Methodologies for estimating pollutant emissions generated by trucks to the atmosphere

2018 ◽  
Author(s):  
H.M. Restrepo P ◽  
J.J. Posada H
Keyword(s):  
Pollutant Emissions

Pollutant emissions research using a well stirred reactor

1994 ◽  
Author(s):  
Joseph Zelina ◽  
Richard Striebich ◽  
Dilip Ballal
Keyword(s):  
Pollutant Emissions ◽  
Stirred Reactor

Pollutant emissions investigation in a compression ignition engine during warm-up time

2017 ◽  
Author(s):  
Naiara Lima Costa ◽  
Ramon Eduardo Pereira Silva ◽  
Letícia Schneider Ferrari
Keyword(s):  
Pollutant Emissions ◽  
Compression Ignition ◽  
Compression Ignition Engine ◽  
Warm Up

MITIGATION OF HAZARDOUS AIR POLLUTANT EMISSIONS: VACUUM vs. CONVENTIONAL SEWER SYSTEM

2017 ◽  
Vol 16 (4) ◽  
pp. 809-819 ◽  
Author(s):  
Gabriel Lazar ◽  
Iulia Carmen Ciobotici Terryn ◽  
Andreea Cocarcea
Keyword(s):  
Air Pollutant ◽  
Pollutant Emissions ◽  
Sewer System ◽  
Hazardous Air Pollutant

Comparative analysis on the effects of diesel particulate filter and selective catalytic reduction systems on a wide spectrum of chemical species emissions

2018 ◽  
Author(s):  
Z. Gerald Liu ◽  
Devin R. Berg ◽  
Thaddeus A. Swor ◽  
James J. Schauer‡
Keyword(s):  
Diesel Engine ◽  
Selective Catalytic Reduction ◽  
Diesel Particulate Filter ◽  
Catalytic Reduction ◽  
Wide Spectrum ◽  
Chemical Species ◽  
Pollutant Emissions ◽  
Particulate Filter ◽  
Diesel Particulate ◽  
Aftertreatment Systems

Two methods, diesel particulate filter (DPF) and selective catalytic reduction (SCR) systems, for controlling diesel emissions have become widely used, either independently or together, for meeting increasingly stringent emissions regulations world-wide. Each of these systems is designed for the reduction of primary pollutant emissions including particulate matter (PM) for the DPF and nitrogen oxides (NOx) for the SCR. However, there have been growing concerns regarding the secondary reactions that these aftertreatment systems may promote involving unregulated species emissions. This study was performed to gain an understanding of the effects that these aftertreatment systems may have on the emission levels of a wide spectrum of chemical species found in diesel engine exhaust. Samples were extracted using a source dilution sampling system designed to collect exhaust samples representative of real-world emissions. Testing was conducted on a heavy-duty diesel engine with no aftertreatment devices to establish a baseline measurement and also on the same engine equipped first with a DPF system and then a SCR system. Each of the samples was analyzed for a wide variety of chemical species, including elemental and organic carbon, metals, ions, n-alkanes, aldehydes, and polycyclic aromatic hydrocarbons, in addition to the primary pollutants, due to the potential risks they pose to the environment and public health. The results show that the DPF and SCR systems were capable of substantially reducing PM and NOx emissions, respectively. Further, each of the systems significantly reduced the emission levels of the unregulated chemical species, while the notable formation of new chemical species was not observed. It is expected that a combination of the two systems in some future engine applications would reduce both primary and secondary emissions significantly.

A statistical approach to pollutant emissions from combined sewer systems

1997 ◽  
Vol 36 (8-9) ◽  
pp. 95-100 ◽  
Author(s):  
Robin G. Veldkamp ◽  
Jan B. M. Wiggers
Keyword(s):  
Suspended Solids ◽  
Statistical Approach ◽  
Low Frequency ◽  
Pollutant Emissions ◽  
Frequency Of Occurrence ◽  
Single Event ◽  
Sewer Systems ◽  
Impervious Area ◽  
Combined Sewer ◽  
Kjeldahl Nitrogen

This research is based on CSO emissions from Dutch sewer systems. During the years 1982 to 1989 research was done on several sewer systems, all of them equiped with a single overflow weir. Pollutant emissions were calculated from the measurements, whereby each storm was considered as a single event. Extreme emissions have a detrimental, sometimes even desastrous effect on water quality. Such extreme emissions are the result of heavy storms, giving it a low frequency of occurrence. From the measurements a statistical model was developed enabling the user to forecast extreme waste emissions with a certain return period in a range of 2 to 10 years. Five pollutants are put in the model: BOD, COD, Kjeldahl nitrogen, total phosphate and suspended solids. The model operates with standardized emission values in kg per ha of impervious area. When the model is used in practice the runoff area to the specific overflow under consideration has to be known.

scholarly journals Combustion Optimization for Coal Fired Power Plant Boilers Based on Improved Distributed ELM and Distributed PSO

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1036 ◽  
Author(s):  
Xinying Xu ◽  
Qi Chen ◽  
Mifeng Ren ◽  
Lan Cheng ◽  
Jun Xie
Keyword(s):  
Power Plant ◽  
Combustion Process ◽  
Optimization Method ◽  
Combustion Efficiency ◽  
Pollutant Emissions ◽  
Combustion Model ◽  
Nox Emissions ◽  
Coupling Characteristics ◽  
Learning Machine ◽  
Combustion Optimization

