Local Pollution Sources Research Articles

Hydrodynamic modelling of a polluted tropical bay: Assessment of anthropogenic impacts on freshwater runoff and estuarine water renewal

A bay's capacity to buffer fluvial fluxes between the land and sea is sensitive to hydrological changes that can affect its water renewal rates. In Cartagena Bay, Colombia, pollution issues have been associated with freshwater fluxes which are projected to increase in future years. This has led to plans to reduce freshwater flows by constructing upstream hydraulic doors. Given the influence of freshwater discharge on coastal water renewal, it is important to assess how these upstream changes will affect the bay's hydrodynamic processes. This study calibrated the 3D MOHID Water model, configured with a high-resolution mixed vertical discretization to capture the bay's characteristic processes of vertical stratification and mixing. A Lagrangian transport model was used to analyze the flow of passive particle tracers and calculate water renewal time scales. Mean residence times of 3–6 days and flushing times of 10–20 days for canal water were found, while mean residence times of 23–33 days and flushing times of 70–99 days were calculated for the bay's complete water volume. An assessment of future scenarios showed that increases in freshwater runoff would result in faster water renewal in the bay, while plans to decrease freshwater discharge would result in slower water renewal in the bay. It is therefore imperative that any plans for reducing fluvial fluxes into the bay be accompanied by the control of local pollution sources, which are abundant and could worsen the bay's water quality issues should water renewal times become longer.

Within-City Spatial Variations in Multiple Measures of PM2.5 Oxidative Potential in Toronto, Canada.

Few studies have characterized within-city spatial variations in the oxidative potential of fine particulate air pollution (PM2.5). In this study, we evaluated multiple measures of PM2.5 oxidative potential across Toronto, Canada (2016-2017), including glutathione/ascorbate-related oxidative potential (OPGSH and OPAA) and dithiothreitol depletion (OPDTT). Integrated 2-week samples were collected from 67 sites in summer and 42 sites in winter. Multivariable linear models were developed to predict OP based on various land use/traffic factors, and PM2.5 metals and black carbon were also examined. All three measures of PM2.5 oxidative potential varied substantially across Toronto. OPAA and OPDTT were primarily associated with traffic-related components of PM2.5 (i.e., Fe, Cu, and black carbon) whereas OPGSH was not a strong marker for traffic during either season. During summer, multivariable models performed best for OPAA ( RCV2 = 0.48) followed by OPDTT ( RCV2 = 0.32) and OPGSH ( RCV2 = 0.22). During winter, model performance was best for OPDTT ( RCV2 = 0.55) followed by OPGSH ( RCV2 = 0.50) and OPAA ( RCV2 = 0.23). Model parameters varied between seasons, and between-season differences in PM2.5 mass concentrations were weakly/moderately correlated with seasonal differences in OP. Our findings highlight substantial within-city variations in PM2.5 oxidative potential. More detailed information is needed on local sources of air pollution to improve model performance.

A hybrid modeling framework to estimate pollutant concentrations and exposures in near road environments

Traffic related air pollution is one of the major local sources of pollution challenging most urban populations. Current air quality modeling approaches can estimate the concentrations of air pollutants on either regional or local scales but cannot effectively estimate concentrations from the combination of regional and local sources at both local and regional scales simultaneously. This study describes a hybrid modeling framework, HYCAMR, combining a regional model, CAMx, and a local-scale dispersion model, R-LINE, to estimate concentrations of both primary and secondary species at high temporal (hourly) and spatial (40 m) resolution. HYCAMR utilizes all the chemical and physical processes available in CAMx and the Particulate Matter Source Apportionment Technology (PSAT) tool to estimate concentrations from both onroad and nonroad emission sources. HYCAMR employs R-LINE, to estimate the normalized dispersion of pollutant mass from onroad emission sources, from primary and secondary roads, at high resolution. Applying R-LINE for one day per month using average daily meteorology yields seasonally-resolved spatial dispersion profiles at low computational cost. Combining the R-LINE spatial dispersion profile with CAMx concentration estimates yields an estimate of the combined concentrations for a range of pollutants at high spatial and temporal resolution. In three major cities in Connecticut, HYCAMR shows strong temporal and seasonal variability in NOx, PM2.5, and elemental carbon (EC) concentrations. This study evaluates HYCAMR year 2011 estimates of NO2 and PM2.5 against two sources: satellite-based estimates at coarse resolution and regression model estimates at census block group resolution. In this evaluation, HYCAMR demonstrates improved agreement with the land-use regression modeling and mixed agreement with satellite-based estimates when compared to the regional CAMx estimates.

