Major Highways Research Articles

Accumulation of road salt in a calcareous fen: Kampoosa Bog, western Massachusetts.

Road salt poses a threat to the quality of soils and water resources. Wetlands located in salt contaminated areas are at risk of experiencing lower plant and animal species diversity. Therefore, it is critical to understand how modifications to salt application rates and hydrological events impact wetland water quality. Here, we use chloride mass flux, discharge, groundwater chloride concentration, meteorological, and salt application data from 2012-2020 to estimate chloride accumulation and outflux rates in the Kampoosa Bog subwatersheds, located in Stockbridge and Lee, Massachusetts, and bordered by major highways (Interstate-90 and U.S. Route 7). We also investigate the correlation between wetland size and chloride retention rate. During the 2018-2019 period, mean annual chloride application rates in the major watershed increased from 363000 kg/year (2012-2017) to 479000 kg/year. This led to a net chloride accumulation (KB100 subwatershed: 339000 kg; KB150 subwatershed: 188000 kg) and increased groundwater chloride concentrations in the fen. Chloride outflux from these subwatersheds was primarily driven by discharge. We found that the relationship between wetland percent cover and chloride retention is complex. Although the percent wetland cover is greater in the KB100 main wetland region compared to the KB150 subwatershed, high precipitation in 2018 resulted in similar chloride retention efficiencies (~26%). During the drier year (2019), chloride retention was higher in the wetland region due to its gentle slopes which promote water accumulation and consequently higher evaporation rates which lowers discharge and chloride outfluxes. The chloride steady-state concentration analysis also suggests that there is potential for chloride accumulation to continue because the watershed has not yet reached steady-state chloride concentrations. Without major modifications to salting practices, chloride concentrations will continue increasing and potentially promote the re-growth of invasives (Phragmites) and continued growth of salt tolerant species (Typha angustifolia/xglauca) that diminish plant diversity.

A novel modelling framework for real-time prediction of path travel times using both traffic and weather data

The problems of path travel time predictions have been studied over decades. Traditional approaches to this challenge have relied on different traffic data. However, in metropolitan cities with frequent rainfall, there is a need to consider the weather effects on real-time prediction of path travel times. Hence, this research integrates traffic data with weather data, including rainfall intensity data and weather forecast data to consider the temporal relationships between weather data and path travel times. The proposed modelling framework is evaluated with data from a major expressway and an urban arterial road in Hong Kong. Results unequivocally demonstrate that incorporating weather data significantly boosts prediction accuracy. This study also examines the impact of different frequencies on weather data, as well as weather forecast correctness, on prediction accuracy. Finally, the applicability of the proposed modelling framework has been verified without and with the input of ground truth on path travel times.

The Policy Potential of Monitoring Market Proximal Maritime Connectivity Over Time: The Case of Aotearoa New Zealand

AbstractA country’s maritime connectivity is integral to its international trade and regional economic growth. Advancements in technology and complex network theory have elevated maritime connectivity in regional transport policy agendas. This study introduces a novel conceptualisation of the maritime network called the market proximal network which better highlights connectivity concerns and opportunities that leverage a country’s current market position. By implementing a temporal view (using Time-Granularity Graphs) of the market proximal network, connectivity trends can be appreciated. The policy value of this approach is illustrated by the case of Aotearoa New Zealand, a maritime connectivity taker, between January 2018 and June 2021. Five maritime connectivity priorities are identified regarding the country’s gateways onto the major maritime highways. The potential policy value of the temporal view of the market proximal network is illustrated by identifying priorities that are actionable because they are based on the existing business cases that draw shipping companies to call in Aotearoa New Zealand.

