Pollution Levels In Cities Research Articles

Methods for Urban Air Pollution Measurement and Forecasting: Challenges, Opportunities, and Solutions

In today’s urban environments, accurately measuring and forecasting air pollution is crucial for combating the effects of pollution. Machine learning (ML) is now a go-to method for making detailed predictions about air pollution levels in cities. In this study, we dive into how air pollution in urban settings is measured and predicted. Using the PRISMA methodology, we chose relevant studies from well-known databases such as PubMed, Springer, IEEE, MDPI, and Elsevier. We then looked closely at these papers to see how they use ML algorithms, models, and statistical approaches to measure and predict common urban air pollutants. After a detailed review, we narrowed our selection to 30 papers that fit our research goals best. We share our findings through a thorough comparison of these papers, shedding light on the most frequently predicted air pollutants, the ML models chosen for these predictions, and which ones work best for determining city air quality. We also take a look at Skopje, North Macedonia’s capital, as an example of a city still working on its air pollution measuring and prediction systems. In conclusion, there are solid methods out there for air pollution measurement and prediction. Technological hurdles are no longer a major obstacle, meaning decision-makers have ready-to-use solutions to help tackle the issue of air pollution.

Status of atmospheric air pollution in Ukraine prior to the full-scale russian invasion. Part 1: ground-level content of pollutants

The paper is dedicated to examination of atmospheric air pollution in Ukraine that is aimed at establishing basic air quality conditions prior to the full-scale Russian invasion. Analyses cover five air pollutants (dust, sulfur dioxide (SO2), carbon monoxide (CO), nitrogen dioxide (NO2), and formaldehyde (CH2O)) across 126 monitoring stations in 39 cities. It was found that the most dangerous excess of air pollution levels in cities was associated with dust, NO2, and CO. At the same time, SO2 content usually did not reach dangerous levels. The highest frequency of exceeding the threshold one-time levels was common for the cities with well-developed industrial facilities. Dangerous air pollution was observed in 15–60% of cases, depending on a pollutant. Dust and NO2 concentrations of the most polluted cities were 10 times higher than their concentrations in smaller cities having no significant industrial emissions. The difference in average CO, SO2, and CH2O concentrations among monitoring stations constituted 3-5 times. We studied the patterns of pollutants' seasonal variability recorded at the monitoring stations. Normally, no significant seasonality except for CH2O and dust was observed. The interannual variability of pollutants, emissions, and their trends were analyzed for the period since 2008. We identified a certain discrepancy in trends between pollutants’ concentrations and emission data over the last years. Pollutant content often continued to grow concurrently with emission reductions. The impact of atmospheric phenomena and wind parameters was studied mainly in terms of its role in formation of high and low atmospheric pollution levels. The analysis indicated a crucial role of local conditions in the formation of an atmospheric pollution field next to monitoring stations. Varying atmospheric pollution values across different monitoring stations within a specific city can be different even under the influence of the same atmospheric phenomena. The wind impact also formed different patterns of atmospheric pollution within same city. 12% to 22% of all monitoring stations (depending on a pollutant) indicated a prevailing impact of a single emission source (or a combined impact of a group of sources). At the same time, air pollution at other monitoring stations was highly variable, with elevated pollution levels being transported from numerous directions. The analysis of the air pollution-affected condition presented in the paper could be used as a basis for comparing ground-level pollution and assessing the warfare consequences in Ukraine. The research emphasizes the importance of updating the information about ground-based monitoring stations.

Smart Parking System for Institute

As the number of vehicles on roads continues to rise, businesses are more likely to encounter a range of issues. To address such challenges, the "Smart Parking System" has been developed as an intelligent and automatic solution for parking vehicles. This system is designed to alleviate problems faced by urban areas on their roads. However, precisely tracking the availability of parking spots across different locations and times remains a significant difficulty. Nonetheless, the Smart Parking System enables parking attendants to easily locate empty parking spaces. Moreover, implementing this smart parking system can help minimize energy consumption and pollution levels in cities, ultimately contributing toward the country's economic growth.