Increasing the combustion efficiency of power plant boilers and reducing pollutant emissions are important for energy conservation and environmental protection. The power plant boiler combustion process is a complex multi-input/multi-output system, with a high degree of nonlinearity and strong coupling characteristics. It is necessary to optimize the boiler combustion model by means of artificial intelligence methods. However, the traditional intelligent algorithms cannot deal effectively with the massive and high dimensional power station data. In this paper, a distributed combustion optimization method for boilers is proposed. The MapReduce programming framework is used to parallelize the proposed algorithm model and improve its ability to deal with big data. An improved distributed extreme learning machine is used to establish the combustion system model aiming at boiler combustion efficiency and NOx emission. The distributed particle swarm optimization algorithm based on MapReduce is used to optimize the input parameters of boiler combustion model, and weighted coefficient method is used to solve the multi-objective optimization problem (boiler combustion efficiency and NOx emissions). According to the experimental analysis, the results show that the method can optimize the boiler combustion efficiency and NOx emissions by combining different weight coefficients as needed.

scholarly journals Economical Speed for Optimizing the Travel Time and Energy Consumption in Train Scheduling using a Fuzzy Multi-Objective Model

2021 ◽  
Author(s):  
Ahmad Reza Jafarian-Moghaddam
Keyword(s):  
Energy Consumption ◽  
Travel Time ◽  
Pollutant Emissions ◽  
Scheduling Problems ◽  
Train Scheduling ◽  
Multi Objective ◽  
Consumption Ratio ◽  
Proposed Model ◽  
Objective Model ◽  
Time And Energy

AbstractSpeed is one of the most influential variables in both energy consumption and train scheduling problems. Increasing speed guarantees punctuality, thereby improving railroad capacity and railway stakeholders’ satisfaction and revenues. However, a rise in speed leads to more energy consumption, costs, and thus, more pollutant emissions. Therefore, determining an economic speed, which requires a trade-off between the user’s expectations and the capabilities of the railway system in providing tractive forces to overcome the running resistance due to rail route and moving conditions, is a critical challenge in railway studies. This paper proposes a new fuzzy multi-objective model, which, by integrating micro and macro levels and determining the economical speed for trains in block sections, can optimize train travel time and energy consumption. Implementing the proposed model in a real case with different scenarios for train scheduling reveals that this model can enhance the total travel time by 19% without changing the energy consumption ratio. The proposed model has little need for input from experts’ opinions to determine the rates and parameters.

scholarly journals Industry 4.0 Maturity Model Assessing Environmental Attributes of Manufacturing Company

2021 ◽  
Vol 11 (11) ◽  
pp. 5151
Author(s):  
Michal Zoubek ◽  
Peter Poor ◽  
Tomas Broum ◽  
Josef Basl ◽  
Michal Simon
Keyword(s):  
Industry 4.0 ◽  
Industrial Revolution ◽  
Cost Savings ◽  
Pollutant Emissions ◽  
Value Stream Mapping ◽  
Maturity Model ◽  
Value Stream ◽  
Environmental Attributes ◽  
Lean And Green ◽  
Environmentally Responsible Manufacturing

The primary purpose of this article is to present a maturity model dealing with environmental manufacturing processes in a company. According to some authors, Industry 4.0 is based on characteristics that have already been the focus of “lean and green” concepts. The goal of the article was to move from resource consumption, pollutant emissions, and more extensive manufacturing towards environmentally responsible manufacturing (ERM). Using environmental materials and methods reduces energy consumption, which generates cost savings and higher profits. Here, value stream mapping (VSM) was applied to identify core processes with environmental potential. This paper provides an understanding of the role of environmental manufacturing in the era of the Fourth Industrial Revolution.

scholarly journals How Does Environmental Regulation Affect the Relationship between FDI and Technological Innovation: From the Perspective of Technology Transactions

Processes ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1264
Author(s):  
Meng Zeng ◽  
Lihang Liu ◽  
Fangyi Zhou ◽  
Yigui Xiao
Keyword(s):  
Environmental Regulation ◽  
Technological Innovation ◽  
Pollutant Emissions ◽  
Regulatory Effect ◽  
Host Countries ◽  
Regional Heterogeneity ◽  
Industrial Sectors ◽  
Reduction Effect ◽  
The Impact ◽  
The Relationship

Many studies have found that FDI can reduce the pollutant emissions of host countries. At the same time, the intensity of environmental regulation would affect the emission reduction effect of FDI in the host country. This study aims to reveal the internal mechanisms of this effect. Specifically, this paper studies the impact of FDI on technological innovation in China’s industrial sectors from the perspective of technology transactions from 2001 to 2019, and then analyzes whether the intensity of environmental regulation can promote the relationship. Results indicate that FDI promotes technological innovation through technology transactions. In addition, it finds that the intensity of environmental regulation significantly positively moderates the relationship between FDI and technological innovation, which is achieved by positively moderating the FDI–technology transaction relationship. Regional heterogeneity analysis is further conducted, and results show that in the eastern and western regions of China, FDI can stimulate technological innovation within regional industrial sectors through technology trading. Moreover, environmental regulation has a significant positive regulatory effect on the above relationship, but these effects are not supported by evidence in the central region of China.

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