Sulfur Dioxide Concentrations Research Articles

What are the challenges to producing high quality red wines from interspecific grapes?

In the U.S. Midwest region, interspecific cold hardy grape cultivars have been developed to be resistant to the harsh cold winter, late spring frosts, and hot and humid summer. However, interspecific grape red wines tend to have higher acidity and lower tannins content than Vitis vinifera wines. This leads to unbalanced wines and an increase of the risk of oxidation and therefore impact the overall quality over time. The content and type of phenolic compounds differ in interspecific grapes and wines, depending on the cultivars, the viticultural practices, the environmental conditions and the wine making process. Because the chemical properties of red wines produced from interspecific grapes compared to Vitis vinifera is not well known, it is a challenge to determine the best wine making practices to produce a high quality wine that remains stable over time. This study focuses on evaluating phenolic compounds, oxidation-related compounds, and sulfur dioxide content in Marquette and Frontenac wines aged in bottles for up to 9 years. The goal is to help improve quality of red wines made from interspecific cold-hardy grape cultivars to increase consumer acceptance and develop optimal wine making practices.

Air quality forecasting using convolutional neural networks

Air pollution is now one of the biggest environmental risks, which causes more than 6 million premature deaths each year from heart diseases, stroke, diabetes, respiratory disease, and so on. Protecting humans from the damage which is caused by air pollution is one of the major issues for the global community. The prediction of air pollution can be done by machine learning (ML) algorithms. ML combines statistics and computer science to maximize the prediction power. ML can be also used to predict the air quality index (AQI). The aim of this research is to develop a convolutional neural network (CNN) model to predict air quality from the unseen data set, which includes concentration of nitrogen dioxide (NO2), carbon monoxide (CO), and sulfur dioxide (SO2). The proposed system will be implemented in two steps; the first step will focus on data analysis and pre-processing, including filtering, feature extraction, constructing convolutional neural network layers, and optimizing the parameters of each layer, while the second step is used to evaluate its model accuracy. The output is predicted as AQI for the developed CNN model. The developed CNN model achieves a root-mean-square error of 13.4150 and a high accuracy of 86.585%. The overall model is implemented using MATLAB software.

Air quality forecasting using convolutional neural networks

Air pollution is now one of the biggest environmental risks, which causes more than 6 million premature deaths each year from heart diseases, stroke, diabetes, respiratory disease, and so on. Protecting humans from the damage which is caused by air pollution is one of the major issues for the global community. The prediction of air pollution can be done by machine learning (ML) algorithms. ML combines statistics and computer science to maximize the prediction power. ML can be also used to predict the air quality index (AQI). The aim of this research is to develop a convolutional neural network (CNN) model to predict air quality from the unseen data set, which includes concentration of nitrogen dioxide (NO2), carbon monoxide (CO), and sulfur dioxide (SO2). The proposed system will be implemented in two steps; the first step will focus on data analysis and pre-processing, including filtering, feature extraction, constructing convolutional neural network layers, and optimizing the parameters of each layer, while the second step is used to evaluate its model accuracy. The output is predicted as AQI for the developed CNN model. The developed CNN model achieves a root-mean-square error of 13.4150 and a high accuracy of 86.585%. The overall model is implemented using MATLAB software.