Landscape Homogeneity May Drive the Distribution of Koala Vehicle Collisions on a Major Highway in the Clarke-Connors Range in Central Queensland, Australia

After the loss and fragmentation of habitat, vehicle collisions are one of the main threats to the long-term survival of wild koalas. Koala road strike data were analysed for a section of the Peak Downs Highway between Nebo and Spencer’s Gap, west of Mackay, Queensland, Australia. The analysis was carried out on 345 records (October 2014 to November 2023), and results suggested the spatial distribution of koala road strike followed a random pattern along this section of the highway, assuming a Poisson point pattern on a linear network. An analysis of the candidate predictors of koala vehicle collisions, including habitat and road variables, found that the amount of high-quality koala habitat (as defined by the local koalas’ tree species preference) present and the driver visibility were the only significant predictors. The relative homogeneity of landuse and vegetation across this landscape may mean that koalas do not concentrate at specific crossing points. More research, including detailed habitat mapping, is needed into this population, which currently lacks government and conservation attention, to inform mitigation efforts and reduce mortality rates for this potentially nationally significant population.

Mobile laboratory measurements of air pollutants in Baltimore, MD elucidate issues of environmental justice

ABSTRACT The City of Baltimore, MD has a history of problems with environmental justice (EJ), air pollution, and the urban heat island (UHI) effect. Current chemical transport models lack the resolution to simulate concentrations on the scale needed, about 100 m, to identify the neighborhoods with anomalously high air pollution levels. In this paper we introduce the capabilities of a mobile laboratory and an initial survey of several pollutants in Baltimore to identify which communities are exposed to disproportionate concentrations of air pollution and to which species. High concentrations of black carbon (BC) stood out at some locations – near major highways, downtown, and in the Curtis Bay neighborhood of Baltimore. Results from the mobile lab are confirmed with longer-term, low-cost monitoring. In Curtis Bay, higher concentrations of BC were measured along Pennington Ave. (mean [5th to 95th percentiles] = 2.08 [2.0–10.9] μg m−3) than along Curtis Ave. just ~ 150 m away (0.67[0.1 – 1.8] μg m−3). Other species, including criteria pollutants ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and fine particulate matter (PM2.5), showed little gradient. Observations with high spatial and temporal resolution help isolate the mechanisms leading to locally high pollutant concentrations. The difference in BC appears to result not from heavier truck traffic or slower dispersion but from the interruptions in traffic flow. Pennington Ave. has three stoplights while Curtis Ave. has none. As heavy-duty diesel-powered vehicles accelerate, they experience turbo-lag and the resulting rich air-fuel mixture exacerbates BC emissions. Immediate mediation might be achieved through smoother traffic flow, and the long-term solution through replacing heavy-duty trucks with electric vehicles. Implications: We present results documenting the locations within Baltimore of high concentrations of Black Carbon pollution and identify the likely source – diesel exhaust emissions exacerbated by stop-and-go traffic and associated turbo-lag. This suggests solutions (smoother traffic, retrofit particulate filters, replacement of diesel with electric vehicles) that would enhance Environmental Justice (EJ) and could be applied to other cities with EJ problems. Synopsis: This paper presents observations of atmospheric black carbon aerosol showing impacts on environmental justice, then identifies causes and suggests solutions.

Identification, mapping, and self-reported practice patterns of village doctors in Sitakunda subdistrict, Bangladesh.

Informally trained health care providers, such as village doctors in Bangladesh, are crucial in providing health care services to the rural poor in low- and middle-income countries. Despite being one of the primary vendors of antibiotics in rural Bangladesh, village doctors often have limited knowledge about appropriate antibiotic use, leading to varied and potentially inappropriate dispensing and treatment practices. In this study, we aimed to identify, map, and survey village doctors in the Sitakunda subdistrict of Bangladesh to understand their distribution, practice characteristics, clinical behaviours, access to technologies, and use of these technologies for clinical decision-making. Using a 'snowball' sampling method, we identified and mapped 411 village doctors, with 371 agreeing to complete a structured survey. The median distance between a residential household and the closest village doctor practice was 0.37 km, and over half of the practices (51.2%) were within 100 m of the major highway. Village doctors were predominately male (98.7%), with a median age of 39. After completing village doctor training, 39.4% had completed an internship, with a median of 15 years of practice experience. Village doctors reported seeing a median of 84 patients per week, including a median of five paediatric diarrhoea cases per week. They stocked a range of antibiotics, with ciprofloxacin and metronidazole being the most prescribed for diarrhoea. Most had access to phones with an internet connection and used online resources for clinical decision-making and guidance. The findings provide insights into the characteristics and practices of village doctors and point to the potential for internet and phone-based interventions to improve patient care and reduce inappropriate antibiotic use in this health care provider group.