Improved Environmental Status: 50 Years of Declining Fish Mercury Levels in Boreal and Subarctic Fennoscandia.

Temporally (1965-2015) and spatially (55°-70°N) extensive records of total mercury (Hg) in freshwater fish showed consistent declines in boreal and subarctic Fennoscandia. The database contains 54 560 fish entries ( n: pike > perch ≫ brown trout > roach ≈ Arctic charr) from 3132 lakes across Sweden, Finland, Norway, and Russian Murmansk area. 74% of the lakes did not meet the 0.5 ppm limit to protect human health. However, after 2000 only 25% of the lakes exceeded this level, indicating improved environmental status. In lakes where local pollution sources were identified, pike and perch Hg concentrations were significantly higher between 1965 and 1990 compared to values after 1995, likely an effect of implemented reduction measures. In lakes where Hg originated from long-range transboundary air pollution (LRTAP), consistent Hg declines (3-7‰ per year) were found for perch and pike in both boreal and subarctic Fennoscandia, suggesting common environmental controls. Hg in perch and pike in LRTAP lakes showed minimal declines with latitude, suggesting that drivers affected by temperature, such as growth dilution, counteracted Hg loading and food web exposure. We recommend that future fish Hg monitoring sampling design should include repeated sampling and collection of pollution history, water chemistry, fish age, and stable isotopes to enable evaluation of emission reduction policies.

Prediction of local particle pollution level based on artificial neural network

Citizens eager to know the local pollution level to prevent from air pollution. The real-time measurement for everywhere is a very expensive way, a statistical model based on artificial neural network is applied in this research. This model can estimate particle pollution level with some influencing factors, including background pollution level, weather conditions, urban morphology and local pollution sources. The monitoring from regulatory monitoring sites is considered as the background level. The field measurements of 20 locations are conducted to feed the output layer of ANN model. The average relative error of prediction compared with measurement is 9.24% for PM10 and 18.90% for PM2.5.

Meteorology influencing springtime air quality, pollution transport, and visibility in Korea

In an environment with many local, remote, persistent, and episodic sources of pollution, meteorology is the primary factor that drives periods of unhealthy air quality and reduced visibility. The 2016 Korea-United States Air Quality (KORUS-AQ) field study provides a unique opportunity to examine the impact of meteorology on the relative influence of local and transboundary pollution. Much of the KORUS-AQ campaign can be grouped into four distinct research periods based on observed synoptic meteorology, including a period of complex aerosol vertical profiles driven by dynamic meteorology, stagnation under a persistent anticyclone, low-level transport and haze development, and a blocking pattern. These episodes are examined using a diverse archive of ground, airborne, and satellite data. While frontal boundaries are recognized as the primary mechanism driving pollution transport in eastern Asia, results show that they are not always related to sustained periods of hazardous air quality and reduced visibility at the surface. Significant long-range transport of pollution and dust was constrained to a few short events, suggesting that the majority of pollutants sampled during KORUS-AQ originated from local sources. A severe regional pollution episode is examined in detail, featuring dense haze and significant secondary particle formation within a shallow moist boundary layer. Observations during KORUS-AQ also highlight a rapid, 40 ppbv increase in ozone pollution as a strong sea breeze front traversed the Seoul Metropolitan Area. Representativeness of meteorology and pollution conditions measured by KORUS-AQ is considered by comparison with climatology. This analysis is an essential step toward improved local and regional forecasting of air quality and visibility.

