Civil & Environmental Engineering Research Works

Permanent URI for this collection

http://hdl.handle.net/1903/1657

Browse

Now showing 1 - 20 of 42

Methods for Adjusting U.S. Geological Survey Rural Regression Peak Discharges in an Urban Setting
(U.S. Geological Survey, 2006) Moglen, Glenn E.; Schwartz, Dorianne E.
A study was conducted of 78 U.S. Geological Survey gaged streams that have been subjected to varying degrees of urbanization over the last three decades. Flood-frequency analysis coupled with nonlinear regression techniques were used to generate a set of equations for converting peak discharge estimates determined from rural regression equations to a set of peak discharge estimates that represent known urbanization. Specifically, urban regression equations for the 2-, 5-, 10-, 25-, 50-, 100-, and 500-year return periods were calibrated as a function of the corresponding rural peak discharge and the percentage of impervious area in a watershed. The results of this study indicate that two sets of equations, one set based on imperviousness and one set based on population density, performed well. Both sets of equations are dependent on rural peak discharges, a measure of development (average percentage of imperviousness or average population density), and a measure of homogeneity of development within a watershed. Average imperviousness was readily determined by using geographic information system methods and commonly available land-cover data. Similarly, average population density was easily determined from census data. Thus, a key advantage to the equations developed in this study is that they do not require field measurements of watershed characteristics as did the U.S. Geological Survey urban equations developed in an earlier investigation. During this study, the U.S. Geological Survey PeakFQ program was used as an integral tool in the calibration of all equations. The scarcity of historical land-use data, however, made exclusive use of flow records necessary for the 30-year period from 1970 to 2000. Such relatively short-duration streamflow time series required a nonstandard treatment of the historical data function of the PeakFQ program in comparison to published guidelines. Thus, the approach used during this investigation does not fully comply with the guidelines set forth in U.S. Geological Survey Bulletin 17B, and modifications may be needed before it can be applied in practice.
Nuclear envelope laminopathies: evidence for developmentally inappropriate chromatin-nuclear envelope interactions
(Springer Nature, 2013-03-18) Perovanovic, Jelena; Jaiswal, Jyoti; Markovic, Nikola; Hoffman, Eric
During terminal differentiation of cells, there is typically a transition of the nuclear envelope from the Lamin B protein to Lamin A/C proteins. This is commensurate with exit from the cell cycle, and maintenance of the transcriptional programs associated with the terminally differentiated cells. Dominant missense mutations in Lamin A/C cause a broad spectrum of human genetic disorders, where specific point mutations are associated with defects in specific organs or tissues. We have previously presented a model where Lamin A/C mutations disrupt developmentally appropriate interactions between chromatin and the nuclear envelope and lead to poor coordination of E2F cell cycle pathways and terminal differentiation pathways [1]. One of the phenotypes caused by Lamin A/C mutations is Emery Dreifuss Muscular Dystrophy (EDMD). An X-linked recessive phenocopy of EDMD is caused by loss of function of emerin – a binding partner to Lamin A/C at the nuclear envelope. Here, we tested the hypothesis that emerin plays a role in chromatin remodeling via stabilizing nuclear lamina-heterochromatin interactions necessary for appropriate and time dependent muscle differentiation. We used WT and emerin null mouse myogenic stem cells to study transcriptional and epigenetic changes during in vitro exit from the cell cycle and differentiation to the myogenic lineage. Specific cell cycle (E2F) and myogenic genes were analyzed by qPCR and ChlP-qPCR to determine mRNA timing and H3K9me3 enrichment on gene promoters. Nuclear lamina-chromatin colocalization was determined and quantified by confocal imaging and Matlab. Our results showed that TK1 and other cell cycle genes are inappropriately persistently expressed in emerin null cells during differentiation causing delayed exit from cell cycle. Transcripts marking commitment to the myogenic lineage (myogenin and Mef5A) showed delayed activation on both mRNA and protein level. Epigenetic imprints predicted observed deviations from transcriptional timing in emerin null cells, with persistent suppressive chromatin state on myog promoter upon myogenic induction and failure to appropriately establish repressive histone marks (H3K9me3) on Tk1 promoter (cell cycle). Finally, we showed that the early cell cycle exit and terminal differentiation of emerin null myoblasts were accompanied by decreased H3K9me3 staining at the nuclear periphery (lamin A/C immunostaining). Myogenic cells lacking emerin exhibit perturbations in terminal commitment to the myogenic lineage. Our transcriptional, chromatin remodeling and gene promoter accessibility data show that both exit from cell cycle and terminal commitment to myogenesis are disrupted due to inappropriate heterochromatin-nuclear lamina interactions in EMD myogenic cells.