CHARACTERISING THE POLLUTION CONCENTRATION IN HIGHLY URBANIZED AREA: AN APPLICATION OF REMOTE SENSING

Abstract. According to estimates from the World Health Organization (WHO), air pollution contributes to about seven million deaths worldwide annually. Currently, more than 90% of people breathe air that exceeds the WHO’s recommended threshold of pollutants. This high degree of air pollution results in serious public health problems, such as pneumonia, acute asthma, chronic respiratory conditions, and shortness of breath. The execution of solutions to lower pollution exposure is therefore required, a study into the causes of air pollution. The “National Clean Air Programme (NCAP)”, a five-year action plan, has been launched by the Ministry of Environment, Forest and Climate Change (MOEFCC, 2019), Government of India. The program’s primary objective is to combat significant air pollution problems over the Indian subcontinent. As a result of economic growth, air pollution concentrations have consistently climbed to dangerous levels. To investigate influence of anthropogenic parameters on urban air, statistical analysis has been carried out for 8 Indian cities for pre- and post-COVID period using Sentinel-5P earth observatory data. These factors include population density, land use and total registered vehicles. The results of the investigation demonstrated that during the lockdown, air pollution levels in cities decreased. It is also discovered that pollutant levels have escalated once more since the lockdown limitations were lifted. It is clear from the findings that parameters affect pollution exposure. This demonstrates categorically that the pandemic has a beneficial effect on pollution exposure. A policy framework can be advised for policymakers based on the study done.

The regional impact of the COVID-19 lockdown on the air quality in Ji'nan, China

A number of strict lockdown measures were implemented in the areas most affected by COVID-19 in China, including Ji’nan city, from 24 January to 7 February 2020. Due to these forced restrictions, the pollution levels in cities across the country drastically decreased within just a few days. Since traffic pollution and industrial emissions are important factors affecting regional air quality, congestion has a significant impact on the environment. Therefore, using the aid of air quality data for six pollutants (PM10, PM2.5, SO2, NO2, CO and O3) from 11 monitoring stations (located in urban, suburban and urban-industrial regions) across Ji’nan, we employed the air quality index (AQI) to investigate the spatial pattern of air quality in the pre-COVID-19 (pre-COVID) and COVID-19-related lockdown (COVID lockdown) periods. The results showed that air quality significantly improved during the COVID lockdown period. Among the selected pollutants, compared to the corresponding pre-COVID levels, the greatest reduction was observed for the concentration of NO2 (54.02%), while the smallest reduction was observed for the concentration of SO2 (27.92%). The PM2.5 (38.73%), PM10 (44.92%) and CO (30.60%) levels also decreased during the COVID lockdown period; only the O3 concentration increased (37.42%) during this period. Overall, air quality improved by approximate improvements of 37.33% during the COVID lockdown period. Approximately 35.48%, 37.01% and 43.43% in the AQI were observed in urban, suburban and urban-industrial regions, respectively. Therefore, the AQI exhibited remarkable regional differences in Ji'nan. This study demonstrates the contributions of the transportation sector and local emissions to improving air quality in typical urban areas, and these research results can provide guidance for the further monitoring of air pollution in northern Chinese cities.

Air Quality Decrement After Lockdown in Major Cities of Rajasthan, India

The lockdown restrictions during the COVID-19 pandemic provided a 'path' of reinstatement of the air quality globally. Despite several financial challenges, air quality improvement positively impacted the environment due to lockdown in the worst pandemic situations. The present study assessed the air pollution scenario in the post lockdown phase in the seven major metropolises of Rajasthan, namely, Jodhpur, Alwar, Jaipur, Kota, Pali, Ajmer, and Udaipur, in the recent pandemic year 2020. The air pollution scenario is determined with the help of the Air Quality Index (AQI) and the concentration level of PM2.5, PM10, NO2, and SO2. This study reveals that most cities of Rajasthan are violating India's national ambient air quality standards (NAAQS). It is found that Jodhpur is on rank first in terms of pollution levels, followed by Alwar, Jaipur, Pali, and Udaipur. The pollution level was higher before the lockdown period then reduced to a certain level due to restricted activities in lockdown. The pollution level is not rapidly increased after lockdown due to rainfall from the southwest monsoon. Winter season consists of higher concentration levels of pollutant and higher than before lockdown period. The study shows the significant impact of lockdown in reducing air pollution levels in cities. But imposing lockdown in a city or country is not a permanent solution to curb air pollution. So, regulating agencies and stakeholders should implement better control and reduction technologies for Indian cities.

