the air quality and health-related impacts from commercial LTO emissions in the continental U.S. for two recent years’ inventories, 2011 and 2016. We quantify the LTO-attributable PM2.5, O3, and NO2 concentrations and health outcomes for mortality and multiple morbidity health endpoints. We also quantify the impacts from two scenarios representing a nation-wide implementation of 5% or 50% blends of sustainable alternative jet fuels. We estimate 80 (68–93) and 88 (75–100) PM2.5-attributable and 610 (310–920) and 1,100 (570–1,700) NO2-attributable premature mortalities in 2011 and 2016, respectively. We estimate a net decrease of 28 (14–56) and 54 (27–110) in O3-attributable premature mortalities across the U.S. in 2011 and 2016, respectively due to the large O3 titration effects near the airports. We also find that the asthma exacerbations due to NO2 exposures from LTO emissions increase from 100,000 (2,500–200,000) in 2011 to 170,000 (4,400–340,000) in 2016. Implementing a 5% or 50% blend of sustainable alternative jet fuel in 2016 results in a 1% or 18% reduction, respectively in PM2.5-attributable premature mortalities. Monetizing the value of avoided total premature mortalities, we find that a 50%-blended sustainable alternative jet fuel results in a 19% decrease in PM2.5 damages per ton of fuel burned and a 2% decrease in total damages per ton of fuel burned as compared to damages from traditional jet fuel. We also quantify health impacts by state and find California to be the most impacted by LTO emissions. We find that LTO-attributable PM2.5 and NO2 premature mortalities increase by 10% and 80%, respectively from 2011 to 2016 and that NO2-attributable premature mortalities are responsible for 91% of total LTO-attributable premature mortalities in both 2011 and 2016. And since we find LTO-attributable NO2 to be unaffected by the implementation of sustainable alternative jet fuels, additional approaches focused on NOX reductions in the combustor are needed to mitigate the air quality-related health impacts from LTO emissions.

Tax compliance can be affected by many factors such as magnitude of compliance cost, the extent of penalty, perceived fairness of the tax system, awareness level of taxpayers and perceptions of government spending. The purpose of the study is identifying factors that affect compliance of individual income taxpayers in Bangladesh. The target population of the study is individual income taxpayers of the fifteen zones of Dhaka. The sample size is determined to 385 self-assessment assesse and 376 general procedure return submitted income taxpayers to which the questionnaire was distributed during the period of 1st December 2019 to 15th February, 2020. The results of the ordered logistic regression model reveal that the fairness, tax penalty and relationship with regard to taxpayer’s perception of government spending have positive and significant relationships with compliance. It also examines the effects of compliance decisions of referrals on others compliance decisions. The findings show a negative but insignificant relationship between them which implies that individual income taxpayer’s make their compliance decisions independent of others' decisions. Finally, the study having evaluated the effect of cost of complying with the tax law on tax compliance and concluded that there is a negative relationship between them implying that higher cost of compliance will lead to lower levels of compliance. Therefore, this paper suggests that maintaining tax fairness, optimum levels of penalty, spending the tax revenue on public development projects, keeping tax rates to the minimum as much as possible and keeping compliance costs to the minimum can enhance the compliance of taxpayers.

AIMS: Metformin may have clinical benefits in dialysis patients; however, its safety in this population is unknown. This systematic review evaluated the safety of metformin in dialysis patients. METHODS: MEDLINE, Embase, CENTRAL, PsycINFO and the Cochrane Library were searched for randomised controlled trials and observational studies evaluating metformin use in dialysis patients. Three authors reviewed the studies and extracted data. The primary outcomes were mortality, occurrence of lactic acidosis and myocardial infarction (MI) in patients taking metformin during dialysis treatment for ≥12 months (long term). Risk of bias was assessed using Risk Of Bias In Nonrandomised Studies of Interventions (ROBINS-1). Overall quality of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation (GRADE). RESULTS: Fifteen observational studies were eligible; 7 were prospective observational studies and 8 were case reports/case series. No randomised controlled trials were identified. The 7 prospective observational studies (n = 194) reported on cautious metformin use in patients undergoing maintenance dialysis. Only 3 provided long-term follow-up data. In 2 long-term studies of metformin therapy (≤1000 mg/d) in patients undergoing peritoneal dialysis (PD), 1 reported 6 deaths (6/83; 7%) due to major cardiovascular events (3 MI) and the other reported no deaths (0/35). One long-term study of metformin therapy (250 mg to 500 mg thrice weekly) in patients undergoing haemodialysis reported 4 deaths (4/61; 7%) due to major cardiovascular events (2 MI). These findings provide very low-quality evidence as they come from small observational studies. CONCLUSION: The evidence regarding the safety of metformin in people undergoing dialysis is inconclusive. Appropriately designed randomised controlled trials are needed to resolve this uncertainty.