Data-driven bottleneck detection on Tehran highways

In metropolitan areas, traffic congestion has become a prevalent challenge due to rapid urbanization and increased vehicle usage, adversely impacting mobility, productivity, and quality of life. Identifying and mitigating persistent traffic bottlenecks is crucial for developing efficient transportation systems and guiding infrastructure planning decisions. This research proposes an innovative data-driven methodology to pinpoint recurrent traffic bottlenecks in Tehran's extensive highway network, addressing the limitations of traditional traffic monitoring methods. Through data mining and image processing techniques applied to 16 months of traffic flow maps from Google Maps, diverse information is extracted, including traffic nodes, congestion hotspots, and locations with the longest queue lengths. The image processing approach involves color-based segmentation, pixel-level analysis, and machine learning algorithms to determine congestion levels across the highway network. The identified bottlenecks are validated against ground truth data from CCTV cameras, demonstrating a remarkable 92 % correlation for key identified points. The proposed approach leverages the power of advanced analytics to comprehensively analyze all major highways, including areas lacking CCTV infrastructure. The robust validation process reinforces the reliability of this data-driven solution in capturing real-world traffic dynamics. As urban mobility challenges escalate globally, the integration of diverse data sources and cutting-edge techniques will be instrumental in guiding intelligent transportation planning and policy decisions.

Spatiotemporal Changes in Air Pollution within the Studied Road Segment

Environmental protection is a pivotal element of sustainable development, both essential and indispensable in the construction of smart, green cities. Road transport contributes significantly to atmospheric pollution, accounting for as much as 25% of annual emissions within the European Union (EU). To combat the adverse effects of road transport, the EU has set targets to reduce greenhouse gas emissions from both passenger and commercial vehicles. Consequently, sustainable air pollution management has become a focal point for numerous researchers. This study continues the investigation into the distribution of air pollutants along a specific highway segment in Poland. The article addresses two primary research questions: first, the temporal and spatial variations in air pollution adjacent to a major highway in Poland, and second, whether emission levels exhibit significant annual differences and if there is a correlation between pollutant concentrations and the distance from the roadway. The findings offer valuable data on one of the principal substances polluting the air along EU transportation routes. Moreover, the analysis provides recommendations for future road infrastructure renovation projects and strategies to protect the public from harmful traffic-related pollutants, thereby supporting the development of green cities in accordance with sustainable development principles.

Reaction to at-home air purifiers installed to reduce traffic-related air pollution in near-highway residences

Background and aimTraffic-related ultrafine particle pollution near highways is associated with adverse health. Reducing exposure by use of portable air purifiers in homes is one approach to reducing this risk. However, the reaction of residents to having air purifiers in homes is not well studied.MethodsWithin the framework of our randomized crossover trial of air purifiers in homes near a major highway, we collected data about participants’ use and reactions to air purifiers using questionnaires at their 30-day and 90-day home visits, recorded electricity consumption using HOBO monitors, and conducted structured interviews with participants.ResultsNearly all 150 participants reported running the air purifiers virtually 24 h every day in both their living room and their bedroom in the prior month. The units’ HOBO electricity use, from a subset of 45 participants, supported the participants’ responses from the questionnaire. Approximately 80% of participants reported setting their air purifier on the medium setting. Tolerance to air purifier noise increased significantly between the 30-day and 90-day home visits, with approximately two thirds reporting not being bothered at all by the noise. The qualitative interviews in a subset of 26 participants yielded consistent responses to those from the questionnaires. Size of unit, airflow, and energy consumption were additional concerns that emerged during the interviews.ConclusionsResults from the questionnaires, HOBO data, and structured interviews all suggest participants had positive reactions towards the presence of in-home APs, and therefore may be receptive to using air purifiers in their homes on a regular basis.Trial registrationClinicalTrials.gov, NCT04279249. Registered 09 October 2019.