Footprint Reduction of Sensor Control Modules for Remote Portable Laboratories.

Following the automation of monitoring systems for pollution levels in cities or protected nature reserves, there comes a need to increase the autonomy of robotic vectors deployed in the field. Thus, it is important to consider the weight that these robots must hold in order to be able to carry out a comprehensive analysis of the environment. A balance must be struck in the size, weight, and complexity of the mobile laboratories used for measurement and the autonomy of robots, especially given that current technology does not allow, in most cases, a completely autonomous battery charging cycle. Thus, in this paper, we consider a microcontroller-based architecture for a mobile laboratory control system that will be used for installation on both an aerial and an aquatic mobile vector. We found that such a system can be repurposed for several sensor types and configurations, thus being able to massively reduce the space allocated when compared to embedded widespread products.

Energy-saving and Emission Reduction Effects of China's Auto Tax Policy

In the face of rapid expansion of China's automobile ownership, serious air pollution, increasing energy consumption, method and policy that promote energy conservation and emission reduction of automobiles have become widespread concerns at present. In this context, this study introduces the reform of vehicle purchase tax, vehicle and vessel tax, and fuel tax in China, and empirically compares the energy saving and emission reduction effects of the three taxes. The results show that the emission reduction effect of the purchase tax reduction is more significant. Moreover, the effect of the purchase tax reduction on reducing air pollutant emissions shows a "U" shaped dynamic change as the pollution level in cities increases and then decreases.

Emission Reduction Effect and Mechanism of Auto-Purchase Tax Preference

As a modern means of transportation, the automobile plays an important role in people’s travel. However, the environmental and energy problems brought by the automobile industry cannot be ignored. Based on unique Chinese urban and new car registration data, this paper empirically analyzes the emission reduction effect of car purchase tax incentives, its spatial heterogeneity, and impact on car consumption structure using difference-in-difference model, regression discontinuity design model, and other methods. We find that the tax incentives can effectively suppress the emission of urban pollutants. The quantile regression shows that the emission reduction effect of the tax incentives shows a dynamic change characteristic of weakening as the pollution level in cities increases. In addition, tax incentives for the purchase of low-energy consumption vehicles increase the market share of small-emission vehicles and change the consumption structure.

The practice of applying health risk assessment in the Federal Project “Clean Air” in the participating cities (Cherepovets, Lipetsk, Omsk, Novokuznetsk): problems and prospects

Introduction. The object of the study is the results obtained during the implementation of the Federal Project (FP) “Clean Air” in 2020 in the supervised participating cities and the assessment of the possibility of implementing the tasks set for Rospotrebnadzor for effective health risk management, reducing morbidity and mortality of the population. The purpose of the study is to assess the risk to public health according to the summary calculations of atmospheric air pollution in the cities of Cherepovets, Lipetsk, Omsk, Novokuznetsk during the implementation of the FP “Clean Air” (baseline, 2017). Materials and methods. The primary approach to implementing the FP “Clean Air” in 2020 is to use the initial data (summary calculations of atmospheric air pollution) and obtain on their basis the levels of exposure and risks to public health. A software product of the “Ecolog-Gorod” series was used to calculate single and average annual concentrations. The health risk assessment procedure was carried out under the requirements of the manual R 2.1.10.1920-04. Results. Studies were conducted to assess the risk to public health based on the data of summary calculations of atmospheric air pollution in the cities participating in the FP “Clean Air” (Cherepovets, Lipetsk, Omsk, Novokuznetsk) in 2017 before the start of the measures provided for by the Comprehensive Plans to reduce emissions of pollutants into the atmospheric air. The assessment of the public health risk from atmospheric air pollution made it possible to establish: priority compounds contained in industrial emissions, the primary industrial sources and their share contribution, as well as the contribution of motor transport and independent heat supply sources emissions to the formation of pollution levels in cities; the population exposed to unacceptable risk levels were determined; substances that should be taken into account when quoting emissions were identified. The variants of improving the quality of preparation of the initial data of summary calculations for health risk assessment are recommended. Conclusion. There are suggested approaches to improving the quality of preparation of initial data of consolidated calculations for health risk assessment.