Differential Probability Functions for Investigating Long-term Changes in Local and Regional Air Pollution Sources

ABSTRACT Conditional probability functions are commonly used for source identification purposes in air pollution studies. CBPF (conditional bivariate probability function) categorizes the probability of high concentrations being observed at a location by wind direction/speed and investigate the directionality of local sources. PSCF (potential source contribution function), a trajectory-ensemble method, identifies the source regions most likely to be associated with high measured concentrations. However, these techniques do not allow the direct identification of areas where changes in emissions have occurred. This study presents an extension of conditional probability methods in which the differences between conditional probability values for temporally different sets of data can be used to explore changes in emissions from source locations. The differential CBPF and differential PSCF were tested using a long-term series of air quality data (12 years; 2005/2016) collected in Rochester, NY. The probability functions were computed for each of 4 periods that represent known changes in emissions. Correlation analyses were also performed on the results to find pollutants undergoing similar changes in local and regional sources. The differential probability functions permitted the identification of major changes in local and regional emission location. In Rochester, changes in local air pollution were related to the shutdown of a large coal power plant (SO2) and to the abatement measures applied to road and off-road traffic (primary pollutants). The concurrent effects of these changes in local emissions were also linked to reduced concentrations of nucleation mode particles. Changes in regional source areas were related to the decreases in secondary inorganic aerosol and organic carbon. The differential probabilities for sulfate, nitrate, and organic aerosol were consistent with differences in the available National Emission Inventory annual emission values. Changes in the source areas of black carbon and PM2.5 mass concentrations were highly correlated.

Экологический мониторинг малых водных систем: алгоритм, программный комплекс, результаты применения к бассейну реки Уж (Украина)

A systematic approach to environmental monitoring of small water systems and its optimization is proposed. For simplify the storage of large amounts of information, accelerate the obtaining of preliminary conclusions of water resources condition, predict the dynamics of both individual indicators and their system attributes, and develop a user-friendly interface, which is tied to the area. To carry out the research, samples of water were taken near the corresponding sections of industrial enterprises of Korosten region, as well as discharges of a storm water system. Based on the standard approach, with the help of physicochemical methods of analysis practically all the hydrochemical parameters in the studied water body were determined. The obtained results were compared with the regulatory guidelines. For systematization and maintenance of environmental monitoring, a software package has been developed, which has been tested on the results of the instrumental laboratory analysis of surface water quality of the river Uzh. The software package is developed to establish local sources of pollution, monitor potentially dangerous man-made objects, and better manage of water resources. A user-friendly interface has been developed, which is tied to the area and is easily adapted to other monitoring objects. Thanks to the developed software package, the implementation of an integrated approach to the collection and analysis of monitoring data is carried out quickly, efficiently and conveniently. The developed approach allows easy adaptation to the objects of the research and does not require significant capital investment.

Комплексная оценка водопользования российской части бассейна озера Байкал на основе геоинформационной технологии

The advantages of the basin approach in the study of regional water use are justified in the article, water management areas according to the water management division of the Russian Federation were used as territorial units of the study. A universal methodic for the integrated assessment of the region’s water management activities was developed, based on geo/information technology. Stages of the study are described, including water management of the area, ranking based on the total anthropogenic load on water bodies and river basins, zoning of the territory to optimize the target use of water resources. The GIS of water use of the Lake Baikal basin is developed on the basis of governmental statistics, mass media examples of organization of water management data, as well as the results of automated mapping of water bodies. The results of water management regionalization are presented and spatial regularities of water use organization in the investigated territory are revealed. The ranking of river basins and water bodies according to the degree of anthropogenic load has been carried out, ecological problems of the region have been identified and their spatial localization has been fixed, the exact locations of pollution sources and their influence on water management have been established. Zoning of the territory under study for targeted use of water resources was proposed, five unique zones were identified, differentiated according to the special conditions for the formation of water resources and the specific use of water bodies, as well as the nature and intensity of the current and forecasted water use. A set of measures to optimize water use within the zones of targeted use of water resources is proposed.

Danube sediment contamination with polychlorinated biphenyls: New interpretation of sediment quality assessment

Among the contaminants of greatest concern, it is still possible to detect in aquatic systems "old" classics such as polychlorinated biphenyls (PCBs). Since PCBs are detected in all environmental matrices and have been identified as harmful substances due to their toxicity, persistence, and bioaccumulation in humans and wildlife, they are still one of the important groups of POPs. For this reason, this original approach studies the toxicological influence of PCBs, quantified in sediment samples collected at ten sites along the river Danube, by an application of advanced classification and clustering methods such as hierarchical cluster analysis (HCA) and Kohonen's self-organising maps (SOMs). Selected multivariate techniques were applied to the monitoring dataset in order to obtain visual images of the components distributed at each sampling site when all components are included in the classification and data projection procedure. After analyzing the data set using both techniques were isolated groups that exhibit similar behavior. In the hexagon and dendogram of variables three main clusters were distinguished. Towards the identification of pollutant spatial patterns, the SOM did not isolate a clear phenomenon probably due to the absence of local pollution sources contributing to the elevated concentrations of these compounds. The presented assumptions indicated that the supplemental application of SOM and HCA offers advantageous features over the usually rough interpretation of PCBs pattern and over the single use of the methods.

