scholarly journals CORRECTION OF MEASURED TAXICAB EXHAUST EMISSION DATA BASED ON CMEM MODLE

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1245-1250
Author(s):  
Q. Li ◽  
T. Jia
Keyword(s):  
Carbon Dioxide ◽  
Time Delay ◽  
Correlation Coefficient ◽  
Carbon Dioxide Emissions ◽  
Motor Vehicle ◽  
Road Traffic ◽  
Quality Analysis ◽  
Exhaust Emission ◽  
Control Group ◽  
Trajectory Data

Carbon dioxide emissions from urban road traffic mainly come from automobile exhaust. However, the carbon dioxide emissions obtained by the instruments are unreliable due to time delay error. In order to improve the reliability of data, we propose a method to correct the measured vehicles’ carbon dioxide emissions from instrument based on the CMEM model. Firstly, the synthetic time series of carbon dioxide emissions are simulated by CMEM model and GPS velocity data. Then, taking the simulation data as the control group, the time delay error of the measured carbon dioxide emissions can be estimated by the asynchronous correlation analysis, and the outliers can be automatically identified and corrected using the principle of DTW algorithm. Taking the taxi trajectory data of Wuhan as an example, the results show that (1) the correlation coefficient between the measured data and the control group data can be improved from 0.52 to 0.59 by mitigating the systematic time delay error. Furthermore, by adjusting the outliers which account for 4.73 % of the total data, the correlation coefficient can raise to 0.63, which suggests strong correlation. The construction of low carbon traffic has become the focus of the local government. In order to respond to the slogan of energy saving and emission reduction, the distribution of carbon emissions from motor vehicle exhaust emission was studied. So our corrected data can be used to make further air quality analysis.

scholarly journals Estimating Causal Effects When the Treatment Affects All Subjects Simultaneously: An Application

2021 ◽  
Vol 5 (2) ◽  
pp. 22
Author(s):  
Chiara Binelli
Keyword(s):  
Machine Learning ◽  
Carbon Dioxide ◽  
Global Warming ◽  
Carbon Dioxide Emissions ◽  
Control Group ◽  
Sources Of Information ◽  
Average Global Temperature ◽  
Causal Impact ◽  
The Impact ◽  
Robust Evidence

Several important questions cannot be answered with the standard toolkit of causal inference since all subjects are treated for a given period and thus there is no control group. One example of this type of questions is the impact of carbon dioxide emissions on global warming. In this paper, we address this question using a machine learning method, which allows estimating causal impacts in settings when a randomized experiment is not feasible. We discuss the conditions under which this method can identify a causal impact, and we find that carbon dioxide emissions are responsible for an increase in average global temperature of about 0.3 degrees Celsius between 1961 and 2011. We offer two main contributions. First, we provide one additional application of Machine Learning to answer causal questions of policy relevance. Second, by applying a methodology that relies on few directly testable assumptions and is easy to replicate, we provide robust evidence of the man-made nature of global warming, which could reduce incentives to turn to biased sources of information that fuels climate change skepticism.

scholarly journals Real-Time Management of Vessel Carbon Dioxide Emissions Based on Automatic Identification System Database Using Deep Learning

2021 ◽  
Vol 9 (8) ◽  
pp. 871
Author(s):  
Yongpeng Wang ◽  
Daisuke Watanabe ◽  
Enna Hirata ◽  
Shigeki Toriumi
Keyword(s):  
Carbon Dioxide ◽  
Real Time ◽  
Time Management ◽  
Carbon Dioxide Emissions ◽  
Fixed Time ◽  
Automatic Identification ◽  
Identification System ◽  
Time Interval ◽  
Trajectory Data ◽  
Fixed Time Interval

In this study, we propose an effective method using deep learning to strengthen real-time vessel carbon dioxide emission management. We propose a method to predict real-time carbon dioxide emissions of the vessel in three steps: (1) convert the trajectory data of the fixed time interval into a spatial–temporal sequence, (2) apply a long short-term memory (LSTM) model to predict the future trajectory and vessel status data of the vessel, and (3) predict the carbon dioxide emissions. Automatic identification system (AIS) database of a liquefied natural gas (LNG) vessel were selected as the sample and we reconstructed the trajectory data with a fixed time interval using cubic spline interpolation. Applying the interpolated AIS data, the carbon dioxide emissions of the vessel were calculated based on the International Towing Tank Conference (ITTC) recommended procedures. The experimental results are twofold. First, it reveals that vessel emissions are currently underestimated. This study clearly indicates that the actual carbon dioxide emissions are higher than those reported. The finding offers insight into how to accurately measure the emissions of vessels, and hence, better execute a greenhouse gases (GHGs) reduction strategy. Second, the LSTM model has a better trajectory prediction performance than the recurrent neural network (RNN) model. The errors of the trajectory endpoint and carbon dioxide emissions were small, which shows that the LSTM model is suitable for spatial–temporal data prediction with excellent performance. Therefore, this study offers insights to strengthen the real-time management and control of vessel greenhouse gas emissions and handle those in a more efficient way.