INVESTIGATION OF TRANSIENT RESISTANCE AND ELECTRICAL EROSION OF SERIAL CONTACT PARTS RELAY PKL - 2204

In this study, the processes of the occurrence of an electric arc and its duration on the contact details of the PKL-2204 series relay are considered in detail. The patterns of changes in electrical erosion, which is a function of current strength and the number of switchings, were also studied. A detailed analysis of the process of opening the contact details was carried out based on the voltage oscillogram. Studies have shown that this process can be considered in three main stages. The first stage is marked by the separation of the contact parts, and at the very moment of the break of the working surfaces, there is a sharp jump in voltage from 45 mV to 13.5 V, accompanied by the formation of an electric arc. The second stage, lasting about 3.5 ms, is characterized by the weakening of the current to zero, and the arc is completely extinguished on the oscillogram. The third stage is marked by the appearance of a voltage peak on the oscillogram, which occurs when the arc is extinguished and is caused by the inductance L=240 mH. This analysis helps to better understand the process of contact opening and may have practical applications in the field of electrical engineering and electronics. Analysis of the results of our research indicates the presence of metals that have high resistance to erosion, regardless of their role as an anode or cathode. Among these metals, we can note nickel, copper, niobium, molybdenum, silver, and others, which show resistance to erosion even when the polarity changes, that is, they are erosion-resistant both at the anode and at the cathode. In particular, among such metals it is worth noting silver, molybdenum and niobium, which demonstrate extraordinary resistance to erosion in various conditions. These results may have important implications for the development of erosion-resistant materials for electronic devices and other applications. On the basis of the conducted research, it was found that the electroerosion resistance of contact parts made of СрН-10 material depends on several factors, including the current strength, the duration of arc burning, the number of commutations, and the physical and mechanical properties of the contact material. Research into the microstructure of the material during the current switching process revealed thermal, mechanical, and fatigue failure. During this process, the low-melting component of the cathode material melts and intensively evaporates, which leads to the formation of a dispersed and bumpy surface. The working surface of the anode is covered with finely dispersed silver particles, which are transferred from the cathode through the gaseous or liquid phase. The analysis of the spectra of the surface layers indicates a significant occurrence of nickel on the working surface of the cathode, which confirms the priority of evaporation of silver from the surface of the contact part during current switching. The study of the effect of chemically active reagents on transient resistance showed that in humid air with a high content of ammonia, hydrogen sulfide, sulfur dioxide, and carbon dioxide, the transient resistance of contact parts increases by 5-7 times.

Changes of Air Pollutants in Urban Cities during the COVID-19 Lockdown-Sri Lanka

In response to the COVID-19 pandemic in early 2020, Sri Lanka underwent a nationwide lockdown that limited motor vehicle movement, industrial operations, and human activities. This study analyzes the impact of COVID-19 lockdown on carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter (PM10, PM2.5) concentrations in two urban cities (Colombo and Kandy) in Sri Lanka, by comparison of data from the lockdown period (March to May 2020) with its analogous period of 2019 and 2021. The results showed that the percentage change of daytime PM10, PM2.5, CO, and NO2 concentration during the lockdown in Colombo (Kandy) is –42.3% (–39.5%), –46% (–54.2%), –14.7% (–8.8%) and –82.2% (–80.9%), respectively. In both cities, the response of NO2 to the lockdown was the most sensitive. In contrast, daytime O3 concentration in Colombo (Kandy) has increased by 6.7% (27.2%), suggesting that the increase in O3 concentration was mainly due to a reduction in NOx emissions leading to lower O3 titration by NO. In addition, daytime SO2 concentration in Colombo has increased by 22.9%, while daytime SO2 concentration in Kandy has decreased by –40%. During the lockdown period, human activities were significantly reduced, causing significant reductions in industrial operations and transportation activities, further reducing emissions and improving air quality in two cities. The results of this study offer potential for local authorities to better understand the emission sources, assess the effectiveness of current air pollution control strategies, and form a basis for formulating better environmental policies to improve air quality and human health.

IMPACT OF SULPHUR DIOXIDE EXPOSURE ON PHOTOSYNTHETIC PIGMENTS IN VIGNA MUNGO

The present studies carried out on Vigna mungo regarding impacts of SO2 exposure on photosynthetic pigments clearly revealed that sulphur dioxide has deleterious effects on different photosynthetic pigments. These effects had become more significant when the plants were exposed to higher doses of sulphur dioxide. During the present investigation four concentrations, i.e. 0.1, 0.3, 0.5 and 0.7 ppm of sulphur dioxide were taken in consideration and their impact on biochemical contents i.e chlorophyll ‘a’, chlorophyll ‘b’, total chlorophyll and carotenoids in Vigna mungo was studied. The observations obtained clearly revealed that a significant reduction was observed in photosynthetic pigments of Vigna mungo. This impact was of great extent in such plants which were exposed to 0.7 ppm of sulphur dioxide as compared to those exposed to lower concentration of sulphur dioxide. It was also observed that the impact was not only dose dependent but also age dependent.

