The Temporal and Frequent Pattern Mining Analysis and Machine Learning Forecasting on Mobile Sourced Urban Air Pollutants

Ground-level ozone and atmospheric fine particles (PM2.5) have been recognized as critical air pollutants that act as important contributors to the toxicity of anthropogenic air pollution in urban areas. To limit the adverse impacts on public health and ecosystems of ground-level ozone and PM2.5, it is necessary and imperative to identify a practical and effective way to predict the upcoming pollution concentration levels accurately. Under this need, various research was conducted aiming to perform the forecasting of ground-level ozone and PM2.5 that mainly utilized the time-series and neural network analysis. In the meantime, machine learning is also adopted in analysis and forecasting in existing research, which is, however, associated with some limitations that are not easily overcome. (1) The majority of existing forecasting models are highly dependent on time-series inputs without considering the influencing factors of the air pollutants. While a relatively accurate prediction may be provided, the influencing factors of the air pollution level caused by real-world complexity are neglected. (2) The existing forecasting models are mainly focused on the short-term estimation, while some of them need to use the previous prediction as a part of the input, which increased the system complexity and decreased the computational efficiency and accuracy. (3) The accurate annual hourly air pollution level forecasting ability is seldomly achieved. The objective of this research is to propose a systematical methodology to forecast the long-term hourly future air pollution concentration levels through historical data considering the concentration influencing factors. To achieve this research goal, a series of methodologies to analyze the historical air pollution concentration by temporal characteristics and frequent pattern data mining algorithms are introduced. The association rules of air pollution concentration levels and the influencing factors are revealed. A systematical air pollution level forecasting approach based on supervised machine learning algorithms with the ability to predict the annual hourly value is proposed and evaluated. To quantify and validate the results, a case study was conducted in the Houston region with the collection and analysis of ten years of historical environmental, meteorological, and transportation-related data. From the results of this research, (1) the complex correlations between the influencing factors and air pollution concentration levels are quantified and presented. (2) The association rules between each dependant and independent parameters are calculated. (3) The supervised machine learning algorithm pool is created and evaluated. And (4), an accurate long-term hourly air pollution level machine learning forecasting procedure is proposed. The innovative methodology of this research is advanced in computation complexity with high accuracy when compared with the existing models, which could be easily applied to similar regions for various types of air pollution concentration level forecasting

Optimal joint production and emissions reduction strategies considering consumers\u27 environmental preferences: A manufacturer\u27s perspective

Carbon cap-and-trade mechanism is a government-mandated, market-based scheme to reduce emissions, which has a significant effect on manufacturers\u27 operation decisions. Based on the cap-and-trade mechanism, this paper studies the joint production and emission reduction problem of a manufacturer. The manufacturer faces emissions-sensitive demand impacted by consumers\u27 environmental preferences (CEP). An extended newsvendor model is used to find the optimal production quantity and emissions reduction quantity. We explore the impacts of market price of carbon credits, emission reduction investment coefficient and CEP on the optimal strategies. Numerical examples are provided to illustrate the theoretical results and orthogonal experimental design technique was applied to find robust system parameters. It is concluded that among all parameters, emissions cap has the greater impact on the expected profit, which is followed by than the market price of carbon credits. This means that the government plays a major role in economic development. The total carbon emissions are mainly affected by the carbon trading price and the product\u27s sale price, which indicates the carbon trading market and product market play a larger role in controlling environmental benefits. Several valuable managerial insights on helping governments and industries understand how market conditions change and make better long-term decisions are further concluded

Synthesis of Best Application and Verification Practices for Long-Life Pavement Markings: Final Report

0-7135Proper application of pavement markings plays an important role in enhancing the safety of roadway users. The purpose of this study is to carefully synthesize information on the usage of various types of pavement marking materials (including but not limited to the types of marking materials and quality control approaches, types of specifications, and application rate verification) to identify marking equipment ability and markings payment bases and develop recommendations with regard to different U.S. states and several foreign countries, and to compare them with the Texas Department of Transportation\u2019s (TxDOT) pavement marking practices. To achieve these objectives, a comprehensive online survey was designed in which a wide range of practical information was collected with respect to marking material types and quality control approaches, types of specifications and application rate verification, and equipment and payment bases from field engineers in other states and countries. In addition, manuals and research papers or reports related to pavement marking materials for other state-level departments of transportation (DOTs) and foreign countries were thoroughly reviewed and synthesized. The TxDOT (2004) Pavement Marking Handbook does not incorporate more recently available marking technologies or quality control procedures for the new marking materials. The researchers therefore recommend adoption of best practices from other states and countries to improve the existing handbook. The implementation of the recommendations would help to enhance the efficiency of TxDOT pavement marking practices, including those for marking durability and retro-reflectivity

Improving Bus Transit Services for Disabled Individuals: Demand Clustering, Bus Assignment, and Route Optimization

