An Investigation into the Impact of Rainfall on Freeway Traffic Flow

The purpose of this research effort was to investigate the impact of rainfall, at varying levels of intensity, on freeway capacity and operating speeds. Findings were derived from traffic and weather data collected in the Hampton Roads region of Virginia. Light rain (0.01 to 0.25 inches per hour) decreases freeway capacity by 4 to 10 percent. Heavy rain (0.25 inches per hour or greater) decreases freeway capacity by 25 to 30 percent. The presence of rain, regardless of intensity, results in approximately a 3 to 5 percent average decrease in operating speed. The findings indicated that the impact of rain is more significant than currently reported in the Highway Capacity Manual.

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Investigating the Impact of Rainfall on Travel Speed

Jurnal Teknologi ◽

10.11113/jt.v71.3756 ◽

2014 ◽

Vol 71 (3) ◽

Cited By ~ 1

Author(s):

Nordiana Mashros ◽

Johnnie Ben-Edigbe ◽

Hashim Mohammed Alhassan ◽

Sitti Asmah Hassan

Keyword(s):

Empirical Studies ◽

Heavy Rain ◽

Weather Conditions ◽

Travel Speed ◽

Operating Conditions ◽

Speed Reduction ◽

Light Rain ◽

Rainfall Condition ◽

Adverse Weather ◽

The Impact

The road network is particularly susceptible to adverse weather with a range of impacts when different weather conditions are experienced. Adverse weather often leads to decreases in traffic speed and subsequently affects the service levels. The paper is aimed at investigating the impact of rainfall on travel speed and quantifying the extent to which travel speed reduction occurs. Empirical studies were conducted on principle road in Terengganu and Johor, respectively for three months. Traffic data were collected by way of automatic traffic counter and rainfall data from the nearest raingauge station were supplied by the Department of Irrigation and Drainage supplemented by local survey data. These data were filtered to obtain traffic flow information for both dry and wet operating conditions and then were analyzed to see the effect of rainfall on percentile speeds. The results indicated that travel speed at 15th, 50th and 85th percentiles decrease with increasing rainfall intensities. It was observed that allpercentile speeds decreased from a minimum of 1% during light rain to a maximum of 14% during heavy rain. Based on the hypothesis that travel speed differ significantly between dry and rainfall condition; the study found substantial changes in percentile speeds and concluded that rainfalls irrespective of their intensities have significant impact on the travel speed.

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Effects of Rain on Freeway Traffic in Southern California

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2616-08 ◽

2017 ◽

Vol 2616 (1) ◽

pp. 69-80 ◽

Cited By ~ 3

Author(s):

Sawanpreet Singh Dhaliwal ◽

Xinkai Wu ◽

John Thai ◽

Xudong Jia

Keyword(s):

Los Angeles ◽

Traffic Management ◽

Southern California ◽

Management Strategies ◽

Heavy Rain ◽

Flow Speed ◽

Free Flow ◽

Light Rain ◽

Free Flow Speed ◽

The Impact

A number of studies in the past quantified the effect of rain on traffic parameters but were limited to wet areas. This research expands the literature by studying the effect of rain in a dry area such as Southern California and considering regional differences in the impact. Traffic data (loop detectors) and precipitation data (rain gauges) from the Los Angeles, California, metropolitan area were analyzed to access the effect of rain on traffic stream parameters such as free-flow speed, speed at capacity, and capacity. Rainfall events were categorized as light, medium, and heavy as discussed in the 2010 Highway Capacity Manual. Density plots and fundamental diagrams for rain types proved that free-flow speed, speed at capacity, and capacity were reduced by 5.7%, 6.91%, and 8.65%, respectively, for light rain; 11.71%, 12.34%, and 17.4%, respectively, for medium rain; and 10.22%, 11.85%, and 15.34%, respectively, for heavy rain. The reductions for free-flow speed were lower, whereas for speed at capacity and for capacity, they were higher than those reported in the 2010 manual. Moreover, headway increased during rain; this finding shows cautious driving behavior. Multiplicative weather adjustment factors were computed to compensate for the loss of speed and capacity. Also demonstrated was the spatial and temporal effect of rain on traffic. Downstream traffic was not much affected by a rainfall event, whereas the upstream traffic was negatively affected. This study is expected to support weather-responsive traffic management strategies for dry areas.