Elimination of Bloodstream Infections Associated with Candida albicans Biofilm in Intravascular Catheters
(MDPI, 2015-06-29) Akbari, Freshta; Kjellerup, Birthe Veno
Intravascular catheters are among the most commonly inserted medical devices and they are known to cause a large number of catheter related bloodstream infections (BSIs). Biofilms are associated with many chronic infections due to the aggregation of microorganisms. One of these organisms is the fungus Candida albicans. It has shown to be one of the leading causes of catheter-related BSIs. The presence of biofilm on intravascular catheters provide increased tolerance against antimicrobial treatments, thus alternative treatment strategies are sought. Traditionally, many strategies, such as application of combined antimicrobials, addition of antifungals, and removal of catheters, have been practiced, but they were not successful in eradicating BSIs. Since these fungal infections can result in significant morbidity, mortality, and increased healthcare cost, other promising preventive strategies, including antimicrobial lock therapy, chelating agents, alcohol, and biofilm disruptors, have been applied. In this review, current success and failure of these new approaches, and a comparison with the previous strategies are discussed in order to understand which preventative treatment is the most effective in controlling the catheter-related BSIs.
Model-Based Design and Formal Verification Processes for Automated Waterway System Operations
(MDPI, 2016-06-07) Petnga, Leonard; Austin, Mark
Waterway and canal systems are particularly cost effective in the transport of bulk and containerized goods to support global trade. Yet, despite these benefits, they are among the most under-appreciated forms of transportation engineering systems. Looking ahead, the long-term view is not rosy. Failures, delays, incidents and accidents in aging waterway systems are doing little to attract the technical and economic assistance required for modernization and sustainability. In a step toward overcoming these challenges, this paper argues that programs for waterway and canal modernization and sustainability can benefit significantly from system thinking, supported by systems engineering techniques. We propose a multi-level multi-stage methodology for the model-based design, simulation and formal verification of automated waterway system operations. At the front-end of development, semi-formal modeling techniques are employed for the representation of project goals and scenarios, requirements and high-level models of behavior and structure. To assure the accuracy of engineering predictions and the correctness of operations, formal modeling techniques are used for the performance assessment and the formal verification of the correctness of functionality. The essential features of this methodology are highlighted in a case study examination of ship and lock-system behaviors in a two-stage lock system.
Soil temperature simulation results in Alaska (1980 - 2014) – Data archive for “Evaluation and enhancement of permafrost modeling with the NASA Catchment Land Surface Model”
(2017) Tao, Jing; Reichle, Rolf; Koster, Randal; Forman, Barton; Xue, Yuan
The datasets archived here include simulation results discussed in the paper, “Evaluation and enhancement of permafrost modeling with the NASA Catchment Land Surface Model”, to be published in Journal of Advances in Modeling Earth Systems. Specifically, subsurface soil temperatures for 1980-2014 across Alaska were produced by a baseline simulation with the NASA Catchment Land Surface Model (CLSM). Five sets of point simulations were also conducted at permafrost sites in Alaska, including 1) T1BC - the top layer temperature is prescribed to observations, 2) T1BC_OrgC – repeat of the T1BC simulation but using the updated model version that incorporates soil thermal impacts of organic carbon content, 3) T2BC - the temperatures of both the 1st and 2nd layer are prescribed to observations, 4) T2BC_OrgC – repeat of the T2BC simulation but using the updated model version, and 5) M2_OrgC – simulations with the updated model version driven by MERRA-2 forcing. Details about the model configuration and the changes defining the updated model version can be found in the paper. The major findings in this paper include: a) profile-average RMSE of simulated soil temperature versus in situ observations is reduced by using corrected local forcing and land cover; b) subsurface heat transport is mostly realistic, and when not, it is improved via treatment of soil organic carbon-related thermal properties; and c) mean bias and RMSE of climatological ALT between simulations and observations are significantly reduced with updated model version.