Air quality during three covid-19 lockdown phases: AQI, PM2.5 and NO2 assessment in cities with more than 1 million inhabitants

Implemented quarantine due to the ongoing novel coronavirus (agent of COVID-19) has an immense impact on human mobility and economic activities as well as on air quality. Since then, and due to the drastic reduction in pollution levels in cities across the world, a large discussion has been magnetized regarding if the lockdown is an adequate alternative counter-measure for enhancing air quality. This paper aimed at studying the Air Quality Index (AQI), PM2.5, and tropospheric NO2 levels in three lockdown phases (before, during, and after) among 21 cities around the world. Simple before/after comparison approach was carried out to capture the declining trend in air pollution levels caused by the lockdown restrictions. The results showed that the frequency distribution for NO2 is more variable than that for PM2.5, and the distribution is flatter from 2020 to the baseline 2018-2019 period. Besides, AQI, in most of the cities, has varied from high to mild pollution during the lockdown and was moderate before. Although during the lockdown, a reduction of 3 to 58% of daily NO2 concentrations was observed across the cities, an increase was detected in three cities including Abidjan (1%), Conakry (3%), and Chengdu (10%). Despite this mixed trend, the NO2 time series clearly showed the effect of the unlocking phase where the NO2 levels increased in almost all cities. Similarly, PM2.5 concentrations have increased in the post-lockdown period, with 50% of the cities reporting significant positive differences between the lock and the unlock phase. Then, the levels of PM2.5 were higher at the pre-lockdown phase than at any other time exhibiting a “U” shape. In addition, during Ramadan, it was noted that altered patterns of daily activities in some Islamic cities have a significant negative impact on air quality.

Green economy – growth and maintenance of the conditions of green growth at the level of polish local authorities

Coal is the central energy resource in Poland, and air pollution levels in cities in Poland are some of the highest in Europe. Environmental protection problems are among the greatest challenges for the Polish authorities and society. As of today, there is a risk of temperatures rising 1.5 °C before 2050; this rise in temperature is leading to the intensification of changes that are unfavorable for people, such as weather disasters. The aim of this article was to analyze the scale of necessary sustainable investments of the local governments in Poland, with particular emphases on the role of cities, the current structural gaps and the financial mismatches. The focus was mainly on the adaptation and mitigation aspects of climate change, with less emphasis on social factors. The results indicated an increasing need for green and/or sustainable investments by local governments. A number of barriers to accessing new forms of sustainable finance were identified. The most important hurdles included low involvement of the private sector in local government financing, regulatory and fiscal barriers, and the inability of local governments to provide effective currency hedging. The need for new mechanisms to help local governments through guarantees or innovative instruments and potentially through new institutions or facilities was demonstrated.

Spatial and temporal representativeness of point measurements for nitrogen dioxide pollution levels in cities