scholarly journals Illicit Drug Abuse in Drivers of Motor Vehicle Collisions

2015 ◽  
Vol 4 (1) ◽  
pp. 39-46
Author(s):  
Mohammad Kalantari Meibodi ◽  
Samira Esfandyari ◽  
Vahid Siyabi ◽  
Sareh Roosta
Keyword(s):  
Drug Abuse ◽  
Illicit Drugs ◽  
Illicit Drug ◽  
Motor Vehicle ◽  
Road Traffic ◽  
Control Group ◽  
Case Group ◽  
Drug Abusers ◽  
Increased Risk ◽  
Illicit Drug Abuse

Background: Motor vehicle Traffic injuries are indeed one of the most important worldwide health problems. Opioids can induce a depressant effect on the central nervous system which may increase the risk of traffic accidents. This cross-sectional case-control study was conducted in Marvdasht, Iran to investigate the presence of drugs in hospitalized non-fatally injured drivers of motor vehicles.Materials and Methods: The cases were 500 drivers of motor vehicle, injured in the road traffic accident and referred to the emergency ward. The controls were 500 patients hospitalized in the same emergency department due to non-traumatic reasons. They were asked about the abuse of any substance during the 72 hours before their referral to the hospital. Urinary samples of patients with negative history of drug consumption were analyzed.Results: From the drivers, 237 (47.4%) of the case group and 278 (55.6%) of the control group had positive-substance consumption. Opium was the common drug abused in the two groups. An eight fold increased risk of road accident was observed for drivers who had used tramadol (OR= 8.2, 95% CI 4.9-13.7, p<0.001). Two or more illicit drugs (poly drug abuse) were detected in 24% of the cases and 31.8% of the controls (50.6% and 57.2% of drug abusers, respectively). Just for tramadol, the prevalence was higher in cases than controls. Conclusion: The results demonstrate the high proportion of illicit drug abuse among Iranian drivers. More health education and policies are necessary to steadily decrease drug abuse in our society.

scholarly journals MONITORING AND CALCULATING THE CARBON DIOXIDE EMISSIONS IN BAGHDAD AND ITS EFFECT ON INCREASING TEMPERATURES FROM 2003-2018 USING REMOTE SENSING DATA

2020 ◽  
Vol 17 (36) ◽  
pp. 357-371
Author(s):  
Mazin Shakir JASIM ◽  
Fouad Kadhum MASHEE
Keyword(s):  
Remote Sensing ◽  
Carbon Dioxide ◽  
Correlation Coefficient ◽  
Carbon Dioxide Emissions ◽  
Pearson Correlation ◽  
Remote Sensing Data ◽  
Hydrocarbon Gases ◽  
Entire Study ◽  
Sensing Data ◽  
The City

The city of Baghdad has witnessed an urban and industrial expansion with an increase in population, especially since 2003. Air pollution sources have multiplied by the increase in the number of vehicles and electricity generators, causing the emission of large quantities of hydrocarbon gases, including carbon dioxide, CO2. The discharge of such gases into the atmosphere and large amounts, will surely have a role in contributing to global warming. Therefore, it will have prominent adverse effects in influencing the rise in temperatures in the city. The research aimed to show the applied aspect of remote sensing and geographic information systems techniques in estimating the CO2 and its relationship to thermal balance for Baghdad city through fifteen stations distributed throughout the city. Remote sensing data adopted from US Geological and the European Centre, in addition to CO2 data for the Atmospheric Infrared sounder (AIRS) from Giovanni for the extended period (2003-2018), were used. Processing and statistical analysis were performed on data using GIS 10.6 and Origin 2018 software. The monthly rates of CO2 showed seasonal fluctuations between winter and summer, where the highest value of CO2 in July and the lowest value in February. Inverse Distance Weighting (IDW) technology was used to represent the spatial distribution of CO2 concentrations in the city. Residential and industrial regions experienced higher levels compared to agricultural areas. Pearson correlation coefficient was used to find out the relationship between carbon dioxide and temperatures. The correlation coefficient showed a high positive relationship between increased gas concentrations and high temperatures for all study stations over the entire study period. It can be concluded the concentration of carbon dioxide differs locally in regions of Baghdad, such as residential, commercial, traffic, industrial, and rural areas, as well as during the months of the year.

scholarly journals The Profitability of Disposing of Vehicles Fulfilling the Older Euro Standards in Terms of CO2 Emission