Mobile VOC measurements in Commerce City, CO reveal the emissions from different sources

ABSTRACT Source attribution of volatile organic compounds (VOCs) can be challenging in urban areas, which have many point sources. Mobile laboratories using time-of-flight mass spectrometers (TOF-MS) can take measurements throughout areas of concern, resulting in data with high spatial resolution that can be used to more easily identify these sources. However, emissions in heavily polluted areas still undergo significant mixing over short distances, making source attribution of some compounds challenging. Positive matrix factorization (PMF) has been widely used for attributing pollutants to different sources when taking stationary measurements due to its ability to process large amounts of data into generally interpretable results. However, some limitations of PMF can impact its usefulness to mobile data; PMF is a computationally intensive process, requires some user choices in attributing factors to emissions sources, and results can be significantly impacted by chemical transformations after emission. Here, both PMF and a simpler comparative analysis method are evaluated in analyzing measurements taken in the Elyria Swansea neighborhood of Commerce City, CO. This neighborhood is located near an oil refinery, a wastewater treatment plant, local industrial shops, and major highways. PMF failed to differentiate between oil refinery emissions and traffic emissions, and had difficulties recognizing other key sources. A simpler comparative analysis showed that the refinery contributed significantly to VOC concentrations throughout the neighborhood, including air toxics such as benzene. A wastewater treatment plant contributed to methanethiol and dimethyl sulfide. Finally, a small woodshop was identified as a hyperlocal VOC source, and contributed high amounts of some VOCs, such as toluene and other solvents, in its immediate surroundings. Implications: This work discusses mobile measurements of VOCs around Commerce City, CO, a heavily polluted urban area north of Denver, using a PTR-TOF-MS. Two different source attribution methods, positive matrix factorization (PMF) and comparative analysis, were evaluated in the context of mobile measurements. The results show that an oil refinery and a woodshop contributed greatly to many VOC concentrations in the Elyria Swansea residential area of Commerce City. Additional sources, such as a wastewater treatment plant, also contributed to some odorous VOCs. PMF was unable to fully describe sources based on the mobile data. Comparative analysis was useful in attributing more VOCs to different sources, but quantitative results were influenced by how the analysis is set up. These findings are relevant to the residents of Denver and regulatory bodies to better understand Denver air pollution, as well as to other mobile studies doing source attribution of VOCs.

Rail noise comparison of FTA methodology with CadnaA modeling at Bronx development site

For environmental studies, identifying road and rail noise is important in projecting potential impacts from increased operations and also in identifying the window/wall attenuation needed to reduce outdoor to indoor noise levels. The Federal Transit Administration's (FTA) transit noise and vibration impact assessment procedures provide spreadsheets for estimating noise levels at specific receptor points. However, computer models such as SoundPLAN and CadnaA are also available. Because these computer models have complex input requirements and account for local terrain, they are rarely used for large corridor studies, but they are well suited to smaller sites. This study compares the FTA procedures with CadnaA modeling at a development site in the Bronx, NY, that is bounded by multiple rail lines and is proximate to a major highway. Discussion of results presents the advantages and disadvantages of each approach and identifies the conditions under which each approach is most appropriate.