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Estimation of Rain Intensity Spectra over the Continental United States Using Ground Radar–Gauge Measurements

Journal of Climate ◽

10.1175/jcli-d-11-00151.1 ◽

2012 ◽

Vol 25 (6) ◽

pp. 1901-1915 ◽

Cited By ~ 21

Author(s):

Xin Lin ◽

Arthur Y. Hou

Keyword(s):

United States ◽

Heavy Rain ◽

Rain Intensity ◽

Light Rain ◽

Geographical Variations ◽

Satellite Sensors ◽

Rain Events ◽

Rain Rates ◽

The Impact ◽

Microwave Sensors

Abstract A high-resolution surface rainfall product is used to estimate rain characteristics over the continental United States as a function of rain intensity. By defining data at 4-km horizontal resolutions and 1-h temporal resolutions as an individual precipitating or nonprecipitating sample, statistics of rain occurrence and rain volume including their geographical and seasonal variations are documented. Quantitative estimations are also conducted to evaluate the impact of missing light rain events due to satellite sensors’ detection capabilities. It is found that statistics of rain characteristics have large seasonal and geographical variations across the continental United States. Although heavy rain events (>10 mm h−1) only occupy 2.6% of total rain occurrence, they may contribute to 27% of total rain volume. Light rain events (<1.0 mm h−1), occurring much more frequently (65%) than heavy rain events, can also make important contributions (15%) to the total rain volume. For minimum detectable rain rates setting at 0.5 and 0.2 mm h−1, which are close to sensitivities of the current and future spaceborne precipitation radars, there are about 43% and 11% of total rain occurrence below these thresholds, and they respectively represent 7% and 0.8% of total rain volume. For passive microwave sensors with their rain pixel sizes ranging from 14 to 16 km and the minimum detectable rain rates around 1 mm h−1, the missed light rain events may account for 70% of rain occurrence and 16% of rain volume. Statistics of rain characteristics are also examined on domains with different temporal and spatial resolutions. Current issues in estimates of rain characteristics from satellite measurements and model outputs are discussed.

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Microphysical Characteristics of Rainfall Observed by a 2DVD Disdrometer during Different Seasons in Beijing, China

Remote Sensing ◽

10.3390/rs13122303 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2303

Author(s):

Li Luo ◽

Jia Guo ◽

Haonan Chen ◽

Meilin Yang ◽

Mingxuan Chen ◽

...

Keyword(s):

Rain Rate ◽

Heavy Rain ◽

Occurrence Frequency ◽

Total Rainfall ◽

Axis Ratio ◽

Seasonal Differences ◽

Mean Values ◽

Light Rain ◽

Beijing China ◽

Maximum Occurrence

The seasonal variations of raindrop size distribution (DSD) and rainfall are investigated using three-year (2016–2018) observations from a two-dimensional video disdrometer (2DVD) located at a suburban station (40.13°N, 116.62°E, ~30 m AMSL) in Beijing, China. The annual distribution of rainfall presents a unimodal distribution with a peak in summer with total rainfall of 966.6 mm, followed by fall. Rain rate (R), mass-weighted mean diameter (Dm), and raindrop concentration (Nt) are stratified into six regimes to study their seasonal variation and relative rainfall contribution to the total seasonal rainfall. Heavy drizzle/light rain (R2: 0.2~2.5 mm h−1) has the maximum occurrence frequency throughout the year, while the total rainfall in summer is primarily from heavy rain (R4: 10~50 mm h−1). The rainfall for all seasons is contributed primarily from small raindrops (Dm2: 1.0~2.0 mm). The distribution of occurrence frequency of Nt and the relative rainfall contribution exhibit similar behavior during four seasons with Nt of 10~1000 m−3 registering the maximum occurrence and rainfall contributions. Rainfall in Beijing is dominated by stratiform rain (SR) throughout the year. There is no convective rainfall (CR) in winter, i.e., it occurs most often during summer. DSD of SR has minor seasonal differences, but varies significantly in CR. The mean values of log10Nw (Nw: mm−1m−3, the generalized intercept parameter) and Dm of CR indicate that the CR during spring and fall in Beijing is neither continental nor maritime, at the same time, the CR in summer is close to the maritime-like cluster. The radar reflectivity (Z) and rain rate (?) relationship (Z = ?R?) showed seasonal differences, but were close to the standard NEXRAD Z-R relationship in summer. The shape of raindrops observed from 2DVD was more spherical than the shape obtained from previous experiments, and the effect of different axis ratio relations on polarimetric radar measurements was investigated through T-matrix-based scattering simulations.