Bus transit provides shorter-distance public transportation services, which are subject to various disability discrimination acts with various dedicated features. The Americans with Disabilities Act (ADA) requires that disabled individuals shall have equal rights to receive fare bus transit services, including fixed-route and door-to-door bus services. Most previous studies were mainly focused on policy aspects as part of the efforts of disability rights. The proper planning of demand requests from disabled individuals has been a critical issue but has gained insufficient attention. The existing methodologies in planning route for special transit buses for disabled individuals normally do not consider passengers\u27 waiting time, lack sufficient flexibility, and have strict restrictions on the total number of served destinations. This paper proposes a four-module based methodology for the planning of bus transit, including demand information collection, demand clustering, transit bus assignment, and a linear programming-based route planning with different objective functions. Houston MetroLift bus transit service was employed as an example to illustrate the proposed method. Three scenarios during the route planning module were designed in this case study: (1) planning for pre-timed shortest distance, (2) planning for the pre-timed shortest waiting time of passengers, and (3) flexible planning. Results showed that scenario 1 obtained the shortest total travel time and the highest benefit for bus providers, scenario 2 is with the shortest average waiting time, while scenario 3 is real-time based with longer total travel time and longer waiting time. Scenarios 2 and 3 consider the special needs of disabled passengers

Impact of Managed-Lane Pricing Strategies on Vehicle-Sourced NOx and HC Emissions

Ground-level ozone is a secondary air pollutant that is formed by chemical reactions between precursors, including nitrogen oxides (NOx) and hydrocarbon (HC). Highway traffic, which can be controlled by traffic operational strategies, is one of the main sources of atmospheric NOx and HC. Managed-lane pricing is one of the popularly used freeway traffic management approaches, while its impacts on ground-level ozone-related vehicle emissions is, however, still unclear. This motivated the purpose of this research. A case study in Houston, USA indicates that, vehicles on managed lanes had fewer hard accelerations/decelerations and higher average speed, which resulted in higher per-vehicle emissions in grams/hour, while the total emissions of a vehicle were roughly comparable to what they would be on a general-purpose lane. Total daily NOx and HC emissions per managed lane were 31.9%–42.6% of those per general-purpose lane. The weight ratios between HC and NOx show that, the ground-level ozone formation of this area is hydrocarbon-limited

Optimal Joint Production and Emissions Reduction Strategies Considering Consumers’ Environmental Preferences: A Manufacturer’s Perspective

Carbon cap-and-trade mechanism is a government-mandated, market-based scheme to reduce emissions, which has a significant effect on manufacturers’ operation decisions. Based on the cap-and-trade mechanism, this paper studies the joint production and emission reduction problem of a manufacturer. The manufacturer faces emissions-sensitive demand impacted by consumers’ environmental preferences (CEP). An extended newsvendor model is used to find the optimal production quantity and emissions reduction quantity. We explore the impacts of market price of carbon credits, emission reduction investment coefficient and CEP on the optimal strategies. Numerical examples are provided to illustrate the theoretical results and orthogonal experimental design technique was applied to find robust system parameters. It is concluded that among all parameters, emissions cap has the greater impact on the expected profit, which is followed by than the market price of carbon credits. This means that the government plays a major role in economic development. The total carbon emissions are mainly affected by the carbon trading price and the product’s sale price, which indicates the carbon trading market and product market play a larger role in controlling environmental benefits. Several valuable managerial insights on helping governments and industries understand how market conditions change and make better long-term decisions are further concluded

0\u20137135: Synthesis of Best Application and Verification Practices for Long-Life Pavement Markings [Project Summary]

To perform this project, the researchers followed five steps. In Step 1, the researchers collected information necessary for identifying best case examples of quality control of liquid and thermoplastic pavement marking material applications. They reviewed practices across the U.S. and other countries using various sources, such as government manuals, reports, guidebooks, research papers, and other publications; conducted a survey via SurveyMonkey.com to obtain the views of pavement marking field practitioners in the U.S. and other countries; and then synthesized the collected information. In Step 2, the researchers identified the best case examples and reviewed practices for various marking materials used across the U.S. and other countries. They also investigated reasons for using particular marking materials on different pavement types. They also identified quality control approaches and methods, including verifying selected thickness or quantity of markings in preformed thermoplastic could be developed; (5) materials specifications from other states can be carefully reviewed; (6) the usage of recently available technology (i.e., stripe scan and marking thickness gauge) for measuring marking thickness can be considered; (7) the installation of data logging systems on striping trucks could be considered in Texas; (8) straightedge tools can be used for measuring the width of markings; (9) removal techniques (flailing and high-pressure water blasting for thermoplastic) can be combined on asphalt and concrete surfaces; (10) inclusion of the cost for mobile retroreflectometer in the marking payment is a worthwhile consideration; and (11) a software tool could be developed for marking material selection