Effectiveness of speed cameras on the prevention of road traffic collisions and casualties in cameroon

Issues related to transport collision and casualties cannot be undermined as it has direct effect on human health and death, hence relevant policies are required to reduce road traffic accidents. To do this, our study has as objectives: to discuss the drivers of the used of speed cameras by drivers in Cameroon., investigate the effects of speed cameras on the prevention of road traffic collisions and casualties in Cameroon and to determine the actual problems faced by drivers in the use of speed Cameras in Cameroon. Methodologically, the study applied the probit technique to estimate the result via primary data. The sample size consisted of 200 drivers collected through a well-structured questionnaire and collect among the drivers plying the Yaoundé-Doula, Douala –Bafoussam and Bafousam-Yaoundé major highway. The key findings revealed that the factors influencing the drivers used of speed cameras are: main occupation, attainment of higher education, married, age, victim of traffic collision and casualties. The result also shows that Speed camera is highly corroborating with the prevention of road traffic collisions and casualties in Cameroon. Finally, the result shows that the lack of awareness, student speed change, inadequate signage, limited visibility, technical limitations and privacy concerns are the actual physical challenges of the use of speed camera in Cameroon. The study suggests that decision makers in the transport sector should multiply the provision of speed cameras. This is a wise step in the prevention of road traffic collisions and casualties in Cameroon and better labour market.

Risk Assessment in Landslide-Prone Terrain within a Complex Geological Setting at Kadugannawa, Sri Lanka: Implications for Highway Maintenance

The major highway in Sri Lanka that links the capital, Colombo, with the second capital, Kandy, passes through Kadugannawa, characterized by steep hills. The geological and geomorphological setting of the terrain often leads to slope failures. The objective of this study is to interpret the key factors influencing the slope failures that occurred in close proximity at two separate locations with two different slope conditions. Typical local and regional brittle and ductile structures include fault scarps, deep-seated detachments, and variable folding. According to our results, one of the studied locations experienced translational landslides because of weakened basement rock surfaces, hydrophilic clay minerals, and anthropogenic influences, whereas the other location experienced multiple stages of mass movement influenced by inhomogeneous colluvial soil and regional, geological, and hydrogeological conditions. Based on the present study, it can be concluded that geological studies must be carried out within the local area rather than at the regional scale. Otherwise, the constructions for the prevention of landslides in complicated geological settings will fail or may not be used for a long period. Moreover, consideration of future climate change is essential when undertaking construction in challenging terrains.

Safety Analysis of 6-Lane National Highway Using Reactive and Proactive Methods: A Case Study

Abstract Globally, traffic-related deaths were 1.35 million per year or nearly 3,700 per day. However, the severity of accidents Over a decade increased by 31.5%, with 37.3 people dying per 100 accidents in India. 4,12,432 accidents (approximately 422 people die daily) were reported in 2021, with 1,53,972 fatalities on Indian highways. National Highways’ safety performance is vital in developing countries such as India. This research paper focuses on the six-lane Jaipur Ring Road, an approximate 150-kilometer-long national highway surrounding the city of Jaipur, India. It is a crucial infrastructure project aimed at easing traffic congestion in and around Jaipur. Initiated in the early 2000s and completed in 2020, the road connects major highways and national highways, reducing traffic congestion and improving connectivity in and around the city. This paper explores the benefits of the Jaipur Ring Road, including improved travel time for commuters, transportation of goods, reduced accident causes, and economic development. Moreover, the article emphasizes the significance of monitoring road conditions to guarantee a secure, effective, and adaptive transportation system. This involves gathering information on road performance safety conditions and identifying areas that require enhancements. The paper highlights the role of trained professionals and community stakeholders in conducting road observations and ensuring that transportation infrastructure meets the needs of local communities. This case study presents some crucial observations made at specific locations on the Jaipur Ring Road. The study aims to analyze the traffic flow, identify potential bottlenecks, and propose solutions to improve the road’s efficiency and safety.