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Proposal to Refine Solar Radiation of Typical Meteorological Year Database and Evaluation on the Influence of Air-Conditioning Load

Atmosphere ◽

10.3390/atmos12040524 ◽

2021 ◽

Vol 12 (4) ◽

pp. 524

Author(s):

Jihui Yuan ◽

Kazuo Emura ◽

Craig Farnham

Keyword(s):

Solar Radiation ◽

Air Conditioning ◽

Energy Savings ◽

Energy Resource ◽

Global Solar Radiation ◽

Resource Assessment ◽

Weather Data ◽

Diffuse Solar Radiation ◽

Chinese Standard ◽

The Impact

The Typical meteorological year (TMY) database is often used to calculate air-conditioning loads, and it directly affects the building energy savings design. Among four kinds of TMY databases in China—including Chinese Typical Year Weather (CTYW), International Weather for Energy Calculations (IWEC), Solar Wind Energy Resource Assessment (SWERA) and Chinese Standard Weather Data (CSWD)—only CSWD is measures solar radiation, and it is most used in China. However, the solar radiation of CSWD is a measured daily value, and its hourly value is separated by models. It is found that the cloud ratio (diffuse solar radiation divided by global solar radiation) of CSWD is not realistic in months of May, June and July while compared to the other sets of TMY databases. In order to obtain a more accurate cloud ratio of CSWD for air-conditioning load calculation, this study aims to propose a method of refining the cloud ratio of CSWD in Shanghai, China, using observed solar radiation and the Perez model which is a separation model of high accuracy. In addition, the impact of cloud ratio on air-conditioning load has also been discussed in this paper. It is shown that the cloud ratio can yield a significant impact on the air conditioning load.

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Blood Donations and Transfusions during the COVID-19 Pandemic in Spain: Impact According to Autonomous Communities and Hospitals

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18073480 ◽

2021 ◽

Vol 18 (7) ◽

pp. 3480

Author(s):

José Antonio García-Erce ◽

Íñigo Romón-Alonso ◽

Carlos Jericó ◽

José María Domingo-Morera ◽

José Luis Arroyo-Rodríguez ◽

...

Keyword(s):

Blood Cells ◽

Blood Components ◽

Health Ministry ◽

State Of Emergency ◽

Blood Donations ◽

Autonomous Communities ◽

Packed Red Blood Cells ◽

Average Decrease ◽

A Prospective Study ◽

The Impact

Worldwide, the COVID-19 pandemic has caused a decline in blood donations, between 30% and 70% in some of the most affected countries. In Spain, during the initial eight weeks after the State of Emergency was decreed on 14 March 2020, in the weekly reports of the Health Ministry, an average decrease of 20% was observed between 11 and week 25 compared with the 2018 donation. We aimed to investigate the impact of the COVID-19 pandemic on blood donations and blood distribution in four autonomous communities, and to explore the evolution of the consumption of blood components (BCs) in ten hospitals of six autonomous communities. We performed a prospective study of grouped cohorts on the donation and distribution of blood in four regional transfusion centers in four autonomous communities in Spain, and a retrospective study of the consumption of blood components in ten hospitals in six autonomous communities. Regarding donations, there was no significant decrease in donations, with differences between autonomous communities, which started between 1 and 15 March 2020 (−11%). The increase in donations in phase II (from 26 May 2020) stands out. Regarding consumption, there was a significant reduction in the consumption of packed red blood cells (RBCs) (24.5%), plasma (45.3%), and platelets (25.3%) in the central period (16 March–10 May). The reduction in the consumption of RBCs was significant in the period from 1–15 March. Conclusions: The COVID-19 pandemic has affected the donation and consumption of BCs.