Abstract. In many cities around the world the overall air quality is improving, but at the same time nitrogen dioxide (NO2) trends show stagnating values and in many cases could not be reduced below air quality standards recommended by the World Health Organization (WHO). Many large cities have built monitoring stations to continuously measure different air pollutants. While most stations follow defined rules in terms of measurement height and distance to traffic emissions, the question remains of how representative are those point measurements for the city-wide air quality. The question of the spatial coverage of a point measurement is important because it defines the area of influence and coverage of monitoring networks, determines how to assimilate monitoring data into model simulations or compare to satellite data with a coarser resolution, and is essential to assess the impact of the acquired data on public health. In order to answer this question, we combined different measurement data sets consisting of path-averaging remote sensing data and in situ point measurements in stationary and mobile setups from a measurement campaign that took place in Munich, Germany, in June and July 2016. We developed an algorithm to strip temporal from spatial patterns in order to construct a consistent NO2 pollution map for Munich. Continuous long-path differential optical absorption spectroscopy (LP DOAS) measurements were complemented with mobile cavity-enhanced (CE) DOAS, chemiluminescence (CL) and cavity attenuated phase shift (CAPS) instruments and were compared to monitoring stations and satellite data. In order to generate a consistent composite map, the LP DOAS diurnal cycle has been used to normalize for the time of the day dependency of the source patterns, so that spatial and temporal patterns can be analyzed separately. The resulting concentration map visualizes pollution hot spots at traffic junctions and tunnel exits in Munich, providing insights into the strong spatial variations. On the other hand, this database is beneficial to the urban planning and the design of control measures of environment pollution. Directly comparing on-street mobile measurements in the vicinity of monitoring stations resulted in a difference of 48 %. For the extrapolation of the monitoring station data to street level, we determined the influence of the measuring height and distance to the street. We found that a measuring height of 4 m, at which the Munich monitoring stations measure, results in 16 % lower average concentrations than a measuring height of 1.5 m, which is the height of the inlet of our mobile measurements and a typical pedestrian breathing height. The horizontal distance of most stations to the center of the street of about 6 m also results in an average reduction of 13 % compared to street level concentration. A difference of 21 % in the NO2 concentrations remained, which could be an indication that city-wide measurements are needed for capturing the full range and variability of concentrations for assessing pollutant exposure and air quality in cities.

Spatial-temporal patterns and influence of land-use and socioeconomic factors on fine particulate matter pollution in Accra, Ghana

Background: Air pollution levels in cities in Sub-Saharan Africa (SSA), the world’s most rapidly urbanizing region, are among the highest globally due to influences from diverse local and regional sources. However, very little is known about within-city disparities at fine spatial-temporal resolution. We examined the space-time patterns of fine particle pollution (PM2.5) in relation to land-use variables and socioeconomic factors in Accra, Ghana, and evaluated trends over a decade.Methods: We measured and analysed weekly gravimetric and minute-by-minute PM2.5 (optical sensor) concentrations from 150 unique locations (10 fixed [1-year] and 140 weekly [7-day] sites) covering a range of land-use, socioeconomic features and source influences.Results: PM2.5 concentrations were highest between December - February, during the “Harmattan” when transported dust and changes in regional and local meteorology affect Accra. In this period, levels were as high as 267 μg/m3 (mean 94.1 μg/m3), compared to annual PM2.5 concentrations ranging from 14.4 to 31.3 μg/m3 at fixed sites. Across all 150 sites, weekly concentrations ranged from <10 μg/m3 to >250 μg/m3. Sites near roadsides had the highest overall mean PM2.5 (43 μg/m3), followed by high-density (poor) and low-density (affluent) residential sites; peri-urban background sites had the lowest levels. By time of day, daily PM2.5 at all sites rose at dawn and peaked at daybreak, followed by a gradual decline till afternoon and a modest evening peak. There were indications of decreased PM2.5 concentrations at residential sites when compared to matching data from a decade ago (39 vs 25 μg/m3), suggesting likely reductions in biomass emissions.Conclusion: Fine particle pollution in Accra may be decreasing over time but remains 2 to 4-fold higher than the WHO guideline with significant variations in relation to spatial, socioeconomic, and land-use factors. Equitable local policies and interventions are needed to reduce air pollution levels and protect the vulnerable.

Effect of lockdown amid COVID-19 pandemic on air quality of the megacity Delhi, India