Advancing Scientific Knowledge: Ethical Issues in the Journal Publication Process
(MDPI, 2017-12-31) McCuen, Richard H.
The goal of this paper is to assess the journal publication process from value and ethical perspectives. The specific objectives are: (1) To define fundamental values relevant to scientific journal publication; (2) To identify stakeholders involved in professional journals and their value rights and responsibilities; (3) To discuss the steps of the journal publication process where ethical dilemmas arise and the potential influences of such dilemmas on the advancement of knowledge; and (4) To summarize actions that can minimize unethical practices throughout the steps of the publication process. Values such as honesty, efficiency, accountability, and fairness will be discussed. Issues related to the various stakeholders such as self-citation, plagiarism, dual publication, a lack of timeliness, and issues related to authorship will be a primary focus.
Compositional Approach to Distributed System Behavior Modeling and Formal Validation of Infrastructure Operations with Finite State Automata: Application to Viewpoint-Driven Verification of Functionality in Waterways
(MDPI, 2018-01-12) Austin, Mark A.; Johnson, John
Now that modern infrastructure systems are moving toward an increased use of automation in their day-to-day operations, there is an emerging need for new approaches to the formal analysis and validation of system functionality with respect to correctness of operations. This paper describes a compositional approach to the multi-level behavior modeling and formal validation of large-scale distributed system operations with hierarchies and networks of finite state automata. To avoid the well-known state explosion problem, we develop a new procedure for viewpoint-action-process traceability, thereby allowing parts of a behavior model not relevant to a specific decision to be removed from consideration. Key features of the methodology are illustrated through the development of behavior models and validation procedures for polite conversation between two individuals, and lockset- and system-level concerns for ships traversing a large-scale waterway system.
Estimating snow mass in North America through assimilation of AMSR-E brightness temperature observations using the Catchment land surface model and support vector machines
(2018-04-16) Xue, Yuan; Forman, Barton; Reichle, Rolf; Forman, Barton
To estimate snow mass across North America, multi-frequency brightness temperature (Tb) observations collected by the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) from 2002 to 2011 were assimilated into the Catchment land surface model using a support vector machine (SVM) as the observation operator as part of a one-dimensional ensemble Kalman filter. The performance of the assimilation system is evaluated through comparisons against ground-based measurements and publicly-available reference SWE and snow depth products. Assimilation estimates agree better with ground-based snow depth measurements than model-only (“open loop”, or OL) estimates in approximately 82% (56 out of 62) of pixels that are colocated with at least two ground-based stations. In addition, assimilation estimates tend to agree better with all snow products over tundra snow, alpine snow, maritime snow, as well as sparsely-vegetated snow-covered pixels. Improvements in snow mass via assimilation translate into improvements in cumulative runoff estimates when compared against discharge measurements in 11 out of 13 major snow-dominated basins in Alaska. These results prove that a SVM can serve as an efficient and effective observation operator for snow mass estimation within a radiance assimilation system.
A Novel Framework for Sustainable Traffic Safety Programs Using the Public as Sensors of Hazardous Road Information
(MDPI, 2018-10-26) Chung, Younshik; Won, Minsu
Traditionally, traffic safety improvement programs (TSIPs) have been based on the number of crashes at a specific location or their severity. However, the crash datasets used for such programs are obtained from the police and include two limitations: not all crashes are collected by the police (most minor and near-miss crashes are not reported), and the traditional process uses crash data recorded for the past two or three years (meaning most data inevitably include a time lag). To overcome these limitations, this study proposes a new approach for a TSIP based on citizen participation through an online survey that is broadcasted through social media. The method uses the public as sensors of hazardous road information, which means that information can be collected on individual experiences of minor crashes and latent risk factors, such as near misses and traffic conflicts. To demonstrate this approach, a case study was carried out in a small district in the city of Goyang, Korea, which has one of the highest usage rates of social media technologies. The proposed method and a traditional method were both assessed.