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Impact of Extreme Weather on Healthcare Utilization by People with HIV in Metropolitan Miami

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18052442 ◽

2021 ◽

Vol 18 (5) ◽

pp. 2442

Author(s):

Daniel Samano ◽

Shubhayu Saha ◽

Taylor Corbin Kot ◽

JoNell E. Potter ◽

Lunthita M. Duthely

Keyword(s):

Relative Risk ◽

The United States ◽

Extreme Weather ◽

South Florida ◽

Heat Index ◽

Extreme Weather Events ◽

Weather Data ◽

Steady Increase ◽

Daily Weather Data ◽

The Impact

Extreme weather events (EWE) are expected to increase as climate change intensifies, leaving coastal regions exposed to higher risks. South Florida has the highest HIV infection rate in the United States, and disruptions in clinic utilization due to extreme weather conditions could affect adherence to treatment and increase community transmission. The objective of this study was to identify the association between EWE and HIV-clinic attendance rates at a large academic medical system serving the Miami-Dade communities. The following methods were utilized: (1) Extreme heat index (EHI) and extreme precipitation (EP) were identified using daily observations from 1990–2019 that were collected at the Miami International Airport weather station located 3.6 miles from the studied HIV clinics. Data on hurricanes, coastal storms and flooding were collected from the National Oceanic and Atmospheric Administration Storms Database (NOAA) for Miami-Dade County. (2) An all-HIV clinic registry identified scheduled daily visits during the study period (hurricane seasons from 2017–2019). (3) Daily weather data were linked to the all-HIV clinic registry, where patients’ ‘no-show’ status was the variable of interest. (4) A time-stratified, case crossover model was used to estimate the relative risk of no-show on days with a high heat index, precipitation, and/or an extreme natural event. A total of 26,444 scheduled visits were analyzed during the 383-day study period. A steady increase in the relative risk of ‘no-show’ was observed in successive categories, with a 14% increase observed on days when the heat index was extreme compared to days with a relatively low EHI, 13% on days with EP compared to days with no EP, and 10% higher on days with a reported extreme weather event compared to days without such incident. This study represents a novel approach to improving local understanding of the impacts of EWE on the HIV-population’s utilization of healthcare, particularly when the frequency and intensity of EWE is expected to increase and disproportionately affect vulnerable populations. More studies are needed to understand the impact of EWE on routine outpatient settings.

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The interplay between environmental exposures and COVID-19 risks in the health of children

Environmental Health ◽

10.1186/s12940-021-00716-z ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Peter D. Sly ◽

Brittany A. Trottier ◽

Catherine M. Bulka ◽

Stephania A. Cormier ◽

Julius Fobil ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Disease Severity ◽

Research Effort ◽

Severe Disease ◽

Environmental Exposures ◽

Research Strategy ◽

Lessons Learned ◽

Research Questions ◽

The Impact

Abstract Background An unusual feature of SARS-Cov-2 infection and the COVID-19 pandemic is that children are less severely affected than adults. This is especially paradoxical given the epidemiological links between poor air quality and increased COVID-19 severity in adults and that children are generally more vulnerable than adults to the adverse consequences of air pollution. Objectives To identify gaps in knowledge about the factors that protect children from severe SARS-Cov-2 infection even in the face of air pollution, and to develop a transdisciplinary research strategy to address these gaps. Methods An international group of researchers interested in children’s environmental health was invited to identify knowledge gaps and to develop research questions to close these gaps. Discussion Key research questions identified include: what are the effects of SAR-Cov-2 infection during pregnancy on the developing fetus and child; what is the impact of age at infection and genetic susceptibility on disease severity; why do some children with COVID-19 infection develop toxic shock and Kawasaki-like symptoms; what are the impacts of toxic environmental exposures including poor air quality, chemical and metal exposures on innate immunity, especially in the respiratory epithelium; what is the possible role of a “dirty” environment in conveying protection – an example of the “hygiene hypothesis”; and what are the long term health effects of SARS-Cov-2 infection in early life. Conclusion A concerted research effort by a multidisciplinary team of scientists is needed to understand the links between environmental exposures, especially air pollution and COVID-19. We call for specific research funding to encourage basic and clinical research to understand if/why exposure to environmental factors is associated with more severe disease, why children appear to be protected, and how innate immune responses may be involved. Lessons learned about SARS-Cov-2 infection in our children will help us to understand and reduce disease severity in adults, the opposite of the usual scenario.