Identifying Leading Nodes of PM2.5 Monitoring Network in Taiwan with Big Data-oriented Social Network Analysis

ABSTRACT TEPA (Taiwan Environmental Protection Administration) currently has regulated six types of air pollutants based on the AQI. Among these, the three items most prone to exceeding the standard are PM2.5, PM10, and O3, in that order. PM2.5 pollution episodes in Taiwan mainly occur in winter and spring when the northeast monsoon prevails. In addition to local pollution sources, transboundary air pollution affects Taiwan. Obviously, the existing AQ monitoring data analyzed by the BD-oriented perspective not only simplifies the simulation calculation and verification resources of the AQ model but also assists in real-time insight into the causal relationships between the AQ and important parameters of meteorology, pollution sources, and regions. This study integrates the BD-oriented Social Network Analysis (SNA) approach and data visualization tools to analyze the event co-occurrence and spatial correlation characteristics of two pollution scenarios for AQ monitoring stations based on two severe PM2.5 pollution conditions: (1) the Z-value of PM2.5 daily average concentration is higher than 1.65 (Scenario I), and (2) the daily average concentration of PM2.5 exceeds TEPA’s regulation on the AQ standard (Scenario II), to identify the regional leading nodes suitable for different pollution scenarios. Furthermore, Principal Component Analysis (PCA) and time series data are employed to verify the spatial-temporal representation of these leading nodes, which can be regarded as means to the real-time AQ management decision-making as well as instant transboundary pollution precaution in the future. This study contributes to the application of the discrete data-driven approach (SNA) and the continuous data-driven approach (PCA) in an ambient AQ monitoring network, which can clearly explain and analyze the regional high pollution characteristics of PM2.5 in Scenarios I and II. The results of this study are consistent with previously relevant findings in Taiwan.

Differences in foliar endophyte communities of red alder (Alnus rubra) exposed to varying air pollutant levels

In the Pacific Northwest, Alnus rubra Bong. (red alder) is a common deciduous tree species especially prevalent in riparian corridors and disturbed sites, including metropolitan areas undergoing land use changes and development. Importantly, red alder is also considered a bioindicator for ozone pollution and, like all plants, harbors a diverse endophyte community that may interact with aerial pollutants. In this study, we surveyed foliar fungal endophyte communities (microfungi) in red alder leaves from the metropolitan area of Portland, Oregon, USA, using culture-based techniques, and found that communities differed significantly by site. Our results suggest that the fungal endophyte community composition in red alder leaves may be influenced in part by local air pollution sources, likely in conjunction with other site characteristics. As urban areas expand, more studies should focus on how the urban environment affects plant–microbe community ecology and endophyte–host interactions, as well as on the long-term consequences for other ecosystem processes such as leaf litter decomposition.

The application of 0–1 mixed integer nonlinear programming optimization model based on a surrogate model to identify the groundwater pollution source

The optimization model is presently used for the identification of pollution sources and it is based on non-linear programming optimization. The decision variables in this model are continuous, resulting in a weak recognition of integer variables including pollution source location. In addition, as the number of pollution sources increase, so the calculated load increases exponentially and accuracy decreases. Compared with previous studies, this study makes a series of improvements by adopting a 0–1 mixed integer nonlinear programming optimization model to enable the simultaneous identification of both location (integer variable) and the release intensity (continuous variable) of the pollution source. One of the constraints in the optimization model is a simulation component which requires thousands of calls during the calculation process and therefore requires considerable computational load. To avoid this problem, the Kriging surrogate model is established in this study to reduce computational load, while at the same time ensuring the accuracy of the simulation results. The identification result is solved using a genetic algorithm (GA) and represents the real location of the pollution source, while release intensities are close to actual ones with small relative errors. The Kriging surrogate model is based on a 0–1 mixed integer nonlinear programming optimization model and can simultaneously identify both the location and the release intensity of the pollution source with a high degree of accuracy and by using short computational times.