Балқаш қаласының атмосфералық ауасының ауыр металдармен ластануы

The article discussed the situation of atmospheric air pollution in the city of Balkhash with chemical elements. The size of suspended particles according to the results of stationary observation of the RM-10 sample was 0.8 MPC with a concentration of dust particles (dust/aerosol, not differentiated by composition) of 99.6%. The norm is 0.05 mg/m3 , the maximum single concentration of solid particles in the atmospheric air of the city of Balkhash was 0.2 MPC. The size of RM is 2.5 concentration of suspended particles. According to the norms, the average daily level of RM 2.5 should not exceed 0.25 mg/m3. Based on our data, the average daily level of RM 2.5 was the maximum RM-2.5 - 0.2 MPC of a single concentration of solid particles with a multiplicity exceeding 0.7 mg/m3 . The average concentration of ozone in the whole city is 1.5 MPC s.s. sulfur dioxide -5.4 MPC m.r.k.; carbon monoxide-2.2 MPC m.r.k; nitrogen dioxide -2.0 MPC m.r.k.; hydrogen sulfide - 20.1 mpc.R.K. It was found that at the maximum permissible single concentration of 0.5 mg/m3, the actual concentration of sulfur dioxide during adverse meteorological conditions exceeded the corresponding MPC by 23.7 times.

Prediction of SO2 Concentration Based on AR-LSTM Neural Network.

Sulphur dioxide is one of the most common air pollutants, forming acid rain and other harmful substances in the atmosphere, which can further damage our ecosystem and cause respiratory diseases in humans. Therefore, it is essential to monitor the concentration of sulphur dioxide produced in industrial processes in real-time to predict the concentration of sulphur dioxide emissions in the next few hours or days and to control them in advance. To address this problem, we propose an AR-LSTM analytical forecasting model based on ARIMA and LSTM. Based on the sensor's time series data set, we preprocess the data set and then carry out the modeling and analysis work. We analyze and predict the proposed analysis and prediction model in two data sets and conduct comparative experiments with other comparison models based on the three evaluation indicators of R2, RMSE and MAE. The results demonstrated the effectiveness of the AR-LSTM analytical prediction model; Finally, a forecasting exercise was carried out for emissions in the coming weeks using our proposed AR-LSTM analytical forecasting model.

Using Multispectral Imaging to Reveal the Relationship between UV Absorbance and Sulphur Dioxide Concentration

The sulphur dioxide (SO2) concentration can be monitored via its absorbance in the ultraviolet (UV) region. To address the absence of a systematic study on the UV absorbance of varying SO2 concentrations, a multispectral imaging method was implemented in the present study. SO2 concentrations and various environmental conditions were controlled by a purpose-built environmental control system with a light path of 4.2 m. Five narrow-band-pass filters in front of a UV camera were used to implement multispectral imaging. Regression models of the relationship between UV absorbance and SO2 concentration at each wavelength are presented. Their residuals were kept relatively small by adopting Jenks natural breaks analysis, with a maximum standard deviation of 0.086. Temperature and SO2 concentrations were significantly associated with UV absorbance. Furthermore, smoothed look-up tables were developed to explicitly elucidate the correlation between UV absorbance and SO2. These have been represented as heat maps, showcasing an example of library construction using a combination of abundant research data.

Анализ стандартов Евразийского экономического союза на кондитерские изделия

A barrier-free trade in the Eurasian Economic Union (EAEU) market is impossible without a unified approach to standardization. The research objective was to analyze and develop proposals that would make it possible to unify the standards of the Eurasian Economic Commission (EAEC) on the content of sulfur dioxide and sulfites in confectionery products.
 The study featured technical regulations and standards for confectionery products, methods for determining sulfur dioxide, and EAEU resources on the results of control oversight activities. The methods included comparison, analogy, analysis, synthesis, peer review, integrated standardization, and system analysis.
 The analysis involved the official websites of the authorized bodies of the EAEU states on control and supervisory measures for compliance with technical regulations. It revealed the main reasons behind the limited confectionery turnover associated with excessive sulfur dioxide and sulfites. The standards showed discrepancies with Technical Regulations of Customs Union TR CU 022/2011 and TR CU 029/2012. The content standards for sulfur dioxide and sulfites in finished products were different. The analysis detected no unified approach to indicators, measurement units, and detection methods. The authors also assessed the advantages and disadvantages of the existing domestic State Standards for methods of sulfur dioxide and sulfite detection in confectionery products. The state standards have to be adapted to the international standards and EU Directives, in particular, by certifying the Monier-Williams method.
 The results can help to unify national and international regulations in order to remove technical barriers in the EAEU market and increase the export volume. They also can help confectionery producers to improve the quality and safety of confectionery products.