Site-specific traffic modelling and simulation for a major Italian highway based on weigh-in-motion systems accounting for gross vehicle weight limitations

The present-day road traffic with the persistent change in the type and volume of vehicles needs to be specifically investigated for effective safety management of aging highway infrastructures. Actual traffic data can be implemented in refined procedures for stochastic simulation of road infrastructure performance, structural health monitoring (SHM), definition of weight limits on highways, and traffic-informed structural safety checks. While weigh-in-motion (WIM) systems had been widely used in many countries, their installation on Italian highways was mostly discussed and carried out only after the catastrophic collapse of the Polcevera bridge in 2018. This study presents a statistical data analysis, probabilistic models, and a simulation procedure for highway traffic, based on measurements of two WIM systems located along European route E45 close to Naples, Italy. Different limitations to maximum gross vehicle weight (GVW) were enforced at the locations of the two WIM systems, according to the Italian road code and the Italian guidelines for risk classification, safety assessment and monitoring of existing bridges, respectively. WIM data sets were filtered to exclude erroneous traffic data and vehicle classes defined according to the number of axles and axle distance were statistically characterised, allowing the derivation of probabilistic models for all traffic parameters of interest. A simulation methodology to generate random traffic load from the WIM data is also presented for its possible use in probabilistic performance assessment and traffic informed SHM of road infrastructures such as bridges.

Predicting Land Cover Using a GIS-Based Markov Chain and Sea Level Inundation for a Coastal Area

New Hanover County, North Carolina, has been experiencing rapid population growth and is expected to continue this growth, leading to increased land use and development in the area. The county is also threatened by sea level rise (SLR) and its effects because of its coastal location and frequent occurrences of major storms and hurricanes. This study used a land change modeler to map the land cover change throughout the county over a period of 20 years, and predicted land cover distribution in the area in the years 2030 and 2050. Statistics revealed that the developed land in the area increased by 85 km2 between 2000 and 2010, and by 60 km2 between 2010 and 2020. Such land is predicted to increase by another 73 km2 by 2030, and 63 km2 by 2050. This increase in development is expected to occur mainly in the central area of the county and along the barrier islands. Modeling of SLR illustrated that the northwestern part of New Hanover County along the Cape Fear River, as well as the beach towns located on the barrier islands, are estimated be the most affected locations. Results indicate that sections of major highways throughout the county, including I-140 near downtown Wilmington and US-421 in Carolina Beach, may be inundated by SLR, which might delay residents during mandatory evacuations for emergency situations such as hurricanes. Some routes may be unusable, leading to traffic congestion on other routes, which may impede some residents from reaching safety before the emergency. Wrightsville Beach and Carolina Beach are estimated to have the highest levels of inundation, with 71.17% and 40.58% of their land being inundated under the most extreme SLR scenario of 3 m, respectively. The use of the present research approach may provide a practical, quick, and low-cost method in modeling rapidly growing urban areas along the eastern United States coastline and locating areas at potential risk of future SLR inundation.

Complex genetic landscape revealed by a population in the eastern Tianshan Mountains of Xinjiang between the 8th and 11th centuries CE

AbstractThe eastern Tianshan Mountain (ETS) region in Xinjiang, China, has played a crucial role as a major highway for large‐scale human migrations and technological exchanges across Eurasia throughout history. Understanding the genetic makeup of past populations holds significant importance in comprehending human mobility in this region. Here, we report genome‐wide ancient DNA for the two individuals whose origins remain uncertain, found at the Dahe ancient city site in the ETS region. Our results indicate that although both individuals display a higher genetic affinity to Asian populations, one individual shows some genetic sharing with South Asians, while the other shares more affinity with populations from Northeastern Asia. Radiocarbon dating shows that the two human remains were not deposited simultaneously. Overall, the combined genetic, physical anthropology and radiocarbon evidence strongly suggests that the ETS region, situated at the heart of the Silk Road, has been a crossroads of diverse populations coexisting between the 8th and 11th centuries. Additionally, the genetic ancestry sharing with the Bronze Age Tarim mummies suggested a long‐term residual of indigenous ancestry in Xinjiang and showed that autochthonous deep Asian ancestry had left their genetic legacy into the historical populations of Xinjiang despite a spanning of over three millennia.

Genetic analysis of harvest samples reveals population structure in a highly mobile generalist carnivore.