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Field survey on frost damage to roof tiles under climatic conditions

Structural Survey ◽

10.1108/ss-07-2015-0033 ◽

2016 ◽

Vol 34 (2) ◽

pp. 135-149 ◽

Cited By ~ 4

Author(s):

Chiemi Iba ◽

Ayumi Ueda ◽

Shuichi Hokoi

Keyword(s):

Field Survey ◽

Winter Season ◽

Frost Damage ◽

Climatic Conditions ◽

Weather Data ◽

Measured Temperature ◽

Content Type ◽

Roof Tile ◽

Deterioration Process ◽

The Impact

Purpose – Frost damage is well-known as the main cause of roof tile deterioration. The purpose of this paper is to develop an analytical model for predicting the deterioration process under certain climatic conditions. This paper describes the results of a field survey conducted to acquire fundamental information useful to this aim. Design/methodology/approach – A field survey of roof tile damage by freezing was conducted in an old temple precinct in Kyoto, Japan. Using detailed observations and photographic recordings, the damage progress was clarified. To examine the impact of climatic conditions upon the damage characteristics, weather data and roof tile temperatures were measured and logged in the winter season. Findings – The deterioration process was observed under the climatic conditions associated with the measured temperature of the roof tiles. In particular, it was revealed that the orientation has a significant influence on increasing or decreasing the risk of frost damage. For certain distinctive forms of damage, the deterioration mechanisms were estimated from the viewpoint of the moisture flow and temperature distribution in the tile. Originality/value – This study contributes to the elucidation of the mechanism behind frost damage to roof tiles. The findings will guide the construction of a numerical model for frost damage prediction.

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Modeling Mine Workforce Fatigue: Finding Leading Indicators of Fatigue in Operational Data Sets

Minerals ◽

10.3390/min11060621 ◽

2021 ◽

Vol 11 (6) ◽

pp. 621

Author(s):

Elaheh Talebi ◽

W. Pratt Rogers ◽

Tyler Morgan ◽

Frank A. Drews

Keyword(s):

Health And Safety ◽

Time Of Day ◽

Weather Data ◽

Data Sets ◽

Leading Indicators ◽

Safety Control ◽

Model Complex ◽

Fatigue Monitoring ◽

The Impact ◽

Operational Data

Mine workers operate heavy equipment while experiencing varying psychological and physiological impacts caused by fatigue. These impacts vary in scope and severity across operators and unique mine operations. Previous studies show the impact of fatigue on individuals, raising substantial concerns about the safety of operation. Unfortunately, while data exist to illustrate the risks, the mechanisms and complex pattern of contributors to fatigue are not understood sufficiently, illustrating the need for new methods to model and manage the severity of fatigue’s impact on performance and safety. Modern technology and computational intelligence can provide tools to improve practitioners’ understanding of workforce fatigue. Many mines have invested in fatigue monitoring technology (PERCLOS, EEG caps, etc.) as a part of their health and safety control system. Unfortunately, these systems provide “lagging indicators” of fatigue and, in many instances, only provide fatigue alerts too late in the worker fatigue cycle. Thus, the following question arises: can other operational technology systems provide leading indicators that managers and front-line supervisors can use to help their operators to cope with fatigue levels? This paper explores common data sets available at most modern mines and how these operational data sets can be used to model fatigue. The available data sets include operational, health and safety, equipment health, fatigue monitoring and weather data. A machine learning (ML) algorithm is presented as a tool to process and model complex issues such as fatigue. Thus, ML is used in this study to identify potential leading indicators that can help management to make better decisions. Initial findings confirm existing knowledge tying fatigue to time of day and hours worked. These are the first generation of models and future models will be forthcoming.

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