There is a paucity of research on the branding of sacral landscapes as a regional strategy in tourism marketing. On the one hand, the concept of place branding, to date, has been transferred very ...little to sacred destinations, while on the other hand, religious content and modern tourist marketing barely fit together. Nonetheless, the perception of religion in a postmodern society opens up new opportunities for sacred places to reposition themselves in the competition faced by tourist destinations. The aim of this article is to show how German tourism regions with a religious focus build their brand. Through analyzing six case studies and distilling the extant literature, this study aims to investigate whether sacral messages really do have religious depth, or whether the sacral landscape is only used superficially to attract attention.
In this paper, we develop a new correlation for the clean-bed filter coefficient (λ0) for Brownian particles, for which diffusion is the main deposition mechanism. The correlation is based on ...numerical Lattice-Boltzmann (LB) simulations in random packings of spheres of uniform diameter. We use LB methods to solve the Navier−Stokes equation for flow and then the advection−diffusion equation for particle transport. We determine a correlation for an “equivalent” single-collector diffusion efficiency, η D , so that we can compare our predictions to “true” single-collector correlations stemming from unit-cell modeling approaches. We compared our new correlation to experiments on the filtration of latex particles. For small particle diameters, 50 nm < d p < 300 nm, when gravity and interception are negligible, our correlation for η D predicts measurements better than unit-cell correlations, which overestimate η D . The good agreement suggests that the representation of three-dimensional transport pathways in porous media plays an important role when modeling transport and deposition of Brownian particles. To model larger particles, for which gravity and interception are important too, we build a correlation for the overall single-collector efficiency η0 by adding corresponding η G and η I terms from unit-cell correlations to our η D model. The resulting correlation predicts experiments with latex particles of d p > 300 nm well.
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•Traffic-related air pollution (using NO2 as a surrogate) can trigger heart attacks.•It is not clear how soon after exposure a heart attack might occur.•We found that traffic-related ...pollution can trigger heart attacks within 6 h.•Risk was elevated at pollution concentrations below air quality standards.
Traffic-related air pollution can trigger myocardial infarction (MI). However, the hourly hazard period of exposure to nitrogen dioxide (NO2), a common traffic tracer, for incident MI has not been fully evaluated. Thus, the current hourly US national air quality standard (100 ppb) is based on limited hourly-level effect estimates, which may not adequately protect cardiovascular health.
We characterized the hourly hazard period of NO2 exposure for MI in New York state (NYS), USA, from 2000 to 2015.
For nine cities in NYS, we obtained data on MI hospitalizations from the NYS Department of Health Statewide Planning and Research Cooperative System and hourly NO2 concentrations from the US Environmental Protection Agency’s Air Quality System database. We used city-wide exposures and a case-crossover study design with distributed lag non-linear terms to assess the relationship between hourly NO2 concentrations over 24 h and MI, adjusting for hourly temperature and relative humidity.
The mean NO2 concentration was 23.2 ppb (standard deviation: 12.6 ppb). In the six hours preceding MI, we found linearly increased risk with increasing NO2 concentrations. At lag hour 0, a 10 ppb increase in NO2 was associated with 0.2 % increased risk of MI (Rate Ratio RR: 1.002; 95 % Confidence Interval CI: 1.000, 1.004). We estimated a cumulative RR of 1.015 (95 % CI: 1.008, 1.021) for all 24 lag hours per 10 ppb increase in NO2. Lag hours 2–3 had consistently elevated risk ratios in sensitivity analyses.
We found robust associations between hourly NO2 exposure and MI risk at concentrations far lower than current hourly NO2 national standards. Risk of MI was most elevated in the six hours after exposure, consistent with prior studies and experimental work evaluating physiologic responses after acute traffic exposure. Our findings suggest that current hourly standards may be insufficient to protect cardiovascular health.
Crowd-sourced traffic data potentially allow prediction of traffic-related air pollution at high temporal and spatial resolution.