Delineating wildlife population boundaries is important for effective population monitoring and management. The bobcat (Lynx rufus) is a highly mobile generalist carnivore that is ecologically and economically important. We sampled 1225 bobcats harvested in South Dakota, USA (2014-2019), of which 878 were retained to assess genetic diversity and infer population genetic structure using 17 microsatellite loci. We assigned individuals to genetic clusters (K) using spatial and nonspatial Bayesian clustering algorithms and quantified differentiation (F ST and ) among clusters. We found support for population genetic structure at K = 2 and K = 4, with pairwise F ST and values indicating weak to moderate differentiation, respectively, among clusters. For K = 2, eastern and western clusters aligned closely with historical bobcat management units and were consistent with a longitudinal suture zone for bobcats previously identified in the Great Plains. We did not observe patterns of population genetic structure aligning with major rivers or highways. Genetic divergence observed at K = 4 aligned roughly with ecoregion breaks and may be associated with environmental gradients, but additional sampling with more precise locational data may be necessary to validate these patterns. Our findings reveal that cryptic population structure may occur in highly mobile and broadly distributed generalist carnivores, highlighting the importance of considering population structure when establishing population monitoring programs or harvest regulations. Our study further demonstrates that for elusive furbearers, harvest can provide an efficient, broad-scale sampling approach for genetic population assessments.

Weather event characterization: a catalyst for improved spatial mapping and benefit quantification in winter road maintenance

Monitoring winter road surface conditions (RSC) is essential for optimizing winter road maintenance operations and ensuring public traffic safety and mobility. However, many existing RSC estimation methods focus primarily on local or site-specific conditions, thus lacking effectiveness in comprehensive spatial mapping under varying winter weather events. Additionally, the potential financial benefits these methods could provide to maintenance authorities remain largely unexplored. This study addresses these gaps by introducing a refined methodology that harnesses the K-Means algorithm to characterize various weather events – a significant stride towards improving the generalizability and accuracy of road surface temperature (RST) estimations. The study also incorporates regression kriging (RK), a renowned geostatistical technique, as an integral component of a system for constructing an extensive spatial map of RSC across large highway networks. This strategy maximizes the use of data from existing road weather information systems (RWIS) to bridge their large spatial gaps. This study further quantifies the potential savings derived from optimally placing RWIS stations and reducing traffic collisions. The efficacy of these methods is validated through a real-world case study on two major interstate highways in Iowa, US, with RST estimation discrepancies as low as 0.619 °C. The findings also indicate potential cost savings by conserving up to 10 RWIS stations, which can be further translated into monetary savings of RWIS capital costs, traffic collisions prevention, enhanced traffic mobility and savings in maintenance material usage.

Critical Environmental Injustice: A Case Study Approach to Understanding Disproportionate Exposure to Toxic Emissions.

Public health research and environmental health research, specifically, have focused on toxic exposure-encompassing individuals or communities that are disproportionately exposed to contaminants that are harmful or potentially harmful to them. Yet, little research has applied critical environmental justice theory-characterized by the idea that marginalized communities need to be treated as indispensable rather than disposable-to the study of toxic exposure. To fill this gap, the current paper offers a case study approach applying critical environmental justice theory to the study of disproportionate and unequal exposure to toxic contaminants. This case study is of Kettleman City, a rural, unincorporated community in the heart of California's Central Valley (USA). This community experiences the co-location of environmental hazards, including residing at the intersection of two major highways and hosting a class I hazardous-waste landfill, which is one of the few licensed to accept PCBs. PCBs are a contaminant that has been linked with several adverse health outcomes, including cancers and low birthweight. Residents may also experience poor air quality from proximity to the highways. This case highlights the uneven distribution of pollution and environmental degradation that may be shouldered by the community, along with their experiences of adverse health and social impacts. This analysis reveals the importance of incorporating a critical environmental justice perspective to unpack experiences of not only disproportionate exposure but also disproportionate procedural and recognitional inequality. This research highlights the untapped potential of environmental justice to catalyze exposure science in challenging the unequal distribution of contaminants.