Fatigue Assessment of Highway Bridges under Traffic Loading Using Microscopic Traffic Simulation
(IntechOpen, 2018-11-13) Zhao, Gengwen; Fu, Chung C.; Lu, Yang; Saad, Timothy
Fatigue is a common failure mode of steel bridges induced by truck traffic. Despite the deterioration caused by environmental factors, the increasing truck traffic volume and weight pose a premier threat to steel highway bridges. Given the uncertainties of the complicated traffic loading and the complexity of the bridge structure, fatigue evaluation based on field measurements under actual traffic flow is recommended. As the quality and the quantity of the available long-term traffic monitoring data and information have been improved, methodologies have been developed to obtain more realistic vehicular live load traffic. A case study of a steel interstate highway bridge using microscopic traffic simulation is presented herein. The knowledge of actual traffic loading may reduce the uncertainty involved in the evaluation of the load-carrying capacity, estimation of the rate of deterioration, and prediction of remaining fatigue life. This chapter demonstrates a systematic approach using traffic simulation and bridge health monitoring-based fatigue assessment.
Utilization of Dynamic and Static Sensors for Monitoring Infrastructures
(IntechOpen, 2018-12-12) Fu, Chung C.; Zhu, Yifan; Hou, Kuang-Yuan
Infrastructures, including bridges, tunnels, sewers, and telecommunications, may be exposed to environmental-induced or traffic-induced deformation and vibrations. Some infrastructures, such as bridges and roadside upright structures, may be sensitive to vibration and displacement where several different types of dynamic and static sensors may be used for their measurement of sensitivity to environmental-induced loads, like wind and earthquake, and traffic-induced loads, such as passing trucks. Remote sensing involves either in situ, on-site, or airborne sensing where in situ sensors, such as strain gauges, displacement transducers, velometers, and accelerometers, are considered conventional but more durable and reliable. With data collected by accelerometers, time histories may be obtained, transformed, and then analyzed to determine their modal frequencies and shapes, while with displacement and strain transducers, structural deflections and internal stress distribution may be measured, respectively. Field tests can be used to characterize the dynamic and static properties of the infrastructures and may be further used to show their changes due to damage. Additionally, representative field applications on bridge dynamic testing, seismology, and earthborn/construction vibration are explained. Sensor data can be analyzed to establish the trend and ensure optimal structural health. At the end, five case studies on bridges and industry facilities are demonstrated in this chapter.
Development of a Fatigue Life Assessment Model for Pairing Fatigue Damage Prognoses with Bridge Management Systems
(IntechOpen, 2018-12-18) Saad, Timothy; Fu, Chung C.; Zhao, Gengwen; Xu, Chaoran
Fatigue damage is one of the primary safety concerns for steel bridges reaching the end of their design life. Currently, US federal requirements mandate regular inspection of steel bridges for fatigue cracks; however, these inspections rely on visual inspection, which is subjective to the inspector’s physically inherent limitations. Structural health monitoring (SHM) can be implemented on bridges to collect data between inspection intervals and gather supplementary information on the bridges’ response to loads. Combining SHM with finite element analyses, this paper integrates two analysis methods to assess fatigue damage in the crack initiation and crack propagation periods of fatigue life. The crack initiation period is evaluated using S-N curves, a process that is currently used by the FHWA and AASHTO to assess fatigue damage. The crack propagation period is evaluated with linear elastic fracture mechanic-based finite element models, which have been widely used to predict steady-state crack growth behavior. Ultimately, the presented approach will determine the fatigue damage prognoses of steel bridge elements and damage prognoses are integrated with current condition state classifications used in bridge management systems. A case study is presented to demonstrate how this approach can be used to assess fatigue damage on an existing steel bridge.
Machine Learning for Projecting Extreme Precipitation Intensity for Short Durations in a Changing Climate
(MDPI, 2019-05-09) Hu, Huiling; Ayyub, Bilal M.
Climate change is one of the prominent factors that causes an increased severity of extreme precipitation which, in turn, has a huge impact on drainage systems by means of flooding. Intensity–duration–frequency (IDF) curves play an essential role in designing robust drainage systems against extreme precipitation. It is important to incorporate the potential threat from climate change into the computation of IDF curves. Most existing works that have achieved this goal were based on Generalized Extreme Value (GEV) analysis combined with various circulation model simulations. Inspired by recent works that used machine learning algorithms for spatial downscaling, this paper proposes an alternative method to perform projections of precipitation intensity over short durations using machine learning. The method is based on temporal downscaling, a downscaling procedure performed over the time scale instead of the spatial scale. The method is trained and validated using data from around two thousand stations in the US. Future projection of IDF curves is calculated and discussed.