Spatio-Temporal analysis of sensor based air pollutants in Raipur city, India


 
 
 
 Introduction: Particulate matter pollutants and gaseous pollutants are some of the most hazardous pollutants released into the atmosphere. In order to determine how these pollutants impact the living being at breathing height, the current study measures these pollutants using wireless sensors at a height of 1 m above the ground.
 Materials and methods: In this study, horizontal monitoring of the air pollutants using wireless sensors at twenty-four locations covering four zones including industrial, residential, public-place and transportation of the Raipur city has been evaluated. Spatial variation has been obtained using Inverse Distance Weighting (IDW) method in Geographic Information System (GIS).
 Results: The obtained results indicate that as compared to the monsoon and post-monsoon seasons, the concentrations of air pollutants are highest in the winter. It was observed that Particulate Matters (PM2.5 and PM10) are the main causes of declining air quality, but Nitrogen dioxide (NO2) and Sulfur dioxide (SO2) concentrations were below Central Pollution Control Board (CPCB) guidelines except for NO2 in winter. The Carbon monoxide (CO) concentration has been above the standard limit in all three seasons. The main finding of this study is to evaluate how air contaminants vary in space and time near the ground surface which is not possible through the static monitoring instruments in the study area.
 Conclusion: The primary benefit of the obtained results is their great resolution in a compact area, effectively addressing the air quality issue. The findings suggest that seasonality has a substantial impact on the amount of pollutants in the city. According to the temporal distributions of the air pollutants, monsoon had the best air quality, followed by post-monsoon while the winter season has the highest concentration of pollution.
 
 
 

610 EMERGING TRIGGERS OF ARRHYTHMIC EVENTS IN REMOTE MONITORED PATIENTS

Abstract Background and aims Worldwide, air pollution is the fourth leading cause of death. Both brief and long-term exposures to air pollution have been associated with marked increases in cardiovascular-related morbidity and mortality. Previous studies have focused on the short-term influence of particulate pollutants on ventricular arrhythmia (VA) development, primarily expressed as 24-hour Holter ECG monitoring arrhythmic burden or as presentation as life-threatening ventricular arrhythmias. The aim of our study was to investigate the association between air pollutant exposure and VA burden in remotely-monitored patients. Methods We enrolled retrospectively 86 patients carriers of implantable cardioverter-defibrillators (ICD), loop recorders (ILR) or pacemaker devices with remote monitoring via CarelinkTM Medtronic or Merlin.netTM PCN Abbott softwares. Intracavitary and ILR tracings were reviewed by EP personnel at our centre to define VA burden and the number of appropriate shocks and ATPs occurred in 2021. Demographic and clinical characteristics (e.g. cardiovascular history, ejection fraction, smoking, antiarrhythmic drugs (AADs)) were collected through telephone interviews. Each patient's residential and working address were used to obtain information on pollutant exposure in the years 2017-2021 in terms of annual mean concentrations of PM10, PM2.5, ozone, sulfur dioxide, carbon dioxide, carbon monoxide and benzene, as determined by European Environmental Agency air quality reports. The primary endpoint was a composite of ventricular fibrillation, sustained and nonsustained ventricular tachycardia, appropriate ATP or shocks in patients with various levels of air pollutants exposure. Results Of 86 patients (58 male, mean age 63.2±18.7 years) enrolled in this study, 44 (51.6%) had received an ICD, 32 of whom (37.2%) with a primary prevention indication. 31 patients (36.1%) had been receiving at least one AAD. History of coronary artery disease (CAD) was present in one third of the study population and baseline mean EF was 49.8±13.8%. VA events occurred in 17 patients (19.8%), all with a significantly lower baseline EF (40.3±12.2% vs 51.5±13.5% p=0.005). Average mean values of benzene concentration in the previous 4 years were significantly higher in patients suffering from a VA event (1.64±0.82 μg/m3 vs 1.12±0.48 μg/m3, p=0.001), as were PM2.5 values (11.64±1.98 vs 10.74±1.28 μg/m3, p=0.023). A weak but positive correlation was found between median PM2.5 concentration, benzene and VAs (p=0.023, p=0.001 respectively). A multivariate regression model was built, including long-term exposure to benzene and PM2.5 and baseline EF, and it would explain 29.8% of the variance in VAs, correctly classifying 78.1% of cases. Conclusions This study was the first to evaluate the relationship between long-term exposure to a wide array of air pollutants and VAs in a European population. In our sample, we found a weak but significant correlation between a higher chronic exposure to benzene and recorded VA events. Possible mechanisms may include oxidative stress and a direct, nonspecific membrane action due to benzene lipophilic properties. Hence, we highlighted the possible role of outdoor benzene exposure in ventricular arrhythmogenesis for the first time, a finding that requires validation through subsequent studies aimed at elucidating the role of air pollution as a ubiquitous, potentially modifiable, population-based risk factor.