Transboundary and traffic influences on air pollution across two Caribbean islands

Exposure to ambient air pollution has been linked to adverse health outcomes ranging from asthma to premature mortality. However, little to no information exists on the exposure of residents and visitors in the Caribbean islands. While a few previous studies have quantified levels of PM10 (particulate matter <10 μm) from Sahara dust in Trinidad, our study focussed on a local source of air pollution, traffic emissions. Mass concentrations of black carbon (BC) and PM2.5 (PM <2.5 μm) were measured at ten locations across the islands of Trinidad and Tobago over a three-week period. PM2.5 concentrations were observed to be heavily influenced by air masses showing origins from the Sahara Desert (31%), North America (26%) and Atlantic Ocean (42%), which resulted in similar average concentrations between the two islands. Average concentrations of BC were five times higher in Trinidad than Tobago (2.0 vs 0.43 μg/m3). In addition, BC in Trinidad was three times higher near than away from major roads (2.21 vs. 0.72 μg/m3), with concentrations reaching levels comparable to those near highways in large Metropolitan cities. The elevated BC concentrations observed in this study suggests that significant exposure to diesel exhaust is occurring in Trinidad, with significant contributions from traffic.

A CFD modelling study of reactive pollutant dispersion in an urban street canyon

This study numerically explores the diffusion rules of pollutants in an idealized urban street canyon where photochemical reactions are present in the neighbourhood. The airborne pollutants dispersion and reaction in street canyons are further investigated in this study. There is a relatively tense traffic pollutants release in urban neighborhoods, including nitrogen oxides and hydrocarbons. Photochemical reaction occurs at strong solar radiation, forming photochemical smog and other environment issues. We selected typical O3 + NO→O2 + NO2 reactions. Effects of the pollutant source location on pollutant dispersion and reaction are also investigated. Numerical simulations were conducted on chemically activity reactive air nitrogen oxides in urban street canyons with W (street canyon wide)/H (building height) = 1. Provided three different locations from the line source street canyon bottom exhaust nitric oxide diffusion and react with ozone in the free stream. The chemical reaction has a significant impact on the concentration of pollutants in the valley volume.

Street-Level Air Pollution, Health Disparities, and Advocacy

Recent mobile monitoring and high density distributed network campaigns have provided unprecedented insight into intra-neighborhood air pollution variability in Oakland, CA. A study examining these data in relation to health records found that elderly residents with higher levels of traffic-related pollution in the immediate vicinity of their homes had elevated cardiovascular risks. West Oakland Environmental Indicators Project, a local environmental justice organization, in partnership with Environmental Defense Fund, a large environmental non-profit, is leading efforts to use these findings to influence community, city, and state level efforts to address harmful air pollution. Several important learnings have emerged from our work to date. First, community residents with experiential understanding of local air pollution sources are key partners in interpreting hyperlocal pollution data. Community partners are also the most credible and trusted communicators of data to local residents, and the most effective advocates for local policy change. Second, messaging around air pollution-related health impacts and inequities at the street and block level can be particularly effective in engaging a broad range of stakeholders. Findings must be communicated in clear and compelling terms, and &amp;#8220;scientific interpreters&amp;#8221; can help accurately represent scientific findings in suitable language and formats. Finally, efforts to translate study results to action require long-term commitment and follow-through &amp;#8211; preliminary data and findings should be shared with community partners as early as possible and ongoing support and collaboration must continue long after research is completed. These elements: trust-based partnerships with local advocates, effective communication, and long-term engagement, require substantial investment of resources beyond those required to conduct traditional research, but are core to enabling translation of hyperlocal air pollution data to action.

Application of macroalgae analysis to assess the natural variability in selected pollution concentrations (N and Hg), and to detect sources of it in coastal environments

Here we present a new method in which algae are used to detect sources of heavy metal and organic pollution in coastal areas. The procedure involves characterization of the natural range of concentrations of the elements in areas not affected by local sources of pollution and subsequent comparison of concentrations in the study site to these natural range levels. To develop the method, the concentrations of various elements were determined in specimens of the macroalgae Fucus vesiculosus collected at >150 sampling sites along the shoreline. The natural variability in the element concentrations in these zones was established by determining the differences in the tissue concentrations of the elements between pairs of samples separated by different distances. The method was then tested in the surroundings of possible sources of nitrogen and was found to be a tool for detecting sources of small scale nitrogen contamination and for monitoring and evaluating water quality.