Amid the COVID-19 pandemic, a nationwide lockdown is imposed in India initially for three weeks from 24th March to 14th April 2020 and extended up to 3rd May 2020. Due to the forced restrictions, pollution level in cities across the country drastically slowed down just within few days which magnetize discussions regarding lockdown to be the effectual alternative measures to be implemented for controlling air pollution. The present article eventually worked on this direction to look upon the air quality scenario amidst the lockdown period scientifically with special reference to the megacity Delhi. With the aid of air quality data of seven pollutant parameters (PM10, PM2.5, SO2, NO2, CO, O3 and NH3) for 34 monitoring stations spread over the megacity we have employed National Air Quality Index (NAQI) to show the spatial pattern of air quality in pre and during-lockdown phases. The results demonstrated that during lockdown air quality is significantly improved. Among the selected pollutants, concentrations of PM10 and PM2.5 have witnessed maximum reduction (>50%) in compare to the pre-lockdown phase. In compare to the last year (i.e. 2019) during the said time period the reduction of PM10 and PM2.5 is as high as about 60% and 39% respectively. Among other pollutants, NO2 (−52.68%) and CO (−30.35%) level have also reduced during-lockdown phase. About 40% to 50% improvement in air quality is identified just after four days of commencing lockdown. About 54%, 49%, 43%, 37% and 31% reduction in NAQI have been observed in Central, Eastern, Southern, Western and Northern parts of the megacity. Overall, the study is thought to be a useful supplement to the regulatory bodies since it showed the pollution source control can attenuate the air quality. Temporary such source control in a suitable time interval may heal the environment.

NO2 Air Pollution Exposure Assessment in Urban Mysore, India

TPS 651: Air pollution exposure modeling 1, Exhibition Hall, Ground floor, August 27, 2019, 3:00 PM - 4:30 PM Introduction: In developing countries, rapid urbanization has led to decreased air quality. Few studies have applied spatially heterogeneous sampling to assess ambient air pollution levels in cities in India, to understand the important local predictors of air pollution exposure, which may be unique to Indian urban environments. Methods: Seasonal sampling was conducted in four campaigns (2016-2017) at 150 sites throughout Mysore, a small and rapidly growing city in south India. Nitrogen dioxide (NO2) levels were assessed using passive Palmes’ tubes and Ogawa badges. Results: Annual average NO2 ranged from 0.8 to 31.2ppb (1.5 to 58.7 μg / m3) for the study area, with higher concentrations in the center of the city. In the final Land Use Regression (LUR) model, proximity to major roads, point sources of pollution, and religious complexes, as well as high human activity land uses and population density were positively associated with air pollution, while proximity to minor roads and low human activity land uses were inversely associated with air pollution (R2= 0.535). Cross-validation of the results confirmed the reliability of the model. Kriging improved estimates by accounting for spatial correlation. Conclusions: The combination of passive NO2 sampling and LUR / Kriging modeling techniques allowed for characterization of NO2 patterns in Mysore. While traffic pollution has been indicated in the past as a major contributor to ambient air pollution levels in urbanizing centers of Asia, results indicate that other pollution factors (e.g., point sources), as well as highly localized characteristics of the urban environment (such as proximity to religious buildings), influence air pollution exposure patterns in urban India. Despite a reputation as one of the cleanest cities in India, areas of Mysore consistently experience pollution in excess of WHO health-protective guidelines for NO2.

The impact of freight transport operations on the level of pollution in cities

Abstract Transport operations are one of the sources of contemporary problems of pollution in urban areas. One of many reasons for such a situation is the growing needs for freight transport using different modes of transport, mainly road transport and the insufficient availability and network of roads. The impact on the environment should be one of more important criteria taken into account while selecting the mode of transport. The objective of the paper is to assess the level of pollution generated from gas emissions, depending on the type of the carrier, category and size of load, taking into account urban areas. On the basis of the obtained results, there was determined the potential of the level of pollution in cities as well as it was identified which mode of transport mostly contributes to the arising pollution

How Public Transport Strikes Affect the Health of Our Citizens?