2019 ◽  
Vol 26 (1) ◽  
pp. 89-94
Author(s):  
Maciej Menes ◽  
Piotr Wiśniowski
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Road Traffic ◽  
Test Procedure ◽  
Exhaust System ◽  
Passenger Cars ◽  
Emission Standard ◽  
Automotive Market ◽  
High Emission ◽  
Living Organisms

Abstract The automotive market is developing very dynamically. In recent years, we can observe activities of automotive concerns in the production of new models of electric, hybrid and hydrogen vehicles, and conventional cars are supplied with increasingly economical and low-emission engines. There are also increasingly stringent standards related to exhaust emissions from the exhaust system. From September 1, 2018, passenger cars have to comply with the Euro 6d-Temp emission standard and be homologated according to the WLTP test procedure including the WLTC driving cycle and emission measurements in road traffic conditions. The exhaust components measured during the test, such as carbon oxides, nitrogen oxides or hydrocarbons, are toxic to living organisms. However, it seems that the most important issue in the long term may be the value of carbon dioxide emissions, the excess of which poses an ecological threat to the entire planet. The production of new vehicles equipped with modern complicated combustion engines, batteries, fuel cells and electronic devices is associated with a very high emission of this greenhouse gas The authors of the following article, based on their own research, sought to estimate the ecological profitability of replacing a used passenger car meeting the Euro-4 emissions standard for a new vehicle bearing in mind the value of carbon dioxide emissions during vehicle production. The analysis was to indicate how intensive the annual operation of the vehicle should be to make it profitable to recycle and replace it with a modern car with lower emissions considering the global sum of carbon dioxide emissions.

scholarly journals High-resolution mapping of motor vehicle carbon dioxide emissions

2014 ◽  
Vol 119 (9) ◽  
pp. 5283-5298 ◽  
Author(s):  
Brian C. McDonald ◽  
Zoe C. McBride ◽  
Elliot W. Martin ◽  
Robert A. Harley
Keyword(s):  
Carbon Dioxide ◽  
High Resolution ◽  
Carbon Dioxide Emissions ◽  
Motor Vehicle ◽  
High Resolution Mapping ◽  
Resolution Mapping

scholarly journals Carbon Dioxide Emissions as an Indicator of Reduction of Negative Externalities Related to Road Motor Vehicle Operation

2014 ◽  
Vol 62 (4) ◽  
pp. 613-621 ◽  
Author(s):  
Břetislav Andrlík
Keyword(s):  
Carbon Dioxide ◽  
European Union ◽  
Carbon Dioxide Emissions ◽  
Motor Vehicle ◽  
Performance Standards ◽  
Motor Vehicles ◽  
The European Union ◽  
Passenger Cars ◽  
Legal Standards ◽  
Harmful Substances

This contribution deals with issues of carbon dioxide emissions generated by road motor vehicles in the Czech Republic and the European Union. We discuss the current need for the introduction of environmental features to the system of taxation of motor vehicles, aiming at the mitigation of harmful substances emitted into the atmosphere. The most harmful substance produced during the combustion of hydrocarbon fuels by motor vehicles is CO2, whose emissions are subsequently used as an instrument for green tax reforms in the European Union member states. In this article we define the main EU legal standards regulating harmful substances emitted into the atmosphere as a result of road motor transport. We may cite for instance the Regulation (EC) No. 443/2009 setting CO2 emission performance standards for new passenger cars. The aim of the European Union is to reduce average emission values of new passenger cars sold in the EU to 130 g CO2/km by 2015 and to 95 g CO2/km by 2020. Assessment of tax on motor vehicles according to CO2 emissions shall help fulfil commitments from the Kyoto Protocol, aiming at the reduction of greenhouse gas emissions.

scholarly journals Carbon Dioxide Emissions of the City Center of Firenze, Italy: Measurement, Evaluation, and Source Partitioning

2009 ◽  
Vol 48 (9) ◽  
pp. 1940-1947 ◽  
Author(s):  
A. Matese ◽  
B. Gioli ◽  
F. P. Vaccari ◽  
A. Zaldei ◽  
F. Miglietta
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Road Traffic ◽  
Initial Period ◽  
City Center ◽  
Domestic Heating ◽  
Gas Consumption ◽  
Carbon Dioxide Co2 ◽  
The City ◽  
Source Partitioning

Abstract An eddy covariance station was installed in the city center of Firenze, Italy, to measure carbon fluxes at half-hourly intervals over a mostly homogeneous urban area. Carbon dioxide (CO2) emission observations made over an initial period of 3.5 months were compared with indirect estimates of CO2 emissions based on inventory data sources of vehicle circulation and natural gas consumption for domestic heating and cooking. Such a comparison provided proper evaluation of the measurements. Using seasonal dynamics of observed fluxes, the overall CO2 source of the city center was partitioned into its major components (i.e., road traffic and domestic heating). Results were directly compared with CO2 source estimates based on inventory sources.

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