The aerosol direct feedback effects (ADFEs) are neglected in traditional air quality modeling studies (where meteorology is used as input and not affected by the chemistry and aerosol microphysics) for estimating the impacts of aircraft emissions on air quality. In this study, aircraft landing and take-off (LTO) attributable change of O3 and PM2.5 concentrations through ADFEs for the year 2005 within the contiguous United States (CONUS) are quantified by a coupled meteorology-chemistry modeling system: Weather Research and Forecasting – Community Multi-scale Air Quality (WRF-CMAQ) model. We first quantified the effects of ADFEs of all aerosols within the CONUS (not the effects of aircraft LTO emissions) on surface meteorology and air quality and found that ADFEs changed on average the downward short-wave radiation (SWR), 2-m temperature (T2), planetary boundary layer (PBL) height, O3 and PM2.5 by −7.38 W/m2, −0.47 K, −20.72 m, −0.41 ppb and +0.28 μg/m3 in 2005. We also found a seasonal influence where ADFE-influenced change (decrease) of SWR, T2, PBL, O3 and change (increase) of PM2.5 were higher in summer than in winter. We found that the aircraft LTO emissions’ contribution to domain average surface concentration of O3 and PM2.5 were +0.0065 ppb and +0.0022 μg/m3 respectively when ADFEs are accounted for. The ADFEs decrease aircraft LTO attributable surface O3 and PM2.5 change by 21% and 23% respectively comparing with that without ADFE in 2005. We also found that in both without-and-with ADFE cases, the aircraft LTO emissions increases domain average of O3 from April to October and decreases from November to March showing a strong seasonal pattern. Our modeling study revealed that use of a coupled model with ADFE shows localized changes in air quality by aircraft LTO emissions across the domain which were masked when looking at domain averages for both O3 and PM2.5, and which may be important for accurately quantifying health risk due to air pollution exposures in densely populated areas.

Impactful academic research plays a stellar role in society, pressing to ask the question of how one measures the impact created by different areas of academic research. Measuring the societal, cultural, economic and scientific impact of research is currently the priority of the National Science Foundation, European Commission and several research funding agencies. The recently concluded United Kingdom’s national research quality exercise, the Research Excellence Framework (REF) 2014, which piloted impact assessment as part of the overall evaluation offers a lens to view how impact of research in different disciplines can be measured. Overall research quality was assessed through quality of outputs, ‘impact’ and research environment. We performed two studies using the REF 2014 as a case study. The first study on 363 Impact Case Studies (ICSs) submitted in 5 research areas (UoAs) reveals that, in general, the impact scores were constructed upon a combination of factors i.e. quantity of quartile-one (Q1) publications, quantity and value of grants/income, number of researchers stated in the ICSs, spin-offs created, discoveries/patents and presentation of esteem data, informing researchers/ academics of the factors to consider in order to achieve a better impact score in research impact assessments. However, there were differences among disciplines in terms of the role played by the factors in achieving their overall scores for the ICSs. The outcome of this study is thus a set of impact indicators, and their relationship with the overall score of impact of research in different disciplines as determined in REF2014, which would in the first instance provide some answers to impact measures that would be useful for researchers in different disciplines. The second study extracts the general themes of impact reported by universities by performing a word frequency analysis in all the ICSs submitted in the five chosen research areas, which were substantially varied owing to their fields.

Aviation emission of gas phase pollutants and particulate matter contribute to global radiative forcing and regional air quality degradation near airports. It is important to understand the formation and time evolution of these pollutants inside aircraft engines to design strategies for emission reduction. A physics and chemistry based zero-dimensional (0D) gas parcel model with detailed jet fuel chemistry and soot microphysics has been developed to predict the time evolution, formation history, and emission index (EI) of key combustion gases and size-resolved soot particles of an aircraft engine. The model was applied to a CFM56-2-C1 aircraft engine for idle operating condition, for which comprehensive measured data from the Aircraft Particle Emissions eXperiment (APEX) campaign are available. The measured EI data of four major pollutants, including CO, NOx (NO + NO 2 ), total hydrocarbon (HC) mass, and soot mass, were used to optimize the model parameters. The model predicts the time evolution of concentration of CO, NOx, HC, soot size distribution, CO 2 , H 2 O, SO 2 , NO, NO 2 , HONO, HNO 3 , SO 3 , H 2 SO 4 , O 2 , H, H 2 , O, OH, HO 2 , H 2 O 2 , and some HC species in the combustor and turbine. Reasonable agreement was found between the simulations and the measurements. It was found for idle operating condition that, for most of the combustion products, concentrations did not change significantly in the turbine and nozzle, however, HONO, H 2 SO 4 , and HO 2 concentrations did change by more than a factor of 10, while NOx, NO, NO 2 , O, OH, soot particle mass and soot particle number by less than a factor of 2. The developed model is computationally efficient and can be used to, study detailed chemical and microphysical processes during combustion, investigate the effects of different fuel compositions and operating conditions on aircraft emissions, and assist air quality study near aircraft emission sources.

The growth of iron particles by thermal decomposition of Fe(CO)5 in a tubular reactor was analyzed by using a one dimensional discrete-sectional model with the coalescence by sintering of neighboring particles incorporated in. A thermal decomposition of Fe(CO)5 vapor to produce iron particles was carried out at reactor temperatures varying from 300 to 1,000°C, and the effect of reactor temperature on particle size was compared with model prediction. The prediction exhibited good agreement with experimental observation that the primary particle size of iron was the largest at an intermediate temperature of 800°C. Model prediction was also compared with Giesen et al.’s [1] experimental data on iron particle production from Fe(CO)5. Good agreement was shown in primary particle size, but a considerable deviation was observed in primary particle size distribution. The deviation may be due to an inadequate understanding of the sintering mechanism for the particles within an agglomerate and to the assumption of an ideal plug flow in model reactor in contrast to the non-ideal dispersive flow in actual reactor.

A one-dimensional discrete-sectional model has been developed to simulate particle growth in aerosol reactors. Two sets of differential equations for volume and surface area, respectively, were solved simultaneously to determine the size distributions of agglomerates and primary particles. The surface area equations were derived in such a way that the coagulation integrals calculated for the volume equations could be used for the surface area equations as well, which is new in this model. The model was applied to a production of TiO2 particles by oxidation of titanium tetrachloride. Model predictions were compared with experimental data and those of a two-dimensional sectional model. Good agreement was shown in calculated particle size distributions between the present model and the two-dimensional model, which is more rigorous but demands a large amount of computer time and memory. Compared to experimental data, the primary particle size calculated by the model was more sensitive to the variation of reactor temperature.