To examine associations (1) of radar-based traffic measurements with ...congestion colors displayed on crowd-sourced traffic data maps and (2) of black carbon (BC) levels with radar and crowd-sourced traffic data.
At an off-ramp of an interstate and a small one-way street in a mixed-use area in New York City, we used radar devices to obtain vehicle speeds and flows (hourly counts) for cars and trucks. At these radar sites and at an additional non-radar equipped site at a 2-way street, we monitored BC levels using aethalometers in the summer and early fall of 2017. At all three sites, free-flow traffic conditions typically did not occur due to the nearby presence of traffic lights and forced turns. We also downloaded real-time traffic maps from a crowd-sourced traffic data provider and assigned an ordinal integer congestion color code CCC to the congestion colors, ranging from 1 (dark red) to 5 (gray).
CCC increased with vehicle speed. Traffic flow was highest for intermediate speeds and intermediate CCC. Regression analyses showed that BC levels increased with either segregated or total vehicle flows. At the off-ramp, time-dependent BC levels can be inferred from time-dependent CCC and radar-derived mean vehicle flow data. A unit decrease in CCC for a mean traffic flow of 100 vehicles/h was associated with a mean (95% CI) increase in BC levels of 0.023 (0.028, 0.018) μg/m3. At the small 1-way and the 2-way street, BC levels were also negatively associated with CCC, though at a >0.05 significance level.
Use of inexpensive crowd-sourced traffic data holds great promise in air pollution modeling and health studies. Time-dependent traffic-related primary air pollution levels may be inferred from radar-calibrated crowd-sourced traffic data, in our case radar-derived mean traffic flow and widely available CCC data. However, at some locations mean traffic flow data may already be available.
•Crowd-sourced traffic data can be calibrated by traffic-radar measurements•Traffic-related black carbon levels depend on traffic volume but may also depend on vehicle speed•Traffic-related black carbon levels can be associated with congestion colors displayed on crowd-sourced traffic maps•Use of inexpensive crowd-sourced traffic data holds great promise in air pollution modeling and health studies
We develop and analyze a novel, quasi-static, pore-scale approach for modeling drainage in a porous medium system. The approach uses: (1) a synthetic, non-overlapping packing of a set of spheres, (2) ...a discrete representation of the sphere packing, and (3) concepts from pore morphology and local pore-scale physics to simulate the drainage process. The grain-size distribution and porosity of two well-characterized porous media were used as input into the drainage simulator, and the simulated results showed good agreement with experimental observations. We further comment on the use of this simulator for determining the size of a representative elementary volume needed to characterize the drainage process.
•Stay-at-home orders decreased NO2 concentrations by 19% (3.2 ppb) in New York City.•Greatest decreases in NO2 were observed from 5 to 7 am and 6 to 7 pm.•Greater decreases in NO2 were found for ...non-roadside pollution monitors.•NO2 changes did not differ between weekends and weekdays.•We found weak evidence for variation in NO2 changes by monitor location.
Policy responses to the COVID-19 pandemic, such as the NY on Pause stay-at-home order (March 22 – June 8, 2020), substantially reduced traffic and traffic-related air pollution (TRAP) in New York City (NYC). We evaluated the magnitude of TRAP decreases and examined the role of modifying factors such as weekend/weekday, road proximity, location, and time-of-day.
Hourly nitrogen dioxide (NO2) concentrations from January 1, 2018 through June 8, 2020 were obtained from the Environmental Protection Agency's Air Quality System for all six hourly monitors in the NYC area. We used an interrupted time series design to determine the impact of NY on Pause on NO2 concentrations, using a mixed effects model with random intercepts for monitor location, adjusted for meteorology and long-term trends. We evaluated effect modification through stratification.