Air Quality Prediction Using the Fractional Gradient-Based Recurrent Neural Network.

In this study, the air quality index (AQI) of Indian cities of different tiers is predicted by using the vanilla recurrent neural network (RNN). AQI is used to measure the air quality of any region which is calculated on the basis of the concentration of ground-level ozone, particle pollution, carbon monoxide, and sulphur dioxide in air. Thus, the present air quality of an area is dependent on current weather conditions, vehicle traffic in that area, or anything that increases air pollution. Also, the current air quality is dependent on the climate conditions and industrialization in that area. Thus, the AQI is history-dependent. To capture this dependency, the memory property of fractional derivatives is exploited in this algorithm and the fractional gradient descent algorithm involving Caputo's derivative has been used in the backpropagation algorithm for training of the RNN. Due to the availability of a large amount of data and high computation support, deep neural networks are capable of giving state-of-the-art results in the time series prediction. But, in this study, the basic vanilla RNN has been chosen to check the effectiveness of fractional derivatives. The AQI and gases affecting AQI prediction results for different cities show that the proposed algorithm leads to higher accuracy. It has been observed that the results of the vanilla RNN with fractional derivatives are comparable to long short-term memory (LSTM).

Association between Cough and Ambient Polycyclic Aromatic Hydrocarbons in Patients with Chronic Cough: An Observational Study in Two Regions of Japan

Ambient polycyclic aromatic hydrocarbons’ (PAHs) specific components are likely involved in respiratory disease development and exacerbation in children and adults. Airborne PAH exposure’s effects on cough symptoms in children and adults with chronic coughs in Kanazawa and Fukuoka, Japan, were investigated in this longitudinal study. A total of 98 patients with chronic coughs were enrolled and followed up between 1 April and 31 May 2020. The enrolled patients were non-smoking adults and children aged 3–83 years. Cough diaries were used to record and collect daily cough symptoms. High-performance liquid chromatography coupled with a fluorescence detector was used to determine the particulate PAH content in daily total suspended particles collected on quartz fiber filters. Ambient concentrations of fine particulate matter, nitrogen dioxide, and sulfur dioxide were obtained from local monitoring sites. Generalized estimated equations were used to estimate the association between daily PAHs and cough symptoms. Among nine PAHs measured, benz[a]anthracene (BaA) was significantly associated with cough symptoms for both lag4 and lag5 PAH exposure. These findings suggest that airborne specific PAHs, especially BaA, affect cough symptoms in children and adults with chronic cough. Further studies are needed to develop effective measures to prevent respiratory diseases against specific PAHs.