Exploring the Utility of Machine Learning-Based Passive Microwave Brightness Temperature Data Assimilation over Terrestrial Snow in High Mountain Asia
(MDPI, 2019-09-28) Kwon, Yonghwan; Forman, Barton A.; Ahmad, Jawairia A.; Kumar, Sujay V.; Yoon, Yeosang
This study explores the use of a support vector machine (SVM) as the observation operator within a passive microwave brightness temperature data assimilation framework (herein SVM-DA) to enhance the characterization of snow water equivalent (SWE) over High Mountain Asia (HMA). A series of synthetic twin experiments were conducted with the NASA Land Information System (LIS) at a number of locations across HMA. Overall, the SVM-DA framework is effective at improving SWE estimates (~70% reduction in RMSE relative to the Open Loop) for SWE depths less than 200 mm during dry snowpack conditions. The SVM-DA framework also improves SWE estimates in deep, wet snow (~45% reduction in RMSE) when snow liquid water is well estimated by the land surface model, but can lead to model degradation when snow liquid water estimates diverge from values used during SVM training. In particular, two key challenges of using the SVM-DA framework were observed over deep, wet snowpacks. First, variations in snow liquid water content dominate the brightness temperature spectral difference (ΔTB) signal associated with emission from a wet snowpack, which can lead to abrupt changes in SWE during the analysis update. Second, the ensemble of SVM-based predictions can collapse (i.e., yield a near-zero standard deviation across the ensemble) when prior estimates of snow are outside the range of snow inputs used during the SVM training procedure. Such a scenario can lead to the presence of spurious error correlations between SWE and ΔTB, and as a consequence, can result in degraded SWE estimates from the analysis update. These degraded analysis updates can be largely mitigated by applying rule-based approaches. For example, restricting the SWE update when the standard deviation of the predicted ΔTB is greater than 0.05 K helps prevent the occurrence of filter divergence. Similarly, adding a thin layer (i.e., 5 mm) of SWE when the synthetic ΔTB is larger than 5 K can improve SVM-DA performance in the presence of a precipitation dry bias. The study demonstrates that a carefully constructed SVM-DA framework cognizant of the inherent limitations of passive microwave-based SWE estimation holds promise for snow mass data assimilation.
Image Data for "Measuring soil coverage using image feature descriptors and the decision tree learning algorithm"
(2020-05) Davis, Allen; Aydilek, Ahmet; Owen, Dylan
Imaging data for identification of ground cover, distinguishing among green vegetation, straw/dormant vegetation, and exposed soil.
Toward sustainable travel: An analysis of campus bikeshare use
(Elsevier, 2020-07) Aliari, Sanaz; Nasri, Arefeh; Nejad, Mohammad Motalleb; Haghani, Ali
In this study, we use University of Maryland's (UMD) bikeshare ridership data along with historical weather data, elevation, and transit service location data to analyze bikeshare trip patterns and explore the various factors influencing demand for the system across the UMD campus. We analyzed the spatial, temporal, and environmental factors influencing trips within a 19-month period to shed some light on how the bikeshare system is being used across campus and in its surroundings and to determine the most important factors shaping the demand. Results show that, similar to the city-wide bikeshare systems, demand for campus bikeshare is mostly influenced by weather, time of day, day of the week, month of the year, and accessibility to transit and various other destinations. However, unlike the city-wide bikeshare systems, there is not a concentration of trips within peak hours, as trips are scattered throughout the day. This is probably due to the flexible working schedules of bikeshare users on-campus (i.e., students and faculty), as opposed to the users of city-wide systems. Additionally, results indicate a higher on-campus usage of the system within the proximity of the transit hubs with a median trip duration of 6.8 min which supports the complementary relationship between bikeshare system and conventional transit systems.
Comparison of Vertical Surface Deformation Estimates Derived from Space-based Gravimetry, Ground-based GPS, and Model-based Hydrologic Loading over Snow-dominated Watersheds in the United States
(2020-07) Yin, Gaohong; Forman, Barton Allen
The data archived here includes the NASA Catchment Land Surface Model output of monthly TWS anomalies (after removing the long-term mean) used in the investigation of vertical displacement comparison for the Great Basin and Upper Colorado basins in the paper “Comparison of Vertical Surface Deformation Estimates Derived from Space-based Gravimetry, Ground-based GPS, and Model-based Hydrologic Loading over Snow-dominated Watersheds in the United States” for publication in the Journal of Geophysical Research – Solid Earth.