NO2 concentrations decreased during NY on Pause by 19% (-3.2 ppb, 95% confidence interval CI: -3.5, -3.0), on average, compared to pre-Pause time trends. We found no evidence for modification by weekend/weekday, but greater decreases in NO2 at non-roadside monitors and weak evidence for modification by location. For time-of-day, we found the largest decreases for 5 am (27%, -4.5 ppb, 95% CI: -5.7, -3.3) through 7 am (24%, -4.0 ppb, 95% CI: -5.2, -2.8), followed by 6 pm and 7 pm (22%, -3.7 ppb, 95% CI: -4.8, -2.6 and 22%, -4.8, -2.5, respectively), while the smallest decreases occurred at 11 pm and 1 am (both: 11%, -1.9 ppb, 95% CI: -3.1, -0.7).
NY on Pause's impact on TRAP varied greatly diurnally. Decreases during early morning and evening time periods are likely due to decreases in traffic. Our results may be useful for planning traffic policies that vary by time of day, such as congestion tolling policies.
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Pulp and paper waste water is one of the major sources of industrial water pollution. This study tested the suitability of ceramic tubular membrane technology as an alternative to conventional waste ...water treatment in the pulp and paper industry. In this context, in series batch and semi-batch membrane processes comprising microfiltration, ultrafiltration and nanofiltration, ceramic membranes were developed to reduce the chemical oxygen demand (COD) and remove residual lignin from the effluent flow during sulfite pulp production. A comparison of the ceramic membranes in terms of separation efficiency and performance revealed that the two-stage process configuration with microfiltration followed by ultrafiltration was most suitable for the efficient treatment of the alkaline bleaching effluent tested herein, reducing the COD concentration and residual lignin levels by more than 35% and 70%, respectively.
Gasoline contains large proportions of harmful chemicals, which can be released during vehicle refueling. Onboard Refueling Vapor Recovery (ORVR) can reduce these emissions, but there is limited ...research on the system's efficacy over time in an actual vehicle fleet. The aims of this study are: (1) determine the feasibility of using an infrared camera to view vapor emissions from refueling; (2) examine the magnitude of refueling-related emissions in an ORVR-saturated fleet, to determine need for an exposure-assessment.
Using an infrared camera optimized for optical gas imaging of volatile organic chemicals, refueling was recorded for 16 vehicles at six gas stations. Pumps were inspected for damage, refueling shut-off valve functioning, and presence of Stage II Vapor Recovery. Vehicle make/model and age were recorded or estimated.
Vapor emissions were observed for 14 of 16 vehicles at each station, with severity varying substantially by vehicle make/model and age. Use of an infrared camera allowed for identification of vapor sources and timing of release, and for visualizing vapor trajectories.
Notably emissions occurred not only at the beginning and end of refueling but also throughout, in contrast to a prior study which did not detect increases in atmospheric hydrocarbon levels mid-refueling. Future studies are vitally needed to determine the risk to individuals during typical refueling in an ORVR saturated vehicle fleet. We recommend comprehensive exposure-assessment including real-time monitoring of emitted volatile organic compounds paired with infrared gas-imaging and measurement of internal dose and health effects of gas station customers.
Motivation
Gas stations chronically release gasoline vapor to the environment that contains the carcinogen benzene. However, there is no method for estimating setbacks for a gas station depending on ...an acceptable excess cancer risk due to the benzene emissions, sales volume, benzene content of the emissions, and inhalation dose, without performing an air dispersion simulation for each scenario.
Methods
We developed a new modeling framework, in which only one air dispersion simulation is performed for a reference gas station. Then, a new scaling law is used to estimate cancer risks and setbacks for different gas station characteristics and exposure scenarios.
Results
Our new scaling law allows estimating cancer risk vs. distance as a function of an acceptable excess cancer risk, total benzene emission rate, and frequency of exposure. Setbacks can also be determined from this scaling law or graphically from a design chart. Calculated setbacks differ only slightly from those determined from air dispersion simulations. Different emission control technologies substantially affect calculated setbacks.
Conclusions
We developed a framework that allows policy makers to examine easily how setbacks depend on regulatable measures such as emission control and acceptable cancer risk as well as on exposure characteristics. The framework also allows incorporating a safety factor to account for increased emissions. While this study was conducted in the context of US gas stations, our framework can be applied world-wide.
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