Longitudinal Study on the Association between Ambient Polycyclic Aromatic Hydrocarbons and Nasal Symptoms in Adult Japanese

The relationship between exposure to polycyclic aromatic hydrocarbons and nasal symptoms currently remains unclear. Therefore, we herein examine this relationship in 51 adults living in Ishikawa prefecture, Japan, and conducted a 2 month follow-up survey on these participants. All participants were asked to record daily nasal symptoms in an allergy diary during the study period between 1 April to 31 May 2020. We collected air pollutant samples during the study period and determined the concentrations of PAHs and total suspended particulates by high-performance liquid chromatography. Sulfur dioxide and nitrogen dioxide concentrations were obtained through the Atmospheric Environmental Regional Observation System. We used generalized estimating equations to analyze the association between pollutant and nasal symptoms. After adjustment for confounding factors, the B values of fluoranthene, pyrene, and Benzo[k]fluoranthene were 2.389 (p = 0.026), 3.744 (p = 0.022) and 9.604 (p = 0.041), respectively, with a one-day lag. In contrast, the B value of indeno[1,2,3-cd]pyrene was −6.664 (p = 0.013) with no lag. Collectively, these results suggest ambient PAHs such as Flt, Pyr, and BkF were associated with nasal symptoms in adults. Further studies are needed to elucidate the mechanisms contributing to the relationships between specific PAHs and nasal symptoms.

Analysis of the pollution emission system of large-scale combustion of biomass briquette fuel in China

In order to realize the sustainable development strategy and reduce the air pollution caused by biomass boiler emissions, the current study added a Selective Catalyst Reduction (SCR) external denitration system and a wet electrostatic precipitator to the original “three-stage” dust removal system for biomass briquetting fuel boiler emissions and completed the upgrading of the “five-stage” dust removal system. Taking the soot concentration, Sulfur dioxide (SO2) concentration, and Nitrogen oxides (NOX) concentration in the flue gas as the evaluation indicators, real-time online monitoring of the operating conditions of the system is carried out. The results show that the average concentration of smoke and dust in the flue gas discharged from the “five-stage” dust removal system is 3.47 mg/m3, with 2.49 mg/m3 for the average concentration of SO2, and 25.48 mg/m3 for the average concentration of NOX. The removal rates of soot, SO2, and NOX have increased by 5.8%, 4%, and 48.5%, respectively, which are much lower than the emission standards of biomass boiler flue gas pollutants. The innovation of this system is unprecedented for the large-scale combustion of biomass briquettes in China, which greatly reduces the emission of harmful gases. This upgrading will not only make a certain contribution to environmental protection but also provide a theoretical basis to the biomass briquette fuel industry.

Analisis Tingkat Pencemaran SO2 pada Udara Ambien Akibat Aktivitas Kendaraan Bermotor di Jalan A.H Nasution Kota Kendari

The air condition on our earth is getting worse day by day due to air pollution. Air pollution changes the composition (composition) of the atmosphere, where the amount and concentration of one or more pollutants endangers the health of living things, damages property, and reduces air comfort. The dense use of motorized vehicle activities in Kendari City is one of the factors that affect ambient air quality. This is what can be used as a reference in conducting this research using a field survey method for the number of vehicles and ambient air dampel testing for air quality in Kendari City with Sulfur Dioxide parameters. The results showed that the daily traffic density at the monitoring point on Jalan A.H Nasution, Kendari City, for motor vehicles was 8,046 units/day, cars were 3,237 units/day, and trucks were 213 units/day. Based on the results of laboratory tests, the concentration of SO2 at the measurement point on Jalan A.H Nasution, Kendari City, was 38.5 g/m3 in the morning, 61.7 g/m3 in the afternoon, and 53.5 g/m3 in the afternoon. Based on government regulation Number 22 of 2021 concerning the implementation and management of the environment, the sulfur dioxide concentration on the A.H Nasuton road, Kendari City, between morning, afternoon and evening is still below the quality standard threshold.

Experience of Substantiation and Results of Monitoring of Priority Air Pollutants in Norilsk within the Federal Clean Air Project