Public transport is seen as a key element to reduce air pollution levels in cities. We want to assess whether public transport strikes are associated with health outcomes (hospitalitzacions and mortality), and if they are mediated by the increase in air pollution.We compiled Barcelona-city data from government records for the period 2005-June 2016. We fitted quasi-Poisson time series regression models for each health outcome with strike occurrence as the explanatory variable. Models were adjusted for day of the week and holiday period. To account for temporal trends, we included a natural spline of time with 5 degrees of freedom per year. Mediation of the effect of strikes on health outcomes by air pollution was evaluated using the Baron and Kenny approach.During the study period, there were 208 days affected by a strike of the metro, train or bus systems. There was a median of 45 deaths per day, with a third of them being from cardiovascular or respiratory causes. In median, there were 74 cardiovascular or respiratory hospitalizations. During strike days there was between a 2.69% and a 45.96% increase in air pollution concentrations.We only detected increases of respiratory mortality during public transport strikes, which increased by 9% (95% CI: 1%, 18%). Stronger associations were found for metro strikes (reaching 66%). In those days, overall mortality and respiratory hospitalizations were also increased by around 16%. Associations between air pollutants and strikes occurrence were found mainly for nitrogen dioxide and black carbon, and especially during metro strikes. However, associations between strikes and health were unaffected by adjusting for air pollution levels, indicating no mediation.Our findings suggest that the increase in air pollution does not explain the increases in health outcomes. One possible explanation could be that days with strikes of the public transport system may magnify respiratory airways susceptibility due to the increase of stress.

Using the COMET Method in the Sustainable City Transport Problem: an Empirical Study of the Electric Powered Cars

This paper investigates the problem of sustainable city transport. The significance of this problem is increasing, considering the inevitable increase of air pollution levels in cities. Currently, cars with diesel engines are not admitted to many city centers, and this trend can be expected to be maintained. Moreover, this restriction will be expanded to all combustion cars in the foreseeable future. Therefore, combustion vehicles will eventually be replaced by electric ones.In this paper, the authors use the Characteristic Objects METhod (COMET) to identify a decision-making model for the selection of the best model of car for sustainable city transport. The COMET method is a new approach that is free of the rank reversal phenomenon. The identified model provides information about the significance level of each of the criteria. The presented approach can easily be expanded by using a greater number of criteria and alternatives, depending on the specification of the considered problem. Moreover, the interval numbers concept is proposed as the basic approach to dealing with input data uncertainty by using the COMET method. The presented technique is an efficient and highly accurate approach to make decisions based on experts’ experience.

Characterization of CDOM from urban waters in Northern-Northeastern China using excitation-emission matrix fluorescence and parallel factor analysis.

Chromophoric dissolved organic matter (CDOM) plays an important role in aquatic systems, but high concentrations of organic materials are considered pollutants. The fluorescent component characteristics of CDOM in urban waters sampled from Northern and Northeastern China were examined by excitation-emission matrix fluorescence and parallel factor analysis (EEM-PARAFAC) to investigate the source and compositional changes of CDOM on both space and pollution levels. One humic-like (C1), one tryptophan-like component (C2), and one tyrosine-like component (C3) were identified by PARAFAC. Mean fluorescence intensities of the three CDOM components varied spatially and by pollution level in cities of Northern and Northeastern China during July-August, 2013 and 2014. Principal components analysis (PCA) was conducted to identify the relative distribution of all water samples. Cluster analysis (CA) was also used to categorize the samples into groups of similar pollution levels within a study area. Strong positive linear relationships were revealed between the CDOM absorption coefficients a(254) (R (2) = 0.89, p < 0.01); a(355) (R (2) = 0.94, p < 0.01); and the fluorescence intensity (F max) for the humic-like C1 component. A positive linear relationship (R (2) = 0.77) was also exhibited between dissolved organic carbon (DOC) and the F max for the humic-like C1 component, but a relatively weak correlation (R (2) = 0.56) was detected between DOC and the F max for the tryptophan-like component (C2). A strong positive correlation was observed between the F max for the tryptophan-like component (C2) and total nitrogen (TN) (R (2) = 0.78), but moderate correlations were observed with ammonium-N (NH4-N) (R (2) = 0.68), and chemical oxygen demand (CODMn) (R (2) = 0.52). Therefore, the fluorescence intensities of CDOM components can be applied to monitor water quality in real time compared to that of traditional approaches. These results demonstrate that EEM-PARAFAC is useful to evaluate the dynamics of CDOM fluorescent components in urban waters from Northern and Northeastern China and this method has potential applications for monitoring urban water quality in different regions with various hydrological conditions and pollution levels.