Evaluation of GEOS-Simulated L-Band Microwave Brightness Temperature Using Aquarius Observations over Non-Frozen Land across North America
(MDPI, 2020-09-22) Park, Jongmin; Forman, Barton A.; Reichle, Rolf H.; De Lannoy, Gabrielle; Tarik, Saad B.
L-band brightness temperature (𝑇𝑏) is one of the key remotely-sensed variables that provides information regarding surface soil moisture conditions. In order to harness the information in 𝑇𝑏 observations, a radiative transfer model (RTM) is investigated for eventual inclusion into a data assimilation framework. In this study, 𝑇𝑏 estimates from the RTM implemented in the NASA Goddard Earth Observing System (GEOS) were evaluated against the nearly four-year record of daily 𝑇𝑏 observations collected by L-band radiometers onboard the Aquarius satellite. Statistics between the modeled and observed 𝑇𝑏 were computed over North America as a function of soil hydraulic properties and vegetation types. Overall, statistics showed good agreement between the modeled and observed 𝑇𝑏 with a relatively low, domain-average bias (0.79 K (ascending) and −2.79 K (descending)), root mean squared error (11.0 K (ascending) and 11.7 K (descending)), and unbiased root mean squared error (8.14 K (ascending) and 8.28 K (descending)). In terms of soil hydraulic parameters, large porosity and large wilting point both lead to high uncertainty in modeled 𝑇𝑏 due to the large variability in dielectric constant and surface roughness used by the RTM. The performance of the RTM as a function of vegetation type suggests better agreement in regions with broadleaf deciduous and needleleaf forests while grassland regions exhibited the worst accuracy amongst the five different vegetation types.
Impact of the Built Environment Measured at Multiple Levels on Nonmotorized Travel Behavior: An Ecological Approach to a Florida Case Study
(MDPI, 2020-10-24) Mahmoudi, Jina; Zhang, Lei
Research continues to reveal the benefits of nonmotorized travel modes such as walking and bicycling. Therefore, identification of the factors that nurture these activities is essential in developing sustainable urban planning policies and designs. Among those factors are the built environment characteristics of the place of residence. To date, research on the role of the built environment in nonmotorized travel has focused on neighborhood-level factors. However, people do not stay within their neighborhoods; they live and work at a regional scale and travel to various destinations and distances each day. Nonetheless, little is known about the impact of built environment factors at larger spatial scales on nonmotorized travel behavior. Guided by the principles of the ecological model of behavior, this study investigates the role of the built environment at hierarchical spatial scales in nonmotorized travel behavior. Multilevel Structural Equation Models have been developed to comprehensively examine the complex links between the built environment and individuals’ nonmotorized travel. Findings indicate that built environment factors at multiple spatial scales can influence nonmotorized travel behavior. Thus, to promote walking and bicycling, more effective policies are those that include multilevel built environment and land use interventions and consider the overall physical form of urban areas.
SMAP soil moisture assimilated Noah-MP model output
(2021) Ahmad, Jawairia; Forman, Bart; Kumar, Sujay
The data archived here includes the NASA Noah-MP (version 4.0.1) land surface model output used in the investigation of the impact of passive microwave-based soil moisture retrieval assimilation on soil moisture estimation in South Asia (Ahmad et al., 2021). SMAP soil moisture retrievals are assimilated into the Noah-MP land surface model to improve the estimation of soil moisture and other related states. The open loop (OL) represents Noah-MP’s modeling capabilities using MERRA2 and IMERG precipitation. Two different types of data assimilation runs were executed using the MERRA2 and IMERG precipitation boundary conditions, i.e., with CDF-matching (DA-CDF) and without CDF matching (DA-NoCDF). The key findings in this paper include: 1) assimilation results without any CDF-matching yielded the lowest error in estimated soil moisture, 2) the best goodness-of-fit statistics were achieved for the IMERG-forced DA-NoCDF soil moisture experiment, 3) biases associated with unmodeled hydrologic processes such as irrigation were corrected via assimilation, and 4) the highest influence of assimilation was observed across croplands.

Browse

Browsing Civil & Environmental Engineering Research Works by Issue Date

Results Per Page

Sort Options