Characteristics, source apportionment and contribution of VOCs to ozone formation in Wuhan, Central China

Based on the detailed data of volatile organic compounds (VOCs) with 102 components measured continuously from September 2016 to August 2017 in Wuhan, the pollution characteristics, source apportionment, chemical reactivity and contribution to O3 formation were analysed. The results revealed that the annual average concentration of total VOCs (TVOCs) was 34.65 ppbv. Alkanes were the species with the largest concentration, which accounted for 45.88% of TVOCs, and propane, ethane and ethene were the most abundant components. Diagnostic ratios (toluene/benzene, typical VOC species/acetylene) showed that vehicle exhaust emissions had significant effects on VOCs. Eight major sources were identified by positive matrix factorization (PMF), which included vehicular exhaust (24.42%), industrial sources (16.43%), coal burning (14.18%), solvent usage in painting/coating (13.48%), liquefied petroleum gas (LPG) usage (12.57%), fuel evaporation (11.34%), biomass burning (5.11%) and biogenic sources (2.47%). In addition, industrial sources, vehicle exhaust and LPG usage were the main sources that significantly aggravated VOC pollution in Wuhan. Potential source contribution function (PSCF) results showed that local pollution sources were the main sources influencing VOC pollution in Wuhan. The results of Empirical Kinetic Modelling Approach (EKMA) showed that Wuhan belongs to a VOC limited area. Finally, the results of the OH radical loss rate (LOH) and ozone formation potential (OFP) showed that alkenes were the species with the largest amount of chemical activity, in which the highest OH radical loss rate was 42.56%. Simultaneously, alkenes contributed the most to O3 formation, which accounted for 48.34%. The results can provide references for local governments regarding control strategies of VOCs and O3 pollution.

Presence of Oil Mineral Aggregates (OMAs) in Surface Sediments from Mexico’s Exclusive Economic Zone, NW Gulf of Mexico

We assessed the presence and distribution of oil mineral aggregates (OMAs) in surficial sediments of Mexican waters in the NW Gulf of Mexico, their potential sources and their correlation with polycyclic aromatic hydrocarbons (PAH). In summer of 2010, OMAs were detected in three shallow sites. In winter of 2011, OMAs were observed in ten sites, two of them in the northernmost area at > 1500m depth. These particles were possibly advected from the north Gulf and Mississippi area following the deep-water currents of the zone. The OMAs from shallower sites may reflect local pollution sources. PAHs displayed low concentrations in both surveys (from 0.01 to 0.7 µgg-1 in summer, and from 0.01 to 0.51µgg-1 in winter), and showed rather a local origin. The expansion of the oil and port industry in the region is accountable for most of the OMAs detected.

The impacts of viaduct settings and street aspect ratios on personal intake fraction in three-dimensional urban-like geometries

High vehicular pollutants exposure to residents in near-road buildings raises special concerns in micro-scale urban science, as it causes severe health problems for those residents. This paper integrates a new parameter, i.e. personal intake fraction (IF_p), into computational fluid dynamics (CFD) simulations to investigate the flow and the resulted personal exposure of two-phase pollutants (CO and particular matters) in three-dimensional (3D) urban-like models. The impacts of street aspect ratios (building height/street width H/W = 0.5–1.5), viaduct settings, noise barriers and pollutant source locations were considered.3D downward helical flows exist in the secondary streets perpendicular to the parallel approaching wind, which produces lateral pollutant transport across the interface between the main street and secondary streets. Therefore, the overall average IF_p (<IF_p>) of CO (∼0.23–0.59 ppm) in our current 3D urban models (H/W = 1) is much smaller than that in two-dimensional (2D) street canyon (∼3.25–5.21 ppm) models. Although narrower 2D street canyons usually present greater <IF_p>, our current 3D urban models do not show this monotone decreasing trend due to the complicated flow structures. <IF_p> of fine particles are always smaller than that of CO. Furthermore, if a single pollutant source is placed on the viaduct, <IF_p> become much smaller than that in cases with a single ground-level source. If the source location changes to the upstream secondary street, <IF_p> significantly decreases due to stronger local wind. Finally, <IF_p> of leeward-side cases usually exceeds that of windward-side cases by several times, but with viaduct settings, this leeward-to-windward ratio significantly decreases.