Introduction: Long-term multicomponent ambient air pollution in residential areas is one of the serious threats to human health. The Federal Clean Air Project implemented within the National Ecology Project aims at fundamental improvement of the quality of life of the Russian population through reduction in emissions of priority (hazardous) pollutants posing the highest health risks. Objective: To substantiate the choice and to analyze the results of monitoring of priority air pollutants in the city of Norilsk included in the Project. Materials and methods: Priority chemicals were determined based on the results of a health risk assessment. The exposure was assessed on the basis of dispersion calculations using a consolidated database of stationary and mobile emission sources (1,970 sources from 110 enterprises and 175 sections of the urban road network) and the “Ecologist – City” 4.60.1 software with the “Average” calculation block, realizing atmospheric dispersion modeling techniques approved in the Russian Federation. The airborne pollutant accounting for at least 95 % of the unacceptable carcinogenic and/or non-carcinogenic risk was considered a priority. The estimates were then verified by the results of measuring ambient concentrations of 20 pollutants within socio-hygienic air quality monitoring in Norilsk for 2020–2021. Results: We established that both short- and long-term exposure to air pollutants posed unacceptable health risks to more than 180 thousand people affected. The list of priority contaminants subject to monitoring and priority regulation comprised ten chemicals, including nitrogen oxide and dioxide, sulfur dioxide, particulate matter, sulfuric acid, carbon oxide, copper oxide, nickel compounds, lead and its compounds, and benzene, of which seven were confirmed as such by the monitoring data. In fact, the measured concentrations of sulfur dioxide, particulate matter, copper and nickel compounds at a number of sites were significantly higher than those estimated by dispersion modeling. Vapors of sulfuric acid, carbon monoxide and nitrogen oxide were below the limit of detection. Conclusions: The health risk assessment methodology used for selecting priority air pollutants is an adequate and effective tool of environmental management. Verification of the lists of priority chemicals compiled on the basis of dispersion modeling using the merged database on the urban sources of air pollution is expedient and necessitates improvement of techniques and mechanisms for stocktaking of emission sources. A significant discrepancy between the estimated and measured data on pollution levels should be discussed by all interested parties and result in changes to the consolidated databases and an increase in the accuracy of subsequent hygienic assessments, including that of public health risks.

Assessment the impact of different fuels used in cement industry on pollutant emissions and ambient air quality: a case study in Egypt

This study aims to assess the impact of using different fuels in Egyptian Titan Alexandria Portland Cement Company on emissions and concentrations of pollutants (Total suspended particles (TSP), nitrogen dioxide (NO2‎), and sulfur dioxide (SO2)) and their influence on ambient air quality during the period 2014–2020 using AERMOD dispersion model. The results showed that changing the fuel from natural gas in 2014 to coal mixed with alternative fuels (Tire-Derived Fuel (TDF), Dried Sewage Sludge (DSS), and Refuse Derived Fuels (RDF)) in 2015–2020 caused fluctuating variations in pollutant emissions and concentrations. The highest and lowest maximum concentrations of TSP occurred in 2017 and 2014 respectively, where the TSP is positively correlated with coal, RDF, and DSS and negatively correlated with natural gas, diesel, and TDF. Also, the lowest and highest maximum NO2 concentrations were detected in 2020 and 2016 followed by 2017 respectively, where NO2 is positively correlated with DSS and negatively correlated with TDF and varies with diesel, coal, and RDF. Moreover, the maximum concentrations of SO2 were the lowest in 2018 and highest in 2016 followed by 2017 because of its considerable positive correlation with natural gas and DSS and negative correlation with RDF, TDF, and coal. Generally, it was found that increasing the percentage of TDF and RDF with decreasing the percentage of DSS, diesel, and coal will reduce pollutant emissions and concentrations and enhance ambient air quality.

Sea Port SO2 Atmospheric Emissions Influence on Air Quality and Exposure at Veracruz, Mexico

In this work, we identify the current atmospheric sulfur dioxide emissions of the Veracruz port, an important Mexican seaport experiencing rapid growth, and its influence on the surrounding areas. Sulfur dioxide emissions based on port activity, as well as meteorology and air quality simulations, are used to assess the impact. It was found that using marine fuel with low sulfur content reduces emissions by 88%. Atmospheric emission estimates based on the bottom-up methodology range from 3 to 7 Mg/year and can negatively impact air quality up to 3 km downwind. After evaluating different characteristics of vessels in CALPUFF, it was found that maximum sulfur dioxide concentrations ranging between 50 and 88 µg/m3 for a 24-h average occurred 500 m from the port. During 2019, five days had unsatisfactory air quality. The combination of a shallow planetary boundary layer, low wind speed, and large atmospheric emissions significantly degraded local air quality.